diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/2011_us_ag_exports.csv" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/2011_us_ag_exports.csv" new file mode 100644 index 0000000..16678cc --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/2011_us_ag_exports.csv" @@ -0,0 +1,51 @@ +code,state,category,total exports,beef,pork,poultry,dairy,fruits fresh,fruits proc,total fruits,veggies fresh,veggies proc,total veggies,corn,wheat,cotton +AL,Alabama,state,1390.63,34.40,10.60,481.00,4.06,8.00,17.10,25.11,5.50,8.90,14.33,34.90,70.00,317.61 +AK,Alaska,state,13.31,0.20,0.10,0.00,0.19,0.00,0.00,0.00,0.60,1.00,1.56,0.00,0.00,0.00 +AZ,Arizona,state,1463.17,71.30,17.90,0.00,105.48,19.30,41.00,60.27,147.50,239.40,386.91,7.30,48.70,423.95 +AR,Arkansas,state,3586.02,53.20,29.40,562.90,3.53,2.20,4.70,6.88,4.40,7.10,11.45,69.50,114.50,665.44 +CA, California, state,16472.88,228.70,11.10,225.40,929.95,2791.80,5944.60,8736.40,803.20,1303.50,2106.79,34.60,249.30,1064.95 +CO,Colorado,state,1851.33,261.40,66.00,14.00,71.94,5.70,12.20,17.99,45.10,73.20,118.27,183.20,400.50,0.00 +CT,Connecticut,state,259.62,1.10,0.10,6.90,9.49,4.20,8.90,13.10,4.30,6.90,11.16,0.00,0.00,0.00 +DE,Delaware,state,282.19,0.40,0.60,114.70,2.30,0.50,1.00,1.53,7.60,12.40,20.03,26.90,22.90,0.00 +FL,Florida,state,3764.09,42.60,0.90,56.90,66.31,438.20,933.10,1371.36,171.90,279.00,450.86,3.50,1.80,78.24 +GA,Georgia,state,2860.84,31.00,18.90,630.40,38.38,74.60,158.90,233.51,59.00,95.80,154.77,57.80,65.40,1154.07 +HI,Hawaii,state,401.84,4.00,0.70,1.30,1.16,17.70,37.80,55.51,9.50,15.40,24.83,0.00,0.00,0.00 +ID,Idaho,state,2078.89,119.80,0.00,2.40,294.60,6.90,14.70,21.64,121.70,197.50,319.19,24.00,568.20,0.00 +IL,Illinois,state,8709.48,53.70,394.00,14.00,45.82,4.00,8.50,12.53,15.20,24.70,39.95,2228.50,223.80,0.00 +IN,Indiana,state,5050.23,21.90,341.90,165.60,89.70,4.10,8.80,12.98,14.40,23.40,37.89,1123.20,114.00,0.00 +IA,Iowa,state,11273.76,289.80,1895.60,155.60,107.00,1.00,2.20,3.24,2.70,4.40,7.10,2529.80,3.10,0.00 +KS,Kansas,state,4589.01,659.30,179.40,6.40,65.45,1.00,2.10,3.11,3.60,5.80,9.32,457.30,1426.50,43.98 +KY,Kentucky,state,1889.15,54.80,34.20,151.30,28.27,2.10,4.50,6.60,0.00,0.00,0.00,179.10,149.30,0.00 +LA,Louisiana,state,1914.23,19.80,0.80,77.20,6.02,5.70,12.10,17.83,6.60,10.70,17.25,91.40,78.70,280.42 +ME,Maine,state,278.37,1.40,0.50,10.40,16.18,16.60,35.40,52.01,24.00,38.90,62.90,0.00,0.00,0.00 +MD,Maryland,state,692.75,5.60,3.10,127.00,24.81,4.10,8.80,12.90,7.80,12.60,20.43,54.10,55.80,0.00 +MA,Massachusetts,state,248.65,0.60,0.50,0.60,5.81,25.80,55.00,80.83,8.10,13.10,21.13,0.00,0.00,0.00 +MI,Michigan,state,3164.16,37.70,118.10,32.60,214.82,82.30,175.30,257.69,72.40,117.50,189.96,381.50,247.00,0.00 +MN,Minnesota,state,7192.33,112.30,740.40,189.20,218.05,2.50,5.40,7.91,45.90,74.50,120.37,1264.30,538.10,0.00 +MS,Mississippi,state,2170.80,12.80,30.40,370.80,5.45,5.40,11.60,17.04,10.60,17.20,27.87,110.00,102.20,494.75 +MO,Missouri,state,3933.42,137.20,277.30,196.10,34.26,4.20,9.00,13.18,6.80,11.10,17.90,428.80,161.70,345.29 +MT,Montana,state,1718.00,105.00,16.70,1.70,6.82,1.10,2.20,3.30,17.30,28.00,45.27,5.40,1198.10,0.00 +NE,Nebraska,state,7114.13,762.20,262.50,31.40,30.07,0.70,1.50,2.16,20.40,33.10,53.50,1735.90,292.30,0.00 +NV,Nevada,state,139.89,21.80,0.20,0.00,16.57,0.40,0.80,1.19,10.60,17.30,27.93,0.00,5.40,0.00 +NH,New Hampshire,state,73.06,0.60,0.20,0.80,7.46,2.60,5.40,7.98,1.70,2.80,4.50,0.00,0.00,0.00 +NJ,New Jersey,state,500.40,0.80,0.40,4.60,3.37,35.00,74.50,109.45,21.60,35.00,56.54,10.10,6.70,0.00 +NM,New Mexico,state,751.58,117.20,0.10,0.30,191.01,32.60,69.30,101.90,16.70,27.10,43.88,11.20,13.90,72.62 +NY,New York,state,1488.90,22.20,5.80,17.70,331.80,64.70,137.80,202.56,54.70,88.70,143.37,106.10,29.90,0.00 +NC,North Carolina,state,3806.05,24.80,702.80,598.40,24.90,23.80,50.70,74.47,57.40,93.10,150.45,92.20,200.30,470.86 +ND,North Dakota,state,3761.96,78.50,16.10,0.50,8.14,0.10,0.20,0.25,49.90,80.90,130.79,236.10,1664.50,0.00 +OH,Ohio,state,3979.79,36.20,199.10,129.90,134.57,8.70,18.50,27.21,20.40,33.10,53.53,535.10,207.40,0.00 +OK,Oklahoma,state,1646.41,337.60,265.30,131.10,24.35,3.00,6.30,9.24,3.40,5.50,8.90,27.50,324.80,110.54 +OR,Oregon,state,1794.57,58.80,1.40,14.20,63.66,100.70,214.40,315.04,48.20,78.30,126.50,11.70,320.30,0.00 +PA,Pennsylvania,state,1969.87,50.90,91.30,169.80,280.87,28.60,60.90,89.48,14.60,23.70,38.26,112.10,41.00,0.00 +RI,Rhode Island,state,31.59,0.10,0.10,0.20,0.52,0.90,1.90,2.83,1.20,1.90,3.02,0.00,0.00,0.00 +SC,South Carolina,state,929.93,15.20,10.90,186.50,7.62,17.10,36.40,53.45,16.30,26.40,42.66,32.10,55.30,206.10 +SD,South Dakota,state,3770.19,193.50,160.20,29.30,46.77,0.30,0.50,0.80,1.50,2.50,4.06,643.60,704.50,0.00 +TN,Tennessee,state,1535.13,51.10,17.60,82.40,21.18,2.00,4.20,6.23,9.40,15.30,24.67,88.80,100.00,363.83 +TX,Texas,state,6648.22,961.00,42.70,339.20,240.55,31.90,68.00,99.90,43.90,71.30,115.23,167.20,309.70,2308.76 +UT,Utah,state,453.39,27.90,59.00,23.10,48.60,3.90,8.40,12.34,2.50,4.10,6.60,5.30,42.80,0.00 +VT,Vermont,state,180.14,6.20,0.20,0.90,65.98,2.60,5.40,8.01,1.50,2.50,4.05,0.00,0.00,0.00 +VA,Virginia,state,1146.48,39.50,16.90,164.70,47.85,11.70,24.80,36.48,10.40,16.90,27.25,39.50,77.50,64.84 +WA,Washington,state,3894.81,59.20,0.00,35.60,154.18,555.60,1183.00,1738.57,138.70,225.10,363.79,29.50,786.30,0.00 +WV,West Virginia,state,138.89,12.00,0.30,45.40,3.90,3.70,7.90,11.54,0.00,0.00,0.00,3.50,1.60,0.00 +WI,Wisconsin,state,3090.23,107.30,38.60,34.50,633.60,42.80,91.00,133.80,56.80,92.20,148.99,460.50,96.70,0.00 +WY,Wyoming,state,349.69,75.10,33.20,0.10,2.89,0.10,0.10,0.17,3.90,6.30,10.23,9.00,20.70,0.00 diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/6.- Sesi\303\263n S\303\241bado.ipynb" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/6.- Sesi\303\263n S\303\241bado.ipynb" deleted file mode 100644 index e69de29..0000000 diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Bokeh.ipynb" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Bokeh.ipynb" new file mode 100644 index 0000000..30992f0 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Bokeh.ipynb" @@ -0,0 +1,656 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Bokeh\n", + "\n", + "Bokeh es similar a Plotly en cuanto a que depende de una librería Javascript externa. \n", + "\n", + "Facilita la creación de Visualizaciones Interactivas.\n", + "\n", + "http://bokeh.pydata.org/\n", + "\n", + "La guia del usuario es muy completa y recomendable. \n", + "\n", + "\n", + "### Integración con Notebooks o Generación de HTML\n", + "\n", + "Si se utiliza output_file o output_notebook, se puede exportar la visualización en el Notebook o bien a un archivo independiente.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "
\n", + "
\n", + "
\n", + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

<Bokeh Notebook handle for In[3]>

" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from bokeh.plotting import figure, output_file, output_notebook, show\n", + "\n", + "# prepare some data\n", + "x = [0.1, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0]\n", + "y0 = [i**2 for i in x]\n", + "y1 = [10**i for i in x]\n", + "y2 = [10**(i**2) for i in x]\n", + "\n", + "# output to static HTML file\n", + "#output_file(\"log_lines.html\")\n", + "output_notebook()\n", + "\n", + "# create a new plot\n", + "p = figure(\n", + " tools=\"pan,box_zoom,reset,save\",\n", + " y_axis_type=\"log\", y_range=[0.001, 10**11], title=\"log axis example\",\n", + " x_axis_label='sections', y_axis_label='particles'\n", + ")\n", + "\n", + "# add some renderers\n", + "p.line(x, x, legend=\"y=x\")\n", + "p.circle(x, x, legend=\"y=x\", fill_color=\"white\", size=8)\n", + "p.line(x, y0, legend=\"y=x^2\", line_width=3)\n", + "p.line(x, y1, legend=\"y=10^x\", line_color=\"red\")\n", + "p.circle(x, y1, legend=\"y=10^x\", fill_color=\"red\", line_color=\"red\", size=6)\n", + "p.line(x, y2, legend=\"y=10^x^2\", line_color=\"orange\", line_dash=\"4 4\")\n", + "\n", + "# show the results\n", + "show(p)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Descarga de datos de muestra\n", + "\n", + "Bokeh tiene un set de datos de muestra que pueden descargarse con el siguiente comando:\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Creating /Users/tozanni/.bokeh directory\n", + "Creating /Users/tozanni/.bokeh/data directory\n", + "Using data directory: /Users/tozanni/.bokeh/data\n", + "Downloading: CGM.csv (1589982 bytes)\n", + " 1589982 [100.00%]\n", + "Downloading: US_Counties.zip (3182088 bytes)\n", + " 3182088 [100.00%]\n", + "Unpacking: US_Counties.csv\n", + "Downloading: us_cities.json (713565 bytes)\n", + " 713565 [100.00%]\n", + "Downloading: unemployment09.csv (253301 bytes)\n", + " 253301 [100.00%]\n", + "Downloading: AAPL.csv (166698 bytes)\n", + " 166698 [100.00%]\n", + "Downloading: FB.csv (9706 bytes)\n", + " 9706 [100.00%]\n", + "Downloading: GOOG.csv (113894 bytes)\n", + " 113894 [100.00%]\n", + "Downloading: IBM.csv (165625 bytes)\n", + " 165625 [100.00%]\n", + "Downloading: MSFT.csv (161614 bytes)\n", + " 161614 [100.00%]\n", + "Downloading: WPP2012_SA_DB03_POPULATION_QUINQUENNIAL.zip (5148539 bytes)\n", + " 5148539 [100.00%]\n", + "Unpacking: WPP2012_SA_DB03_POPULATION_QUINQUENNIAL.csv\n", + "Downloading: gapminder_fertility.csv (64346 bytes)\n", + " 64346 [100.00%]\n", + "Downloading: gapminder_population.csv (94509 bytes)\n", + " 94509 [100.00%]\n", + "Downloading: gapminder_life_expectancy.csv (73243 bytes)\n", + " 73243 [100.00%]\n", + "Downloading: gapminder_regions.csv (7781 bytes)\n", + " 7781 [100.00%]\n", + "Downloading: world_cities.zip (646858 bytes)\n", + " 646858 [100.00%]\n", + "Unpacking: world_cities.csv\n", + "Downloading: airports.json (6373 bytes)\n", + " 6373 [100.00%]\n", + "Downloading: movies.db.zip (5067833 bytes)\n", + " 5067833 [100.00%]\n", + "Unpacking: movies.db\n" + ] + } + ], + "source": [ + "import bokeh.sampledata\n", + "bokeh.sampledata.download()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generación de charts de alto nivel e integración con Pandas\n", + "\n", + "http://bokeh.pydata.org/en/latest/docs/user_guide/charts.html\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(global) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " if (typeof (window._bokeh_onload_callbacks) === \"undefined\") {\n", + " window._bokeh_onload_callbacks = [];\n", + " }\n", + "\n", + " function run_callbacks() {\n", + " window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", + " delete window._bokeh_onload_callbacks\n", + " console.info(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(js_urls, callback) {\n", + " window._bokeh_onload_callbacks.push(callback);\n", + " if (window._bokeh_is_loading > 0) {\n", + " console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " window._bokeh_is_loading = js_urls.length;\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var s = document.createElement('script');\n", + " s.src = url;\n", + " s.async = false;\n", + " s.onreadystatechange = s.onload = function() {\n", + " window._bokeh_is_loading--;\n", + " if (window._bokeh_is_loading === 0) {\n", + " console.log(\"Bokeh: all BokehJS libraries loaded\");\n", + " run_callbacks()\n", + " }\n", + " };\n", + " s.onerror = function() {\n", + " console.warn(\"failed to load library \" + url);\n", + " };\n", + " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", + " }\n", + " };\n", + "\n", + " var js_urls = ['https://cdn.pydata.org/bokeh/release/bokeh-0.12.0.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.0.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-compiler-0.12.0.min.js'];\n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " \n", + " function(Bokeh) {\n", + " Bokeh.$(\"#9c5581f9-fffa-4bae-b07f-951d63982eda\").text(\"BokehJS successfully loaded\");\n", + " },\n", + " function(Bokeh) {\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.0.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.0.min.css\");\n", + " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.0.min.css\");\n", + " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.0.min.css\");\n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i](window.Bokeh);\n", + " }\n", + " }\n", + "\n", + " if (window._bokeh_is_loading === 0) {\n", + " console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(js_urls, function() {\n", + " console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(this));" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "
\n", + "
\n", + "
\n", + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

<Bokeh Notebook handle for In[17]>

" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from bokeh.charts import Histogram, output_file, show\n", + "from bokeh.sampledata.autompg import autompg as df\n", + "\n", + "p = Histogram(df, values='hp', color='cyl',\n", + " title=\"HP Distribution (color grouped by CYL)\",\n", + " legend='top_right')\n", + "\n", + "output_notebook()\n", + "#output_file(\"histogram_color.html\")\n", + "\n", + "show(p)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Ejecutando aplicaciones interactivas\n", + "\n", + "El siguiente ejemplo hay que copiarlo y pegarlo a myapp.py\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# myapp.py\n", + "\n", + "import numpy as np\n", + "\n", + "from bokeh.layouts import column\n", + "from bokeh.models import Button\n", + "from bokeh.palettes import RdYlBu3\n", + "from bokeh.plotting import figure, curdoc\n", + "\n", + "# create a plot and style its properties\n", + "p = figure(x_range=(0, 100), y_range=(0, 100), toolbar_location=None)\n", + "p.border_fill_color = 'black'\n", + "p.background_fill_color = 'black'\n", + "p.outline_line_color = None\n", + "p.grid.grid_line_color = None\n", + "\n", + "# add a text renderer to out plot (no data yet)\n", + "r = p.text(x=[], y=[], text=[], text_color=[], text_font_size=\"20pt\",\n", + " text_baseline=\"middle\", text_align=\"center\")\n", + "\n", + "i = 0\n", + "\n", + "ds = r.data_source\n", + "\n", + "# create a callback that will add a number in a random location\n", + "def callback():\n", + " global i\n", + " ds.data['x'].append(np.random.random()*70 + 15)\n", + " ds.data['y'].append(np.random.random()*70 + 15)\n", + " ds.data['text_color'].append(RdYlBu3[i%3])\n", + " ds.data['text'].append(str(i))\n", + " ds.trigger('data', ds.data, ds.data)\n", + " i = i + 1\n", + "\n", + "# add a button widget and configure with the call back\n", + "button = Button(label=\"Press Me\")\n", + "button.on_click(callback)\n", + "\n", + "# put the button and plot in a layout and add to the document\n", + "curdoc().add_root(column(button, p))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Posteriormente correrlo con:\n", + "\n", + "bokeh serve --show myapp.py\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Actualizando los charts con un thread de Python\n", + "\n", + "Copiar el siguiente codigo en un programa threads.py y ejecutar con bokeh serve --show threads.py\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from functools import partial\n", + "import time\n", + "\n", + "from concurrent.futures import ThreadPoolExecutor\n", + "from tornado import gen\n", + "\n", + "from bokeh.document import without_document_lock\n", + "from bokeh.models import ColumnDataSource\n", + "from bokeh.plotting import curdoc, figure\n", + "\n", + "source = ColumnDataSource(data=dict(x=[0], y=[0], color=[\"blue\"]))\n", + "i = 0\n", + "doc = curdoc()\n", + "executor = ThreadPoolExecutor(max_workers=2)\n", + "\n", + "def blocking_task(i):\n", + " time.sleep(1)\n", + " return i\n", + "\n", + "# the unlocked callback uses this locked callback to safely update\n", + "@gen.coroutine\n", + "def locked_update(i):\n", + " source.stream(dict(x=[source.data['x'][-1]+1], y=[i], color=[\"blue\"]))\n", + "\n", + "# this unclocked callback will not prevent other session callbacks from\n", + "# executing while it is in flight\n", + "@gen.coroutine\n", + "@without_document_lock\n", + "def unlocked_task():\n", + " global i\n", + " i += 1\n", + " res = yield executor.submit(blocking_task, i)\n", + " doc.add_next_tick_callback(partial(locked_update, i=res))\n", + "\n", + "@gen.coroutine\n", + "def update():\n", + " source.stream(dict(x=[source.data['x'][-1]+1], y=[i], color=[\"red\"]))\n", + "\n", + "p = figure(x_range=[0, 100], y_range=[0,20])\n", + "l = p.circle(x='x', y='y', color='color', source=source)\n", + "\n", + "doc.add_periodic_callback(unlocked_task, 1000)\n", + "doc.add_periodic_callback(update, 200)\n", + "doc.add_root(p)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ejemplos de aplicaciones completas\n", + "\n", + "Lo mas recomendable es clonar el repo y correr algunas aplicaciones.\n", + "\n", + "git clone \"https://github.com/bokeh/bokeh\"\n", + "\n", + "Luego, desde el subdirectorio examples/apps, ejecutar:\n", + "\n", + "bokeh serve --show gapminder/" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Ejercicios de Matplotlib.ipynb" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Ejercicios de Matplotlib.ipynb" new file mode 100644 index 0000000..4ec0e43 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Ejercicios de Matplotlib.ipynb" @@ -0,0 +1,2029 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualizando con Pandas y Matplotlib\n", + "\n", + "http://pandas.pydata.org/pandas-docs/stable/visualization.html\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "u'0.18.0'" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "pd.__version__\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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account numbernameskucategoryquantityunit priceext pricedate
0296809Carroll PLCQN-82852Belt1344.48578.242014-09-27 07:13:03
198022Heidenreich-BoscoMJ-21460Shoes1953.621018.782014-07-29 02:10:44
2563905Kerluke, Reilly and BechtelarAS-93055Shirt1224.16289.922014-03-01 10:51:24
393356Waters-WalkerAS-93055Shirt582.68413.402013-11-17 20:41:11
4659366Waelchi-FaheyAS-93055Shirt1899.641793.522014-01-03 08:14:27
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" + ], + "text/plain": [ + " account number name sku category quantity \\\n", + "0 296809 Carroll PLC QN-82852 Belt 13 \n", + "1 98022 Heidenreich-Bosco MJ-21460 Shoes 19 \n", + "2 563905 Kerluke, Reilly and Bechtelar AS-93055 Shirt 12 \n", + "3 93356 Waters-Walker AS-93055 Shirt 5 \n", + "4 659366 Waelchi-Fahey AS-93055 Shirt 18 \n", + "\n", + " unit price ext price date \n", + "0 44.48 578.24 2014-09-27 07:13:03 \n", + "1 53.62 1018.78 2014-07-29 02:10:44 \n", + "2 24.16 289.92 2014-03-01 10:51:24 \n", + "3 82.68 413.40 2013-11-17 20:41:11 \n", + "4 99.64 1793.52 2014-01-03 08:14:27 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%matplotlib inline\n", + "sales = pd.read_csv(\"sample-salesv2.csv\",parse_dates=['date'])\n", + "sales.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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account numberquantityunit priceext price
count1000.0000001000.0000001000.0000001000.00000
mean535208.89700010.32800056.179630579.84390
std277589.7460145.68759725.331939435.30381
min93356.0000001.00000010.06000010.38000
25%299771.0000005.75000035.995000232.60500
50%563905.00000010.00000056.765000471.72000
75%750461.00000015.00000076.802500878.13750
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" + ], + "text/plain": [ + " account number quantity unit price ext price\n", + "count 1000.000000 1000.000000 1000.000000 1000.00000\n", + "mean 535208.897000 10.328000 56.179630 579.84390\n", + "std 277589.746014 5.687597 25.331939 435.30381\n", + "min 93356.000000 1.000000 10.060000 10.38000\n", + "25% 299771.000000 5.750000 35.995000 232.60500\n", + "50% 563905.000000 10.000000 56.765000 471.72000\n", + "75% 750461.000000 15.000000 76.802500 878.13750\n", + "max 995267.000000 20.000000 99.970000 1994.80000" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sales.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lo que podemos ver en la descripción:\n", + "- Tenemos 1000 registros. \n", + "- Los agregados sobre account_number no significan nada.\n", + "- quantity: Tenemos un promedio de 10.32 items por transaccion y stdev de 5.68\n", + "- El costo promedio de cada transaccion es de 579.84\n", + "\n", + "Para ver columnas individuales:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "count 1000.000000\n", + "mean 56.179630\n", + "std 25.331939\n", + "min 10.060000\n", + "25% 35.995000\n", + "50% 56.765000\n", + "75% 76.802500\n", + "max 99.970000\n", + "Name: unit price, dtype: float64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sales['unit price'].describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para ver los tipos de datos de cada columna, usamos dtypes.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "account number int64\n", + "name object\n", + "sku object\n", + "category object\n", + "quantity int64\n", + "unit price float64\n", + "ext price float64\n", + "date datetime64[ns]\n", + "dtype: object" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sales.dtypes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Graficando datos\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Crear un histograma de una variable" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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nameext pricedate
0Carroll PLC578.242014-09-27 07:13:03
1Heidenreich-Bosco1018.782014-07-29 02:10:44
2Kerluke, Reilly and Bechtelar289.922014-03-01 10:51:24
3Waters-Walker413.402013-11-17 20:41:11
4Waelchi-Fahey1793.522014-01-03 08:14:27
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" + ], + "text/plain": [ + " name ext price date\n", + "0 Carroll PLC 578.24 2014-09-27 07:13:03\n", + "1 Heidenreich-Bosco 1018.78 2014-07-29 02:10:44\n", + "2 Kerluke, Reilly and Bechtelar 289.92 2014-03-01 10:51:24\n", + "3 Waters-Walker 413.40 2013-11-17 20:41:11\n", + "4 Waelchi-Fahey 1793.52 2014-01-03 08:14:27" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customers = sales[['name','ext price','date']]\n", + "customers.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para ver la distribucion de compras por cliente." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "name\n", + "Berge LLC 52\n", + "Carroll PLC 57\n", + "Cole-Eichmann 51\n", + "Davis, Kshlerin and Reilly 41\n", + "Ernser, Cruickshank and Lind 47\n", + "Gorczany-Hahn 42\n", + "Hamill-Hackett 44\n", + "Hegmann and Sons 58\n", + "Heidenreich-Bosco 40\n", + "Huel-Haag 43\n", + "Kerluke, Reilly and Bechtelar 52\n", + "Kihn, McClure and Denesik 58\n", + "Kilback-Gerlach 45\n", + "Koelpin PLC 53\n", + "Kunze Inc 54\n", + "Kuphal, Zieme and Kub 52\n", + "Senger, Upton and Breitenberg 59\n", + "Volkman, Goyette and Lemke 48\n", + "Waelchi-Fahey 54\n", + "Waters-Walker 50\n", + "dtype: int64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer_group = customers.groupby('name')\n", + "# customer_group.describe() \n", + "#customer_group.mean()\n", + "customer_group.size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora, determinar cuanto compró cada cliente, utilizando la función sum y sort para mostrar los mayores compradores.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ext price
name
Berge LLC30064.87
Carroll PLC35934.31
Cole-Eichmann30435.42
Davis, Kshlerin and Reilly19054.76
Ernser, Cruickshank and Lind28089.02
Gorczany-Hahn22207.90
Hamill-Hackett23433.78
Hegmann and Sons35213.72
Heidenreich-Bosco25428.29
Huel-Haag21087.88
Kerluke, Reilly and Bechtelar27389.43
Kihn, McClure and Denesik38935.29
Kilback-Gerlach26987.20
Koelpin PLC26811.66
Kunze Inc34406.54
Kuphal, Zieme and Kub27031.86
Senger, Upton and Breitenberg29577.46
Volkman, Goyette and Lemke32006.87
Waelchi-Fahey28968.68
Waters-Walker36778.96
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" + ], + "text/plain": [ + " ext price\n", + "name \n", + "Berge LLC 30064.87\n", + "Carroll PLC 35934.31\n", + "Cole-Eichmann 30435.42\n", + "Davis, Kshlerin and Reilly 19054.76\n", + "Ernser, Cruickshank and Lind 28089.02\n", + "Gorczany-Hahn 22207.90\n", + "Hamill-Hackett 23433.78\n", + "Hegmann and Sons 35213.72\n", + "Heidenreich-Bosco 25428.29\n", + "Huel-Haag 21087.88\n", + "Kerluke, Reilly and Bechtelar 27389.43\n", + "Kihn, McClure and Denesik 38935.29\n", + "Kilback-Gerlach 26987.20\n", + "Koelpin PLC 26811.66\n", + "Kunze Inc 34406.54\n", + "Kuphal, Zieme and Kub 27031.86\n", + "Senger, Upton and Breitenberg 29577.46\n", + "Volkman, Goyette and Lemke 32006.87\n", + "Waelchi-Fahey 28968.68\n", + "Waters-Walker 36778.96" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sales_totals = customer_group.sum()\n", + "sales_totals" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ya que tenemos un dataframe resumido, producir una gráfica es muy simple." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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TVQlImirpSkl3SLpd0gdy+zGS5ku6OT9eXehzlKQ5ku6UtGehfTtJt0n6raQTCu2rSjon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\nCPP/9cUf0obwbZsAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "my_plot = sales_totals.plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Sin embargo, esta grafica es limitada. Vamos a intentar las siguientes mejoras:\n", + " - ordenar de forma descendiente\n", + " - eliminar la leyenda del eje x\n", + " - agregar un titulo\n", + " - agregar titulos de los ejes" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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NY7wy2skUvwPMKSqPvKbRYnfg9vz+XGDv7Fm1FrAOcJ3t+cDjkjbPi+r7AD8r9Nk3v98D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\nsbI2p8p2Y59Ok5+ipj9ZbSEz0eQEkqmE1FC4Q/panNgLOX1IFXkHhqR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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "my_plot = sales_totals.sort_values(by='ext price',ascending=False).plot(kind='bar',legend=None,title='Total Sales')\n", + "my_plot.set_xlabel(\"Customers\")\n", + "my_plot.set_ylabel(\"Sales ($)\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Resumen general de las categorias, usamos pie, pero podemos simplemente cambiar a \"bar\"" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([], dtype=object)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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wrs77647e9lDVQap6euLz7lPVg5tYZhGC/Jv+dGJwxvzDYHZmOVAVVLjM6SSmCTKi0FS1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\n8kSkg4hMp/59Bpw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namecategoryext pricedate
0Carroll PLCBelt578.242014-09-27 07:13:03
1Heidenreich-BoscoShoes1018.782014-07-29 02:10:44
2Kerluke, Reilly and BechtelarShirt289.922014-03-01 10:51:24
3Waters-WalkerShirt413.402013-11-17 20:41:11
4Waelchi-FaheyShirt1793.522014-01-03 08:14:27
\n", + "
" + ], + "text/plain": [ + " name category ext price date\n", + "0 Carroll PLC Belt 578.24 2014-09-27 07:13:03\n", + "1 Heidenreich-Bosco Shoes 1018.78 2014-07-29 02:10:44\n", + "2 Kerluke, Reilly and Bechtelar Shirt 289.92 2014-03-01 10:51:24\n", + "3 Waters-Walker Shirt 413.40 2013-11-17 20:41:11\n", + "4 Waelchi-Fahey Shirt 1793.52 2014-01-03 08:14:27" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customers = sales[['name','category','ext price','date']]\n", + "customers.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Obtener el histograma de una sola categoria.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[]], dtype=object)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cat_group = customers.groupby(['category','name']).sum()\n", + "cat_group.reset_index(inplace=True)\n", + "cat_group\n", + "belts = cat_group[cat_group['category'] == \"Belt\"]\n", + "belts.hist()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ext price
namecategory
Berge LLCBelt6033.53
Shirt9670.24
Shoes14361.10
Carroll PLCBelt9359.26
Shirt13717.61
Shoes12857.44
Cole-EichmannBelt8112.70
Shirt14528.01
Shoes7794.71
Davis, Kshlerin and ReillyBelt1604.13
Shirt7533.03
Shoes9917.60
Ernser, Cruickshank and LindBelt5894.38
Shirt16944.19
Shoes5250.45
Gorczany-HahnBelt3642.48
Shirt12576.83
Shoes5988.59
Hamill-HackettBelt1609.74
Shirt8880.04
Shoes12944.00
Hegmann and SonsBelt4909.38
Shirt16774.47
Shoes13529.87
Heidenreich-BoscoBelt6262.94
Shirt5965.25
Shoes13200.10
Huel-HaagBelt2219.51
Shirt11944.01
Shoes6924.36
Kerluke, Reilly and BechtelarBelt4102.11
Shirt12958.23
Shoes10329.09
Kihn, McClure and DenesikBelt10116.90
Shirt18956.35
Shoes9862.04
Kilback-GerlachBelt2863.40
Shirt9904.85
Shoes14218.95
Koelpin PLCBelt5327.96
Shirt7908.28
Shoes13575.42
Kunze IncBelt4264.59
Shirt15638.87
Shoes14503.08
Kuphal, Zieme and KubBelt2009.69
Shirt12101.14
Shoes12921.03
Senger, Upton and BreitenbergBelt9509.88
Shirt7659.70
Shoes12407.88
Volkman, Goyette and LemkeBelt4429.01
Shirt12791.27
Shoes14786.59
Waelchi-FaheyBelt8285.72
Shirt11689.05
Shoes8993.91
Waters-WalkerBelt5957.24
Shirt18633.71
Shoes12188.01
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" + ], + "text/plain": [ + " ext price\n", + "name category \n", + "Berge LLC Belt 6033.53\n", + " Shirt 9670.24\n", + " Shoes 14361.10\n", + "Carroll PLC Belt 9359.26\n", + " Shirt 13717.61\n", + " Shoes 12857.44\n", + "Cole-Eichmann Belt 8112.70\n", + " Shirt 14528.01\n", + " Shoes 7794.71\n", + "Davis, Kshlerin and Reilly Belt 1604.13\n", + " Shirt 7533.03\n", + " Shoes 9917.60\n", + "Ernser, Cruickshank and Lind Belt 5894.38\n", + " Shirt 16944.19\n", + " Shoes 5250.45\n", + "Gorczany-Hahn Belt 3642.48\n", + " Shirt 12576.83\n", + " Shoes 5988.59\n", + "Hamill-Hackett Belt 1609.74\n", + " Shirt 8880.04\n", + " Shoes 12944.00\n", + "Hegmann and Sons Belt 4909.38\n", + " Shirt 16774.47\n", + " Shoes 13529.87\n", + "Heidenreich-Bosco Belt 6262.94\n", + " Shirt 5965.25\n", + " Shoes 13200.10\n", + "Huel-Haag Belt 2219.51\n", + " Shirt 11944.01\n", + " Shoes 6924.36\n", + "Kerluke, Reilly and Bechtelar Belt 4102.11\n", + " Shirt 12958.23\n", + " Shoes 10329.09\n", + "Kihn, McClure and Denesik Belt 10116.90\n", + " Shirt 18956.35\n", + " Shoes 9862.04\n", + "Kilback-Gerlach Belt 2863.40\n", + " Shirt 9904.85\n", + " Shoes 14218.95\n", + "Koelpin PLC Belt 5327.96\n", + " Shirt 7908.28\n", + " Shoes 13575.42\n", + "Kunze Inc Belt 4264.59\n", + " Shirt 15638.87\n", + " Shoes 14503.08\n", + "Kuphal, Zieme and Kub Belt 2009.69\n", + " Shirt 12101.14\n", + " Shoes 12921.03\n", + "Senger, Upton and Breitenberg Belt 9509.88\n", + " Shirt 7659.70\n", + " Shoes 12407.88\n", + "Volkman, Goyette and Lemke Belt 4429.01\n", + " Shirt 12791.27\n", + " Shoes 14786.59\n", + "Waelchi-Fahey Belt 8285.72\n", + " Shirt 11689.05\n", + " Shoes 8993.91\n", + "Waters-Walker Belt 5957.24\n", + " Shirt 18633.71\n", + " Shoes 12188.01" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "category_group = customers.groupby(['name','category']).sum()\n", + "category_group" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora, es necesario \"desapilar\" con \"unstack\" para poder crear una grafica \"apilada\".\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ext price
categoryBeltShirtShoes
name
Berge LLC6033.539670.2414361.10
Carroll PLC9359.2613717.6112857.44
Cole-Eichmann8112.7014528.017794.71
Davis, Kshlerin and Reilly1604.137533.039917.60
Ernser, Cruickshank and Lind5894.3816944.195250.45
\n", + "
" + ], + "text/plain": [ + " ext price \n", + "category Belt Shirt Shoes\n", + "name \n", + "Berge LLC 6033.53 9670.24 14361.10\n", + "Carroll PLC 9359.26 13717.61 12857.44\n", + "Cole-Eichmann 8112.70 14528.01 7794.71\n", + "Davis, Kshlerin and Reilly 1604.13 7533.03 9917.60\n", + "Ernser, Cruickshank and Lind 5894.38 16944.19 5250.45" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "category_group.unstack().head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos a personalizar labels, leyendas y ubicacion de la leyenda." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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IOAyYWPBxmZmZmW2UWvrcvCsijgBeiIizgH2AKcUelpmZmdnGqSW4+Wv6vULS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\noVDoK0pyUygUCoVCoa/4f6MiVY2H1Jv3AAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "my_plot = category_group.unstack().plot(kind='bar',stacked=True,title='Ventas por cliente',figsize=(9, 7))\n", + "my_plot.set_xlabel(\"Clientes\")\n", + "my_plot.set_ylabel(\"Ventas\")\n", + "my_plot.legend([\"Belts\",\"Shirts\",\"Shoes\"], loc=9,ncol=4)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos a generar una agrupacion por fecha para analizar evolucion de las ventas en el tiempo, veremos la forma de hacerlo por categoria tambien." + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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m7mNOnz4dLVu2xCWXXIKCggIsXboU11xzDQBJ+Rk2bBgAoGXLllH7LV26FEOG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\nLF8EExhXENH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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "date_group = customers.groupby(['date','category']).sum()\n", + "date_group.reset_index()\n", + "date_group.unstack().plot(title='Evolucion de ventas por categoria',figsize=(10, 10))\n", + "#date_group.unstack().plot(subplots=True,title='Evolucion de ventas por categoria',figsize=(10, 10))\n", + "#date_group.unstack().hist(figsize=(10,10))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora, si queremos hacer una visualizacion de porcentajes, es decir, comparar las proporciones de venta de cada cliente, es necesario crear un nuevo dataframe agrupando por cliente y calculando la suma." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ext price
name
Berge LLC30064.87
Carroll PLC35934.31
Cole-Eichmann30435.42
Davis, Kshlerin and Reilly19054.76
Ernser, Cruickshank and Lind28089.02
\n", + "
" + ], + "text/plain": [ + " ext price\n", + "name \n", + "Berge LLC 30064.87\n", + "Carroll PLC 35934.31\n", + "Cole-Eichmann 30435.42\n", + "Davis, Kshlerin and Reilly 19054.76\n", + "Ernser, Cruickshank and Lind 28089.02" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Por renglon\n", + "customer_total = customers.groupby(['name']).sum()\n", + "customer_total.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora, vamos a generar el la suma agregada por cliente y categoria, luego, vamos a dividir el resultante por el total del cliente, calculado en el dataframe customer_total y uniendo con level por nombre del cliente (level='name')" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ext price
namecategory
Berge LLCBelt0.200684
Shirt0.321646
Shoes0.477670
Carroll PLCBelt0.260455
Shirt0.381741
\n", + "
" + ], + "text/plain": [ + " ext price\n", + "name category \n", + "Berge LLC Belt 0.200684\n", + " Shirt 0.321646\n", + " Shoes 0.477670\n", + "Carroll PLC Belt 0.260455\n", + " Shirt 0.381741" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "customer_pct = customers.groupby(['name','category']).sum().div(customer_total,level='name')\n", + "customer_pct.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finalmente, vamos a generar el gráfico, primero invocamos unstack para convertir los índices de renglón en índices de columna. Luego graficamos, es necesario ajustar el límite con set_ylim." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 1.0)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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VVdpvv/3Simdm6tixY3y7sLCwUtkFBQXVvnfp0qXq2rXrLvtXrVqlzZs3q0+f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\nd3YUqjNXY4ci7IWSjrP9B3Vj3PYMomH/fe5ISn8QSUxNMPLZB/ihpJ0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ext priceTotalBeltRShirtRShoeR
categoryBeltShirtShoes
name
Berge LLC6033.539670.2414361.1030064.870.2006840.3216460.477670
Carroll PLC9359.2613717.6112857.4435934.310.2604550.3817410.357804
Cole-Eichmann8112.7014528.017794.7130435.420.2665550.4773390.256107
Davis, Kshlerin and Reilly1604.137533.039917.6019054.760.0841850.3953360.520479
Ernser, Cruickshank and Lind5894.3816944.195250.4528089.020.2098460.6032320.186922
Gorczany-Hahn3642.4812576.835988.5922207.900.1640170.5663220.269660
Hamill-Hackett1609.748880.0412944.0023433.780.0686930.3789420.552365
Hegmann and Sons4909.3816774.4713529.8735213.720.1394170.4763620.384222
Heidenreich-Bosco6262.945965.2513200.1025428.290.2462980.2345910.519111
Huel-Haag2219.5111944.016924.3621087.880.1052510.5663920.328357
Kerluke, Reilly and Bechtelar4102.1112958.2310329.0927389.430.1497700.4731110.377120
Kihn, McClure and Denesik10116.9018956.359862.0438935.290.2598390.4868680.253293
Kilback-Gerlach2863.409904.8514218.9526987.200.1061020.3670200.526878
Koelpin PLC5327.967908.2813575.4226811.660.1987180.2949570.506325
Kunze Inc4264.5915638.8714503.0834406.540.1239470.4545320.421521
Kuphal, Zieme and Kub2009.6912101.1412921.0327031.860.0743450.4476620.477993
Senger, Upton and Breitenberg9509.887659.7012407.8829577.460.3215250.2589710.419505
Volkman, Goyette and Lemke4429.0112791.2714786.5932006.870.1383770.3996410.461982
Waelchi-Fahey8285.7211689.058993.9128968.680.2860230.4035060.310470
Waters-Walker5957.2418633.7112188.0136778.960.1619740.5066400.331385
\n", + "
" + ], + "text/plain": [ + " ext price Total \\\n", + "category Belt Shirt Shoes \n", + "name \n", + "Berge LLC 6033.53 9670.24 14361.10 30064.87 \n", + "Carroll PLC 9359.26 13717.61 12857.44 35934.31 \n", + "Cole-Eichmann 8112.70 14528.01 7794.71 30435.42 \n", + "Davis, Kshlerin and Reilly 1604.13 7533.03 9917.60 19054.76 \n", + "Ernser, Cruickshank and Lind 5894.38 16944.19 5250.45 28089.02 \n", + "Gorczany-Hahn 3642.48 12576.83 5988.59 22207.90 \n", + "Hamill-Hackett 1609.74 8880.04 12944.00 23433.78 \n", + "Hegmann and Sons 4909.38 16774.47 13529.87 35213.72 \n", + "Heidenreich-Bosco 6262.94 5965.25 13200.10 25428.29 \n", + "Huel-Haag 2219.51 11944.01 6924.36 21087.88 \n", + "Kerluke, Reilly and Bechtelar 4102.11 12958.23 10329.09 27389.43 \n", + "Kihn, McClure and Denesik 10116.90 18956.35 9862.04 38935.29 \n", + "Kilback-Gerlach 2863.40 9904.85 14218.95 26987.20 \n", + "Koelpin PLC 5327.96 7908.28 13575.42 26811.66 \n", + "Kunze Inc 4264.59 15638.87 14503.08 34406.54 \n", + "Kuphal, Zieme and Kub 2009.69 12101.14 12921.03 27031.86 \n", + "Senger, Upton and Breitenberg 9509.88 7659.70 12407.88 29577.46 \n", + "Volkman, Goyette and Lemke 4429.01 12791.27 14786.59 32006.87 \n", + "Waelchi-Fahey 8285.72 11689.05 8993.91 28968.68 \n", + "Waters-Walker 5957.24 18633.71 12188.01 36778.96 \n", + "\n", + " BeltR ShirtR ShoeR \n", + "category \n", + "name \n", + "Berge LLC 0.200684 0.321646 0.477670 \n", + "Carroll PLC 0.260455 0.381741 0.357804 \n", + "Cole-Eichmann 0.266555 0.477339 0.256107 \n", + "Davis, Kshlerin and Reilly 0.084185 0.395336 0.520479 \n", + "Ernser, Cruickshank and Lind 0.209846 0.603232 0.186922 \n", + "Gorczany-Hahn 0.164017 0.566322 0.269660 \n", + "Hamill-Hackett 0.068693 0.378942 0.552365 \n", + "Hegmann and Sons 0.139417 0.476362 0.384222 \n", + "Heidenreich-Bosco 0.246298 0.234591 0.519111 \n", + "Huel-Haag 0.105251 0.566392 0.328357 \n", + "Kerluke, Reilly and Bechtelar 0.149770 0.473111 0.377120 \n", + "Kihn, McClure and Denesik 0.259839 0.486868 0.253293 \n", + "Kilback-Gerlach 0.106102 0.367020 0.526878 \n", + "Koelpin PLC 0.198718 0.294957 0.506325 \n", + "Kunze Inc 0.123947 0.454532 0.421521 \n", + "Kuphal, Zieme and Kub 0.074345 0.447662 0.477993 \n", + "Senger, Upton and Breitenberg 0.321525 0.258971 0.419505 \n", + "Volkman, Goyette and Lemke 0.138377 0.399641 0.461982 \n", + "Waelchi-Fahey 0.286023 0.403506 0.310470 \n", + "Waters-Walker 0.161974 0.506640 0.331385 " + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Por columna\n", + "cc = customers.groupby(['name','category']).sum().unstack()\n", + "cc['Total'] = cc['ext price']['Belt'] + cc['ext price']['Shirt'] + cc['ext price']['Shoes']\n", + "cc['BeltR'] = cc['ext price']['Belt'] / cc['Total']\n", + "cc['ShirtR'] = cc['ext price']['Shirt'] / cc['Total']\n", + "cc['ShoeR'] = cc['ext price']['Shoes'] / cc['Total']\n", + "cc\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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7xhSWkLQkm29qBQAAUkOCAQAAoiPBAAAA0ZFgAACA6Mqikyc9cwGg5eIav3kq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\nF9iSSJAutF11zLrXazVfv5NHG4Z/Y8S5FnhemYLrCAReVaM5XdKvmn1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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cc[['BeltR','ShirtR','ShoeR']].plot(kind='bar',stacked=True, figsize=(9, 7))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ¿Qué sigue?\n", + "\n", + "Para mejorar la presentación de los charts de Matplotlib y facilitar algunos procesos, se tiene Seaborn:\n", + " \n", + "https://stanford.edu/~mwaskom/software/seaborn/\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Plotly Examples.ipynb" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Plotly Examples.ipynb" new file mode 100644 index 0000000..a2ae710 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Plotly Examples.ipynb" @@ -0,0 +1,579 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot.ly\n", + "\n", + "Plotly es una libreria y conjunto de herramientas basada en Javascript que tiene una capa de compatibilidad con Python y Jupyter.\n", + "\n", + "\n", + "La versión de Plotly Offline es Open Source y puede utilizarse libremente en el ambiente de Jupyter Notebook. \n", + "\n", + "https://plot.ly/python/offline/\n", + "\n", + "Una ventaja adicional que ofrece es que una vez generadas las gráficas y visualizaciones, estas pueden ser exportadas para ser mejoradas y compartidas a través de los servicios online de Plotly. \n", + "\n", + "Se pueden editar y refinar con temas y otros ajustes visuales en el Webapp de Plotly, y también se pueden crear Dashboards utilizando [Dashboards.ly](https://dashboards.ly/create)\n", + "\n", + "Para instalar:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "! pip install plotly --upgrade" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Revisar la instalación:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.12.4\n" + ] + } + ], + "source": [ + "from plotly import __version__\n", + "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n", + "\n", + "print __version__ # requires version >= 1.9.0\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para utilizar Plotly en Jupyter, hay que correr la siguiente linea. Esto inserta el código Javascript de Plotly Offline en el Notebook. " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "init_notebook_mode(connected=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Gráfico de líneas simple" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data = [{\"x\": [1, 2, 3], \"y\": [3, 1, 6]}]\n", + "#data\n", + "#iplot(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Boxplot\n", + "\n", + "https://plot.ly/python/reference/#box" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "from plotly.graph_objs import *\n", + "import numpy as np\n", + "\n", + "data = [Box(y = np.random.randn(50), showlegend=False) for i in range(10)]\n", + "#data\n", + "#iplot(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Histogramas en 1 y 2 dimensiones\n", + "\n", + "https://plot.ly/python/reference/#histogram" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.random.randn(1000)\n", + "y = np.random.randn(1000)\n", + "\n", + "iplot([Histogram(x=x)])\n", + "\n", + "#iplot([Histogram2d(x=x,y=y)])\n", + "iplot([Histogram2dContour(x=x,y=y)])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Integración con Pandas" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from plotly.graph_objs import Bar, Scatter, Figure, Layout\n", + "import pandas as pd\n", + "df = pd.read_csv('life_expectancy.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Africa_Life Expentancy [in years]Africa_textAfrica_marker.sizeAfrica_Gross Domestic Product per Capita [in USD of the year 2000]Americas_Life Expentancy [in years]Americas_textAmericas_marker.sizeAmericas_Gross Domestic Product per Capita [in USD of the year 2000]Asia_Life Expentancy [in years]Asia_textAsia_marker.sizeAsia_Gross Domestic Product per Capita [in USD of the year 2000]Europe_Life Expentancy [in years]Europe_textEurope_marker.sizeEurope_Gross Domestic Product per Capita [in USD of the year 2000]Oceania_Life Expentancy [in years]Oceania_textOceania_marker.sizeOceania_Gross Domestic Product per Capita [in USD of the year 2000]
072.301Country: Algeria <br>Life Expectancy: 72.30...33333216.06223.36746575.320Country: Argentina <br>Life Expectancy: 75....40301927.012779.37964043.828Country: Afghanistan <br>Life Expectancy: 4...3.188992e+07974.58033876.423Country: Albania <br>Life Expectancy: 76.42...3600523.05937.02952681.235Country: Australia <br>Life Expectancy: 81....20434176.034435.36744
142.731Country: Angola <br>Life Expectancy: 42.731...12420476.04797.23126765.554Country: Bolivia <br>Life Expectancy: 65.55...9119152.03822.13708475.635Country: Bahrain <br>Life Expectancy: 75.63...7.085730e+0529796.04834079.829Country: Austria <br>Life Expectancy: 79.82...8199783.036126.49270080.204Country: New Zealand <br>Life Expectancy: 8...4115771.025185.00911
256.728Country: Benin <br>Life Expectancy: 56.728 ...8078314.01441.28487372.390Country: Brazil <br>Life Expectancy: 72.39 ...190010647.09065.80082564.062Country: Bangladesh <br>Life Expectancy: 64...1.504483e+081391.25379279.441Country: Belgium <br>Life Expectancy: 79.44...10392226.033692.605080NaNNaNNaNNaN
350.728Country: Botswana <br>Life Expectancy: 50.7...1639131.012569.85177080.653Country: Canada <br>Life Expectancy: 80.653...33390141.036319.23501059.723Country: Cambodia <br>Life Expectancy: 59.7...1.413186e+071713.77868674.852Country: Bosnia and Herzegovina <br>Life Ex...4552198.07446.298803NaNNaNNaNNaN
452.295Country: Burkina Faso <br>Life Expectancy: ...14326203.01217.03299478.553Country: Chile <br>Life Expectancy: 78.553 ...16284741.013171.63885072.961Country: China <br>Life Expectancy: 72.961 ...1.318683e+094959.11485473.005Country: Bulgaria <br>Life Expectancy: 73.0...7322858.010680.792820NaNNaNNaNNaN
\n", + "
" + ], + "text/plain": [ + " Africa_Life Expentancy [in years] \\\n", + "0 72.301 \n", + "1 42.731 \n", + "2 56.728 \n", + "3 50.728 \n", + "4 52.295 \n", + "\n", + " Africa_text Africa_marker.size \\\n", + "0 Country: Algeria
Life Expectancy: 72.30... 33333216.0 \n", + "1 Country: Angola
Life Expectancy: 42.731... 12420476.0 \n", + "2 Country: Benin
Life Expectancy: 56.728 ... 8078314.0 \n", + "3 Country: Botswana
Life Expectancy: 50.7... 1639131.0 \n", + "4 Country: Burkina Faso
Life Expectancy: ... 14326203.0 \n", + "\n", + " Africa_Gross Domestic Product per Capita [in USD of the year 2000] \\\n", + "0 6223.367465 \n", + "1 4797.231267 \n", + "2 1441.284873 \n", + "3 12569.851770 \n", + "4 1217.032994 \n", + "\n", + " Americas_Life Expentancy [in years] \\\n", + "0 75.320 \n", + "1 65.554 \n", + "2 72.390 \n", + "3 80.653 \n", + "4 78.553 \n", + "\n", + " Americas_text Americas_marker.size \\\n", + "0 Country: Argentina
Life Expectancy: 75.... 40301927.0 \n", + "1 Country: Bolivia
Life Expectancy: 65.55... 9119152.0 \n", + "2 Country: Brazil
Life Expectancy: 72.39 ... 190010647.0 \n", + "3 Country: Canada
Life Expectancy: 80.653... 33390141.0 \n", + "4 Country: Chile
Life Expectancy: 78.553 ... 16284741.0 \n", + "\n", + " Americas_Gross Domestic Product per Capita [in USD of the year 2000] \\\n", + "0 12779.379640 \n", + "1 3822.137084 \n", + "2 9065.800825 \n", + "3 36319.235010 \n", + "4 13171.638850 \n", + "\n", + " Asia_Life Expentancy [in years] \\\n", + "0 43.828 \n", + "1 75.635 \n", + "2 64.062 \n", + "3 59.723 \n", + "4 72.961 \n", + "\n", + " Asia_text Asia_marker.size \\\n", + "0 Country: Afghanistan
Life Expectancy: 4... 3.188992e+07 \n", + "1 Country: Bahrain
Life Expectancy: 75.63... 7.085730e+05 \n", + "2 Country: Bangladesh
Life Expectancy: 64... 1.504483e+08 \n", + "3 Country: Cambodia
Life Expectancy: 59.7... 1.413186e+07 \n", + "4 Country: China
Life Expectancy: 72.961 ... 1.318683e+09 \n", + "\n", + " Asia_Gross Domestic Product per Capita [in USD of the year 2000] \\\n", + "0 974.580338 \n", + "1 29796.048340 \n", + "2 1391.253792 \n", + "3 1713.778686 \n", + "4 4959.114854 \n", + "\n", + " Europe_Life Expentancy [in years] \\\n", + "0 76.423 \n", + "1 79.829 \n", + "2 79.441 \n", + "3 74.852 \n", + "4 73.005 \n", + "\n", + " Europe_text Europe_marker.size \\\n", + "0 Country: Albania
Life Expectancy: 76.42... 3600523.0 \n", + "1 Country: Austria
Life Expectancy: 79.82... 8199783.0 \n", + "2 Country: Belgium
Life Expectancy: 79.44... 10392226.0 \n", + "3 Country: Bosnia and Herzegovina
Life Ex... 4552198.0 \n", + "4 Country: Bulgaria
Life Expectancy: 73.0... 7322858.0 \n", + "\n", + " Europe_Gross Domestic Product per Capita [in USD of the year 2000] \\\n", + "0 5937.029526 \n", + "1 36126.492700 \n", + "2 33692.605080 \n", + "3 7446.298803 \n", + "4 10680.792820 \n", + "\n", + " Oceania_Life Expentancy [in years] \\\n", + "0 81.235 \n", + "1 80.204 \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN \n", + "\n", + " Oceania_text Oceania_marker.size \\\n", + "0 Country: Australia
Life Expectancy: 81.... 20434176.0 \n", + "1 Country: New Zealand
Life Expectancy: 8... 4115771.0 \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "\n", + " Oceania_Gross Domestic Product per Capita [in USD of the year 2000] \n", + "0 34435.36744 \n", + "1 25185.00911 \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN " + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = {\n", + " 'data': [\n", + " Scatter(x=df[continent+'_Life Expentancy [in years]'],\n", + " y=df[continent+'_Gross Domestic Product per Capita [in USD of the year 2000]'],\n", + " text=df[continent+'_text'],\n", + " marker=Marker(size=df[continent+'_marker.size'], sizemode='area', sizeref=131868,),\n", + " mode='markers',\n", + " name=continent) for continent in ['Africa', 'Americas', 'Asia', 'Europe', 'Oceania']\n", + " ],\n", + " 'layout': Layout(xaxis=XAxis(title='Life Expectancy'), yaxis=YAxis(title='GDP per Capita', type='log'))\n", + "}\n", + "\n", + "iplot(data, show_link=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Práctica sugerida\n", + "\n", + "Vamos a reescribir la grafica y construir la estructura con una sintaxis mas legible.\n", + "\n", + "Referencias:\n", + "\n", + "* Bubble Charts: https://plot.ly/python/bubble-charts/\n", + "\n", + "* Scatter Trace Type: https://plot.ly/python/reference/#scatter\n" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "x0=df['Americas_Life Expentancy [in years]']\n", + "y0=df['Americas_Gross Domestic Product per Capita [in USD of the year 2000]']\n", + "t0=df['Americas_text']\n", + "s0=df['Americas_marker.size']\n", + "\n", + "americas = Scatter(x=x0,y=y0,text=t0,marker=Marker(size=s0, sizemode='area', sizeref=131868,),mode='markers',name=continent)\n", + "layout = Layout(xaxis=XAxis(title='Life Expectancy'), yaxis=YAxis(title='GDP per Capita'))\n", + "\n", + "#iplot([americas])\n", + "\n", + "#data = {'data':[americas],'layout':layout}\n", + "#iplot(data)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Sesion 1 - Productos de datos y comunicacion.ipynb" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Sesion 1 - Productos de datos y comunicacion.ipynb" deleted file mode 100644 index 1fd76c8..0000000 --- "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Sesion 1 - Productos de datos y comunicacion.ipynb" +++ /dev/null @@ -1,95 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Comunicación, visualización y productos de datos\n", - "# Sesión 1\n", - "-----\n", - "\n", - "\n", - "## 1. Productos y productos de datos\n", - "### Temas\n", - " - Definición de producto\n", - " - Productos de datos\n", - " - Ejemplos de productos de datos\n", - "\n", - "## 2. Principios de diseño de producto\n", - "### Temas\n", - " - Características de los productos exitosos\n", - " - Caracterización del usuario\n", - " - Definición y priorización de features del producto\n", - "\n", - "### Lecturas\n", - "\n", - "- http://www.newyorker.com/news/news-desk/steve-jobs-technology-alone-is-not-enough\n", - "- http://headrush.typepad.com/\n", - "- http://uxmag.com/articles/how-to-design-for-the-gut\n", - "- http://www.slideshare.net/dan_o/how-to-build-great-products-by-dan-olsen\n", - "- https://www.amazon.com/Emotional-Design-Love-Everyday-Things/dp/0465051367\n", - "\n", - " \n", - "## 3. Storytelling\n", - "### Temas\n", - " - Elementos principales de una historia de datos\n", - " - Uso de los atributos preatentivos\n", - " - Leyes de Tufte y Data-Ink ratio\n", - "\n", - "### Lecturas\n", - " - http://www.storytellingwithdata.com/\n", - " - http://junkcharts.typepad.com/\n", - " - Creating effective slides: https://www.youtube.com/watch?v=meBXuTIPJQk\n", - " \n", - "\n", - "## 4. Generación de engagement\n", - "### Temas\n", - " - Principios de diseño emocional\n", - " - Principios y técnicas de gamification\n", - " - Estética\n", - "\n", - "### Lecturas\n", - " - http://mysterioustrousers.com/news/2013/3/25/visceral-apps-and-you\n", - " - http://blog.usabilla.com/designing-usability-just-isnt-enough/\n", - " - Clear App: https://youtu.be/S00H-rz7fGo\n", - " - Path App: https://youtu.be/oWbWyCyehWg\n", - " - VoteEasy: http://works.periscopic.com/voteeasy/#\n", - " - MusicMap: http://www.musicmap.info/\n", - " - Information is beautiful. http://www.davidmccandless.com/books/\n", - " - Information is beautiful award:http://www.informationisbeautifulawards.com/\n", - " - The Visual Display of Quantitative Information. https://www.edwardtufte.com/tufte/\n", - " \n", - " \n", - "## 5. Galería de visualizaciones interactivas\n", - "\n", - "- http://visual.ly/50-years-change-lgbt-civil-rights?view=true\n", - "- http://www.bloomberg.com/graphics/2014-hottest-year-on-record/\n", - "- https://www.gapminder.org/world/\n", - "\n", - "\n", - "\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.10" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Sesi\303\263n 2 - Principios de Visualizaci\303\263n de Datos.ipynb" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Sesi\303\263n 2 - Principios de Visualizaci\303\263n de Datos.ipynb" new file mode 100644 index 0000000..ba490d7 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/Sesi\303\263n 2 - Principios de Visualizaci\303\263n de Datos.ipynb" @@ -0,0 +1,89 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. Análisis de datos temporales\n", + "\n", + " * Gráfico de barras para series de tiempo (pros y contras)\n", + " * Gráfico de líneas para series de tiempo (pros y contras)\n", + " * Transformaciones de datos\n", + " * Barras agrupadas vs. barras apiladas\n", + " * Small-multiples \n", + " * Relación de aspecto y consistencia de ejes (aspect ratio)\n", + " * Heatmaps\n", + " * Comparación de dos períodos\n", + " * Slopegraph\n", + "\n", + "2. ¿Inicio del Eje-Y en ceros?\n", + "\n", + "3. Análisis temporal de proporciones\n", + " * Barras apiladas para shares\n", + " * Stacked areas 100%\n", + "\n", + "4. Análisis de frecuencias y proporciones\n", + " * Barras horizontales y análisis de baseline\n", + " * Barras apiladas horizontales y sus aplicaciones\n", + " * Box-plots y violin-plots\n", + "\n", + "5. Pie-Charts, pros y contras\n", + " * Pies vs. Barrras\n", + " * Desventajas de los pie-charts\n", + " \n", + "6. Análisis de rankings\n", + " * Packed bubble chart\n", + " * Gráfico de barras horizontal\n", + "\n", + "7. Análisis de jerarquías\n", + " * Treemaps\n", + " \n", + "8. Visualizaciones cartesianas vs. radiales\n", + " * Radar o spider charts\n", + "\n", + "9. Relaciones y datos multidimensionales\n", + " * Scatterplot\n", + " * Bubble chart\n", + " * Heatmap para datos multivariados\n", + "\n", + "10. Visualización de datos geográficos\n", + " * Choroplet\n", + " * Geo-scatterplot\n", + " * Gráfico de densidad de puntos\n", + " * Heatmaps geográficos\n", + "\n", + "11. Selección de escala de color\n", + "\n", + "12. Herramientas para visualizaciones\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/data/us_deaths_100k_arrests.xlsx" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/data/us_deaths_100k_arrests.xlsx" deleted file mode 100644 index cf69164..0000000 Binary files "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/data/us_deaths_100k_arrests.xlsx" and /dev/null differ diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/life_expectancy.csv" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/life_expectancy.csv" new file mode 100644 index 0000000..927dc98 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/life_expectancy.csv" @@ -0,0 +1,53 @@ +Africa_Life Expentancy [in years],Africa_text,Africa_marker.size,Africa_Gross Domestic Product per Capita [in USD of the year 2000],Americas_Life Expentancy [in years],Americas_text,Americas_marker.size,Americas_Gross Domestic Product per Capita [in USD of the year 2000],Asia_Life Expentancy [in years],Asia_text,Asia_marker.size,Asia_Gross Domestic Product per Capita [in USD of the year 2000],Europe_Life Expentancy [in years],Europe_text,Europe_marker.size,Europe_Gross Domestic Product per Capita [in USD of the year 2000],Oceania_Life Expentancy [in years],Oceania_text,Oceania_marker.size,Oceania_Gross Domestic Product per Capita [in USD of the year 2000] +72.301,Country: Algeria
Life Expectancy: 72.301 years
GDP per capita: 6223.367465 $
Population: 33.333216 million,33333216.0,6223.367465,75.32,Country: Argentina
Life Expectancy: 75.32 years
GDP per capita: 12779.37964 $
Population: 40.301927 million,40301927.0,12779.37964,43.828,Country: Afghanistan
Life Expectancy: 43.828 years
GDP per capita: 974.5803384 $
Population: 31.889923 million,31889923.0,974.5803384,76.423,Country: Albania
Life Expectancy: 76.423 years
GDP per capita: 5937.029526 $
Population: 3.600523 million,3600523.0,5937.029526,81.235,Country: Australia
Life Expectancy: 81.235 years
GDP per capita: 34435.36744 $
Population: 20.434176 million,20434176.0,34435.36744 +42.731,Country: Angola
Life Expectancy: 42.731 years
GDP per capita: 4797.231267 $
Population: 12.420476 million,12420476.0,4797.231267,65.554,Country: Bolivia
Life Expectancy: 65.554 years
GDP per capita: 3822.137084 $
Population: 9.119152 million,9119152.0,3822.137084,75.635,Country: Bahrain
Life Expectancy: 75.635 years
GDP per capita: 29796.04834 $
Population: 0.708573 million,708573.0,29796.04834,79.829,Country: Austria
Life Expectancy: 79.829 years
GDP per capita: 36126.4927 $
Population: 8.199783 million,8199783.0,36126.4927,80.204,Country: New Zealand
Life Expectancy: 80.204 years
GDP per capita: 25185.00911 $
Population: 4.115771 million,4115771.0,25185.00911 +56.728,Country: Benin
Life Expectancy: 56.728 years
GDP per capita: 1441.284873 $
Population: 8.078314 million,8078314.0,1441.284873,72.39,Country: Brazil
Life Expectancy: 72.39 years
GDP per capita: 9065.800825 $
Population: 190.010647 million,190010647.0,9065.800825,64.062,Country: Bangladesh
Life Expectancy: 64.062 years
GDP per capita: 1391.253792 $
Population: 150.448339 million,150448339.0,1391.253792,79.441,Country: Belgium
Life Expectancy: 79.441 years
GDP per capita: 33692.60508 $
Population: 10.392226 million,10392226.0,33692.60508,,,, +50.728,Country: Botswana
Life Expectancy: 50.728 years
GDP per capita: 12569.85177 $
Population: 1.639131 million,1639131.0,12569.85177,80.653,Country: Canada
Life Expectancy: 80.653 years
GDP per capita: 36319.23501 $
Population: 33.390141 million,33390141.0,36319.23501,59.723,Country: Cambodia
Life Expectancy: 59.723 years
GDP per capita: 1713.778686 $
Population: 14.131858 million,14131858.0,1713.778686,74.852,Country: Bosnia and Herzegovina
Life Expectancy: 74.852 years
GDP per capita: 7446.298803 $
Population: 4.552198 million,4552198.0,7446.298803,,,, +52.295,Country: Burkina Faso
Life Expectancy: 52.295 years
GDP per capita: 1217.032994 $
Population: 14.326203 million,14326203.0,1217.032994,78.553,Country: Chile
Life Expectancy: 78.553 years
GDP per capita: 13171.63885 $
Population: 16.284741 million,16284741.0,13171.63885,72.961,Country: China
Life Expectancy: 72.961 years
GDP per capita: 4959.114854 $
Population: 1318.683096 million,1318683096.0,4959.114854,73.005,Country: Bulgaria
Life Expectancy: 73.005 years
GDP per capita: 10680.79282 $
Population: 7.322858 million,7322858.0,10680.79282,,,, +49.58,Country: Burundi
Life Expectancy: 49.58 years
GDP per capita: 430.0706916 $
Population: 8.390505 million,8390505.0,430.0706916,72.889,Country: Colombia
Life Expectancy: 72.889 years
GDP per capita: 7006.580419 $
Population: 44.22755 million,44227550.0,7006.580419,82.208,"Country: Hong Kong, China
Life Expectancy: 82.208 years
GDP per capita: 39724.97867 $
Population: 6.980412 million",6980412.0,39724.97867,75.748,Country: Croatia
Life Expectancy: 75.748 years
GDP per capita: 14619.22272 $
Population: 4.493312 million,4493312.0,14619.22272,,,, +50.43,Country: Cameroon
Life Expectancy: 50.43 years
GDP per capita: 2042.09524 $
Population: 17.696293 million,17696293.0,2042.09524,78.782,Country: Costa Rica
Life Expectancy: 78.782 years
GDP per capita: 9645.06142 $
Population: 4.133884 million,4133884.0,9645.06142,64.698,Country: India
Life Expectancy: 64.698 years
GDP per capita: 2452.210407 $
Population: 1110.396331 million,1110396331.0,2452.210407,76.486,Country: Czech Republic
Life Expectancy: 76.486 years
GDP per capita: 22833.30851 $
Population: 10.228744 million,10228744.0,22833.30851,,,, +44.741,Country: Central African Republic
Life Expectancy: 44.741 years
GDP per capita: 706.016537 $
Population: 4.369038 million,4369038.0,706.016537,78.273,Country: Cuba
Life Expectancy: 78.273 years
GDP per capita: 8948.102923 $
Population: 11.416987 million,11416987.0,8948.102923,70.65,Country: Indonesia
Life Expectancy: 70.65 years
GDP per capita: 3540.651564 $
Population: 223.547 million,223547000.0,3540.651564,78.332,Country: Denmark
Life Expectancy: 78.332 years
GDP per capita: 35278.41874 $
Population: 5.46812 million,5468120.0,35278.41874,,,, +50.651,Country: Chad
Life Expectancy: 50.651 years
GDP per capita: 1704.063724 $
Population: 10.238807 million,10238807.0,1704.063724,72.235,Country: Dominican Republic
Life Expectancy: 72.235 years
GDP per capita: 6025.374752 $
Population: 9.319622 million,9319622.0,6025.374752,70.964,Country: Iran
Life Expectancy: 70.964 years
GDP per capita: 11605.71449 $
Population: 69.45357 million,69453570.0,11605.71449,79.313,Country: Finland
Life Expectancy: 79.313 years
GDP per capita: 33207.0844 $
Population: 5.23846 million,5238460.0,33207.0844,,,, +65.152,Country: Comoros
Life Expectancy: 65.152 years
GDP per capita: 986.1478792 $
Population: 0.71096 million,710960.0,986.1478792,74.994,Country: Ecuador
Life Expectancy: 74.994 years
GDP per capita: 6873.262326 $
Population: 13.75568 million,13755680.0,6873.262326,59.545,Country: Iraq
Life Expectancy: 59.545 years
GDP per capita: 4471.061906 $
Population: 27.499638 million,27499638.0,4471.061906,80.657,Country: France
Life Expectancy: 80.657 years
GDP per capita: 30470.0167 $
Population: 61.083916 million,61083916.0,30470.0167,,,, +46.462,"Country: Congo, Dem. Rep.
Life Expectancy: 46.462 years
GDP per capita: 277.5518587 $
Population: 64.606759 million",64606759.0,277.5518587,71.878,Country: El Salvador
Life Expectancy: 71.878 years
GDP per capita: 5728.353514 $
Population: 6.939688 million,6939688.0,5728.353514,80.745,Country: Israel
Life Expectancy: 80.745 years
GDP per capita: 25523.2771 $
Population: 6.426679 million,6426679.0,25523.2771,79.406,Country: Germany
Life Expectancy: 79.406 years
GDP per capita: 32170.37442 $
Population: 82.400996 million,82400996.0,32170.37442,,,, +55.322,"Country: Congo, Rep.
Life Expectancy: 55.322 years
GDP per capita: 3632.557798 $
Population: 3.80061 million",3800610.0,3632.557798,70.259,Country: Guatemala
Life Expectancy: 70.259 years
GDP per capita: 5186.050003 $
Population: 12.572928 million,12572928.0,5186.050003,82.603,Country: Japan
Life Expectancy: 82.603 years
GDP per capita: 31656.06806 $
Population: 127.467972 million,127467972.0,31656.06806,79.483,Country: Greece
Life Expectancy: 79.483 years
GDP per capita: 27538.41188 $
Population: 10.70629 million,10706290.0,27538.41188,,,, +48.328,Country: Cote d'Ivoire
Life Expectancy: 48.328 years
GDP per capita: 1544.750112 $
Population: 18.013409 million,18013409.0,1544.750112,60.916,Country: Haiti
Life Expectancy: 60.916 years
GDP per capita: 1201.637154 $
Population: 8.502814 million,8502814.0,1201.637154,72.535,Country: Jordan
Life Expectancy: 72.535 years
GDP per capita: 4519.461171 $
Population: 6.053193 million,6053193.0,4519.461171,73.338,Country: Hungary
Life Expectancy: 73.338 years
GDP per capita: 18008.94444 $
Population: 9.956108 million,9956108.0,18008.94444,,,, +54.791,Country: Djibouti
Life Expectancy: 54.791 years
GDP per capita: 2082.481567 $
Population: 0.496374 million,496374.0,2082.481567,70.198,Country: Honduras
Life Expectancy: 70.198 years
GDP per capita: 3548.330846 $
Population: 7.483763 million,7483763.0,3548.330846,67.297,"Country: Korea, Dem. Rep.
Life Expectancy: 67.297 years
GDP per capita: 1593.06548 $
Population: 23.301725 million",23301725.0,1593.06548,81.757,Country: Iceland
Life Expectancy: 81.757 years
GDP per capita: 36180.78919 $
Population: 0.301931 million,301931.0,36180.78919,,,, +71.338,Country: Egypt
Life Expectancy: 71.338 years
GDP per capita: 5581.180998 $
Population: 80.264543 million,80264543.0,5581.180998,72.567,Country: Jamaica
Life Expectancy: 72.567 years
GDP per capita: 7320.880262 $
Population: 2.780132 million,2780132.0,7320.880262,78.623,"Country: Korea, Rep.
Life Expectancy: 78.623 years
GDP per capita: 23348.13973 $
Population: 49.04479 million",49044790.0,23348.13973,78.885,Country: Ireland
Life Expectancy: 78.885 years
GDP per capita: 40675.99635 $
Population: 4.109086 million,4109086.0,40675.99635,,,, +51.579,Country: Equatorial Guinea
Life Expectancy: 51.579 years
GDP per capita: 12154.08975 $
Population: 0.551201 million,551201.0,12154.08975,76.195,Country: Mexico
Life Expectancy: 76.195 years
GDP per capita: 11977.57496 $
Population: 108.700891 million,108700891.0,11977.57496,77.588,Country: Kuwait
Life Expectancy: 77.588 years
GDP per capita: 47306.98978 $
Population: 2.505559 million,2505559.0,47306.98978,80.546,Country: Italy
Life Expectancy: 80.546 years
GDP per capita: 28569.7197 $
Population: 58.147733 million,58147733.0,28569.7197,,,, +58.04,Country: Eritrea
Life Expectancy: 58.04 years
GDP per capita: 641.3695236 $
Population: 4.906585 million,4906585.0,641.3695236,72.899,Country: Nicaragua
Life Expectancy: 72.899 years
GDP per capita: 2749.320965 $
Population: 5.675356 million,5675356.0,2749.320965,71.993,Country: Lebanon
Life Expectancy: 71.993 years
GDP per capita: 10461.05868 $
Population: 3.921278 million,3921278.0,10461.05868,74.543,Country: Montenegro
Life Expectancy: 74.543 years
GDP per capita: 9253.896111 $
Population: 0.684736 million,684736.0,9253.896111,,,, +52.947,Country: Ethiopia
Life Expectancy: 52.947 years
GDP per capita: 690.8055759 $
Population: 76.511887 million,76511887.0,690.8055759,75.537,Country: Panama
Life Expectancy: 75.537 years
GDP per capita: 9809.185636 $
Population: 3.242173 million,3242173.0,9809.185636,74.241,Country: Malaysia
Life Expectancy: 74.241 years
GDP per capita: 12451.6558 $
Population: 24.821286 million,24821286.0,12451.6558,79.762,Country: Netherlands
Life Expectancy: 79.762 years
GDP per capita: 36797.93332 $
Population: 16.570613 million,16570613.0,36797.93332,,,, +56.735,Country: Gabon
Life Expectancy: 56.735 years
GDP per capita: 13206.48452 $
Population: 1.454867 million,1454867.0,13206.48452,71.752,Country: Paraguay
Life Expectancy: 71.752 years
GDP per capita: 4172.838464 $
Population: 6.667147 million,6667147.0,4172.838464,66.803,Country: Mongolia
Life Expectancy: 66.803 years
GDP per capita: 3095.772271 $
Population: 2.874127 million,2874127.0,3095.772271,80.196,Country: Norway
Life Expectancy: 80.196 years
GDP per capita: 49357.19017 $
Population: 4.627926 million,4627926.0,49357.19017,,,, +59.448,Country: Gambia
Life Expectancy: 59.448 years
GDP per capita: 752.7497265 $
Population: 1.688359 million,1688359.0,752.7497265,71.421,Country: Peru
Life Expectancy: 71.421 years
GDP per capita: 7408.905561 $
Population: 28.674757 million,28674757.0,7408.905561,62.069,Country: Myanmar
Life Expectancy: 62.069 years
GDP per capita: 944.0 $
Population: 47.76198 million,47761980.0,944.0,75.563,Country: Poland
Life Expectancy: 75.563 years
GDP per capita: 15389.92468 $
Population: 38.518241 million,38518241.0,15389.92468,,,, +60.022,Country: Ghana
Life Expectancy: 60.022 years
GDP per capita: 1327.60891 $
Population: 22.873338 million,22873338.0,1327.60891,78.746,Country: Puerto Rico
Life Expectancy: 78.746 years
GDP per capita: 19328.70901 $
Population: 3.942491 million,3942491.0,19328.70901,63.785,Country: Nepal
Life Expectancy: 63.785 years
GDP per capita: 1091.359778 $
Population: 28.90179 million,28901790.0,1091.359778,78.098,Country: Portugal
Life Expectancy: 78.098 years
GDP per capita: 20509.64777 $
Population: 10.642836 million,10642836.0,20509.64777,,,, +56.007,Country: Guinea
Life Expectancy: 56.007 years
GDP per capita: 942.6542111 $
Population: 9.947814 million,9947814.0,942.6542111,69.819,Country: Trinidad and Tobago
Life Expectancy: 69.819 years
GDP per capita: 18008.50924 $
Population: 1.056608 million,1056608.0,18008.50924,75.64,Country: Oman
Life Expectancy: 75.64 years
GDP per capita: 22316.19287 $
Population: 3.204897 million,3204897.0,22316.19287,72.476,Country: Romania
Life Expectancy: 72.476 years
GDP per capita: 10808.47561 $
Population: 22.276056 million,22276056.0,10808.47561,,,, +46.388,Country: Guinea-Bissau
Life Expectancy: 46.388 years
GDP per capita: 579.231743 $
Population: 1.472041 million,1472041.0,579.231743,78.242,Country: United States
Life Expectancy: 78.242 years
GDP per capita: 42951.65309 $
Population: 301.139947 million,301139947.0,42951.65309,65.483,Country: Pakistan
Life Expectancy: 65.483 years
GDP per capita: 2605.94758 $
Population: 169.270617 million,169270617.0,2605.94758,74.002,Country: Serbia
Life Expectancy: 74.002 years
GDP per capita: 9786.534714 $
Population: 10.150265 million,10150265.0,9786.534714,,,, +54.11,Country: Kenya
Life Expectancy: 54.11 years
GDP per capita: 1463.249282 $
Population: 35.610177 million,35610177.0,1463.249282,76.384,Country: Uruguay
Life Expectancy: 76.384 years
GDP per capita: 10611.46299 $
Population: 3.447496 million,3447496.0,10611.46299,71.688,Country: Philippines
Life Expectancy: 71.688 years
GDP per capita: 3190.481016 $
Population: 91.077287 million,91077287.0,3190.481016,74.663,Country: Slovak Republic
Life Expectancy: 74.663 years
GDP per capita: 18678.31435 $
Population: 5.447502 million,5447502.0,18678.31435,,,, +42.592,Country: Lesotho
Life Expectancy: 42.592 years
GDP per capita: 1569.331442 $
Population: 2.012649 million,2012649.0,1569.331442,73.747,Country: Venezuela
Life Expectancy: 73.747 years
GDP per capita: 11415.80569 $
Population: 26.084662 million,26084662.0,11415.80569,72.777,Country: Saudi Arabia
Life Expectancy: 72.777 years
GDP per capita: 21654.83194 $
Population: 27.601038 million,27601038.0,21654.83194,77.926,Country: Slovenia
Life Expectancy: 77.926 years
GDP per capita: 25768.25759 $
Population: 2.009245 million,2009245.0,25768.25759,,,, +45.678,Country: Liberia
Life Expectancy: 45.678 years
GDP per capita: 414.5073415 $
Population: 3.193942 million,3193942.0,414.5073415,,,,,79.972,Country: Singapore
Life Expectancy: 79.972 years
GDP per capita: 47143.17964 $
Population: 4.553009 million,4553009.0,47143.17964,80.941,Country: Spain
Life Expectancy: 80.941 years
GDP per capita: 28821.0637 $
Population: 40.448191 million,40448191.0,28821.0637,,,, +73.952,Country: Libya
Life Expectancy: 73.952 years
GDP per capita: 12057.49928 $
Population: 6.036914 million,6036914.0,12057.49928,,,,,72.396,Country: Sri Lanka
Life Expectancy: 72.396 years
GDP per capita: 3970.095407 $
Population: 20.378239 million,20378239.0,3970.095407,80.884,Country: Sweden
Life Expectancy: 80.884 years
GDP per capita: 33859.74835 $
Population: 9.031088 million,9031088.0,33859.74835,,,, +59.443,Country: Madagascar
Life Expectancy: 59.443 years
GDP per capita: 1044.770126 $
Population: 19.167654 million,19167654.0,1044.770126,,,,,74.143,Country: Syria
Life Expectancy: 74.143 years
GDP per capita: 4184.548089 $
Population: 19.314747 million,19314747.0,4184.548089,81.701,Country: Switzerland
Life Expectancy: 81.701 years
GDP per capita: 37506.41907 $
Population: 7.554661 million,7554661.0,37506.41907,,,, +48.303,Country: Malawi
Life Expectancy: 48.303 years
GDP per capita: 759.3499101 $
Population: 13.327079 million,13327079.0,759.3499101,,,,,78.4,Country: Taiwan
Life Expectancy: 78.4 years
GDP per capita: 28718.27684 $
Population: 23.174294 million,23174294.0,28718.27684,71.777,Country: Turkey
Life Expectancy: 71.777 years
GDP per capita: 8458.276384 $
Population: 71.158647 million,71158647.0,8458.276384,,,, +54.467,Country: Mali
Life Expectancy: 54.467 years
GDP per capita: 1042.581557 $
Population: 12.031795 million,12031795.0,1042.581557,,,,,70.616,Country: Thailand
Life Expectancy: 70.616 years
GDP per capita: 7458.396327 $
Population: 65.068149 million,65068149.0,7458.396327,79.425,Country: United Kingdom
Life Expectancy: 79.425 years
GDP per capita: 33203.26128 $
Population: 60.776238 million,60776238.0,33203.26128,,,, +64.164,Country: Mauritania
Life Expectancy: 64.164 years
GDP per capita: 1803.151496 $
Population: 3.270065 million,3270065.0,1803.151496,,,,,74.249,Country: Vietnam
Life Expectancy: 74.249 years
GDP per capita: 2441.576404 $
Population: 85.262356 million,85262356.0,2441.576404,,,,,,,, +72.801,Country: Mauritius
Life Expectancy: 72.801 years
GDP per capita: 10956.99112 $
Population: 1.250882 million,1250882.0,10956.99112,,,,,73.422,Country: West Bank and Gaza
Life Expectancy: 73.422 years
GDP per capita: 3025.349798 $
Population: 4.018332 million,4018332.0,3025.349798,,,,,,,, +71.164,Country: Morocco
Life Expectancy: 71.164 years
GDP per capita: 3820.17523 $
Population: 33.757175 million,33757175.0,3820.17523,,,,,62.698,"Country: Yemen, Rep.
Life Expectancy: 62.698 years
GDP per capita: 2280.769906 $
Population: 22.211743 million",22211743.0,2280.769906,,,,,,,, +42.082,Country: Mozambique
Life Expectancy: 42.082 years
GDP per capita: 823.6856205 $
Population: 19.951656 million,19951656.0,823.6856205,,,,,,,,,,,,,,,, +52.906,Country: Namibia
Life Expectancy: 52.906 years
GDP per capita: 4811.060429 $
Population: 2.05508 million,2055080.0,4811.060429,,,,,,,,,,,,,,,, +56.867,Country: Niger
Life Expectancy: 56.867 years
GDP per capita: 619.6768924 $
Population: 12.894865 million,12894865.0,619.6768924,,,,,,,,,,,,,,,, +46.859,Country: Nigeria
Life Expectancy: 46.859 years
GDP per capita: 2013.977305 $
Population: 135.031164 million,135031164.0,2013.977305,,,,,,,,,,,,,,,, +76.442,Country: Reunion
Life Expectancy: 76.442 years
GDP per capita: 7670.122558 $
Population: 0.798094 million,798094.0,7670.122558,,,,,,,,,,,,,,,, +46.242,Country: Rwanda
Life Expectancy: 46.242 years
GDP per capita: 863.0884639 $
Population: 8.860588 million,8860588.0,863.0884639,,,,,,,,,,,,,,,, +65.528,Country: Sao Tome and Principe
Life Expectancy: 65.528 years
GDP per capita: 1598.435089 $
Population: 0.199579 million,199579.0,1598.435089,,,,,,,,,,,,,,,, +63.062,Country: Senegal
Life Expectancy: 63.062 years
GDP per capita: 1712.472136 $
Population: 12.267493 million,12267493.0,1712.472136,,,,,,,,,,,,,,,, +42.568,Country: Sierra Leone
Life Expectancy: 42.568 years
GDP per capita: 862.5407561 $
Population: 6.144562 million,6144562.0,862.5407561,,,,,,,,,,,,,,,, +48.159,Country: Somalia
Life Expectancy: 48.159 years
GDP per capita: 926.1410683 $
Population: 9.118773 million,9118773.0,926.1410683,,,,,,,,,,,,,,,, +49.339,Country: South Africa
Life Expectancy: 49.339 years
GDP per capita: 9269.657808 $
Population: 43.997828 million,43997828.0,9269.657808,,,,,,,,,,,,,,,, +58.556,Country: Sudan
Life Expectancy: 58.556 years
GDP per capita: 2602.394995 $
Population: 42.292929 million,42292929.0,2602.394995,,,,,,,,,,,,,,,, +39.613,Country: Swaziland
Life Expectancy: 39.613 years
GDP per capita: 4513.480643 $
Population: 1.133066 million,1133066.0,4513.480643,,,,,,,,,,,,,,,, +52.517,Country: Tanzania
Life Expectancy: 52.517 years
GDP per capita: 1107.482182 $
Population: 38.13964 million,38139640.0,1107.482182,,,,,,,,,,,,,,,, +58.42,Country: Togo
Life Expectancy: 58.42 years
GDP per capita: 882.9699438 $
Population: 5.701579 million,5701579.0,882.9699438,,,,,,,,,,,,,,,, +73.923,Country: Tunisia
Life Expectancy: 73.923 years
GDP per capita: 7092.923025 $
Population: 10.276158 million,10276158.0,7092.923025,,,,,,,,,,,,,,,, +51.542,Country: Uganda
Life Expectancy: 51.542 years
GDP per capita: 1056.380121 $
Population: 29.170398 million,29170398.0,1056.380121,,,,,,,,,,,,,,,, +42.384,Country: Zambia
Life Expectancy: 42.384 years
GDP per capita: 1271.211593 $
Population: 11.746035 million,11746035.0,1271.211593,,,,,,,,,,,,,,,, +43.487,Country: Zimbabwe
Life Expectancy: 43.487 years
GDP per capita: 469.7092981 $
Population: 12.311143 million,12311143.0,469.7092981,,,,,,,,,,,,,,,, diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/myapp.py" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/myapp.py" new file mode 100644 index 0000000..7d7b0b6 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/myapp.py" @@ -0,0 +1,42 @@ +# myapp.py + +import numpy as np + +from bokeh.layouts import column +from bokeh.models import Button +from bokeh.palettes import RdYlBu3 +from bokeh.plotting import figure, curdoc + +# create a plot and style its properties +p = figure(x_range=(0, 100), y_range=(0, 100), toolbar_location=None) +p.border_fill_color = 'black' +p.background_fill_color = 'black' +p.outline_line_color = None +p.grid.grid_line_color = None + +# add a text renderer to out plot (no data yet) +r = p.text(x=[], y=[], text=[], text_color=[], text_font_size="20pt", + text_baseline="middle", text_align="center") + +i = 0 + +ds = r.data_source + +# create a callback that will add a number in a random location +def callback(): + global i + ds.data['x'].append(np.random.random()*70 + 15) + ds.data['y'].append(np.random.random()*70 + 15) + ds.data['text_color'].append(RdYlBu3[i%3]) + ds.data['text'].append(str(i)) + ds.trigger('data', ds.data, ds.data) + i = i + 1 + +# add a button widget and configure with the call back +button = Button(label="Press Me") +button.on_click(callback) + +# put the button and plot in a layout and add to the document +curdoc().add_root(column(button, p)) + + diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/sample-salesv2.csv" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/sample-salesv2.csv" new file mode 100644 index 0000000..f5c30d5 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/sample-salesv2.csv" @@ -0,0 +1,1001 @@ +account number,name,sku,category,quantity,unit price,ext price,date +296809,Carroll PLC,QN-82852,Belt,13,44.48,578.24,2014-09-27 07:13:03 +098022,Heidenreich-Bosco,MJ-21460,Shoes,19,53.62,1018.78,2014-07-29 02:10:44 +563905,"Kerluke, Reilly and Bechtelar",AS-93055,Shirt,12,24.16,289.92,2014-03-01 10:51:24 +093356,Waters-Walker,AS-93055,Shirt,5,82.68,413.40,2013-11-17 20:41:11 +659366,Waelchi-Fahey,AS-93055,Shirt,18,99.64,1793.52,2014-01-03 08:14:27 +563905,"Kerluke, Reilly and Bechtelar",AS-93055,Shirt,17,52.82,897.94,2013-12-04 02:07:05 +995267,Cole-Eichmann,GS-86623,Shoes,18,15.28,275.04,2014-04-09 16:15:03 +524021,Hegmann and Sons,LL-46261,Shoes,7,78.78,551.46,2014-06-18 19:25:10 +929400,"Senger, Upton and Breitenberg",LW-86841,Shoes,17,38.19,649.23,2014-02-10 05:55:56 +563905,"Kerluke, Reilly and Bechtelar",KV-99194,Shirt,12,26.98,323.76,2014-05-20 00:21:28 +995267,Cole-Eichmann,KV-99194,Shirt,19,60.22,1144.18,2014-03-10 06:23:31 +524021,Hegmann and Sons,QN-82852,Belt,6,13.12,78.72,2013-11-03 18:38:16 +758133,"Kihn, McClure and Denesik",LL-46261,Shoes,4,59.69,238.76,2014-01-11 21:48:28 +555594,"Ernser, Cruickshank and Lind",FK-71853,Shirt,12,97.25,1167.00,2014-09-19 13:20:00 +201259,Koelpin PLC,GS-86623,Shoes,9,81.44,732.96,2014-08-12 08:05:27 +093356,Waters-Walker,LL-46261,Shoes,18,53.33,959.94,2014-07-15 23:21:11 +563905,"Kerluke, Reilly and Bechtelar",KV-99194,Shirt,4,35.62,142.48,2014-10-05 23:38:16 +201259,Koelpin PLC,KV-99194,Shirt,17,98.23,1669.91,2014-01-26 01:52:36 +758133,"Kihn, McClure and Denesik",WJ-02096,Belt,15,69.52,1042.80,2013-11-13 21:38:46 +296809,Carroll PLC,VG-32047,Shirt,12,80.12,961.44,2014-05-24 16:03:28 +750461,"Volkman, Goyette and Lemke",WJ-02096,Belt,13,81.19,1055.47,2014-01-08 02:45:07 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,2,48.15,96.30,2014-04-28 07:01:04 +563905,"Kerluke, Reilly and Bechtelar",MJ-21460,Shoes,1,54.94,54.94,2014-08-09 11:22:15 +734922,Berge LLC,QN-82852,Belt,4,57.75,231.00,2013-11-04 09:48:26 +296809,Carroll PLC,AS-93055,Shirt,14,47.68,667.52,2014-01-12 00:28:09 +304860,Huel-Haag,QN-82852,Belt,2,41.40,82.80,2014-09-23 02:36:55 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,6,58.52,351.12,2014-03-14 02:28:57 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,12,96.62,1159.44,2013-12-13 03:19:19 +850140,Kunze Inc,KV-99194,Shirt,12,93.67,1124.04,2014-02-19 06:03:09 +115138,Gorczany-Hahn,VG-32047,Shirt,12,72.63,871.56,2014-02-07 03:30:14 +711951,Kilback-Gerlach,AS-93055,Shirt,2,90.80,181.60,2014-03-26 20:56:14 +676847,Hamill-Hackett,AS-93055,Shirt,6,42.96,257.76,2013-11-14 22:16:18 +711951,Kilback-Gerlach,AS-93055,Shirt,1,71.50,71.50,2014-04-14 16:58:07 +305803,"Davis, Kshlerin and Reilly",AS-93055,Shirt,1,74.43,74.43,2014-09-20 09:49:19 +201259,Koelpin PLC,GS-86623,Shoes,8,35.38,283.04,2013-12-12 02:37:57 +115138,Gorczany-Hahn,QN-82852,Belt,16,24.87,397.92,2014-02-20 07:42:49 +296809,Carroll PLC,WJ-02096,Belt,14,15.33,214.62,2013-12-03 01:25:07 +093356,Waters-Walker,AS-93055,Shirt,12,94.34,1132.08,2014-09-04 13:39:04 +850140,Kunze Inc,MJ-21460,Shoes,18,12.78,230.04,2014-02-20 13:18:47 +676847,Hamill-Hackett,LL-46261,Shoes,3,28.71,86.13,2014-01-02 12:49:41 +115138,Gorczany-Hahn,VG-32047,Shirt,11,11.21,123.31,2013-12-10 20:13:01 +201259,Koelpin PLC,KV-99194,Shirt,4,29.79,119.16,2013-11-07 17:43:31 +201259,Koelpin PLC,LW-86841,Shoes,11,35.82,394.02,2014-06-21 19:49:30 +676847,Hamill-Hackett,WJ-02096,Belt,6,55.43,332.58,2014-08-08 13:50:43 +304860,Huel-Haag,GS-86623,Shoes,4,95.75,383.00,2014-03-15 12:50:59 +304860,Huel-Haag,MJ-21460,Shoes,10,12.63,126.30,2014-06-05 22:34:03 +850140,Kunze Inc,MJ-21460,Shoes,10,26.21,262.10,2014-04-21 02:14:10 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,11,92.10,1013.10,2014-03-21 14:26:03 +750461,"Volkman, Goyette and Lemke",MJ-21460,Shoes,10,98.27,982.70,2014-10-02 04:41:10 +555594,"Ernser, Cruickshank and Lind",FK-71853,Shirt,6,65.40,392.40,2014-09-17 19:15:27 +995267,Cole-Eichmann,KV-99194,Shirt,10,23.79,237.90,2013-11-17 23:56:36 +201259,Koelpin PLC,MJ-21460,Shoes,7,52.01,364.07,2014-05-23 17:49:08 +758133,"Kihn, McClure and Denesik",FK-71853,Shirt,11,13.06,143.66,2014-03-01 08:58:41 +850140,Kunze Inc,GS-86623,Shoes,14,92.43,1294.02,2014-08-03 21:22:07 +201259,Koelpin PLC,FK-71853,Shirt,14,57.69,807.66,2014-05-26 16:29:02 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,10,83.05,830.50,2014-01-05 10:16:57 +098022,Heidenreich-Bosco,GS-86623,Shoes,10,26.49,264.90,2014-02-12 07:27:39 +929400,"Senger, Upton and Breitenberg",GS-86623,Shoes,15,88.24,1323.60,2014-07-09 19:31:43 +305803,"Davis, Kshlerin and Reilly",LL-46261,Shoes,13,75.38,979.94,2014-03-05 09:26:56 +850140,Kunze Inc,LW-86841,Shoes,16,66.61,1065.76,2014-07-25 22:56:12 +734922,Berge LLC,GS-86623,Shoes,3,99.88,299.64,2014-08-04 23:08:09 +995267,Cole-Eichmann,AS-93055,Shirt,7,41.75,292.25,2014-07-08 15:01:53 +115138,Gorczany-Hahn,AS-93055,Shirt,13,22.23,288.99,2014-01-13 18:31:57 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,18,71.38,1284.84,2014-09-24 04:14:12 +098022,Heidenreich-Bosco,LW-86841,Shoes,9,89.82,808.38,2013-11-30 23:19:44 +115138,Gorczany-Hahn,KV-99194,Shirt,10,85.12,851.20,2014-05-17 03:23:30 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,17,75.04,1275.68,2014-02-09 16:56:59 +750461,"Volkman, Goyette and Lemke",KV-99194,Shirt,3,45.05,135.15,2014-02-17 04:26:57 +563905,"Kerluke, Reilly and Bechtelar",GS-86623,Shoes,16,76.77,1228.32,2014-01-05 02:40:58 +659366,Waelchi-Fahey,VG-32047,Shirt,11,99.09,1089.99,2014-07-15 21:09:33 +555594,"Ernser, Cruickshank and Lind",AS-93055,Shirt,3,71.25,213.75,2014-09-29 06:24:24 +563905,"Kerluke, Reilly and Bechtelar",QN-82852,Belt,14,40.30,564.20,2014-01-15 18:10:47 +659366,Waelchi-Fahey,AS-93055,Shirt,1,10.38,10.38,2014-09-12 21:26:08 +304860,Huel-Haag,GS-86623,Shoes,8,69.32,554.56,2014-08-05 15:34:59 +758133,"Kihn, McClure and Denesik",QN-82852,Belt,12,82.74,992.88,2014-07-28 00:55:13 +524021,Hegmann and Sons,QN-82852,Belt,17,81.64,1387.88,2014-05-29 05:51:07 +676847,Hamill-Hackett,LL-46261,Shoes,5,50.63,253.15,2014-10-22 11:43:28 +850140,Kunze Inc,LW-86841,Shoes,6,81.41,488.46,2014-09-11 08:41:22 +115138,Gorczany-Hahn,QN-82852,Belt,13,18.45,239.85,2014-01-19 21:22:08 +563905,"Kerluke, Reilly and Bechtelar",AS-93055,Shirt,17,17.36,295.12,2014-01-29 14:09:39 +304860,Huel-Haag,AS-93055,Shirt,9,55.09,495.81,2014-06-28 22:39:25 +995267,Cole-Eichmann,LL-46261,Shoes,3,17.54,52.62,2014-01-17 19:11:41 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,7,82.51,577.57,2014-01-13 08:06:03 +304860,Huel-Haag,WJ-02096,Belt,3,14.90,44.70,2013-11-21 14:28:29 +659366,Waelchi-Fahey,FK-71853,Shirt,6,89.05,534.30,2014-05-15 02:19:37 +563905,"Kerluke, Reilly and Bechtelar",QN-82852,Belt,18,57.99,1043.82,2014-09-25 06:23:20 +201259,Koelpin PLC,VG-32047,Shirt,1,35.82,35.82,2014-04-01 11:12:52 +734922,Berge LLC,LW-86841,Shoes,5,56.00,280.00,2013-11-22 17:45:35 +555594,"Ernser, Cruickshank and Lind",WJ-02096,Belt,7,77.52,542.64,2014-02-01 09:30:21 +555594,"Ernser, Cruickshank and Lind",LL-46261,Shoes,12,47.07,564.84,2014-08-08 11:08:24 +758133,"Kihn, McClure and Denesik",KV-99194,Shirt,18,70.12,1262.16,2013-10-25 03:43:33 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,20,28.61,572.20,2014-09-30 19:16:05 +115138,Gorczany-Hahn,FK-71853,Shirt,12,73.92,887.04,2014-05-15 13:22:25 +201259,Koelpin PLC,FK-71853,Shirt,2,38.82,77.64,2013-12-10 17:54:51 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,14,69.26,969.64,2014-01-20 20:34:55 +734922,Berge LLC,GS-86623,Shoes,19,28.54,542.26,2013-10-26 17:03:00 +296809,Carroll PLC,LL-46261,Shoes,7,79.15,554.05,2014-03-07 09:38:37 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,20,36.19,723.80,2014-07-02 08:35:43 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,19,93.21,1770.99,2014-04-20 18:58:11 +201259,Koelpin PLC,MJ-21460,Shoes,5,23.76,118.80,2014-08-17 11:00:49 +115138,Gorczany-Hahn,FK-71853,Shirt,2,44.10,88.20,2014-08-09 18:31:40 +115138,Gorczany-Hahn,LL-46261,Shoes,20,41.05,821.00,2014-02-20 07:29:02 +305803,"Davis, Kshlerin and Reilly",LW-86841,Shoes,19,47.78,907.82,2014-02-22 13:15:38 +711951,Kilback-Gerlach,LW-86841,Shoes,9,95.92,863.28,2014-05-29 22:08:13 +093356,Waters-Walker,GS-86623,Shoes,4,50.10,200.40,2014-08-11 02:09:32 +098022,Heidenreich-Bosco,WJ-02096,Belt,10,75.51,755.10,2013-10-22 23:19:39 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,19,64.38,1223.22,2014-09-02 21:51:04 +524021,Hegmann and Sons,FK-71853,Shirt,12,17.42,209.04,2014-01-22 14:25:19 +115138,Gorczany-Hahn,MJ-21460,Shoes,11,81.67,898.37,2014-09-06 11:50:34 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,6,74.08,444.48,2014-02-28 18:37:43 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,18,25.91,466.38,2014-08-12 22:48:01 +524021,Hegmann and Sons,LL-46261,Shoes,6,57.32,343.92,2013-12-20 12:38:08 +750461,"Volkman, Goyette and Lemke",QN-82852,Belt,6,78.61,471.66,2013-12-18 12:13:25 +563905,"Kerluke, Reilly and Bechtelar",MJ-21460,Shoes,5,50.85,254.25,2014-08-02 05:30:13 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,13,72.12,937.56,2014-03-09 14:23:35 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,14,24.91,348.74,2014-04-06 19:20:34 +555594,"Ernser, Cruickshank and Lind",MJ-21460,Shoes,9,43.25,389.25,2014-04-26 16:22:46 +299771,"Kuphal, Zieme and Kub",QN-82852,Belt,12,66.32,795.84,2013-11-19 04:47:16 +659366,Waelchi-Fahey,AS-93055,Shirt,2,24.30,48.60,2013-11-10 13:25:32 +734922,Berge LLC,MJ-21460,Shoes,12,53.70,644.40,2014-09-27 02:51:01 +201259,Koelpin PLC,LL-46261,Shoes,16,80.82,1293.12,2014-08-19 00:53:50 +555594,"Ernser, Cruickshank and Lind",QN-82852,Belt,10,91.71,917.10,2014-06-25 19:11:32 +563905,"Kerluke, Reilly and Bechtelar",KV-99194,Shirt,11,16.05,176.55,2014-09-26 03:52:52 +093356,Waters-Walker,VG-32047,Shirt,17,86.18,1465.06,2014-08-13 15:42:49 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,14,87.56,1225.84,2014-04-27 07:55:06 +676847,Hamill-Hackett,GS-86623,Shoes,20,27.49,549.80,2014-07-02 12:51:29 +093356,Waters-Walker,GS-86623,Shoes,4,73.11,292.44,2014-08-21 19:29:11 +758133,"Kihn, McClure and Denesik",FK-71853,Shirt,11,90.64,997.04,2014-05-11 06:10:17 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,12,72.17,866.04,2014-09-15 20:49:18 +659366,Waelchi-Fahey,LL-46261,Shoes,9,50.76,456.84,2014-08-29 11:32:00 +093356,Waters-Walker,FK-71853,Shirt,16,21.43,342.88,2014-05-25 00:38:58 +093356,Waters-Walker,LL-46261,Shoes,20,21.09,421.80,2013-12-23 04:50:54 +524021,Hegmann and Sons,VG-32047,Shirt,20,25.37,507.40,2014-07-19 17:18:19 +676847,Hamill-Hackett,KV-99194,Shirt,20,29.59,591.80,2014-01-01 19:55:03 +995267,Cole-Eichmann,KV-99194,Shirt,17,20.24,344.08,2014-10-01 21:20:26 +850140,Kunze Inc,WJ-02096,Belt,13,71.35,927.55,2014-06-09 20:22:22 +524021,Hegmann and Sons,KV-99194,Shirt,16,79.67,1274.72,2013-10-25 07:31:02 +711951,Kilback-Gerlach,LW-86841,Shoes,2,60.75,121.50,2014-05-17 13:10:42 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,5,44.47,222.35,2014-04-11 05:00:15 +093356,Waters-Walker,GS-86623,Shoes,2,86.17,172.34,2014-03-12 14:25:12 +555594,"Ernser, Cruickshank and Lind",LW-86841,Shoes,14,54.50,763.00,2014-10-06 09:47:02 +299771,"Kuphal, Zieme and Kub",AS-93055,Shirt,18,37.75,679.50,2014-04-05 20:02:30 +299771,"Kuphal, Zieme and Kub",FK-71853,Shirt,20,32.70,654.00,2014-04-26 05:18:02 +296809,Carroll PLC,MJ-21460,Shoes,15,93.06,1395.90,2014-08-17 18:39:56 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,17,49.59,843.03,2013-10-29 12:57:27 +750461,"Volkman, Goyette and Lemke",WJ-02096,Belt,17,45.43,772.31,2014-05-09 06:44:04 +711951,Kilback-Gerlach,AS-93055,Shirt,2,31.54,63.08,2014-01-26 05:15:19 +304860,Huel-Haag,LW-86841,Shoes,6,93.02,558.12,2013-11-23 08:51:18 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,16,57.02,912.32,2014-10-14 14:07:31 +711951,Kilback-Gerlach,FK-71853,Shirt,11,53.17,584.87,2014-06-10 15:11:01 +305803,"Davis, Kshlerin and Reilly",LL-46261,Shoes,12,52.51,630.12,2014-08-03 03:39:52 +115138,Gorczany-Hahn,MJ-21460,Shoes,13,96.31,1252.03,2013-12-03 04:04:40 +201259,Koelpin PLC,LW-86841,Shoes,16,90.97,1455.52,2014-08-29 07:41:36 +734922,Berge LLC,KV-99194,Shirt,7,64.02,448.14,2013-11-05 03:55:12 +563905,"Kerluke, Reilly and Bechtelar",GS-86623,Shoes,15,18.41,276.15,2014-03-02 17:47:13 +305803,"Davis, Kshlerin and Reilly",MJ-21460,Shoes,2,29.63,59.26,2014-03-27 23:48:17 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,4,46.82,187.28,2014-02-15 06:51:19 +850140,Kunze Inc,VG-32047,Shirt,9,93.69,843.21,2014-03-20 15:25:39 +093356,Waters-Walker,GS-86623,Shoes,15,64.11,961.65,2013-10-23 08:28:53 +304860,Huel-Haag,LL-46261,Shoes,3,48.87,146.61,2014-04-03 22:36:22 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,14,87.01,1218.14,2013-12-14 16:40:16 +929400,"Senger, Upton and Breitenberg",KV-99194,Shirt,4,17.98,71.92,2014-07-22 19:10:27 +734922,Berge LLC,AS-93055,Shirt,10,93.77,937.70,2014-08-17 09:21:15 +734922,Berge LLC,MJ-21460,Shoes,6,84.73,508.38,2014-07-20 18:27:59 +711951,Kilback-Gerlach,QN-82852,Belt,11,45.49,500.39,2013-11-12 10:13:25 +299771,"Kuphal, Zieme and Kub",LL-46261,Shoes,17,70.23,1193.91,2014-08-14 13:57:01 +995267,Cole-Eichmann,FK-71853,Shirt,10,51.29,512.90,2014-09-16 05:26:10 +093356,Waters-Walker,AS-93055,Shirt,16,75.48,1207.68,2014-08-23 04:04:11 +676847,Hamill-Hackett,MJ-21460,Shoes,19,56.90,1081.10,2014-10-21 08:46:48 +524021,Hegmann and Sons,FK-71853,Shirt,10,71.89,718.90,2014-09-11 00:45:37 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,10,13.02,130.20,2014-06-30 10:31:23 +304860,Huel-Haag,MJ-21460,Shoes,3,79.49,238.47,2014-06-02 13:06:24 +734922,Berge LLC,AS-93055,Shirt,11,81.53,896.83,2014-09-01 17:46:10 +659366,Waelchi-Fahey,LL-46261,Shoes,1,18.68,18.68,2014-05-19 18:10:49 +201259,Koelpin PLC,MJ-21460,Shoes,20,45.32,906.40,2014-07-06 22:06:23 +711951,Kilback-Gerlach,AS-93055,Shirt,10,68.74,687.40,2014-03-27 12:14:12 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,10,90.00,900.00,2014-07-10 22:17:15 +995267,Cole-Eichmann,WJ-02096,Belt,6,20.30,121.80,2014-05-23 10:24:32 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,17,58.67,997.39,2013-12-08 13:43:29 +659366,Waelchi-Fahey,FK-71853,Shirt,2,12.68,25.36,2014-04-27 03:38:16 +676847,Hamill-Hackett,GS-86623,Shoes,17,49.68,844.56,2014-01-28 15:37:10 +524021,Hegmann and Sons,MJ-21460,Shoes,2,95.37,190.74,2014-03-30 08:27:54 +524021,Hegmann and Sons,AS-93055,Shirt,20,96.98,1939.60,2014-06-13 18:23:55 +296809,Carroll PLC,VG-32047,Shirt,16,23.79,380.64,2014-02-26 18:22:57 +995267,Cole-Eichmann,KV-99194,Shirt,2,37.86,75.72,2014-04-04 19:30:50 +304860,Huel-Haag,KV-99194,Shirt,9,66.18,595.62,2014-01-15 11:55:40 +524021,Hegmann and Sons,KV-99194,Shirt,6,98.89,593.34,2014-04-22 00:24:15 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,4,25.02,100.08,2014-05-26 06:54:22 +563905,"Kerluke, Reilly and Bechtelar",WJ-02096,Belt,16,64.58,1033.28,2013-12-17 23:35:15 +305803,"Davis, Kshlerin and Reilly",FK-71853,Shirt,18,48.70,876.60,2014-02-10 08:43:23 +734922,Berge LLC,QN-82852,Belt,16,24.66,394.56,2013-12-12 00:57:07 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,5,43.15,215.75,2014-04-06 06:24:33 +296809,Carroll PLC,QN-82852,Belt,2,54.52,109.04,2014-08-24 09:43:19 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,8,91.14,729.12,2014-06-11 10:12:04 +098022,Heidenreich-Bosco,LW-86841,Shoes,13,65.79,855.27,2014-06-28 04:47:33 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,8,14.73,117.84,2014-03-19 05:18:21 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,14,96.18,1346.52,2014-10-04 09:49:10 +524021,Hegmann and Sons,MJ-21460,Shoes,6,81.10,486.60,2014-02-15 15:29:46 +098022,Heidenreich-Bosco,FK-71853,Shirt,12,38.32,459.84,2014-06-25 09:29:53 +929400,"Senger, Upton and Breitenberg",FK-71853,Shirt,3,51.80,155.40,2014-03-31 04:17:46 +850140,Kunze Inc,FK-71853,Shirt,13,40.29,523.77,2014-09-01 23:53:15 +098022,Heidenreich-Bosco,KV-99194,Shirt,10,22.17,221.70,2014-02-26 06:59:32 +711951,Kilback-Gerlach,MJ-21460,Shoes,15,43.41,651.15,2014-03-09 00:29:06 +115138,Gorczany-Hahn,KV-99194,Shirt,11,67.32,740.52,2014-02-28 18:44:43 +524021,Hegmann and Sons,FK-71853,Shirt,3,17.90,53.70,2014-10-14 19:22:12 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,7,44.27,309.89,2014-10-08 13:05:13 +524021,Hegmann and Sons,FK-71853,Shirt,18,51.72,930.96,2014-02-14 00:05:05 +305803,"Davis, Kshlerin and Reilly",AS-93055,Shirt,9,22.01,198.09,2014-04-08 03:17:21 +563905,"Kerluke, Reilly and Bechtelar",KV-99194,Shirt,10,36.38,363.80,2014-01-02 13:43:36 +304860,Huel-Haag,FK-71853,Shirt,11,63.78,701.58,2014-07-15 23:58:16 +201259,Koelpin PLC,MJ-21460,Shoes,10,56.51,565.10,2014-09-22 16:34:24 +555594,"Ernser, Cruickshank and Lind",AS-93055,Shirt,2,10.47,20.94,2014-04-23 15:24:21 +734922,Berge LLC,GS-86623,Shoes,8,21.39,171.12,2014-03-12 11:43:23 +201259,Koelpin PLC,LL-46261,Shoes,13,26.49,344.37,2014-09-09 14:59:01 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,20,95.60,1912.00,2014-10-12 20:10:43 +995267,Cole-Eichmann,LL-46261,Shoes,17,72.91,1239.47,2014-02-26 16:19:25 +659366,Waelchi-Fahey,FK-71853,Shirt,15,89.45,1341.75,2014-09-09 09:21:01 +305803,"Davis, Kshlerin and Reilly",KV-99194,Shirt,4,63.39,253.56,2014-09-15 18:49:05 +305803,"Davis, Kshlerin and Reilly",QN-82852,Belt,15,51.64,774.60,2014-09-07 02:44:53 +115138,Gorczany-Hahn,LW-86841,Shoes,6,72.98,437.88,2014-06-15 03:34:22 +850140,Kunze Inc,MJ-21460,Shoes,8,63.28,506.24,2014-06-21 21:09:50 +555594,"Ernser, Cruickshank and Lind",WJ-02096,Belt,15,63.31,949.65,2014-04-23 06:25:35 +734922,Berge LLC,MJ-21460,Shoes,10,44.59,445.90,2014-05-04 18:52:20 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,7,41.87,293.09,2013-12-09 01:15:23 +299771,"Kuphal, Zieme and Kub",LW-86841,Shoes,4,35.00,140.00,2014-04-13 20:37:05 +659366,Waelchi-Fahey,WJ-02096,Belt,13,68.39,889.07,2013-11-27 12:45:23 +555594,"Ernser, Cruickshank and Lind",LL-46261,Shoes,8,82.19,657.52,2014-07-19 13:51:23 +296809,Carroll PLC,AS-93055,Shirt,1,58.80,58.80,2014-09-06 13:00:55 +296809,Carroll PLC,QN-82852,Belt,16,27.44,439.04,2014-07-06 13:23:48 +296809,Carroll PLC,MJ-21460,Shoes,14,99.50,1393.00,2014-06-07 23:28:22 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,3,56.34,169.02,2014-07-13 09:41:43 +995267,Cole-Eichmann,LW-86841,Shoes,9,83.87,754.83,2014-07-28 01:53:47 +296809,Carroll PLC,MJ-21460,Shoes,19,56.63,1075.97,2013-12-08 02:40:53 +711951,Kilback-Gerlach,WJ-02096,Belt,1,56.95,56.95,2014-03-08 15:50:55 +524021,Hegmann and Sons,GS-86623,Shoes,10,31.81,318.10,2013-11-18 23:11:16 +995267,Cole-Eichmann,QN-82852,Belt,13,40.34,524.42,2014-09-08 14:00:39 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,10,91.59,915.90,2014-03-19 14:06:11 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,7,95.78,670.46,2014-05-16 23:44:14 +296809,Carroll PLC,LL-46261,Shoes,9,90.91,818.19,2014-10-11 20:37:05 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,12,24.09,289.08,2013-12-08 06:53:09 +711951,Kilback-Gerlach,LL-46261,Shoes,9,10.81,97.29,2013-12-06 00:59:43 +093356,Waters-Walker,QN-82852,Belt,3,59.61,178.83,2014-08-02 13:29:11 +201259,Koelpin PLC,WJ-02096,Belt,16,16.30,260.80,2014-04-05 02:00:02 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,4,23.08,92.32,2014-09-13 11:34:24 +524021,Hegmann and Sons,MJ-21460,Shoes,18,42.01,756.18,2013-11-27 03:18:14 +676847,Hamill-Hackett,LL-46261,Shoes,5,74.02,370.10,2013-11-10 07:30:39 +093356,Waters-Walker,QN-82852,Belt,11,77.66,854.26,2014-03-15 17:01:26 +098022,Heidenreich-Bosco,LL-46261,Shoes,7,14.75,103.25,2014-09-14 23:53:52 +659366,Waelchi-Fahey,LW-86841,Shoes,16,38.75,620.00,2014-03-20 05:48:40 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,13,53.39,694.07,2014-02-26 15:03:04 +676847,Hamill-Hackett,KV-99194,Shirt,1,55.51,55.51,2014-07-15 17:41:23 +305803,"Davis, Kshlerin and Reilly",KV-99194,Shirt,7,16.00,112.00,2014-05-05 21:05:51 +850140,Kunze Inc,AS-93055,Shirt,20,63.75,1275.00,2014-02-09 10:28:34 +201259,Koelpin PLC,GS-86623,Shoes,15,66.78,1001.70,2014-04-29 20:36:59 +093356,Waters-Walker,VG-32047,Shirt,2,75.16,150.32,2013-11-26 12:30:16 +098022,Heidenreich-Bosco,MJ-21460,Shoes,14,34.80,487.20,2014-03-08 06:35:20 +296809,Carroll PLC,QN-82852,Belt,14,14.82,207.48,2014-04-06 19:17:38 +676847,Hamill-Hackett,VG-32047,Shirt,4,88.99,355.96,2013-12-16 01:09:18 +711951,Kilback-Gerlach,LW-86841,Shoes,13,71.43,928.59,2014-04-26 03:39:28 +304860,Huel-Haag,LL-46261,Shoes,6,23.37,140.22,2013-10-22 22:50:47 +711951,Kilback-Gerlach,LL-46261,Shoes,19,30.06,571.14,2014-06-28 01:20:04 +555594,"Ernser, Cruickshank and Lind",QN-82852,Belt,2,74.42,148.84,2013-12-09 09:10:44 +659366,Waelchi-Fahey,QN-82852,Belt,4,38.69,154.76,2014-02-14 02:42:30 +201259,Koelpin PLC,AS-93055,Shirt,3,16.22,48.66,2014-07-11 08:17:44 +296809,Carroll PLC,VG-32047,Shirt,15,63.45,951.75,2014-10-12 09:08:07 +563905,"Kerluke, Reilly and Bechtelar",KV-99194,Shirt,19,78.34,1488.46,2014-09-28 19:20:15 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,9,79.63,716.67,2014-02-16 01:11:09 +750461,"Volkman, Goyette and Lemke",LW-86841,Shoes,3,96.59,289.77,2014-01-11 05:10:44 +524021,Hegmann and Sons,WJ-02096,Belt,20,66.27,1325.40,2014-10-05 01:36:59 +115138,Gorczany-Hahn,AS-93055,Shirt,8,16.11,128.88,2014-08-06 01:09:28 +850140,Kunze Inc,FK-71853,Shirt,7,76.23,533.61,2013-11-06 02:36:22 +524021,Hegmann and Sons,LL-46261,Shoes,15,20.61,309.15,2014-05-26 03:15:30 +995267,Cole-Eichmann,GS-86623,Shoes,6,55.05,330.30,2013-12-27 08:33:09 +299771,"Kuphal, Zieme and Kub",LW-86841,Shoes,9,60.33,542.97,2014-09-16 13:47:08 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,12,96.02,1152.24,2014-04-06 03:35:41 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,16,94.05,1504.80,2014-03-13 22:14:32 +734922,Berge LLC,MJ-21460,Shoes,19,88.62,1683.78,2014-01-29 06:44:37 +850140,Kunze Inc,FK-71853,Shirt,6,38.76,232.56,2014-09-18 05:56:57 +995267,Cole-Eichmann,QN-82852,Belt,10,12.35,123.50,2014-07-05 01:51:03 +299771,"Kuphal, Zieme and Kub",LW-86841,Shoes,3,30.77,92.31,2014-03-01 02:12:31 +659366,Waelchi-Fahey,FK-71853,Shirt,14,23.86,334.04,2014-09-30 12:37:58 +659366,Waelchi-Fahey,WJ-02096,Belt,3,72.43,217.29,2014-10-03 23:46:12 +296809,Carroll PLC,VG-32047,Shirt,10,91.46,914.60,2013-11-24 08:11:02 +850140,Kunze Inc,QN-82852,Belt,19,75.70,1438.30,2014-02-15 14:11:02 +563905,"Kerluke, Reilly and Bechtelar",KV-99194,Shirt,9,95.53,859.77,2014-03-18 14:35:55 +305803,"Davis, Kshlerin and Reilly",AS-93055,Shirt,15,67.57,1013.55,2014-08-02 12:03:04 +093356,Waters-Walker,GS-86623,Shoes,3,99.42,298.26,2014-01-27 11:30:33 +304860,Huel-Haag,MJ-21460,Shoes,9,75.62,680.58,2013-12-18 14:27:30 +305803,"Davis, Kshlerin and Reilly",LL-46261,Shoes,9,84.10,756.90,2014-10-06 21:13:27 +093356,Waters-Walker,LL-46261,Shoes,11,78.54,863.94,2013-12-28 22:14:49 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,3,67.37,202.11,2014-09-01 18:40:25 +563905,"Kerluke, Reilly and Bechtelar",MJ-21460,Shoes,15,42.96,644.40,2014-04-06 13:20:57 +734922,Berge LLC,LL-46261,Shoes,2,62.32,124.64,2014-03-12 11:38:47 +711951,Kilback-Gerlach,AS-93055,Shirt,7,82.95,580.65,2014-08-05 11:34:16 +201259,Koelpin PLC,WJ-02096,Belt,14,40.79,571.06,2014-01-16 02:43:35 +304860,Huel-Haag,QN-82852,Belt,7,38.58,270.06,2014-08-29 23:41:16 +676847,Hamill-Hackett,FK-71853,Shirt,1,99.97,99.97,2014-05-10 12:10:10 +711951,Kilback-Gerlach,GS-86623,Shoes,11,96.66,1063.26,2014-02-13 11:43:17 +563905,"Kerluke, Reilly and Bechtelar",FK-71853,Shirt,17,75.69,1286.73,2013-11-25 02:35:28 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,18,42.02,756.36,2014-03-19 23:24:01 +115138,Gorczany-Hahn,WJ-02096,Belt,12,80.25,963.00,2013-11-06 05:25:34 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,4,70.28,281.12,2014-01-25 23:43:12 +305803,"Davis, Kshlerin and Reilly",LW-86841,Shoes,5,49.68,248.40,2014-09-20 17:40:46 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,14,73.92,1034.88,2013-11-23 17:48:24 +296809,Carroll PLC,WJ-02096,Belt,17,69.41,1179.97,2014-09-11 02:20:46 +850140,Kunze Inc,AS-93055,Shirt,18,87.42,1573.56,2014-05-31 04:28:20 +850140,Kunze Inc,KV-99194,Shirt,20,74.34,1486.80,2014-01-27 19:42:12 +305803,"Davis, Kshlerin and Reilly",VG-32047,Shirt,17,59.12,1005.04,2014-05-11 06:38:13 +850140,Kunze Inc,AS-93055,Shirt,14,77.40,1083.60,2014-08-16 21:03:22 +734922,Berge LLC,LL-46261,Shoes,15,58.85,882.75,2014-08-22 04:35:06 +305803,"Davis, Kshlerin and Reilly",QN-82852,Belt,1,44.77,44.77,2014-02-25 11:20:59 +201259,Koelpin PLC,VG-32047,Shirt,15,26.93,403.95,2014-01-24 10:23:39 +093356,Waters-Walker,MJ-21460,Shoes,12,95.96,1151.52,2014-06-12 00:58:43 +299771,"Kuphal, Zieme and Kub",AS-93055,Shirt,8,31.12,248.96,2013-12-03 14:12:26 +563905,"Kerluke, Reilly and Bechtelar",GS-86623,Shoes,7,83.84,586.88,2014-10-20 05:47:49 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,4,19.86,79.44,2013-11-30 16:47:24 +299771,"Kuphal, Zieme and Kub",FK-71853,Shirt,3,77.07,231.21,2014-06-14 17:54:02 +734922,Berge LLC,LW-86841,Shoes,15,46.94,704.10,2014-05-23 13:09:21 +711951,Kilback-Gerlach,FK-71853,Shirt,11,39.02,429.22,2013-12-08 14:04:38 +734922,Berge LLC,VG-32047,Shirt,2,33.92,67.84,2014-06-27 15:53:05 +299771,"Kuphal, Zieme and Kub",FK-71853,Shirt,11,81.22,893.42,2013-12-01 05:10:26 +201259,Koelpin PLC,QN-82852,Belt,2,25.42,50.84,2014-03-21 17:57:32 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,4,59.07,236.28,2014-04-07 08:54:29 +304860,Huel-Haag,KV-99194,Shirt,15,50.20,753.00,2013-12-29 14:24:05 +305803,"Davis, Kshlerin and Reilly",LW-86841,Shoes,3,24.83,74.49,2014-05-20 15:22:35 +201259,Koelpin PLC,MJ-21460,Shoes,12,89.95,1079.40,2013-12-28 16:19:22 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,4,67.14,268.56,2014-01-30 10:21:27 +524021,Hegmann and Sons,FK-71853,Shirt,8,22.67,181.36,2013-12-30 14:16:13 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,6,50.19,301.14,2014-04-26 22:58:25 +734922,Berge LLC,KV-99194,Shirt,7,46.71,326.97,2014-06-15 15:52:58 +659366,Waelchi-Fahey,FK-71853,Shirt,17,75.46,1282.82,2013-11-17 15:36:57 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,13,23.73,308.49,2014-01-11 12:21:50 +711951,Kilback-Gerlach,QN-82852,Belt,11,71.02,781.22,2014-01-14 18:43:44 +734922,Berge LLC,MJ-21460,Shoes,15,77.10,1156.50,2013-12-07 11:53:40 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,3,39.99,119.97,2013-11-13 02:00:22 +201259,Koelpin PLC,QN-82852,Belt,14,95.77,1340.78,2014-05-04 10:45:11 +850140,Kunze Inc,GS-86623,Shoes,14,13.93,195.02,2014-01-23 17:49:03 +555594,"Ernser, Cruickshank and Lind",MJ-21460,Shoes,15,42.09,631.35,2014-10-17 03:56:02 +201259,Koelpin PLC,VG-32047,Shirt,5,60.51,302.55,2014-10-22 07:16:46 +296809,Carroll PLC,GS-86623,Shoes,5,41.58,207.90,2014-03-29 08:13:19 +734922,Berge LLC,QN-82852,Belt,12,89.48,1073.76,2014-05-23 06:43:54 +850140,Kunze Inc,MJ-21460,Shoes,2,18.29,36.58,2014-01-16 20:23:03 +304860,Huel-Haag,WJ-02096,Belt,1,23.12,23.12,2014-10-17 20:09:53 +659366,Waelchi-Fahey,MJ-21460,Shoes,14,53.60,750.40,2014-09-14 11:01:14 +750461,"Volkman, Goyette and Lemke",MJ-21460,Shoes,16,72.41,1158.56,2014-09-19 21:41:12 +201259,Koelpin PLC,MJ-21460,Shoes,5,33.20,166.00,2014-09-04 23:45:59 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,20,14.99,299.80,2014-06-01 20:29:08 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,3,45.60,136.80,2013-12-21 04:01:40 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,18,80.70,1452.60,2014-05-09 23:51:49 +734922,Berge LLC,MJ-21460,Shoes,4,15.22,60.88,2013-11-15 07:17:16 +734922,Berge LLC,LL-46261,Shoes,13,53.11,690.43,2014-08-29 16:34:09 +115138,Gorczany-Hahn,QN-82852,Belt,1,90.21,90.21,2014-01-30 17:16:08 +676847,Hamill-Hackett,VG-32047,Shirt,4,76.81,307.24,2014-09-06 20:28:27 +098022,Heidenreich-Bosco,AS-93055,Shirt,17,61.31,1042.27,2014-03-19 02:46:57 +524021,Hegmann and Sons,FK-71853,Shirt,7,33.00,231.00,2014-02-04 19:29:41 +995267,Cole-Eichmann,QN-82852,Belt,4,36.62,146.48,2014-08-11 23:29:08 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,10,72.10,721.00,2014-07-19 16:40:01 +524021,Hegmann and Sons,AS-93055,Shirt,18,23.74,427.32,2014-06-18 06:31:15 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,6,51.13,306.78,2014-06-13 21:32:57 +093356,Waters-Walker,FK-71853,Shirt,17,58.55,995.35,2014-05-04 23:02:26 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,6,54.27,325.62,2014-05-15 19:28:27 +305803,"Davis, Kshlerin and Reilly",LL-46261,Shoes,13,77.78,1011.14,2013-11-30 17:23:21 +201259,Koelpin PLC,QN-82852,Belt,8,69.58,556.64,2014-04-03 01:34:49 +676847,Hamill-Hackett,LW-86841,Shoes,10,67.36,673.60,2014-07-15 04:34:11 +299771,"Kuphal, Zieme and Kub",LL-46261,Shoes,15,16.55,248.25,2014-01-09 17:51:49 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,16,99.13,1586.08,2014-09-26 10:54:06 +995267,Cole-Eichmann,QN-82852,Belt,17,69.11,1174.87,2014-09-23 05:58:41 +563905,"Kerluke, Reilly and Bechtelar",AS-93055,Shirt,12,81.57,978.84,2014-09-25 14:09:16 +563905,"Kerluke, Reilly and Bechtelar",FK-71853,Shirt,20,62.12,1242.40,2014-07-01 22:14:25 +734922,Berge LLC,VG-32047,Shirt,4,96.25,385.00,2014-07-09 19:18:49 +098022,Heidenreich-Bosco,LL-46261,Shoes,18,71.34,1284.12,2013-11-17 00:18:08 +711951,Kilback-Gerlach,QN-82852,Belt,19,33.10,628.90,2014-03-04 07:23:35 +296809,Carroll PLC,WJ-02096,Belt,15,38.73,580.95,2014-02-03 03:57:26 +929400,"Senger, Upton and Breitenberg",VG-32047,Shirt,17,43.10,732.70,2014-08-19 11:22:06 +296809,Carroll PLC,WJ-02096,Belt,16,91.09,1457.44,2014-03-18 23:14:03 +524021,Hegmann and Sons,LW-86841,Shoes,13,60.72,789.36,2014-01-18 22:40:14 +201259,Koelpin PLC,QN-82852,Belt,3,64.13,192.39,2014-08-07 15:28:03 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,14,40.86,572.04,2014-08-21 08:07:56 +676847,Hamill-Hackett,LW-86841,Shoes,1,73.74,73.74,2014-09-04 10:46:25 +305803,"Davis, Kshlerin and Reilly",VG-32047,Shirt,6,26.40,158.40,2014-09-04 09:18:54 +850140,Kunze Inc,MJ-21460,Shoes,19,36.32,690.08,2014-08-10 20:15:29 +676847,Hamill-Hackett,LL-46261,Shoes,17,10.96,186.32,2014-01-19 22:01:00 +115138,Gorczany-Hahn,FK-71853,Shirt,17,88.39,1502.63,2014-07-31 12:28:26 +098022,Heidenreich-Bosco,VG-32047,Shirt,20,94.00,1880.00,2014-05-31 22:53:56 +555594,"Ernser, Cruickshank and Lind",LW-86841,Shoes,4,34.42,137.68,2014-10-10 18:54:24 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,14,68.25,955.50,2014-03-16 21:35:20 +299771,"Kuphal, Zieme and Kub",LW-86841,Shoes,5,89.36,446.80,2014-06-08 14:33:12 +758133,"Kihn, McClure and Denesik",KV-99194,Shirt,3,44.37,133.11,2014-04-23 12:05:25 +850140,Kunze Inc,VG-32047,Shirt,11,69.20,761.20,2014-03-14 03:16:51 +555594,"Ernser, Cruickshank and Lind",QN-82852,Belt,12,92.94,1115.28,2014-10-10 18:02:37 +995267,Cole-Eichmann,VG-32047,Shirt,4,54.20,216.80,2014-08-28 06:28:19 +676847,Hamill-Hackett,QN-82852,Belt,3,42.71,128.13,2014-06-09 12:21:47 +929400,"Senger, Upton and Breitenberg",KV-99194,Shirt,4,81.46,325.84,2013-10-25 16:52:01 +098022,Heidenreich-Bosco,MJ-21460,Shoes,9,22.08,198.72,2014-01-21 05:08:12 +305803,"Davis, Kshlerin and Reilly",AS-93055,Shirt,8,98.01,784.08,2014-04-11 08:23:07 +750461,"Volkman, Goyette and Lemke",WJ-02096,Belt,13,83.60,1086.80,2014-08-19 20:42:22 +098022,Heidenreich-Bosco,MJ-21460,Shoes,1,82.28,82.28,2014-10-05 08:28:30 +676847,Hamill-Hackett,AS-93055,Shirt,16,44.38,710.08,2014-09-16 05:22:44 +093356,Waters-Walker,MJ-21460,Shoes,5,54.96,274.80,2013-11-18 19:41:31 +299771,"Kuphal, Zieme and Kub",VG-32047,Shirt,7,97.85,684.95,2014-03-02 21:47:35 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,11,12.27,134.97,2014-01-15 07:26:27 +563905,"Kerluke, Reilly and Bechtelar",LL-46261,Shoes,8,83.88,671.04,2014-07-03 13:24:21 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,2,31.18,62.36,2014-09-21 03:36:32 +524021,Hegmann and Sons,WJ-02096,Belt,13,15.28,198.64,2014-07-26 14:07:00 +711951,Kilback-Gerlach,QN-82852,Belt,14,40.48,566.72,2014-07-10 06:12:22 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,5,38.73,193.65,2014-04-26 11:51:54 +201259,Koelpin PLC,GS-86623,Shoes,5,23.38,116.90,2014-07-26 09:33:15 +711951,Kilback-Gerlach,LL-46261,Shoes,1,54.04,54.04,2014-06-09 20:05:03 +734922,Berge LLC,WJ-02096,Belt,17,25.26,429.42,2014-06-16 10:03:35 +850140,Kunze Inc,GS-86623,Shoes,3,46.00,138.00,2013-10-25 11:42:04 +676847,Hamill-Hackett,GS-86623,Shoes,8,34.76,278.08,2013-11-19 02:20:09 +734922,Berge LLC,VG-32047,Shirt,1,93.10,93.10,2013-12-25 10:00:14 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,10,23.43,234.30,2014-08-20 16:25:05 +305803,"Davis, Kshlerin and Reilly",WJ-02096,Belt,7,41.77,292.39,2014-10-21 05:51:47 +676847,Hamill-Hackett,QN-82852,Belt,11,53.13,584.43,2014-09-24 02:05:24 +711951,Kilback-Gerlach,LW-86841,Shoes,9,90.02,810.18,2014-08-22 13:18:26 +676847,Hamill-Hackett,KV-99194,Shirt,14,37.64,526.96,2014-02-15 06:51:00 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,18,50.99,917.82,2014-02-20 05:55:31 +296809,Carroll PLC,VG-32047,Shirt,9,67.68,609.12,2014-05-22 05:51:16 +299771,"Kuphal, Zieme and Kub",AS-93055,Shirt,18,19.01,342.18,2013-11-14 11:33:02 +659366,Waelchi-Fahey,MJ-21460,Shoes,15,19.62,294.30,2013-11-24 23:33:56 +659366,Waelchi-Fahey,WJ-02096,Belt,14,75.49,1056.86,2014-02-18 02:07:31 +305803,"Davis, Kshlerin and Reilly",WJ-02096,Belt,1,69.57,69.57,2013-12-21 16:04:44 +115138,Gorczany-Hahn,WJ-02096,Belt,6,95.08,570.48,2014-02-01 01:28:20 +305803,"Davis, Kshlerin and Reilly",GS-86623,Shoes,17,20.45,347.65,2014-08-30 03:56:20 +305803,"Davis, Kshlerin and Reilly",QN-82852,Belt,4,85.30,341.20,2014-10-17 13:18:21 +304860,Huel-Haag,VG-32047,Shirt,16,63.97,1023.52,2014-02-06 19:14:35 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,1,93.72,93.72,2014-09-30 09:16:18 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,12,64.09,769.08,2014-04-22 14:36:05 +093356,Waters-Walker,LW-86841,Shoes,16,16.59,265.44,2014-09-07 02:26:24 +115138,Gorczany-Hahn,WJ-02096,Belt,3,52.57,157.71,2014-08-15 13:23:42 +929400,"Senger, Upton and Breitenberg",VG-32047,Shirt,1,34.40,34.40,2014-05-19 20:50:19 +093356,Waters-Walker,VG-32047,Shirt,13,45.97,597.61,2014-07-05 08:56:46 +296809,Carroll PLC,LL-46261,Shoes,10,37.40,374.00,2014-05-05 05:17:28 +750461,"Volkman, Goyette and Lemke",LW-86841,Shoes,14,15.58,218.12,2013-12-23 21:32:05 +995267,Cole-Eichmann,AS-93055,Shirt,11,45.24,497.64,2014-08-06 01:25:27 +734922,Berge LLC,GS-86623,Shoes,9,30.49,274.41,2014-03-02 13:04:07 +758133,"Kihn, McClure and Denesik",KV-99194,Shirt,18,90.84,1635.12,2014-02-01 21:38:06 +659366,Waelchi-Fahey,GS-86623,Shoes,1,38.20,38.20,2013-11-23 15:45:41 +850140,Kunze Inc,QN-82852,Belt,8,72.29,578.32,2014-02-15 21:05:44 +850140,Kunze Inc,MJ-21460,Shoes,20,61.03,1220.60,2013-12-23 23:07:45 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,18,77.66,1397.88,2014-10-18 18:07:37 +929400,"Senger, Upton and Breitenberg",VG-32047,Shirt,10,16.01,160.10,2014-05-07 20:02:28 +676847,Hamill-Hackett,LW-86841,Shoes,9,61.42,552.78,2014-10-16 12:50:55 +304860,Huel-Haag,VG-32047,Shirt,17,64.75,1100.75,2014-09-13 02:51:49 +296809,Carroll PLC,KV-99194,Shirt,16,50.36,805.76,2014-01-03 07:56:48 +305803,"Davis, Kshlerin and Reilly",VG-32047,Shirt,4,64.91,259.64,2014-02-20 20:48:46 +758133,"Kihn, McClure and Denesik",KV-99194,Shirt,16,65.00,1040.00,2014-05-14 17:57:45 +305803,"Davis, Kshlerin and Reilly",GS-86623,Shoes,6,57.28,343.68,2014-04-09 15:32:28 +676847,Hamill-Hackett,VG-32047,Shirt,3,71.55,214.65,2014-02-16 04:42:01 +995267,Cole-Eichmann,VG-32047,Shirt,4,37.74,150.96,2014-03-21 08:21:18 +201259,Koelpin PLC,QN-82852,Belt,12,41.57,498.84,2014-05-22 08:56:14 +659366,Waelchi-Fahey,QN-82852,Belt,13,59.59,774.67,2013-12-04 04:11:33 +524021,Hegmann and Sons,FK-71853,Shirt,20,62.71,1254.20,2014-03-06 22:55:08 +115138,Gorczany-Hahn,GS-86623,Shoes,16,37.88,606.08,2013-12-05 07:33:43 +750461,"Volkman, Goyette and Lemke",LW-86841,Shoes,20,83.10,1662.00,2014-09-14 18:26:11 +555594,"Ernser, Cruickshank and Lind",WJ-02096,Belt,10,11.81,118.10,2014-03-13 00:31:33 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,20,59.10,1182.00,2014-10-02 05:30:08 +563905,"Kerluke, Reilly and Bechtelar",QN-82852,Belt,8,60.70,485.60,2014-04-01 13:03:54 +659366,Waelchi-Fahey,WJ-02096,Belt,1,42.83,42.83,2013-11-05 05:06:14 +734922,Berge LLC,QN-82852,Belt,17,76.13,1294.21,2013-11-25 14:33:27 +201259,Koelpin PLC,FK-71853,Shirt,4,41.09,164.36,2014-08-24 20:22:11 +659366,Waelchi-Fahey,GS-86623,Shoes,12,32.84,394.08,2014-09-13 15:23:40 +296809,Carroll PLC,VG-32047,Shirt,5,10.81,54.05,2014-08-28 00:56:58 +115138,Gorczany-Hahn,LL-46261,Shoes,1,26.19,26.19,2014-01-10 05:09:07 +115138,Gorczany-Hahn,LL-46261,Shoes,12,48.63,583.56,2014-09-17 06:25:26 +305803,"Davis, Kshlerin and Reilly",LL-46261,Shoes,5,51.82,259.10,2014-01-08 02:36:38 +750461,"Volkman, Goyette and Lemke",LW-86841,Shoes,7,53.36,373.52,2014-06-02 19:58:55 +711951,Kilback-Gerlach,KV-99194,Shirt,5,56.33,281.65,2014-09-06 01:57:32 +304860,Huel-Haag,AS-93055,Shirt,11,79.58,875.38,2013-11-21 04:46:33 +734922,Berge LLC,FK-71853,Shirt,7,58.95,412.65,2014-03-14 04:16:55 +850140,Kunze Inc,MJ-21460,Shoes,9,78.44,705.96,2013-12-18 17:23:54 +995267,Cole-Eichmann,WJ-02096,Belt,15,54.77,821.55,2013-11-14 11:15:21 +098022,Heidenreich-Bosco,GS-86623,Shoes,15,73.45,1101.75,2014-01-03 12:09:44 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,14,21.01,294.14,2014-01-01 00:15:37 +524021,Hegmann and Sons,FK-71853,Shirt,15,45.99,689.85,2014-01-21 14:40:49 +524021,Hegmann and Sons,LW-86841,Shoes,11,89.80,987.80,2014-03-14 06:17:28 +734922,Berge LLC,FK-71853,Shirt,4,63.74,254.96,2014-08-31 19:57:31 +296809,Carroll PLC,KV-99194,Shirt,9,36.35,327.15,2014-01-17 22:03:57 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,13,55.99,727.87,2013-12-27 08:36:12 +296809,Carroll PLC,FK-71853,Shirt,4,12.28,49.12,2014-04-03 06:43:35 +659366,Waelchi-Fahey,WJ-02096,Belt,10,64.42,644.20,2014-09-05 03:46:20 +563905,"Kerluke, Reilly and Bechtelar",LL-46261,Shoes,5,29.87,149.35,2014-08-02 00:25:56 +305803,"Davis, Kshlerin and Reilly",GS-86623,Shoes,13,66.85,869.05,2013-11-19 07:26:52 +299771,"Kuphal, Zieme and Kub",LL-46261,Shoes,5,13.07,65.35,2014-08-30 04:09:41 +563905,"Kerluke, Reilly and Bechtelar",QN-82852,Belt,5,56.63,283.15,2014-10-13 02:27:35 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,19,89.14,1693.66,2013-11-14 18:25:50 +524021,Hegmann and Sons,LW-86841,Shoes,5,67.31,336.55,2013-12-16 09:59:38 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,17,11.24,191.08,2014-04-25 15:37:03 +524021,Hegmann and Sons,AS-93055,Shirt,10,73.82,738.20,2014-10-22 04:43:23 +850140,Kunze Inc,QN-82852,Belt,15,11.74,176.10,2014-01-09 04:36:36 +524021,Hegmann and Sons,LL-46261,Shoes,5,83.98,419.90,2014-05-24 20:18:52 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,6,63.40,380.40,2013-12-09 19:01:44 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,15,80.59,1208.85,2014-10-05 18:13:24 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,19,31.41,596.79,2014-05-09 11:00:05 +296809,Carroll PLC,WJ-02096,Belt,9,61.39,552.51,2014-07-15 13:04:50 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,15,96.00,1440.00,2014-10-21 15:04:18 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,12,94.51,1134.12,2014-07-26 07:44:53 +305803,"Davis, Kshlerin and Reilly",KV-99194,Shirt,15,18.07,271.05,2014-05-24 05:33:35 +659366,Waelchi-Fahey,MJ-21460,Shoes,13,74.07,962.91,2014-01-13 12:18:04 +995267,Cole-Eichmann,FK-71853,Shirt,16,88.32,1413.12,2014-06-17 22:27:38 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,4,77.19,308.76,2014-04-03 19:08:57 +098022,Heidenreich-Bosco,GS-86623,Shoes,18,58.56,1054.08,2014-08-25 17:52:34 +305803,"Davis, Kshlerin and Reilly",MJ-21460,Shoes,12,81.42,977.04,2014-07-09 13:58:55 +850140,Kunze Inc,AS-93055,Shirt,3,68.90,206.70,2014-09-13 01:40:40 +995267,Cole-Eichmann,QN-82852,Belt,19,39.75,755.25,2014-05-23 15:58:55 +093356,Waters-Walker,KV-99194,Shirt,11,83.22,915.42,2014-01-03 19:04:02 +750461,"Volkman, Goyette and Lemke",QN-82852,Belt,19,17.25,327.75,2014-02-08 14:06:56 +659366,Waelchi-Fahey,QN-82852,Belt,7,41.70,291.90,2014-01-14 22:56:55 +524021,Hegmann and Sons,MJ-21460,Shoes,20,44.56,891.20,2014-02-11 11:05:35 +201259,Koelpin PLC,WJ-02096,Belt,4,15.24,60.96,2014-09-12 06:29:42 +115138,Gorczany-Hahn,KV-99194,Shirt,1,66.03,66.03,2014-03-06 19:04:47 +995267,Cole-Eichmann,LL-46261,Shoes,8,95.99,767.92,2014-02-28 06:46:39 +711951,Kilback-Gerlach,WJ-02096,Belt,18,18.29,329.22,2014-05-28 10:39:07 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,1,50.58,50.58,2014-01-10 01:35:58 +995267,Cole-Eichmann,WJ-02096,Belt,6,47.21,283.26,2014-01-27 15:50:35 +750461,"Volkman, Goyette and Lemke",VG-32047,Shirt,3,82.06,246.18,2014-03-14 17:54:57 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,18,36.32,653.76,2014-03-25 15:08:27 +850140,Kunze Inc,QN-82852,Belt,10,45.33,453.30,2013-10-23 00:45:16 +296809,Carroll PLC,VG-32047,Shirt,18,30.34,546.12,2014-06-21 11:50:51 +995267,Cole-Eichmann,WJ-02096,Belt,14,23.57,329.98,2014-04-11 23:10:59 +929400,"Senger, Upton and Breitenberg",GS-86623,Shoes,14,16.78,234.92,2014-04-15 00:55:47 +929400,"Senger, Upton and Breitenberg",VG-32047,Shirt,4,92.05,368.20,2013-11-20 17:39:53 +563905,"Kerluke, Reilly and Bechtelar",MJ-21460,Shoes,6,25.35,152.10,2014-02-21 00:43:26 +850140,Kunze Inc,VG-32047,Shirt,13,28.29,367.77,2014-05-14 11:34:59 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,6,70.64,423.84,2014-04-13 10:46:26 +304860,Huel-Haag,KV-99194,Shirt,7,32.91,230.37,2014-03-21 02:07:18 +201259,Koelpin PLC,WJ-02096,Belt,10,31.82,318.20,2014-05-10 12:48:18 +676847,Hamill-Hackett,FK-71853,Shirt,12,74.47,893.64,2014-03-22 00:45:00 +676847,Hamill-Hackett,LW-86841,Shoes,6,72.92,437.52,2014-04-30 13:50:54 +995267,Cole-Eichmann,AS-93055,Shirt,14,70.03,980.42,2013-12-31 09:37:47 +093356,Waters-Walker,KV-99194,Shirt,19,47.53,903.07,2014-03-10 16:34:16 +929400,"Senger, Upton and Breitenberg",AS-93055,Shirt,5,82.05,410.25,2013-12-03 12:28:55 +711951,Kilback-Gerlach,LW-86841,Shoes,16,99.65,1594.40,2014-10-06 23:33:32 +734922,Berge LLC,FK-71853,Shirt,17,49.12,835.04,2014-02-24 20:49:28 +676847,Hamill-Hackett,LL-46261,Shoes,6,52.06,312.36,2014-02-04 19:46:55 +305803,"Davis, Kshlerin and Reilly",KV-99194,Shirt,13,71.70,932.10,2014-07-08 01:00:22 +305803,"Davis, Kshlerin and Reilly",MJ-21460,Shoes,3,37.34,112.02,2013-11-12 01:13:29 +304860,Huel-Haag,WJ-02096,Belt,20,58.52,1170.40,2013-11-21 18:37:52 +299771,"Kuphal, Zieme and Kub",LL-46261,Shoes,16,18.08,289.28,2013-12-12 00:31:40 +098022,Heidenreich-Bosco,GS-86623,Shoes,6,81.70,490.20,2014-10-04 16:06:25 +929400,"Senger, Upton and Breitenberg",FK-71853,Shirt,13,89.53,1163.89,2014-08-11 16:47:07 +299771,"Kuphal, Zieme and Kub",AS-93055,Shirt,7,24.63,172.41,2014-01-28 18:58:01 +305803,"Davis, Kshlerin and Reilly",GS-86623,Shoes,10,73.08,730.80,2013-10-29 17:00:22 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,12,52.24,626.88,2014-02-22 00:09:48 +524021,Hegmann and Sons,QN-82852,Belt,4,84.72,338.88,2013-10-22 13:54:50 +299771,"Kuphal, Zieme and Kub",VG-32047,Shirt,13,37.56,488.28,2013-11-10 06:24:28 +929400,"Senger, Upton and Breitenberg",AS-93055,Shirt,18,22.98,413.64,2014-06-02 14:24:05 +995267,Cole-Eichmann,MJ-21460,Shoes,2,79.87,159.74,2014-08-15 04:36:37 +093356,Waters-Walker,KV-99194,Shirt,7,59.50,416.50,2014-04-29 12:04:58 +659366,Waelchi-Fahey,WJ-02096,Belt,14,67.01,938.14,2013-12-13 15:04:13 +201259,Koelpin PLC,MJ-21460,Shoes,5,61.76,308.80,2013-10-30 04:16:24 +750461,"Volkman, Goyette and Lemke",MJ-21460,Shoes,7,33.16,232.12,2014-08-25 05:45:04 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,1,77.22,77.22,2014-01-21 12:40:40 +296809,Carroll PLC,WJ-02096,Belt,8,55.69,445.52,2014-01-02 21:35:10 +304860,Huel-Haag,AS-93055,Shirt,13,72.75,945.75,2013-11-02 06:09:13 +304860,Huel-Haag,GS-86623,Shoes,20,71.91,1438.20,2014-02-14 02:11:56 +758133,"Kihn, McClure and Denesik",KV-99194,Shirt,2,58.02,116.04,2014-05-28 00:51:31 +296809,Carroll PLC,AS-93055,Shirt,19,78.72,1495.68,2014-08-01 13:54:15 +850140,Kunze Inc,FK-71853,Shirt,8,44.56,356.48,2014-10-01 13:21:06 +711951,Kilback-Gerlach,LW-86841,Shoes,19,92.34,1754.46,2014-05-13 03:41:20 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,12,19.81,237.72,2014-10-12 12:33:27 +563905,"Kerluke, Reilly and Bechtelar",QN-82852,Belt,2,29.15,58.30,2013-12-29 06:05:11 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,8,71.71,573.68,2014-06-15 23:49:22 +093356,Waters-Walker,GS-86623,Shoes,13,52.61,683.93,2014-01-31 10:14:51 +711951,Kilback-Gerlach,MJ-21460,Shoes,4,90.75,363.00,2013-10-27 22:03:05 +659366,Waelchi-Fahey,MJ-21460,Shoes,3,50.33,150.99,2014-02-25 05:11:55 +098022,Heidenreich-Bosco,VG-32047,Shirt,6,96.02,576.12,2013-12-25 18:02:41 +201259,Koelpin PLC,KV-99194,Shirt,14,66.37,929.18,2013-11-05 13:34:42 +676847,Hamill-Hackett,LL-46261,Shoes,3,59.85,179.55,2013-10-26 04:33:08 +524021,Hegmann and Sons,FK-71853,Shirt,2,66.63,133.26,2013-12-07 04:15:11 +734922,Berge LLC,AS-93055,Shirt,8,94.37,754.96,2013-12-31 01:14:11 +734922,Berge LLC,MJ-21460,Shoes,2,37.10,74.20,2014-10-04 18:30:12 +659366,Waelchi-Fahey,QN-82852,Belt,1,78.95,78.95,2014-09-01 04:34:57 +659366,Waelchi-Fahey,FK-71853,Shirt,7,76.57,535.99,2014-09-01 21:04:49 +201259,Koelpin PLC,AS-93055,Shirt,10,43.97,439.70,2014-10-03 17:04:10 +676847,Hamill-Hackett,VG-32047,Shirt,6,59.00,354.00,2014-08-26 02:03:17 +850140,Kunze Inc,GS-86623,Shoes,4,17.63,70.52,2013-11-06 15:35:14 +555594,"Ernser, Cruickshank and Lind",AS-93055,Shirt,12,40.03,480.36,2014-09-18 02:54:50 +115138,Gorczany-Hahn,VG-32047,Shirt,1,61.73,61.73,2013-12-19 05:37:56 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,9,38.76,348.84,2013-11-18 18:59:05 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,15,35.73,535.95,2014-07-29 13:03:54 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,7,80.19,561.33,2014-05-22 07:55:43 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,14,12.35,172.90,2014-02-28 10:45:43 +098022,Heidenreich-Bosco,QN-82852,Belt,20,38.39,767.80,2013-11-18 22:22:57 +734922,Berge LLC,QN-82852,Belt,11,60.05,660.55,2014-09-28 12:19:39 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,15,17.57,263.55,2014-03-09 21:17:26 +659366,Waelchi-Fahey,GS-86623,Shoes,9,43.69,393.21,2014-03-12 02:19:35 +676847,Hamill-Hackett,GS-86623,Shoes,18,69.13,1244.34,2014-02-11 23:45:29 +304860,Huel-Haag,QN-82852,Belt,3,94.18,282.54,2014-09-09 20:05:35 +524021,Hegmann and Sons,VG-32047,Shirt,17,80.42,1367.14,2014-05-13 03:46:45 +850140,Kunze Inc,AS-93055,Shirt,13,31.53,409.89,2014-06-12 12:09:39 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,6,18.33,109.98,2014-01-16 01:38:16 +850140,Kunze Inc,KV-99194,Shirt,1,73.79,73.79,2013-11-07 19:52:06 +296809,Carroll PLC,LW-86841,Shoes,3,10.67,32.01,2014-05-30 21:32:51 +093356,Waters-Walker,GS-86623,Shoes,19,53.33,1013.27,2014-05-31 08:48:28 +296809,Carroll PLC,AS-93055,Shirt,18,55.23,994.14,2013-12-02 17:42:51 +296809,Carroll PLC,WJ-02096,Belt,7,77.91,545.37,2014-10-17 14:13:45 +995267,Cole-Eichmann,VG-32047,Shirt,20,28.81,576.20,2014-03-19 16:59:03 +299771,"Kuphal, Zieme and Kub",VG-32047,Shirt,16,31.86,509.76,2014-09-04 05:27:45 +296809,Carroll PLC,GS-86623,Shoes,8,28.32,226.56,2014-10-01 04:15:37 +659366,Waelchi-Fahey,GS-86623,Shoes,2,88.57,177.14,2014-06-16 02:35:22 +524021,Hegmann and Sons,VG-32047,Shirt,11,52.58,578.38,2014-01-22 08:06:36 +201259,Koelpin PLC,WJ-02096,Belt,14,20.87,292.18,2014-02-09 05:27:27 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,7,54.95,384.65,2013-12-31 04:32:30 +734922,Berge LLC,AS-93055,Shirt,11,36.86,405.46,2014-01-01 08:13:10 +995267,Cole-Eichmann,KV-99194,Shirt,5,52.07,260.35,2014-09-17 06:06:34 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,19,71.71,1362.49,2013-12-29 04:27:13 +750461,"Volkman, Goyette and Lemke",KV-99194,Shirt,3,71.09,213.27,2013-11-16 02:18:39 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,7,60.04,420.28,2013-12-14 15:26:14 +711951,Kilback-Gerlach,KV-99194,Shirt,5,55.82,279.10,2014-05-24 05:01:20 +734922,Berge LLC,KV-99194,Shirt,16,24.13,386.08,2013-12-20 01:56:23 +093356,Waters-Walker,WJ-02096,Belt,20,62.39,1247.80,2014-04-19 16:00:54 +201259,Koelpin PLC,FK-71853,Shirt,2,83.01,166.02,2014-01-05 22:32:10 +555594,"Ernser, Cruickshank and Lind",GS-86623,Shoes,2,58.61,117.22,2014-04-25 18:15:52 +524021,Hegmann and Sons,LW-86841,Shoes,15,98.54,1478.10,2014-09-04 06:01:32 +659366,Waelchi-Fahey,WJ-02096,Belt,15,20.03,300.45,2014-09-06 09:47:38 +093356,Waters-Walker,VG-32047,Shirt,17,71.32,1212.44,2014-09-16 10:45:19 +711951,Kilback-Gerlach,VG-32047,Shirt,10,55.04,550.40,2014-08-19 17:39:10 +093356,Waters-Walker,QN-82852,Belt,19,95.37,1812.03,2014-05-20 09:39:21 +750461,"Volkman, Goyette and Lemke",LW-86841,Shoes,16,19.83,317.28,2014-09-03 12:10:24 +995267,Cole-Eichmann,WJ-02096,Belt,5,50.88,254.40,2014-02-15 03:16:45 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,17,36.81,625.77,2013-12-05 23:10:45 +524021,Hegmann and Sons,VG-32047,Shirt,4,42.78,171.12,2014-03-07 04:28:42 +995267,Cole-Eichmann,VG-32047,Shirt,6,87.35,524.10,2013-12-12 21:41:39 +299771,"Kuphal, Zieme and Kub",QN-82852,Belt,10,59.42,594.20,2014-06-11 12:10:16 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,3,30.80,92.40,2014-01-29 11:47:43 +734922,Berge LLC,MJ-21460,Shoes,14,74.75,1046.50,2014-02-06 23:35:03 +201259,Koelpin PLC,LW-86841,Shoes,12,73.70,884.40,2014-03-12 01:27:20 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,10,36.30,363.00,2014-04-14 22:51:06 +093356,Waters-Walker,GS-86623,Shoes,10,75.72,757.20,2014-01-31 09:09:36 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,14,73.07,1022.98,2013-11-29 18:17:10 +201259,Koelpin PLC,VG-32047,Shirt,19,76.09,1445.71,2014-08-04 04:24:32 +093356,Waters-Walker,VG-32047,Shirt,13,45.42,590.46,2013-12-29 21:47:14 +201259,Koelpin PLC,WJ-02096,Belt,10,65.97,659.70,2014-03-19 04:16:23 +201259,Koelpin PLC,WJ-02096,Belt,2,20.06,40.12,2014-05-31 02:07:45 +296809,Carroll PLC,GS-86623,Shoes,3,62.25,186.75,2014-03-26 00:33:22 +659366,Waelchi-Fahey,KV-99194,Shirt,6,86.20,517.20,2013-11-14 19:38:21 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,14,23.97,335.58,2013-12-01 12:17:58 +115138,Gorczany-Hahn,QN-82852,Belt,10,10.06,100.60,2014-03-08 10:50:44 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,7,34.71,242.97,2014-04-29 04:10:38 +929400,"Senger, Upton and Breitenberg",AS-93055,Shirt,14,31.36,439.04,2014-01-12 16:01:32 +555594,"Ernser, Cruickshank and Lind",LW-86841,Shoes,1,96.74,96.74,2014-04-30 16:25:44 +524021,Hegmann and Sons,QN-82852,Belt,1,93.93,93.93,2014-03-18 14:44:49 +676847,Hamill-Hackett,AS-93055,Shirt,9,58.32,524.88,2013-12-16 15:10:41 +296809,Carroll PLC,LL-46261,Shoes,8,58.48,467.84,2014-05-31 00:30:56 +758133,"Kihn, McClure and Denesik",WJ-02096,Belt,6,68.70,412.20,2013-12-07 08:40:13 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,4,65.73,262.92,2014-06-04 13:29:57 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,8,60.40,483.20,2013-12-26 04:26:05 +093356,Waters-Walker,KV-99194,Shirt,20,49.97,999.40,2014-04-28 20:35:33 +711951,Kilback-Gerlach,KV-99194,Shirt,19,38.38,729.22,2014-05-25 09:18:43 +734922,Berge LLC,LW-86841,Shoes,11,72.20,794.20,2013-11-13 21:15:53 +659366,Waelchi-Fahey,KV-99194,Shirt,13,32.24,419.12,2013-12-22 05:25:56 +750461,"Volkman, Goyette and Lemke",LL-46261,Shoes,8,95.39,763.12,2014-01-12 00:59:09 +659366,Waelchi-Fahey,WJ-02096,Belt,5,73.03,365.15,2014-01-23 12:48:34 +296809,Carroll PLC,VG-32047,Shirt,11,33.31,366.41,2014-07-29 15:09:19 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,3,65.52,196.56,2014-04-02 22:23:07 +304860,Huel-Haag,GS-86623,Shoes,5,45.24,226.20,2013-12-12 03:58:09 +304860,Huel-Haag,FK-71853,Shirt,20,81.79,1635.80,2014-09-23 04:52:44 +524021,Hegmann and Sons,AS-93055,Shirt,7,91.68,641.76,2013-11-10 14:15:25 +299771,"Kuphal, Zieme and Kub",GS-86623,Shoes,16,68.37,1093.92,2014-01-25 17:14:26 +296809,Carroll PLC,GS-86623,Shoes,20,66.43,1328.60,2013-12-30 09:47:58 +929400,"Senger, Upton and Breitenberg",FK-71853,Shirt,3,97.08,291.24,2014-01-28 10:18:57 +659366,Waelchi-Fahey,LW-86841,Shoes,11,99.58,1095.38,2014-08-16 12:51:50 +850140,Kunze Inc,FK-71853,Shirt,6,63.84,383.04,2014-01-06 17:32:46 +758133,"Kihn, McClure and Denesik",FK-71853,Shirt,11,75.07,825.77,2014-06-23 22:07:37 +734922,Berge LLC,FK-71853,Shirt,6,17.54,105.24,2014-08-19 04:51:46 +115138,Gorczany-Hahn,KV-99194,Shirt,19,71.61,1360.59,2014-06-11 12:52:36 +995267,Cole-Eichmann,QN-82852,Belt,17,92.49,1572.33,2013-12-30 08:52:54 +995267,Cole-Eichmann,LW-86841,Shoes,1,40.04,40.04,2014-05-04 08:13:07 +758133,"Kihn, McClure and Denesik",KV-99194,Shirt,6,92.02,552.12,2014-06-20 23:33:17 +093356,Waters-Walker,KV-99194,Shirt,12,66.41,796.92,2014-04-02 00:13:13 +995267,Cole-Eichmann,GS-86623,Shoes,13,53.32,693.16,2013-11-09 01:35:47 +299771,"Kuphal, Zieme and Kub",LL-46261,Shoes,7,48.69,340.83,2014-07-29 18:34:42 +734922,Berge LLC,WJ-02096,Belt,18,75.81,1364.58,2013-12-08 08:54:42 +995267,Cole-Eichmann,MJ-21460,Shoes,4,89.88,359.52,2014-06-28 09:15:38 +524021,Hegmann and Sons,LW-86841,Shoes,10,73.73,737.30,2014-10-08 20:26:26 +296809,Carroll PLC,AS-93055,Shirt,19,67.10,1274.90,2014-06-20 16:14:34 +659366,Waelchi-Fahey,WJ-02096,Belt,17,62.47,1061.99,2014-06-16 14:44:12 +758133,"Kihn, McClure and Denesik",QN-82852,Belt,12,29.83,357.96,2014-01-27 07:20:04 +758133,"Kihn, McClure and Denesik",QN-82852,Belt,18,24.57,442.26,2014-04-03 13:47:21 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,1,27.41,27.41,2014-08-10 21:23:09 +098022,Heidenreich-Bosco,GS-86623,Shoes,9,92.90,836.10,2014-05-16 07:08:48 +093356,Waters-Walker,AS-93055,Shirt,9,95.16,856.44,2013-12-03 07:38:11 +929400,"Senger, Upton and Breitenberg",FK-71853,Shirt,7,77.52,542.64,2014-08-26 18:28:56 +711951,Kilback-Gerlach,MJ-21460,Shoes,14,40.64,568.96,2014-10-21 15:55:43 +995267,Cole-Eichmann,GS-86623,Shoes,5,54.09,270.45,2014-10-19 21:08:59 +115138,Gorczany-Hahn,FK-71853,Shirt,17,62.60,1064.20,2013-12-15 18:40:06 +758133,"Kihn, McClure and Denesik",WJ-02096,Belt,18,93.91,1690.38,2014-08-11 18:42:50 +711951,Kilback-Gerlach,LW-86841,Shoes,11,29.20,321.20,2013-12-26 04:44:50 +304860,Huel-Haag,AS-93055,Shirt,9,23.99,215.91,2014-08-04 09:20:38 +929400,"Senger, Upton and Breitenberg",LW-86841,Shoes,16,92.41,1478.56,2014-05-25 15:09:33 +555594,"Ernser, Cruickshank and Lind",LW-86841,Shoes,2,17.89,35.78,2014-08-30 15:52:20 +676847,Hamill-Hackett,LL-46261,Shoes,19,47.71,906.49,2013-12-16 00:12:31 +850140,Kunze Inc,WJ-02096,Belt,9,76.78,691.02,2013-12-29 01:08:35 +750461,"Volkman, Goyette and Lemke",GS-86623,Shoes,18,76.54,1377.72,2014-01-21 02:04:48 +304860,Huel-Haag,AS-93055,Shirt,5,63.59,317.95,2014-02-08 20:17:34 +995267,Cole-Eichmann,LL-46261,Shoes,20,53.25,1065.00,2013-12-10 12:10:01 +201259,Koelpin PLC,LL-46261,Shoes,7,91.20,638.40,2014-02-28 18:14:54 +296809,Carroll PLC,LW-86841,Shoes,8,95.17,761.36,2014-07-18 09:26:00 +524021,Hegmann and Sons,WJ-02096,Belt,11,54.79,602.69,2014-05-20 14:10:47 +201259,Koelpin PLC,LL-46261,Shoes,3,62.68,188.04,2014-01-14 23:34:45 +676847,Hamill-Hackett,GS-86623,Shoes,10,72.15,721.50,2014-04-07 09:45:23 +305803,"Davis, Kshlerin and Reilly",VG-32047,Shirt,1,78.93,78.93,2014-02-24 00:46:07 +563905,"Kerluke, Reilly and Bechtelar",LL-46261,Shoes,20,37.75,755.00,2013-12-24 08:34:32 +563905,"Kerluke, Reilly and Bechtelar",LL-46261,Shoes,6,41.95,251.70,2013-12-09 23:19:11 +676847,Hamill-Hackett,LW-86841,Shoes,11,91.04,1001.44,2014-05-30 04:37:34 +201259,Koelpin PLC,MJ-21460,Shoes,18,29.75,535.50,2014-10-10 12:44:46 +929400,"Senger, Upton and Breitenberg",LW-86841,Shoes,4,46.09,184.36,2014-07-23 09:02:37 +929400,"Senger, Upton and Breitenberg",KV-99194,Shirt,17,94.19,1601.23,2014-01-17 12:05:59 +524021,Hegmann and Sons,AS-93055,Shirt,9,76.23,686.07,2014-03-22 11:25:47 +296809,Carroll PLC,LL-46261,Shoes,12,39.49,473.88,2014-05-22 17:50:01 +734922,Berge LLC,KV-99194,Shirt,6,88.31,529.86,2013-12-23 16:08:03 +734922,Berge LLC,VG-32047,Shirt,11,58.29,641.19,2014-04-23 09:49:39 +850140,Kunze Inc,KV-99194,Shirt,17,80.50,1368.50,2014-08-21 15:51:34 +659366,Waelchi-Fahey,VG-32047,Shirt,4,40.80,163.20,2014-04-26 23:38:33 +524021,Hegmann and Sons,AS-93055,Shirt,7,73.69,515.83,2014-09-11 02:00:52 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,3,63.58,190.74,2014-04-20 20:45:20 +563905,"Kerluke, Reilly and Bechtelar",FK-71853,Shirt,1,65.61,65.61,2013-10-30 09:34:40 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,13,72.07,936.91,2014-02-22 13:36:56 +524021,Hegmann and Sons,MJ-21460,Shoes,14,36.60,512.40,2014-07-01 22:27:00 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,14,38.93,545.02,2013-12-23 14:57:03 +734922,Berge LLC,FK-71853,Shirt,7,51.72,362.04,2013-12-07 09:43:31 +304860,Huel-Haag,FK-71853,Shirt,14,51.11,715.54,2013-12-18 06:44:56 +555594,"Ernser, Cruickshank and Lind",LW-86841,Shoes,4,93.90,375.60,2013-11-16 08:42:24 +995267,Cole-Eichmann,LW-86841,Shoes,15,17.68,265.20,2013-11-04 20:12:32 +850140,Kunze Inc,FK-71853,Shirt,11,85.24,937.64,2014-07-15 19:12:33 +995267,Cole-Eichmann,QN-82852,Belt,2,53.38,106.76,2014-09-12 09:29:52 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,12,39.64,475.68,2014-10-15 01:53:52 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,6,83.60,501.60,2013-11-27 21:04:11 +304860,Huel-Haag,FK-71853,Shirt,8,74.64,597.12,2014-03-06 03:36:31 +299771,"Kuphal, Zieme and Kub",AS-93055,Shirt,18,13.67,246.06,2014-05-11 20:21:19 +850140,Kunze Inc,LL-46261,Shoes,11,72.69,799.59,2013-10-23 15:54:16 +750461,"Volkman, Goyette and Lemke",WJ-02096,Belt,7,23.04,161.28,2014-09-01 01:15:01 +676847,Hamill-Hackett,AS-93055,Shirt,3,50.86,152.58,2014-10-04 23:43:05 +676847,Hamill-Hackett,MJ-21460,Shoes,6,17.46,104.76,2014-05-22 06:36:25 +093356,Waters-Walker,QN-82852,Belt,11,44.93,494.23,2014-06-19 04:21:18 +850140,Kunze Inc,LW-86841,Shoes,18,44.87,807.66,2014-07-12 18:59:33 +750461,"Volkman, Goyette and Lemke",WJ-02096,Belt,6,54.49,326.94,2014-04-14 11:01:03 +995267,Cole-Eichmann,VG-32047,Shirt,9,41.58,374.22,2014-06-21 21:58:56 +850140,Kunze Inc,LL-46261,Shoes,8,80.60,644.80,2013-12-05 20:18:00 +524021,Hegmann and Sons,MJ-21460,Shoes,19,67.55,1283.45,2014-06-21 20:12:03 +305803,"Davis, Kshlerin and Reilly",WJ-02096,Belt,5,16.32,81.60,2013-11-17 08:52:44 +299771,"Kuphal, Zieme and Kub",VG-32047,Shirt,15,21.39,320.85,2013-12-07 12:59:30 +995267,Cole-Eichmann,QN-82852,Belt,19,99.90,1898.10,2014-04-23 22:30:58 +758133,"Kihn, McClure and Denesik",AS-93055,Shirt,7,48.05,336.35,2014-02-04 09:34:00 +758133,"Kihn, McClure and Denesik",QN-82852,Belt,18,94.04,1692.72,2014-07-25 18:30:19 +555594,"Ernser, Cruickshank and Lind",AS-93055,Shirt,15,94.00,1410.00,2014-07-22 11:45:36 +201259,Koelpin PLC,GS-86623,Shoes,5,26.55,132.75,2013-11-22 05:59:05 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,5,64.85,324.25,2014-05-13 16:03:58 +734922,Berge LLC,QN-82852,Belt,5,16.73,83.65,2014-03-01 13:41:40 +555594,"Ernser, Cruickshank and Lind",LL-46261,Shoes,7,46.60,326.20,2014-09-06 15:20:19 +098022,Heidenreich-Bosco,QN-82852,Belt,6,48.13,288.78,2013-11-04 03:41:41 +296809,Carroll PLC,FK-71853,Shirt,3,55.60,166.80,2013-11-27 18:35:28 +296809,Carroll PLC,LL-46261,Shoes,19,78.56,1492.64,2014-07-19 20:45:37 +201259,Koelpin PLC,QN-82852,Belt,5,25.46,127.30,2013-10-23 07:39:47 +563905,"Kerluke, Reilly and Bechtelar",WJ-02096,Belt,9,43.28,389.52,2014-08-24 22:30:54 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,15,41.15,617.25,2014-02-12 05:07:04 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,19,39.29,746.51,2014-03-21 14:27:33 +758133,"Kihn, McClure and Denesik",QN-82852,Belt,9,46.44,417.96,2014-07-02 06:59:14 +659366,Waelchi-Fahey,QN-82852,Belt,1,95.03,95.03,2014-03-31 10:31:43 +098022,Heidenreich-Bosco,FK-71853,Shirt,16,82.77,1324.32,2014-07-21 08:11:22 +676847,Hamill-Hackett,LL-46261,Shoes,6,72.06,432.36,2014-08-10 14:34:54 +659366,Waelchi-Fahey,MJ-21460,Shoes,5,43.64,218.20,2014-01-30 19:04:33 +299771,"Kuphal, Zieme and Kub",LW-86841,Shoes,2,76.42,152.84,2014-09-09 14:28:18 +659366,Waelchi-Fahey,VG-32047,Shirt,11,25.74,283.14,2014-02-06 22:09:58 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,2,40.68,81.36,2014-06-20 03:39:40 +659366,Waelchi-Fahey,WJ-02096,Belt,4,12.66,50.64,2014-06-01 03:07:50 +929400,"Senger, Upton and Breitenberg",VG-32047,Shirt,3,21.25,63.75,2014-03-08 05:49:21 +758133,"Kihn, McClure and Denesik",FK-71853,Shirt,16,96.47,1543.52,2014-03-17 15:44:50 +750461,"Volkman, Goyette and Lemke",GS-86623,Shoes,9,34.83,313.47,2014-01-28 15:52:04 +524021,Hegmann and Sons,KV-99194,Shirt,1,24.90,24.90,2014-07-05 14:02:45 +929400,"Senger, Upton and Breitenberg",KV-99194,Shirt,11,19.26,211.86,2013-12-01 21:23:11 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,7,84.46,591.22,2013-11-15 23:56:38 +850140,Kunze Inc,LW-86841,Shoes,14,62.03,868.42,2014-03-29 03:29:59 +299771,"Kuphal, Zieme and Kub",KV-99194,Shirt,3,79.00,237.00,2013-11-26 08:15:06 +711951,Kilback-Gerlach,KV-99194,Shirt,12,31.44,377.28,2013-12-15 21:44:27 +524021,Hegmann and Sons,WJ-02096,Belt,2,73.96,147.92,2013-12-08 04:33:54 +115138,Gorczany-Hahn,QN-82852,Belt,18,18.41,331.38,2014-05-07 04:59:51 +555594,"Ernser, Cruickshank and Lind",QN-82852,Belt,18,39.11,703.98,2014-01-19 06:06:01 +115138,Gorczany-Hahn,FK-71853,Shirt,5,94.62,473.10,2014-02-14 22:33:04 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,7,50.85,355.95,2014-07-25 14:33:33 +115138,Gorczany-Hahn,AS-93055,Shirt,7,45.14,315.98,2014-04-13 09:02:34 +296809,Carroll PLC,FK-71853,Shirt,6,15.69,94.14,2014-05-09 02:08:03 +098022,Heidenreich-Bosco,QN-82852,Belt,10,76.76,767.60,2013-12-08 18:53:38 +850140,Kunze Inc,LW-86841,Shoes,20,53.03,1060.60,2014-08-20 20:57:38 +304860,Huel-Haag,GS-86623,Shoes,2,78.64,157.28,2014-04-24 06:13:24 +093356,Waters-Walker,QN-82852,Belt,19,72.11,1370.09,2014-02-22 07:22:10 +563905,"Kerluke, Reilly and Bechtelar",GS-86623,Shoes,16,33.21,531.36,2014-09-05 17:43:19 +850140,Kunze Inc,AS-93055,Shirt,8,59.23,473.84,2014-04-15 02:11:56 +093356,Waters-Walker,LL-46261,Shoes,13,81.45,1058.85,2013-11-02 14:31:09 +115138,Gorczany-Hahn,AS-93055,Shirt,3,61.04,183.12,2014-05-26 22:06:38 +850140,Kunze Inc,AS-93055,Shirt,2,39.31,78.62,2014-03-05 15:04:43 +524021,Hegmann and Sons,FK-71853,Shirt,7,60.29,422.03,2014-08-15 15:41:54 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,14,46.43,650.02,2014-05-17 10:02:32 +750461,"Volkman, Goyette and Lemke",WJ-02096,Belt,15,15.12,226.80,2014-03-16 15:37:39 +296809,Carroll PLC,LL-46261,Shoes,8,51.47,411.76,2014-01-09 11:37:20 +734922,Berge LLC,MJ-21460,Shoes,15,91.88,1378.20,2013-12-10 12:02:09 +296809,Carroll PLC,VG-32047,Shirt,16,82.36,1317.76,2014-03-24 12:29:30 +098022,Heidenreich-Bosco,LL-46261,Shoes,8,84.24,673.92,2014-04-18 19:19:35 +659366,Waelchi-Fahey,GS-86623,Shoes,10,88.36,883.60,2014-08-24 23:09:27 +676847,Hamill-Hackett,LW-86841,Shoes,10,47.20,472.00,2014-05-05 18:51:45 +929400,"Senger, Upton and Breitenberg",WJ-02096,Belt,20,51.16,1023.20,2013-10-31 15:48:14 +304860,Huel-Haag,KV-99194,Shirt,3,55.75,167.25,2013-11-22 04:34:56 +201259,Koelpin PLC,MJ-21460,Shoes,13,81.58,1060.54,2014-02-10 01:33:21 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,1,13.47,13.47,2014-08-07 04:18:29 +676847,Hamill-Hackett,VG-32047,Shirt,11,23.33,256.63,2013-12-29 02:31:41 +098022,Heidenreich-Bosco,WJ-02096,Belt,12,84.23,1010.76,2014-01-28 00:34:31 +659366,Waelchi-Fahey,LL-46261,Shoes,17,98.86,1680.62,2014-05-10 02:37:09 +850140,Kunze Inc,KV-99194,Shirt,5,12.07,60.35,2013-10-24 08:39:48 +676847,Hamill-Hackett,AS-93055,Shirt,8,87.50,700.00,2014-01-26 12:58:22 +659366,Waelchi-Fahey,VG-32047,Shirt,8,63.37,506.96,2014-05-02 01:13:09 +524021,Hegmann and Sons,FK-71853,Shirt,9,87.07,783.63,2014-09-10 21:37:02 +098022,Heidenreich-Bosco,KV-99194,Shirt,2,88.57,177.14,2013-12-31 08:53:19 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,1,16.29,16.29,2014-04-25 04:33:22 +201259,Koelpin PLC,GS-86623,Shoes,8,55.16,441.28,2014-08-14 03:02:46 +995267,Cole-Eichmann,MJ-21460,Shoes,20,25.66,513.20,2014-03-24 03:39:51 +098022,Heidenreich-Bosco,LL-46261,Shoes,13,19.69,255.97,2014-01-28 23:58:09 +305803,"Davis, Kshlerin and Reilly",MJ-21460,Shoes,3,71.28,213.84,2014-08-07 10:01:03 +524021,Hegmann and Sons,QN-82852,Belt,6,57.14,342.84,2014-08-24 06:07:33 +659366,Waelchi-Fahey,MJ-21460,Shoes,3,97.92,293.76,2014-08-03 14:44:21 +555594,"Ernser, Cruickshank and Lind",VG-32047,Shirt,9,60.94,548.46,2014-09-14 01:36:31 +093356,Waters-Walker,LL-46261,Shoes,6,51.18,307.08,2014-07-31 17:50:40 +659366,Waelchi-Fahey,FK-71853,Shirt,18,62.58,1126.44,2014-03-31 08:44:34 +750461,"Volkman, Goyette and Lemke",FK-71853,Shirt,13,77.42,1006.46,2014-07-16 00:38:04 +093356,Waters-Walker,LL-46261,Shoes,11,36.49,401.39,2013-12-26 18:47:55 +305803,"Davis, Kshlerin and Reilly",KV-99194,Shirt,17,57.50,977.50,2014-02-25 14:46:40 +296809,Carroll PLC,WJ-02096,Belt,17,76.08,1293.36,2013-11-14 23:35:37 +659366,Waelchi-Fahey,FK-71853,Shirt,14,11.91,166.74,2014-03-09 23:23:06 +850140,Kunze Inc,LW-86841,Shoes,17,82.86,1408.62,2014-10-02 16:34:54 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,16,51.93,830.88,2014-01-17 08:36:29 +299771,"Kuphal, Zieme and Kub",LL-46261,Shoes,17,96.71,1644.07,2014-09-04 18:21:15 +115138,Gorczany-Hahn,QN-82852,Belt,15,25.75,386.25,2013-11-30 12:14:42 +850140,Kunze Inc,AS-93055,Shirt,6,38.77,232.62,2014-06-19 22:24:10 +304860,Huel-Haag,LW-86841,Shoes,6,52.93,317.58,2013-12-03 02:57:43 +711951,Kilback-Gerlach,MJ-21460,Shoes,17,97.99,1665.83,2014-01-15 22:54:28 +659366,Waelchi-Fahey,QN-82852,Belt,10,36.72,367.20,2014-06-18 14:02:05 +734922,Berge LLC,MJ-21460,Shoes,9,84.43,759.87,2014-06-23 09:12:45 +750461,"Volkman, Goyette and Lemke",GS-86623,Shoes,11,68.13,749.43,2014-05-09 09:32:44 +299771,"Kuphal, Zieme and Kub",VG-32047,Shirt,6,92.62,555.72,2014-06-19 12:30:22 +995267,Cole-Eichmann,KV-99194,Shirt,8,51.86,414.88,2013-11-23 02:03:48 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,19,52.45,996.55,2014-08-08 03:00:19 +304860,Huel-Haag,KV-99194,Shirt,19,32.23,612.37,2014-10-02 01:11:44 +563905,"Kerluke, Reilly and Bechtelar",QN-82852,Belt,4,61.06,244.24,2014-05-09 03:27:55 +711951,Kilback-Gerlach,AS-93055,Shirt,11,44.56,490.16,2014-02-23 05:35:58 +115138,Gorczany-Hahn,WJ-02096,Belt,1,58.03,58.03,2013-12-11 14:01:46 +758133,"Kihn, McClure and Denesik",QN-82852,Belt,11,39.89,438.79,2014-05-18 15:53:12 +524021,Hegmann and Sons,MJ-21460,Shoes,18,51.46,926.28,2014-07-08 18:37:36 +676847,Hamill-Hackett,AS-93055,Shirt,12,92.28,1107.36,2014-04-28 21:34:27 +115138,Gorczany-Hahn,FK-71853,Shirt,20,32.53,650.60,2014-10-22 10:04:21 +304860,Huel-Haag,VG-32047,Shirt,6,67.49,404.94,2014-09-17 12:35:31 +296809,Carroll PLC,VG-32047,Shirt,11,14.92,164.12,2014-01-14 05:53:11 +299771,"Kuphal, Zieme and Kub",MJ-21460,Shoes,3,16.50,49.50,2014-08-09 14:56:26 +734922,Berge LLC,WJ-02096,Belt,20,25.09,501.80,2014-02-15 00:17:15 +711951,Kilback-Gerlach,KV-99194,Shirt,20,72.86,1457.20,2013-12-27 03:41:18 +304860,Huel-Haag,WJ-02096,Belt,4,60.95,243.80,2014-01-20 10:14:17 +676847,Hamill-Hackett,QN-82852,Belt,12,47.05,564.60,2013-10-24 07:27:44 +850140,Kunze Inc,VG-32047,Shirt,20,36.00,720.00,2013-11-19 04:49:59 +555594,"Ernser, Cruickshank and Lind",LW-86841,Shoes,3,25.52,76.56,2013-12-15 23:23:29 +098022,Heidenreich-Bosco,QN-82852,Belt,3,43.89,131.67,2014-02-06 22:02:39 +098022,Heidenreich-Bosco,LL-46261,Shoes,6,55.68,334.08,2014-02-25 02:43:31 +734922,Berge LLC,KV-99194,Shirt,13,21.76,282.88,2014-09-16 19:43:28 +659366,Waelchi-Fahey,VG-32047,Shirt,14,85.44,1196.16,2014-06-04 14:34:07 +711951,Kilback-Gerlach,AS-93055,Shirt,20,88.71,1774.20,2014-08-14 19:08:27 +929400,"Senger, Upton and Breitenberg",LW-86841,Shoes,1,32.44,32.44,2014-06-21 04:34:22 +758133,"Kihn, McClure and Denesik",FK-71853,Shirt,12,40.53,486.36,2014-03-06 03:01:26 +711951,Kilback-Gerlach,LL-46261,Shoes,8,41.95,335.60,2014-05-18 00:50:58 +098022,Heidenreich-Bosco,KV-99194,Shirt,3,41.04,123.12,2014-10-09 15:27:45 +750461,"Volkman, Goyette and Lemke",AS-93055,Shirt,4,65.64,262.56,2014-02-15 17:07:56 +734922,Berge LLC,FK-71853,Shirt,4,59.00,236.00,2014-08-15 07:13:09 +296809,Carroll PLC,GS-86623,Shoes,19,20.01,380.19,2013-11-20 14:26:00 +711951,Kilback-Gerlach,LL-46261,Shoes,18,37.06,667.08,2014-07-09 17:04:57 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,8,13.41,107.28,2013-12-21 04:32:13 +115138,Gorczany-Hahn,AS-93055,Shirt,19,36.84,699.96,2014-09-13 06:33:24 +659366,Waelchi-Fahey,KV-99194,Shirt,18,13.47,242.46,2014-03-25 04:34:58 +299771,"Kuphal, Zieme and Kub",LW-86841,Shoes,11,87.09,957.99,2013-10-22 16:08:40 +201259,Koelpin PLC,QN-82852,Belt,19,18.85,358.15,2014-07-02 12:21:25 +850140,Kunze Inc,LW-86841,Shoes,7,56.99,398.93,2014-06-25 22:06:27 +115138,Gorczany-Hahn,AS-93055,Shirt,20,31.99,639.80,2014-09-15 19:14:27 +304860,Huel-Haag,GS-86623,Shoes,14,27.24,381.36,2014-03-14 04:16:47 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,11,51.07,561.77,2014-03-06 09:21:00 +524021,Hegmann and Sons,GS-86623,Shoes,11,40.32,443.52,2014-02-07 07:39:54 +758133,"Kihn, McClure and Denesik",WJ-02096,Belt,19,62.80,1193.20,2014-08-27 15:48:09 +115138,Gorczany-Hahn,LW-86841,Shoes,5,33.56,167.80,2014-09-20 07:43:39 +299771,"Kuphal, Zieme and Kub",FK-71853,Shirt,17,60.22,1023.74,2014-09-26 18:44:51 +296809,Carroll PLC,GS-86623,Shoes,8,21.41,171.28,2014-09-11 18:45:17 +296809,Carroll PLC,KV-99194,Shirt,13,43.03,559.39,2014-01-20 19:43:09 +093356,Waters-Walker,LL-46261,Shoes,11,76.80,844.80,2014-02-23 18:36:40 +850140,Kunze Inc,MJ-21460,Shoes,12,81.66,979.92,2014-09-04 03:23:22 +995267,Cole-Eichmann,FK-71853,Shirt,16,63.20,1011.20,2014-06-22 09:34:54 +711951,Kilback-Gerlach,LW-86841,Shoes,1,95.18,95.18,2013-11-16 10:27:30 +201259,Koelpin PLC,VG-32047,Shirt,10,20.20,202.00,2014-10-02 18:38:33 +305803,"Davis, Kshlerin and Reilly",LL-46261,Shoes,15,59.34,890.10,2013-12-04 02:43:20 +296809,Carroll PLC,WJ-02096,Belt,16,91.77,1468.32,2014-02-23 18:10:13 +734922,Berge LLC,MJ-21460,Shoes,4,87.65,350.60,2014-04-26 20:59:35 +711951,Kilback-Gerlach,LL-46261,Shoes,13,34.40,447.20,2014-04-27 02:17:28 +734922,Berge LLC,LL-46261,Shoes,18,44.89,808.02,2014-05-28 15:41:26 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,15,75.00,1125.00,2014-09-25 18:00:19 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,8,19.05,152.40,2014-01-08 00:39:35 +115138,Gorczany-Hahn,WJ-02096,Belt,5,13.31,66.55,2014-06-02 11:41:36 +304860,Huel-Haag,KV-99194,Shirt,5,58.12,290.60,2014-08-02 12:08:32 +676847,Hamill-Hackett,LL-46261,Shoes,19,58.95,1120.05,2014-03-12 06:27:02 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,16,51.28,820.48,2013-12-19 05:40:26 +659366,Waelchi-Fahey,KV-99194,Shirt,2,35.44,70.88,2013-10-25 14:47:00 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,16,79.23,1267.68,2014-09-20 09:36:03 +524021,Hegmann and Sons,LW-86841,Shoes,2,19.42,38.84,2014-08-23 03:19:29 +093356,Waters-Walker,KV-99194,Shirt,9,70.81,637.29,2014-01-30 11:06:55 +555594,"Ernser, Cruickshank and Lind",WJ-02096,Belt,10,27.65,276.50,2014-08-05 02:49:13 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,18,53.57,964.26,2013-11-09 07:53:05 +098022,Heidenreich-Bosco,GS-86623,Shoes,19,87.08,1654.52,2014-09-20 22:36:07 +304860,Huel-Haag,AS-93055,Shirt,3,88.25,264.75,2013-11-22 02:08:50 +115138,Gorczany-Hahn,MJ-21460,Shoes,16,74.73,1195.68,2014-10-08 07:30:19 +758133,"Kihn, McClure and Denesik",VG-32047,Shirt,15,39.14,587.10,2014-08-02 17:24:19 +850140,Kunze Inc,LW-86841,Shoes,5,63.32,316.60,2014-02-13 19:42:05 +305803,"Davis, Kshlerin and Reilly",LW-86841,Shoes,7,18.99,132.93,2014-04-17 16:31:36 +093356,Waters-Walker,FK-71853,Shirt,6,48.34,290.04,2014-10-07 11:12:45 +093356,Waters-Walker,MJ-21460,Shoes,1,76.61,76.61,2014-05-07 10:17:28 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,11,10.12,111.32,2014-03-29 05:53:03 +995267,Cole-Eichmann,AS-93055,Shirt,20,96.14,1922.80,2014-08-02 19:08:15 +304860,Huel-Haag,MJ-21460,Shoes,10,69.19,691.90,2014-01-07 14:36:19 +563905,"Kerluke, Reilly and Bechtelar",VG-32047,Shirt,16,64.75,1036.00,2014-02-11 09:04:11 +201259,Koelpin PLC,LW-86841,Shoes,1,62.87,62.87,2014-01-01 22:40:22 +299771,"Kuphal, Zieme and Kub",QN-82852,Belt,13,13.05,169.65,2014-09-04 16:33:40 +093356,Waters-Walker,KV-99194,Shirt,2,96.80,193.60,2014-07-13 09:44:29 +098022,Heidenreich-Bosco,LL-46261,Shoes,6,23.04,138.24,2014-03-02 03:45:46 +850140,Kunze Inc,KV-99194,Shirt,8,35.98,287.84,2014-05-20 14:38:17 +115138,Gorczany-Hahn,AS-93055,Shirt,9,14.71,132.39,2014-03-01 13:31:22 +995267,Cole-Eichmann,GS-86623,Shoes,2,43.85,87.70,2014-06-09 21:31:11 +563905,"Kerluke, Reilly and Bechtelar",LW-86841,Shoes,9,52.42,471.78,2014-05-22 11:49:32 +098022,Heidenreich-Bosco,QN-82852,Belt,15,20.07,301.05,2014-06-27 12:15:09 +659366,Waelchi-Fahey,QN-82852,Belt,17,56.27,956.59,2014-02-09 14:52:49 +098022,Heidenreich-Bosco,QN-82852,Belt,8,79.20,633.60,2014-06-07 18:59:21 +555594,"Ernser, Cruickshank and Lind",MJ-21460,Shoes,7,97.93,685.51,2014-04-05 00:29:44 +524021,Hegmann and Sons,QN-82852,Belt,8,49.06,392.48,2014-05-03 20:50:41 +750461,"Volkman, Goyette and Lemke",GS-86623,Shoes,5,62.46,312.30,2014-05-13 14:52:47 +305803,"Davis, Kshlerin and Reilly",FK-71853,Shirt,20,11.96,239.20,2014-09-04 18:27:56 +201259,Koelpin PLC,KV-99194,Shirt,12,91.33,1095.96,2014-03-01 09:46:48 +115138,Gorczany-Hahn,WJ-02096,Belt,3,93.50,280.50,2014-08-25 21:36:41 +098022,Heidenreich-Bosco,GS-86623,Shoes,19,26.88,510.72,2014-04-07 07:12:29 +555594,"Ernser, Cruickshank and Lind",MJ-21460,Shoes,8,49.15,393.20,2014-10-12 21:49:47 +098022,Heidenreich-Bosco,WJ-02096,Belt,7,52.04,364.28,2013-11-07 19:58:39 +995267,Cole-Eichmann,KV-99194,Shirt,13,97.04,1261.52,2014-06-17 08:28:31 +555594,"Ernser, Cruickshank and Lind",AS-93055,Shirt,6,29.88,179.28,2014-09-04 14:54:23 +524021,Hegmann and Sons,KV-99194,Shirt,6,62.36,374.16,2014-01-07 03:14:00 +524021,Hegmann and Sons,AS-93055,Shirt,15,88.44,1326.60,2014-10-15 01:54:05 +711951,Kilback-Gerlach,KV-99194,Shirt,16,79.71,1275.36,2014-08-30 06:23:27 +676847,Hamill-Hackett,LW-86841,Shoes,11,96.57,1062.27,2014-01-09 13:36:39 +296809,Carroll PLC,VG-32047,Shirt,12,79.85,958.20,2014-01-16 11:38:27 +093356,Waters-Walker,AS-93055,Shirt,2,47.74,95.48,2014-03-22 02:00:16 +995267,Cole-Eichmann,KV-99194,Shirt,18,97.33,1751.94,2014-01-16 12:27:14 +676847,Hamill-Hackett,FK-71853,Shirt,18,98.39,1771.02,2014-01-06 08:14:31 +995267,Cole-Eichmann,LL-46261,Shoes,2,94.06,188.12,2013-12-16 21:29:38 +929400,"Senger, Upton and Breitenberg",LL-46261,Shoes,11,19.17,210.87,2013-10-26 13:17:07 +305803,"Davis, Kshlerin and Reilly",GS-86623,Shoes,18,20.74,373.32,2013-10-22 20:01:38 +995267,Cole-Eichmann,AS-93055,Shirt,7,80.69,564.83,2014-01-10 21:42:10 +093356,Waters-Walker,AS-93055,Shirt,15,84.23,1263.45,2014-07-18 04:09:08 +524021,Hegmann and Sons,GS-86623,Shoes,9,39.14,352.26,2013-11-17 23:11:28 +929400,"Senger, Upton and Breitenberg",VG-32047,Shirt,10,67.36,673.60,2013-11-02 03:09:24 +734922,Berge LLC,VG-32047,Shirt,14,93.45,1308.30,2014-02-10 07:13:32 +201259,Koelpin PLC,LL-46261,Shoes,8,62.68,501.44,2013-11-10 16:34:17 +555594,"Ernser, Cruickshank and Lind",QN-82852,Belt,13,86.33,1122.29,2013-10-23 02:35:36 +711951,Kilback-Gerlach,GS-86623,Shoes,1,25.23,25.23,2014-02-15 18:56:38 +555594,"Ernser, Cruickshank and Lind",KV-99194,Shirt,14,93.56,1309.84,2014-10-21 14:14:21 +296809,Carroll PLC,LW-86841,Shoes,19,22.36,424.84,2014-07-08 00:03:47 +711951,Kilback-Gerlach,LW-86841,Shoes,13,72.82,946.66,2014-02-10 18:44:09 +098022,Heidenreich-Bosco,AS-93055,Shirt,4,22.33,89.32,2014-05-22 10:55:51 +929400,"Senger, Upton and Breitenberg",MJ-21460,Shoes,5,41.67,208.35,2013-12-04 08:24:01 +296809,Carroll PLC,MJ-21460,Shoes,13,29.69,385.97,2014-03-25 09:03:04 +758133,"Kihn, McClure and Denesik",GS-86623,Shoes,20,20.83,416.60,2014-09-07 19:59:58 +524021,Hegmann and Sons,LW-86841,Shoes,12,96.49,1157.88,2014-08-24 02:46:41 +758133,"Kihn, McClure and Denesik",WJ-02096,Belt,15,51.35,770.25,2014-05-13 12:39:44 +563905,"Kerluke, Reilly and Bechtelar",GS-86623,Shoes,16,90.96,1455.36,2013-11-02 09:19:40 +711951,Kilback-Gerlach,LW-86841,Shoes,12,22.81,273.72,2014-09-17 02:46:57 +093356,Waters-Walker,AS-93055,Shirt,19,28.76,546.44,2013-12-19 19:43:07 +098022,Heidenreich-Bosco,VG-32047,Shirt,2,35.71,71.42,2014-07-03 03:16:33 +296809,Carroll PLC,LL-46261,Shoes,9,32.75,294.75,2014-02-08 10:48:21 +758133,"Kihn, McClure and Denesik",LW-86841,Shoes,2,92.23,184.46,2014-02-18 03:57:38 +524021,Hegmann and Sons,MJ-21460,Shoes,12,18.24,218.88,2014-05-01 16:46:03 +305803,"Davis, Kshlerin and Reilly",AS-93055,Shirt,6,49.81,298.86,2013-11-01 16:31:25 +304860,Huel-Haag,QN-82852,Belt,2,22.38,44.76,2014-01-23 23:47:01 +929400,"Senger, Upton and Breitenberg",QN-82852,Belt,10,25.65,256.50,2013-12-20 14:10:18 +299771,"Kuphal, Zieme and Kub",QN-82852,Belt,12,37.50,450.00,2013-12-30 04:04:50 +115138,Gorczany-Hahn,VG-32047,Shirt,20,72.35,1447.00,2014-08-11 19:02:14 +758133,"Kihn, McClure and Denesik",LL-46261,Shoes,2,48.21,96.42,2014-09-16 16:12:02 +711951,Kilback-Gerlach,VG-32047,Shirt,1,91.96,91.96,2013-10-23 15:08:31 +929400,"Senger, Upton and Breitenberg",GS-86623,Shoes,7,62.27,435.89,2013-12-30 01:55:14 +093356,Waters-Walker,KV-99194,Shirt,20,99.74,1994.80,2014-04-18 15:39:12 +098022,Heidenreich-Bosco,QN-82852,Belt,15,82.82,1242.30,2014-03-27 04:42:40 +734922,Berge LLC,GS-86623,Shoes,8,85.04,680.32,2014-02-26 14:43:51 +995267,Cole-Eichmann,LW-86841,Shoes,10,73.24,732.40,2014-06-07 10:04:53 +093356,Waters-Walker,AS-93055,Shirt,9,68.62,617.58,2014-08-12 08:06:21 +304860,Huel-Haag,QN-82852,Belt,1,57.33,57.33,2014-08-27 11:27:28 +850140,Kunze Inc,KV-99194,Shirt,9,27.16,244.44,2014-02-08 06:22:34 +659366,Waelchi-Fahey,LW-86841,Shoes,10,56.56,565.60,2014-10-01 11:38:04 +296809,Carroll PLC,WJ-02096,Belt,20,14.37,287.40,2014-07-20 17:22:03 +758133,"Kihn, McClure and Denesik",WJ-02096,Belt,11,60.50,665.50,2014-08-03 10:39:51 +850140,Kunze Inc,GS-86623,Shoes,16,19.66,314.56,2014-05-03 21:18:15 +093356,Waters-Walker,GS-86623,Shoes,13,90.95,1182.35,2014-06-14 12:43:51 +304860,Huel-Haag,LL-46261,Shoes,9,98.22,883.98,2014-07-26 01:10:57 +098022,Heidenreich-Bosco,LW-86841,Shoes,14,74.83,1047.62,2014-06-27 05:58:33 diff --git "a/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/threads.py" "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/threads.py" new file mode 100644 index 0000000..06f6cc7 --- /dev/null +++ "b/6.- Comunicaci\303\263n, Visualizaci\303\263n y Productos de Datos/threads.py" @@ -0,0 +1,44 @@ +from functools import partial +import time +from concurrent.futures import ThreadPoolExecutor +from tornado import gen +from bokeh.document import without_document_lock +from bokeh.models import ColumnDataSource +from bokeh.plotting import curdoc, figure + +source = ColumnDataSource(data=dict(x=[0], y=[0], color=["blue"])) +i = 0 +doc = curdoc() +executor = ThreadPoolExecutor(max_workers=2) + +def blocking_task(i): + time.sleep(1) + return i + +# the unlocked callback uses this locked callback to safely update +@gen.coroutine +def locked_update(i): + source.stream(dict(x=[source.data['x'][-1]+1], y=[i], color=["blue"])) + +# this unclocked callback will not prevent other session callbacks from +# executing while it is in flight +@gen.coroutine +@without_document_lock +def unlocked_task(): + global i + i += 1 + res = yield executor.submit(blocking_task, i) + doc.add_next_tick_callback(partial(locked_update, i=res)) + +@gen.coroutine +def update(): + source.stream(dict(x=[source.data['x'][-1]+1], y=[i], color=["red"])) + +p = figure(x_range=[0, 100], y_range=[0,20]) +l = p.circle(x='x', y='y', color='color', source=source) + +doc.add_periodic_callback(unlocked_task, 1000) +doc.add_periodic_callback(update, 200) +doc.add_root(p) + +