plotagem_visualizacao.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "plotagem_visualizacao.ipynb",
      "provenance": [],
      "mount_file_id": "1LdR_P-fXfILLStGzQaJF8-hVZMLnPeJW",
      "authorship_tag": "ABX9TyPLoDqa88w7KBd8qE/Dxs9E",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/anicelysantos/book-python-para-analise-de-dados/blob/main/plotagem_visualizacao.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nqx80TS3xXxN"
      },
      "source": [
        "***Python para análise de dados - Capítulo 9***\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mBVO9oIPZBQ4"
      },
      "source": [
        "# Imports"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eXIUKsF7xWp_"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cwyHqhDpBjr5"
      },
      "source": [
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6rYEYr1_M-e7"
      },
      "source": [
        "from numpy.random import randn"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2CoPrba7HVhH"
      },
      "source": [
        "from datetime import datetime"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i1xYVm_OOddT"
      },
      "source": [
        "#Importar para salvar figuras em objetos do tipo artigo\n",
        "from io import BytesIO"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xHPg_2kJXENV"
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M_Bv7W0L8UOP"
      },
      "source": [
        "# Introdução rápida à API da matplotlib"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vGBo3o2_7h3O",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6016ca1a-f80a-4dc2-a72d-60b2e596da7b"
      },
      "source": [
        "data = np.arange(10)\n",
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "t2dLRX7k8iIW",
        "outputId": "29ab5c74-c344-4010-91b6-c55f65fb689b"
      },
      "source": [
        "plt.plot(data)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fbf3a616550>]"
            ]
          },
          "metadata": {},
          "execution_count": 60
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "STppnrNe8w4L"
      },
      "source": [
        "**Figuras e subplotagens**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 151
        },
        "id": "SFJl5uYV8l3F",
        "outputId": "aae46e1a-b9af-48d4-b83e-30cefa110de8"
      },
      "source": [
        "fig = plt.figure()\n",
        "ax1 = fig.add_subplot(2,2,1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gh8G8dqJ9Ai2"
      },
      "source": [
        "ax2 = fig.add_subplot(2,2,2)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GfiHyUYe9jSu"
      },
      "source": [
        "ax3 = fig.add_subplot(2,2,3)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "4mf_u2iCAArf",
        "outputId": "edee8ee6-11fd-4482-895c-5037821c97e7"
      },
      "source": [
        "fig = plt.figure()\n",
        "ax1 = fig.add_subplot(2,2,1)\n",
        "ax2 = fig.add_subplot(2,2,2)\n",
        "ax3 = fig.add_subplot(2,2,3)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAD8CAYAAAB6paOMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAWoElEQVR4nO3df8yddX3/8efLIpCh02q7xJQO6laF6hbRE3QxmS4KVL5Ja+KylYUIhq0ZE5foN9+ExT9Yyj9uZnMx6Sb9bo26ZBTlj2/uZRrCVyAkxmpPA0PpgtbOSTvzpVrkHxwIvL9/XBfz9OZu74ue6z7nbq/nIznpuX6d9+fced993ef6ca5UFZKk4XrFvAcgSZovg0CSBs4gkKSBMwgkaeAMAkkaOINAkgZu2SBIsjfJE0m+c4rlSfLZJIeTPJLk7RPLbkjyvfZxQ58Dl6Zlb0uNLp8IPg9sPc3yDwCb28dO4O8AkrwOuA14J3AlcFuStdMMVurZ57G3peWDoKoeBE6cZpXtwBersR94bZI3ANcA91bViap6EriX0//SSTNlb0uN83p4jQ3A4xPTR9t5p5r/Ekl20vzFxUUXXfSOyy67rIdhSUs7ePDgj6tqfYdV7W2dNV5GX79EH0EwtaraA+wBGI1GNR6P5zwincuS/MesatnbmpVp+rqPs4aOARsnpi9u551qvnS2sLc1CH0EwQLw4fYMi3cBT1XVj4B7gKuTrG0PpF3dzpPOFva2BmHZXUNJ7gTeC6xLcpTmbIlXAlTV54CvANcCh4GngY+0y04kuR040L7Urqo63YE5aabsbamxbBBU1XXLLC/go6dYthfYe2ZDk1aWvS01vLJYkgbOIJCkgTMIJGngDAJJGjiDQJIGziCQpIEzCCRp4AwCSRo4g0CSBs4gkKSBMwgkaeAMAkkaOINAkgbOIJCkgTMIJGngDAJJGrhOQZBka5LHkhxOcusSyz+T5OH28d0kP51Y9vzEsoU+By9Nw76WGl1uVbkG2A1cBRwFDiRZqKpDL65TVR+fWP9jwBUTL/Gzqnpbf0OWpmdfS7/Q5RPBlcDhqjpSVc8C+4Dtp1n/OuDOPgYnrSD7Wmp1CYINwOMT00fbeS+R5BJgE3DfxOwLk4yT7E/ywVNst7NdZ3z8+PGOQ5emsuJ93W5rb2vV6/tg8Q7g7qp6fmLeJVU1Av4A+Jskv7Z4o6raU1WjqhqtX7++5yFJUzujvgZ7W2eHLkFwDNg4MX1xO28pO1j08bmqjrX/HgEe4OT9rNK82NdSq0sQHAA2J9mU5HyaX4qXnCWR5DJgLfCNiXlrk1zQPl8HvBs4tHhbaQ7sa6m17FlDVfVckluAe4A1wN6qejTJLmBcVS/+8uwA9lVVTWx+OXBHkhdoQudTk2dlSPNiX0u/kJP7e/5Go1GNx+N5D0PnsCQH2/37M2VvayVN09deWSxJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNXKcgSLI1yWNJDie5dYnlNyY5nuTh9vGHE8tuSPK99nFDn4OXpmVvSx1uVZlkDbAbuAo4ChxIsrDErfnuqqpbFm37OuA2YAQUcLDd9sleRi9Nwd6WGl0+EVwJHK6qI1X1LLAP2N7x9a8B7q2qE+0vyL3A1jMbqtQ7e1uiWxBsAB6fmD7azlvsQ0keSXJ3ko0vZ9skO5OMk4yPHz/ecejS1Oxtif4OFv8zcGlV/SbNX0ZfeDkbV9WeqhpV1Wj9+vU9DUnqhb2tc16XIDgGbJyYvrid99+q6idV9Uw7+ffAO7puK82RvS3RLQgOAJuTbEpyPrADWJhcIckbJia3Af/WPr8HuDrJ2iRrgavbedJqYG9LdDhrqKqeS3ILTZOvAfZW1aNJdgHjqloA/jTJNuA54ARwY7vtiSS30/zCAeyqqhMr8D6kl83elhqpqnmP4SSj0ajG4/G8h6FzWJKDVTWadV17Wytpmr72ymJJGjiDQJIGziCQpIEzCCRp4AwCSRo4g0CSBs4gkKSBMwgkaeAMAkkaOINAkgbOIJCkgTMIJGngDAJJGjiDQJIGziCQpIHrFARJtiZ5LMnhJLcusfwTSQ61N/j+WpJLJpY9n+Th9rGweFtpXuxrqbHsHcqSrAF2A1cBR4EDSRaq6tDEag8Bo6p6OsnNwF8Cv98u+1lVva3ncUtTsa+lX+jyieBK4HBVHamqZ4F9wPbJFarq/qp6up3cT3Mjb2k1s6+lVpcg2AA8PjF9tJ13KjcBX52YvjDJOMn+JB9caoMkO9t1xsePH+8wJGlqK97XYG/r7LDsrqGXI8n1wAh4z8TsS6rqWJI3Avcl+XZVfX9yu6raA+yB5r6ufY5JmtaZ9jXY2zo7dPlEcAzYODF9cTvvJEneD3wS2FZVz7w4v6qOtf8eAR4ArphivFJf7Gup1SUIDgCbk2xKcj6wAzjpLIkkVwB30PyyPDExf22SC9rn64B3A5MH46R5sa+l1rK7hqrquSS3APcAa4C9VfVokl3AuKoWgE8DrwK+nATgh1W1DbgcuCPJCzSh86lFZ2VIc2FfS7+QqtW123I0GtV4PJ73MHQOS3KwqkazrmtvayVN09deWSxJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNXKcgSLI1yWNJDie5dYnlFyS5q13+zSSXTiz7s3b+Y0mu6W/o0vTsbalDECRZA+wGPgBsAa5LsmXRajcBT1bVrwOfAf6i3XYLzb1g3wJsBf62fT1p7uxtqdHlE8GVwOGqOlJVzwL7gO2L1tkOfKF9fjfwvjQ3ed0O7KuqZ6rq34HD7etJq4G9LdHh5vXABuDxiemjwDtPtU57U/CngNe38/cv2nbD4gJJdgI728lnknyn0+j7tw748YDqzrP2PN/zm9t/7W3rnku137z8KkvrEgQrrqr2AHsAkozncWPxedb2Pc++9qxq2dvDqjvP2tP0dZddQ8eAjRPTF7fzllwnyXnAa4CfdNxWmhd7W6JbEBwANifZlOR8mgNkC4vWWQBuaJ//LnBfVVU7f0d75sUmYDPwrX6GLk3N3pbosGuo3S96C3APsAbYW1WPJtkFjKtqAfgH4B+THAZO0PxC0a73JeAQ8Bzw0ap6fpmSe8787UxtXrV9z3OobW9b9xyrfcZ10/xxI0kaKq8slqSBMwgkaeDmFgTTXNo/g9qfSHIoySNJvpbkklnUnVjvQ0kqSS+noHWpm+T32vf8aJJ/6qNul9pJfjXJ/Ukean/e1/ZUd2+SJ0513n4an23H9UiSt/dRt33tufT2vPq6S+2J9ezt6WquTF9X1cwfNAfmvg+8ETgf+Fdgy6J1/gT4XPt8B3DXDGv/DvBL7fOb+6jdpW673quBB2kuVhrN6P1uBh4C1rbTvzLDn/Ue4Ob2+RbgBz3V/m3g7cB3TrH8WuCrQIB3Ad88m3t7Xn1tb8+2t1eqr+f1iWCaS/tXvHZV3V9VT7eT+2nOEV/xuq3bab7P5r96qNm17h8Bu6vqSYCqemKGtQv45fb5a4D/7KNwVT1Ic5bPqWwHvliN/cBrk7yhh9Lz6u159XWn2i17e0or1dfzCoKlLu1ffHn+SZf2Ay9e2j+L2pNuoknYFa/bfozbWFX/0kO9znWBNwFvSvL1JPuTbJ1h7T8Hrk9yFPgK8LGeai/n5fZBn6+7Er09r77uVNvenllvn1Ffr4qvmFitklwPjID3zKDWK4C/Bm5c6VpLOI/mI/R7af5KfDDJb1TVT2dQ+zrg81X1V0l+i+ac/bdW1QszqD1Is+zrtp69vcp7e16fCKa5tH8WtUnyfuCTwLaqemYGdV8NvBV4IMkPaPbvLfRwUK3L+z0KLFTVz6v5Js3v0vzyTKtL7ZuALwFU1TeAC2m+tGulrdRXRMyrt+fV111q29uz6+0z6+s+DpycwQGP84AjwCZ+caDlLYvW+SgnH1D70gxrX0FzIGjzLN/zovUfoJ8Dal3e71bgC+3zdTQfLV8/o9pfBW5sn19Osx81Pf3ML+XUB9X+BycfVPvW2dzb8+pre3v2vb0Sfd1bM5zBm7mWJp2/D3yynbeL5i8VaNLzyzTf8/4t4I0zrP1/gf8HPNw+FmZRd9G6vfyydHy/ofnofgj4NrBjhj/rLcDX21+kh4Gre6p7J/Aj4Oc0fxXeBPwx8McT73l3O65v9/Wznmdvz6uv7e3Z9fZK9bVfMSFJA9flVpVnfAFDkhuSfK993LDU9pKk+epysPjzNPvZTuUDNAdfNtPcienvAJK8DriN5o5PVwK3JVk7zWAlSf1bNgjqzC9guAa4t6pOVHMxx72cPlAkSXPQx3UEp7qAofOFDZm4r+tFF130jssuu6yHYUlLO3jw4I+rav28xyGtFqvigrKauK/raDSq8Xhmt5TVACX5j3mPQVpN+rig7FQXMHhPV0k6C/QRBAvAh9uzh94FPFVVP6K5/d/VSda2B4mvbudJklaRZXcNJbmT5ns61rVfnnQb8EqAqvoczZcpXUtzcczTwEfaZSeS3E5zg3CAXVV1uoPOkqQ56HLz+uuWWV40l8wvtWwvsPfMhiZJmgVvVSlJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNXKcgSLI1yWNJDie5dYnln0nycPv4bpKfTix7fmLZQp+DlyRNr8utKtcAu4GrgKPAgSQLVXXoxXWq6uMT638MuGLiJX5WVW/rb8iSpD51+URwJXC4qo5U1bPAPmD7ada/Drizj8FJklZelyDYADw+MX20nfcSSS4BNgH3Tcy+MMk4yf4kHzzFdjvbdcbHjx/vOHRJUh/6Pli8A7i7qp6fmHdJVY2APwD+JsmvLd6oqvZU1aiqRuvXr+95SJKk0+kSBMeAjRPTF7fzlrKDRbuFqupY++8R4AFOPn4gSZqzLkFwANicZFOS82n+s3/J2T9JLgPWAt+YmLc2yQXt83XAu4FDi7eVJM3PsmcNVdVzSW4B7gHWAHur6tEku4BxVb0YCjuAfVVVE5tfDtyR5AWa0PnU5NlGkqT5y8n/b8/faDSq8Xg872HoHJbkYHvcShJeWSxJg2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHCdgiDJ1iSPJTmc5NYllt+Y5HiSh9vHH04suyHJ99rHDX0OXpI0vWXvUJZkDbAbuAo4ChxIsrDEncbuqqpbFm37OuA2YAQUcLDd9sleRi9JmlqXTwRXAoer6khVPQvsA7Z3fP1rgHur6kT7n/+9wNYzG6okaSV0CYINwOMT00fbeYt9KMkjSe5OsvHlbJtkZ5JxkvHx48c7Dl2S1Ie+Dhb/M3BpVf0mzV/9X3g5G1fVnqoaVdVo/fr1PQ1JktRFlyA4BmycmL64nfffquonVfVMO/n3wDu6bitJmq8uQXAA2JxkU5LzgR3AwuQKSd4wMbkN+Lf2+T3A1UnWJlkLXN3OkyStEsueNVRVzyW5heY/8DXA3qp6NMkuYFxVC8CfJtkGPAecAG5stz2R5HaaMAHYVVUnVuB9SJLOUKpq3mM4yWg0qvF4PO9h6ByW5GBVjeY9Dmm18MpiSRo4g0CSBs4gkKSBMwgkaeAMAkkaOINAkgbOIJCkgTMIJGngDAJJGjiDQJIGziCQpIEzCCRp4AwCSRo4g0CSBs4gkKSBMwgkaeA6BUGSrUkeS3I4ya1LLP9EkkNJHknytSSXTCx7PsnD7WNh8baSpPla9laVSdYAu4GrgKPAgSQLVXVoYrWHgFFVPZ3kZuAvgd9vl/2sqt7W87glST3p8ongSuBwVR2pqmeBfcD2yRWq6v6qerqd3A9c3O8wJUkrpUsQbAAen5g+2s47lZuAr05MX5hknGR/kg8utUGSne064+PHj3cYkiSpL8vuGno5klwPjID3TMy+pKqOJXkjcF+Sb1fV9ye3q6o9wB5obl7f55gkSafX5RPBMWDjxPTF7byTJHk/8ElgW1U98+L8qjrW/nsEeAC4YorxSpJ61iUIDgCbk2xKcj6wAzjp7J8kVwB30ITAExPz1ya5oH2+Dng3MHmQWZI0Z8vuGqqq55LcAtwDrAH2VtWjSXYB46paAD4NvAr4chKAH1bVNuBy4I4kL9CEzqcWnW0kSZqzVK2uXfKj0ajG4/G8h6FzWJKDVTWa9zik1cIriyVp4AwCSRo4g0CSBs4gkKSBMwgkaeAMAkkaOINAkgbOIJCkgTMIJGngDAJJGjiDQJIGziCQpIEzCCRp4AwCSRo4g0CSBs4gkKSB6xQESbYmeSzJ4SS3LrH8giR3tcu/meTSiWV/1s5/LMk1/Q1dktSHZYMgyRpgN/ABYAtwXZIti1a7CXiyqn4d+AzwF+22W2jucfwWYCvwt+3rSZJWiS6fCK4EDlfVkap6FtgHbF+0znbgC+3zu4H3pbl58XZgX1U9U1X/DhxuX0+StEose/N6YAPw+MT0UeCdp1qnvdn9U8Dr2/n7F227YXGBJDuBne3kM0m+02n0/VsH/HhAdedZe57v+c1zqiutSl2CYMVV1R5gD0CS8bxuLD6v2r7n2deeR11pteqya+gYsHFi+uJ23pLrJDkPeA3wk47bSpLmqEsQHAA2J9mU5Hyag78Li9ZZAG5on/8ucF9VVTt/R3tW0SZgM/CtfoYuSerDsruG2n3+twD3AGuAvVX1aJJdwLiqFoB/AP4xyWHgBE1Y0K73JeAQ8Bzw0ap6fpmSe8787UxtXrV9z8OpLa06af5wlyQNlVcWS9LAGQSSNHBzC4JpvrZiBrU/keRQkkeSfC3JJbOoO7Heh5JUkl5Or+xSN8nvte/50ST/1EfdLrWT/GqS+5M81P68r+2p7t4kT5zqmpQ0PtuO65Ekb++jrnRWqqqZP2gOOn8feCNwPvCvwJZF6/wJ8Ln2+Q7grhnW/h3gl9rnN/dRu0vddr1XAw/SXIg3mtH73Qw8BKxtp39lhj/rPcDN7fMtwA96qv3bwNuB75xi+bXAV4EA7wK+2Xef+/Bxtjzm9Ylgmq+tWPHaVXV/VT3dTu6nuf5hxeu2bqf5rqb/6qFm17p/BOyuqicBquqJGdYu4Jfb568B/rOPwlX1IM0ZbKeyHfhiNfYDr03yhj5qS2ebeQXBUl9bsfirJ0762grgxa+tmEXtSTfR/OW44nXb3RMbq+pfeqjXuS7wJuBNSb6eZH+SrTOs/efA9UmOAl8BPtZT7eW83D6Qzlmr4ismVqsk1wMj4D0zqPUK4K+BG1e61hLOo9k99F6aTz8PJvmNqvrpDGpfB3y+qv4qyW/RXI/y1qp6YQa1JTG/TwTTfG3FLGqT5P3AJ4FtVfXMDOq+Gngr8ECSH9Dst17o4YBxl/d7FFioqp9X8y2x36UJhml1qX0T8CWAqvoGcCHNF9KtNL/+RGrNKwim+dqKFa+d5ArgDpoQ6Gt/+WnrVtVTVbWuqi6tqktpjk1sq6ppvyCty8/6/9B8GiDJOppdRUemrNu19g+B97W1L6cJguM91F7OAvDh9uyhdwFPVdWPZlBXWnXmsmuopvjaihnV/jTwKuDL7fHpH1bVthnU7V3HuvcAVyc5BDwP/K+qmvrTV8fa/xP430k+TnPg+MY+Aj/JnTThtq49/nAb8Mp2XJ+jOR5xLc09Mp4GPjJtTels5VdMSNLAeWWxJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwP1/Xwr5739PIxQAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "nDFKleHYAE0k",
        "outputId": "e2da7d4e-b0b2-46de-9df0-6230b04c50c7"
      },
      "source": [
        "#O 'k--' inclui uma linha tracejada\n",
        "plt.plot(np.random.randn(50).cumsum(), 'k--')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fbf41927c10>]"
            ]
          },
          "metadata": {},
          "execution_count": 65
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RjW9UGNXAcAd"
      },
      "source": [
        "_=ax1.hist(np.random.randn(100), bins=20, color='k', alpha=0.3)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GaZthGh4A-Xm",
        "outputId": "0432af71-5c22-4e92-803d-06fd1229af4a"
      },
      "source": [
        "ax2.scatter(np.arange(30), np.arange(30) + 3 * np.random.randn(30))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7fbf3a621dd0>"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "uE_y2XAjBICl",
        "outputId": "a91e8f43-54cc-4cb5-96be-47dc4daaf822"
      },
      "source": [
        "fig, axes = plt.subplots(2,3)\n",
        "axes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7fbf3a2f7890>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fbf3a378e10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fbf3a7a2fd0>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7fbf3a805690>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fbf3a75d510>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fbf3aba07d0>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 68
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 6 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "44PTVvsFKzm4"
      },
      "source": [
        "**Ajustanto o espaçamento em torno das subplotagens**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "dBikxULtKzUw",
        "outputId": "7b62b844-ab6d-47de-d9ef-1092cf9c52d2"
      },
      "source": [
        "fig, axes = plt.subplots(2,2, sharex=True, sharey=True) \n",
        "for i in range(2):\n",
        "  for j in range(2):\n",
        "    axes[i,j].hist(np.random.randn(500), bins=50, color='k', alpha=0.5)\n",
        "plt.subplots_adjust(wspace=0, hspace=0)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 4 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4m0WZ0JlMEJv"
      },
      "source": [
        "**Cores, marcadores e estilos de linha**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "rPETArUiKIEd",
        "outputId": "14c77e5f-d321-44cb-f626-94625162c09f"
      },
      "source": [
        "plt.plot(randn(30).cumsum(), 'ko--')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fbf39fbcc90>]"
            ]
          },
          "metadata": {},
          "execution_count": 75
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "CKHLa45jMZ2K",
        "outputId": "d063763b-09da-4113-a3ce-0ccc027b5c2d"
      },
      "source": [
        "#outra forma de escrever o mesmo código\n",
        "plt.plot(randn(30).cumsum(), color='k', linestyle='dashed',marker='o')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fbf39efc650>]"
            ]
          },
          "metadata": {},
          "execution_count": 77
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fUFW3HU7Nbur"
      },
      "source": [
        "data = np.random.randn(30).cumsum()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "jmWcohnwNzGT",
        "outputId": "5c057bff-0c36-40d0-9ccf-787f76fd8de1"
      },
      "source": [
        "plt.plot(data, 'k--', label='Default')\n",
        "plt.plot(data, 'k-', drawstyle='steps-post', label='steps-post')\n",
        "plt.legend(loc='best')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fbf39a6f510>"
            ]
          },
          "metadata": {},
          "execution_count": 83
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GGbDfaQ9OqU3"
      },
      "source": [
        "**Definindo os tiques,os rótulos dos eixos e os rótulos dos tiques**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "curW4RIDOEGq",
        "outputId": "f7045c0f-e35c-4801-b55c-feb2f32935a7"
      },
      "source": [
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "ax.plot(np.random.randn(1000).cumsum())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f2c871c50d0>]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "N6wL7LP-PZbq",
        "outputId": "a6ed108a-3adc-4052-b2f5-12f3886cbfef"
      },
      "source": [
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "ax.plot(np.random.randn(1000).cumsum())\n",
        "\n",
        "ticks = ax.set_xticks([0,250,500,750,1000])\n",
        "\n",
        "#rotation gira os rótulos do eixo, no caos do exemplo do eixo x. Set_label coloca nomes no eixo\n",
        "labels = ax.set_xticklabels(['one','two','three','four','five'], rotation=30, fontsize='small')\n",
        "\n",
        "#Set_title define o título da plotagem\n",
        "ax.set_title('Minha plotagem matplotlib')\n",
        "\n",
        "ax.set_xlabel('Stages')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Stages')"
            ]
          },
          "metadata": {},
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        },
        "id": "Wt2UmijoQQBz",
        "outputId": "ebbc6089-01d8-40fd-ca7d-6a51753de6eb"
      },
      "source": [
        "#Outro jeito de fazer a mesma plotagem\n",
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "ax.plot(np.random.randn(1000).cumsum())\n",
        "\n",
        "ticks = ax.set_xticks([0,250,500,750,1000])\n",
        "\n",
        "props = {\n",
        "    'title': 'Minha plotagem matplotlib',\n",
        "    'xlabel':'Stages'\n",
        "}\n",
        "ax.set(**props)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0.5, 0, 'Stages'), Text(0.5, 1.0, 'Minha plotagem matplotlib')]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z9z3zP4HSUVl"
      },
      "source": [
        "**Acrescentando legendas**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "9fG1H2GYSJJh",
        "outputId": "dde0f706-00e4-4e58-de7b-4bb42e6cf28e"
      },
      "source": [
        "fig = plt.figure(); ax = fig.add_subplot(1,1,1)\n",
        "ax.plot(randn(1000). cumsum(), 'k', label='one')\n",
        "ax.plot(randn(1000).cumsum(), 'k--', label='two')\n",
        "ax.plot(randn(1000).cumsum(), 'k.', label='three')\n",
        "\n",
        "#cria uma legenda\n",
        "ax.legend(loc='best')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f2c870a2b10>"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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wQ29XnzzHcVUAvAPgJIAyhBAq3vEYRnfOawdfavibb75Beno6Pv30U9SuXRu9e/dmP4oqVarg22+/RaNGjbBp0ybs27cPgYGBaNSoEbp37878oGfPnkWrVq3QuHFjdOzY8a3RN6ERHZ6envDx8QEAtmjK94/zw/ukjLRCoRBMiWmGMWB5JF+QNGjQAID5iJ1CY/Y5jsP+/ftx5MgRh/YnKysLarUarq6uoto9e/fuxS+//ILU1FR5kJIPNBqN2edXpUoV5OTkgBCCrKwsREREFGif7GbkOY7zAPA3gLGEEEF8GjFaQtEhAsdxQziOO8Nx3JmEhAS79MWesal8qeGffvoJ0dHRTIny9u3bOH78ODvW29sb586dQ7t27TBz5kwcOHAA586dQ5MmTTB//nzodDqMHj0af/31F86ePYtBgwYxHfo3HWrkS5QoAXd3dzg7OyM+Ph7u7u6C4hwNGzZkry2NxPkhmVJqk4VZUNvb2xvVqlXD5cuXRffTyBtCCDp06ICNGzdCrVZj4sSJUKvVdu8PXRt4/vw5IiIizFwKtJ/ff/+9XIg8H3h7e5vlIRS2vIVdZA04jlPBaODXEUI2v9z8hOO4coSQOI7jygEQFdgmhIQDCAeAJk2a5HuuqNVq0bZtW3ZTHzx4kBVYtgdNmzZlmY8NGzbE3bt30aJFCwBAz549ARgTb65cucIKSmRnZyMwMBDXrl3DpUuX0L59ewBGt87bImBFjXzx4sXBcRy8vb0RFxcHPz8/ZtRGjRqFOnXqwMnJCTk5ORZ95z4+PkhNTUWjRo0E2u38UWpefOn2xNfXFw8fPhTdJxZeWbJkSXh6eiIrK0tS3ycv0BGkWq1m4ZObNm0S6CpRd9p3330nJ0vlEa1Wi7Fjx1p8SCqVSvTr168Ae2Wf6BoOwEoAMYQQfq76NgD9Acx5+e/W/F7LGmj4kl6vR3Z2NjQajV2NPH+UpVQqBaXgaBQGIQTt27c3C8e7ePEi6tatW6jZb4VFSkoKihcvzgw3NWCffPIJMypUP+batWusIIsUW7duxcKFC6FSqVhIJgAWd758+XIMGDDA3m/DJsqXL28Wxw8YY+JjY2NRpkwZQYESqs8DAKVLl7aYsGULer0ehBBBlA9fuhkwJocpFArExMTAz8/PLGdBJnc0Gg2ysrIsrms0btzYrvbIGuzxyH4PQF8AbTiO+/fl3wcwGvf2HMfdANDu5f8dTnBwMJydnaFUKuHs7CxaZMQWTKWGreHdd9/F8ePHcfPmTQDA8+fPcf36ddSqVQsJCQnMyOt0Osnp/JtGcnIyM2DAq4Sc+vXro0ePHqhUqRJGjBgBwJilmlsUU7169RAeHg5PT0+kpaWxHxYt1EFnBIVJmTJlRBOP7t27B71ez4qgUPz8/NhnlJaWZrd4eerC4g9QTBd6U1JSYDAYUK9ePVy6dMku133bCA4ONhO6M4WKGxYk+f4VEEKOAZB6Z23z276tBAYG4uDBg9BoNAgODs73U5MvNezq6iqZQcmnVKlSWLNmDXr16sV+YDNnzkTNmjXx119/YcyYMUhJSUFOTg7Gjh2LunXr5quPrwOmRp4+OP39/eHr65tr4pAUxYoVg8FgQEZGBtzc3JirxxadGUfh6emJ1NRU5OTkCB44t27dAmCM79+69dUE18/PTxDCuHnzZrMHQV6giTnOzs6IiYmBv7+/mZHnj9xNlVVlhGi1Wqvty8SJE3H9+nU8evQIwcHBSExMhFarLdDR/BspNRwYGGjXD9FUapiyePFi9tp0caVNmzY4ffq02TkNGzZEZGSk3fr2upCcnCwwYG5ubnjx4gWqV6+er3bp4mxaWhri4+ORk5ODypUro1SpUvlq1x7Qh5qXlxfi4uKYO48a+Q8//BAdOnRgKpdubm6iD8L8wh/J165dGwEBAWb6NYsXL8aAAQPwn//8Ry5CboHw8HCMGjUKer0earVasOYXGhpqFlnj6emJiRMnYtKkSZg7dy4IIXBxcbH7WqEl5BUWmQIhJSVFYORPnjyJtWvX2iwXYArfyNPQtLzOCuxNyZIlARj7tnPnThw5cgTr1q3DrVu34OrqinLlymH37t0sN6BSpUoCCWRrjC0hBC1atED37t1x4sQJ0UU//kgeMGrli43WPTw8rL7u24hWq8XIkSOh0+lgMBiQmZnJ9GjCw8OxZcsWwfFqtRre3t5o2bIlIiMjYTAYQAgRnFcQvJEjeZmix/Pnz5kRAYw+9Xr16uW7Xb6RL2rwR+V9+vSBTqdj/69cuTI4jgPHcbh06RJ27twpkGcArHOb6HQ6Fsb7119/Yfbs2Zg0SZhc/ttvxpxEGnnk7u4uMOTp6en47LPPWPgqvxqWzCs0Go0g0IIQwtbUTAXsOI7DwoULkZiYKDiHnleQOjbySF6mQLBnSCAfOlqeP38+U7X873//a/fr5AW+Jj3fwAPCpC+O4/Dhhx9CoVBAqVTif//7HwDrRtT8vABAPKWeavfQkFJ3d3fBA6RYsWLYuXMnMjIyWFamjHm+TXBwsFl46fr166HVakXdg4mJiQgODjYLAOA4rkB1bF4LI/82plq/ae85MzPTIUk+1L3x+++/Y8eOHahRowb+7//+z+7XyQtU2kAMS9m406dPR7t27awayZsaeQr//mnSpAkAoGvXrgDMjTyldOnSGDJkCGrWrJnrdd90aL7N1KlT0bJlS4SHhyMwMBATJkwQHEcIQWhoKDZs2CDYrlAo2MJsZGQkWrZsCYVCAYVCARcXl3xH/dlCkTfytOzbm2b0LEEIQWJiokNGvoVFVlaWQ94PP9rp7t27Fsv6FTSmozv++88t4cjd3d0qF5Spkf/zzz/x22+/QaFQ4Pr16wCM7pdq1aqx8D5avxYQPgy8vLxw/fp1KBQKFor6thIREYGMjAwYDAbk5ORg1KhR0Gq1+PHHH5lkBeX69etmayFdunRhC6uBgYE4cuQIjh07hiFDhqB///4F9j6A18AnX6FCBcTGxsJekgevCy4uLlbXFH0dcNRInu/31uv1RcrIcxwHQgib7p87dw6jRo0CkLuR9/LywpkzZ3K9hthInkoGDxs2DMuXLxckiwHCkTx/RO/t7c2ytk+ePJnrtd9UtFotVq5cKdim1+tZYmVgYCDOnz/P9tWsWRM3b95kC9wqlQoTJ04UbXvVqlXIzs7G8uXLsWTJEkHxekdR5I28SqWCn59fYXdDJh/QtHpHjOQ5jsMXX3zBlP+KkpGn0BHdjRs32Lbc5CzKlCmDhw8f4vLlyxbzKKiRb9euHQ4cOADAmM2q0+lw+PBh/PLLL2bnUCNPCAHHcejcuTP27NmDatWqsdBKulj7NhIREWG2hqJUKhEcHMwe2CqVCjqdDkqlEp06dUKnTp2wcuVKlC9fHhMnThQNj4yIiGAPAr1ejxEjRiAgIMDhoZRF3l0j8/pDb2xHjOQB4KeffmKvi6KRp3h5ebHXq1evtngsfR+5RSAdPHgQADBixAjo9XqoVCqBHAK9Dj9nw93dnYXyubu7Y+3atThx4gQaNGiAP/74A19//bVo/sK1a9feWvEyvV6PLVu2ICgoCGFhYTAYDFAqlSCEYOTIkRgxYgTOnDmDvXv3SrZhKtVBZweORjbyMg6HJv84ao3B09OTuT+KspGvWLEiAOMCJ5VblsKazGrgVRUntVoNhUIhiOgBjBE6HTp0YIuvgDAe/tatW8jKymL73333XRw6dAiffPKJoJ2nT5+idu3aZguPbyL9+vUzc6cZDAaW7EQIYbVbqc8+t1quWq1WoFgLvJodOBrZyMs4lKVLlzJ3gyOrH9WqVQtA7m6QwoQaeWsMOP9hZU3QAU0qE0sEM32g0Mzb58+fY9KkSWbuAicnJzN3BV0Ti4mJybUvRQUaAhkeHm6T9DiNouHr0Ihp0kjp1IgZbo1GI/geOY7DkiVLCiTrtcj75GVeb6joGCAur2svaLWjojyS9/LywqpVqyRrzPLhPwiioqKYbDUffpINXUCtVq0amznVrFkT169fFyShAUIjf+LECQQFBQn2Ozs7mxl56gJq06YNkpKSWH5CUYWGQGZmZrK1B2vlBLRaLRYtWgSO46BQKPDee+8hJibGLPgjNzEyPsHBwVCr1cjKygLHcejSpYugjoIjkUfyMgVG9+7dHdY2NfK5uUEKm4EDB1qMn6eULl2aveZnUz548IC5A/jJUnTd4/Dhw2wb1S03TcahRv7hw4eIjY0VuHIA46yAtkeh4ZwTJ05kWjtFGVPZX7r4b40PPCIiApmZmcwdc+zYMTMD36BBA8n1CbFrUOHEIUOGwMnJCdu3b0dwcDCGDx/ucOlx2cjLFAhz5sxhyTiOYNOmTejSpYuZT/p1xdvbm4Xp/fzzz8xYBQUFoXXr1khMTGSj61KlSuHjjz8GYMxq7du3L6KiopjbYNCgQYK26cieunYqVaok2E8jR/jwF3MfPHhgj7foEKiLRqxCE8dxufrAtVotVq1aJXg48I05laK4fPmyqBvNkp89MDAQlSpVYj787OxshIWFoW3btg419LK7RsZh8P3DVatWdei1goKCzNwOrzv169dnr6n2D/1Mf/jhB6ZNvmjRIuaTVygUghqier3ezNhRvR9qrE3XMXr27GkWf//hhx/ixYsX8Pb2LrJGXqvVIjg4GDqdDiqVCm3atBHMOqypeCVWo5VC3TN04dUUhUKBxYsXW3QHBQcHQ6lUsvP5MwxH+eflkbyMw6hSpQp77chR/JsM1ZtJTExESkoKU5JcuXIl871bqoUrZtioUXdzc8OGDRuYCiblyy+/ZElbAHDkyBGo1WocOXIEvr6+gmpWRQkah04IQXZ2tplbKScnJ9ci2qZFh/hhv4QQEEKgUCigUqnMylNOmDAh1+SmwMBAsxoBhBDcv3/fYaN52cgXYfR6fZEdNdnCvHnzBKXnZKyH1ixITExETEwM85WnpqayB6clIy8GLYK+a9cu9OzZ02wRNSMjAykpKXjy5Ak2bdrEdHY6deoEHx+fAhXXsieEEKxcudKiMaW+8++//x4ajQZfffWV2QJru3btoNFoWGYxYBzl87OvLWHq3yeEYNmyZUwjx97I7poizNy5czFp0iTcuHEj38U1CpO3NYHGHlBJ2sTERLa4bIqtRn7Xrl0AgGPHjuHq1auoXbu2YP/gwYNx6tQpJCUlMWVPyvTp0/NdA8BR8AuTS6HT6XJ1jVy8eBEajQbJycmYP3++me+9YcOGCAwMxMWLF9k2W+SDS5UqJRqKSjVy7J0FKxv5Igyt8Xn8+PHXzsjzF+4KUjv7TYN+ds+ePcNnn30meoytRn7MmDEAjIbpyJEjZkZepVIhLS1NYOCdnJzg7u6Ojh072nStgkRMZlkM06pYfMLDwzF06FAAkIwiosXiExMToVAoYDAYoFAorJrhaLVai7V7+Ro59kI28kUY6g8UKwZd1KE1RJs0acJC+WRshxp5S9WuLMkWW9s+H2dnZzMp4qSkJKhUKjx48ABXr15F+/bt83xNR0CjYqxh+/bt8PT0FK3Ralr8gxpxPjQbmMa+Z2dnw9nZ2arsVUsLu4DxN2/vLFjZJ19EOXbsGDZu3Aig8Cr1nDp1Cl27djWLmbYGOqoZN26c2QKVjPVQvRs6euzZsyfu37+POXPmsGP+/PNPdOzY0Wp/Lt+tkZaWhm3btgn2q9VqgZEfP348PDw8oFarsXbtWnTo0AFHjhzJ83tyBFLGk+M4VvGKEhMTg6lTp4qGLprKOfTq1UsQuTRx4kS2uMr331tbs5Uu7EpF+owePdr+UTZ0xbgo/DVu3JjIGAHA/saMGVMofShZsiQBQM6dO2fTedeuXSMBAQEEANm7d6+Devf2UKJECXYvHDx4kBBCyNmzZwX3CP2bOHGiVW0GBQUJzktKSiI6nY6MGTOGDBs2TLAvPj6enTdnzhwCgIwbN84h7zWvREVFEVdXV6JUKolCoRD0PyQkxGwbAKJUKsmsWbPM2goLCyMdOnQgYWFhZNasWUSpVFo8Pi99nTVrFgkLCyMVKlQQ9Klp06Z5ahPAGSJhVwvdsPP/ZCP/CtMbcunSpXa/RlhYGLlw4YLkfnd3dwKArF+/3qZ233//fdbv06dP57ebbz0fffQR+24j8rQAACAASURBVDzPnz/Pts+cOdPMeHEcR6Kioiy2FxUVRYYMGSI47/bt2+TcuXMEAKlevbpg34MHD9i5kyZNIgDI9OnTya1bt4jBYHDY+7YVajxDQkLMDCfHcYJtCoWCuLq6WvVZ0YeHNcfbimlfQ0JC8tSObORfQ8RGafbk7t27BADx9/eXPMbT05MAIPPmzbOp7e7duwuMh0z++O6779jn+ezZM7bddMRtjaFYtGgRUSgURKFQECcnJ8HDODIykgAgpUuXFrR348YNdn5sbCwBwB7k33//vUPfe16Iiopi783JyYmEhYUJ3isA0qFDB6sNNn142NvA07ZVKhUBQFQqVZ6vYcnIyz75t5S//voLwKtkG1OSkpJYFIK1C1oUvlaKHFmTd2iKPs0+bd68OYtpt7TQuG3bNknlxb179zJNFv6CYmJiIlvgp4vmFH72q6+vL1q2bMl88tOmTcvnu3QMSqUSHMdBqVQiICAAv/76K1QqFRQKBVxdXTF9+nSrfd+BgYGYPHmyQzJSaWnAWbNm4ciRIw65hhxdUwQxPpjtz7lz56BSqXD+/HlWwEDKyPMX8S5fvowHDx4wqVxL5OTkYMuWLez/tob3yRihKorZ2dls4ZqvH6PRaAQqlHwMBgOGDx8OQgicnZ1x+PBhZjxoWKRSqYRKpUJmZiYAo5GnImQ0/LVs2bJ4/PgxMjMzkZOTgy+//BLffvstPD09BTH7GRkZcHV1tfMnkHfoZ0MIQU5ODjQaDSZPnoyAgACEhobi2rVrCA0NlazgpNVqodFoRKNvHAEtKego5JF8EeThw4cAjAbYNPIhr+zfvx+NGzdG/fr10bdvX+zfvx8A2I/clOjoaIHezJIlS6y6zty5cwUGwBY5VplXUBVFvV7PjDk/yio4ONjiZ2swGECIUReFpvK/ePECUVFRAIDvv/8ehw4dYscnJiaaVS6i8sZZWVm4fPky1qxZg549e6J69epwcnLCt99+CwCIj4+3wzu2H6bSBDQk8eLFi9iyZQtiYmKwZcsWtGjRwiwiiT5cp02b5nDhsIJCNvJFEKpJsmbNGnTp0gXdunWzWOfTGkzjrKlcgpSRT01NhZeXF0sIuXPnjlXXuXv3bt47KcPw9vZm7hT6r2kora0PUH4SUHJyMvr164fOnTsDMBr5a9euCY5v2rQpAONInYYhpqSkoEGDBsjJyWHx+XFxcTb1w9FIhTaaFuc2GAwYNWqUwJBrNBpkZ2czlciCKM/naGR3TRGETsupFoaHh4dAOzwvSE2npYx8SkoKSpQogfbt26NJkyZsKi+GTqdD8+bNMXXqVKZVDuCNU4UsSMSyN/v27cteh4aGSrprTKHGmO/uCQ0NBQDcvHkTzs7OTACNUrVqVbRs2RKAMBkvNTUVFSpUAGCUOACA3r17s4FJUcHUBaLVanHu3Dmz40wzTOkswJYEp6KOXUbyHMet4jgunuO4S7xtXhzH7ec47sbLf4t2KZkiBDWo1J9tDyMv5effu3cvYmNjzbanpqYy41CsWDGBgTDlyZMnOHPmDEJCQjB//nwARoMUGRmZrz6/zYiVSqTJPuHh4YJ1DwBmCT98fv75Z2i1WsmkOr1eL/DJA0YFUVqTl36ngHFQ0KZNGyxcuJD57mnpRcB4n1m6VwoL0/J7FJVKJTDkeUlwKurYy12zBsD7JtsmAThICKkB4ODL/8tYgSOMPM1gpH5UPmIREnwjX7x4cYs/XNNoDABYsWJFXrv61qPVapmIGB9q+E1T7wFYVPmko1Wp71Cv1yMqKkpwjzk7OzMjf+rUKbadzh7osRkZGYK+rlq1CiVKlCiUkT2NRhLzo9MRumnd1oEDByIwMFBwriOjaQoFqdhKW/8AVAFwiff/awDKvXxdDsC13NqQ4+SN/PTTTwQASU1NJYQQMmPGDAKA6HS6PLc5d+5cAoCkpKSYxVW/8847gmNzcnKIu7s7+eqrrwghhPTp04f4+flJtq3RaBwa0/+2MWzYMLPkHfDiqMPCwkSzN023wSTpJysri8yePVv0OADEzc2N5UZ89NFHxGAwkHLlypkdl5yczF6bJkO1a9eOACA7d+4s0M8sKiqKqNVqwnEcUavVovHmUVFRZNiwYUStVguSm/gJT87OzmTYsGEOiYl3JCikOPkyhBC6IvMYQO4l6mWQkZHBijJQ/za/8HJeoSMvvs+cYrpwduHCBTx//pwtvJUsWdJMcpYP3RcREYFmzZoxzR0Zy4iNPE3Lz/HR6XQIDQ1FQECAWd1WUxGtKlWqoHfv3ihXrhz+85//ADCOzidNmoSJEyeKLtpmZGSwOHw66qWKjHzoCB8AfvrpJwwaNAg5OTlYvHgxDhw4AABo1qyZtR+DXYiIiGA1XfkRRXwCAwPRr18/DBw4EF26dEH//v2xZcsWfPDBB8jIyCjQknwFSYEsvBJC6MjEDI7jhgAYApjXmnzbOHz4MNq0aQPAuOhKRYxoTc709HSUKFECgLHwwIYNGzBq1ChwHIfPP/8cCoUCv//+u2jb6enpcHV1FYiFrVy5EoMHD8bjx48Fsc40QoZWDPL19UVKSgrS09NZX/hQI9+qVSvB4qCMNFqtFq1bt2YLfDSWPTeVwm3btqFs2bJmDwFCCFQqFQwGA5ydndGjRw+2uPrw4UO0aNECQ4YMQc2aNfHjjz+iWrVqZgacEMIMOHX/uLm5sf0lS5ZEUlKSwLd/8+ZN7NixA1u2bMHo0aMBAHXr1i2SSXA0PDIrK8tijQNCCIuseRNcNo4cyT/hOK4cALz8VzSYlhASTghpQghpUqpUKQd2p+jz448/stf8cDe+kaf069cPY8aMweXLlwEAf/zxB9atWyfZNt9Ax8TE4MaNGxg0aBDWrl0LQBhiSUf2ZcuWBQAWTcGPq+ZDjTxVTJTJndDQUMHIkxpkWgNUCoPBgMePH5v5lxUKBQYPHswWDKlqJf+8sLAwzJs3D4C09jqd6VEjzx+1r1mzBoBxsb5cuXL4/PPPUbVqVSQkJAjK5HXq1El03cCR9OvXj30mzs7OovLWNDzSmiI2Tk5Ob0RkDeBYI78NQP+Xr/sD2OrAa70R8H8ofKhx5rtraESDv7+/VW0/f/6c/YBr167NipD4+fkBeDV6X7hwIUaOHAkA8PHxAQBWk/L48eOibT979gwqlUrUFSRjjlarxfbt2wXbtm/fzhb9PvjgA4vnly1bFgcPHsTQoUOhVquhVCqhVqvRr18/tmBoKpkLgD1QOnbsaJb4RKHnffHFFwBeuYFGjx7NNOQfPHgALy8vPHz4kFVHqlixIn799VcAxsLiU6ZMsfbjsAt0FvTDDz9IjsBzk/nl06lTpzdiFA/YyV3DcdwfAIIB+HAcFwvgfwDmAPiT47jBAO4B6GGPa73JUHeJl5cXfvvtN7adumj4fvG4uDiULl0aSqWS1ey0hJSrpXLlygBejeTDwsLYPur3rVatGnx8fCQjfJ49ewYvLy85u9VKxML5CCEs8UYssoaiUCjQr18/Fgfer18/0RT8gIAAKJVKM9fP06dPWYKb2H4XFxdB3+h+pVIJV1dXlCpVCvfv30daWhpiYmLYsT/99BOWL1+OOnXqYOPGjUwbqSDJTR6AhkdGREQgPDzc4oiezmLfBOxi5AkhvSR2tbVH+28Df/31FzZu3IgKFSrg3r17gtFGuXLlALwKocvJycGff/4JwPqsRykjX6ZMGdb2sWPHcOPGDdHz3d3dJRd+ExMTZVeNDVCXDN/IqFQqeHt7Y/r06ZJFWhQKBZYuXQoAmD17NjPsYoYtN98+ANSsWRMVK1bE/v37mbE2/f5pH6kLqVKlSrh//z4+++wzzJ07l523fv16XL16FWfPnsWBAwfw7NkzVhavKEFH/JYMPH2QvikUrW/gLYUQgu7duwMwjuJNfxh0VNG3b180adIErVu3lrwJmzVrJqgaRElLSxM18iqVCj4+Pnj8+DGCgoJYgoupwqGlWP24uLg3auRTEJgamapVq2LUqFGidUW9vb3xzjvvoHPnzti9ezdat26dq7ZKbr59wOjymz59uiBSx9QPzR/JA6+MfEhIiNkAg0bmeHl5wWAwWMySLkxy0/0BICjS/bojG/kiAF8XRqyWJ1/J8ezZszh27Jik//7UqVOYPHmyYFtycjJOnDjBfOymULVBSv369TFw4EDBMe7u7qJGnhCCqKgo2cjbgJi7JiYmRlD8nE9iYiKio6Oxfft2bNmyhQmXWdJWCQwMxJIlSyQNvZOTEyZOnAhAOBs0rRdLw2hbtWoFwLiGc/v2bZw/f97sQdWpUycAr9yOUpIZjsJSMpQppiGofMQ0bV5nZCNfBODHqYulnouNOpYvX251+1Szg84WTDHNaKVrAHw8PDxE3TVHjx5l+2WsIzg4mNUNzc86Rm4RIEOGDMGSJUvMrlGlShVERkaKhmyePXtWcGzr1q2RkJDAFoPr16+PjIwMjBgxwuxBRbVuevbsiatXrxZoGKUt6pF8dw3HcQgJCcGwYcMED0SaJWwLDRo0wP/93//lqf+ORDbyRQBqYEuUKIHNmzfbpU3+KIpGUkgtShUvXpwV3gaAJk2amB0j5a6hujc0GkPGOqiBFEt6MmXGjBmi260JBeR/rxSqQAq8ijihtG7d2ux4/gyQPjDE+k3Dfr28vFCrVi02WiaEYP369YLiI/bGFvVIvhSxi4sLJk6ciKVLl2L8+PHsGIPBYNNDymAw4MKFC0y0rSghG/lC5urVqzh27BgA42jk448/Fj2OhjoCYKNAS/B/yFeuXIGnp6ekS6VYsWKC2YSY2JWUu4bq1lSpUiXXPskYiYiIkHTN8FGr1ShWrBi+/vpr0f06nc4ss5MQglWrVrGaBPxZA/8YagRpxAm9N3ILG5SKf+c4DmfOnAFgdD/Onz+fuQD37duH3r17Y+bMmWbx+/ZCSkNeDCkRMn4CokKhEH1ASlHUNPX5vNVG/sGDB2bT04LG398fs2bNAmDuD+Vz8eJFPHv2jFX7MWXs2LGC//NFw27cuIFatWpJugaKFSsmuEnFqjlJuWvodeiim4xlLMkWmJKVlYVatWrB3d3dog/ZtP3Bgwfj22+/xeHDh9GsWTNoNBrmSgHM3TyBgYG4c+eOpEolv+2dO3eK7iOEsJHvtWvXMH78eNy5cwdxcXF4/32jdmGJEiXQrl07XLhwwar3Yi20ktOCBQusVo8UEyELDg4W5B3YkgxV1DT1+bzVevJ16tRBenq6w8rt2YolI+/u7i6qYePk5IRWrVqZlebju2tSU1MtGmFTrXmxzGOpkfyzZ8/g7u5u1exCxnLZPjHOnDkDjuOwfPlyDB48WOCi4TjOLMqKukTWrVuHdevWYfbs2Zg0aRK6deuGyMhIcBwn+rB3cXERZLcCr4ynt7c3EhMTcf/+fcnfCn/kS9tp3rw5C/8FjHIHiYmJ+Pvvv1G/fn2rPwNLaLVaBAcHQ6fTQaVS5UuKgI7w81L6z5pclcLirTbydMpMCCkSiTx5yRilFXpo/1u3bo3Dhw8LSvClp6dbrM9KZQsAoHPnzqzsGx/qkzf9rJKSkuRRvA3kFr6nUCiYIXdxccGAAQMAAAMGDMDWrVsFOvJdu3Y1M0StW7eGm5sbMzqTJ09Ghw4dcPLkSQAQ1D2VMmJarRYRERFYuXIl+41wHAcnJyeoVCoz3zrHcYKRL3/QwB/hrl+/HjVr1sTu3bvttkAZERHB8gqys7MRGhqKf/75J8/t5bXeqiPXG/LLW+2u6dixIxo0aFBoBj4hIYG97tq1q82JI//73/8AAJcuXcKePXsAGBNcgFcj+VWrVuHKlSsWo1+++eYbwWuxz8PDwwOEELMZwqFDh2Qjnw9Mv3P+SP3ChQss+engwYPw9/dnbht+CKQp9B6gaDQaJmORm8+aRqksW7ZMsG5ACIFOp0OnTp0E95KzszOGDh0qcJGYzggov//+O65fv47Tp09bzOq1BdPiKtu2bSuU0Ee+kS9qo/q32sg/f/4cL168EM0wJIQIFi8dQenSpdlr/rTWWuiI+8aNGyyJhv4wqTEePHgwAMuzBKVSiV27dqFmzZpmBoJCz+e7bD7//HPcv39fMmZfxpzQ0FBByGKLFi0EayzUiD958gQ1atRg2zds2ICwsDAolUpwHCcZ/z5mzBjcv39fsE2hUGDGjBk4fvw4ZsyYYdFnTQuIW4J/7TVr1mDp0qWC9kyNvFgZyM6dO9vFTWoaTGAwGERlhh0N/zMranWO32ojz3Ecbty4ISq89dNPP6FSpUoFtjBrrU87IyMD5cuXBwC0a9cOO3bsgK+vL9vPN/L8UTdfMlaMTp064dq1a5IPG7oYy1+cO3HiBACYGRUZccSEyerUqQONRoOQkBA0bdoUH374IQDzxe/SpUsjKSkJOTk5ApeLKbdu3WJ6RJTExERMmTIF1atXx3fffWfRHcEvIG4Kx3HYvn274B4Qqzbl5+cnqAw2bdo0jBgxwuw4sRKHYlhKcnrnnXesasPR8I28te+roHirjfwPP/wAwHx6dfXqVVYmj4ai2RvTxTdrswMTEhLw6NEjzJ8/HxzHoXPnzoJROr3ZQkNDBXLF1oTsWaJq1aoAjPrhgPEzozORjz76KF9tvy2YZroqlUq2cLpr1y6cPn0aO3bsQHBwsNlouEyZMkwz3pLL5eHDh/D19UWPHq/0AIOCgjBr1iymUyQGNaS7d++WdF8SQsz0cOgASavVYvjw4Rg+fDjOnj0riK1/7733WOTNuHHj2HZr/NiWkpy0Wi3Gjh3L+ismM5yeng43Nzd89913uV4rP/DfC7/weVHgrTbydHRrauSpIQMck8k5cuRI9OnTR7CNb5AtQUdR/IVUtVqNkJAQ+Pv7s8ibK1euCGKSGzdubLHd3FLCqRuHClgNGjQIMTExKF26NNMol7EMDdFTKBRwcnLCkiVLEBgYyBYP6Qi9YsWKZoaWZiGvXbvWYpggNfJ8qV/q96eLuKaEh4ejVatWmDJlCrZs2WKTG6VMmTIIDw9HUFAQli1bhmXLlqFVq1Y4evQoqw6VnJzMHlre3t7Q6/XIysqyKreCuo/oOfzZC02AIoRAoVCgffv2ZgvKMTExyMjIwOzZsyWF3+wB38jbEl9fIEjVBSyMv4Ku8Vq8eHECgKxZs0awvWLFiqyGZd++fW1qMzMzkyxbtozo9XrJY2jb9G/8+PHkzp07VrV/9OhRAoDs3buXbWvUqBFp3LgxiYyMJPfu3WPtrlixggAgCxYssNimNfUxs7OzCQAyY8YMcvXqVXaNgIAAq/otYyQqKorMmjVL8BkPGzZMcD8MHDjQ7LxNmzYRAOTChQuSbRsMBqJQKMiUKVMIIYRUqVKFACAdO3YkAMilS5dE++Pk5CRZ9zW3v549e4rWl/Xx8WGvIyIiSEpKClm+fDmJiYkhhBDy999/k549e5rViDXFtJ5tWFiYYJ9KpRLUsTVl//797Nz4+HiL18oPixYtYteZMWMGIYSQu3fvkl69erFazZTk5GTSp08fu/YHFmq8Frph5/8VpJF/+PAh+1KWLFnCtmdmZuarKPUff/xBAJBz586J7j9x4kS+2t+7dy8BQI4dO8a2rVy5kgAg4eHhRK/Xs3anT59OAJATJ05YbNPUyAwbNowQYm6QXF1dyYQJE8iPP/7Ijj179qxN/ZcxJyoqijg7O7PP9Pjx42bHpKenkwcPHpDs7GzJdrKzs0n//v3J5s2bCSGEJCUlse/Wy8uLxMXFmZ0za9YsolAo8mTgPTw8SOXKlUX30ULkw4cPJ5mZmWbXDQ0NJYCxsLwl+P1TKBQkJCSEdOjQgUycOJG4urqya3Xo0MHs4UkIIREREaxP169ft3it/DB37lzWlzFjxhBCCOnfvz8BQGbPni14mIWHhxMAZOjQoXa7viUj/9a6a2bOnMle00LHgPjKOLFh+kqnbWIiX8CrKkuUlStXWt02ABb/zl9IbdSoEQBjavUvv/zC2qTrCZ6enjZdAxD3hZYoUQKpqalsUTAmJoZd+3Xm0aNHgnBWRyLmFgsMDBT4jJs3b252nru7O3bt2sXqCIihUqmwZs0aJo3h6enJVCSllEL5LiQauUPhOI6FXopRunRpUTejWq1mv5lFixaJRl/R4IFHjx5Jts/vn1KphEKhwJYtW7Bv3z6Ehoay3wIhBPv27cOUKVPM/PZ814m1LtG8QIMQypcvj6dPn+Lu3btMUXby5Mn473//y46lLuDIyEj88ssvDk/GfGuNPI1y6NOnj0CQi0YL8BcTaep+YmIiOI7Dhg0bJNulN5W1N5RYdIIl2rZti5iYGEHZv8jISADGB9S4ceOYEaYSxpbi2OkPQqVSCRauTH2hERERyMnJwe3bt5lOuKUEq9eFrKws+Pr6CiKUHAUt3j1lyhS0bt1aYIz4CWliPHnyBEOHDsWkSZMkjxEzFjTM1pIk8cGDBzFz5ky89957gjYIIbh9+7ZkuGZgYCDS09NZCKhCoUBISAgOHz6Mn3/+GZUqVZI8lz48YmJiJN8PvcaCBQtQs2bNXPNICCFm4mT8SCBHGnlaCat06dI4fPgw/Pz8BP3gDyrp7ycmJgZjx45lIn+O4o0z8tZqSmdkZODLL7/ErFmzBKvh9Av4/PPP2TZ6c9BRPl+tzhTa1s6dO5GTkyNZnYeGykkljkjh4eGB2rVrC86j2jf0h0OveeDAAQDSRp4uuIWHh4PjOAwdOpQtXPFD6QwGA5YvX46nT5/i4MGDiImJgUKhyDUs83Vg48aNAIzRR47WP4+IiBAU7+bHc9Nr0zqqptDSj5YkEc6dOwe1Wo3du3ezbTTWftiwYZLn0e+bykbzMRgMZhnQHMchLCwMDRo0gF6vR4cOHaBQKEAIYdceO3asaG0ESoMGDQAA3bp1k6xGBhh/zyNHjkRMTEyuC6d0kMKPOuIPohxp5CnR0dGiOjb8BxRfV0rs//bmjTLytmhKZ2RkoHjx4ggICMD333/PttObgp+oRKNv6APA0pcye/ZsAMYbateuXVCpVEzPnc+yZcuwYsUKmyR6c3Jy0LJlS3zzzTeC1fy5c+di5MiRLJrB9McgFoNPfzw6nQ4GgwE6nQ63b99m+xMTEwU3Jn1wEEJw8uRJuLu7FwkpiPzCdxc4OvTNUvw0NfJSKo/0u3j8+LGkiyM1NRXZ2dmCAQDHcRg4cKAgq9kUrVYrqg9PMa3fq1AoEBAQwH4HO3bsgMFgYA+v0NBQyWtRXFxc2Hvq27ev5HGWtH5M77/27dubRR0V1Ejezc0N48aNkxwA8nMPTO2Hox8+b5SRtxRuxYcQgoyMDLi4uMDd3V0QQkkNOV+ki4Yl0phga3S8ExIScOjQIRBCBPVPAwIC8PHHH8PX1xeDBw8WaG6HhIQw7Xcxfv75Zxw9ehRz584V9KFPnz5YvHgxc9NY0z/qfqEQQrB//372cAwODpZUPoyJiSmypd1sZcCAASx225HvSavVClL5VSqVIJ6b+pelZnY1a9ZE165dAQCnT58WPYauK5gKzK1atcqi4Y2IiJCccSoUCpQtW1bgdjEYDNBoNJIZ4dZKC2zbtg2A5YerJU13vpFXq9WYPn26WVhpSkoKc4U5yphmZ2fjxYsXKFmyJCuuAgDTp09nZQT56yGm/ZCNvA2YuhikbpCcnByULl0aJUuWFIg5Aa9+6PxkjhcvXiA5ORlTp04FYPTjiiUX8Y3r7du38csvvwB45RIAwB4upmRmZmLr1q1YsmSJqPbFgwcPBFolYm3QpKjcCjhTuVtT+G4EjUYjuGFNEVOqfB0pW7Ys2rRpAwBYuHChw67Dr8DEcRwGDx4sMEh9+vTBvn37JB+sHMfh559/BiA9k3zy5AkAWEx6sha6EKtWq9GvXz9BEhN5KSsstkAMWC8tQN1At27dEgjqUbRaLUaPHi15fqVKlVhVp8OHD4vmDaSkpMDX1xdKpdJhxpS26+npKQi4qFSpEurVq4exY8fi8ePHzPeelJSEWrVq4datW+z/juSNMvJ8F4Ml0X+VSoXHjx9j/PjxAiOv1+sxcuRIAMYHBh2NPH/+3Mxv+Pvvv5u1y3eh8CN2+L7ezMxMM2lf4NW08tdffxWdgfALCwcEBIi6SqpVq4Z79+4Jyvzt3bvX7DiNRmMxA3b16tWYNm0aduzYIdjOv2bVqlVf+xqYoaGhzL8MGF1ojsK0GpGpRHCVKlXQvn17iy4wakCkjNWYMWMAWB79iiEmDTBhwgRB0pVYQQ2+Rn1e8PT0ZFEnYn7sSZMmCVyPZcuWFXw+d+/exfbt2/HOO+9ISjWkpqaiRIkSKFGiRK56+XmF1mIoVaqUwMjTLHH6fVSrVg16vR5//vkn9Ho9i3qTR/I24O3tzfSyVSqVVaL/bm5uzB3D95mqVCrm/njx4gUWL14sOM+0cEdOTg57QPTp0wcLFixgswH+kzozM1N0FM7/osWmr3wjL1XfVaVSoVKlSgJderEQuOTkZIthWzqdDnq93mxGwD/n5MmTZhEirxOLFy9m0hWmejKOQKoaEeXUqVPMfSEF/V6ljNXJkycxaNAgm9VMTddfQkJC8OOPPwqKaogV1OA/TIYNG8YitOjo3xqorrxprYLw8HAWNUaJj49nLiuKXq+3WHQ7JSUFxYsXh6enJ/uN6fV60doItrJr1y7odDoWqlyhQgWBa5aGr1J3UXZ2NnP53rx5M9eHtr14Y4w8ndrp9XoWSsU3jHweP36Mrl27QqPRoHnz5oiOjkZCQgJ7IlOta+r+uH//Ppt+0hG96WLQ1atXsXr1agDGyBwPDw9mrK0x8uHh4ey12Azkww8/RMeOHQX9MiUnJwczZ87EkSNH2DaxCBhL9S8JISwmObf43dxqaRZl+G4APz8/9tk6UhdcrBoRJSwsTFTEi4+TkxPc3d0ljXzTpk1tzrsAhAbc1dVVVMJY7CHFN2hLly7FkSNH8MMPP0i67B8KlAAAIABJREFUTsSg9/KlS5fQu3dvNqsWW4CWuh+lim6PGTMGV69eRYkSJQRGfsSIEShWrJhVa1dSnDlzBp07d8b48ePZ2oSvry+8vLywe/dupKamshl7r169WK4AdeFWrVoVSqUSxYsXl9011kJ1LCiEEAwfPlz0Cf/06VNs27YN8fHxaNKkCZ4+fYrExES2cEV9tKVLl4azszN+/fVXAEbdEP7onk+dOnXwn//8BzVq1ECnTp3YtLJcuXLsS6QLvmLuGupvBcRj5+vWrYvPPvsMgLSRVygUmDZtGnr27Mm2iR1rKWyT4zh8/fXXaNeuXa4jwtxqadqLhIQEnDhxwi6jL0A4aixdujQ8PDxYSKuYAd27d69Az8gRJCcnSybQ8Tlx4oRorDwhBB999JHFZCkpcptl8I/jP6T4s1m9Xo/AwEAEBwdDo9FYPcOjiUG9e/fG+vXrcejQIQDAJ598YnasWNlLwCj0JnYfLlq0CADMjDwdsFkK8cwN6u7ct28fzp8/D3d3d5Y38v777wtURNVqNVOz3bx5M4BXM3N+vxzFG2PkxfyQUgtA9EOlC6+A0WibRie4ubkhKCiIxcf7+/tLipopFAq89957iI2NhU6nY66AIUOGoG3btgCMBkSv1wv6ev78eURHRwvamj59utmo5ejRoxg4cCAAaSNNjTJdgKPvgY9WqxX8ADmOExhzQggWLVqETz75hGVCisFxHL766qs8l1qzBRo1QWdK+SElJYX9AL/55hvEx8fj4sWL6NmzJy5evCiaU/D++++jXr16+b62JeLj4wVhu1LUq1dP9LiMjAxs376dJcDZiqVZhiVatGgBwPh7oFFZ1oQwU0wHIXQx0tTNWLt2bRw+fNgsa5fjOCxevNhiv/nuGkIIc6PeuHED+/fvx7Fjx3J/oybQGV9SUhIuXbqE+vXrSyZ+AcJCLpUrV2a/y4Iw8m9E+T+tVmvTNJW/Gk558eIFc9fwf0T8BcpSpUqxUbipkd+5cyeWLVuGzMxM/PHHH5gyZYpACRB4FeLm4+ODo0ePYuXKldi/fz8boaxatQqDBg0CYJQk4GdB8hdTbanEZHrjRURECN4TnXFQ9wx1dUVHR6N///7YunWr6KIYIQTz5s1DSEiIwwx9dHQ0Ll26xFxjuUUNWcPly5fZ606dOsHT0xNOTk4oVaqUaMQQnVV9+eWX+b42rZkqVj80Pj4eDRs2zLWNf/75B1lZWWxWR6Gzk7yUkMwPn3/+OY4dO4bo6Gjs2LFDUIrPmnqr1atXx549e3DgwAHMnTsXZ86cQceOHc0WoD08PFhbq1evRlZWFpt1urq64sGDB5IZ2Hwj/8MPP7Aol8TERJb0aKu0AP/3//TpU4vyD4Bxvaxbt27YvHkz6tSpw7aXLFnS4e6a197I0wQosWxFU21pCt/I05uSjuSdnJwExp9fEMPHxwdOTk5wdnYWFNMGwBKf5s+fL9DyJoRg8eLFCAkJwddffw3A+LA4d+4cfvvtN3Zc06ZN4e/vj/Lly+PRo0eoWLEiLl++jHLlyuHixYtISEjA1KlTBYlbYtBz+JrkWq0WoaGhuHbtGnuQUahfksrfGgwGKJVKQX1PKWi8tCOM/LVr19ClSxc8fPiQZWvaoxgDf9ZUoUIFphljMBgQFhaGqlWrMv888Er/Rypc0FrofZqdnQ1nZ2eBW4QQgri4OMF1pQgLC8OzZ8/MjDy9Hx0hjW0J+lBp1aqVYLter7fKlVesWDF07NgRHTt2RPny5QWhmqbHAcYZx8KFCzFq1Cjo9XosWrQIOp0O9evXx/nz50XPdXZ2RrFixZCamopp06ax7fmRBKafNyEET58+NdOkEoOO5vkJkJ6ennmefVnLa2/k+ZrSFKVSydKtxQyQk5MT/Pz8ULJkSTx//hzFihWDXq9HQkICfHx8BKMIfoIMnWK5u7ubGflHjx6hUqVKGD58uGD7V199hUWLFmHDhg2IiooCYHS3mFZTWrt2LWrWrClY+Fu1apVAq92a6XydOnUQGhqK//73v/jkk0+g1WrRsmVLi+nwlB49eiAhIQGZmZlmkQ1iONInr9FomIGleQbUX5sfduzYgapVq+LGjRsCV5RCocCcOXPw7rvvCowtlRM4fvw4evXqlefr0vtUr9eLjnLPnDkjGSPPx83NDXv37oXBYBD0n96nBW3kLUlbWPPw1+v12LJlC/z9/TFjxgzBPk9PT6SlpUGv1wsGHImJiTAYDOwPMNbDlcLJyQkeHh5myW75GTTQkTwhBImJiYK8GikmT56M2rVrMwE5oGDcNQ6XDwbwPoBrAG4CmGTp2LxIDZvKtHIcR1QqlUC29dmzZ1a19dFHH5H69esLtn3xxRdmOtZ+fn6kT58+guMCAwNJmzZtzNr8999/zfS1XVxczKRZz58/Twgh5Oeff5aUdt2wYYNV76Ny5cqkf//+hBCjVKtUe2J/CoWCycTy/ziOE2z39fUVfCb2Zv78+WZ9qFy5cr7bXb9+Pfntt99E9/Xt25d4eHiQtLQ0tu306dMEAFGr1Va1L6YXT7fnptlvDWq1mgAgBw4cEGw/e/YsqVatGomMjMxTu3klMjJS8l6aMWNGru8zJydH8nx6f/Xs2ZPUqFGDnRMVFUVcXV3N7lPTGg50+4oVK0R/B59++mme5L4JIWTJkiWCthYuXGhzG4QQMnbsWFK8ePE8ncsHhaUnD0AJ4BaAqgCcAZwHUEfq+LzqyYeEhEjeKB06dCAAyMmTJ9nxBoNBoO+ck5NDHj9+TAIDA0nbtm0FbWdnZ5vpcDdu3JgAELRRo0YN0qNHD9H+8YsqHDp0SNC/rVu3stcPHz4khBAyb9480fdy8OBBqz6PWrVqkZ49exJCzIsu5OWvTp06JCwsjOl304eBVKEGezBz5kxBH0aOHElWr17tkGtR1q1bRwCQy5cvk7CwMDJhwgRCiPHh36BBg1zPp8ZHqVSafTZhYWFEqVQSjuOIs7MzKzJx9uxZsnXrVjJv3jyr+rh69WoCgGg0GsH2O3fuEJ1OZ8O7tQ+3b9+WvG84jrPqHpE6/5133iGLFy8mc+bMId26dROcQ2so8P8SEhLYfv7DY/369eSXX34xO75JkyZ5NvJUP57+HTlyxOY2CCGs5kNOTk6ezqdYMvKOjq5pCuAmIeQ2ISQbwAYAXXM5x2ZMV9z501g6xafhaUuWLGGRMBQnJyeULVsW8fHxZotvKpXKrH0aDrVv3z627fbt2wJtEj5169Zlr6tVqyZ4zQ+1oguw48aNYyFxlMmTJ1u1MAcY3UF0jcI00YWiVCoxceJENG3aFCqVymK4ZMuWLTFkyBAsWLAA1apVA8dxMBgMDo2Tz8jIgEKhwNKlSwEY379U+TpbuHnzpuRCF5UDSEhIwNChQzF37lwARn/9+fPnc3V5iblkgFdicDSHIycnh0WeXLt2Df/88w+Ln86NAQMGgBAi8IFv3LgRfn5+mD59ulVt2BOqCy8GIQSZmZlW3yOmQnrR0dEYNWoUXrx4waQ2KIMHDzY7X0yexNXVFZ9++qlgQXrjxo1o3LixaO0IazF11wYFBeWpHbr+56hsXMDxIZS+APgqRrEvt9kV07Rsfrgb9dnRsEWaBCMW3iVm5MUICAgAYDQYz549Q+/evSWz6EaNGiXwF/J98RcuXBDEzJv6U/n++V69egmSTyzBN/JSQmO1atVCSEgITp48iSNHjmDmzJmiaepUSIsWTb5z545xdKBQONQn/+LFC7i5ubHv7dSpU4iOjs53QfKGDRsKtL35lCpVCk5OTkhJSWHREjt27GDyDvyHuhjBwcGs8AY/dpuvWwOAFWAHjA/b1NRUQZayLRBC2CLsDz/8YNXaiz0RKwjCh7zUubEGqeSk+Ph4jBgxAq1bt7YoS8z/vVCjuWjRIqhUKoGR9/DwgJeXlyCznNgQXRMXFyeI0mrTpk2eFVlppJwj/fKFHifPcdwQjuPOcBx3Jq/Vefir5AqFQjC6oCNUjUaDFStWsBuJH4b4v//9D4Dx6U/1Jixx8uRJAMYsvUWLFmH9+vVsn+niDk2kotDomEOHDsHNzQ3+/v7MoNAfjE6nQ+XKldnDysfHhz1YrIEaeRqyJ7byf+XKFRbLTJNY6MIwpUGDBjhy5AgCAwPZKJUu+LVr185i4kx+mTx5Mk6dOsU+g5UrV6JRo0ai4ZzWcv/+fTx//lwyBLVevXrIzs7GRx99hJ49e0KpVAqu17lzZ/bdS0GE7koA5jISHMexAUF8fLzNRr5Dhw5M0prjOLNZaVHDkmHmIxUim5mZyfJdevTowUbsM2fORFxcHFuw5UfY0dkancHzjby7u7vZgMlSLYEtW7aA4zjcu3cPd+7cQfny5QVJZ7bKSPChI3lHhlE62sg/BMAPXq3wchuDEBJOCGlCCGmSV2VD/lRJpVJhz5497P9+fn4AjHHm/Fhn/pdUtWpV9mFbk/Ti6uqKFi1a4NKlS2b7+HrSYiMTOhqkq/ElSpSAh4cHWrduzUYDTk5OiI2NZbLDuVUNMmXPnj34/vvv0bZtW0yZMkUyUobvUhDT7ea/P77AFl/W1doiLbZSqlQp+Pv7w9/fHxkZGcxVk5dpbXJyMkJCQphsQLdu3USPUygU4DgOhBBcvHgRer2e/fhq1aoFACwMVgx+DoJOp0NoaCi0Wq0gQgowGjNaSejRo0c2G/mbN28KJKn37duHChUqoFKlSla3UZDkNgOlGeZS8EfJxYsXZ7Ph1atX4/PPP2czeb6hpuHJNCKNH5lmq5GnSXjr1q0THQTmVszEEtTuOLL8pKON/GkANTiO8+M4zhnAZwAsqzDlAX5ygan2CM2g4+Pq6op27dqx/1+6dIlNl6wJhQKMqoGxsbFm/kZ+WJalKRgdYej1erRs2VIQnkd93rTKDj+21xpcXFxw7NgxVoVIDFN3C3U18KFx8IAw9X3BggXQaDQIDw8XFGkJDw/Ps8EnhKBWrVpYt24dAKPs7/79+9n7yY+Yk4uLC7Zu3YqdO3fC3d0dtWvXljx26NChWLJkCbZt24auXbuyB+SSJUsAwCb31Pbt20W12hUKBapUqQLAmEhz6tQpm6ps+fj44N69e3j+/DkePHiApk2bIjY21iwst6jw7rvvon79+pgwYYLofkv9ViqVzI1YsWJFREZGspnBrVu3cPjwYTYD5v/2nz17BqVSyTJy6UMaMIZ9WmPknz17JpiFSenn58eFSB8aO3fuzHMbuSK1ImuvPwAfALgOY5TNFEvH5jW65ubNm6Ir+6bb6J9SqRScz69WHxMTY9U1x48fL4g2oX/Nmzdnx5w/f16wLzg4mL0Wq2DPp0KFCnletT9z5gxp3bq1IKoHLyNihg0bRsLCwkTD/MLCwgSfhVioHz+ChH8sDV0ViyyxBp1ORwCQoKAg8ujRI+Ls7Ey+/vprtv/UqVMEANm2bZvNn8fJkydZP/38/CweK3XPWBO5YhrJpFAozCK/OI4jYWFhZNKkSf/f3pmHR1Flbfy93ek0EPYdgyGDQADZwUALhCAQBRHD6OeGBoUhBEFE0GhABWWRkWFENklGdpFlBkSFcQCVPIBpiMgumwooYQdBDEuW7vP90X0vVdXVe4dAc3/PU0/Std6q6j5169xz3qOaf+TIEZ/Pp2fPngSATCYT7d27V7Wf0kB7rZo1a6b6rIxE0SM9Pd3tdU9ISKBff/1VNe+9995TfeYRaxs2bBD7bNq0Kd1333267Tx+/LhLiK7e9eeh2Q0aNCAA9OKLL+q2cfbs2UFdPx6tN3ny5ID3AQ/RNSXuwCOi/wLQDzsJEVp/VlRUFOx2u24hAsCReTZ27FihNqkt9uGpp8epVauW7v5zcnJARLDZbCLaYdiwYZg5c6boCZhMJq8DVrm5ufjwww99yqTTcvHiRWzcuNFlfqdOnUS0ih6pqalo3ry58H+mpKS4+NyVESRKyBk1QkSiKpc//vqIiAjExMSgfv362LVrFwoLC5GcnCyW8558IO4a5duVu0FXX9rnDqvVikWLFumWedS69B599FGkpqbi5ZdfFvMiIyOFW9EX+NtmUVGREE6bPn26iwzvzYYnIWqLc+slsSklHpKTk7F161YcOXIETZs2VQ1wW61Wl7fxjIwM4VYDbvSkeU/+xIkT2L9/v3hb0lKtWjWXcRm9njx3w/BrrPcWeeXKlaBrHdetWxc//PCDW3sVLKU+8BoKtEY+MjISn3/+uUvoI+fAgQMu2XUcvapMenjKPj1z5gxMJhM+++wzAMC7776L7t27Y+LEiQCgW5VJS506dTB58mS3ynuecOcDVbq13GGxWPDRRx/ho48+0jXSem4dDv/RearK5Y69e/fit99+w4ULF8SPSTlGEx0djQULFvgsL0BEWL58OYqKilRRT23atPFpe6UUMR/zGTVqFBhjqtC7rKwsdOrUCXPmzEFubq5qH3a73UW9kn8nlSF4/hYr4T7ouLg4kT3ZrFmzUvfJc9+5dixKKRNSUFCgqsWcmJiIhIQEbNq0CWfOnEH9+vVVPvji4mJs3boV33//PRYsWCDmK7/j3LhzQ80f6u7qJ5ctW9blt+CLgeV+cz7oXbdu3ZAUs+fXp6SylcPSyF+8eBFJSUmq3tebb77pk7/dVyOvLLHGGEOZMmVEz1OpofHCCy+gSpUq2LBhA6ZNmwbAd79/oCh/ALyIijsdH3+xWCweywICnqtyuYP7vM+fPy8qNSmNQ1RUFPr37+9T9BPgGHx+6qmnMG7cOJWRP3jwoMfteOGOJ598UhR46NmzJwDgn//8JwDg73//OwBHL3PIkCEuRs1TOB2/B8oBXK4u6it820OHDol5ngYOS5rExEQ0bNhQDNxz9VL++1N2VHJzc1W1mAsLC8V2RUVF2L9/vypeno8btWvXDnXq1BHzlR2AyZMnA7hxDXiEm6c3yfj4eFy6dElExvly/fgbynPPPYeTJ0+KfJlg4edbUuJyYWHku3btKgbslHC1uddeew3jx4/3qVyZr+4ApZEnIrz//vtCKVJZaUjZo33llVdQvnx5NGnSxKdjBIryx0DOmPYZM2aELNzR3RsSj04xGAx+9+R57z0qKkoUPdHqq2/ZskV3IF2L1WoV34fdu3erwlrdFcHmPPLIIyAidOzYEQ0bNgRwQxyrZcuWAG5EUC1atEg3goq/0WgxGo2wWCxYvHgxjhw5glGjRol4eX/QKzjeo0cPv/cTKjZu3IjDhw/jkUceAeBwz0yYMAHLli0DAJUx/P3331W1mLWcO3cO2dnZSEtLc6ndqnwLO3z4MAYPHozU1FThJtMaeWWiIeB4wCoTEytVqoToaEfazpAhQ7x28Lg9KVeuHOrUqeOTlpQv8Ddjd9+bYAkLI1+jRg1VdqgWftO9/cAB3+NV+ZeDj9onJCSIMDhl4W7liP8TTzyBy5cvo169ej4dI1DMZrOqF2yz2Vw064NBryYo4HhN5775oUOHqqpdAY58hoKCAqxdu9YlY/DKlSto2bKluDaDBw92Ka7SrVs3t6UPOVzTnPfQLl26hCpVqqBt27b48MMP8fbbb3sM+1QuK1euHB544AERwvrf//4XS5cuFXkNegJXWn1+JVxoKyUlBX369EFycrJLHV1fqFChguiw9OjRAz/99NMtER//73//G7///rvQpuc9VGWFtkuXLuHChQtu33bi4uJ0XYbFxcUYP3489u3bB4PBgDJlyoAxhujoaGHcuSy0OyO/cOFClzESrtS6Z88eTJgwQfj3lQ+hhx9+WOVK0Sv6Ewz83pVUIltYGHnA4c8aPXo0jEYjmjZtqvoSzZ07FwsXLhQDn3w9vSenr8Uhatasic2bN2P48OEwGAyIi4sTRl6ZSad9Mwg0M85fkpKSSmzf7qQSlBQXF6tqb545cwbVq1dHUlISevfurVLiAxx66OXLlxcKkOXKlXO5VmXLlvXqO120aJFKldRsNmPAgAHYvn07hg8fjoULF6JLly548803XQpbKH3F3bp1w549e/DJJ5+IDsRdd92Fy5cvY9OmTThy5IjLsRljeO2119z2yEaMGKF62LobF/KFzp07w2g0Yt26dV61zG8WZrNZDGharVZVDQTOpUuXkJiYqPs7YIzplh4EHG8H06dPR0pKCux2O65evYo5c+YIQ84YE4qh3D2nNfJ6KH3q7733nsilUJZiNJvNql67t6AJf5FG3g8OHz6M2NhYjB07VpVcUlRUpNI94dLCV69edYkEcJcoo0enTp3w4osvYv369ShTpozqi8CzEP3ZXyh5+eWXQ+6P57iTStCirL3JX6l53DmPgedcuXIFBw8exCuvvIJevXqJLGQl5cqV8zsCoUKFCsLocg2ZoqIi2O12EQXEWbRoEa5duwabzYbr169j3LhxOHbsmOqBlp6ejuTkZNxzzz0uvfDo6GjMmTPHrZG/7777sG7dOvE5mNfzY8eOwWaz+ZxNerPhD1st/E1Zz13z6KOPunUp8vPUFrnnv/NKlSoJI++P7LI2CY2/AfNxIcBh/BcuXIgmTZrg73//O06ePOl1v/7w6quvokuXLiH9japwF1tZGlOgcfKKWFECQI888ohbZcrc3Fz6z3/+QwAoOTmZoqOjVcu1cqXupGP1uH79utjP66+/rlKpLA2MRiN16dKlRJQi09LSPOYi8InLxX788ccu8c9KcnNzxTpxcXG6x6xfvz7169fPY7tycnJUUtO8jVlZWTRp0iRVm00mk7g2OTk5FBER4RLTro355/kLgUwNGzYUqqh8ChQunRsRERHwPkoST8qw77zzjss8g8Hg8Xvaq1cv1foff/wxff7557RixQoymUxUr149euqpp4johoJpQUGB13b+8ccfYp9ly5alF198kYhu2JIff/xRtT6fX9q/bS0oRRXKm8rZs2fxwQcf4Msvv8Rf//pXMaChfL2Ki4sTvezVq1eLwhSMMdSuXRvPPfecWJf7d8eMGYPExEQXH+6ePXvQr18/0cswm81i0DM+Pv6muWbcUaZMGbRt27ZE9GVSUlI8FgTn8Cib2NhYPPvss2L+woULQURYsGABjh07hvvuu08oK+oVMgd8c9dcuHBBpfRJzt5ycXExqlWrpuo9v/LKK+LaaEXE+Lba3r6vIZhVq1ZFZmYmJk2aJOb99NNPqhjwYHpu3K1xswXJfMXd4DzgWpCbq416+p4qxz9iYmIwcOBA9OnTB3/9619RUFCA2rVri548HwfTqlrqoeztX7t2DTk5Odi8eTMAxxuru7DjUBSwuVmElZGvUaOG+BFv27ZNhPp98MEHYp19+/bhnXfecTHARIQrV66ojIjSv1tYWOhSFHzHjh0qcTLAEUkwbdo09O7dW8zjoXZDhgwJucaLJ5RqlKGGyxzEx8er5iuvq9lsFjIA3bp1w+LFizFv3jzExcWhTZs2ojh5586dsXz5cvFDHj58uO4xZ8yYgYyMDI/tWrNmja6EbIUKFVRjCYwx8TCxWq347bffdF1QdrtdpTioJymbnJzsMkbxt7/9TYjKaePXTSYT8vPzgypM7qlo9K2Au8F5wHFN+fKoqCjcfffdoraxO5QBEcoQZK76WbVqVWHkr1+/LgZmvaG9bz/++KMY1NYTBeTjKMHIFN903HXxS2MK1l1DRDR58mQCQCNGjBCv7bwSU1pamqqKlN507733CveM9pVT62Lggv+FhYVu26OtXBVMVSB/qV69OlWoUIFGjhxZYsfQukeMRiMlJydTWlqa6jztdjstXryYWrduTTExMQSAxo8fr3KNvPXWW3T16tWgXoUzMjJ03UirV692uRcGg4HS09OpbNmyZDAYyGAwUGxsLFWuXNnFbcPPZc2aNS77Pnr0KOXk5FBCQgLVrVuX0tPTXQqIrFixQqzfsWPHoK87kcN1ULt27ZDsK9RMmjRJJXuhnB5//HFVwQ4A9NNPP6m2z8rKojFjxojPynuilCu4du0aDRgwgLp06SIkK4YPH06VKlXyua3ubMGIESNU6125coXq1atHAGjJkiWBXJYSA6VVGcrfKRRG/sqVKzR58mQaP368+LHzv506dfLJd2o0GikyMlJlvPjEfcx2u52GDx/utXSX1g/MGKNJkyYFfZ7eyMnJUf3IfHmw2Gy2gAys9mHYpEkTFyM/aNAgl2v5xRdfqD5/8MEHHo/zv//9jwCQ1Wp1u47WQPOJV9XS05Lx5TuRnJxMRA6jkpGRoVo2bNgwl3ZMmjRJaAcZjUZ65513hKbL3r17/b7Gepw7d44uX74ckn2FGu0DVXu9GjVqpJq3du1a1fZ8PpHje6m8T8oqXTabjcqWLUstWrQgwKEJNXjwYKpZs6ZLm7Kzs2nq1Kku33F39/xf//qXar0zZ84QAJo5cyYREW3cuLFUqnHp4cnIh5W7BnBEYLz++uvo1q2b8MmR04Xja+gTj2fWU5ebO3cu8vLy0KFDB+zbt8+tNjknMTFR5RuMiIgosUIbSrKzs1Wvq75U5+nYsWNA2bha/+uBAwcwZ84cdO3aVbinlPkC3A+qLcLhTZKWV7VXSklrUeqLKH2/PK9B21b+3fAGj6goU6YMJk2aJLRnqlWrpisTq5RmttlsMJlMGD16NIDg9MeVVK9e3acwwdLAU2Z05cqV8ccff+CBBx4Q4zrucliWLFmC06dPg4hEpJoymdBgMKBhw4Yi7+LLL78U7hots2bNwqhRo1x+C9u3b3dZ9/7773fJRObHiIqKwubNm9G1a1chVXIrE3ZGnmOxWFTa7oAjPd2boedhhxEREbp+z7vuugtHjx5Fbm4uvv32W5dQML1Em169eoXsh+0r3MhwQ9+pUyfExMTgjTfe0F2/sLAQW7duFX5Nf0hJSdHV2FHq1SuNPB/Ymjlzpmp9ZRaxHoMHD0alSpWwfft2TJw4UWQgKlFe56KiIvTs2RNr164VSWuefMWe0JabmzBhAjZu3IiGDRvqSjhYLBbXNdHAAAAgAElEQVRERkaKwdz27duLQTxftIvCkdq1ayMyMhK5ubk4c+YMkpKSRB7JuHHjVNmonGeffVY83J9//nlMmTJFFd4IOGpG8I7UmTNnUFBQ4PI7P378uMh30Ia+tm3b1uVhOW7cOJffPzfyM2fOFH57bQi2v/zyyy9ui6WEDHdd/NKYQuGuUaIMaQRA3333HeXk5LiEsSknZbHl9PR0F79iZmYm7d+/X3z+5JNPxPG0flht8Ws+paWlhfQ83ZGTkyNCz06dOqV6BVZy4cIFlSxxoMdKS0tT7cdoNAr3VnJyMjVr1oyuXbtGROpX5I4dO1JUVJTHsQ1Ow4YNxXZKaVlOnTp1XNwx6enpoo1698PTFB8fL85Bj4cffphat26tu0y5H6vVSjabjVJTUz26m8KJtLQ03WvKXS8pKSmUk5OjWrZv3z4iUl87Xrz84MGDusdJTU0VbrqxY8eK75qSTz75hABQ/fr1qVGjRi770LZRG0pNRLRp0yYCQJUqVRLrTZ8+nYiILl++TE899RSdOnXK63Xh4zpjx44lwBFuHSy4k9w1SrRP80qVKsFisWDcuHFuk3l4seWioiIcPnwY7dq1E8u48BbX6OD75CiFlwoKCrBy5cpSFY6yWCxCNE2pZ6Pl4sWLojexZcuWgI+VkpKi6v3Y7XaMGDECVqtV9K70XqO//fZb7Nu3z6eQN2VKuV6yjV4Y5Pvvv4++ffu6TdBxh8lkQmJiIlauXOki0QA43tpOnjzpNjlG+R2rWrUqDAYDMjMzA5KPvh1x94ZHThfZ4sWL0a1bN5Xo3KpVq1zW3717N8qWLes2szcmJka46bZt24ZLly65fM94JFXfvn1x+PBh1Rur9u21bdu2um/eZrMZDz/8MJYuXSrm8STLTz75BMuWLfOYxbxlyxbk5eWJyLuvv/4agGtCVqgJayNvtVpVhn7t2rUYMmQI3n//fa9qhkSE1atXC1+hwWAQIYHKMEulRoxSeMlut6NGjRpuw7huVihlv379hKGPiYlRlUDkKN0kR48e9VmJU4s21pyIhMvm0UcfRb9+/cQyZeZnZGSkW+1vLbxaFqCvGFqhQgXdeOvVq1dj3rx5iIiI8Nl1xkv4rV+/HoMHD1YZei6BsHv3bly8eNHlfirVFXv16oVGjRr5dMxwgtcGdle+ksiRh/DEE0+IeVpNIwDYtWsXWrRo4TZsdMyYMRgyZAgAx3hNdna2SwePG/kePXogNTVVPGhWr17tIqbnThIkPj4ea9asQc+ePdG7d29MnjxZdEy85SvYbDZ07txZ9R3iYaHaanYhx10XvzSmULtrlBEOcLoP4OH10d1kMBgoPj5eRIyUL19eLNuzZ484nvb1lDFG8fHxuu6gmxlK+dFHHxEA+vTTT12WXbt2TXU+gO/VsbRwdwh3cRkMBrdVog4dOhSwe4hHqSxYsMBlWWZmJiUlJancOsr7kZycTJMmTaL09HSX+240Gqlfv34eXTccbfSMNmLqwIEDYrtp06b5fY7hhLZilvaab9iwQXweOnQoEbm6TwYPHuzxGIsXL1atn5iYKJYVFBRQXFwcAa6Zqg899JDYZsmSJQSAvvzyS91jaLd9+OGHqWPHjmSz2ejHH38kAPTGG2/obnvlyhW316Bv3740cuRI+t///uf1WroDd1IIpRKtD1bPmPMfvrdygWazWfjalcs+//xzEVfvzgfJDV7Lli1V826Wb37z5s3imKdOnVL5G7mxbdiwoQgNXL9+fcDH4jIQ2hKD+fn5qjTzY8eOBWzkT58+TQBo1qxZqvmejAmflA9XrTRD3bp1KTk52W18tzJPQjn+Yjab6dtvv1W1pWrVqgSAatasSfn5+X6fY7ihN74FOEJTbTab6nPfvn1d1ps7d67H/a9du1a1vrLM48GDB1XfNZvNJkIft2zZIpbt37+flixZQnl5ebrHSExMpL59+4rPL7zwAtWuXVtITMydO5cOHTqku+2FCxdU7atSpYr4v3Xr1gSA3n33Xb+uqZI71sgTkWpgR68nzxijtLQ0VQ9Ubx2+jO9jwoQJNH/+fJeBVncPC4PBQE2aNCkVI19QUKB6ozh37pxYxh8A69atoyNHjvj0gwqEFi1aiFhzIkfMcZ06dWjevHl+78tms9G5c+dctEm6du3q1cjz+010w1Br7xmvVRsZGan6TphMJlX8f2ZmpojP3rlzp6otfJtffvnF7/MLR7Rv1fx68mvp7b7xAVl3WK1WAkCPPfYYAaAPP/xQLOM24IMPPqAjR44QY4wWLlxIRETnz58Xx/CWc9C0aVN67LHHxOfRo0eTwWCgtm3bUo0aNTxue/LkSdX5KJPj+DRlyhSP+/CEJyMf1j55LUTk4o/lCo3Tpk1z66slIhiNRlEUo2vXrujQoQNOnTol6p0WFhZi586dbn3wdrtdVcnHZDKVmOqcVkYhMjIS27ZtE0UclH7BM2fOAHBIJ3PfpF4ty2C5du2aajCsZs2aOHnypF9VkXh46rZt21C9enVERkbizz//xIQJE1BQUCDCJDl6g+tEhPnz58NqtQppBqXWDeAIsxw/fjyys7ORmpoq5hcVFSEzMxPdunVDVlYWRowYIfTJtTr3tWrVwsCBA32uZBXu6JWNVP5WvPmlvdVdbtGiBZYtW4bc3Fzs2rULvXv3xtq1awHckB6+7777ULlyZRCRCHt9/fXXxT4iIiKQnZ0tJMm1XL9+XTXwX6VKFVFLulWrVvj+++/datooz89iseDhhx92KToSap16TlgbeT44xuFFLRISEhAfH4/k5GRReebChQuOVxsdzGazGByy2WzYunUrypUrJ2LRufHXKyKhRFuIoCSEw6xWKxISEjBnzhyXhCQ+oKSMBjl79iwAh1HiRrgkBoKuXLniUt7srbfectH+cQe/l2+++SYSEhIwaNAgjBo1ClOnTsVbb72F+fPnuyS13H///boP7uLiYhG/b7FY8Nprr6mWDxw4EBkZGbBYLC5x9USOwcIpU6agoKBA3FNlyUebzYbz5897FOm6E9FGPinvg14Uzvjx4/Hkk0/i4sWLXrV6ypUrh8aNG+P48eMYM2YM7rnnHvTu3RsZGRmiI1O+fHlUqlRJVZ6S/33iiSdw/fp1dO3aFStXrtQ9hjbJiidCnjhxAuXKlcOECRMwcuRIl+1+//13HDx4EK+++ioAoF27djh69ChGjhwpImz4OZQI7rr4pTGV9MCrctIOCubk5JDZbNZd9/nnn1fJ0DLGaOLEiUTkeGU3mUxkMBgoMjKSzGazT6nyrVq1Cum5cvQGf5WDgvXq1aOUlBTxef369ZSSkkKFhYVkt9vphx9+oDNnzgTdDq1Ec6VKlWj48OFiOffDli1b1qd9aQewuRvl/vvvJwA0ZswYl2scHx/v4oJzNxjMB2y1MfHuNFj4PebLevfuLbaZMmUKPfrooyG5juEC91tr74XyPmhdGv7KPyhdL8rpnnvuIQD0888/E5HDNdS+fXsqKiqiHj16UIcOHYiI6OrVqwTArexI1apVVRIWO3bsoPT0dKpQoQI988wzNHDgQIqOjnbZrmLFigSAioqKaPfu3ZSfny8GeZWTMufGX3CnumuUqeXanoDdbldlZAKuPQ3Otm3bXEIDP/30U1itVuzcuRPFxcWw2+2w2Wx44YUXfKq3uWfPnhIJo9S+TTDGVDIKDRo0UPVGevTogYULF8JkMoExhjZt2gRdu1JbYclqtbr05HkP25t0MH8zyc3NVc0n51sXr9C0fv160RtkjMFsNmPgwIEwm80ii7lVq1ZITU3FN9984/IWlZqainXr1qncMwB0qxgxxoTrr3v37oiJiVH1wvbs2YNdu3aFrAZoOKBXaObVV19V3QdtLoe/ha2Vshj/+Mc/xP9t2rTBt99+K6QtAMdv+pNPPsHVq1fFcfjvwl1uy3PPPYdOnTqJz61bt0arVq3QuHFjPPbYY6hevTrOnTun8gjs3LlThG8uWLAAd911F6KionTlQ0qsTq87618aU0kNvCYkJLiECWp7dJ6KHFgsFt03ApPJ5KLAGB8frxuep50MBkOJCJVpe/Ja5UwiR0TNe++9R3a7na5du6YKDZs/fz5t3LgxqDZowwsnTpxI77zzjhAJ4wAOMTN/zkdvUg64tm7dWvUGkZmZ6XLvvBUeUeIt/C8zM5Nyc3NVURV8+enTp/24auFPZmamePNRDroq+eGHH8T1C+RNaPv27bR8+XKRPd24cWPVYCnRjYHYDz/8kFq1akV9+vQRy7hirTZyyx3du3cXobVTpkxRDeDqhU3yLG0e5FCzZk1auHAhAe4zen0Bd3J0jV7cM2OMkpKSVK4ad24dADR58mS3DwF3xlw7Pzk5WYSReYofDxZthSO9ePzmzZsTAFq5ciV17tyZevToIZbVrl2bUlNTg26DMurI3Xnu3LmTLly44HFfnoy80WikZ555RiUz0bhxY9XxtCqgfOJSB97wJIHh7vryZcocCon33AIOv36hCD3t0aMH1apVi5YvXy7mFRYWEuCoIPf2228LVUkiUn1XlNjtdiouLnbZP1dXzc/PF/ILR44coezsbF1Z6k2bNhERUXFxMcXExNDSpUuFGmtubm7A53nHGnmtLoayF601BFq/a4UKFcT/S5cuVfVClD15s9nsNvRSaYyUDxRfywkGijL+W/tj+u6771Rta9SoET355JNieWxsrMpnHyjK8ywsLKS8vDyhW+Pvfjxd37S0NDp27BhVr15dzNOOtWjL+gGgBg0a+HR8X2Lv09LSaNmyZXT+/HnVd+7KlSt+n2844+vDn18/Pf0Yf3Gn2cTnafMblDLSSv78808CQP/4xz9U89PT0wkAjR49mk6fPk3fffcd5efnU82aNcV+srKyxP87duxwaaPdbqfvvvsuqPO8Y428u16g1sgrMzV5TyM2Npb+8pe/UHJyMs2aNUtX2Kpfv36UmZlJDRo0cFkWERFBBoOBIiIiPApclQR8EFkvs5ZrsgMOYSQA9NJLL4nljRs3pieeeCKk7dm2bRsBoFWrVgW0vSdXmslkourVq6sMufbBpvc98LUnT0SUkJDg0ch37tyZatWqJQb4ANCcOXMCOtdwx5dOjp6RDZT169d7NPLz589Xzed1hr/55hv6888/xXz+tsgFyTg83n3z5s1ERNSpUycX1/ChQ4dEPsWJEydCcl5apJHXMfLaV0X+5eNFgMuVK0cPPvggEXmO0nE3Py0trcR77HrwzFuTySTUNJVt2LNnDwGOZAyugqeswKP1UYYC3hs+cuRIQNsrC1Awxty6yPg5ax9sysxnxphfPnki7+MCnTt3dpm3YsWKgM5VElojzzsy2v2NHDlSzH/rrbfEfJvNRvPnz6fY2FgaPXq0mN+nTx8CbsgucOx2u1Ce1PPB33vvvWSz2XyqIhcMJWbkAfwfgB8B2AG00yzLAPAzgEMAHvRlfyXhruE9WqPRSEaj0as/PD8/n3799Vdq0KAB/d///Z/Yj15mpKfepSfj7i5cL1Tnq30IKR9oFy9eFMuaNGlCTZo0UWVlVqlShUJ9H95++21ijOn6NH2FP4TT0tI8ZibrPdiU2wfy0PVU5Qi4EcapnL7++uuAz/VO59ChQ/TVV1+FZF8nTpzQNfJFRUVi/rhx41y2q1ixoqr838SJEwkA/fjjj26PdenSJZfvwdtvv01EDhmPYORCvFGSRr4JgDgA2UojD6ApgN0AzAD+AuAXAEZv+yup6Br+4/bnhz5u3DiaN28eNWvWjIYOHUqNGzemnj176v6gtZMnV4DWxxuIoXd3Hnox8noPNOU6/DWTs2DBAho1alRI/Mm8nX379qVq1aoFvR9+D73V6fU0qBdMG7SyFHC+FY4aNYoGDx5Mhw8fJsAR7RPMA00SWrp06aIbZcb973riZ9HR0TRgwAC/jmO3212+HyXlntFSYkZe7MTVyGcAyFB8XgfA4m0/JWHk/SUvL4/Gjx9Phw8fJiJSFQjwdfJkYLTRGklJSWKZLw8hT4NXWt9x06ZNdfeVn58v3Exa5Tuu5udOaMlXlEliRqOR6tWrF9B+9AqxeIqEKsnIJV8eovXr16dnnnkm5MeWBM4vv/yiG56Yl5dHVapU0X3ratKkCT3++ON+H0sphnYz6+96MvIllQwVDUApAJHnnHfLc/r0abz11lv44YcfQESiPJk7atSoofpsNBo91nB97LHHdD/rJRDpkZ2drdLL4clcVqvVpeBHo0aNdKUToqKiRHKXtuQeTwzR0/X2FavViqFDh6KoqAh2ux12ux0NGjRwKYvoC4sWLcL169fF+a5cudJjubTu3bvrJjuFgtatW8NoNIIxBpPJhMGDB6uOdfjwYRw5cqTk9cElflG/fn0XXSPAUff3999/V0mfcCpWrCiKAAHAe++9h6FDh3o9lrJuwC1Tf9ed9acbvfCvAezTmR4l9z35mQCeVXyeC+BxN/tPBbAdwPaYmJib9eBzC9eFBkBTp06ll19+mQBQtWrVCADVqVNHuAuMRiOlp6cLP7iy3J0n0tPTqUGDBiq3jjKCxGAwqOL4lbjryeuljXtSueTrHD16VDV/3bp1um4cf9CLTefKjv70svVi/jMzM3VDIgFHRFNJDXQrI7DcRUydPXuWHnnkEak8GQYof487duyg3r17uy3zqKVFixbUrVu3Em6hGnjoyevXwFM/BLr7/+jACQB3Kz7Xdc7T238WgCwAaNeuHQVwrJCiLOdXsWJFTJ06Fe3bt0fLli3x+OOPo3HjxnjooYcwbNgw2Gw2TJs2Db169ULt2rWRkpLitQdptVoxY8YMFBYWYsaMGbjnnnvw1VdfYfXq1WIdu92ODRs2YPPmzfjmm28AOHrw1apVw1dffYVKlSrBbrfj+eefF8fjEg68vJ03lcu7774bx48fV50vEJqefGJiIgwGg6rHXVRUBOBGcW9fetqLFi1SVdxp3749UlNT0bx5c7zxxhvYsmWLSvTNm4hVMPA3KLvdDsaYbvHuGjVq4IsvviixNkhuHqtWrRLSG8uXL8fFixddfivuUIrV3RK4s/7+THDtyd8L9cDrEZTSwKu/KAsY8Cw5k8lEqampBIAGDBjgElLpboBTD+W2Sp16vckXrXtljzI9PZ2io6MpISHBa1tmzZpFd999t8sA4c6dOwlwZMMGg7vYdm+RR0q0Yww8v0FZmCQpKUml9V8SUhFEvifySMIH/r3r37//LT/WghKMrukLh7+9AMAZAOsUy8bAEVVzCEBPX/Z3Kxh5ohs3lw9KKg3Nxo0bdUMqfTUw2hJ53iZPlYqgGLjlmXd6xt8fLl++TF999RX17duXYmNjA9oHkftMUWUJPU/oSU0oH3rKgVj+OTIyUlXUI9TcjGxlya0DT3R68MEHqUyZMjRq1KjSbpJbSszIh3q6VYz8jBkzCLgRE8uNzH//+1+xjlaEzJ+are7C8fQmb9mWmZmZuqn/yqidQKhTpw45XvQCw51mjK+JSHpSE2azmdLS0lz0T3gCmLJEozTEklDQu3dvatSoEbVo0eKWzmL2ZOTDWmo4UO6//368/vrriI2NVc3nlVusViv++c9/8jcWMMbwwgsv+BzRYbFYfB55v379utuKVenp6UhNTUV2drbKNw24RvH4is1mw6pVqxAZGYl27doFtA8A2Lt3r7g+SlasWOFThE1iYiLMZjMMBgOMRqMo8JKSkiLkoyMjI0Uk05EjR1BUVOQSdSSRBEOtWrVQu3Zt7N69G4MHDy7t5gSE14HXO5E2bdqgTZs2LvN5eTytUTUYDH6X8ktMTHTRSNfCNdF37NihOl6rVq3QoUMHJCcnq9rF6devn4suuj/wB8Svv/6Kq1evBlSxZunSpbrzeTUgbw9EXpovOzsbiYmJqvWV8wGgW7duokqTwWBQGX+JJBgGDhyIX3/9tbSbERzuuvilMd0q7hotAwYMIAB09uxZInJNc/dnMFFvez4p3RMGg4GSk5MpJyeHYmNjXXzTylA+7SBnsAXCldII2gLVvqI9N+UUSjkH5UC2p9BTiSRQPvvsM+rQoQOdPHmytJviFgQTQikB/va3v6FOnTqix2yxWDBgwABkZmaCiGC3230OCwQcoYE81FEJEYmqQ3a7HatXr8batWtVYYR8Pb7Oiy++6OKqCZaoqCiRBLJr1y6sW7cOrVq1woMPPuj3vuLi4nDu3Dn8/vvvAByurZ07d/q0rdVq1e3JK1GGjkZGRmLcuHElkggluTO5evUq+vbtC8BRI/a2xJ31L43pVu3J6xFMSJ07VUPGmFBS1Fvuy6SVUQ6Eu+++m5599lmXffuDpzb68ubjz/WVUS+SkkKpR3MrAznwWjL0798fgwYN8juNPiUlxSVxx2AwoEyZMpg5cyYaN27ssozXGTUYDIiIiIDRaBSDkkr69OkTdE+2VatWMJlMLvM3bNjg0/ZEhO7du+umkgOOxKhFixZ53Ic7+QY9LBYLqlWrhnHjxiErK8unNkokvsAYQ+PGjVG7du3SbkrASHdNAHCdGe4i8HfQFQAiIiJgs9lgNBoxatQoVK5cWbgldu7ciQMHDoh1+/Tpg/j4eFSrVg0XLlwQg4rZ2dm4dOkS3n//fbFuz549gz6/2bNnq4xl3bp1kZeXh6SkJN2IGS2MMWzYsAFZWVluIxK0Bce1aN0wngZSlcdZv349AAQ18CyRKNm9e7fI2L4dkUY+APR6mf70nrOzs1V+9sqVKyMjI0N8TklJwfz581FQUACj0YiePXvqGi2LxYL33nsPBoNBRJbopdv7S926dfHuu++iTZs26Nu3L2JjY5GXl+f3fnibV65cievXr2PTpk1imbeekafoGi0rV650+SyNvCRUREZGIjIysrSbETDSXRMAvJepjdUO1fYWiwXTp0+HyWQCEeGll17CkCFDdOPLq1WrJlw3ZrM5pKGD0dEO4dDDhw/j6aef9vmVdevWrYiLi8P333+P1NRUrFu3DpMnTxYuIIPBgNatW3vdj8ViQUZGhtcHqDtlT4lEAjnwGijBDvZ5215ZjBvQ18fxRRkxGJTa2MOGDaPKlSv7tN3KlStdwi9zcnLIZDIFHHbqjZKqtiWR3A5ADryGHl97mYFsb7VaMW/ePJX/m4hc9OPHjRsnkoCIKCSuGiVxcXEYOXIkypcvj9dee03lblHyxx9/YPbs2aK9586dA6DW2s/Ozlb5NX0ZfLVarT5r0Ddv3hyJiYlo3ry513UlkjsJ6ZO/BcnOzlbJ9PLoGu7a4QO/3MAzxhAREVEiWZ484zUmJgYAcPLkSVy8eBH33nuvWGfLli149dVX0aVLF9x7773CyFevXl2sk5iYCKPR6LHghxLt4LanCCZ/1pVI7jRkT/4WhBtEjtFoVIVqKrXNgRsut1Bjs9kwZ84cnD17Fnv27EG/fv0QHR2NZs2aqdYrV64crl27hhUrVgAAzp8/jwoVKsBsNot1LBYLZs+eLSormc1mj1FJ/oRQ+rOuRHKnIY38LQjPqOXwSBxtgRAeO8/XCbVxUz5oli1bhk8//VR8XrNmjfh/x44dAIB3330XgKMEGs8SVJKamorZs2ejR48emD59usfetj+D28EOhEskYY07Z31pTLfTwGtJo9VjNxqNqoFKrX48QqwJw6lSpQoNGzaMnnrqKRcpY7vdTosWLaLmzZuL+VeuXKELFy7o7svXLFYuHZycnOyzPrzMepXcyUBq19x+aAdRbTYbFi1aBIvFAqvViqlTp7ps46smjD+UL18e+fn56NWrF5YtWybmr1+/HmvWrFG5XMqVK4e+ffti/fr1uu4jX/ILrFYrEhMThbaPN7cOx2KxSD+8RKKDdNfcomj98kq0A7MlyfHjx7FgwQI8++yzGD16tJgfERGBli1buqzPNehHjhzpsswXt4o2Ckf62CWS4JA9+VsUi8WCUaNGqSQLeAKRtmg34L1wd6C8+eabqFWrFhhjmDRpEgCgbdu2OHPmDCpXrizWi4yMxNWrV3HXXXcBuBFGqT0nb1msiYmJMJlM4txKKmpIIrlTkD35W5jKlSuLqlBKyQKLxYIZM2aInr7RaMTMmTNLxF0xfvx4DBs2DADQrFkzJCcno3///sjLy8OqVavEek2aNAEAzJ07FwDw9NNP6+7PW36B8twYY6rBZYlE4j/SyN/C8BJ4RqPRRbJA67MPdSKUHhUrVsQff/yBQYMGIT8/H/n5+QAchjkzMxNRUVHYuXMnkpOT0atXr4CPw8+FiGCz2aS7RiIJAumuuYXx5N7wR6UxVOzfvx+XLl1CcXExypcvj1OnTgEA1q1bhwoVKiApKQmfffYZ9u/fH9RxSuPcJJJwRRr5Wxx3USP+qDSGitGjRyM9PR1EhEGDBuHjjz9G69atRVHyJUuWoHHjxnj55Zc97seXik/9+/cH4FDklFEzEkngML1Qt9KiXbt2tH379tJuhsQLdrtdjAdkZWVh0KBBPm/rTYJAKdlgMBgwa9YsKRsskXiBMfYDEbXTWyZ98hK/MRgMuO+++wA4qkj5Q3Z2NgoKCmCz2VBQUODib+fL7XY7iouLMWzYMJ8EyiQSiT7SyEsCon379qhcubIw9r5SrVo1obljt9tFcXROYmKiiCgCIAdeJZIgkUZeEhA1atTApUuX/C6LduHCBd2wUM7evXvRsGFDGAyGEimEIpHcaUgjLwkILpp26dIlv7bjyU6AoxassifPa7UeOHAAdrsdnTp1krLBEkmQSCMvCYixY8fixIkTqsIgvsIlGWw2G4YPHy587tparZs3bw6+oRLJHY408pKAMBqNQsLAH7S6O8rBV21tViLyWj1KIpF4Jigjzxibwhg7yBjbwxj7jDFWWbEsgzH2M2PsEGPsweCbKgkH9ITXuMsmNTUVCQkJpdEsiSRsCbYnvwFAMyJqAeAwgAwAYIw1BfAUgHsBPARgNmNMX1JRckdhsVjQu3dv1Z51v6YAAAd1SURBVDylRPLkyZNhNpt9qh4lkUi8E1TGKxGtV3zcCuBx5/+PAlhGRAUAjjLGfgYQD0AGPEtQu3Ztt8ssFgs2btx4UzN5JZJwJpQ++QEAvnL+Hw3guGJZnnOeRIKUlBRRvjAyMlLVW/dF8kAikfiO1548Y+xrAHpdrzFE9LlznTEAigEs8bcBjLFUAKkAEBMT4+/mktsQLie8cuVKPPbYY8KYe5M8kEgk/uPVyBNRd0/LGWPPA+gNoBvdEMI5AeBuxWp1nfP09p8FIAtwaNd4b7LkdsdqtWLEiBEoLCzE5s2b0bx5c1gsFp/KA0okEv8INrrmIQDpAPoQ0VXFoi8APMUYMzPG/gKgIYDcYI4lCR/0jDngiLLhma5SYlgiCQ3BSg3PBGAGsMFZwWcrEaUR0Y+MsRUA9sPhxhlKRDenKKnklkepF280GvHbb78hKysLL730EoqKimA0GjFt2jTZi5dIQkCw0TUNPCybCGBiMPuXhCdcC3/RokWYP38+/vWvfwFQZ8IqwyolEkngyIxXSanAe+ncbaPMgpVIJKFDVoaSlApWqxUff/wxlEVrDAYDiMglrFIikQSO7MlLSgWthg3g0Jc3GAyYPn269MdLJCFCGnlJqaCnYQNIf7xEEmqkkZeUChaLBffff39pN0MiCXukkZeUCllZWdi0aZPusooVK97k1kgk4Ys08pJSQVsgRMnUqVNl8W6JJERIIy8pFbQFQpTY7XZZvFsiCREyhFJSKqSmpgJw9Ohr1KiBpUuXwm63A4CUNJBIQog08pJSIzU1Fc2bN0e3bt0AOEoKPvLII0hPT5chlBJJiJDuGkmpwsXKeC8+Pj5eGniJJIRIIy8pVbhYmdFolG4aiaQEkO4aSanCxcpkNSiJpGSQRl5S6lgsFmncJZISQrprJBKJJIyRRl4ikUjCGGnkJRKJJIyRRl4ikUjCGGnkJRKJJIyRRl4ikUjCGKYsv1baMMbOAfg1wM2rAzgfwubcDshzvjOQ53xnEMw51yOiGnoLbikjHwyMse1E1K6023Ezked8ZyDP+c6gpM5ZumskEokkjJFGXiKRSMKYcDLyWaXdgFJAnvOdgTznO4MSOeew8clLJBKJxJVw6slLJBKJRENYGHnG2EOMsUOMsZ8ZY2+UdntCBWPsbsbYRsbYfsbYj4yxl53zqzLGNjDGfnL+reKczxhj053XYQ9jrE3pnkFgMMaMjLGdjLE1zs9/YYxtc57XcsZYpHO+2fn5Z+fy2NJsdzAwxiozxv7DGDvIGDvAGLOE831mjL3i/E7vY4wtZYyVCcf7zBibxxg7yxjbp5jn931ljPV3rv8TY6y/P2247Y08Y8wIYBaAngCaAniaMda0dFsVMooBjCKipgA6ABjqPLc3AHxDRA0BfOP8DDiuQUPnlArgo5vf5JDwMoADis9/B/ABETUAcBHAQOf8gQAuOud/4FzvduVDAP8josYAWsJx/mF5nxlj0QCGA2hHRM0AGAE8hfC8zwsAPKSZ59d9ZYxVBTAWQHsA8QDG8geDTxDRbT0BsABYp/icASCjtNtVQuf6OYAeAA4BqOOcVwfAIef/mQCeVqwv1rtdJgB1nV/8BwCsAcDgSBCJ0N5vAOsAWJz/RzjXY6V9DgGccyUAR7VtD9f7DCAawHEAVZ33bQ2AB8P1PgOIBbAv0PsK4GkAmYr5qvW8Tbd9Tx43vjCcPOe8sML5itoawDYAtYjolHPRaQC1nP+Hw7WYBiAdgN35uRqAS0RU7PysPCdxvs7lfzjXv934C4BzAOY73VQfM8aiEKb3mYhOAPgHgN8AnILjvv2A8L/PHH/va1D3OxyMfNjDGCsPYCWAEUR0WbmMHI/2sAiRYoz1BnCWiH4o7bbcZCIAtAHwERG1BnAFN17hAYTdfa4C4FE4Hm53AYiCq0vjjuBm3NdwMPInANyt+FzXOS8sYIyZ4DDwS4holXP2GcZYHefyOgDOOuff7teiI4A+jLFjAJbB4bL5EEBlxhgvVak8J3G+zuWVAFy4mQ0OEXkA8ohom/Pzf+Aw+uF6n7sDOEpE54ioCMAqOO59uN9njr/3Naj7HQ5G/nsADZ0j85FwDOB8UcptCgmMMQZgLoADRPRPxaIvAPAR9v5w+Or5/BTnKH0HAH8oXgtveYgog4jqElEsHPfxWyLqB2AjgMedq2nPl1+Hx53r33a9XSI6DeA4YyzOOasbgP0I0/sMh5umA2OsnPM7zs83rO+zAn/v6zoASYyxKs63oCTnPN8o7UGJEA1s9AJwGMAvAMaUdntCeF6d4HiV2wNgl3PqBYc/8hsAPwH4GkBV5/oMjkijXwDshSN6odTPI8BzTwSwxvl/fQC5AH4G8G8AZuf8Ms7PPzuX1y/tdgdxvq0AbHfe69UAqoTzfQbwDoCDAPYBWAzAHI73GcBSOMYdiuB4YxsYyH0FMMB5/j8DeMGfNsiMV4lEIgljwsFdI5FIJBI3SCMvkUgkYYw08hKJRBLGSCMvkUgkYYw08hKJRBLGSCMvkUgkYYw08hKJRBLGSCMvkUgkYcz/A8soCmakWwUwAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h6gGN-a-UoBV"
      },
      "source": [
        "**Anotações e desenhos em uma subplotagem**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EpLYcch7TWUJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        },
        "outputId": "2f036248-cf04-49c0-d5d3-521268fb762f"
      },
      "source": [
        "fig = plt.figure()\n",
        "\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "\n",
        "data = pd.read_csv('/content/drive/MyDrive/dados_pandas/pydata-book-2nd-edition/examples/spx.csv', index_col=0, parse_dates=True)\n",
        "spx = data['SPX']\n",
        "\n",
        "spx.plot(ax=ax, style='k-')\n",
        "\n",
        "#criar anotações no gráfico\n",
        "crisis_data = [\n",
        "               (datetime(2007,10,11), 'Peak of bull market'),\n",
        "               (datetime(2008, 3, 12), 'Bear Stearns Fails'),\n",
        "               (datetime(2008, 9, 15), 'Lehman Bankruptcy')\n",
        "]\n",
        "\n",
        "for date, label in crisis_data:\n",
        "  #desenhando as setas\n",
        "  ax.annotate(label, xy=(date, spx.asof(date) + 75), xytext= (date, spx.asof(date) + 225),\n",
        "              arrowprops=dict(facecolor='black', headwidth=4, width=2, headlength=4),\n",
        "              horizontalalignment='left', verticalalignment='top')\n",
        "\n",
        "#Faz um zoom no período de 2007 a 2011\n",
        "ax.set_xlim(['1/1/2007', '1/1/2011'])\n",
        "ax.set_ylim([600, 1800])\n",
        "\n",
        "#adicionando título\n",
        "ax.set_title('Datas importantes da crise financeira entre 2008-2009')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Datas importantes da crise financeira entre 2008-2009')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "YQeKXS4AG4Zp",
        "outputId": "183c483d-a252-42fb-a296-e7c65527ccc4"
      },
      "source": [
        "fig = plt.figure()\n",
        "#dimensões da plotagem\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "\n",
        "#dimensões das formas geométricas\n",
        "rect = plt.Rectangle((0.2, 0.75), 0.4, 0.15, color='k', alpha=0.3)\n",
        "circ = plt.Circle((0.7, 0.2), 0.15, color='b', alpha=0.3)\n",
        "pgon = plt.Polygon([[0.15, 0.15], [0.35, 0.4], [0.2, 0.6]], color='g', alpha=0.5)\n",
        "\n",
        "ax.add_patch(rect)\n",
        "ax.add_patch(circ)\n",
        "ax.add_patch(pgon)\n",
        "\n",
        "#incluindo título\n",
        "ax.set_title('Plotando figurinhas')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HG8UALpuMVyH"
      },
      "source": [
        "**Salvando plotagens em arquivos**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OkT-3pzKMOxX"
      },
      "source": [
        "#salvando em svg\n",
        "plt.savefig('/content/drive/MyDrive/dados_pandas/figpath.svg')\n",
        "\n",
        "#salvando um png com o mínimo de espaços em branco\n",
        "plt.savefig('figpath.png', dpi=400, bbox_inches='tight')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5RMeenduOUMU"
      },
      "source": [
        "#Slavando figuras em objeto do tipo arquivo\n",
        "buffer = BytesIO()\n",
        "plt.savefig(buffer)\n",
        "plot_data = buffer.getvalue()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YicXUnaPPXxs"
      },
      "source": [
        "# Plotagem com o pandas e o seaborn"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A0UyqyuiPcm5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "6a5f3a3e-cace-4192-df6c-6cb63df5dea1"
      },
      "source": [
        "#plot cria um gráfico de linha\n",
        "s = pd.Series(np.random.randn(10).cumsum(), index=np.arange(0,100,10))\n",
        "s.plot()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e701650>"
            ]
          },
          "metadata": {},
          "execution_count": 38
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "01ODcWbfPik4",
        "outputId": "fc4490c1-8a6a-4570-d988-4022a6601670"
      },
      "source": [
        "df = pd.DataFrame(np.random.randn(10,4).cumsum(0), columns=['A','B','C','D'], index=np.arange(0,100,10))\n",
        "df.plot()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e6b7310>"
            ]
          },
          "metadata": {},
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nU3OSAI4SF7v"
      },
      "source": [
        "**Plotagem de barras**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "nNCTiE_pRCCo",
        "outputId": "52cb2347-ff1b-4f4e-e022-0ab6a15b673a"
      },
      "source": [
        "fig, axes = plt.subplots(2,1)\n",
        "data = pd.Series(np.random.rand(16), index=list('abcdefghijklmnop'))\n",
        "data.plot.bar(ax=axes[0], color='k', alpha=0.7)\n",
        "\n",
        "data.plot.barh(ax=axes[1], color='darkred', alpha=0.7)"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e5a1dd0>"
            ]
          },
          "metadata": {},
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 234
        },
        "id": "6x7n9LiCSpfm",
        "outputId": "5a7beff9-ff30-427e-aed9-5a75f6874560"
      },
      "source": [
        "df = pd.DataFrame(np.random.rand(6,4), index=['one','two','three','four','five','six'], columns=pd.Index(['A','B','C','D'], name='Genus'))\n",
        "df"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Genus</th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>D</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>one</th>\n",
              "      <td>0.807738</td>\n",
              "      <td>0.658596</td>\n",
              "      <td>0.732575</td>\n",
              "      <td>0.883559</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>two</th>\n",
              "      <td>0.078954</td>\n",
              "      <td>0.556136</td>\n",
              "      <td>0.585192</td>\n",
              "      <td>0.996500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>three</th>\n",
              "      <td>0.725126</td>\n",
              "      <td>0.743556</td>\n",
              "      <td>0.778960</td>\n",
              "      <td>0.179229</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>four</th>\n",
              "      <td>0.790585</td>\n",
              "      <td>0.107973</td>\n",
              "      <td>0.857333</td>\n",
              "      <td>0.862193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>five</th>\n",
              "      <td>0.739372</td>\n",
              "      <td>0.178711</td>\n",
              "      <td>0.837530</td>\n",
              "      <td>0.784102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>six</th>\n",
              "      <td>0.844193</td>\n",
              "      <td>0.532199</td>\n",
              "      <td>0.265018</td>\n",
              "      <td>0.515175</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Genus         A         B         C         D\n",
              "one    0.807738  0.658596  0.732575  0.883559\n",
              "two    0.078954  0.556136  0.585192  0.996500\n",
              "three  0.725126  0.743556  0.778960  0.179229\n",
              "four   0.790585  0.107973  0.857333  0.862193\n",
              "five   0.739372  0.178711  0.837530  0.784102\n",
              "six    0.844193  0.532199  0.265018  0.515175"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "epjiAI7XT5JH",
        "outputId": "2d77f735-55ca-4fc2-ab1a-46ee27327504"
      },
      "source": [
        "df.plot.bar()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e5f6d10>"
            ]
          },
          "metadata": {},
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "iYKHW3pqUC62",
        "outputId": "d6b15e10-1d2f-4172-a11e-ebb813d046e3"
      },
      "source": [
        "df.plot.barh(stacked=True, alpha=0.5)"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e40c9d0>"
            ]
          },
          "metadata": {},
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "8rQPamO4UcnG",
        "outputId": "b7f44c4c-e43e-4a06-8c80-aaaacae719b9"
      },
      "source": [
        "tips = pd.read_csv('/content/drive/MyDrive/dados_pandas/pydata-book-2nd-edition/examples/tips.csv')\n",
        "party_counts = pd.crosstab(tips['day'], tips['size'])\n",
        "party_counts"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>size</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>day</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Fri</th>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sat</th>\n",
              "      <td>2</td>\n",
              "      <td>53</td>\n",
              "      <td>18</td>\n",
              "      <td>13</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sun</th>\n",
              "      <td>0</td>\n",
              "      <td>39</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Thur</th>\n",
              "      <td>1</td>\n",
              "      <td>48</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "size  1   2   3   4  5  6\n",
              "day                      \n",
              "Fri   1  16   1   1  0  0\n",
              "Sat   2  53  18  13  1  0\n",
              "Sun   0  39  15  18  3  1\n",
              "Thur  1  48   4   5  1  3"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "YnSpwoP9VwfW",
        "outputId": "eb4dee2a-200a-40db-afb2-b245c224e765"
      },
      "source": [
        "party_counts = party_counts.loc[:, 2:5]\n",
        "party_pcts = party_counts.div(party_counts.sum(1), axis=0)\n",
        "party_pcts"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>size</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>day</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Fri</th>\n",
              "      <td>0.888889</td>\n",
              "      <td>0.055556</td>\n",
              "      <td>0.055556</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sat</th>\n",
              "      <td>0.623529</td>\n",
              "      <td>0.211765</td>\n",
              "      <td>0.152941</td>\n",
              "      <td>0.011765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sun</th>\n",
              "      <td>0.520000</td>\n",
              "      <td>0.200000</td>\n",
              "      <td>0.240000</td>\n",
              "      <td>0.040000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Thur</th>\n",
              "      <td>0.827586</td>\n",
              "      <td>0.068966</td>\n",
              "      <td>0.086207</td>\n",
              "      <td>0.017241</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "size         2         3         4         5\n",
              "day                                         \n",
              "Fri   0.888889  0.055556  0.055556  0.000000\n",
              "Sat   0.623529  0.211765  0.152941  0.011765\n",
              "Sun   0.520000  0.200000  0.240000  0.040000\n",
              "Thur  0.827586  0.068966  0.086207  0.017241"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "id": "uxduJOt6WFoN",
        "outputId": "f84bfed3-789c-41b2-ecf0-c45f8e21ab9a"
      },
      "source": [
        "party_pcts.plot.bar()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e9b2810>"
            ]
          },
          "metadata": {},
          "execution_count": 46
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "KyT1zKe9WXFv",
        "outputId": "dedf4cf9-028a-42b4-aee5-98b6217a857b"
      },
      "source": [
        "tips['tip_pct'] = tips['tip'] / (tips['total_bill'] - tips['tip'])\n",
        "tips.head()"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>tip_pct</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.063204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.191244</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.199886</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.162494</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.172069</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   total_bill   tip smoker  day    time  size   tip_pct\n",
              "0       16.99  1.01     No  Sun  Dinner     2  0.063204\n",
              "1       10.34  1.66     No  Sun  Dinner     3  0.191244\n",
              "2       21.01  3.50     No  Sun  Dinner     3  0.199886\n",
              "3       23.68  3.31     No  Sun  Dinner     2  0.162494\n",
              "4       24.59  3.61     No  Sun  Dinner     4  0.172069"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "oYc7ZiDZXUQ-",
        "outputId": "88ae4b84-45a9-47f5-ad0a-75007ccc3a00"
      },
      "source": [
        "sns.barplot(x='tip_pct', y='day', data=tips, orient='h')"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e4c6410>"
            ]
          },
          "metadata": {},
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GzsqunqYX2-w"
      },
      "source": [
        "As linhas pretas representam o intervalo de confiança de 95%"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "NfKaoPWrYKhk",
        "outputId": "c71e67ac-17db-4993-812c-dd6a5e1e6992"
      },
      "source": [
        "sns.barplot(x='tip_pct', y='day', hue='time', data=tips, orient='h')\n",
        "\n",
        "#outra opção de estilo\n",
        "#sns.set(style='whitegrid')"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e1cd590>"
            ]
          },
          "metadata": {},
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEHCAYAAACwUAEWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAW6UlEQVR4nO3de3CV9Z3H8c83CSRcIsitUWlMsCkCAqmJtbar1aWrbNW2Y9G6riLalQra7shAxx1aim53xgnu7mxtXRfWHYplWytYdVvrqFV0W8YLkQgoUAShDbQKUZeL3PnuH+cRDzH55STn8pxz8n7NZPKc81zy/eWQ8+H3/M7ze8zdBQBAZ0riLgAAkN8ICgBAEEEBAAgiKAAAQQQFACCoLO4CMmnYsGFeU1MTdxkAUFCam5t3ufvwztYXVVDU1NRo1apVcZcBAAXFzLaF1nPqCQAQRFAAAIIICgBAEEEBAAgqqsHs9a1tapizJO4yAGRI84KpcZcA0aMAAHSBoAAABBEUAIAgggIAEERQAACCCAoAQBBBAQAIIigAAEEEBQAgqKiuzAaQMGDTkyo5tC/uMtI2derTcZdQMKqqqtTU1JSVYxMUQBEqObRPpQd3x11G2rZvL/w2FAOCAihCx/oOiLuEjKgeVhl3CQWjqqoqa8cmKIAitK/u4rhLyIglTAqYFxjMBgAEERQAgCCCAgAQRFAAAIJyGhRmNtfMXjOzNWbWYmbn5vLnAwC6L2efejKz8yRdJulsdz9oZsMk9c3VzwcA9EwuexSnSNrl7gclyd13ufsOM9sahYbMrNHMVkTL883sv8xshZltMbNv5bBWAEAkl0HxpKSPm9nvzexeM/t8CvucKekSSZ+W9D0z65PVCgEAH5GzU0/uvtfMGiSdL+kiSQ+a2e1d7ParqAdy0MzelvQxSa3JG5jZdEnTJam6ulrNXKADABmV0yuz3f2opBWSVpjZWknXSzqiD3s2Fe12OZi0fFQd1OvuCyUtlKTGxkbPcMkA0Ovl7NSTmY02s7qkp+olbZO0VVJD9NxXc1UPACA1uexRDJR0j5kNVqIX8YYSp4zGSLrfzP5Rid4GACCP5HKMolnSZztY9b+SPtnB9vPbPT4rO5UBAEK4MhsAEERQAACCCAoAQBBBAQAIIigAAEEEBQAgiKAAAAQRFACAIIICABBEUAAAgggKAEAQQQEACCIoAABBBAUAIIigAAAEERQAgCCCAgAQRFAAAIIICgBAEEEBAAgiKAAAQQQFACCIoAAABBEUAIAgggIAEERQAACCCAoAQFBZ3AVk0vrWNjXMWRJ3GUDeal4wNe4SUIDoUQAAgggKAEAQQQEACCIoAABBBAUAIIigAAAEERQAgCCCAgAQRFAAAIKK6spsoDcYsOlJlRza16N9p059OiM1VFVVqampKSPHQv4jKIACU3Jon0oP7u7Rvtu392w/9G4EBVBgjvUd0ON9q4dVZqSGqqqqjBwHhYGgAArMvrqLe7zvEiYFRA8wmA0ACCIoAABBBAUAIIigAAAEERQAgKBYgsLM5prZa2a2xsxazOzcwLbTzOzUXNYHAPhQzj8ea2bnSbpM0tnuftDMhknqG9hlmqR1knbkoDwAQDtx9ChOkbTL3Q9KkrvvcvcdZjbPzF42s3VmttASpkhqlLQ06nn0i6FeAOjVzN1z+wPNBkr6raT+kp6W9KC7P2dmQ9z9nWibByT93N3/x8xWSJrt7qs6Od50SdMlqbq6umHbtm25aAYAFA0za3b3xs7W57xH4e57JTUo8ea+U9KDZjZN0kVm9qKZrZX0l5LGpXi8he7e6O6Nw4cPz1bZANBrxTKFh7sflbRC0oooGL4haYKkRnf/o5nNl1QRR20AgBPFMZg9WtIxd98UPVUvaaMSQbErOjU1RdKyaP0eSZmZyQxAr3H48GG1trbqwIEDcZeSNyoqKjRy5Ej16dOnW/vF0aMYKOkeMxss6YikN5Q4DfWeEp9u+rOkl5O2XyzpPjPbL+k8d9+f23IBFKLW1lZVVlaqpqZGZhZ3ObFzd7W1tam1tVW1tbXd2jfnQeHuzZI+28Gq70Rf7bdfLml5tusCUFwOHDhASCQxMw0dOlQ7d+7s9r5cmQ2gaBESJ+rp74OgAAAEERQA0APvvfee7r33XknSjh07NGXKlJgryh6CAgB6IDkoTj31VC1btqyLPQoXt0IFgB64/fbbtXnzZtXX16uurk7r16/XunXrtHjxYj3yyCPat2+fNm3apNmzZ+vQoUN64IEHVF5erscff1xDhgzR5s2bdcstt2jnzp3q37+/Fi1apDPPPDPuZnWIHgUA9MBdd92lM844Qy0tLVqwYMEJ69atW6eHH35YL7/8subOnav+/ftr9erVOu+887RkyRJJ0vTp03XPPfeoublZd999t2bOnBlHM1JCjwIAMuyiiy5SZWWlKisrNWjQIF1++eWSpPHjx2vNmjXau3evVq5cqSuvvPL4PgcPHoyr3C4RFACQYeXl5ceXS0pKjj8uKSnRkSNHdOzYMQ0ePFgtLS1xldgtnHoCgB6orKzUnj17erTvSSedpNraWj300EOSEldNv/rqq5ksL6MICgDogaFDh+pzn/uczjrrLM2ZM6fb+y9dulT333+/Jk6cqHHjxunRRx/NQpWZkfP7UWRTY2Ojr1rV4W0rAPQy69ev15gxY+IuI+909HvJu/tRAAAKC0EBAAgiKAAAQSkFhZmVZrsQAEB+SrVHscnMFpjZ2KxWAwDIO6kGxURJv5f0n2b2gplNN7OTslgXACBPpHRltrvvkbRI0iIz+7yk/5b0r2a2TNI/uvsbWawRANLWMGdJRo/XvGBql9uUlpZq/PjxOnz4sMrKyjR16lTddtttKikp0apVq7RkyRL94Ac/yGhd2ZBSUERjFJdKukFSjaR/lrRU0vmSHpf0ySzVBwAFq1+/fsen6Xj77bd1zTXXaPfu3brjjjvU2NioxsZOL13IiCNHjqisLP2ZmlIeo5D0ZUkL3P1T7v4v7v6Wuy+T9ETaVQBAkRsxYoQWLlyoH/7wh3J3rVixQpdddpkkaf78+brxxht14YUXatSoUcd7GVu3btWYMWN00003ady4cbr44ou1f/9+SdLmzZs1efJkNTQ06Pzzz9eGDRskSdOmTdPNN9+sc889V9/+9rczUnuqUTPB3fd2tMLdv5WRSgCgyI0aNUpHjx7V22+//ZF1GzZs0LPPPqs9e/Zo9OjRmjFjhiRp06ZN+ulPf6pFixbpqquu0vLly3Xttddq+vTpuu+++1RXV6cXX3xRM2fO1DPPPCNJam1t1cqVK1VampkPrKYaFEfM7BZJ4yRVfPCku9+YkSoAoJe79NJLVV5ervLyco0YMUJvvfWWJKm2tlb19fWSpIaGBm3durXLacqvvPLKjIWElHpQPCBpg6RLJN0p6W8lrc9YFQDQC2zZskWlpaUaMWKE1q8/8S00eWry0tJSHTlypMPn9+/f3+U05QMGDMho3amOUXzC3b8raZ+7/1iJge1zM1oJABSxnTt36uabb9att94qM0vrWLmepjzVHsXh6Pt7ZnaWpD9LGpGdkgAg81L5OGum7d+/X/X19cc/Hnvddddp1qxZGTn20qVLNWPGDH3/+9/X4cOHdfXVV2vixIkZOXZ7KU0zbmZ/J2m5pPGSFksaKOm77v4fWamqh5hmHMAHmGa8Yz2ZZjzYozCz5Oi7Ifr+o+h7Zk+CAQDyUlenniqj76MlnSPpsejx5ZJeylZRPbW+tS3jV18CxS6OUzIoLMGgcPc7JMnMnpd0djSVh8xsvqRfZb06AEDsUv3U08ckHUp6fCh6DgBQ5FL91NMSSS+Z2S+ix19RYlAbAFDkUp099p/M7NdKTAIoSTe4++rslQUAyBcpTyvo7q9IeiWLtQBA1vzhzvEZPV71vLVdbjNw4EDt3dvhNHlpmz9/vgYOHKjZs2dn5fjJuGc2ACCIoACAHLrwwgv1wYXBu3btUk1NjSRp8eLFuuKKKzR58mTV1dWdMEX4E088obPPPlsTJ07UpEmTjj//+uuvf2Rq8mxI/44WAICMaGlp0erVq1VeXq7Ro0frm9/8pioqKnTTTTfp+eefV21trd55553j23c0NXmfPn0yXhdBAQB5YtKkSRo0aJAkaezYsdq2bZveffddXXDBBaqtrZUkDRky5Pj2HU1NPnLkyIzXxaknAMihsrIyHTt2TJJ04MCBE9Z1NtV4Z7q7fU8RFACQQzU1NWpubpYkLVu2rMvtP/OZz+j555/Xm2++KUknnHrKFU49AegVUvk4a6a9//77J5wKmjVrlmbPnq2rrrpKCxcu1KWXXtrlMYYPH66FCxfqiiuu0LFjxzRixAg99dRT2Sz7I1KaZrxQDKiq9TOvuyPuMoCCUqyTAjLNeMd6Ms04p54AAEEEBQAgiKAAULSK6dR6JvT090FQAChKFRUVamtrIywi7q62tjZVVFR0e9+sfOrJzIZK+k30sErSUUk7JdVI2uHuY7PxcwHgAyNHjlRra6t27twZdyl5o6KiokcX5GUlKNy9TVK9dPxueHvd/W4zq5H0y54e18zK3D07V5QAKCp9+vQ5fjUz0hPHqadSM1tkZq+Z2ZNm1k+SzGyFmTVGy8PMbGu0PM3MHjOzZ/RhLwUAkCNxXHBXJ+lv3P0mM/u5pK9K+kkX+5wtaYK7f+SSRDObLmm6JJ02qI9+Ubkg0/UCRe0Pd3b8NxPHBWrIT3H0KN5095ZouVmJcYuuPNVRSEiSuy9090Z3bxwyoDRTNQIAInEExcGk5aP6sFdzRB/W035Yfl+2iwIAdCyfPh67VVJDtDwlxjoAAEnyKSjuljTDzFZLGhZ3MQCAhKKaFHDCaf38l9/4RNxlAEWBwezeg0kBAQBpISgAAEEEBQAgiKAAAARxK1SgSN29ZrB2Hej5/wXLpqZ/57uqqio1NTWlfRzEi6AAitSuAyV6a38af+Lbt2euGBQ0ggIoUsMqjikx4UHPlA05Pe0aqqqq0j4G4kdQAEVq9oT30tq/et5zGaoEhY7BbABAEEEBAAgiKAAAQQQFACCIoAAABBEUAIAgggIAEERQAACCiuqCu76njFP1vFVxlwEARYUeBQAgiKAAAAQRFACAIIICABBEUAAAgggKAEAQQQEACCIoAABBBAUAIIigAAAEFdUUHutb29QwZ0ncZQAFq3nB1LhLQB6iRwEACCIoAABBBAUAIIigAAAEERQAgCCCAgAQRFAAAIIICgBAEEEBAAgqqiuzgXw3YNOTKjm0L+4yOjV16tNxl5CyqqoqNTU1xV1Gr0BQADlUcmifSg/ujruMTm3fnr+1IT4EBZBDx/oOiLuEoOphlXGXkLKqqqq4S+g1CAogh/bVXRx3CUFLmBQQHWAwGwAQRFAAAIIICgBAEEEBAAjKi6Aws6Nm1pL0VdPBNo+b2eDcVwcAvVu+fOppv7vXd7TCzEySufsXc1wTAEB50qNoz8xqzGyjmS2RtE7Sx81sq5kNi7s2AOht8qVH0c/MWqLlNyXdJqlO0vXu/oIkJToWAIBcM3ePuwaZ2V53H5j0uEbSs+5em/TcVkmN7r6r3b7TJU2XpNMG9WlYOWt0LkoGkGeq562Nu4SCZWbN7t7Y2fq8PPUUSWnmNHdf6O6N7t44ZEBptmsCgF4nn4MCAJAHCAoAQFBeDGYnj09Ej7dKOqvdczU5LAkAEKFHAQAIIigAAEEEBQAgiKAAAAQRFACAoLz41BOA3Ll7zWDtOlB8/0csm1p8t3GtqqpSU1NT3GUQFEBvs+tAid7aX4R/+tu3x11B0SrCfy0AQoZVHJN0JO4yMq5syOlxl5BxVVVVcZcgiaAAep3ZE96Lu4SsqJ73XNwlFK3iO1EJAMgoggIAEERQAACCCAoAQBBBAQAIIigAAEEEBQAgqKiuo+h7yjhVz1sVdxkAUFToUQAAgggKAEAQQQEACCIoAABBBAUAIMjcPe4aMsbM9kjaGHcdWTBM0q64i8iSYm0b7SosxdouKbW2ne7uwztbWVQfj5W00d0b4y4i08xsVTG2SyrettGuwlKs7ZIy0zZOPQEAgggKAEBQsQXFwrgLyJJibZdUvG2jXYWlWNslZaBtRTWYDQDIvGLrUQAAMoygAAAEFUxQmNlkM9toZm+Y2e0drC83swej9S+aWU3Sun+Int9oZpfksu6u9LRdZlZjZvvNrCX6ui/XtYek0K4LzOwVMztiZlParbvezDZFX9fnruqupdmuo0mv12O5qzo1KbRtlpm9bmZrzOw3ZnZ60rpCfs1C7crb1yyFdt1sZmuj2n9rZmOT1nXvPdHd8/5LUqmkzZJGSeor6VVJY9ttM1PSfdHy1ZIejJbHRtuXS6qNjlMad5sy0K4aSevibkMa7aqRNEHSEklTkp4fImlL9P3kaPnkuNuUbruidXvjbkOabbtIUv9oeUbSv8VCf806bFc+v2YptuukpOUvSXoiWu72e2Kh9Cg+LekNd9/i7ock/UzSl9tt82VJP46Wl0maZGYWPf8zdz/o7m9KeiM6Xj5Ip135rMt2uftWd18j6Vi7fS+R9JS7v+Pu70p6StLkXBSdgnTale9Saduz7v5+9PAFSSOj5UJ/zTprVz5LpV27kx4OkPTBJ5e6/Z5YKEFxmqQ/Jj1ujZ7rcBt3PyLp/yQNTXHfuKTTLkmqNbPVZvacmZ2f7WK7IZ3feaG/XiEVZrbKzF4ws69ktrS0dbdtX5f06x7um0vptEvK39cspXaZ2S1mtllSk6RvdWffZMU2hUdv8idJ1e7eZmYNkh4xs3Ht/heB/HK6u283s1GSnjGzte6+Oe6iusvMrpXUKOnzcdeSSZ20q6BfM3f/kaQfmdk1kr4jqUfjR4XSo9gu6eNJj0dGz3W4jZmVSRokqS3FfePS43ZF3cY2SXL3ZiXOM34y6xWnJp3feaG/Xp1y9+3R9y2SVkj6VCaLS1NKbTOzL0iaK+lL7n6wO/vGJJ125fNr1t3f+c8kfdAj6v7rFfegTIoDN2VKDJDV6sOBm3HttrlFJw76/jxaHqcTB262KH8Gs9Np1/AP2qHEgNZ2SUPiblOq7UradrE+Opj9phKDoidHy8XQrpMllUfLwyRtUrvBx3xvmxJvkpsl1bV7vqBfs0C78vY1S7FddUnLl0taFS13+z0x9gZ34xfzRUm/j17QudFzdyrxPwBJqpD0kBIDMy9JGpW079xov42S/jrutmSiXZK+Kuk1SS2SXpF0edxt6Wa7zlHi3Og+JXp+ryXte2PU3jck3RB3WzLRLkmflbQ2+gNdK+nrcbelB217WtJb0b+5FkmPFclr1mG78v01S6Fd/5b0HvGskoKku++JTOEBAAgqlDEKAEBMCAoAQBBBAQAIIigAAEEEBQAgiKAAAAQRFEAKzGywmc2Mlk81s2U5+Jn1ZvbFbP8coCsEBZCawUpM+S533+HuU7rYPhPqlbioCogVQQGk5i5JZ0Q3gXnIzNZJkplNM7NHzWxFdNOe73V2gOhmUxvMbKmZrTezZWbWP1p3jpmtNLNXzewlMxukxFW2X4t+5tdy0kqgAwQFkJrbJW1293pJc9qt+7QSU6pMkHSlmTUGjjNa0r3uPkbSbkkzzayvpAcl/b27T5T0BSWmAJmnxE106t39wcw2B0gdQQGk7yl3b3P3/ZIelvQXgW3/6O6/i5Z/Em07WtKf3P1lKXHDGU/cewTICwQFkL72E6aFJlDrzrZAXiAogNTskVTZybq/MrMhZtZPiTn/f9fJdpJUbWbnRcvXSPqtEjN4nmJm50iSmVVG9x4J/UwgZwgKIAWeuEnU76JB7AXtVr8kabmkNZKWu/uqwKE2SrrFzNYrcb+Df/fEPY+/JukeM3tViXtOVygxNfRYBrMRN6YZB9JgZtMkNbr7rSlsWyPpl+5+VpbLAjKKHgUAIIgeBZBhZjZU0m86WDUpOoUFFBSCAgAQxKknAEAQQQEACCIoAABBBAUAIOj/AUn6I4qT38ZkAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f-xYMh6lZNn8"
      },
      "source": [
        "**Histograma e plotagens de densidade**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "H3MLb0svXpuV",
        "outputId": "c7a666bc-fb55-4807-bc08-d30db0331ab0"
      },
      "source": [
        "tips['tip_pct'].plot.hist(bins=50)\n",
        "\n"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e169ed0>"
            ]
          },
          "metadata": {},
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "XTayX02dYd-t",
        "outputId": "494a2548-3740-4153-c514-225989108a26"
      },
      "source": [
        "tips['tip_pct'].plot.density()"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95e605a90>"
            ]
          },
          "metadata": {},
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "id": "xAX0U2x3Z0ol",
        "outputId": "169598a2-0065-4db0-9f89-2e574df6c226"
      },
      "source": [
        "comp1 = np.random.normal(0, 1, size=200)\n",
        "comp2 = np.random.normal(10, 2, size=200)\n",
        "\n",
        "values = pd.Series(np.concatenate([comp1, comp2]))\n",
        "\n",
        "sns.distplot(values, bins=100, color='k')"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd95dfd49d0>"
            ]
          },
          "metadata": {},
          "execution_count": 52
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ILWjYsqhasjk"
      },
      "source": [
        "**Plotagem de dispersão ou de pontos**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qQvd0358aSCx"
      },
      "source": [
        "macro = pd.read_csv('/content/drive/MyDrive/dados_pandas/pydata-book-2nd-edition/examples/macrodata.csv')"
      ],
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b7eM4x-gWUJ7"
      },
      "source": [
        "data = macro[['cpi','m1','tbilrate','unemp']]"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HDaUrMmC49pT"
      },
      "source": [
        "trans_data = np.log(data).diff().dropna()"
      ],
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "r3c9VcJa5RVN",
        "outputId": "795df307-fb8d-4f26-8a93-9d0f480a4153"
      },
      "source": [
        "trans_data[-5:]"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cpi</th>\n",
              "      <th>m1</th>\n",
              "      <th>tbilrate</th>\n",
              "      <th>unemp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>-0.007904</td>\n",
              "      <td>0.045361</td>\n",
              "      <td>-0.396881</td>\n",
              "      <td>0.105361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>-0.021979</td>\n",
              "      <td>0.066753</td>\n",
              "      <td>-2.277267</td>\n",
              "      <td>0.139762</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>0.002340</td>\n",
              "      <td>0.010286</td>\n",
              "      <td>0.606136</td>\n",
              "      <td>0.160343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>0.008419</td>\n",
              "      <td>0.037461</td>\n",
              "      <td>-0.200671</td>\n",
              "      <td>0.127339</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>0.008894</td>\n",
              "      <td>0.012202</td>\n",
              "      <td>-0.405465</td>\n",
              "      <td>0.042560</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          cpi        m1  tbilrate     unemp\n",
              "198 -0.007904  0.045361 -0.396881  0.105361\n",
              "199 -0.021979  0.066753 -2.277267  0.139762\n",
              "200  0.002340  0.010286  0.606136  0.160343\n",
              "201  0.008419  0.037461 -0.200671  0.127339\n",
              "202  0.008894  0.012202 -0.405465  0.042560"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 366
        },
        "id": "vvu8aefT5UT8",
        "outputId": "faeca00d-4326-4e2b-ed94-f31903f5170a"
      },
      "source": [
        "#plotagem de dispersão com regressão linear\n",
        "sns.regplot('m1', 'unemp',data=trans_data)\n",
        "plt.title('Mudanças no log %s versus log %s' % ('m1','unemp'))"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Mudanças no log m1 versus log unemp')"
            ]
          },
          "metadata": {},
          "execution_count": 57
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 680
        },
        "id": "CU9SQknu6yap",
        "outputId": "2541498e-1ef8-47e4-d844-44c24522344c"
      },
      "source": [
        "#Plotagem de dispersão\n",
        "sns.pairplot(trans_data, diag_kind='kde', plot_kws={'alpha':0.2})"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fd95de62bd0>"
            ]
          },
          "metadata": {},
          "execution_count": 58
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 20 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ni4zCi7U7jD4"
      },
      "source": [
        "**Grades de faceta e dados de categoria**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "id": "6oxXSyik7PRe",
        "outputId": "ee8cfa91-d5dd-44ba-9673-7f966971b2af"
      },
      "source": [
        "#Porcentagem de gorjetas por dia/hora/fumante\n",
        "sns.factorplot(x='day', y='tip_pct', hue='time', col='smoker',\n",
        "               kind='bar', data=tips[tips.tip_pct < 1])"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:3714: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
            "  warnings.warn(msg)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fd95e32e810>"
            ]
          },
          "metadata": {},
          "execution_count": 59
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 789.625x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 733
        },
        "id": "NugxhC9R760l",
        "outputId": "7fb17131-8b8f-4010-b0b1-7edf55178e88"
      },
      "source": [
        "#tip_pct por dia; faceta por hora/fumante\n",
        "sns.factorplot(x='day', y='tip_pct', row='time',\n",
        "               col='smoker',\n",
        "               kind='bar', data=tips[tips.tip_pct < 1])"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:3714: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
            "  warnings.warn(msg)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fd95d733750>"
            ]
          },
          "metadata": {},
          "execution_count": 60
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 4 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 454
        },
        "id": "njMADikm-kzf",
        "outputId": "7bfdef80-0788-4deb-efe5-7394ac5e6541"
      },
      "source": [
        "#Plotagem que mostra mediana, quartis e valores discrepantes\n",
        "\n",
        "sns.factorplot(x='tip_pct', y='day', kind='box', data=tips[tips.tip_pct < 0.5])"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:3714: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
            "  warnings.warn(msg)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fd95d4762d0>"
            ]
          },
          "metadata": {},
          "execution_count": 61
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}