Arvato Project Workbook.html

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<title>Arvato Project Workbook</title>

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  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
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<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
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.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
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.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
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<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

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<h1 id="Capstone-Project:-Create-a-Customer-Segmentation-Report-for-Arvato-Financial-Services">Capstone Project: Create a Customer Segmentation Report for Arvato Financial Services<a class="anchor-link" href="#Capstone-Project:-Create-a-Customer-Segmentation-Report-for-Arvato-Financial-Services">&#182;</a></h1><p>In this project, you will analyze demographics data for customers of a mail-order sales company in Germany, comparing it against demographics information for the general population. You'll use unsupervised learning techniques to perform customer segmentation, identifying the parts of the population that best describe the core customer base of the company. Then, you'll apply what you've learned on a third dataset with demographics information for targets of a marketing campaign for the company, and use a model to predict which individuals are most likely to convert into becoming customers for the company. The data that you will use has been provided by our partners at Bertelsmann Arvato Analytics, and represents a real-life data science task.</p>
<p>If you completed the first term of this program, you will be familiar with the first part of this project, from the unsupervised learning project. The versions of those two datasets used in this project will include many more features and has not been pre-cleaned. You are also free to choose whatever approach you'd like to analyzing the data rather than follow pre-determined steps. In your work on this project, make sure that you carefully document your steps and decisions, since your main deliverable for this project will be a blog post reporting your findings.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># import libraries here</span>
<span class="o">!</span>pip install lightgbm
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>

<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">StandardScaler</span>
<span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="k">import</span> <span class="n">PCA</span>
<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">Imputer</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">stats</span>
<span class="kn">from</span> <span class="nn">sklearn.cluster</span> <span class="k">import</span> <span class="n">KMeans</span>

<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">roc_auc_score</span>
<span class="kn">import</span> <span class="nn">lightgbm</span> <span class="k">as</span> <span class="nn">lgb</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">GridSearchCV</span>

<span class="c1"># producing visualizations in notebook</span>
<span class="o">%</span><span class="k">matplotlib</span> inline
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<pre>Collecting lightgbm
  Downloading https://files.pythonhosted.org/packages/0b/9d/ddcb2f43aca194987f1a99e27edf41cf9bc39ea750c3371c2a62698c509a/lightgbm-2.3.1-py2.py3-none-manylinux1_x86_64.whl (1.2MB)
    100% |████████████████████████████████| 1.2MB 9.8MB/s eta 0:00:01
Requirement already satisfied: numpy in /opt/conda/lib/python3.6/site-packages (from lightgbm) (1.12.1)
Requirement already satisfied: scikit-learn in /opt/conda/lib/python3.6/site-packages (from lightgbm) (0.19.1)
Requirement already satisfied: scipy in /opt/conda/lib/python3.6/site-packages (from lightgbm) (1.2.1)
Installing collected packages: lightgbm
Successfully installed lightgbm-2.3.1
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<h2 id="Part-0:-Get-to-Know-the-Data">Part 0: Get to Know the Data<a class="anchor-link" href="#Part-0:-Get-to-Know-the-Data">&#182;</a></h2><p>There are four data files associated with this project:</p>
<ul>
<li><code>Udacity_AZDIAS_052018.csv</code>: Demographics data for the general population of Germany; 891 211 persons (rows) x 366 features (columns).</li>
<li><code>Udacity_CUSTOMERS_052018.csv</code>: Demographics data for customers of a mail-order company; 191 652 persons (rows) x 369 features (columns).</li>
<li><code>Udacity_MAILOUT_052018_TRAIN.csv</code>: Demographics data for individuals who were targets of a marketing campaign; 42 982 persons (rows) x 367 (columns).</li>
<li><code>Udacity_MAILOUT_052018_TEST.csv</code>: Demographics data for individuals who were targets of a marketing campaign; 42 833 persons (rows) x 366 (columns).</li>
</ul>
<p>Each row of the demographics files represents a single person, but also includes information outside of individuals, including information about their household, building, and neighborhood. Use the information from the first two files to figure out how customers ("CUSTOMERS") are similar to or differ from the general population at large ("AZDIAS"), then use your analysis to make predictions on the other two files ("MAILOUT"), predicting which recipients are most likely to become a customer for the mail-order company.</p>
<p>The "CUSTOMERS" file contains three extra columns ('CUSTOMER_GROUP', 'ONLINE_PURCHASE', and 'PRODUCT_GROUP'), which provide broad information about the customers depicted in the file. The original "MAILOUT" file included one additional column, "RESPONSE", which indicated whether or not each recipient became a customer of the company. For the "TRAIN" subset, this column has been retained, but in the "TEST" subset it has been removed; it is against that withheld column that your final predictions will be assessed in the Kaggle competition.</p>
<p>Otherwise, all of the remaining columns are the same between the three data files. For more information about the columns depicted in the files, you can refer to two Excel spreadsheets provided in the workspace. <a href="./DIAS Information Levels - Attributes 2017.xlsx">One of them</a> is a top-level list of attributes and descriptions, organized by informational category. <a href="./DIAS Attributes - Values 2017.xlsx">The other</a> is a detailed mapping of data values for each feature in alphabetical order.</p>
<p>In the below cell, we've provided some initial code to load in the first two datasets. Note for all of the <code>.csv</code> data files in this project that they're semicolon (<code>;</code>) delimited, so an additional argument in the <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html"><code>read_csv()</code></a> call has been included to read in the data properly. Also, considering the size of the datasets, it may take some time for them to load completely.</p>
<p>You'll notice when the data is loaded in that a warning message will immediately pop up. Before you really start digging into the modeling and analysis, you're going to need to perform some cleaning. Take some time to browse the structure of the data and look over the informational spreadsheets to understand the data values. Make some decisions on which features to keep, which features to drop, and if any revisions need to be made on data formats. It'll be a good idea to create a function with pre-processing steps, since you'll need to clean all of the datasets before you work with them.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># load in the data</span>
<span class="n">azdias</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/Term2/capstone/arvato_data/Udacity_AZDIAS_052018.csv&#39;</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;;&#39;</span><span class="p">)</span>
<span class="n">customers</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/Term2/capstone/arvato_data/Udacity_CUSTOMERS_052018.csv&#39;</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;;&#39;</span><span class="p">)</span>
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<pre>/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2785: DtypeWarning: Columns (18,19) have mixed types. Specify dtype option on import or set low_memory=False.
  interactivity=interactivity, compiler=compiler, result=result)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias_copy</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">customers_copy</span> <span class="o">=</span> <span class="n">customers</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
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<h2 id="Analyzing-the-raw-customer-file">Analyzing the raw customer file<a class="anchor-link" href="#Analyzing-the-raw-customer-file">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">customers</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
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        vertical-align: top;
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>LNR</th>
      <th>AGER_TYP</th>
      <th>AKT_DAT_KL</th>
      <th>ALTER_HH</th>
      <th>ALTER_KIND1</th>
      <th>ALTER_KIND2</th>
      <th>ALTER_KIND3</th>
      <th>ALTER_KIND4</th>
      <th>ALTERSKATEGORIE_FEIN</th>
      <th>ANZ_HAUSHALTE_AKTIV</th>
      <th>...</th>
      <th>VK_ZG11</th>
      <th>W_KEIT_KIND_HH</th>
      <th>WOHNDAUER_2008</th>
      <th>WOHNLAGE</th>
      <th>ZABEOTYP</th>
      <th>PRODUCT_GROUP</th>
      <th>CUSTOMER_GROUP</th>
      <th>ONLINE_PURCHASE</th>
      <th>ANREDE_KZ</th>
      <th>ALTERSKATEGORIE_GROB</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>9626</td>
      <td>2</td>
      <td>1.0</td>
      <td>10.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>10.0</td>
      <td>1.0</td>
      <td>...</td>
      <td>2.0</td>
      <td>6.0</td>
      <td>9.0</td>
      <td>7.0</td>
      <td>3</td>
      <td>COSMETIC_AND_FOOD</td>
      <td>MULTI_BUYER</td>
      <td>0</td>
      <td>1</td>
      <td>4</td>
    </tr>
    <tr>
      <th>1</th>
      <td>9628</td>
      <td>-1</td>
      <td>9.0</td>
      <td>11.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>...</td>
      <td>3.0</td>
      <td>0.0</td>
      <td>9.0</td>
      <td>NaN</td>
      <td>3</td>
      <td>FOOD</td>
      <td>SINGLE_BUYER</td>
      <td>0</td>
      <td>1</td>
      <td>4</td>
    </tr>
    <tr>
      <th>2</th>
      <td>143872</td>
      <td>-1</td>
      <td>1.0</td>
      <td>6.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>...</td>
      <td>11.0</td>
      <td>6.0</td>
      <td>9.0</td>
      <td>2.0</td>
      <td>3</td>
      <td>COSMETIC_AND_FOOD</td>
      <td>MULTI_BUYER</td>
      <td>0</td>
      <td>2</td>
      <td>4</td>
    </tr>
    <tr>
      <th>3</th>
      <td>143873</td>
      <td>1</td>
      <td>1.0</td>
      <td>8.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>8.0</td>
      <td>0.0</td>
      <td>...</td>
      <td>2.0</td>
      <td>NaN</td>
      <td>9.0</td>
      <td>7.0</td>
      <td>1</td>
      <td>COSMETIC</td>
      <td>MULTI_BUYER</td>
      <td>0</td>
      <td>1</td>
      <td>4</td>
    </tr>
    <tr>
      <th>4</th>
      <td>143874</td>
      <td>-1</td>
      <td>1.0</td>
      <td>20.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>14.0</td>
      <td>7.0</td>
      <td>...</td>
      <td>4.0</td>
      <td>2.0</td>
      <td>9.0</td>
      <td>3.0</td>
      <td>1</td>
      <td>FOOD</td>
      <td>MULTI_BUYER</td>
      <td>0</td>
      <td>1</td>
      <td>3</td>
    </tr>
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</table>
<p>5 rows × 369 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#cleaning the cutomers file of NaN values</span>
<span class="n">customers</span><span class="o">.</span><span class="n">isna</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="s1">&#39;barh&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f643842e390&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[6]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">customers</span><span class="o">.</span><span class="n">isna</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">&gt;</span><span class="mf">0.9</span>
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    <div class="prompt output_prompt">Out[6]:</div>


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<pre>ALTER_KIND4                   True
ALTER_KIND3                   True
ALTER_KIND2                   True
ALTER_KIND1                   True
KK_KUNDENTYP                 False
EXTSEL992                    False
KBA05_SEG7                   False
KBA05_KW1                    False
KBA05_SEG4                   False
KBA05_SEG5                   False
KBA05_SEG6                   False
KBA05_MAXAH                  False
KBA05_SEG8                   False
KBA05_KW2                    False
KBA05_VORB0                  False
KBA05_KRSZUL                 False
KBA05_VORB1                  False
KBA05_KRSVAN                 False
KBA05_KRSOBER                False
KBA05_SEG9                   False
MOBI_REGIO                   False
KBA05_KW3                    False
KBA05_SEG3                   False
KBA05_KRSHERST3              False
KBA05_MAXBJ                  False
KBA05_MAXHERST               False
KBA05_MAXSEG                 False
KBA05_MAXVORB                False
KBA05_MOD1                   False
KBA05_MOD2                   False
                             ...  
D19_VERSAND_ANZ_24           False
D19_SAMMELARTIKEL            False
D19_SCHUHE                   False
D19_SONSTIGE                 False
D19_TECHNIK                  False
D19_TELKO_ANZ_12             False
D19_TELKO_ANZ_24             False
D19_TELKO_DATUM              False
D19_TELKO_MOBILE             False
D19_TELKO_OFFLINE_DATUM      False
D19_TELKO_ONLINE_DATUM       False
D19_TELKO_REST               False
D19_TIERARTIKEL              False
D19_VERSAND_ANZ_12           False
D19_VERSAND_DATUM            False
FINANZ_MINIMALIST            False
D19_VERSAND_OFFLINE_DATUM    False
D19_VERSAND_ONLINE_DATUM     False
D19_VERSAND_REST             False
D19_VERSI_ANZ_12             False
D19_VERSI_ANZ_24             False
D19_VERSI_DATUM              False
D19_VERSI_OFFLINE_DATUM      False
D19_VERSI_ONLINE_DATUM       False
D19_VERSICHERUNGEN           False
D19_VOLLSORTIMENT            False
D19_WEIN_FEINKOST            False
FINANZ_ANLEGER               False
FINANZ_HAUSBAUER             False
LNR                          False
Length: 369, dtype: bool</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># finding the number of columns with NaN values</span>
<span class="n">column_nan</span> <span class="o">=</span> <span class="n">customers</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">column_nan</span><span class="p">,</span> <span class="n">bins</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="o">+.</span><span class="mi">05</span><span class="p">,</span><span class="o">.</span><span class="mi">05</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Number of features&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Number of columns with NaN values&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Percentage of missing values&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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
"
>
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<div class="prompt input_prompt">In&nbsp;[8]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">customers</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
</pre></div>

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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>LNR</th>
      <th>AGER_TYP</th>
      <th>AKT_DAT_KL</th>
      <th>ALTER_HH</th>
      <th>ALTER_KIND1</th>
      <th>ALTER_KIND2</th>
      <th>ALTER_KIND3</th>
      <th>ALTER_KIND4</th>
      <th>ALTERSKATEGORIE_FEIN</th>
      <th>ANZ_HAUSHALTE_AKTIV</th>
      <th>...</th>
      <th>VK_DHT4A</th>
      <th>VK_DISTANZ</th>
      <th>VK_ZG11</th>
      <th>W_KEIT_KIND_HH</th>
      <th>WOHNDAUER_2008</th>
      <th>WOHNLAGE</th>
      <th>ZABEOTYP</th>
      <th>ONLINE_PURCHASE</th>
      <th>ANREDE_KZ</th>
      <th>ALTERSKATEGORIE_GROB</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>191652.000000</td>
      <td>191652.000000</td>
      <td>145056.000000</td>
      <td>145056.000000</td>
      <td>11766.000000</td>
      <td>5100.000000</td>
      <td>1275.000000</td>
      <td>236.000000</td>
      <td>139810.000000</td>
      <td>141725.000000</td>
      <td>...</td>
      <td>143781.000000</td>
      <td>143781.000000</td>
      <td>143781.000000</td>
      <td>137910.000000</td>
      <td>145056.000000</td>
      <td>141725.000000</td>
      <td>191652.000000</td>
      <td>191652.000000</td>
      <td>191652.000000</td>
      <td>191652.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>95826.500000</td>
      <td>0.344359</td>
      <td>1.747525</td>
      <td>11.352009</td>
      <td>12.337243</td>
      <td>13.672353</td>
      <td>14.647059</td>
      <td>15.377119</td>
      <td>10.331579</td>
      <td>4.965863</td>
      <td>...</td>
      <td>4.374417</td>
      <td>4.564769</td>
      <td>3.168868</td>
      <td>4.152716</td>
      <td>8.646371</td>
      <td>3.723133</td>
      <td>2.576806</td>
      <td>0.090247</td>
      <td>1.376432</td>
      <td>3.060907</td>
    </tr>
    <tr>
      <th>std</th>
      <td>55325.311233</td>
      <td>1.391672</td>
      <td>1.966334</td>
      <td>6.275026</td>
      <td>4.006050</td>
      <td>3.243335</td>
      <td>2.753787</td>
      <td>2.307653</td>
      <td>4.134828</td>
      <td>14.309694</td>
      <td>...</td>
      <td>2.924355</td>
      <td>2.887035</td>
      <td>2.233516</td>
      <td>1.974375</td>
      <td>1.154001</td>
      <td>2.095540</td>
      <td>1.168486</td>
      <td>0.286536</td>
      <td>0.484492</td>
      <td>1.086254</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.000000</td>
      <td>-1.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>5.000000</td>
      <td>8.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>...</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>47913.750000</td>
      <td>-1.000000</td>
      <td>1.000000</td>
      <td>8.000000</td>
      <td>9.000000</td>
      <td>11.000000</td>
      <td>13.000000</td>
      <td>14.000000</td>
      <td>9.000000</td>
      <td>1.000000</td>
      <td>...</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>1.000000</td>
      <td>2.000000</td>
      <td>9.000000</td>
      <td>2.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>3.000000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>95826.500000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>11.000000</td>
      <td>13.000000</td>
      <td>14.000000</td>
      <td>15.000000</td>
      <td>16.000000</td>
      <td>10.000000</td>
      <td>1.000000</td>
      <td>...</td>
      <td>4.000000</td>
      <td>4.000000</td>
      <td>3.000000</td>
      <td>5.000000</td>
      <td>9.000000</td>
      <td>3.000000</td>
      <td>3.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>3.000000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>143739.250000</td>
      <td>2.000000</td>
      <td>1.000000</td>
      <td>16.000000</td>
      <td>16.000000</td>
      <td>16.000000</td>
      <td>17.000000</td>
      <td>17.000000</td>
      <td>13.000000</td>
      <td>4.000000</td>
      <td>...</td>
      <td>7.000000</td>
      <td>7.000000</td>
      <td>4.000000</td>
      <td>6.000000</td>
      <td>9.000000</td>
      <td>5.000000</td>
      <td>3.000000</td>
      <td>0.000000</td>
      <td>2.000000</td>
      <td>4.000000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>191652.000000</td>
      <td>3.000000</td>
      <td>9.000000</td>
      <td>21.000000</td>
      <td>18.000000</td>
      <td>18.000000</td>
      <td>18.000000</td>
      <td>18.000000</td>
      <td>25.000000</td>
      <td>523.000000</td>
      <td>...</td>
      <td>11.000000</td>
      <td>13.000000</td>
      <td>11.000000</td>
      <td>6.000000</td>
      <td>9.000000</td>
      <td>8.000000</td>
      <td>6.000000</td>
      <td>1.000000</td>
      <td>2.000000</td>
      <td>9.000000</td>
    </tr>
  </tbody>
</table>
<p>8 rows × 361 columns</p>
</div>
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<div class="prompt input_prompt">In&nbsp;[9]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">customers</span><span class="o">.</span><span class="n">dtypes</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
</pre></div>

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<pre>float64    267
int64       94
object       8
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#percentage of customers who bought the service</span>
<span class="p">(</span><span class="n">customers</span><span class="p">[</span><span class="n">customers</span><span class="p">[</span><span class="s1">&#39;ONLINE_PURCHASE&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">customers</span><span class="p">[</span><span class="s1">&#39;ONLINE_PURCHASE&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span><span class="o">*</span><span class="mi">100</span>
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<pre>9.02469058501868</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#rows with most NULL that are common</span>
<span class="n">customers</span><span class="p">[(</span><span class="n">customers</span><span class="p">[</span><span class="s1">&#39;KBA05_SEG3&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">())</span> <span class="o">|</span> <span class="p">(</span><span class="n">customers</span><span class="p">[</span><span class="s1">&#39;MOBI_REGIO&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">())]</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<pre>KBA05_SEG3                   55980
KBA05_MAXVORB                55980
KBA05_MOD8                   55980
KBA05_MOD4                   55980
KBA05_MOD3                   55980
KBA05_MOD2                   55980
MOBI_REGIO                   55980
KBA05_MOD1                   55980
KBA05_MAXHERST               55980
KBA05_MOTRAD                 55980
KBA05_MAXBJ                  55980
KBA05_MAXAH                  55980
KBA05_KW3                    55980
KBA05_KW2                    55980
KBA05_KW1                    55980
KBA05_KRSZUL                 55980
KBA05_MOTOR                  55980
KBA05_SEG1                   55980
KBA05_KRSOBER                55980
KBA05_VORB0                  55980
KBA05_ZUL4                   55980
KBA05_ZUL3                   55980
KBA05_ZUL2                   55980
KBA05_ZUL1                   55980
KBA05_VORB2                  55980
KBA05_VORB1                  55980
KBA05_SEG9                   55980
KBA05_SEG10                  55980
KBA05_SEG8                   55980
KBA05_SEG7                   55980
                             ...  
D19_VERSAND_ANZ_24               0
D19_SAMMELARTIKEL                0
D19_SCHUHE                       0
D19_SONSTIGE                     0
D19_TECHNIK                      0
D19_TELKO_ANZ_12                 0
D19_TELKO_ANZ_24                 0
D19_TELKO_DATUM                  0
D19_TELKO_MOBILE                 0
D19_TELKO_OFFLINE_DATUM          0
D19_TELKO_ONLINE_DATUM           0
D19_TELKO_REST                   0
D19_TIERARTIKEL                  0
D19_VERSAND_ANZ_12               0
D19_VERSAND_DATUM                0
FINANZ_MINIMALIST                0
D19_VERSAND_OFFLINE_DATUM        0
D19_VERSAND_ONLINE_DATUM         0
D19_VERSAND_REST                 0
D19_VERSI_ANZ_12                 0
D19_VERSI_ANZ_24                 0
D19_VERSI_DATUM                  0
D19_VERSI_OFFLINE_DATUM          0
D19_VERSI_ONLINE_DATUM           0
D19_VERSICHERUNGEN               0
D19_VOLLSORTIMENT                0
D19_WEIN_FEINKOST                0
FINANZ_ANLEGER                   0
FINANZ_HAUSBAUER                 0
LNR                              0
Length: 369, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#percentage of NULL values in rows</span>
<span class="n">customers</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span><span class="o">/</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span>
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<pre>0       0.015260
1       0.072934
2       0.285675
3       0.749534
4       6.514995
5      11.907372
6      13.731948
7      14.198947
8      14.500893
9      14.584261
10     14.633520
11     14.678851
12     14.702863
13     14.714644
14     14.727772
15     14.786007
16     14.799360
17     14.810917
18     14.818771
19     14.819781
20     14.821240
21     14.822698
22     14.827187
23     14.836724
24     14.925927
25     14.993587
26     15.021527
27     15.051822
28     15.105793
29     15.140913
         ...    
219    15.902004
220    15.902116
221    15.904136
222    15.910532
223    15.933758
224    16.068517
225    16.197554
226    16.252086
227    16.261286
228    16.262857
229    16.262970
233    16.263082
234    16.263306
235    16.264540
236    16.265887
237    16.265999
238    16.266111
242    16.266224
243    16.266448
244    16.268916
245    16.270487
246    16.271385
247    16.272507
248    16.273741
249    16.275312
250    16.275649
252    16.907591
253    21.503982
255    21.504094
259    21.504430
Length: 171, dtype: float64</pre>
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<h2 id="Analyzing-the-azdias-file">Analyzing the azdias file<a class="anchor-link" href="#Analyzing-the-azdias-file">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>LNR</th>
      <th>AGER_TYP</th>
      <th>AKT_DAT_KL</th>
      <th>ALTER_HH</th>
      <th>ALTER_KIND1</th>
      <th>ALTER_KIND2</th>
      <th>ALTER_KIND3</th>
      <th>ALTER_KIND4</th>
      <th>ALTERSKATEGORIE_FEIN</th>
      <th>ANZ_HAUSHALTE_AKTIV</th>
      <th>...</th>
      <th>VHN</th>
      <th>VK_DHT4A</th>
      <th>VK_DISTANZ</th>
      <th>VK_ZG11</th>
      <th>W_KEIT_KIND_HH</th>
      <th>WOHNDAUER_2008</th>
      <th>WOHNLAGE</th>
      <th>ZABEOTYP</th>
      <th>ANREDE_KZ</th>
      <th>ALTERSKATEGORIE_GROB</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>910215</td>
      <td>-1</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>3</td>
      <td>1</td>
      <td>2</td>
    </tr>
    <tr>
      <th>1</th>
      <td>910220</td>
      <td>-1</td>
      <td>9.0</td>
      <td>0.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>21.0</td>
      <td>11.0</td>
      <td>...</td>
      <td>4.0</td>
      <td>8.0</td>
      <td>11.0</td>
      <td>10.0</td>
      <td>3.0</td>
      <td>9.0</td>
      <td>4.0</td>
      <td>5</td>
      <td>2</td>
      <td>1</td>
    </tr>
    <tr>
      <th>2</th>
      <td>910225</td>
      <td>-1</td>
      <td>9.0</td>
      <td>17.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>17.0</td>
      <td>10.0</td>
      <td>...</td>
      <td>2.0</td>
      <td>9.0</td>
      <td>9.0</td>
      <td>6.0</td>
      <td>3.0</td>
      <td>9.0</td>
      <td>2.0</td>
      <td>5</td>
      <td>2</td>
      <td>3</td>
    </tr>
    <tr>
      <th>3</th>
      <td>910226</td>
      <td>2</td>
      <td>1.0</td>
      <td>13.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>13.0</td>
      <td>1.0</td>
      <td>...</td>
      <td>0.0</td>
      <td>7.0</td>
      <td>10.0</td>
      <td>11.0</td>
      <td>NaN</td>
      <td>9.0</td>
      <td>7.0</td>
      <td>3</td>
      <td>2</td>
      <td>4</td>
    </tr>
    <tr>
      <th>4</th>
      <td>910241</td>
      <td>-1</td>
      <td>1.0</td>
      <td>20.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>14.0</td>
      <td>3.0</td>
      <td>...</td>
      <td>2.0</td>
      <td>3.0</td>
      <td>5.0</td>
      <td>4.0</td>
      <td>2.0</td>
      <td>9.0</td>
      <td>3.0</td>
      <td>4</td>
      <td>1</td>
      <td>3</td>
    </tr>
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</table>
<p>5 rows × 366 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#cleaning the azdias file of NaN values</span>
<span class="n">azdias</span><span class="o">.</span><span class="n">isna</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="s1">&#39;barh&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f64383e3d30&gt;</pre>
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
"
>
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</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[15]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt output_prompt">Out[15]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>ALTER_KIND4                    0.998648
ALTER_KIND3                    0.993077
ALTER_KIND2                    0.966900
ALTER_KIND1                    0.909048
EXTSEL992                      0.733996
KK_KUNDENTYP                   0.655967
ALTERSKATEGORIE_FEIN           0.295041
D19_LETZTER_KAUF_BRANCHE       0.288495
D19_LOTTO                      0.288495
D19_VERSI_ONLINE_QUOTE_12      0.288495
D19_BANKEN_ONLINE_QUOTE_12     0.288495
D19_SOZIALES                   0.288495
D19_GESAMT_ONLINE_QUOTE_12     0.288495
D19_KONSUMTYP                  0.288495
D19_TELKO_ONLINE_QUOTE_12      0.288495
D19_VERSAND_ONLINE_QUOTE_12    0.288495
KBA05_MOTOR                    0.149597
KBA05_MOD8                     0.149597
KBA05_MOD4                     0.149597
KBA05_MOD3                     0.149597
KBA05_MOD2                     0.149597
KBA05_SEG1                     0.149597
KBA05_MOD1                     0.149597
KBA05_MAXVORB                  0.149597
KBA05_MAXSEG                   0.149597
KBA05_MAXHERST                 0.149597
KBA05_MAXBJ                    0.149597
KBA05_MAXAH                    0.149597
KBA05_KW3                      0.149597
KBA05_MOTRAD                   0.149597
                                 ...   
D19_RATGEBER                   0.000000
FINANZ_ANLEGER                 0.000000
D19_REISEN                     0.000000
D19_SAMMELARTIKEL              0.000000
D19_SCHUHE                     0.000000
D19_SONSTIGE                   0.000000
D19_TECHNIK                    0.000000
D19_TELKO_ANZ_12               0.000000
D19_TELKO_ANZ_24               0.000000
D19_TELKO_DATUM                0.000000
D19_TELKO_MOBILE               0.000000
D19_TELKO_OFFLINE_DATUM        0.000000
D19_TELKO_ONLINE_DATUM         0.000000
D19_TELKO_REST                 0.000000
D19_TIERARTIKEL                0.000000
D19_VERSAND_ANZ_12             0.000000
D19_VERSAND_ANZ_24             0.000000
D19_VERSAND_DATUM              0.000000
D19_VERSAND_OFFLINE_DATUM      0.000000
D19_VERSAND_ONLINE_DATUM       0.000000
D19_VERSAND_REST               0.000000
D19_VERSI_ANZ_12               0.000000
D19_VERSI_ANZ_24               0.000000
D19_VERSI_DATUM                0.000000
D19_VERSI_OFFLINE_DATUM        0.000000
D19_VERSI_ONLINE_DATUM         0.000000
D19_VERSICHERUNGEN             0.000000
D19_VOLLSORTIMENT              0.000000
D19_WEIN_FEINKOST              0.000000
LNR                            0.000000
Length: 366, dtype: float64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># finding number of columns with NaN values</span>
<span class="n">column_nan_percent</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">column_nan_percent</span><span class="p">,</span> <span class="n">bins</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="o">+.</span><span class="mi">05</span><span class="p">,</span><span class="o">.</span><span class="mi">05</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Number of features&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Number of columns with nan values&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Percentage of missing values&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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
"
>
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<div class="prompt input_prompt">In&nbsp;[17]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>LNR</th>
      <th>AGER_TYP</th>
      <th>AKT_DAT_KL</th>
      <th>ALTER_HH</th>
      <th>ALTER_KIND1</th>
      <th>ALTER_KIND2</th>
      <th>ALTER_KIND3</th>
      <th>ALTER_KIND4</th>
      <th>ALTERSKATEGORIE_FEIN</th>
      <th>ANZ_HAUSHALTE_AKTIV</th>
      <th>...</th>
      <th>VHN</th>
      <th>VK_DHT4A</th>
      <th>VK_DISTANZ</th>
      <th>VK_ZG11</th>
      <th>W_KEIT_KIND_HH</th>
      <th>WOHNDAUER_2008</th>
      <th>WOHNLAGE</th>
      <th>ZABEOTYP</th>
      <th>ANREDE_KZ</th>
      <th>ALTERSKATEGORIE_GROB</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>8.912210e+05</td>
      <td>891221.000000</td>
      <td>817722.000000</td>
      <td>817722.000000</td>
      <td>81058.000000</td>
      <td>29499.000000</td>
      <td>6170.000000</td>
      <td>1205.000000</td>
      <td>628274.000000</td>
      <td>798073.000000</td>
      <td>...</td>
      <td>770025.000000</td>
      <td>815304.000000</td>
      <td>815304.000000</td>
      <td>815304.000000</td>
      <td>783619.000000</td>
      <td>817722.000000</td>
      <td>798073.000000</td>
      <td>891221.000000</td>
      <td>891221.000000</td>
      <td>891221.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>6.372630e+05</td>
      <td>-0.358435</td>
      <td>4.421928</td>
      <td>10.864126</td>
      <td>11.745392</td>
      <td>13.402658</td>
      <td>14.476013</td>
      <td>15.089627</td>
      <td>13.700717</td>
      <td>8.287263</td>
      <td>...</td>
      <td>2.417322</td>
      <td>6.001214</td>
      <td>7.532130</td>
      <td>5.945972</td>
      <td>3.933406</td>
      <td>7.908791</td>
      <td>4.052836</td>
      <td>3.362438</td>
      <td>1.522098</td>
      <td>2.777398</td>
    </tr>
    <tr>
      <th>std</th>
      <td>2.572735e+05</td>
      <td>1.198724</td>
      <td>3.638805</td>
      <td>7.639683</td>
      <td>4.097660</td>
      <td>3.243300</td>
      <td>2.712427</td>
      <td>2.452932</td>
      <td>5.079849</td>
      <td>15.628087</td>
      <td>...</td>
      <td>1.166572</td>
      <td>2.856091</td>
      <td>3.247789</td>
      <td>2.771464</td>
      <td>1.964701</td>
      <td>1.923137</td>
      <td>1.949539</td>
      <td>1.352704</td>
      <td>0.499512</td>
      <td>1.068775</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.916530e+05</td>
      <td>-1.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>4.000000</td>
      <td>7.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>...</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>4.144580e+05</td>
      <td>-1.000000</td>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>8.000000</td>
      <td>11.000000</td>
      <td>13.000000</td>
      <td>14.000000</td>
      <td>11.000000</td>
      <td>1.000000</td>
      <td>...</td>
      <td>2.000000</td>
      <td>3.000000</td>
      <td>5.000000</td>
      <td>4.000000</td>
      <td>2.000000</td>
      <td>8.000000</td>
      <td>3.000000</td>
      <td>3.000000</td>
      <td>1.000000</td>
      <td>2.000000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>6.372630e+05</td>
      <td>-1.000000</td>
      <td>3.000000</td>
      <td>13.000000</td>
      <td>12.000000</td>
      <td>14.000000</td>
      <td>15.000000</td>
      <td>15.000000</td>
      <td>14.000000</td>
      <td>4.000000</td>
      <td>...</td>
      <td>2.000000</td>
      <td>6.000000</td>
      <td>8.000000</td>
      <td>6.000000</td>
      <td>4.000000</td>
      <td>9.000000</td>
      <td>3.000000</td>
      <td>3.000000</td>
      <td>2.000000</td>
      <td>3.000000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>8.600680e+05</td>
      <td>-1.000000</td>
      <td>9.000000</td>
      <td>17.000000</td>
      <td>15.000000</td>
      <td>16.000000</td>
      <td>17.000000</td>
      <td>17.000000</td>
      <td>17.000000</td>
      <td>9.000000</td>
      <td>...</td>
      <td>3.000000</td>
      <td>9.000000</td>
      <td>10.000000</td>
      <td>8.000000</td>
      <td>6.000000</td>
      <td>9.000000</td>
      <td>5.000000</td>
      <td>4.000000</td>
      <td>2.000000</td>
      <td>4.000000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>1.082873e+06</td>
      <td>3.000000</td>
      <td>9.000000</td>
      <td>21.000000</td>
      <td>18.000000</td>
      <td>18.000000</td>
      <td>18.000000</td>
      <td>18.000000</td>
      <td>25.000000</td>
      <td>595.000000</td>
      <td>...</td>
      <td>4.000000</td>
      <td>11.000000</td>
      <td>13.000000</td>
      <td>11.000000</td>
      <td>6.000000</td>
      <td>9.000000</td>
      <td>8.000000</td>
      <td>6.000000</td>
      <td>2.000000</td>
      <td>9.000000</td>
    </tr>
  </tbody>
</table>
<p>8 rows × 360 columns</p>
</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#percentage of rows with missing values and how much</span>
<span class="n">azdias</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span><span class="o">/</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span>
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<pre>0        0.033886
1        0.212293
2        0.996386
3        3.208856
4       16.583541
5       37.966228
6       56.098543
7       61.873654
8       63.318077
9       63.872934
10      64.066040
11      64.290114
12      64.518565
13      64.701685
14      65.184842
15      72.662336
16      82.272186
17      82.839498
18      83.348126
19      83.452589
20      83.515200
21      83.628752
22      83.731420
23      83.807271
24      83.888957
25      83.976702
26      84.033814
27      84.070057
28      84.145234
29      84.207733
          ...    
223     89.636241
224     89.954568
225     90.517279
226     91.010198
227     91.200611
228     91.211944
229     91.212842
231     91.213291
232     91.214637
233     91.217106
234     91.229673
235     91.428838
236     91.721021
237     91.740881
238     91.741779
241     91.741891
242     91.742003
243     91.742116
244     91.743911
245     91.745931
246     91.747838
247     91.748511
248     91.749746
249     91.750643
250     91.750980
252     94.883873
253     99.997980
256     99.998093
258     99.999439
259    100.000000
Length: 204, dtype: float64</pre>
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<h1 id="Data-Pre-Processing">Data Pre-Processing<a class="anchor-link" href="#Data-Pre-Processing">&#182;</a></h1>
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<p>As we can see from above data that there are alot of rows with alot of missing value. Hence, we can set a threshhold to remove the rows with maximum of missing values, such that reatin upto 80% of data.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[</span><span class="n">azdias</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> <span class="o">&lt;=</span> <span class="mi">16</span><span class="p">]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The number of rows retained in the new azdias dataset are: &#39;</span><span class="p">,</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<pre>The number of rows retained in the new azdias dataset are:  733227
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#dropping the columns with more that 65% of values missing(NULL)</span>

<span class="n">drop_columns</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">column_nan_percent</span> <span class="o">&gt;</span> <span class="mf">0.65</span><span class="p">]</span>

<span class="n">azdias</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span> <span class="n">drop_columns</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The number of columns retained in the new azdias dataset are: &#39;</span><span class="p">,</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
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<pre>The number of columns retained in the new azdias dataset are:  360
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#dropping certain columns in the customers dataframe to match it with azdias file</span>

<span class="n">customers</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;CUSTOMER_GROUP&#39;</span><span class="p">,</span> <span class="s1">&#39;ONLINE_PURCHASE&#39;</span><span class="p">,</span> <span class="s1">&#39;PRODUCT_GROUP&#39;</span><span class="p">],</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">customers</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">drop_columns</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#checking if the columns in both the dataframes are equal or not</span>

<span class="n">customers</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">==</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
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<pre>True</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#checking the number of rows in the 2 new datasets</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Rows in azdias: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Rows in customers: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">customers</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
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<pre>Rows in azdias: 733227
Rows in customers: 191652
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<p>Dropping the 'D19_LETZTER_KAUF_BRANCHE' &amp; 'EINGEFUEGT_AM' columns from azdias and customers datasets respectively, as they have too many different values.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;D19_LETZTER_KAUF_BRANCHE&#39;</span><span class="p">,</span> <span class="s1">&#39;EINGEFUEGT_AM&#39;</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">customers</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;D19_LETZTER_KAUF_BRANCHE&#39;</span><span class="p">,</span> <span class="s1">&#39;EINGEFUEGT_AM&#39;</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<p>Now we are removing the highly correlated columns to reduce the number of columns/features in our dataset. This approach has followed the approach from Chris Albon's website: <a href="https://chrisalbon.com/machine_learning/feature_selection/drop_highly_correlated_features/">https://chrisalbon.com/machine_learning/feature_selection/drop_highly_correlated_features/</a></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#finding the correlation matrix </span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Number of columns in azdias before dropping: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">azdias</span><span class="o">.</span><span class="n">columns</span><span class="p">)))</span>
<span class="n">azdias_matrix</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">corr</span><span class="p">()</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span>
<span class="n">upper_azdias</span> <span class="o">=</span> <span class="n">azdias_matrix</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">triu</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">azdias_matrix</span><span class="o">.</span><span class="n">shape</span><span class="p">),</span> <span class="n">k</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">bool</span><span class="p">))</span>

<span class="c1">#identifying the columns to drop based on the threshold limit</span>
<span class="n">azdias_drop_columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">column</span> <span class="k">for</span> <span class="n">column</span> <span class="ow">in</span> <span class="n">upper_azdias</span><span class="o">.</span><span class="n">columns</span> <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">upper_azdias</span><span class="p">[</span><span class="n">column</span><span class="p">]</span> <span class="o">&gt;</span> <span class="o">.</span><span class="mi">7</span><span class="p">)]</span>

<span class="c1">#dropping the columns from azdias</span>
<span class="n">azdias</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">azdias_drop_columns</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The number of columns left in azdias after dropping: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">azdias</span><span class="o">.</span><span class="n">columns</span><span class="p">)))</span>

<span class="c1">#repeating the same for customers</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Number of columns in customer before dropping: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">customers</span><span class="o">.</span><span class="n">columns</span><span class="p">)))</span>
<span class="n">customers_matrix</span> <span class="o">=</span> <span class="n">customers</span><span class="o">.</span><span class="n">corr</span><span class="p">()</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span>
<span class="n">upper_customers</span> <span class="o">=</span> <span class="n">customers_matrix</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">triu</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">customers_matrix</span><span class="o">.</span><span class="n">shape</span><span class="p">),</span> <span class="n">k</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">bool</span><span class="p">))</span>

<span class="n">customers_drop_columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">column</span> <span class="k">for</span> <span class="n">column</span> <span class="ow">in</span> <span class="n">upper_customers</span><span class="o">.</span><span class="n">columns</span> <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">upper_customers</span><span class="p">[</span><span class="n">column</span><span class="p">]</span> <span class="o">&gt;</span> <span class="o">.</span><span class="mi">7</span><span class="p">)]</span>

<span class="n">customers</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">customers_drop_columns</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;The number of columns left in customer after dropping: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">customers</span><span class="o">.</span><span class="n">columns</span><span class="p">)))</span>
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<pre>Number of columns in azdias before dropping: 358
The number of columns left in azdias after dropping: 238
Number of columns in customer before dropping: 358
The number of columns left in customer after dropping: 256
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<span class="n">azdias</span><span class="o">.</span><span class="n">select_dtypes</span><span class="p">(</span><span class="n">include</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;object&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
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        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
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      <th></th>
      <th>CAMEO_DEU_2015</th>
      <th>CAMEO_DEUG_2015</th>
      <th>CAMEO_INTL_2015</th>
      <th>OST_WEST_KZ</th>
    </tr>
  </thead>
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    <tr>
      <th>0</th>
      <td>8A</td>
      <td>8</td>
      <td>51</td>
      <td>W</td>
    </tr>
    <tr>
      <th>1</th>
      <td>4C</td>
      <td>4</td>
      <td>24</td>
      <td>W</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2A</td>
      <td>2</td>
      <td>12</td>
      <td>W</td>
    </tr>
    <tr>
      <th>3</th>
      <td>6B</td>
      <td>6</td>
      <td>43</td>
      <td>W</td>
    </tr>
    <tr>
      <th>4</th>
      <td>8C</td>
      <td>8</td>
      <td>54</td>
      <td>W</td>
    </tr>
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</table>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#finding the categorical field</span>

<span class="n">columns_azdias</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">columns</span>
<span class="n">numerical_columns_azdias</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">_get_numeric_data</span><span class="p">()</span><span class="o">.</span><span class="n">columns</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;numeric_columns: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">columns_azdias</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;categorical: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">columns_azdias</span><span class="p">)</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">numerical_columns_azdias</span><span class="p">))))</span>
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<pre>num_cols: Index([&#39;LNR&#39;, &#39;AGER_TYP&#39;, &#39;AKT_DAT_KL&#39;, &#39;ALTER_HH&#39;, &#39;ALTERSKATEGORIE_FEIN&#39;,
       &#39;ANZ_HAUSHALTE_AKTIV&#39;, &#39;ANZ_HH_TITEL&#39;, &#39;ANZ_KINDER&#39;, &#39;ANZ_PERSONEN&#39;,
       &#39;ANZ_TITEL&#39;,
       ...
       &#39;UMFELD_ALT&#39;, &#39;UMFELD_JUNG&#39;, &#39;UNGLEICHENN_FLAG&#39;, &#39;VERDICHTUNGSRAUM&#39;,
       &#39;VERS_TYP&#39;, &#39;VHA&#39;, &#39;VHN&#39;, &#39;W_KEIT_KIND_HH&#39;, &#39;WOHNLAGE&#39;, &#39;ZABEOTYP&#39;],
      dtype=&#39;object&#39;, length=238)
categorical: [&#39;OST_WEST_KZ&#39;, &#39;CAMEO_DEU_2015&#39;, &#39;CAMEO_INTL_2015&#39;, &#39;CAMEO_DEUG_2015&#39;]
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<table border="1" class="dataframe">
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      <th></th>
      <th>CAMEO_DEUG_2015</th>
      <th>OST_WEST_KZ</th>
      <th>CAMEO_DEU_2015</th>
      <th>CAMEO_INTL_2015</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>8</td>
      <td>W</td>
      <td>8A</td>
      <td>51</td>
    </tr>
    <tr>
      <th>1</th>
      <td>4</td>
      <td>W</td>
      <td>4C</td>
      <td>24</td>
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      <th>2</th>
      <td>2</td>
      <td>W</td>
      <td>2A</td>
      <td>12</td>
    </tr>
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      <th>3</th>
      <td>6</td>
      <td>W</td>
      <td>6B</td>
      <td>43</td>
    </tr>
    <tr>
      <th>4</th>
      <td>8</td>
      <td>W</td>
      <td>8C</td>
      <td>54</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#checking for the missing values in the columns, in this case the &#39;X&#39; also denotes the missing value </span>
<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>8      74523
9      59226
6      57592
4      54348
8.0    53892
2      43712
3      43573
9.0    43108
7      42090
6.0    41974
4.0    39642
2.0    31759
3.0    31691
7.0    30814
5      28701
5.0    20532
1      19610
1.0    14219
X        270
Name: CAMEO_DEUG_2015, dtype: int64</pre>
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<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;X&#39;</span><span class="p">,</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;OST_WEST_KZ&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>W    577348
O    155879
Name: OST_WEST_KZ, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#checking for the missing values in the columns, in this case &#39;XX&#39; also denotes the missing value </span>
<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>6B    53163
8A    50274
4C    43279
2D    32407
7A    32136
3C    32132
3D    31853
8B    31468
8C    29804
4A    29658
9D    27180
9B    26287
9C    23776
7B    22976
9A    19760
2C    17496
8D    16869
6E    15427
5D    13928
6C    13900
2B    13871
2A    11697
1D    11325
1A    10027
5A     9548
5B     9516
5C     8896
7C     8513
4B     8138
4D     7974
6A     6342
6D     5713
3A     5691
3B     5588
9E     5331
6F     5021
7D     4944
4E     4941
1E     4711
7E     4335
5F     3996
1C     3979
1B     3787
5E     3349
XX      270
Name: CAMEO_DEU_2015, dtype: int64</pre>
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<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;XX&#39;</span><span class="p">,</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>51      74003
51.0    53514
41      50093
24      48391
41.0    36487
24.0    34994
14      33490
43      30680
54      24996
14.0    24179
43.0    22483
25      21167
54.0    18265
22      17054
25.0    15627
45      14439
13      13818
55      12825
22.0    12604
52      11392
23      11309
45.0    10344
13.0    10080
34      10017
55.0     9375
15       9271
31       9194
52.0     8368
23.0     8108
44       8005
34.0     7260
15.0     6765
12       6743
31.0     6696
44.0     5895
35       5702
32       5568
33       5218
12.0     4954
35.0     4007
32.0     3948
33.0     3678
XX        270
Name: CAMEO_INTL_2015, dtype: int64</pre>
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<span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;XX&#39;</span><span class="p">,</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#replacing the same values in the same columns of the customer dataframe, basically same as the above set of cells for customer</span>
<span class="n">customers</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">customers</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;X&#39;</span><span class="p">,</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="n">customers</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">customers</span><span class="p">[</span><span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;XX&#39;</span><span class="p">,</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="n">customers</span><span class="p">[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">customers</span><span class="p">[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;XX&#39;</span><span class="p">,</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<span class="n">azdias</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;OST_WEST_KZ&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>CAMEO_DEUG_2015    1951
OST_WEST_KZ           0
CAMEO_DEU_2015     1951
CAMEO_INTL_2015    1951
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#the 3 columns having NULL values, filling these with &#39;-1</span>
<span class="n">azdias</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="n">customers</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">customers</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<span class="n">azdias</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
<span class="n">customers</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">customers</span><span class="p">[[</span><span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">,</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#converting the categorical variable by creating dummy variables for them</span>
<span class="n">azdias</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">azdias</span><span class="p">)</span>
<span class="n">customers</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">customers</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Shape of new azdias dataset: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">azdias</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Shape of new customers dataset: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">customers</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
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<pre>Shape of new azdias dataset: (733227, 283)
Shape of new customers dataset: (191652, 301)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">column_azdias</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">columns</span>
<span class="n">column_customers</span> <span class="o">=</span> <span class="n">customers</span><span class="o">.</span><span class="n">columns</span>

<span class="n">column_customers</span>
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<pre>Index([&#39;LNR&#39;, &#39;AGER_TYP&#39;, &#39;AKT_DAT_KL&#39;, &#39;ALTER_HH&#39;, &#39;ALTERSKATEGORIE_FEIN&#39;,
       &#39;ANZ_HAUSHALTE_AKTIV&#39;, &#39;ANZ_HH_TITEL&#39;, &#39;ANZ_KINDER&#39;, &#39;ANZ_PERSONEN&#39;,
       &#39;ANZ_TITEL&#39;,
       ...
       &#39;CAMEO_DEU_2015_8B&#39;, &#39;CAMEO_DEU_2015_8C&#39;, &#39;CAMEO_DEU_2015_8D&#39;,
       &#39;CAMEO_DEU_2015_9A&#39;, &#39;CAMEO_DEU_2015_9B&#39;, &#39;CAMEO_DEU_2015_9C&#39;,
       &#39;CAMEO_DEU_2015_9D&#39;, &#39;CAMEO_DEU_2015_9E&#39;, &#39;OST_WEST_KZ_O&#39;,
       &#39;OST_WEST_KZ_W&#39;],
      dtype=&#39;object&#39;, length=301)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Imputing the NaN values will the column&#39;s mode</span>

<span class="n">impute</span> <span class="o">=</span> <span class="n">Imputer</span><span class="p">(</span><span class="n">missing_values</span><span class="o">=</span><span class="s1">&#39;NaN&#39;</span><span class="p">,</span><span class="n">strategy</span><span class="o">=</span><span class="s1">&#39;most_frequent&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>

<span class="n">impute_azdias</span> <span class="o">=</span> <span class="n">impute</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">azdias</span><span class="p">)</span>
<span class="n">impute_azdias</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">impute_azdias</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;imputed azdias: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">impute_azdias</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)))</span>

<span class="n">impute_customer</span> <span class="o">=</span> <span class="n">impute</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">customers</span><span class="p">)</span>
<span class="n">impute_customer</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">impute_customer</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;imputed customers: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">impute_customer</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)))</span>
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<pre>imputed azdias:         0    1    2     3     4     5    6    7    8    9   ...   273  274  \
0  910220.0 -1.0  9.0   0.0  21.0  11.0  0.0  0.0  2.0  0.0 ...   0.0  0.0   
1  910225.0 -1.0  9.0  17.0  17.0  10.0  0.0  0.0  1.0  0.0 ...   0.0  0.0   
2  910226.0  2.0  1.0  13.0  13.0   1.0  0.0  0.0  0.0  0.0 ...   0.0  0.0   
3  910241.0 -1.0  1.0  20.0  14.0   3.0  0.0  0.0  4.0  0.0 ...   0.0  0.0   
4  910244.0  3.0  1.0  10.0  10.0   5.0  0.0  0.0  1.0  0.0 ...   0.0  1.0   

   275  276  277  278  279  280  281  282  
0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
2  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
3  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
4  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  

[5 rows x 283 columns]
imputed customers:         0    1    2     3     4    5    6    7    8    9   ...   291  292  \
0    9626.0  2.0  1.0  10.0  10.0  1.0  0.0  0.0  2.0  0.0 ...   0.0  0.0   
1    9628.0 -1.0  9.0  11.0  10.0  1.0  0.0  0.0  3.0  0.0 ...   0.0  0.0   
2  143872.0 -1.0  1.0   6.0   0.0  1.0  0.0  0.0  1.0  0.0 ...   0.0  0.0   
3  143873.0  1.0  1.0   8.0   8.0  0.0  0.0  0.0  0.0  0.0 ...   0.0  0.0   
4  143874.0 -1.0  1.0  20.0  14.0  7.0  0.0  0.0  4.0  0.0 ...   0.0  0.0   

   293  294  295  296  297  298  299  300  
0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  
2  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
3  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  
4  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  

[5 rows x 301 columns]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#since all the columns are now numerical value, we will now change the data type to int</span>
<span class="n">azdias</span> <span class="o">=</span> <span class="n">impute_azdias</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
<span class="n">customers</span> <span class="o">=</span> <span class="n">impute_customer</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Checking &amp; Cleaning Outliers</span>
<span class="n">azdias</span> <span class="o">=</span> <span class="n">azdias</span><span class="p">[(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">zscore</span><span class="p">(</span><span class="n">azdias</span><span class="p">))</span> <span class="o">&lt;</span> <span class="mi">6</span><span class="p">)</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)]</span>
<span class="n">customers</span> <span class="o">=</span> <span class="n">customers</span><span class="p">[(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">zscore</span><span class="p">(</span><span class="n">customers</span><span class="p">))</span> <span class="o">&lt;</span> <span class="mi">6</span><span class="p">)</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Normalising the data</span>
<span class="n">azdias</span><span class="p">[</span><span class="n">azdias</span><span class="o">.</span><span class="n">columns</span><span class="p">]</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">azdias</span><span class="p">)</span>
<span class="n">customers</span><span class="p">[</span><span class="n">customers</span><span class="o">.</span><span class="n">columns</span><span class="p">]</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">customers</span><span class="p">)</span>

<span class="n">azdias</span><span class="o">.</span><span class="n">shape</span>
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<h2 id="Complete-Pre-Processing-Data-Function-(summary-of-all-above-cells)">Complete Pre-Processing Data Function (summary of all above cells)<a class="anchor-link" href="#Complete-Pre-Processing-Data-Function-(summary-of-all-above-cells)">&#182;</a></h2><p>This is mostly for the supervised machine learning part of the project so that the above cells written right now for <strong>Clustering</strong>, dont have to be repeated for SML</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">data_preprocess</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">cluster</span><span class="p">,</span> <span class="n">dataname</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">cluster</span><span class="p">:</span>
        <span class="k">if</span> <span class="n">dataname</span> <span class="o">==</span> <span class="s1">&#39;azdias&#39;</span><span class="p">:</span>
            <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> <span class="o">&lt;=</span> <span class="mi">16</span><span class="p">]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
        <span class="k">elif</span> <span class="n">dataname</span> <span class="o">==</span> <span class="s1">&#39;customers&#39;</span><span class="p">:</span>            
            <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;CUSTOMER_GROUP&#39;</span><span class="p">,</span> <span class="s1">&#39;ONLINE_PURCHASE&#39;</span><span class="p">,</span> <span class="s1">&#39;PRODUCT_GROUP&#39;</span><span class="p">],</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Dropping columns with more than 65% missing values&quot;</span><span class="p">)</span>      
    <span class="n">columns_drop</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;EXTSEL992&#39;</span><span class="p">,</span> <span class="s1">&#39;KK_KUNDENTYP&#39;</span><span class="p">,</span> <span class="s1">&#39;ALTER_KIND1&#39;</span><span class="p">,</span> <span class="s1">&#39;ALTER_KIND2&#39;</span><span class="p">,</span> <span class="s1">&#39;ALTER_KIND3&#39;</span><span class="p">,</span> <span class="s1">&#39;ALTER_KIND4&#39;</span><span class="p">]</span>
    
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns_drop</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;D19_LETZTER_KAUF_BRANCHE&#39;</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;EINGEFUEGT_AM&#39;</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;columns dropped&#39;</span><span class="p">)</span>
    
    <span class="c1"># computing the correlation matrix and dropping the correlated matrix</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Computing Correlation matrix&#39;</span><span class="p">)</span>
    <span class="n">correlation_matrix</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">corr</span><span class="p">()</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span>
    <span class="n">upper_data</span> <span class="o">=</span> <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">triu</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">correlation_matrix</span><span class="o">.</span><span class="n">shape</span><span class="p">),</span> <span class="n">k</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">bool</span><span class="p">))</span>
    <span class="n">drop_column</span>  <span class="o">=</span> <span class="p">[</span><span class="n">col</span> <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">upper_data</span><span class="o">.</span><span class="n">columns</span> <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">upper_data</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">&gt;</span> <span class="o">.</span><span class="mi">7</span><span class="p">)]</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">drop_column</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;shape after dropping the correlated columns: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
    
    <span class="c1">#filling the missing and unknown values with -1 </span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;filling nan vlaues with -1&#39;</span><span class="p">)</span>
    <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">replace</span><span class="p">([</span><span class="s1">&#39;X&#39;</span><span class="p">,</span><span class="s1">&#39;XX&#39;</span><span class="p">],</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;CAMEO_INTL_2015&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEUG_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
    <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;OST_WEST_KZ&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[[</span><span class="s1">&#39;OST_WEST_KZ&#39;</span><span class="p">,</span> <span class="s1">&#39;CAMEO_DEU_2015&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
    
     <span class="c1"># filling na fields with 9 that has marked 9 as unknown</span>
    <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[(</span><span class="n">data</span><span class="o">==</span><span class="mi">9</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[(</span><span class="n">data</span><span class="o">==</span><span class="mi">9</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">9</span><span class="p">)</span>

    <span class="c1"># filling na fields with 0 that has marked 0 as unknown</span>
    <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[(</span><span class="n">data</span><span class="o">==</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[(</span><span class="n">data</span><span class="o">==</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>

    <span class="c1"># filling na fields with -1 that has marked -1 as unknown</span>
    <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[(</span><span class="n">data</span><span class="o">==-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()]]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">[(</span><span class="n">data</span><span class="o">==-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()]]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;values filled&#39;</span><span class="p">)</span>
    <span class="c1">#creating dummy variable for the categorical variables</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;creating dummy variables&#39;</span><span class="p">)</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Shape of data after creating dummy vairables: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
    
    <span class="n">columns_data</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
    
    <span class="c1">#imputing the nan value with mode</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Imputing nan values with mode&#39;</span><span class="p">)</span>
    <span class="n">mode_impute</span> <span class="o">=</span> <span class="n">Imputer</span><span class="p">(</span><span class="n">missing_values</span><span class="o">=</span><span class="s1">&#39;NaN&#39;</span><span class="p">,</span><span class="n">strategy</span><span class="o">=</span><span class="s1">&#39;most_frequent&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">mode_impute</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;shape after imputing the values&#39;</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
    
    <span class="c1">#converting all values in df to int</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
    
    <span class="c1">#reomving outliers</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;removing outliers&#39;</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">cluster</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Removing outliers&#39;</span><span class="p">)</span>
        <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">zscore</span><span class="p">(</span><span class="n">data</span><span class="p">))</span> <span class="o">&lt;</span> <span class="mi">6</span><span class="p">)</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)]</span> 
        
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Shape before normalising: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
    <span class="n">normaliser</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">normaliser</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span> <span class="n">columns_data</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Shape after normalising: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
        
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s1">&#39;LNR&#39;</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">data</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias</span> <span class="o">=</span> <span class="n">data_preprocess</span><span class="p">(</span><span class="n">azdias_copy</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="s1">&#39;azdias&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;*****************************************************&quot;</span><span class="p">)</span>
<span class="n">customers</span> <span class="o">=</span> <span class="n">data_preprocess</span><span class="p">(</span><span class="n">customers_copy</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="s1">&#39;customers&#39;</span><span class="p">)</span>
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<pre>Dropping columns with more than 65% missing values
columns dropped
Computing Correlation matrix
shape after dropping the correlated columns: (733227, 238)
filling nan vlaues with -1
values filled
creating dummy variables
Shape of data after creating dummy vairables: (733227, 284)
Imputing nan values with mode
shape after imputing the values (733227, 284)
removing outliers
Removing outliers
Shape before normalising: (415405, 284)
Shape after normalising: (415405, 284)
*****************************************************
Dropping columns with more than 65% missing values
columns dropped
Computing Correlation matrix
shape after dropping the correlated columns: (191652, 256)
filling nan vlaues with -1
values filled
creating dummy variables
Shape of data after creating dummy vairables: (191652, 303)
Imputing nan values with mode
shape after imputing the values (191652, 303)
removing outliers
Removing outliers
Shape before normalising: (100341, 303)
Shape after normalising: (100341, 303)
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<p>We are finally done with cleaning and pre-processing the data. Now we will use this data to analyse the relationships between the variables/attributes.</p>

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<h2 id="Part-1:-Customer-Segmentation-Report">Part 1: Customer Segmentation Report<a class="anchor-link" href="#Part-1:-Customer-Segmentation-Report">&#182;</a></h2><p>The main bulk of your analysis will come in this part of the project. Here, you should use unsupervised learning techniques to describe the relationship between the demographics of the company's existing customers and the general population of Germany. By the end of this part, you should be able to describe parts of the general population that are more likely to be part of the mail-order company's main customer base, and which parts of the general population are less so.</p>
<p><strong>We first reduce the dimension of our dataset further. We can now use PCA for dimensional reduction. To decide the exact components we want to keep, we can see the variance across the features. We want our dataset to maintain a high vairance for better results</strong></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#plotting the graph for pca</span>
<span class="n">data_pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">azdias</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">18</span><span class="p">,</span><span class="mi">9</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">data_pca</span><span class="o">.</span><span class="n">explained_variance_ratio_</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of features&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Variance distribution across features&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Cumulative Variance&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<p><strong>We can see from the graph above, that at 220 components we are getting high variance which is neccessary for keeping critical information about the data. So now we will use PCA to reduce the dimension of data to 220.</strong></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">dimension_reduce</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">n_component</span><span class="o">=</span><span class="mi">220</span><span class="p">):</span>
    <span class="n">data_pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="n">n_component</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
    <span class="n">dimension_reduce</span> <span class="o">=</span> <span class="n">data_pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
    <span class="n">dimension_reduce</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">dimension_reduce</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Variance of reduced dataset: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">data_pca</span><span class="o">.</span><span class="n">explained_variance_ratio_</span><span class="o">.</span><span class="n">sum</span><span class="p">()))</span>
    <span class="k">return</span> <span class="n">dimension_reduce</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#performind data reduction on the dataset</span>
<span class="n">azdias_pca</span> <span class="o">=</span> <span class="n">dimension_reduce</span><span class="p">(</span><span class="n">azdias</span><span class="p">)</span>
<span class="n">customers_pca</span> <span class="o">=</span> <span class="n">dimension_reduce</span><span class="p">(</span><span class="n">customers</span><span class="p">)</span>
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<pre>Variance of reduced dataset: 0.9870114176448358
Variance of reduced dataset: 0.9973588406142715
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#printing the new shape of our dataset</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Shape of new azdias dataset: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">azdias_pca</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Shape of new customer dataset: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">customers_pca</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
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<pre>Shape of new azdias dataset: (415405, 220)
Shape of new customer dataset: (100341, 220)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">azdias_pca</span><span class="o">.</span><span class="n">to_pickle</span><span class="p">(</span><span class="s1">&#39;azdias_pca.p&#39;</span><span class="p">)</span>
<span class="n">customers_pca</span><span class="o">.</span><span class="n">to_pickle</span><span class="p">(</span><span class="s1">&#39;customers_pca.p&#39;</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#loading pickle files</span>
<span class="n">azdias_pca</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_pickle</span><span class="p">(</span><span class="s1">&#39;azdias_pca.p&#39;</span><span class="p">)</span>
<span class="n">customers_pca</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_pickle</span><span class="p">(</span><span class="s1">&#39;customers_pca.p&#39;</span><span class="p">)</span>
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<h1 id="Clustering">Clustering<a class="anchor-link" href="#Clustering">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#defining the no. of clusters</span>
<span class="k">def</span> <span class="nf">k_mean_scores</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
    <span class="n">k_means</span> <span class="o">=</span> <span class="n">KMeans</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">k_means_model</span> <span class="o">=</span> <span class="n">k_means</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
    <span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="n">k_means_model</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># checking the scores for different no. of clusters</span>
<span class="n">accuracies</span> <span class="o">=</span> <span class="p">[]</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">25</span><span class="p">):</span>
    <span class="n">accuracies</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k_mean_scores</span><span class="p">(</span><span class="n">azdias_pca</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="mi">20000</span><span class="p">),</span> <span class="n">i</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">marks</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">24</span><span class="p">,</span><span class="mi">24</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">marks</span><span class="p">,</span> <span class="n">accuracies</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">25</span><span class="p">,</span><span class="mi">2</span><span class="p">)))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of Clusters&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Average Within-Cluster Distances&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot; Distance within clusters vs No. of clusters&quot;</span><span class="p">)</span>
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<pre>Text(0.5,1,&#39; Distance within clusters vs No. of clusters&#39;)</pre>
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<p><strong>As we can see from the above chart, that the average distance within the clusters almost flatterns when the number of clusters reaches 16. So we will use 16 clusters for our analysis</strong></p>

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<div class="prompt input_prompt">In&nbsp;[18]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#making the model with 16 clusters</span>
<span class="n">k_means</span> <span class="o">=</span> <span class="n">KMeans</span><span class="p">(</span><span class="n">n_clusters</span> <span class="o">=</span> <span class="mi">16</span><span class="p">)</span>
<span class="n">k_means_model</span> <span class="o">=</span> <span class="n">k_means</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">azdias_pca</span><span class="p">)</span>
<span class="n">azdias_predict</span> <span class="o">=</span> <span class="n">k_means_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">azdias_pca</span><span class="p">)</span>
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<div class="prompt input_prompt">In&nbsp;[19]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#saving the prediction of the model in a pickle file</span>

<span class="n">cluster_azdias</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">azdias_predict</span><span class="p">,</span> <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Cluster&#39;</span><span class="p">])</span>
<span class="n">cluster_azdias</span><span class="o">.</span><span class="n">to_pickle</span><span class="p">(</span><span class="s1">&#39;azdias_clustered&#39;</span><span class="p">)</span>
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<div class="prompt input_prompt">In&nbsp;[20]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#doing the same above actions for the customer dataset</span>

<span class="n">customers_predict</span> <span class="o">=</span> <span class="n">k_means_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">customers_pca</span><span class="p">)</span>
<span class="n">cluster_customers</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">customers_predict</span><span class="p">,</span> <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Cluster&#39;</span><span class="p">])</span>
<span class="n">cluster_customers</span><span class="o">.</span><span class="n">to_pickle</span><span class="p">(</span><span class="s1">&#39;customers_clustered&#39;</span><span class="p">)</span>
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<h2 id="Analying-and-comparing-the-cluster-between-the-general-population-and-customers">Analying and comparing the cluster between the general population and customers<a class="anchor-link" href="#Analying-and-comparing-the-cluster-between-the-general-population-and-customers">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#counting the number of values in each clusters</span>
<span class="n">cluster_customer</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="n">customers_predict</span><span class="p">)</span>
<span class="n">unique_val_customer</span> <span class="o">=</span> <span class="n">cluster_customer</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>

<span class="n">cluster_people</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="n">azdias_predict</span><span class="p">)</span>
<span class="n">unique_val_people</span> <span class="o">=</span> <span class="n">cluster_people</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>

<span class="c1">#combining the two dataframes</span>
<span class="n">cluster_combine</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">unique_val_people</span><span class="p">,</span> <span class="n">unique_val_customer</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
<span class="n">cluster_combine</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Cluster No&#39;</span><span class="p">,</span><span class="s1">&#39;Values in poplutation&#39;</span><span class="p">,</span><span class="s1">&#39;Values in customer&#39;</span><span class="p">]</span>

<span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;difference&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in customer&#39;</span><span class="p">]</span><span class="o">/</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in customer&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span> <span class="o">-</span> <span class="p">(</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in poplutation&#39;</span><span class="p">]</span><span class="o">/</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in poplutation&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
<span class="n">cluster_combine</span>
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      <th>Cluster No</th>
      <th>Values in poplutation</th>
      <th>Values in customer</th>
      <th>difference</th>
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      <th>0</th>
      <td>0</td>
      <td>37329</td>
      <td>62</td>
      <td>-8.924381</td>
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    <tr>
      <th>1</th>
      <td>1</td>
      <td>24943</td>
      <td>15154</td>
      <td>9.097999</td>
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    <tr>
      <th>2</th>
      <td>2</td>
      <td>14901</td>
      <td>22</td>
      <td>-3.565177</td>
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    <tr>
      <th>3</th>
      <td>3</td>
      <td>40037</td>
      <td>315</td>
      <td>-9.324135</td>
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    <tr>
      <th>4</th>
      <td>4</td>
      <td>23436</td>
      <td>732</td>
      <td>-4.912211</td>
    </tr>
    <tr>
      <th>5</th>
      <td>5</td>
      <td>31989</td>
      <td>23</td>
      <td>-7.677756</td>
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      <th>6</th>
      <td>6</td>
      <td>17667</td>
      <td>67</td>
      <td>-4.186186</td>
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      <th>7</th>
      <td>7</td>
      <td>24439</td>
      <td>44908</td>
      <td>38.872210</td>
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    <tr>
      <th>8</th>
      <td>8</td>
      <td>23172</td>
      <td>987</td>
      <td>-4.594525</td>
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      <th>9</th>
      <td>9</td>
      <td>32669</td>
      <td>2535</td>
      <td>-5.337988</td>
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      <th>10</th>
      <td>10</td>
      <td>30382</td>
      <td>10032</td>
      <td>2.684081</td>
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      <th>11</th>
      <td>11</td>
      <td>9027</td>
      <td>2048</td>
      <td>-0.132020</td>
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    <tr>
      <th>12</th>
      <td>12</td>
      <td>33235</td>
      <td>6967</td>
      <td>-1.057303</td>
    </tr>
    <tr>
      <th>13</th>
      <td>13</td>
      <td>23352</td>
      <td>77</td>
      <td>-5.544764</td>
    </tr>
    <tr>
      <th>14</th>
      <td>14</td>
      <td>21359</td>
      <td>2018</td>
      <td>-3.130587</td>
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    <tr>
      <th>15</th>
      <td>15</td>
      <td>27468</td>
      <td>14394</td>
      <td>7.732741</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;pop_percent&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in poplutation&#39;</span><span class="p">]</span><span class="o">/</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in poplutation&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
<span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;cust_percent&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in customer&#39;</span><span class="p">]</span><span class="o">/</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Values in customer&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>

<span class="n">figure</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">5</span><span class="p">))</span>

<span class="n">axes</span> <span class="o">=</span> <span class="n">figure</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
<span class="n">axes</span> <span class="o">=</span> <span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;pop_percent&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;Cluster No&#39;</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span> <span class="n">width</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">align</span><span class="o">=</span><span class="s1">&#39;edge&#39;</span><span class="p">,</span> <span class="n">kind</span><span class="o">=</span><span class="s1">&#39;bar&#39;</span><span class="p">,</span><span class="n">position</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">axes</span> <span class="o">=</span> <span class="n">cluster_combine</span><span class="p">[</span><span class="s1">&#39;cust_percent&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;bar&#39;</span><span class="p">,</span><span class="n">color</span><span class="o">=</span><span class="s1">&#39;yellow&#39;</span><span class="p">,</span><span class="n">width</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">align</span><span class="o">=</span><span class="s1">&#39;edge&#39;</span><span class="p">,</span><span class="n">position</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Ratio Percentage&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;Clusters&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span> 
<span class="n">axes</span><span class="o">.</span><span class="n">tick_params</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="n">which</span> <span class="o">=</span> <span class="s1">&#39;major&#39;</span><span class="p">,</span> <span class="n">labelsize</span> <span class="o">=</span> <span class="mi">13</span><span class="p">)</span>
<span class="n">axes</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="n">ticklabels</span><span class="o">=</span><span class="nb">range</span><span class="p">(</span><span class="mi">20</span><span class="p">))</span>
<span class="n">axes</span><span class="o">.</span><span class="n">margins</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span><span class="n">y</span><span class="o">=</span><span class="mf">0.1</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">((</span><span class="s1">&#39;General Population&#39;</span><span class="p">,</span> <span class="s1">&#39;Customers&#39;</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">((</span><span class="s1">&#39;Ratio of General Population Vs Customer segments as percentage of total per cluster&#39;</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cluster_combine</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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  <thead>
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      <th></th>
      <th>Cluster No</th>
      <th>Values in poplutation</th>
      <th>Values in customer</th>
      <th>difference</th>
      <th>pop_percent</th>
      <th>cust_percent</th>
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    <tr>
      <th>0</th>
      <td>0</td>
      <td>37329</td>
      <td>62</td>
      <td>-8.924381</td>
      <td>8.99</td>
      <td>0.06</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1</td>
      <td>24943</td>
      <td>15154</td>
      <td>9.097999</td>
      <td>6.00</td>
      <td>15.10</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2</td>
      <td>14901</td>
      <td>22</td>
      <td>-3.565177</td>
      <td>3.59</td>
      <td>0.02</td>
    </tr>
    <tr>
      <th>3</th>
      <td>3</td>
      <td>40037</td>
      <td>315</td>
      <td>-9.324135</td>
      <td>9.64</td>
      <td>0.31</td>
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    <tr>
      <th>4</th>
      <td>4</td>
      <td>23436</td>
      <td>732</td>
      <td>-4.912211</td>
      <td>5.64</td>
      <td>0.73</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Showing the Highest Positive and Negative weights when a PC component and Weight is passed</span>
<span class="k">def</span> <span class="nf">pca_weights</span><span class="p">(</span><span class="n">pc</span> <span class="p">,</span> <span class="n">weights</span><span class="p">,</span> <span class="n">data_pca</span><span class="p">):</span>
    <span class="n">variance_ratio</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">data_pca</span><span class="o">.</span><span class="n">explained_variance_ratio_</span><span class="p">,</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;EXPLAINED_VARIANCE&#39;</span><span class="p">])</span>
    <span class="n">variance_ratio</span>  <span class="o">=</span> <span class="n">variance_ratio</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
    <span class="n">azdias_weights</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">data_pca</span><span class="o">.</span><span class="n">components_</span><span class="p">,</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">azdias</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
    <span class="n">azdias_weights</span> <span class="o">=</span> <span class="n">azdias_weights</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>    
    
    <span class="n">final_result</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">variance_ratio</span><span class="p">,</span> <span class="n">azdias_weights</span><span class="p">],</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>  <span class="n">join_axes</span><span class="o">=</span><span class="p">[</span><span class="n">variance_ratio</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
    <span class="n">final_result</span><span class="p">[:</span><span class="mi">5</span><span class="p">]</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Number of Principal Component: &quot;</span><span class="p">,</span> <span class="p">(</span><span class="n">pc</span><span class="p">))</span>    
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Maximum Positive weights:&quot;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">final_result</span><span class="o">.</span><span class="n">iloc</span><span class="p">[(</span><span class="n">pc</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)[:</span><span class="n">weights</span><span class="p">])</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Maximum Negative weights:&quot;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">final_result</span><span class="o">.</span><span class="n">iloc</span><span class="p">[(</span><span class="n">pc</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()[:</span><span class="n">weights</span><span class="p">])</span>
    

<span class="n">data_pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">azdias</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pca_weights</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="n">data_pca</span><span class="p">)</span>
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<pre>Number of Principal Component:  15


Maximum Positive weights:
KBA13_VORB_0        0.252
KBA05_ZUL1          0.246
KBA13_KRSZUL_NEU    0.227
KBA13_BJ_2008       0.198
KBA13_BJ_2009       0.187
Name: 14, dtype: float64


Maximum Negative weights:
KBA13_VORB_1_2    -0.304
KBA13_BJ_2004     -0.230
KBA05_MAXBJ       -0.211
KBA05_ZUL2        -0.162
RT_SCHNAEPPCHEN   -0.158
Name: 14, dtype: float64
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<h2 id="Part-2:-Supervised-Learning-Model">Part 2: Supervised Learning Model<a class="anchor-link" href="#Part-2:-Supervised-Learning-Model">&#182;</a></h2><p>Now that you've found which parts of the population are more likely to be customers of the mail-order company, it's time to build a prediction model. Each of the rows in the "MAILOUT" data files represents an individual that was targeted for a mailout campaign. Ideally, we should be able to use the demographic information from each individual to decide whether or not it will be worth it to include that person in the campaign.</p>
<p>The "MAILOUT" data has been split into two approximately equal parts, each with almost 43 000 data rows. In this part, you can verify your model with the "TRAIN" partition, which includes a column, "RESPONSE", that states whether or not a person became a customer of the company following the campaign. In the next part, you'll need to create predictions on the "TEST" partition, where the "RESPONSE" column has been withheld.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">mailout_train</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/Term2/capstone/arvato_data/Udacity_MAILOUT_052018_TRAIN.csv&#39;</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;;&#39;</span><span class="p">)</span>
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<pre>/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2785: DtypeWarning: Columns (18,19) have mixed types. Specify dtype option on import or set low_memory=False.
  interactivity=interactivity, compiler=compiler, result=result)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X</span> <span class="o">=</span> <span class="n">mailout_train</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;RESPONSE&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">mailout_train</span><span class="p">[</span><span class="s1">&#39;RESPONSE&#39;</span><span class="p">]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>LNR</th>
      <th>AGER_TYP</th>
      <th>AKT_DAT_KL</th>
      <th>ALTER_HH</th>
      <th>ALTER_KIND1</th>
      <th>ALTER_KIND2</th>
      <th>ALTER_KIND3</th>
      <th>ALTER_KIND4</th>
      <th>ALTERSKATEGORIE_FEIN</th>
      <th>ANZ_HAUSHALTE_AKTIV</th>
      <th>...</th>
      <th>VHN</th>
      <th>VK_DHT4A</th>
      <th>VK_DISTANZ</th>
      <th>VK_ZG11</th>
      <th>W_KEIT_KIND_HH</th>
      <th>WOHNDAUER_2008</th>
      <th>WOHNLAGE</th>
      <th>ZABEOTYP</th>
      <th>ANREDE_KZ</th>
      <th>ALTERSKATEGORIE_GROB</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1763</td>
      <td>2</td>
      <td>1.0</td>
      <td>8.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>8.0</td>
      <td>15.0</td>
      <td>...</td>
      <td>2.0</td>
      <td>5.0</td>
      <td>2.0</td>
      <td>1.0</td>
      <td>6.0</td>
      <td>9.0</td>
      <td>3.0</td>
      <td>3</td>
      <td>2</td>
      <td>4</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1771</td>
      <td>1</td>
      <td>4.0</td>
      <td>13.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>13.0</td>
      <td>1.0</td>
      <td>...</td>
      <td>3.0</td>
      <td>1.0</td>
      <td>2.0</td>
      <td>1.0</td>
      <td>4.0</td>
      <td>9.0</td>
      <td>7.0</td>
      <td>1</td>
      <td>2</td>
      <td>3</td>
    </tr>
    <tr>
      <th>2</th>
      <td>1776</td>
      <td>1</td>
      <td>1.0</td>
      <td>9.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>7.0</td>
      <td>0.0</td>
      <td>...</td>
      <td>1.0</td>
      <td>6.0</td>
      <td>4.0</td>
      <td>2.0</td>
      <td>NaN</td>
      <td>9.0</td>
      <td>2.0</td>
      <td>3</td>
      <td>1</td>
      <td>4</td>
    </tr>
    <tr>
      <th>3</th>
      <td>1460</td>
      <td>2</td>
      <td>1.0</td>
      <td>6.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>6.0</td>
      <td>4.0</td>
      <td>...</td>
      <td>4.0</td>
      <td>8.0</td>
      <td>11.0</td>
      <td>11.0</td>
      <td>6.0</td>
      <td>9.0</td>
      <td>1.0</td>
      <td>3</td>
      <td>2</td>
      <td>4</td>
    </tr>
    <tr>
      <th>4</th>
      <td>1783</td>
      <td>2</td>
      <td>1.0</td>
      <td>9.0</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>9.0</td>
      <td>53.0</td>
      <td>...</td>
      <td>4.0</td>
      <td>2.0</td>
      <td>2.0</td>
      <td>1.0</td>
      <td>6.0</td>
      <td>9.0</td>
      <td>3.0</td>
      <td>3</td>
      <td>1</td>
      <td>3</td>
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<p>5 rows × 366 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<pre>0    0
1    0
2    0
3    0
4    0
Name: RESPONSE, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%%</span><span class="k">time</span>
train_data = data_preprocess(X, False)
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<pre>Dropping columns with more than 65% missing values
columns dropped
Computing Correlation matrix
shape after dropping the correlated columns: (42962, 253)
filling nan vlaues with -1
values filled
creating dummy variables
Shape of data after creating dummy vairables: (42962, 300)
Imputing nan values with mode
shape after imputing the values (42962, 300)
removing outliers
Shape before normalising: (42962, 300)
Shape after normalising: (42962, 300)
CPU times: user 21.2 s, sys: 525 ms, total: 21.8 s
Wall time: 28.8 s
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_data</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
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    <tr style="text-align: right;">
      <th></th>
      <th>AGER_TYP</th>
      <th>AKT_DAT_KL</th>
      <th>ALTER_HH</th>
      <th>ALTERSKATEGORIE_FEIN</th>
      <th>ANZ_HAUSHALTE_AKTIV</th>
      <th>ANZ_HH_TITEL</th>
      <th>ANZ_KINDER</th>
      <th>ANZ_PERSONEN</th>
      <th>ANZ_TITEL</th>
      <th>ARBEIT</th>
      <th>...</th>
      <th>CAMEO_DEU_2015_8D</th>
      <th>CAMEO_DEU_2015_9A</th>
      <th>CAMEO_DEU_2015_9B</th>
      <th>CAMEO_DEU_2015_9C</th>
      <th>CAMEO_DEU_2015_9D</th>
      <th>CAMEO_DEU_2015_9E</th>
      <th>CAMEO_DEU_2015_XX</th>
      <th>OST_WEST_KZ_-1</th>
      <th>OST_WEST_KZ_O</th>
      <th>OST_WEST_KZ_W</th>
    </tr>
    <tr>
      <th>LNR</th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>-1.656309</th>
      <td>1.031262</td>
      <td>-0.545883</td>
      <td>-0.371726</td>
      <td>-0.428455</td>
      <td>0.573402</td>
      <td>-0.499090</td>
      <td>-0.204857</td>
      <td>-0.752038</td>
      <td>-0.083831</td>
      <td>-0.459891</td>
      <td>...</td>
      <td>-0.167172</td>
      <td>-0.104604</td>
      <td>-0.110149</td>
      <td>-0.100902</td>
      <td>-0.125771</td>
      <td>-0.094216</td>
      <td>-0.016003</td>
      <td>-0.47014</td>
      <td>-0.494196</td>
      <td>0.778419</td>
    </tr>
    <tr>
      <th>-1.655987</th>
      <td>0.323502</td>
      <td>0.396516</td>
      <td>0.523127</td>
      <td>0.837103</td>
      <td>-0.445506</td>
      <td>-0.499090</td>
      <td>-0.204857</td>
      <td>-0.402222</td>
      <td>-0.083831</td>
      <td>-0.860749</td>
      <td>...</td>
      <td>-0.167172</td>
      <td>-0.104604</td>
      <td>-0.110149</td>
      <td>-0.100902</td>
      <td>-0.125771</td>
      <td>-0.094216</td>
      <td>-0.016003</td>
      <td>-0.47014</td>
      <td>-0.494196</td>
      <td>0.778419</td>
    </tr>
    <tr>
      <th>-1.655785</th>
      <td>0.323502</td>
      <td>-0.545883</td>
      <td>-0.192755</td>
      <td>-0.681567</td>
      <td>-0.518285</td>
      <td>2.042255</td>
      <td>-0.204857</td>
      <td>-1.101855</td>
      <td>-0.083831</td>
      <td>-0.059034</td>
      <td>...</td>
      <td>-0.167172</td>
      <td>-0.104604</td>
      <td>-0.110149</td>
      <td>-0.100902</td>
      <td>-0.125771</td>
      <td>-0.094216</td>
      <td>-0.016003</td>
      <td>-0.47014</td>
      <td>2.023489</td>
      <td>-1.284655</td>
    </tr>
    <tr>
      <th>-1.668538</th>
      <td>1.031262</td>
      <td>-0.545883</td>
      <td>-0.729667</td>
      <td>-0.934679</td>
      <td>-0.227168</td>
      <td>-0.499090</td>
      <td>-0.204857</td>
      <td>-0.402222</td>
      <td>-0.083831</td>
      <td>-0.059034</td>
      <td>...</td>
      <td>-0.167172</td>
      <td>-0.104604</td>
      <td>-0.110149</td>
      <td>-0.100902</td>
      <td>-0.125771</td>
      <td>-0.094216</td>
      <td>-0.016003</td>
      <td>-0.47014</td>
      <td>-0.494196</td>
      <td>0.778419</td>
    </tr>
    <tr>
      <th>-1.655502</th>
      <td>1.031262</td>
      <td>-0.545883</td>
      <td>-0.192755</td>
      <td>-0.175344</td>
      <td>3.339007</td>
      <td>-0.499090</td>
      <td>-0.204857</td>
      <td>-0.752038</td>
      <td>-0.083831</td>
      <td>-0.459891</td>
      <td>...</td>
      <td>-0.167172</td>
      <td>-0.104604</td>
      <td>-0.110149</td>
      <td>-0.100902</td>
      <td>-0.125771</td>
      <td>-0.094216</td>
      <td>-0.016003</td>
      <td>-0.47014</td>
      <td>-0.494196</td>
      <td>0.778419</td>
    </tr>
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</table>
<p>5 rows × 299 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#splitting the dataset into training and testing</span>
<span class="n">X_train</span><span class="p">,</span> <span class="n">X_val</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_val</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">stratify</span><span class="o">=</span><span class="n">y</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%%</span><span class="k">time</span>
#basic training use LGBMRegressor
regressor = lgb.LGBMRegressor(
            learning_rate=0.001, 
            lambda_l2 = 0.1,
            n_estimators=6000
        )

classfier = lgb.LGBMRegressor(random_state=0)
parm = {&#39;learning_rate&#39; : [0.01, 0.001, 0.001],
        &#39;n_estimators&#39; : [100, 500, 1000, 2000],
        &#39;max_depth&#39;: [3, 5, 10]
       }

#Performing grid search
object_cv = GridSearchCV(classfier, parm, scoring = &#39;roc_auc&#39;)

#Fitting the model
fit_cv = object_cv.fit(X_train, y_train)

#Getting the estimator and prediction
best_classfier = fit_cv.best_estimator_
normal_predictions = (classfier.fit(X_train, y_train)).predict(X_val)
best_clf_predictions = best_classfier.predict(X_val)

# Report the before-and-afterscores
print(&quot;Unoptimized Model Prediction&quot;)
print(&quot;ROC score on testing data: {:.6f}&quot;.format(roc_auc_score(y_val, normal_predictions)))
print(&quot;-----------------------------------------------------------------------&quot;)
print(&quot;Best Model Prdictions&quot;)
print(&quot;ROC score on testing data: {:.6f}&quot;.format(roc_auc_score(y_val, best_clf_predictions)))
print(&quot;-----------------------------------------------------------------------&quot;)
print(fit_cv.best_params_)
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<pre>Unoptimized Model Prediction
ROC score on testing data: 0.674472
-----------------------------------------------------------------------
Best Model Prdictions
ROC score on testing data: 0.760259
-----------------------------------------------------------------------
{&#39;learning_rate&#39;: 0.001, &#39;max_depth&#39;: 10, &#39;n_estimators&#39;: 500}
CPU times: user 1h 2min 23s, sys: 8.7 s, total: 1h 2min 32s
Wall time: 1h 2min 46s
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<h2 id="Part-3:-Kaggle-Competition">Part 3: Kaggle Competition<a class="anchor-link" href="#Part-3:-Kaggle-Competition">&#182;</a></h2><p>Now that you've created a model to predict which individuals are most likely to respond to a mailout campaign, it's time to test that model in competition through Kaggle. If you click on the link <a href="http://www.kaggle.com/t/21e6d45d4c574c7fa2d868f0e8c83140">here</a>, you'll be taken to the competition page where, if you have a Kaggle account, you can enter. If you're one of the top performers, you may have the chance to be contacted by a hiring manager from Arvato or Bertelsmann for an interview!</p>
<p>Your entry to the competition should be a CSV file with two columns. The first column should be a copy of "LNR", which acts as an ID number for each individual in the "TEST" partition. The second column, "RESPONSE", should be some measure of how likely each individual became a customer – this might not be a straightforward probability. As you should have found in Part 2, there is a large output class imbalance, where most individuals did not respond to the mailout. Thus, predicting individual classes and using accuracy does not seem to be an appropriate performance evaluation method. Instead, the competition will be using AUC to evaluate performance. The exact values of the "RESPONSE" column do not matter as much: only that the higher values try to capture as many of the actual customers as possible, early in the ROC curve sweep.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">mailout_test</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;../../data/Term2/capstone/arvato_data/Udacity_MAILOUT_052018_TEST.csv&#39;</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;;&#39;</span><span class="p">)</span>
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<pre>/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2785: DtypeWarning: Columns (18,19) have mixed types. Specify dtype option on import or set low_memory=False.
  interactivity=interactivity, compiler=compiler, result=result)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Shape of test set before cleaning: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">mailout_test</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="n">cleaned_test</span> <span class="o">=</span> <span class="n">data_preprocess</span><span class="p">(</span><span class="n">mailout_test</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Shape of test set after cleaning: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">cleaned_test</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
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<pre>Shape of test set before cleaning: (42833, 366)
Dropping columns with more than 65% missing values
columns dropped
Computing Correlation matrix
shape after dropping the correlated columns: (42833, 253)
filling nan vlaues with -1
values filled
creating dummy variables
Shape of data after creating dummy vairables: (42833, 300)
Imputing nan values with mode
shape after imputing the values (42833, 300)
removing outliers
Shape before normalising: (42833, 300)
Shape after normalising: (42833, 300)
Shape of test set after cleaning: (42833, 299)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">kaggle_prediction</span> <span class="o">=</span> <span class="n">best_classfier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">cleaned_test</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">kaggle_submission</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="n">mailout_test</span><span class="p">[</span><span class="s1">&#39;LNR&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;int32&#39;</span><span class="p">),</span> <span class="n">data</span><span class="o">=</span><span class="n">kaggle_prediction</span><span class="p">)</span>
<span class="n">kaggle_submission</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">{</span><span class="mi">0</span><span class="p">:</span> <span class="s2">&quot;RESPONSE&quot;</span><span class="p">},</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">kaggle_submission</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>RESPONSE</th>
    </tr>
    <tr>
      <th>LNR</th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1754</th>
      <td>0.017549</td>
    </tr>
    <tr>
      <th>1770</th>
      <td>0.030563</td>
    </tr>
    <tr>
      <th>1465</th>
      <td>0.009816</td>
    </tr>
    <tr>
      <th>1470</th>
      <td>0.009816</td>
    </tr>
    <tr>
      <th>1478</th>
      <td>0.009816</td>
    </tr>
    <tr>
      <th>1782</th>
      <td>0.009816</td>
    </tr>
    <tr>
      <th>1485</th>
      <td>0.008746</td>
    </tr>
    <tr>
      <th>1519</th>
      <td>0.012388</td>
    </tr>
    <tr>
      <th>1835</th>
      <td>0.020385</td>
    </tr>
    <tr>
      <th>1522</th>
      <td>0.009816</td>
    </tr>
  </tbody>
</table>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">kaggle_submission</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s1">&#39;customer_segmentation_kaggle_submission.csv&#39;</span><span class="p">)</span>
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