Análise_Aula_2.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Análise Aula 2.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyM3qn/IQnwyYQ5SKbbRuhBz",
      "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/MisterGusMan/Alura_ID3/blob/main/An%C3%A1lise_Aula_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "28TL-uUis-bH"
      },
      "source": [
        "Na aula 2, continuaremos a analisar o DataSet do experimento."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "kUhqfeEgtAwQ",
        "outputId": "1b6a60bd-26e1-48a4-c530-3606dd20fec5"
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "sns.set_style('darkgrid')\n",
        "%matplotlib inline\n",
        "plt.rcParams[\"figure.figsize\"] = (8, 6)\n",
        "\n",
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "\n",
        "df = pd.read_csv(url_dados, compression = 'zip')\n",
        "df.head()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
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              "      <th>c-77</th>\n",
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              "      <th>c-80</th>\n",
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              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
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              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
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              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
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              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gx4-fOm4tuVV",
        "outputId": "174658dc-f504-400d-e5b9-1e886d1b6040"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 23814 entries, 0 to 23813\n",
            "Columns: 877 entries, id to c-99\n",
            "dtypes: float64(872), int64(1), object(4)\n",
            "memory usage: 159.3+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "54U6j55cuepS",
        "outputId": "5ae97432-1721-4d8b-b0af-8f46b90ea83d"
      },
      "source": [
        "print(df['tratamento'].unique(), '\\t', df['dose'].unique(), '\\t', df['tempo'].unique())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['com_droga' 'com_controle'] \t ['D1' 'D2'] \t [24 72 48]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yw2NlC6TuXjg"
      },
      "source": [
        "Em experimentos biológicos, normalmente não utillizamos o nome ```droga```, sendo preferível usar ```composto```. Assim, vamos mudar o nome desta coluna no DataSet."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "JlhNUWUdvomM",
        "outputId": "75be4771-2ffe-4a2c-8e0c-5357e6743bad"
      },
      "source": [
        "df.rename(columns={'droga':'composto'}, inplace=True)\n",
        "df.head()"
      ],
      "execution_count": 3,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NmJ09hhtwTz2"
      },
      "source": [
        "Podemos agora trabalhar nos desafios propostos."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fyqumcfiwgjL"
      },
      "source": [
        "#Desafio 01: Ordenar o gráfico countplot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jI2-BY55wjzw",
        "outputId": "775e2b90-ab77-4947-f32e-49986e412f29"
      },
      "source": [
        "# 5 compostos mais presentes:\n",
        "comp = df['composto'].value_counts().index[:5]\n",
        "comp"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['cacb2b860', '87d714366', '9f80f3f77', '8b87a7a83', '5628cb3ee'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "Sp9cU-XMxBEI",
        "outputId": "80d3d695-e6fa-4e60-8aa4-2081012c761c"
      },
      "source": [
        "# Utilizando o método query para retonar os itens do DataSet com os compostos presentes em comp:\n",
        "sub = df.query('composto in @comp')\n",
        "sub"
      ],
      "execution_count": null,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>id_002fb9c19</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>8.7380</td>\n",
              "      <td>0.1914</td>\n",
              "      <td>2.4380</td>\n",
              "      <td>-0.2930</td>\n",
              "      <td>3.2010</td>\n",
              "      <td>1.4910</td>\n",
              "      <td>5.3920</td>\n",
              "      <td>-1.0420</td>\n",
              "      <td>-8.4860</td>\n",
              "      <td>-2.5790</td>\n",
              "      <td>-6.7470</td>\n",
              "      <td>3.6150</td>\n",
              "      <td>-1.4510</td>\n",
              "      <td>0.6909</td>\n",
              "      <td>-0.7623</td>\n",
              "      <td>-2.9400</td>\n",
              "      <td>-9.2850</td>\n",
              "      <td>-6.7110</td>\n",
              "      <td>-0.4195</td>\n",
              "      <td>1.1600</td>\n",
              "      <td>-1.3180</td>\n",
              "      <td>1.3660</td>\n",
              "      <td>-1.4020</td>\n",
              "      <td>-2.6220</td>\n",
              "      <td>0.7204</td>\n",
              "      <td>-2.5930</td>\n",
              "      <td>-4.0630</td>\n",
              "      <td>-0.8282</td>\n",
              "      <td>-3.5000</td>\n",
              "      <td>0.9206</td>\n",
              "      <td>-5.1450</td>\n",
              "      <td>9.8040</td>\n",
              "      <td>-2.6840</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>-0.1427</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-9.5910</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.8870</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-4.9020</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-5.5520</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.7960</td>\n",
              "      <td>-8.1770</td>\n",
              "      <td>-9.8990</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-6.7840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23793</th>\n",
              "      <td>id_ffd26f361</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.6008</td>\n",
              "      <td>0.2781</td>\n",
              "      <td>-0.3319</td>\n",
              "      <td>-0.8782</td>\n",
              "      <td>0.9281</td>\n",
              "      <td>0.7535</td>\n",
              "      <td>0.5971</td>\n",
              "      <td>1.6350</td>\n",
              "      <td>-0.3146</td>\n",
              "      <td>0.4984</td>\n",
              "      <td>-1.1890</td>\n",
              "      <td>0.3772</td>\n",
              "      <td>-0.8196</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-2.0350</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.7586</td>\n",
              "      <td>-0.4024</td>\n",
              "      <td>-0.0449</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.2358</td>\n",
              "      <td>0.7919</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>0.4232</td>\n",
              "      <td>1.8460</td>\n",
              "      <td>-2.0940</td>\n",
              "      <td>0.1438</td>\n",
              "      <td>-0.6604</td>\n",
              "      <td>0.7243</td>\n",
              "      <td>0.0338</td>\n",
              "      <td>-0.0182</td>\n",
              "      <td>-0.2022</td>\n",
              "      <td>0.8827</td>\n",
              "      <td>0.3147</td>\n",
              "      <td>-0.9263</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1934</td>\n",
              "      <td>1.2240</td>\n",
              "      <td>-0.1178</td>\n",
              "      <td>0.1459</td>\n",
              "      <td>-0.1242</td>\n",
              "      <td>0.3106</td>\n",
              "      <td>-0.7959</td>\n",
              "      <td>0.5681</td>\n",
              "      <td>0.3663</td>\n",
              "      <td>0.4874</td>\n",
              "      <td>-0.0548</td>\n",
              "      <td>0.1810</td>\n",
              "      <td>1.3470</td>\n",
              "      <td>1.6210</td>\n",
              "      <td>-0.8260</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>0.3264</td>\n",
              "      <td>0.9241</td>\n",
              "      <td>0.3012</td>\n",
              "      <td>1.2980</td>\n",
              "      <td>-0.2789</td>\n",
              "      <td>0.7019</td>\n",
              "      <td>-0.3528</td>\n",
              "      <td>0.7383</td>\n",
              "      <td>1.0300</td>\n",
              "      <td>0.6527</td>\n",
              "      <td>1.6750</td>\n",
              "      <td>-0.5046</td>\n",
              "      <td>0.2942</td>\n",
              "      <td>0.2950</td>\n",
              "      <td>1.2470</td>\n",
              "      <td>0.9569</td>\n",
              "      <td>-0.2065</td>\n",
              "      <td>-0.4918</td>\n",
              "      <td>0.7863</td>\n",
              "      <td>0.0504</td>\n",
              "      <td>0.8813</td>\n",
              "      <td>0.7757</td>\n",
              "      <td>-0.5272</td>\n",
              "      <td>0.7082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23802</th>\n",
              "      <td>id_fff3976bd</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>3.2890</td>\n",
              "      <td>2.1270</td>\n",
              "      <td>0.9770</td>\n",
              "      <td>2.0490</td>\n",
              "      <td>2.3170</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>-0.6357</td>\n",
              "      <td>-6.9060</td>\n",
              "      <td>-4.4830</td>\n",
              "      <td>-2.8400</td>\n",
              "      <td>-5.3310</td>\n",
              "      <td>0.6547</td>\n",
              "      <td>-2.2080</td>\n",
              "      <td>3.6030</td>\n",
              "      <td>0.6380</td>\n",
              "      <td>-2.1280</td>\n",
              "      <td>-3.1680</td>\n",
              "      <td>-4.2180</td>\n",
              "      <td>-0.3170</td>\n",
              "      <td>0.2140</td>\n",
              "      <td>-1.7660</td>\n",
              "      <td>-1.9700</td>\n",
              "      <td>-1.4820</td>\n",
              "      <td>-1.3710</td>\n",
              "      <td>-0.2628</td>\n",
              "      <td>-0.5276</td>\n",
              "      <td>-2.4160</td>\n",
              "      <td>-0.4638</td>\n",
              "      <td>-3.8630</td>\n",
              "      <td>-0.8880</td>\n",
              "      <td>-1.9850</td>\n",
              "      <td>2.0530</td>\n",
              "      <td>-1.4700</td>\n",
              "      <td>-3.3220</td>\n",
              "      <td>1.8800</td>\n",
              "      <td>...</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.0200</td>\n",
              "      <td>-6.7560</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.1240</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-5.7500</td>\n",
              "      <td>-8.4760</td>\n",
              "      <td>-6.9470</td>\n",
              "      <td>-4.7650</td>\n",
              "      <td>-9.7690</td>\n",
              "      <td>-5.7900</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-5.7450</td>\n",
              "      <td>-2.3570</td>\n",
              "      <td>-9.1190</td>\n",
              "      <td>-4.5980</td>\n",
              "      <td>-8.7760</td>\n",
              "      <td>-7.7980</td>\n",
              "      <td>-4.1620</td>\n",
              "      <td>-6.1510</td>\n",
              "      <td>-5.7400</td>\n",
              "      <td>-6.8700</td>\n",
              "      <td>-9.1000</td>\n",
              "      <td>-3.3360</td>\n",
              "      <td>-6.6420</td>\n",
              "      <td>-2.2750</td>\n",
              "      <td>-3.4720</td>\n",
              "      <td>-6.2670</td>\n",
              "      <td>-6.3980</td>\n",
              "      <td>-8.6300</td>\n",
              "      <td>-8.1490</td>\n",
              "      <td>-6.2900</td>\n",
              "      <td>-8.0970</td>\n",
              "      <td>-8.7330</td>\n",
              "      <td>-2.3780</td>\n",
              "      <td>-8.4480</td>\n",
              "      <td>-4.4550</td>\n",
              "      <td>-5.7930</td>\n",
              "      <td>-3.7000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23805</th>\n",
              "      <td>id_fff6df1c5</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>5628cb3ee</td>\n",
              "      <td>1.7380</td>\n",
              "      <td>-1.2900</td>\n",
              "      <td>-0.4533</td>\n",
              "      <td>-1.1640</td>\n",
              "      <td>-0.4841</td>\n",
              "      <td>-0.2392</td>\n",
              "      <td>-0.1774</td>\n",
              "      <td>-1.3980</td>\n",
              "      <td>-0.4059</td>\n",
              "      <td>0.1553</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-0.8020</td>\n",
              "      <td>-0.5039</td>\n",
              "      <td>-0.7167</td>\n",
              "      <td>-0.5016</td>\n",
              "      <td>-0.9369</td>\n",
              "      <td>-0.5864</td>\n",
              "      <td>-0.1009</td>\n",
              "      <td>0.8987</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>-1.3460</td>\n",
              "      <td>-0.5087</td>\n",
              "      <td>-0.0892</td>\n",
              "      <td>-0.6559</td>\n",
              "      <td>0.0864</td>\n",
              "      <td>-0.6251</td>\n",
              "      <td>0.2471</td>\n",
              "      <td>-0.4523</td>\n",
              "      <td>-0.0389</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.0796</td>\n",
              "      <td>-0.2560</td>\n",
              "      <td>-0.7851</td>\n",
              "      <td>-0.1687</td>\n",
              "      <td>-1.2890</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2866</td>\n",
              "      <td>0.3854</td>\n",
              "      <td>-0.4986</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.5843</td>\n",
              "      <td>0.0907</td>\n",
              "      <td>-0.9303</td>\n",
              "      <td>0.1981</td>\n",
              "      <td>0.6515</td>\n",
              "      <td>0.2877</td>\n",
              "      <td>0.4389</td>\n",
              "      <td>-0.3859</td>\n",
              "      <td>0.5203</td>\n",
              "      <td>-1.1070</td>\n",
              "      <td>2.3870</td>\n",
              "      <td>0.1820</td>\n",
              "      <td>-0.6434</td>\n",
              "      <td>-0.9722</td>\n",
              "      <td>-0.4200</td>\n",
              "      <td>-0.5693</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>1.1110</td>\n",
              "      <td>-0.5117</td>\n",
              "      <td>-1.2130</td>\n",
              "      <td>0.3769</td>\n",
              "      <td>0.5296</td>\n",
              "      <td>1.0400</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>1.0150</td>\n",
              "      <td>-0.7669</td>\n",
              "      <td>0.2865</td>\n",
              "      <td>0.5974</td>\n",
              "      <td>-0.2727</td>\n",
              "      <td>0.1188</td>\n",
              "      <td>1.0770</td>\n",
              "      <td>-1.0250</td>\n",
              "      <td>0.1516</td>\n",
              "      <td>0.4503</td>\n",
              "      <td>-0.6312</td>\n",
              "      <td>-0.8302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3235 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "16     id_002fb9c19     com_droga     48   D1  ... -9.9840 -9.9840 -9.9840 -6.7840\n",
              "25     id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38     id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40     id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23793  id_ffd26f361  com_controle     48   D2  ...  0.8813  0.7757 -0.5272  0.7082\n",
              "23802  id_fff3976bd     com_droga     24   D1  ... -8.4480 -4.4550 -5.7930 -3.7000\n",
              "23805  id_fff6df1c5     com_droga     48   D2  ...  0.1516  0.4503 -0.6312 -0.8302\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "\n",
              "[3235 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "id": "w3NjKYKZ1sil",
        "outputId": "1a24ba49-6e09-4759-c5b1-9e1c1bf19c06"
      },
      "source": [
        "# Gerando o countplot deste subset:\n",
        "sns.countplot(x = 'composto', data = sub).set(title = 'Os 5 compostos mais utilizados', ylabel = 'Quantidade')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0.5, 'Quantidade'), Text(0.5, 1.0, 'Os 5 compostos mais utilizados')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "id": "A8RpO0NW47Aj",
        "outputId": "a9eb3efa-0423-4e03-afbb-eeb0fd5f4c32"
      },
      "source": [
        "# Para ordenar este gráfico, temos que passar os valores do subset na plotagem com o parâmetro order:\n",
        "sns.countplot(x = 'composto', \n",
        "              data = sub, \n",
        "              order = sub['composto'].value_counts().index\n",
        "              ).set(title = 'Os 5 compostos mais utilizados', ylabel = 'Quantidade')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0.5, 'Quantidade'), Text(0.5, 1.0, 'Os 5 compostos mais utilizados')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d18sLVWW7NjA"
      },
      "source": [
        "#Desafio 02: Melhorar a visualização alterando tamanho da fonte"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 443
        },
        "id": "kwopTR6V7iN9",
        "outputId": "ac3fd949-909a-4ed9-d7aa-054a82414631"
      },
      "source": [
        "# Para alterar o tamanho da fonte em um gráfico seaborn, podemos manualmente definir o tamanho da fonte em cada elemento:\n",
        "p = sns.countplot(x = 'composto', \n",
        "              data = sub, \n",
        "              order = sub['composto'].value_counts().index\n",
        "              )\n",
        "p.set_title('Os 5 compostos mais utilizados', fontsize = 30)\n",
        "p.set_ylabel('Quantidade', fontsize = 20)\n",
        "p.set_xlabel('Composto', fontsize = 20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Composto')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9QQzTq1r_Zpd"
      },
      "source": [
        "#Desafio 03: Plotar os histogramas com seaborn"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kd0wZCOk_gEJ"
      },
      "source": [
        "Histogramas no seaborn são definidos pela função sns.histplot(). Podemos plotar qualquer variável, incluindo estatísticas de uma coluna, como o máximo, mínimo, média, entre outras:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "id": "BpnNsSTkBZ4T",
        "outputId": "6005e387-8ec3-4a2b-ed5b-396c18e2b5dc"
      },
      "source": [
        "# Valores das colunas g-0 até g-771:\n",
        "desc = df.loc[:,'g-0':'g-771']\n",
        "desc.describe()"
      ],
      "execution_count": 6,
      "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>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>g-39</th>\n",
              "      <th>...</th>\n",
              "      <th>g-732</th>\n",
              "      <th>g-733</th>\n",
              "      <th>g-734</th>\n",
              "      <th>g-735</th>\n",
              "      <th>g-736</th>\n",
              "      <th>g-737</th>\n",
              "      <th>g-738</th>\n",
              "      <th>g-739</th>\n",
              "      <th>g-740</th>\n",
              "      <th>g-741</th>\n",
              "      <th>g-742</th>\n",
              "      <th>g-743</th>\n",
              "      <th>g-744</th>\n",
              "      <th>g-745</th>\n",
              "      <th>g-746</th>\n",
              "      <th>g-747</th>\n",
              "      <th>g-748</th>\n",
              "      <th>g-749</th>\n",
              "      <th>g-750</th>\n",
              "      <th>g-751</th>\n",
              "      <th>g-752</th>\n",
              "      <th>g-753</th>\n",
              "      <th>g-754</th>\n",
              "      <th>g-755</th>\n",
              "      <th>g-756</th>\n",
              "      <th>g-757</th>\n",
              "      <th>g-758</th>\n",
              "      <th>g-759</th>\n",
              "      <th>g-760</th>\n",
              "      <th>g-761</th>\n",
              "      <th>g-762</th>\n",
              "      <th>g-763</th>\n",
              "      <th>g-764</th>\n",
              "      <th>g-765</th>\n",
              "      <th>g-766</th>\n",
              "      <th>g-767</th>\n",
              "      <th>g-768</th>\n",
              "      <th>g-769</th>\n",
              "      <th>g-770</th>\n",
              "      <th>g-771</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>0.132026</td>\n",
              "      <td>...</td>\n",
              "      <td>0.263569</td>\n",
              "      <td>-0.242638</td>\n",
              "      <td>0.110180</td>\n",
              "      <td>-0.039868</td>\n",
              "      <td>-0.064056</td>\n",
              "      <td>0.193629</td>\n",
              "      <td>0.004470</td>\n",
              "      <td>-0.187085</td>\n",
              "      <td>0.067186</td>\n",
              "      <td>0.006159</td>\n",
              "      <td>-0.201189</td>\n",
              "      <td>-0.243317</td>\n",
              "      <td>0.548903</td>\n",
              "      <td>0.247065</td>\n",
              "      <td>0.085950</td>\n",
              "      <td>0.090544</td>\n",
              "      <td>0.215525</td>\n",
              "      <td>-0.007705</td>\n",
              "      <td>0.236954</td>\n",
              "      <td>0.022785</td>\n",
              "      <td>0.103224</td>\n",
              "      <td>0.048402</td>\n",
              "      <td>0.109367</td>\n",
              "      <td>-0.103262</td>\n",
              "      <td>0.004129</td>\n",
              "      <td>0.066211</td>\n",
              "      <td>0.072773</td>\n",
              "      <td>-0.033051</td>\n",
              "      <td>-0.400643</td>\n",
              "      <td>-0.338978</td>\n",
              "      <td>0.207299</td>\n",
              "      <td>0.009161</td>\n",
              "      <td>0.171027</td>\n",
              "      <td>0.002316</td>\n",
              "      <td>-0.209799</td>\n",
              "      <td>-0.076251</td>\n",
              "      <td>0.134162</td>\n",
              "      <td>-0.128018</td>\n",
              "      <td>-0.219210</td>\n",
              "      <td>0.101524</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>0.990477</td>\n",
              "      <td>...</td>\n",
              "      <td>1.075809</td>\n",
              "      <td>1.309482</td>\n",
              "      <td>0.881283</td>\n",
              "      <td>0.917119</td>\n",
              "      <td>1.186966</td>\n",
              "      <td>1.212621</td>\n",
              "      <td>1.175611</td>\n",
              "      <td>1.182180</td>\n",
              "      <td>1.057292</td>\n",
              "      <td>0.996940</td>\n",
              "      <td>1.029370</td>\n",
              "      <td>1.378815</td>\n",
              "      <td>2.023791</td>\n",
              "      <td>1.639307</td>\n",
              "      <td>1.238753</td>\n",
              "      <td>0.961212</td>\n",
              "      <td>1.293783</td>\n",
              "      <td>0.966213</td>\n",
              "      <td>1.284074</td>\n",
              "      <td>1.015557</td>\n",
              "      <td>1.035968</td>\n",
              "      <td>1.048645</td>\n",
              "      <td>0.856080</td>\n",
              "      <td>1.175372</td>\n",
              "      <td>0.701031</td>\n",
              "      <td>0.996914</td>\n",
              "      <td>1.077310</td>\n",
              "      <td>1.579948</td>\n",
              "      <td>1.913468</td>\n",
              "      <td>1.701554</td>\n",
              "      <td>1.096488</td>\n",
              "      <td>1.200395</td>\n",
              "      <td>1.357701</td>\n",
              "      <td>1.052771</td>\n",
              "      <td>1.201918</td>\n",
              "      <td>1.115477</td>\n",
              "      <td>0.951264</td>\n",
              "      <td>1.230636</td>\n",
              "      <td>1.326193</td>\n",
              "      <td>1.417674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.223000</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.504000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-3.790000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.920000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.462000</td>\n",
              "      <td>-6.634000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.912000</td>\n",
              "      <td>-9.833000</td>\n",
              "      <td>-7.227000</td>\n",
              "      <td>-5.561000</td>\n",
              "      <td>-8.393000</td>\n",
              "      <td>-5.790000</td>\n",
              "      <td>-4.915000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.918000</td>\n",
              "      <td>-5.255000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.264000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.505000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.193000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.795000</td>\n",
              "      <td>-8.180000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.269000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>-0.401700</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.390700</td>\n",
              "      <td>-0.565075</td>\n",
              "      <td>-0.433275</td>\n",
              "      <td>-0.498650</td>\n",
              "      <td>-0.526300</td>\n",
              "      <td>-0.430750</td>\n",
              "      <td>-0.488775</td>\n",
              "      <td>-0.593125</td>\n",
              "      <td>-0.498275</td>\n",
              "      <td>-0.489800</td>\n",
              "      <td>-0.564100</td>\n",
              "      <td>-0.538000</td>\n",
              "      <td>-0.464000</td>\n",
              "      <td>-0.521975</td>\n",
              "      <td>-0.488600</td>\n",
              "      <td>-0.442925</td>\n",
              "      <td>-0.457200</td>\n",
              "      <td>-0.477900</td>\n",
              "      <td>-0.458175</td>\n",
              "      <td>-0.479075</td>\n",
              "      <td>-0.478825</td>\n",
              "      <td>-0.489300</td>\n",
              "      <td>-0.327500</td>\n",
              "      <td>-0.576775</td>\n",
              "      <td>-0.278275</td>\n",
              "      <td>-0.492700</td>\n",
              "      <td>-0.501575</td>\n",
              "      <td>-0.526450</td>\n",
              "      <td>-0.507375</td>\n",
              "      <td>-0.559175</td>\n",
              "      <td>-0.433875</td>\n",
              "      <td>-0.502250</td>\n",
              "      <td>-0.537075</td>\n",
              "      <td>-0.508775</td>\n",
              "      <td>-0.606175</td>\n",
              "      <td>-0.506200</td>\n",
              "      <td>-0.353100</td>\n",
              "      <td>-0.544600</td>\n",
              "      <td>-0.554400</td>\n",
              "      <td>-0.523800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>0.007400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.065650</td>\n",
              "      <td>-0.014100</td>\n",
              "      <td>0.030850</td>\n",
              "      <td>-0.001800</td>\n",
              "      <td>-0.008400</td>\n",
              "      <td>0.101400</td>\n",
              "      <td>0.033400</td>\n",
              "      <td>-0.001600</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>0.014800</td>\n",
              "      <td>-0.044000</td>\n",
              "      <td>0.017400</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>-0.015550</td>\n",
              "      <td>0.025350</td>\n",
              "      <td>0.017750</td>\n",
              "      <td>0.053450</td>\n",
              "      <td>0.027700</td>\n",
              "      <td>-0.002100</td>\n",
              "      <td>0.009500</td>\n",
              "      <td>-0.004450</td>\n",
              "      <td>-0.000050</td>\n",
              "      <td>0.002400</td>\n",
              "      <td>0.024250</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>0.013600</td>\n",
              "      <td>0.001350</td>\n",
              "      <td>0.007350</td>\n",
              "      <td>0.038700</td>\n",
              "      <td>0.059600</td>\n",
              "      <td>-0.005900</td>\n",
              "      <td>-0.013600</td>\n",
              "      <td>-0.027700</td>\n",
              "      <td>-0.011850</td>\n",
              "      <td>0.009900</td>\n",
              "      <td>0.005400</td>\n",
              "      <td>0.000600</td>\n",
              "      <td>0.028700</td>\n",
              "      <td>-0.006500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>0.439400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.646900</td>\n",
              "      <td>0.467900</td>\n",
              "      <td>0.543400</td>\n",
              "      <td>0.477200</td>\n",
              "      <td>0.497400</td>\n",
              "      <td>0.846400</td>\n",
              "      <td>0.573875</td>\n",
              "      <td>0.501675</td>\n",
              "      <td>0.519825</td>\n",
              "      <td>0.515000</td>\n",
              "      <td>0.412375</td>\n",
              "      <td>0.479400</td>\n",
              "      <td>0.646325</td>\n",
              "      <td>0.565200</td>\n",
              "      <td>0.610075</td>\n",
              "      <td>0.506975</td>\n",
              "      <td>0.671725</td>\n",
              "      <td>0.514175</td>\n",
              "      <td>0.524175</td>\n",
              "      <td>0.501325</td>\n",
              "      <td>0.516975</td>\n",
              "      <td>0.517475</td>\n",
              "      <td>0.375275</td>\n",
              "      <td>0.572250</td>\n",
              "      <td>0.251600</td>\n",
              "      <td>0.540950</td>\n",
              "      <td>0.530900</td>\n",
              "      <td>0.527900</td>\n",
              "      <td>0.475275</td>\n",
              "      <td>0.522075</td>\n",
              "      <td>0.648500</td>\n",
              "      <td>0.492150</td>\n",
              "      <td>0.522500</td>\n",
              "      <td>0.457000</td>\n",
              "      <td>0.483000</td>\n",
              "      <td>0.511175</td>\n",
              "      <td>0.409075</td>\n",
              "      <td>0.498500</td>\n",
              "      <td>0.496400</td>\n",
              "      <td>0.536950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.889000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.635000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.664000</td>\n",
              "      <td>9.566000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.497000</td>\n",
              "      <td>6.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.323000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.533000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.008000</td>\n",
              "      <td>5.900000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.552000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.346000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>6.317000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                g-0           g-1  ...         g-770         g-771\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean       0.248366     -0.095684  ...     -0.219210      0.101524\n",
              "std        1.393399      0.812363  ...      1.326193      1.417674\n",
              "min       -5.513000     -5.737000  ...    -10.000000    -10.000000\n",
              "25%       -0.473075     -0.562200  ...     -0.554400     -0.523800\n",
              "50%       -0.008850     -0.046600  ...      0.028700     -0.006500\n",
              "75%        0.525700      0.403075  ...      0.496400      0.536950\n",
              "max       10.000000      5.039000  ...     10.000000     10.000000\n",
              "\n",
              "[8 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lRhKEwhMVsmY",
        "outputId": "3290c265-ea50-40e7-a7da-08f2a5319f2d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        }
      },
      "source": [
        "fig, ax = plt.subplots(3, constrained_layout = True, figsize = (12,8))\n",
        "\n",
        "sns.histplot(desc.max(), bins = 50, ax = ax[0], color = 'tab:red')\n",
        "ax[0].set(ylabel = 'Quantidade', title = 'Contagem dos maiores valores de g-0 a g-771')\n",
        "\n",
        "sns.histplot(desc.min(), bins = 50, ax = ax[1], color = 'tab:blue')\n",
        "ax[1].set(ylabel = 'Quantidade', title = 'Contagem dos menores valores de g-0 a g-771')\n",
        "\n",
        "sns.histplot(desc.mean(), bins = 100, ax = ax[2], color = 'tab:green')\n",
        "ax[2].set(ylabel = 'Quantidade', title = 'Contagem dos valores médios de g-0 a g-771')\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0.5, 'Quantidade'),\n",
              " Text(0.5, 1.0, 'Contagem dos valores médios de g-0 a g-771')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QsQ4nrZPmbiL"
      },
      "source": [
        "Como era esperado, a distribuição de valores máximos é maior em 10, os mínimos são maiores em -10, e a distribuição de valores médios é uma distribuição normal, com a maior concentração no valor central 0."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "qH4YhAPDw6VC",
        "outputId": "6b95a116-a76f-4d9f-ef85-5b0a27bac63c"
      },
      "source": [
        "fig, ax = plt.subplots(2,1, constrained_layout = True)\n",
        "\n",
        "hist1 = sns.histplot(data = df, x = 'g-0', bins = 100,ax=ax[0], color = \"red\")\n",
        "ax[0].set(ylabel = \"Quantidade\",xlabel ='', title = \"Distribuição dos valores de g-0\")\n",
        "\n",
        "hist2 = sns.histplot(data = df, x = 'g-771', bins = 100, ax=ax [1],color = \"orange\")\n",
        "ax[1].set(ylabel= \"Quantidade\", xlabel = '', title = \"Distribuição dos valores de g-771\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7TkRsN1voY2t"
      },
      "source": [
        "#Desafio 04: Estudar sobre as estatíticas retornadas no .describe()"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "IRG1WMSqoinM",
        "outputId": "2dd9f6d1-93b5-423d-e36c-f0ad28c0c04b"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": null,
      "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>tempo</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>48.020156</td>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.517397</td>\n",
              "      <td>-0.360770</td>\n",
              "      <td>-0.435752</td>\n",
              "      <td>-0.613591</td>\n",
              "      <td>-0.402083</td>\n",
              "      <td>-0.619682</td>\n",
              "      <td>-0.452265</td>\n",
              "      <td>-0.497164</td>\n",
              "      <td>-0.413836</td>\n",
              "      <td>-0.277029</td>\n",
              "      <td>-0.547845</td>\n",
              "      <td>-0.358611</td>\n",
              "      <td>-0.442906</td>\n",
              "      <td>-0.475194</td>\n",
              "      <td>-0.010404</td>\n",
              "      <td>-0.467001</td>\n",
              "      <td>-0.276963</td>\n",
              "      <td>-0.455848</td>\n",
              "      <td>-0.412918</td>\n",
              "      <td>-0.456404</td>\n",
              "      <td>-0.472514</td>\n",
              "      <td>-0.505481</td>\n",
              "      <td>-0.492735</td>\n",
              "      <td>-0.446836</td>\n",
              "      <td>-0.463029</td>\n",
              "      <td>-0.409310</td>\n",
              "      <td>-0.333124</td>\n",
              "      <td>-0.295009</td>\n",
              "      <td>-0.328342</td>\n",
              "      <td>-0.401615</td>\n",
              "      <td>-0.469244</td>\n",
              "      <td>-0.461411</td>\n",
              "      <td>-0.513256</td>\n",
              "      <td>-0.500142</td>\n",
              "      <td>-0.507093</td>\n",
              "      <td>-0.353726</td>\n",
              "      <td>-0.463485</td>\n",
              "      <td>-0.378241</td>\n",
              "      <td>-0.470252</td>\n",
              "      <td>-0.301505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>19.402807</td>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>...</td>\n",
              "      <td>2.122318</td>\n",
              "      <td>1.710725</td>\n",
              "      <td>1.898871</td>\n",
              "      <td>2.307820</td>\n",
              "      <td>1.785055</td>\n",
              "      <td>2.225596</td>\n",
              "      <td>1.991021</td>\n",
              "      <td>2.063896</td>\n",
              "      <td>1.887001</td>\n",
              "      <td>1.459639</td>\n",
              "      <td>2.187835</td>\n",
              "      <td>1.730634</td>\n",
              "      <td>1.924716</td>\n",
              "      <td>2.021927</td>\n",
              "      <td>1.029820</td>\n",
              "      <td>2.004317</td>\n",
              "      <td>1.429340</td>\n",
              "      <td>1.924263</td>\n",
              "      <td>1.888788</td>\n",
              "      <td>1.832863</td>\n",
              "      <td>2.011396</td>\n",
              "      <td>2.091353</td>\n",
              "      <td>2.055624</td>\n",
              "      <td>1.987476</td>\n",
              "      <td>2.014045</td>\n",
              "      <td>1.883974</td>\n",
              "      <td>1.647241</td>\n",
              "      <td>1.634073</td>\n",
              "      <td>1.663170</td>\n",
              "      <td>1.832794</td>\n",
              "      <td>2.000488</td>\n",
              "      <td>2.042475</td>\n",
              "      <td>2.001714</td>\n",
              "      <td>2.107105</td>\n",
              "      <td>2.159589</td>\n",
              "      <td>1.629291</td>\n",
              "      <td>2.059725</td>\n",
              "      <td>1.703615</td>\n",
              "      <td>1.834828</td>\n",
              "      <td>1.407918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.839000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.452000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.938000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.588075</td>\n",
              "      <td>-0.564025</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.583250</td>\n",
              "      <td>-0.566500</td>\n",
              "      <td>-0.603200</td>\n",
              "      <td>-0.541575</td>\n",
              "      <td>-0.560825</td>\n",
              "      <td>-0.555200</td>\n",
              "      <td>-0.534500</td>\n",
              "      <td>-0.569100</td>\n",
              "      <td>-0.558300</td>\n",
              "      <td>-0.573350</td>\n",
              "      <td>-0.594275</td>\n",
              "      <td>-0.389925</td>\n",
              "      <td>-0.551200</td>\n",
              "      <td>-0.544150</td>\n",
              "      <td>-0.575075</td>\n",
              "      <td>-0.568275</td>\n",
              "      <td>-0.582650</td>\n",
              "      <td>-0.558575</td>\n",
              "      <td>-0.562375</td>\n",
              "      <td>-0.572800</td>\n",
              "      <td>-0.561225</td>\n",
              "      <td>-0.560675</td>\n",
              "      <td>-0.560100</td>\n",
              "      <td>-0.533700</td>\n",
              "      <td>-0.504575</td>\n",
              "      <td>-0.544275</td>\n",
              "      <td>-0.569150</td>\n",
              "      <td>-0.566175</td>\n",
              "      <td>-0.565975</td>\n",
              "      <td>-0.589975</td>\n",
              "      <td>-0.568700</td>\n",
              "      <td>-0.563775</td>\n",
              "      <td>-0.567975</td>\n",
              "      <td>-0.552575</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.592600</td>\n",
              "      <td>-0.562900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.017650</td>\n",
              "      <td>-0.041550</td>\n",
              "      <td>-0.002950</td>\n",
              "      <td>-0.012650</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.004950</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.023800</td>\n",
              "      <td>-0.011450</td>\n",
              "      <td>-0.007100</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.009300</td>\n",
              "      <td>0.081550</td>\n",
              "      <td>-0.006900</td>\n",
              "      <td>0.018400</td>\n",
              "      <td>-0.014650</td>\n",
              "      <td>-0.014350</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>-0.005300</td>\n",
              "      <td>-0.004050</td>\n",
              "      <td>0.003300</td>\n",
              "      <td>-0.007900</td>\n",
              "      <td>-0.004600</td>\n",
              "      <td>-0.002400</td>\n",
              "      <td>0.007850</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>-0.020600</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>-0.009900</td>\n",
              "      <td>0.003250</td>\n",
              "      <td>-0.009100</td>\n",
              "      <td>-0.013750</td>\n",
              "      <td>-0.003300</td>\n",
              "      <td>-0.010250</td>\n",
              "      <td>-0.001250</td>\n",
              "      <td>-0.006800</td>\n",
              "      <td>0.014000</td>\n",
              "      <td>-0.019500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>...</td>\n",
              "      <td>0.452675</td>\n",
              "      <td>0.427675</td>\n",
              "      <td>0.462175</td>\n",
              "      <td>0.447975</td>\n",
              "      <td>0.447150</td>\n",
              "      <td>0.441250</td>\n",
              "      <td>0.470600</td>\n",
              "      <td>0.458550</td>\n",
              "      <td>0.441000</td>\n",
              "      <td>0.460075</td>\n",
              "      <td>0.460950</td>\n",
              "      <td>0.449975</td>\n",
              "      <td>0.445200</td>\n",
              "      <td>0.473200</td>\n",
              "      <td>0.563575</td>\n",
              "      <td>0.456350</td>\n",
              "      <td>0.493400</td>\n",
              "      <td>0.448375</td>\n",
              "      <td>0.451975</td>\n",
              "      <td>0.463075</td>\n",
              "      <td>0.447675</td>\n",
              "      <td>0.462000</td>\n",
              "      <td>0.468900</td>\n",
              "      <td>0.452375</td>\n",
              "      <td>0.460475</td>\n",
              "      <td>0.461675</td>\n",
              "      <td>0.465950</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.450075</td>\n",
              "      <td>0.430875</td>\n",
              "      <td>0.457750</td>\n",
              "      <td>0.461500</td>\n",
              "      <td>0.445675</td>\n",
              "      <td>0.452900</td>\n",
              "      <td>0.470900</td>\n",
              "      <td>0.444750</td>\n",
              "      <td>0.465225</td>\n",
              "      <td>0.446400</td>\n",
              "      <td>0.461275</td>\n",
              "      <td>0.438650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>3.888000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>4.857000</td>\n",
              "      <td>3.549000</td>\n",
              "      <td>3.382000</td>\n",
              "      <td>3.328000</td>\n",
              "      <td>4.157000</td>\n",
              "      <td>3.736000</td>\n",
              "      <td>3.582000</td>\n",
              "      <td>3.119000</td>\n",
              "      <td>3.323000</td>\n",
              "      <td>5.014000</td>\n",
              "      <td>2.898000</td>\n",
              "      <td>4.185000</td>\n",
              "      <td>3.170000</td>\n",
              "      <td>3.276000</td>\n",
              "      <td>4.992000</td>\n",
              "      <td>3.770000</td>\n",
              "      <td>2.851000</td>\n",
              "      <td>3.211000</td>\n",
              "      <td>4.534000</td>\n",
              "      <td>3.890000</td>\n",
              "      <td>3.994000</td>\n",
              "      <td>4.321000</td>\n",
              "      <td>4.020000</td>\n",
              "      <td>3.738000</td>\n",
              "      <td>3.252000</td>\n",
              "      <td>5.406000</td>\n",
              "      <td>3.110000</td>\n",
              "      <td>3.320000</td>\n",
              "      <td>4.069000</td>\n",
              "      <td>3.960000</td>\n",
              "      <td>3.927000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>3.747000</td>\n",
              "      <td>2.814000</td>\n",
              "      <td>3.505000</td>\n",
              "      <td>2.924000</td>\n",
              "      <td>3.111000</td>\n",
              "      <td>3.805000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 873 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              tempo           g-0  ...          c-98          c-99\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean      48.020156      0.248366  ...     -0.470252     -0.301505\n",
              "std       19.402807      1.393399  ...      1.834828      1.407918\n",
              "min       24.000000     -5.513000  ...    -10.000000    -10.000000\n",
              "25%       24.000000     -0.473075  ...     -0.592600     -0.562900\n",
              "50%       48.000000     -0.008850  ...      0.014000     -0.019500\n",
              "75%       72.000000      0.525700  ...      0.461275      0.438650\n",
              "max       72.000000     10.000000  ...      3.111000      3.805000\n",
              "\n",
              "[8 rows x 873 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8s3zbe22omcD"
      },
      "source": [
        "As estatísticas das colunas retornadas pelo método .describe() são:\n",
        "\n",
        "*   count: Contagem de itens da coluna;\n",
        "*   mean: Valor médio dos itens da coluna (soma / quantidade)\n",
        "*   std: Desvio Padrão (Standard Deviation) dos itens da coluna;\n",
        "*   min | max: Menor e maior valor da coluna\n",
        "*   25% | 50% | 75%: Valores do primeiro, segundo e terceiro quartil.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eafuDpp5q8oG"
      },
      "source": [
        "#Desafio 05: Refletir sobre a manipulação do tamanho das visualizações. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3HM0d3tWsIEU"
      },
      "source": [
        "O tamanho das visualizações é de extrema importância para uma boa intepretação dos dados, pois pequenas nuâncias podem se perder com uma plotagem de tamanho reduzido ou muito grande. É importante analisar os dados antes de realizar a visualização para definir as dimensões."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "dEPRcedftFFE",
        "outputId": "adc348bb-d018-46fb-93f1-33a274c27468"
      },
      "source": [
        "# Gráfico com apenas 5 barras e tamanho (4,4):\n",
        "fig, ax = plt.subplots(2,1, constrained_layout = True, figsize=(4,4))\n",
        "\n",
        "hist1 = sns.histplot(data = df, x = 'c-0', bins = 10,ax=ax[0], color = \"purple\")\n",
        "ax[0].set(ylabel = \"Quantidade\",xlabel ='', title = \"Distribuição dos valores de c-0\")\n",
        "\n",
        "hist2 = sns.histplot(data = df, x = 'c-99', bins = 10, ax=ax [1],color = \"pink\")\n",
        "ax[1].set(ylabel= \"Quantidade\", xlabel = '', title = \"Distribuição dos valores de c-99\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 288x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "Tv8rlIDBtXpj",
        "outputId": "ff25c8f5-f73d-49fc-b53e-477c2e7fa220"
      },
      "source": [
        "# Mesmo gráfico, agora em tamanho (8,6) com 100 barras:\n",
        "fig, ax = plt.subplots(2,1, constrained_layout = True, figsize=(8,6))\n",
        "\n",
        "hist1 = sns.histplot(data = df, x = 'c-0', bins = 100,ax=ax[0], color = \"purple\")\n",
        "ax[0].set(ylabel = \"Quantidade\",xlabel ='', title = \"Distribuição dos valores de c-0\")\n",
        "\n",
        "hist2 = sns.histplot(data = df, x = 'c-99', bins = 100, ax=ax [1],color = \"pink\")\n",
        "ax[1].set(ylabel= \"Quantidade\", xlabel = '', title = \"Distribuição dos valores de c-99\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dKkSxKhst2mj"
      },
      "source": [
        "#Desafio 06: Fazer outras análises com o boxplot e até com o histograma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u1EfGR7kt67F",
        "outputId": "96bb5c73-1847-4dff-c95a-8947e114d19b"
      },
      "source": [
        "df['tempo'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([24, 72, 48])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H0LvAXhiuIt9",
        "outputId": "a0104f12-07b9-43f6-e781-3ce946f1b232"
      },
      "source": [
        "df['dose'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['D1', 'D2'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 508
        },
        "id": "dgunyAd1uMEk",
        "outputId": "695dee2f-6762-49ce-8d41-e39e43c2835d"
      },
      "source": [
        "fig, ax = plt.subplots(2, constrained_layout = True)\n",
        "\n",
        "c1 = sns.countplot(data = sub, x = 'composto',ax=ax[0], palette = 'rainbow', hue = 'tempo', order = sub['composto'].value_counts().index)\n",
        "ax[0].set(ylabel = \"Quantidade\",xlabel ='', title = \"Compostos mais utilizados pelo tempo\")\n",
        "\n",
        "c2 = sns.countplot(data = sub, x = 'composto',ax=ax[1], palette = 'coolwarm', hue = 'dose', order = sub['composto'].value_counts().index)\n",
        "ax[1].set(ylabel = \"Quantidade\",xlabel ='', title = \"Compostos mais utilizados pela dose\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0.5, 'Quantidade'),\n",
              " Text(0.5, 0, ''),\n",
              " Text(0.5, 1.0, 'Compostos mais utilizados pela dose')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lbT89Lqs2QCoqSlBS0i6vyhQXF7H+3e/WagfWxNShA+qtrIaS77EXEZGmbdasBEVFTXteVyKRf8wAhQ2QWgJbASe7++tmNprQnbaCuyfNbLUHQVVVJcl3DFJpaYfVLUaq0VjHf4mISN1KJpNUVS1v6GqskWTyhzFDrtigkOHgdGC6u78en08kBEyzzKw7QPz/bVw/A+idtn2vuExERESkXhUsQHL3b4BpZmZx0SDg38CjwIi4bATwSHz8KHCEmSXMbCAwv67GH4mIiIjURqFnsZ0M/D3OYPsSOJIQlN1vZkcDU4EhMe0kwhT/zwnT/I8scN1ERESkiZg16xv+9KeL4w0nE+y3368YMuSwFevvuecubrrpOh5//FlKSkrWuLyCBkju/h7Z7y8wKEvaJHBiIesjIiIia66uZ4YvrqhiUQ3jWouKWnLSSb/HbFMWL17EUUcNZ9ttt6dv3w2YNesb3nzzNbp1W7fO6qQ7aYuIiEittKvjmeFThw5gUQ1punbtSteu4a7Z7dq1p0+fPsyZ8y19+27ADTdcw29/ewrnnnt6ndWpac/ZExERkR+dmTO/5rPPnH79tuDll1+ga9d12HjjTeq0DAVIIiIi0mQsXryY888/i1NPPZ2iopZMmHAHxxxzfJ2XowBJREREmoTKykouuOAs9txzL3bZZXdmzJjOzJlfM3LkYRx00L7Mnv0tRx11OHPnzlnjsjQGSURERBq9ZDLJZZf9gfXX78uhhw4DYMMNN+Lxx59Zkeagg/blttvubPyz2ERERETqwgcfvM9TT01iww03YuTIoQAcd9wJ7LDDjgUpTwGSiIiI1Mriiqo6/c3RxRVVNabp339LXnnlrZxpJk58rK6qpABJREREamdR+eIap+U3dRqkLSIiIpJBAZKIiIhIBgVIIiIiIhkUIImIiIhkUIAkIiIikkGz2ERERKTJqKqq4phjhlNaug5XXHEdb731BmPGjGb58iRt27bl/PNH0atX7zUuRwGSiIiI1MrandvSqqjuQohlVZXMn7ckr7QPPHAP66/fl8WLw40Grrrqci6//Gr69OnLQw89wPjxYzn//FFrXCcFSCIiIlIrrYpaMrp8cp3ld2rJXnml+/bbWbz66hSOOOIo7rvv7wAkErBoUQiWFi1aSNeupXVSJwVIIiIi0iRcf/3V/Pa3p6xoPQI455wLOfPMU2ndujXt27fn1lvvqJOyChogmdlXwAKgCqh0923MrDNwH9AH+AoY4u5lZpYARgN7A4uBke7+TiHrJyIiIk3DlCkvU1LSmU033Yx33ln5kyP33Xc3V145ms0334K7757ADTdcyznnXLjG5dVHC9Ju7j4n7fk5wHPufrmZnROfnw0MBjaOf9sDN8f/IiIi8iP34YfvM2XKS7z22hSWLVvGokULOfPMU5k69Ss233wLAHbffU/OOOPkOimvIab57w+Mj4/HAwekLZ/g7kl3fw0oMbPuDVA/ERERaWSOP/4kHn54EhMnPsaoUX9m66235bLLrmbRooX8739TAXjrrddYf/0+dVJeoVuQksDTZpYEbnX3vwLd3H1mXP8N0C0+7glMS9t2elw2k2oUFSUoKWlX97WWvOjYi4j8OMyalaCoqLBtKrXJP5W2detWnHPOhVxwwdm0aJGgQ4eOnH/+xVnzSiRqFzMUOkDa0d1nmNk6wDNm9mn6SndPxuBptVRVJSkvX5xX2tLSDqtbjFQj32MvIiJNWzKZpKpq+Yrny6oq8555lo9lVZWr5F+T/v23on//raiqWs5OO+3KTjvtusr6bHklkz+MGXLFBgUNkNx9Rvz/rZk9DGwHzDKz7u4+M3ahfRuTzwDS7+zUKy4TERGRRiTfexY1ZQVrLzOz9mbWIfUY2BP4CHgUGBGTjQAeiY8fBY4ws4SZDQTmp3XFiYiIiNSbQrYgdQMeNrNUOXe7+2QzexO438yOBqYCQ2L6SYQp/p8TpvkfWcC6iYiIiFSrYAGSu38J9M+yfC4wKMvyJHBioeojIiIikq+GmOYvIiIi0qgpQBIRERHJoN9iExERkUbvf//7iosuOm/F86+/nsExxxzH7NmzmTLlJYqLi+nRoxfnnXcxHTqs+a19FCCJiIhIrXQuaU1Rcas6y6+qYhnzypfmTLPeen0YN+7ukL6qil/9am923nk3/ve/qRx33Im0bNmSMWOu58477+CEE05Z4zopQBIREZFaKSpuxZzHzqyz/LrueyWQO0BK9/bbb9KzZ0/WXbc766678lfJNt/8J7zwwnN1UieNQRIREZEm5dlnn+LnP//FD5Y/8cSjDBz4szopQwGSiIiINBkVFRVMmfISu+3281WWjx8/lqKiIvbcc3CdlKMuNhEREWkyXnttCptssimdO3dZsWzSpMf4179eYfTom0kkEnVSjgIkERERaTIyu9dee+1f3H33BG644a+0adOmzsrJK0Ays27ApUAPdx9sZv2AHdx9bJ3VRERERCSHJUuW8Oabb3DmmeevWHbttVdQUVHB738ffoxj88234Mwzz6sui7zl24I0DrgDSNXoM+A+QAGSiIjIj0xVxbI486zu8stH27ZtmTRp1Vlq9933jzqrR7p8A6Su7n6/mZ0L4O6VZlZVkBqJiIhIoxbuWZT/tPymKN9ZbIvMrAuQBDCzgcD8gtVKREREpAHl24J0GvAosKGZTQFKgYMKVisRERGRBpRXgOTu75jZLoABibDIKwpaMxEREWk0kslknU2hr2/JZLLW2+QMkMzswGpWbWJmuPtDtS5RREREmpSWLVuxaNF3tG/fsckFSclkkkWLvqNly9r9dlxNLUj7xv/rAD8Dno/PdwP+BdQYIJlZEfAWMMPd9zGzvsC9QBfgbWC4uy8zs9bABGBrYC5wiLt/Vau9ERERkTrXqVMpZWWzWbiwvKGrslpatmxFp06ltdsm10p3PxLAzJ4G+rn7zPi8O2Hqfz5OBT4BOsbnfwGudfd7zewW4Gjg5vi/zN03MrNDY7pDarU3IiIiUueKilrStWv3mhM2I/nOYuudCo6iWcB6NW1kZr2AXwK3xecJYHdgYkwyHjggPt4/PieuHxTTi4iIiNSrfGexPWdmTwH3xOeHAM/msd11wFlAh/i8C1Du7pXx+XSgZ3zcE5gGK+6zND+mn5NnHUVERETqRL6z2E6KA7Z3iov+6u4P59rGzPYBvnX3t81s1zWrZnZFRQlKStoVImvJg469iIg0V3n/WG2csVabWWv/B+xnZnsDbQhjkEYDJWbWMrYi9QJmxPQzgN7AdDNrCaxNGKxdraqqJOXli/OqTGlph5oTSa3ke+xFREQao1yxQb4/VjsQuAHYDGgFFAGL3L1jddu4+7nAuXH7XYEz3P1wM3uAcJPJe4ERwCNxk0fj81fj+ufdvfY3LhARERFZQ/kO0r4ROAz4D9AWOAa4aTXLPBs4zcw+J4wxSv3g7VigS1x+GnDOauYvIiIiskZq08X2uZkVuXsVcIeZvUtsIcpj2xeAF+LjL4HtsqT5Hjg43/qIiIiIFEq+AdJiM2sFvGdmVwAzyb/1SURERKRJyTfIGU4Yd3QSsIgwmPrXhaqUiIiISEPKd5r/1PhwCXBJ4aojIiIi0vBq+rHaD4FqZ5K5+0/rvEYiIiIiDaymFqR94v8T4/874/9h5AicRERERJqymn6sdiqAme3h7gPSVp1tZu+gqfgiIiLSDOU7SDthZv+XemJmP6vFtiIiIiJNSr7T/I8GbjeztYEEUAYcVbBaiYiIiDSgfGexvQ30jwES7j6/oLUSERERaUA1zWIb5u53mdlpGcsBcPdrClg3ERERkQZRUwtS+/g/28/dahabiIiINEs1zWK7NT581t2npK9LH7QtIiIi0pzkOxPthjyXiYiIiDR5NY1B2gH4GVCaMQ6pI+G32URERESanZrGILUC1orp0schfQccVKhKiYiIiDSkmsYgvQi8aGbj0n6wVkRERKRZy/dGka3N7K9An/Rt3H33QlRKREREpCHlGyA9ANwC3AZU5bOBmbUBXgJax3ImuvvFZtYXuBfoArwNDHf3ZWbWGpgAbA3MBQ5x969qsS8iIiIidSLfAKnS3W+uZd5Lgd3dfaGZFQOvmNmTwGnAte5+r5ndQvgZk5vj/zJ338jMDgX+AhxSyzJFRERE1li+AdJjZnYC8DAh8AHA3edVt4G7J4GF8Wlx/EsCuwND4/LxwChCgLR/fAwwEbjRzBIxHxEREZF6k2+ANCL+PzNtWRLYINdGZlZE6EbbCLgJ+AIod/fKmGQ60DM+7glMA3D3SjObT+iGm5NnHUVERETqRL4/Vtt3dTJ39ypgSzMrIbQ+bbo6+VSnqChBSUm7usxSakHHXkREmqt8W5Awsy2AfkCb1DJ3n5DPtu5ebmb/BHYASsysZWxF6gXMiMlmAL2B6WbWElibMFi7WlVVScrLF+dV/9LSbD8nJ2si32MvIiLSGOWKDfL6qREzu5jw0yI3ALsBVwD71bBNaWw5wszaAnsAnwD/ZOVNJkcAj8THj7KyK+8g4HmNPxIREZGGkO9vsR0EDAK+cfcjgf6EFp5cugP/NLMPgDeBZ9z9ceBs4DQz+5wwxmhsTD8W6BKXnwacU6s9EREREakj+XaxLXH35WZWaWYdgW8J3WHVcvcPgAFZln8JbJdl+ffAwXnWR0RERKRg8g2Q3ordZX8jzEpbCLxasFqJiIiINKB8Z7GdEB/eYmaTgY6xhUhERESk2ckrQDKznbMtc/eX6r5KIiIiIg0r3y629BtEtiGMIXqbcFdsERERkWYl3y62fdOfm1lv4LqC1EhERESkgeU7zT/TdGCzuqyIiIiISGOR7xikGwi/vQYhqBoAvFOoSomIiIg0pHzHIH0KFMXHc4F73H1KYaokIiIi0rByBkhmVgxcCRwBfBUXdyP85MgUM9vS3d8raA1FCmjtzm1pVZT3TxKusWVVlcyft6TeyhMRkdVT05XhaqAdsL67LwCId9K+ysxuBvYC+ha2iiKF06qoJaPLJ9dbeaeW7FVvZYmIyOqrKUDaG9g4/Udj3f07M/stMAcYXMjKiYiIiDSEmgKk5enBUYq7V5nZbHd/rUD1kh+p9iXtaFdcVHPCJipZVUFpaYd6LbOqYhnzypfWa5kiIk1dTQHSv83sCHefkL7QzIYBnxSuWvJj1a64iPXvfrfeyps69Ae/p1xQiaJi5jx2Zs0J61DXfa8EFCCJiNRGTQHSicBDZnYU4c7ZANsAbYFfFbJiIiIiIg0lZ4Dk7jOA7c1sd2DzuHiSuz9X8JqJiIiINJB8f2rkeeD5AtdFREREpFFY3Z8aEREREWm2CnaHvPiDthMIN5ZMAn9199Fm1hm4D+hDuPnkEHcvM7MEMJpwa4HFwEh318+ZiIiISL0rZAtSJXC6u/cDBgInmlk/4BzgOXffGHguPodwT6WN499vgJsLWDcRERGRahUsQHL3makWoHgX7k+AnsD+wPiYbDxwQHy8PzDB3ZPx/kolZta9UPUTERERqU69/AiVmfUBBgCvA93cfWZc9Q2hCw5C8DQtbbPpcdlMqlFUlKCkpF2d11fyo2PfdOhciYjUTsEDJDNbC3gQ+F38mZIV69w9aWY/uFN3vqqqkpSXL84rbX3fvfjHIN9jXxs6T4VRiHMlItLU5brmFHQWm5kVE4Kjv7v7Q3HxrFTXWfz/bVw+A+idtnmvuExERESkXhUsQIqz0sYCn7j7NWmrHgVGxMcjgEfSlh9hZgkzGwjMT+uKExEREak3hexi+z9gOPChmb0Xl50HXA7cb2ZHA1OBIXHdJMIU/88J0/yPLGDdRERERKpVsADJ3V8BEtWsHpQlfZLw228iIiIiDUp30hYRERHJoABJREREJIMCJBEREZEMCpBEREREMihAEhEREcmgAElEREQkgwIkERERkQwKkEREREQyKEASERERyaAASURERCSDAiQRERGRDAqQRERERDIoQBIRERHJoABJREREJIMCJBEREZEMCpBEREREMrQsVMZmdjuwD/Ctu28Rl3UG7gP6AF8BQ9y9zMwSwGhgb2AxMNLd3ylU3URERERyKWQL0jhgr4xl5wDPufvGwHPxOcBgYOP49xvg5gLWS0RERCSngnCsvBkAACAASURBVAVI7v4SMC9j8f7A+Ph4PHBA2vIJ7p5099eAEjPrXqi6iYiIiORS32OQurn7zPj4G6BbfNwTmJaWbnpcJiIiIlLvCjYGqSbunjSz5JrkUVSUoKSkXV1VSWpJx77p0LkSEamd+g6QZplZd3efGbvQvo3LZwC909L1istyqqpKUl6+OK+CS0s71LauUoN8j31t6DwVRiHOlYhIU5frmlPfXWyPAiPi4xHAI2nLjzCzhJkNBOandcWJiIiI1KtCTvO/B9gV6Gpm04GLgcuB+83saGAqMCQmn0SY4v85YZr/kYWql4iIiEhNChYgufth1awalCVtEjixUHURkaZt7c5taVVUfyMCllVVMn/eknorT0QanwYbpC0iTVf7kna0Ky6q1zJHl0+ut7JO6TCo3sfDVVUsY1750notU0SqpwBJRGqtXXER69/9br2VN3XogHorCyBRVMycx86s1zK77nsloABJpLFQgCQiIvIjoi7r/ChAEhGROlHfF97lVRW0KCqut/KgeXSFtipqqS7rPChAEhFpppr7WLFTS/ZSV2gT0FS7rBUgiYg0U819rFhz0RCBrNRMAZKIiEgDUiDbONX3nbRFREREGj0FSCIiIiIZFCCJiIiIZFCAJCIiIpJBAZKIiIhIBgVIIiIiIhkUIImIiIhkUIAkIiIikkEBkoiIiEgGBUgiIiIiGRrVT42Y2V7AaKAIuM3dL2/gKomIiMiPUKNpQTKzIuAmYDDQDzjMzPo1bK1ERETkx6jRBEjAdsDn7v6luy8D7gX2b+A6iYiIyI9QYwqQegLT0p5Pj8tERERE6lUimUw2dB0AMLODgL3c/Zj4fDiwvbuflGOz2cDU+qifiIiINDvrA6XZVjSmQdozgN5pz3vFZblk3SkRERGRNdGYAqQ3gY3NrC8hMDoUGNqwVRIREZEfo0YzBsndK4GTgKeAT4D73f3jhq2ViIiI/Bg1mjFIIiIiIo1Fo2lBEhEREWksFCCJiIiIZGhMg7SbNTNb6O5rZVl+JbAvsAz4AjjS3cvNbCSwTbbbHJjZ74FjgCTwYdzmezNLAH8CDgaqgJvd/fq4fDSwN7AYGOnu7xRiPxtStuMCPAN0iEnWAd5w9wOybPsVsA3QBbgvbdUGwEXufp2ZHQyMAjYDtnP3tzLyWA/4NzDK3a8yszbAS0BrwnttortfHNNmPVdx3a7AdUAxMMfdd1ntg9IEmNmpwLFAAvhbPNabEm4WmwQOAvYj+2u+b0zXBXgbGO7uy8ysFHgcaAWcApwPdCech5eBE929KqOcQ6n+3N8HWFxeApS7+5aFOSKNRzXvqU8Jn01zMtKuB4wnHJ8i4Bx3n2RmhwNnpiX9KbCVu7+Xo9yXyeN9m5a+GLgN2Ipwjie4+2W53oPNSfz8WkD4LKl0923i8pOBE+PyJ9z9LDPbA7ic8N5YBpzp7s/H9IcB5xHO99fAsMzznFbmrsAZ7r5PlnWTyfJ+q6v9rS9qQWp4zwBbuPtPgc+Ac3MlNrOehA/8bdx9C8IH0aFx9UjCrRI2dffNCB/8EH6+ZeP49xvg5jrehwZX3XFx953cfct4MXsVeChXPh6k0m9NCCgfjqs/Ag4kfOBmcw3wZNrzpcDu7t4f2BLYy8wGxnUjyXKuzKwEGAPs5+6bEwKoZsvMtiAER9sB/YF9zGwj4ADCxWwA8D3Vv+b/Alzr7hsBZcDRcfkg4EN3H+DuLwND4nnYgnB7kNRxXVFOrnPv7oekrXuQGl5HzUENnzXZXECYXDMgphsD4O5/Tzt2w4H/5gqO4ja1et8Szmdrd/8J4dwdZ2Z9yP0ebG52i8csFRztRvg1iv7xs+SqmG4OsG88ViOAO2P6loQv0rvF69EHhIlTq6O691uTohakPJnZEcAZhMj6A+B+wgdCK2AucLi7zzKztYAbCK0RSeASd38w5nEtsCfwDeHiPdvdn04r5jXCt+WU3mb2AuGO4ne5+yVxeUugrZlVAO0IkT7Ab4Gh7r4cwN2/jcv3J3yjSgKvmVmJmXV395l1cWwakeqOC2bWEdid8A0YM+sC3EM4tq8SWi8yDQK+cPepAO7+Sdz2BwnN7ADgv8Ci1LJ4vBfGp8XxLzUrorpzNRR4yN3/l7G8udoMeN3dFwOY2YuEY3ACUGVmg4BhZDm3sRVud1beDmQ8MMrMXgWuiOm3AXZw9+9impaE92zSzPYGfpcqx913S6vXKuc+JZY5JJb7Y1Dde+osMxsMLCG8jj8nvLY7xvVrp6VNdxgrv7hhZjcD2wJtydK6k+V9ux3hIt4mln2ku3ssu328yLcltIx8V8N7sLn7LXC5uy+FlZ8l7v5uWpqPCee3NbCc8DnY3szmEs7l5wDxS8sthGCnipUBT0czewLYCPgncIK7L8/2fov5bEj4zdVSwheQY93909jiewuwXtzud+4+pS4PxupQC1IezGxzQjCU+iZyKvAKMDB+W7oXOCsmvxCY7+4/iVH483F5e+CtGMm/CGRr5j2KVVsgtgN+TWiSPtjMtnH3GYRvAv8DZsayUkHWhsAhZvaWmT1pZhvH5c3+Z1xqOC4QWgqeS3vjXgy8Es/Hw6x8Y6Y7lBBE5RSD4rOBS7KsKzKz94BvgWfc/fW4qrpztQnQycxeMLO3Y2DenH0E7GRmXcysHaEbOPVhea2775bj3HYhdHVVxrymAz1j68RFwH3xG/USADN7inAeFhAuxpPSy8moV3Xnfidglrv/p64OQGNVw3tqfmyBuJHQHQyh+3mYmU0HJgEnZ8n2EFY9rufHFo+fAruY2U8z0me+bz8FdoqfuxcBl8blEwlfTmbG+l7l7vMg53uwOUkCT8fPjN/EZZsQ3luvm9mLZrZtlu1+Dbzj7kvdvYIQVH1ICG77AWNjur8DN8Xr388IxxnCNerkmHZDQgs78MP3W1z8V+Bkd9+a0OAwJi4fTXgfbhvrdNvqH4q6owApP7sDD6T6YuMbrxfwlJl9SOhf3zym/TkhQiamLYsPl7NyfMNdwI7pBZjZ+UAl4YWY8oy7z40f8A8BO5pZJ0KLUF+gByHaHxbTtwa+jx84fwNuX9MdbypqOC4QvrmmfzDvTDgPuPsThO6Z9PxaEca9PJBH8aMIb+6FmSvcvSp2E/QCtotdSlD9uWpJ6CL4JfAL4EIz2ySPOjRJsVXuL8DTwGTgPcI31BXyOLf5lvULwriI1uRoAarh3Ge+jpqtGo77PWn/d4iPDwPGuXsvQqB7p5m1SMtve2Cxu3+UVswQM3sHeJfwGdovoxqZx3tt4AEz+wi4lpWfu9sRXjc9Yn1PN7MNIOd7sDnZ0d23IgynONHMdiZ8lnQGBhKuUffHFlBgxRf/vwDHxefFhABpAOE4fgCca2YdCF88Ut3N36dafAljw770ML7oHtKua5nvt/hF8meE8/cecGtcD+G6eWNc/iihZeoHY3brmwKk1XcDcGP8FnUcocm3NlY081oYkL0PoZsumS1N2vOfE/rwZ8eI/yHCiw7CN+hUX/3DhG9lsHo/49LUVHtczKwr4QP0iVrkN5jwzWpWHmm3B66IAyV/B5xnZqv03bt7OaEJeq+4qLpzNR14yt0XxYD8JcLYnGbL3ce6+9buvjMhUP0sI0l153YuUBK7VSCP17W7fw88QrjwVyfruY/lHMiqA7mbs1yfNdk+p44mDD3A3V8lfCZ2TUu3SqtcHGB/BjAotrY/QdrnaDXv2z8C//QwJmrftPRDgcnuXhG7kqYQhjmskOU92GzE1r5UN9rDhOM2ndBdn3T3Nwhf0rsCmFmvmO4Id/8iZrNlzOOLeB26n5XnuzrZrlHp9Up/v7UgTm5I+9ssJm1B6JFJLe+Z7QtnfVOAlJ/nCV1cXQDMrDPhm0zqw3hEWtpnCLMGiGk7xYctWDm+aCihiw4z24vQPbdfWlSesoeZdTaztoSm5imE5uOBZtYufhsYRLjzOMA/gFRXwS6svNA8ChxhZok4QHF+Mxx/lOu4HAQ8Ht+sKS8Rx67EsRSdWFXeLQUeBpT2cfc+hO6GS939RjMrjYOuiedwD0IXAVR/rh4htBS2jF1O26ftR7NkZuvE/+sRApC7M5JkPbfxQ/yfrHxfjSAcv8z81zKz7vFxS0Lr3KeZ6dJUd+5/Dnzq7tPz3bcmLtd76pC0/6+mpR8EYGabEYKX2fF5C8LYrRXjjwhjXBYB882sGyEwTZftfZv+uTsyo667x7LaE1pNPq3hPdgsmFn72MqT2vc9CV3XKz5jYit0K2BOPB5PEGYZpo/zmQH0i+OBIByrT9x9ATA9jrPEzFrHzyYILXJ94/k9BHiluvdb7Cb9r4XZwMTrUerL39OkdcmaWaOYIaoAKQ8efvLkz8CLZvY+YbbSKEJT4duEWQEpfyKMIfkopk1dBBcRXkwfEd7If4jLbyRMZ33GzN4zs1vS8nqDMGPmA+BBd38r9p9PBN4h9BW3IPTrQpi6+evY7XcZYXouhPEAXxIG3P2NMAC2WanhuGQbT3IJsLOZfUy4KP8vtSJ+yOxBxswZM/tVHF+xA/BE7GPPpTvwTzP7gPBbg8+4++NxXdZzFbucJhPO+RvAbRldEs3Rg2b2b+AxwnTg8vSVNZzbs4HTzOxzwpiksfxQe+DReB5SY1FuyZKu2nMf5TUmrbmo4bh3isfzVOD3cdnpwLHxc+8ewu1EUi0KOwPT3P3LtPzfJ3StfUoIijMH5WY73lcAl5nZu6w6yegmYK34fn4TuMPdPyD3e7C56EYITN4nfGY84e6TCd32G8Rrzr3AiHg+TiIMqr4oXnPeM7N13P1rwufiS/F4bcnKMV7DgVPi8n8B68blbxKuYZ8QJqk8TO732+HA0bGuH7OyJfcUYBsz+yB+Fhxfx8doteinRkREREQyqAVJREREJIMCJBEREZEMCpBEREREMihAEhEREcmgAElEREQkgwIkERERkQwKkEREREQyKEASERERyaAASURERCSDAiQRERGRDAqQRERERDIoQBKRRsHMnjSzEfVZjpmNNLNX0tYtNLMN6ri8cWb2p7rMc02Y2QtmdkzNKes3L5HGpmXNSUTEzIYCpwGbAgsIv1L9Z3d/JeeGjYCZ7Qrc5e69Grouubj74LrO08xGARu5+7B8ynH3teq6DiLSNKkFSaQGZnYacB1wKdANWA8YA+zfkPUSEZHCUQuSSA5mtjbwB+BId38obdVj8Q8zaw38BRgS190PnO3uS1OtN8D1wBlAFfBbYBkh6OoKXOXul8a8RgFbxHR7A/+JZb8f128G3AxsCcwAznX3R+O6vYGrgN7Ad8C1Me2TQGszWxjrtwkwN0eduwLjgB2B5cDHwC7uvjzL8UkCJwK/B9aN+zQOuDPux2RgmLsvM7NOcfn2hM+eKcDx7j495vUCoaXrNjPbCBgb97MCeM7dD8lS/q5ktI6Z2VfAMbGM84CEmR0AfOHu/dPLqWZ/NgYWA5+lrWoBtHX3hJltCPwN6A8kgaeAE929POYxINZ9Y2BSTJNexrHA2UBn4JV4DL42swRwDXA40AaYChzm7h9lqecLwKvAIEKr5j8Jr5N5cf3AmFe/mM+p7v5Clnxy7kuW9HsANwDdCecykbauBeF4Hwu0JZz7k919vpm1AW4DBgNFhNf1Pu4+K77HriG83pcDdwAXu3tVtjqI1Be1IInktgPhYvVwjjTnAwMJF/P+wHbABWnr14159AQuIlyQhgFbAzsBF5pZ37T0+wMPEC6gdwP/MLNiMysmBGVPA+sAJwN/NzOL240FjnP3DoTg5Hl3X0S4KH3t7mvFv69rqPPpwHSglNBidh4ZF/kMv4j7MhA4C/hr3L/esR6HxXQtCBe/9QmtcEuAG6vJ849xPzsBvQgX5Vpx98mEVr/74n73r8W26cdrLcL5vzeuTgCXAT2AzQj7OQrAzFoB/yAED50J5/HXqXzNbPe47RBCkDE1Ld89gZ0JAezaMc3cHNU8Ajgq5lNJCMIxs57AE8CfYh3OAB40s9IseVS7L5li4PwQ4XXSFfgC+L+0JCPj327ABsBarDy/I+I+9Qa6AMcTzj+EgLoS2AgYEI+DxjVJg1MLkkhuXYA57l6ZI83hhG/K3wKY2SXArcCFcX0FYbxSlZndSwggRrv7AuBjM/s3IUj5b0z/trtPjHldQwhYBsZ1awGXx9ac583scUIAMiqW08/M3nf3MqBsNetcQbjoru/unwMv13CMrnD37+K+fAQ87e5fxnyfJFz0xrv7XODB1EZm9mdCy0c2FYRAqkdsYWqwsV5mdjahlWZHgHhMPo+rZ8dzdHF8PhAoBq5z9yQwMXbRphwO3O7u78S8zwXKzKwPYZ87xLLecPdPaqjananWJTO7EHgvDj4fBkxy90kx3TNm9hahhWZ8egY17EumvYGP016b1xFem+n7dk3auT8X+MjMjoz71oUwHuwD4O2YplvMt8TdlwCLzOxa4DeE16NIg1GAJJLbXKCrmbXMEST1ILQEpEyNy1bkkdZdkPrWPCtt/RJC4JMyLfXA3Zeb2fS0/KZldHVNJbRMQWipuAC43Mw+AM5x91dXo85XEgKup2Pj1F/d/fJq8sm2L5nP1wUws3aEbr+9CC1DAB3MrChLd8pZhFakN8ysDLja3W/PUYeCMLPBwKnA9vECnrqojya0/nUgtIylgtEewIwYHKWkH+cewDupJ+6+0MzmAj3d/XkzuxG4CVjfzB4CzojBZzbT0h5PJQRmXQmB5cFmtm/a+mKyBKM17EumHqz62kya2bSM9ZmvqZaEVsg7Ca1H95pZCaHb+fxY12Jg5sqGUFpk7JtIg1AXm0hurwJLgQNypPma8EGfsl5ctrp6px7EcR29Yn5fA73jsvSyZgC4+5vuvj+h++0fhHFFkL17rNo6u/sCdz/d3TcA9gNOM7NBa7A/KacDRgg2OhK6kyBtHEuKu3/j7se6ew/gOGBMHJeUaRHQLvXEzIoIXYMpuboGc4pdl+OBIe6efsG+NOb7k7gfw9L2YSbQM44nSlkv7fEqx93M2hNaVlLn8Hp335owdmgT4MwcVeyd9ng9QivNHEJwcae7l6T9ta8myM21L5lmsuprM5FRh2yvqUpglrtXuPsl7t4P+BmwD6GLcBrh/dU1ra4d3X3zHPstUi/UgiSSQxxgehFwk5lVEsbFVAA/B3Zz97OAe4ALzOxNwsXmIsI35NW1tZkdCDwKnEK4gLxGuHAtBs4ys6sJ4z/2BbaNY18OBh6Pdf6OMOAVQotOFzNb293nx2XV1tnM9gE+JYwxmU8YMP6DAdqroQOhRanczDpTfVcOZnYw8GrsXiuLdcxWh8+ANmb2S8K5OQ9onbZ+FrCHmbXINsg8R/kdgUeA87PcyqED4bjMj+N90oOYVwlBwSlmNoZwfrZjZevNPcA9ZnY38AkhQHnd3b8ys20JX1rfIQR+31ezzynDzGwC8BVhIsHE2I17F/Cmmf0CeJbQQjMQ+Dw1ID7Pfcn0BHBj2mvzRGLrYNq+nR27VWezcvxXpZntRgje/k2YQFABLHf3mWb2NHB17CZcCPQFern7iznqIlJwakESqYG7X024B9IFhA/+acBJhFYaCINh3wI+AD4kXODW5MaAjwCHEAKD4cCB8Rv4MsIFdzDhYjMGOMLdP43bDQe+isHR8YQxIcT19wBfmlm5mfWooc4bEy6sCwkX/DHuXt1Yodq4jjC7aQ4h4JucI+22wOtx5t2jhFlYX2YmigHfCYQZUjMIgUV6EPBA/D/XzN4hf1sRWruutXDzyIVpswAvievnE4KGFbMb4zk6kDBYeR7hPKavf5YwzutBQovMhsChcXVHwgD+MkL31FxCd2d17iQMcP6GMAnglFjGNMJA//NY+Xo9k+yf99XuSyZ3n0MIwi+PdduYMBMx5fZYp5cI4+m+J0wkgBBITSQER58AL8a0EFqSWhGCp7KYrnuO/RapF4lkcrVboEWkjlmWGxuKZMp1qwIRqRtqQRIRERHJoABJREREJIO62EREREQyqAVJREREJIMCJBEREZEMTfo+SMuXL09WVamLUERERGqvuLhoDqveXHaFJh0gVVUlKS9f3NDVEBERkSaotLTD1OrWqYtNREREJIMCJBEREZEMCpBEREREMjTpMUgiIiJSWFVVlZSVzaaycllDV2W1tWzZik6dSikqyj/sUYAkIiIi1Sorm02bNu1o335dEolEQ1en1pLJJIsWfUdZ2Wy6ds3/d5DVxSYiIiLVqqxcRvv2HZtkcASQSCRo375jrVvAfjQtSCWd2lPcsvHHgxWVyykvW9TQ1RAREVmhqQZHKatT/x9NgFTcsgWT3lzY0NWo0d7brtXQVRAREalzY8feStu27Rg6dHhDVyUvjb9JRURERKSe/WhakERERKR+jR8/lieffIJOnTqxzjrdMNuM//zHufLKy1i69Ht69OjFuedeRMeOHXnggXt55JEHKSoqok+fvlxyyWUsWbKEa6+9gv/+9wsqKys56qjfsNNOu9ZL3RUgiYiISJ379NNPeO65pxk37m6qqio56qhhmG3Gn/50Mb/73ZkMGLA1t912C3fc8TdOPfV07rprHA888CitWrViwYIFAEyYcDtbb70t5513MQsWLODYY0ewzTbb07Zt24LXX11sIiIiUuc++OBddt55N9q0aUP79mux44478/33S1iwYAEDBmwNwODB+/D+++8AsOGGG/OHP1zAU09NoqioCIA33niNu+4ax8iRQzn55ONYtmwps2Z9Uy/1VwuSiIiINLgrr7yO999/lylTXmLChNsZP/5ekskkf/7zFay3Xp96r48CpEYmWVVFaWmHhq5GjaoqKplXvqShqyEiIo1U//5bcemloxg+fCRVVVVMmfIy++13IB06dOT999+lf/8BTJ78BFtuuRXLly/n229nsdVW2/DTn27Js88+zZIlS9h++x2YOPE+fv/7s0gkEnz22adsssmm9VJ/BUiNTKKoiLnP3dvQ1ahRl0GHNnQVRESkETPblN1334MRI4bSqVMnNt20HwAXXDAqbZB2T84992KWL1/OH/5wIYsWLSSZTHLQQYfSoUMHRo48mtGjr2bEiENZvjxJjx49uOKK6+ql/olkMlkvBRVCRUVVsrx8cV5pS0s7NJn7IDWVAGn27AUNXQ0RESmwb76Zyrrrrt/Q1Vhj2fajtLTD28A22dJrkLaIiIhIBgVIIiIiIhkUIImIiIhkUIAkIiIikkEBkoiIiEgGBUgiIiIiGXQfJBEREWnUdt55OzbYYCMqKyspKipir71+ySGHDKVFixbMn1/OBReczaef/pvBg/fhtNPOrpMyFSCJiIhI3ko6tae4Zd11QFVULqe8bFHONK1bt2bcuLsBKCubx6hRF7B48SKOPvo4WrVqzTHH/Jb//vdzvvzyizqrlwIkERERyVtxyxZ1euPlvbddq1bpO3XqzFlnncexx47gqKN+Q9u2benff0tmzJhWZ3UCjUESERGRJqZnz14sX15FWdm8gpWhAElEREQkgwIkERERaVJmzJhOixZFdOrUuWBlKEASERGRJqOsrIyrrrqMX/96CIlEomDlFHSQtpn9HjgGSAIfAkcC3YF7gS7A28Bwd19mZq2BCcDWwFzgEHf/qpD1ExERkcZv6dKljBw5dMU0/1/8Ym8OPfTwFesPOmhfFi1aRGVlBS+//CLXXHMjfftusEZlFixAMrOewClAP3dfYmb3A4cCewPXuvu9ZnYLcDRwc/xf5u4bmdmhwF+AQwpVPxEREam9isrltZ55VlN+NXnppTdyrp848bG6qs4KhZ7m3xJoa2YVQDtgJrA7MDSuHw+MIgRI+8fHABOBG80s4e7JAtdRRERE8lTTPYuai4KNQXL3GcBV/9/encfZUZaJHv91ugOyJ4TIxQQHUHgEGRZZ3RCIjoAojiAgsgRwuQoIgwLKOAr3znVhuCIXFFQYBHXYBIQRBBkQUAaQRQQUHgdRJBkEhIQlYUun7x/v28nh2MtJ6JPT3fy+n09/+py33qp6T9WpOk+9SxXwJ0pg9CSlSW1uZi6o2WYB0+rracBDdd4FNf+UdpVPkiRpMO1sYptMqRVaF5gLXAjsNJLr6O7uYtKkFUdykVoCbntJGv8eeaSL7u6xP6arq2vJYoZ2NrG9E/hDZj4GEBEXA28FJkVET60lmg7MrvlnA2sDsyKiB1iN0ll7UL29fcydO7+lwkyduspSfQgNrtVtL0kau/r6+ujtHb6f0GjX1/fXMcNQsUE7Q8I/AdtGxIoR0QXMAH4L/AzYo+Y5ALi0vr6svqdOv9b+R5IkqRPa2QfpFkpn6zsoQ/wnAN8GjgGOjIj7KX2MzqyznAlMqelHAp9tV9kkSZKG0tZRbJn5ReCLTckPAFsPkPc54IPtLI8kSRp7tttua9Zb7/WL7oO0007vYa+99mHChAnceuvNnHbaqSxY8CI9PRM55JDD2WKLrV72Ots9zF+SJI0jq09age6JIxc+9L64gCfmPjtknuWXX57vfvffAJgz5wmOO+7zzJ8/j4MP/jirrTaJE044iTXWmMoDD9zPkUcexo9+9JOXXS4DJEmS1LLuiT08fs15I7a8KTP2XqL8kyevztFHH8tHP3oABx30MTbY4A2Lpq277ut4/vnneeGFF1huueVeVrnG/rg9SZL0ijJt2nQWLuxlzpwnXpJ+3XXXsMEGb3jZwRFYgyRJksaBBx74PaeddgonnfSNEVmeNUiSJGlMmT17FhMmdDN58uoAPProIxx77FF8/vPHM23a9BFZhwGSJEkaM+bMmcOJJ36Z3Xffk66uLp5++mmOOuoIPvGJQ9lkk81GbD02sUmSpFHt+eefZ+bMfRYN83/3u3dh770/DMBFF53P7NkPcdZZZ3DWWWcAcNJJpy6qXVpaBkiSJKllvS8uWOKRZ8Mtbzg33PDLQafNnPkRZs78yIiVp58BkiRJatlw9ywaDSeGjQAAF81JREFUL+yDJEmS1MQASZIkqYkBkiRJGlJfX1+ni/CyLE35DZAkSdKgenqWY968p8ZskNTX18e8eU/R07Nkd9e2k7YkSRrU5MlTmTPnMZ55Zm6ni7LUenqWY/LkqUs2T5vKIkmSxoHu7h7WWGOtThdjmbOJTZIkqYkBkiRJUhMDJEmSpCYGSJIkSU0MkCRJkpoYIEmSJDVpaZh/RKwJfAl4TWbuHBEbAW/OzDPbWjpJkqQOaLUG6bvAVcBr6vvfAUe0o0CSJEmd1mqAtEZmXgAsBMjMBUBv20olSZLUQa0GSPMiYgrQBxAR2wJPtq1UkiRJHdTqo0aOBC4DXhcRNwJTgT3aVipJkqQOailAysw7IuIdQABdJSlfHG6+iJgEnAFsTKl9OghI4HxgHeCPwJ6ZOSciuoCTgV2A+cDMzLxjST+QJEnSyzVkgBQRHxhk0gYRQWZePMzyTwauzMw9ImI5YEXgWOCazPxKRHwW+CxwDLAzsH792wY4rf6XJElapoarQXpv/f9q4C3AtfX9DsB/AoMGSBGxGrAdMBMgM18AXoiI3YDta7azgesoAdJuwDmZ2QfcHBGTImKtzHx4yT6SJEnSyzNkgJSZBwJExE+BjfqDlYhYizL0fyjrAo8BZ0XEpsDtwOHAmg1Bz5+BNevracBDDfPPqmkGSJIkaZlqtZP22k01OY8Ar21h2W8CDsvMWyLiZEpz2iKZ2RcRfS2Xtkl3dxeTJq24tLPrZXLbS5LGq1YDpGsi4irg3Pp+L+A/hplnFjArM2+p739ICZAe6W86qzVRj9bps4G1G+afXtMG1dvbx9y581v6AFOnrtJSPrWu1W0vSdJoNFRs0NJ9kDLzUOBbwKb179uZedgw8/wZeCgioibNAH5LuV3AATXtAODS+voyYP+I6Oq/z5L9jyRJUie0WoPUP2JtuFFrzQ4DflBHsD0AHEgJyi6IiIOBB4E9a94rKEP876cM8z9wCdclSZI0Ilp9WO22wCnAhsByQDcwLzNXHWq+zLwT2HKASTMGyNsHHNJKeSRJktqp1UeNnAp8CPgvYAXgI8A32lUoSZKkTmo1QCIz7we6M7M3M88CdmpfsSRJkjqn1T5I82s/ojsj4gTKvYlaDq4kSZLGklaDnP0o/Y4OBeZRhuPv3q5CSZIkdVKrD6t9sL58Fji+fcWRJEnqvOEeVns3MOidrjNzkxEvkSRJUocNV4O0a/3fP/z+e/X/vgwROEmSJI1lwz2s9kGAiHhXZm7eMOmYiLiDpmerSZIkjQetdtLuioi39r+JiLcswbySJEljSqvD/A8G/jUiVgO6gDnAQW0rlSRJUge1OortdmDTGiCRmU+2tVSSJEkdNNwotn0z8/sRcWRTOgCZ+bU2lk2SJKkjhqtBWqn+X2WAaY5ikyRJ49Jwo9i+VV/+R2be2DitsdO2JEnSeNLqSLRTWkyTJEka84brg/Rm4C3A1KZ+SKtSns0mSZI07gzXB2k5YOWar7Ef0lPAHu0qlCRJUicN1wfpeuD6iPhuwwNrJUmSxrVWbxS5fER8G1incZ7M3LEdhZIkSeqkVgOkC4HTgTOA3vYVR5IkqfNaDZAWZOZpbS2JJEnSKNFqgPTvEfFJ4BLg+f7EzHyiLaWSJEnqoFYDpAPq/6Ma0vqA9Ua2OJIkSZ3X6sNq1213QSRJkkaLVmuQiIiNgY2AV/WnZeY57SiUJElSJ7UUIEXEF4HtKQHSFcDOwC8AAyRJkjTutFqDtAewKfCrzDwwItYEvt/KjBHRDdwGzM7MXSNiXeA8YApwO7BfZr4QEctTAq4tgMeBvTLzj0v0aSRJkkZAqw+rfTYzFwILImJV4FFg7RbnPRy4t+H9V4GTMvP1wBzg4Jp+MDCnpp9U80mSJC1zrQZIt0XEJOA7lFqfO4CbhpspIqYD76HcYJKI6AJ2BH5Ys5wNvL++3q2+p06fUfNLkiQtU62OYvtkfXl6RFwJrJqZd7Uw69eBo1n8oNspwNzMXFDfzwKm1dfTgIfq+hZExJM1/19aKaMkSdJIabWT9nYDpWXmDUPMsyvwaGbeHhHbL30RB9fd3cWkSSu2Y9FqgdtekjRetdpJu/EGka8CtqY0tQ31sNq3Au+LiF3qPKsCJwOTIqKn1iJNB2bX/LMp/ZpmRUQPsBqls/agenv7mDt3fksfYOrUVYbPpCXS6raXJGk0Gio2aLWJ7b2N7yNibUrz2VDzfA74XM2/PfCZzPxwRFxIGRV3HuUO3ZfWWS6r72+q06/NzL5WyidJkjSSWu2k3WwWsOFSznsMcGRE3E/pY3RmTT8TmFLTjwQ+u5TLlyRJella7YN0CuXZa1CCqs0pI9lakpnXAdfV1w9Qmuia8zwHfLDVZWp8mjR5JSb2LG3cvuy8uGAhc+fM63QxJElt0mofpPuA7vr6ceDczLyxPUXSK9nEnglccesznS7GsHbZauVOF0GS1EZDBkgRMRH4F2B/4I81eU3gFODGiNgsM+9sawklSZKWseFqkP4vsCLwN5n5NEC9k/aJEXEasBOwbnuLKEmStGwNFyDtAqzfOJosM5+KiE9QbuC4czsLJ0mS1AnD9YZdONBQ+8zsBR7LzJvbUyxJkqTOGa4G6bcRsX9mntOYGBH78tIH0EqvKH29vWPm5qO9Ly7gibnPdroYkjSmDBcgHQJcHBEHUe6cDbAlsALw9+0smDSadXV38/g153W6GC2ZMmPvThdBksacIQOkzJwNbBMROwJvrMlXZOY1bS+ZJElSh7T6qJFrgWvbXBZJkqRRYfTfsliSJGkZM0CSJElqYoAkSZLUxABJkiSpiQGSJElSEwMkSZKkJgZIkiRJTQyQJEmSmhggSZIkNTFAkiRJamKAJEmS1MQASZIkqYkBkiRJUhMDJEmSpCYGSJIkSU0MkCRJkpoYIEmSJDXpadeCI2Jt4BxgTaAP+HZmnhwRqwPnA+sAfwT2zMw5EdEFnAzsAswHZmbmHe0qnyRJ0mDaWYO0APh0Zm4EbAscEhEbAZ8FrsnM9YFr6nuAnYH169/HgNPaWDZJkqRBtS1AysyH+2uAMvNp4F5gGrAbcHbNdjbw/vp6N+CczOzLzJuBSRGxVrvKJ0mSNJhl0gcpItYBNgduAdbMzIfrpD9TmuCgBE8PNcw2q6ZJkiQtU23rg9QvIlYGLgKOyMynImLRtMzsi4i+pV12d3cXkyatOAKl1NJw248d7itJWjJtDZAiYiIlOPpBZl5ckx+JiLUy8+HahPZoTZ8NrN0w+/SaNqje3j7mzp3fUlmmTl1licqu4bW67ZeE+6k92rGvJGmsG+o3p21NbHVU2pnAvZn5tYZJlwEH1NcHAJc2pO8fEV0RsS3wZENTnCRJ0jLTzhqktwL7AXdHxJ017VjgK8AFEXEw8CCwZ512BWWI//2UYf4HtrFskiRJg2pbgJSZvwC6Bpk8Y4D8fcAh7SqPJElSq7yTtiRJUhMDJEmSpCYGSJIkSU0MkCRJkpoYIEmSJDUxQJIkSWpigCRJktTEAEmSJKlJ2x9WK2n8mTR5JSb2jP7rqxcXLGTunHmdLoakMcgASdISm9gzgStufabTxRjWzm9aYcw8ALn3xQU8MffZThdDUmWAJGnc6uru5vFrzut0MVoyZcbenS6CpAajv45ckiRpGbMGSZLGqbHSV2xhby8Turs7XYyWtKMp1P008kZiPxkgSdI4NVb6iu2y1cqv6KZQ99PIG4n9NPpDVkmSpGXMAEmSJKmJAZIkSVITAyRJkqQmBkiSJElNDJAkSZKaGCBJkiQ1MUCSJElqYoAkSZLUxABJkiSpiQGSJElSEwMkSZKkJqPqYbURsRNwMtANnJGZX+lwkSRJ0ivQqKlBiohu4BvAzsBGwIciYqPOlkqSJL0SjZoACdgauD8zH8jMF4DzgN06XCZJkvQKNJoCpGnAQw3vZ9U0SZKkZaqrr6+v02UAICL2AHbKzI/U9/sB22TmoUPM9hjw4LIonyRJGnf+Bpg60ITR1El7NrB2w/vpNW0oA34oSZKkl2M0BUi3AutHxLqUwGhvYJ/OFkmSJL0SjZo+SJm5ADgUuAq4F7ggM3/T2VJJkqRXolHTB0mSJGm0GDU1SJIkSaOFAZIkSVKT0dRJe1yLiGcyc+UB0v8FeC/wAvB74MDMnBsRM4EtB7rNQUT8A/ARoA+4u87zXER0Af8MfBDoBU7LzP9X008GdgHmAzMz8452fM5OGmi7AFcDq9QsrwZ+mZnvH2DePwJbAlOA8xsmrQd8ITO/HhEfBI4DNgS2zszbmpbxWuC3wHGZeWJEvAq4AViecqz9MDO/WPMOuK/qtO2BrwMTgb9k5juWeqOMARFxOPBRoAv4Tt3Wb6DcLLYP2AN4HwN/59et+aYAtwP7ZeYLETEV+DGwHPAp4B+BtSj74efAIZnZ27SevRl8358PRE2fBMzNzM3as0VGj0GOqfso56a/NOV9LXA2Zft0A5/NzCsi4sPAUQ1ZNwHelJl3DrHen9PCcduQfyJwBvAmyj4+JzO/PNQxOJ7U89fTlHPJgszcsqYfBhxS0y/PzKMj4l3AVyjHxgvAUZl5bc3/IeBYyv7+b2Df5v3csM7tgc9k5q4DTLuSAY63kfq8y4o1SJ13NbBxZm4C/A743FCZI2Ia5YS/ZWZuTDkR7V0nz6TcKuENmbkh5cQP5fEt69e/jwGnjfBn6LjBtktmvj0zN6s/ZjcBFw+1nCz6829BCSgvqZPvAT5AOeEO5GvATxrePw/smJmbApsBO0XEtnXaTAbYVxExCfgm8L7MfCMlgBq3ImJjSnC0NbApsGtEvB54P+XHbHPgOQb/zn8VOCkzXw/MAQ6u6TOAuzNz88z8ObBn3Q8bU24P0r9dF61nqH2fmXs1TLuIYb5H48Ew55qBfJ4yuGbzmu+bAJn5g4Zttx/wh6GCozrPEh23lP25fGb+LWXffTwi1mHoY3C82aFus/7gaAfK0yg2reeSE2u+vwDvrdvqAOB7NX8P5UJ6h/p7dBdl4NTSGOx4G1OsQWpRROwPfIYSWd8FXEA5ISwHPA58ODMfiYiVgVMotRF9wPGZeVFdxknA3wF/pvx4P5aZP21Yzc2Uq+V+a0fEdZQ7in8/M4+v6T3AChHxIrAiJdIH+ASwT2YuBMjMR2v6bpQrqj7g5oiYFBFrZebDI7FtRpHBtgsRsSqwI+UKmIiYApxL2bY3UWovms0Afp+ZDwJk5r113r/KGBHvB/4AzOtPq9v7mfp2Yv3rHxUx2L7aB7g4M//UlD5ebQjckpnzASLieso2+CTQGxEzgH0ZYN/WWrgdWXw7kLOB4yLiJuCEmn9L4M2Z+VTN00M5ZvsiYhfgiP71ZOYODeV6yb7vV9e5Z13vK8Fgx9TREbEz8Czle3w/5bu9ap2+WkPeRh9i8YUbEXEasBWwAgPU7gxw3G5N+RF/VV33gZmZdd0r1R/5FSg1I08NcwyOd58AvpKZz8Pic0lm/qohz28o+3d5YCHlPLhSRDxO2Zf3A9SLltMpwU4viwOeVSPicuD1wM+AT2bmwoGOt7qc11GeuTqVcgHy0cy8r9b4ng68ts53RGbeOJIbY2lYg9SCiHgjJRjqvxI5HPgFsG29WjoPOLpm/yfgycz82xqFX1vTVwJuq5H89cBA1bwH8dIaiK2B3SlV0h+MiC0zczblSuBPwMN1Xf1B1uuAvSLitoj4SUSsX9PH/WNchtkuUGoKrmk4cL8I/KLuj0tYfGA22psSRA2pBsXHAMcPMK07Iu4EHgWuzsxb6qTB9tUGwOSIuC4ibq+B+Xh2D/D2iJgSEStSmoH7T5YnZeYOQ+zbKZSmrgV1WbOAabV24gvA+fWK+lmAiLiKsh+epvwYX9G4nqZyDbbv3w48kpn/NVIbYLQa5ph6stZAnEppDobS/LxvRMwCrgAOG2Cxe/HS7fqPtcZjE+AdEbFJU/7m4/Y+4O31vPsF4Es1/YeUi5OHa3lPzMwnYMhjcDzpA35azxkfq2kbUI6tWyLi+ojYaoD5dgfuyMznM/NFSlB1NyW43Qg4s+b7AfCN+vv3Fsp2hvIbdVjN+zpKDTvw18dbTf42cFhmbkGpcPhmTT+ZchxuVct0xtJvipFjgNSaHYEL+9ti64E3HbgqIu6mtK+/seZ9JyVCpuadU18uZHH/hu8Db2tcQUT8I7CA8kXsd3VmPl5P8BcDb4uIyZQaoXWB11Ci/X1r/uWB5+oJ5zvAv77cDz5WDLNdoFy5Np6Yt6PsBzLzckrzTOPylqP0e7mwhdUfRzm4n2mekJm9tZlgOrB1bVKCwfdVD6WJ4D3Au4F/iogNWijDmFRr5b4K/BS4EriTcoW6SAv7ttV1vZvSL2J5hqgBGmbfN3+Pxq1htvu5Df/fXF9/CPhuZk6nBLrfi4gJDcvbBpifmfc0rGbPiLgD+BXlHLpRUzGat/dqwIURcQ9wEovPu1tTvjevqeX9dESsB0Meg+PJ2zLzTZTuFIdExHaUc8nqwLaU36gLag0osOjC/6vAx+v7iZQAaXPKdrwL+FxErEK58Ohvbn6uv8aX0jfsgSz9i86l4Xet+XirF5Jvoey/O4Fv1elQfjdPremXUWqm/qrP7rJmgLT0TgFOrVdRH6dU+S6JRdW8UTpk70pppusbKE/D+3dS2vAfqxH/xZQvHZQr6P62+ksoV2WwdI9xGWsG3S4RsQblBHr5EixvZ8qV1SMt5N0GOKF2lDwCODYiXtJ2n5lzKVXQO9WkwfbVLOCqzJxXA/IbKH1zxq3MPDMzt8jM7SiB6u+asgy2bx8HJtVmFWjhe52ZzwGXUn74BzPgvq/r+QAv7cg9ng11rhnoPHUwpesBmXkT5Zy4RkO+l9TK1Q72nwFm1Nr2y2k4jw5y3P5v4GdZ+kS9tyH/PsCVmflibUq6kdLNYZEBjsFxo9b29TejXULZbrMozfV9mflLykX6GgARMb3m2z8zf18Xs1ldxu/r79AFLN7fgxnoN6qxXI3H2wTq4IaGvw1r1gmUFpn+9GkDXXAuawZIrbmW0sQ1BSAiVqdcyfSfjA9oyHs1ZdQANe/k+nICi/sX7UNpoiMidqI0z72vISrv966IWD0iVqBUNd9IqT7eNiJWrFcDMyh3Hgf4EdDfVPAOFv/QXAbsHxFdtYPik+Ow/9FQ22UP4Mf1YO13A7XvSu1LMZmXarmmIEuH0nUycx1Kc8OXMvPUiJhaO11T9+G7KE0EMPi+upRSU9hTm5y2afgc41JEvLr+fy0lAPm3piwD7tt6Ev8Zi4+rAyjbr3n5K0fEWvV1D6V27r7mfA0G2/fvBO7LzFmtfrYxbqhjaq+G/zc15J8BEBEbUoKXx+r7CZS+W4v6H1H6uMwDnoyINSmBaaOBjtvG8+7MprLuWNe1EqXW5L5hjsFxISJWqrU8/Z/97yhN14vOMbUWejngL3V7XE4ZZdjYz2c2sFHtDwRlW92bmU8Ds2o/SyJi+XpuglIjt27dv3sBvxjseKvNpH+IMhqY+nvUf/H3UxqaZCNiVIwQNUBqQZZHnvwf4PqI+DVltNJxlKrC2ymjAvr9M6UPyT01b/+P4DzKl+keyoH8v2r6qZThrFdHxJ0RcXrDsn5JGTFzF3BRZt5W289/CNxBaSueQGnXhTJ0c/fa7PdlyvBcKP0BHqB0uPsOpQPsuDLMdhmoP8nxwHYR8RvKj/Kf+ifUk8y7aBo5ExF/X/tXvBm4vLaxD2Ut4GcRcRflWYNXZ+aP67QB91VtcrqSss9/CZzR1CQxHl0UEb8F/p0yHHhu48Rh9u0xwJERcT+lT9KZ/LWVgMvqfujvi3L6APkG3fdVS33Sxothtvvkuj0PB/6hpn0a+Gg9751LuZ1If43CdsBDmflAw/J/TWlau48SFDd3yh1oe58AfDkifsVLBxl9A1i5Hs+3Amdl5l0MfQyOF2tSApNfU84Zl2fmlZRm+/Xqb855wAF1fxxK6VT9hfqbc2dEvDoz/5tyXryhbq/NWNzHaz/gUzX9P4H/UdNvpfyG3UsZpHIJQx9vHwYOrmX9DYtrcj8FbBkRd9Vzwf8c4W20VHzUiCRJUhNrkCRJkpoYIEmSJDUxQJIkSWpigCRJktTEAEmSJKmJAZIkSVITAyRJkqQmBkiSJElN/j+TEZRIcvwCxAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "8-KlObsQwQBr",
        "outputId": "522281a4-f8c7-4989-9e68-cfd50a2b784c"
      },
      "source": [
        "fig, ax = plt.subplots(4, constrained_layout=True)\n",
        "plt.suptitle('Comportamento dos genes em relação ao composto cacb2b860', fontsize = 20)\n",
        "c = df[df.composto == 'cacb2b860']\n",
        "\n",
        "box1 = sns.boxplot(data = c, x = 'g-0',ax=ax[0], color = \"red\")\n",
        "box2 = sns.boxplot(data = c, x = 'g-250',ax=ax[1], color = \"blue\")\n",
        "box3 = sns.boxplot(data = c, x = 'g-500',ax=ax[2], color = \"green\")\n",
        "box3 = sns.boxplot(data = c, x = 'g-750',ax=ax[3], color = \"yellow\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iVRFm_HS6GN4",
        "outputId": "a3ee0b5e-f303-4695-c032-73b0d97b1022"
      },
      "source": [
        "# Comparação entre os genes com maiores e menores valores médios :\n",
        "m = df.loc[:,'g-0':'g-771'].mean().sort_values()\n",
        "min, max = m[:3], m[:-4:-1]\n",
        "print(min,'\\n\\n',max)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "g-370   -0.648438\n",
            "g-508   -0.641689\n",
            "g-37    -0.606710\n",
            "dtype: float64 \n",
            "\n",
            " g-707    0.744700\n",
            "g-100    0.553186\n",
            "g-744    0.548903\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 601
        },
        "id": "aRXy_YEc-p-p",
        "outputId": "90f19f85-1990-4912-b135-3c19bbf8eed5"
      },
      "source": [
        "fig, ax = plt.subplots(2,3, figsize = (10,8), constrained_layout = True)\n",
        "\n",
        "hist1 = sns.histplot(data = df, x = 'g-370', bins = 100,ax=ax[0,0], color = \"blue\")\n",
        "hist2 = sns.histplot(data = df, x = 'g-508', bins = 100,ax=ax[0,1], color = \"red\")\n",
        "hist3 = sns.histplot(data = df, x = 'g-37', bins = 100,ax=ax[0,2], color = \"yellow\")\n",
        "hist4 = sns.histplot(data = df, x = 'g-707', bins = 100,ax=ax[1,0], color = \"green\")\n",
        "hist5 = sns.histplot(data = df, x = 'g-100', bins = 100, ax=ax [1,1],color = \"purple\")\n",
        "hist6 = sns.histplot(data = df, x = 'g-744', bins = 100, ax=ax [1,2],color = \"brown\")\n",
        "fig.suptitle('Vizualização dos genes que apresentam menores e maiores valores médios', fontsize=20)\n",
        "ax[0,0].set(ylabel= \"Quantidade\")\n",
        "ax[0,1].set(ylabel= '')\n",
        "ax[0,2].set(ylabel= '')\n",
        "ax[1,2].set(ylabel= '')\n",
        "ax[1,1].set(ylabel= '')\n",
        "ax[1,0].set(ylabel= \"Quantidade\");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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xr4vXxDtLJ3b3/zazpcDOZjY2JcCK6nHsVVJc52sqrHNSbp0Lq1xmufX/b3r/79IHV3fvNrPniTYUG7GofnsGsA9Rd7v0mWV7em/MuTn3wHI1Gvpzv7iGqBrzmJldT/xvd7v7n3qJd6lbiLr/7zezc3P7t5hguLp0Bu27Tfy2TFjxuKx0XYGNj8ua7ncpM/n1wLMVrmt3saHdWF9qvd7cQDyH/tDMbgJ+Suy7cvEoq6oEgrsXzOwqoqHMB4GzLeo3n0ak+L7T2/ylzOytRG7VM8BR7r45bQ+Ky9yf2HGtRH2vBUSDjPVECnAKVRS5VuHrwOFEA9svlYnHu4mSgr8RdWmfJBoBrieqpLy1JB4d6b3PG2gqwrqfuFHeR5yUK4kUdgdxMOSXPTa9V7oIFMM7KvyeV1xWpWoiz7FpAmEssDKfk1/k7l1m9mciAVUMu9miTuPZRGp5OoCZPQDMcvfFVcZzpZfvj7hc3LdL75Po/UQdUyZsdZkwiP8jXzq3DVFPcFwf6+gxwPui3MX9uTJh/VHcf29Pr0rK7b+N9OP4zuvruBzLxv/XCi/fLXBxe/pqNzEGwN0707Xns0QRdrGE48+pGP7C3P7fjrg+9XUMjCFKlIp6O84g6h9XZTOuk5V6div2Wlfu92L8es2pHKT1DMW+rub6+vfEsZuPdz2OvUqK6yyXiNpknVXa5D9K1/uyvyVdlBwnZvYRog3GKuJe+j9EtYgC0X5jD/q+p2/OPbDcNbLm+4W7X5LudWcSJVsfBQpm9nOiNKXcg+tG3P2vZnYjcWwcRrTZ2JKoRvonSjIYte/K6u3aUct1Baq/31Xz3FStmq437n6fRUcn/0a0CTkJwMyc6PDgugrL6VFtCQJEnc3PEfWAZwFvIXL47qyQ41KWRQ8NtxApxSO9fL3kYmlCpfiVOyDPIxquHOzud5WscxZx49ssZvYp4kHtx0R98XIuIOrM7ZMraSnO/y0igZBXvCHtQN8DnX2QeHgq14vMAcQDVF7xoP+7CsubUDJdb4rTjCcaUpcqt441wLZmtkXpjSrVfd2eeDjp4e63AbeZ2dZE48KjiEaJPzKzvUqL3svoTOtsLZNIGN/Ldt3i7tVUteqP4jp+5+5v6nXKnAHYFxX3P5WPid7OvXLnXXHbPuLutRSXllPr8Z03nmhgWaq4naXHeKUxQ4rTVT0qeSrVOS1lmuxKdEgwg2jUOopojFZc9ih337aa5Q6SQb9ONoih2Nf562u5XLlK19d6HHuVFNc5xd0XVLPOoZDuD+cTD1Bv8uj2Mf/7AeXmK2Nz7oHl/qd+3S/cfT4wP2WCvBl4N5Hxs8jM/qHKHPF5RAJhKvEM8k7igfWy/PVd+25Q1Xq/yz83lVNp3/a2rKqvNx69Zh5l0VB6byJz+8PAtWb2J3f/aW8rrLYNAulBfgHxUHcMG+o69do4Oc+ie7PbiNTVv/TygLMqve9UZhntbChqzXs9kVt6V5nfSh/Ka2ZmxxH1Kv+LGDGvUhHu64HHyiQORhE90pQqtl+opsHQ69P7D8r8Vm4bf5fe/9lyPeTkFHvaqTS+RV5xmk3WY2avpcx/ldY/iqjKUOogIjeu7Lrd/S/ufqe7f5xodLMl1e2j4jrfXOa3cvv/D0Qibf++6mT2l0f7i0eB3Sy6R6t1/v7uiweJfVFuuydXmKfiuUcUVZcqHr9vqSI+fan1+O7199xxuaSkelFv+r097l5w90fd/XI25C4dU7LsbVIVn8FSvC5VKlUY1OtkAxmKfV28vk4u/cFixPsdgacb5Ngb8HUOsu2JDIlfl3nAHcOG6hZ9Gch7IGzm/cLdV7v7Qnf/EFEtaFvK3x/LzXs3UT1nikWnAsXqRaW9u2nfDZ6azpdUne4JYAcze12ZSSbXsO5+X2882p792t0/w4b2WX1mBlWdQEiKVYnOJlJxf6bKEYctuhpcQJQ6THf3OypNm3bqH4g2Dz0NslL9/0uIHLBSS4jc0jeWrPc0KjdsrEpKcX+PqK/2ztI6lGXiMcmiB4ji/BmRoi/X7dw8Itf7X81sk4PdNu7FaEl6n1wyzV6UGT0y5S4tJrqd+2jJPPsRPQytorr/8BqiTu+HLXo0Ki5nFDFORrljaW56/w/LdZGbPhcbsc3JhR9U4UJUTH1XUxWtWBfyQtu4y6+xlMlNS6UMlxOp769ZDJ2+ETObYJs2DKzVJcSD/dyUE1K6jm1s4y4MB2JffDe9X2S5rj5TIuW8CvMU646WdtX2j5TJwU9FvL8EjjWzso2BzewfzexV5X4rsSS9Ty6Zv+zxXeIjFt3PFefJH5ffrTjXpr5L3MRmm1lpQ3PMbJTFeBDF77tZ9EVfqtz/VOzS7jv560NuWVunKiObYxWRe1faZWTREgbpOtlghmJfF69v56XMr+KyW4AvE8fenHIzVjCYx14ltxK5kTOsQnemZnaAle/ifDCtIOK/d3qoLcZlC6LDgqp6sBnge2C/7hdmdnB6BihVvCbWUsV6HtFm6EyindbD7v67kmm07wZJP+933yWuBV+wXJepFl3InlU6fy9qut6Y2ZvL7WNquD7UUsUIoj/jJWzooeWKcvXLKziLaJD7FJUbRF3tG3rI+RKpP1oz+z5Rp/9goj7YfxF16PK+StzgfmVRV28NkeP5z0SbgOOqjGc5c4iT8l7gQ7Zp45rV7v7V9PlSomuw35nZD4iH6gPZ0I/v0fkZ3f3PZva+FMefmdmPiQZs7URD6J2IahcQD7+fBL5q0Y3fH4n6fEcRXWiV63P8DKLh2pfM7DCioc5ORJ3T9cQASn32duHuSywGbPlK2rYbiH38DiK34uEU3/w815rZFKJ73Ectusst1oHcmRjoJN9zwNeIlPbdxHH2MlEsdgjRXqXsOAYl5gMnEEVpj5jZAuKY+ReifruxaY9LFxDH0xnA0WZ2J9Em5FXE/j2QqMdX9eAypdx9rpntTepP2syKvR1tS+yLg4gLyRlploHYF9cRx8S7iH1xK7EvjiP2RbkcjVuJ4+rElDi9l3jYnJJ+O77MPO8j6rXPMbOz0jyriRyNNxJjQxxA3yN+9+f4LrobeKjkuNyDaHz2xV7m24i7v2BRWngLcI+Z3UGU/hSI8+YAoli/mOB6O3Fu/YboCnNF2u4pxHH2pdyy77ANgx790cwWEr3zjCHaSbyVaFC+yVgpNcT/RTO7F3iLmV2T4tQNLEjVVgbzOtkwhmhf/9rMvkiMVfOIRUPAvxCle7un5W/STq2X5Q3asdfLOv/PzI4lunu8zcx+TfTwtC6t85+ITL0JDOHDmLuvN7OvEd3X/j5du7YkngG2JTpt2GSsmQoG5B6YU+v94hbgRTO7h7iWZ0QO9D8R16deq3mU+B5R1fuzxLV8k7FhtO8GXa33u68Qzzz/AjyY7v0dxL30F8T9uU/9uN58CjjEzIq9wL1IDAJ5BJGw67P2T00lCKlh1VW5oFoaJxdzIF5LNFAp95qYW9dcohrT/xJFaccTPdMcSJmGZB5dah1NHFjvJRpQv0ScCLfVEM/e4n5shXj3pK7d/VtE707LU7zfT/SAsR+Vq9PcRtykryF6BJhF1CMtEDe44nT/S5wctxE39JnEze5M4mJQbtlPpWV/k3g4/gRxgNwOHOib9u1fkbtfQpwcTxMDjJxKjBz8ZjZUTSl1YtqWF4j2G2ekaWemZeV9njjhdyP++zOI1O7ngX9y90rryMexQJRuXUBcQD9M3DDnpXXCpu0e/o84gU8m6rEXGwcfzoZ6vKVdoNXM3WcQx+hviL6XP05cHMYSJ/ZXc5MP1L54D3GMjiK2/11EQqTcgz4e3aEeSvTUtXua57XEf3VlhXmWEomXfyMeRt9PZAi8mUgETafv9jX9Or5zPkZ0OTuZKOkYR+SWHeK5Ll6rkUo330gM5jeR2PenEfvjTiIBWrSIyBUbTRxnZxOJvcXAW7yklzN3/0L6/TbiWvZR4j/agbhgVyrZqcVJafmHE//9BaRqBYN8nWwoQ7Gv3f0c4hr3R+L6cRZxrp1HjKVQbQZacXmDduz1ss6HiYe2LxDXomlEW6e9iWoNJxG1BYbavxPb9FfiGnIs8YC6Lxt6AezTQN4D0/JqvV+cS2TIvIm4lk0j7k3nEG2Bqu4B0t3/h3jA34JoRFvpvqR9N0hqvd95dNn8NiLzeBxxf3orcb8qHYelr3XXcr35BlFdd2fiHP4wUT3/G8BeXkVvRlmhUKm9lNSLmU0jHh738vK98Ug/mNnbiVKwi929ryorw56ZFYCfu/vkeselv6yXIelFRESkf2ptgyBD42Yix+iQekekGVWoc7wdG9o9VFVnUkRERGQkqrUNggwiMzubaEBUbKQzKL3qjACXWIx4+Guij+gdiWLRbYnxK8oN4iIiIiIiKIHQaNqJ+voZMfz8ovpGp2ndTNTXP5poDPQ3orHfHGrrVURERERkxFEbBBERERER6aE2CCIiIiIi0kMJBBERERER6aEEgoiIiIiI9FACQUREREREeiiBICIiIiIiPZRAEBERERGRHkogiIiIiIhIDyUQRERERESkhxIIIiIiIiLSQwkEERERERHpoQSCiIiIiIj0aK13BJrR+vXrC93dhV6naWnJ6GuawaY4KA6DEYcttmj5MzBu82M0tJrlvB1s2sbhodZtbKbzVueqtq/Zbe72NcL5qgRCP3R3F1i9el2v03R0jO5zmsGmOCgOgxGHcePanhmA6Ay5ZjlvB5u2cXiodRub6bzVuarta3abu32NcL6qipGIiIiIiPRQAkFERERERHoogSAiIiIiIj2UQBARERERkR5KIIiIiIiISA8lEEREREREpIcSCCIiIiIi0kMJBBERERER6dHUA6WZ2ceADwIF4PfANGACcD2wHfAAcJK7v2xmrwDmA3sDLwDvdfclaTmzgNOAbuAsd180xJsiw1iW1TsGIiNP6XlXGL6Dtoo0reJ5qvOz8TRtCYKZ7QCcBezj7rsDLcAJwBeAS9399cAq4sGf9L4qhV+apsPMdk3z7QYcDnzDzFqGcltk+MoymDlzK045ZZQSCiJDqH3mdNrPPTveZ07X+SfSYLIM2tun096u87MRNW0CIWkFtjKzVmA0sBw4BLgp/T4POCZ9npK+k34/1MyyFH69u7/k7k8DTwD7DlH8ZQTo7IS1a+sdC5ERpnjidXbGS0QaUGd6SaNp2gSCuy8Dvgz8D5EwWENUKVrt7l1psqXADunzDsCzad6uNP12+fAy84iIiIiIjChN2wbBzLYhcv93BlYD3yeqCA26lpaMjo7RfUwzqs9pBpvi0BhxaG2N6kVjx47s/SAiIiLNoWkTCMDbgKfd/U8AZnYzcCDQYWatqZRgR2BZmn4ZsBOwNFVJGks0Vi6GF+XnKau7u8Dq1et6jVxHx+g+pxlsikP945Bl0NW1Fa2tLaxZs66uDbEGaj+MG9c2ALERERGRRtW0VYyIqkX7m9no1JbgUOAx4GfAcWmaqcCt6fOC9J30+53uXkjhJ5jZK8xsZ2AScN8QbYOIiIiISENp2gSCu99LNDZ+kOjidBTwbeAc4ONm9gTRxmBOmmUOsF0K/zhwblrOo8CNROLidmCGu3cP4aaIiIiIiDSMZq5ihLvPBmaXBD9FmV6I3P1vwHsqLOci4KIBj6CIiIiISJNp2hIEEREREREZeEogiIiIiIhIDyUQRERERESkhxIIIiIiIiLSo6kbKYuIiFQjy6jrOCTNxsx2AuYD44EC8G13v8zMtgVuACYCS4Dj3X1V6m78MuBIYB1wirs/mJY1FTgvLfpCd583lNsiIrVTCYKIiAxvbW20z/oEWVbviDSVLuBsd98V2B+YYWa7El2E3+Huk4A70neAI4hxhCYBpwNXAqQExWxgP6KHwdlmts1QboiI1E4lCCIyZMxsLnAUsMLdd09hNwCWJukAVrv7nmY2EXgc8PTbPe5+Rppnb+BqYCtgIfCRNPChSFmFtWvrHYWm4u7LgeXp81ozexzYAZgCTE6TzQPuIsYfmgLMT+fhPWbWYWYT0rSL3X0lgJktBg4HrhuyjRGRmimBICJD6WrgCqLqAgDu/t7iZzP7CrAmN/2T7r5nmeVcCXwIuJdIIBwO/HgQ4isy4qXE+l7E+TY+JQucuWQAACAASURBVB4AniOqIEEkHp7NzbY0hVUKr6ilJaOjY3SvcWppGdXnNM1sJGzf2LGjaWmJiixjxw6vbR0O/58SCCIyZNz9F+lhYxOpDvPxwCG9LSPlSra7+z3p+3zgGJRAEBlwZjYG+AHwUXfvNLOe39y9YGYDXnLX3V1g9ep1vU7T0TG6z2ma2UjYvjVr1tHevh6Azs51w6qN0Ob+f+PGtQ1gbPpHbRBEpFG8BXje3f+YC9vZzH5nZj83s7eksB2IXMiiPnMkRaR2ZrYFkTi4xt1vTsHPp0R6MbG+IoUvA3bKzb5jCqsULiOc2gQ1NpUgiEijOJGN6yUvB/7e3V9IbQ5+aGa79XfhqrYQRso20lryyrJhVY1hsP/HVKI3B3jc3S/J/bQAmApcnN5vzYXPNLPriQbJa9x9uZktAj6fa5h8GDBr0CIuDS/LoKXlZNratq53VKQXSiCISN2ZWStwLLB3MczdXwJeSp8fMLMngV2I3Mcdc7NXlSOpagthuG9jlkV95kLXesi/RmV0rhk+1Rhq/R/7UWXhQOAk4Pdm9lAK+zSRMLjRzE4DniGqBUK0BToSeILo5nQagLuvNLMLgPvTdJ8rNliWkWwtsL7ekZBeKIEgIo3gbcAf3L2n6pCZjQNWunu3mb2W6D7xqfTA0Wlm+xONJk8GLq9LrKWhZBm0z5xOy9g2uuodmSbn7r8CKlUCObTM9AVgRoVlzQXmDlzsRGSwqQ2CiAwZM7sO+E18tKUpFxLgBDbt9vAg4OGUe3kTcEYu5/FM4Coit/JJ1EBZijo74cUX6x0LEZGmphIEERky7n5ihfBTyoT9gGggWW763wK7D2jkREREBFAJgoiIiIiI5CiBICIiIiJ1oy5PG48SCCIiIiJSJ220t39CiYQGowSCiIgMC3rAEGlOhcLaekdBSjRtI2WL8d5vyAW9FvgMMD+FTwSWAMe7+6o06MtlRD/N64BT3P3BtKypwHlpORe6+7yh2AYRERkYWQbtF85mmAxzIDIsZZkS8s2iaUsQPOzp7nsSgyutA24BzgXucPdJwB3pO8ARRD/qk4DTgSsBzGxbYDYx8uO+wOzciI8iItIkCureVKRhZRm0t0+nre3sekdFqtC0CYQShwJPuvszwBSgWAIwDzgmfZ4CzHf3grvfA3SY2QTgHcBid1/p7quAxcDhQxt9ERERkeGukxhFWRpd01YxKpEfZGm8uy9Pn58DxqfPOwDP5uZZmsIqhVfU0pLR0TG61wi1tIzqc5rBpjg0RhxaW0eRZTB27MjeDyIiItIcmj6BYGZbAu8CZpX+5u4FMxvwKqnd3QVWr17X6zQdHaP7nGawKQ71j0OWQVfXVrS2trBmzToKdawgPVD7Ydy4tgGIjYiIiDSq4VDF6AjgQXd/Pn1/PlUdIr2vSOHLgJ1y8+2YwiqFi4iIiIiMOMMhgXAiG6oXASwApqbPU4Fbc+Enm1lmZvsDa1JVpEXAYWa2TWqcfFgKExEREREZcZo6gWBmWwNvB27OBV8MvN3M/gi8LX0HWAg8BTwBfAc4E8DdVwIXAPen1+dSmIiIiIjIiNPUbRDc/S/AdiVhLxC9GpVOWwBmVFjOXGDuYMRRREQaQ7H/9Xq2BRIRaQZNXYIgIiJSlTFjaJsxnfaZ0zVQk4hIH5q6BEFERKRqnZ31joGISFNQCYKIiIiIiPRQAkFERERERHoogSAiIiIiIj2UQBARERERkR5KIIiIiIhIXWUZ6mGsgagXIxEZMmY2FzgKWOHuu6ew84EPAX9Kk33a3Rem32YBpwHdwFnuviiFHw5cBrQAV7n7xYiISJMaQ1vbdAA6O7+lsUoagBIIIjKUrgauAOaXhF/q7l/OB5jZrsAJwG7Aq4Gfmtku6eevE6OoLwXuN7MF7v7YYEZcREQGk7ohbiSqYiQiQ8bdfwGsrHLyKcD17v6Suz8NPAHsm15PuPtT7v4ycH2aVkREGpSqDzUXJRBEpBHMNLOHzWyumW2TwnYAns1NszSFVQoXEZEGlGXQ3j673tGQGqiKkYjU25XABUAhvX8FOHWgV9LSktHRMbqPaUb1OU2zG87b2NIyClpHkWUZra3xueeVfgMYO7b5t384/48yPBUKL9Y7ClIDJRBEpK7c/fniZzP7DvCj9HUZsFNu0h1TGL2EV9TdXWD16nW9TtPRMbrPaZrdcN3GLIP27vXQtZ7WQoGurvjc80q/AXSuWdf0jSBr/R/HjWsbxNiIyHCjBIKI1JWZTXD35enru4FH0ucFwLVmdgnRSHkScB+QAZPMbGciYXAC8L6hjbWIiMjwpQSCiAwZM7sOmAxsb2ZLgdnAZDPbk6hitASYDuDuj5rZjcBjQBcww92703JmAouIbk7nuvujQ7wpIiIiw5YSCCIyZNz9xDLBc3qZ/iLgojLhC4GFAxg1ERERSdSLkYiIiIiI9FACQUREREREejR1FSMz6wCuAnYn6i+fCjhwAzCRqM98vLuvMrMMuAw4ElgHnOLuD6blTAXOS4u90N3nDeFmiIiIiIg0jGYvQbgMuN3d/wHYA3gcOBe4w90nAXek7wBHEL2gTAJOJ/pex8y2JRpK7keM0Do7N1CTiIiIiMiI0rQJBDMbCxxEauDo7i+7+2pgClAsAZgHHJM+TwHmu3vB3e8BOsxsAvAOYLG7r3T3VcBi4PAh3BQRERERkYbRzFWMdgb+BHzXzPYAHgA+AozP9an+HDA+fd4BeDY3/9IUVim8omYZkVVxaIw4tLaOIsvqP3prvfeDiIiINIdmTiC0Am8CPuzu95rZZWyoTgSAuxfMbMDHy2yWEVkVh/rHIcugq2srWltbWFPn0VsHaj9oRFYREZHhrWmrGBE5/Uvd/d70/SYiwfB8qjpEel+Rfl8G7JSbf8cUVilcRERERGTEadoEgrs/BzxrZpaCDiVGXF0ATE1hU4Fb0+cFwMlmlpnZ/sCaVBVpEXCYmW2TGicflsJEREREREacZq5iBPBh4Boz2xJ4CphGJHpuNLPTgGeA49O0C4kuTp8gujmdBuDuK83sAuD+NN3n3H3l0G2CiIiIiEjjaOoEgrs/BOxT5qdDy0xbAGZUWM5cYO7Axk5EREREpPk0dQJBREREBp6ZzQWOAla4++4p7HzgQ0QPggCfdveF6bdZwGlAN3CWuy9K4YcTYxa1AFe5+8VDuR0i0j9KIIiIiEipq4ErgPkl4Ze6+5fzAWa2K3ACsBvwauCnZrZL+vnrwNuJjkXuN7MF7v7YYEZcRDZf0zZSFhERkcHh7r8Aqm2PNwW43t1fcvenibZ++6bXE+7+lLu/DFyfphWRBqcEgoiIiFRrppk9bGZzU89/MIADkYpIY1AVIxEREanGlcAFQCG9fwU4daBX0tKS9Tnq+3AfGX44bl9LyygiX3oUWZbR2rrh+4YXjB3b/Ns9HP4/JRBERKSpZVm8ZHC5+/PFz2b2HeBH6WtvA47WPBBpd3ehz1HfB2pk+EY13LYvy6C9fT0Qr9bWAl1dG75veEFn5zoKhbpFdUBs7v83blzbAMamf5RAEBGRppVl0D5zOowZA0okDCozm5AGGAV4N/BI+rwAuNbMLiEaKU8C7iP+kUlmtjORMDgBeN/QxlpE+kMJBBERaW6dnVAoQHv9c92GCzO7DpgMbG9mS4HZwGQz25OoYrQEmA7g7o+a2Y3AY0AXMMPdu9NyZgKLiG5O57r7o0O8KSLSD0ogiIiIyEbc/cQywXN6mf4i4KIy4QuBhQMYNREZAkogiMiQqTD40peAo4GXgSeBae6+2swmAo8Dnma/x93PSPPsTfTTvhXx8PGRNFq6iIiIbCZ1cyoiQ+lq4PCSsMXA7u7+RuC/gVm535509z3T64xc+JXEiK6T0qt0mSIiItJPSiCIyJApN/iSu//E3bvS13uInk4qMrMJQLu735NKDeYDxwxGfEVEREYiVTESkUZyKnBD7vvOZvY7oBM4z91/SQy0tDQ3jQZfEhERGUBKIIhIQzCzfyN6QLkmBS0H/t7dX0htDn5oZrv1d/kafCkMx21saR0FraOgJd57BmHKv9JvoIGYRET6ogSCiNSdmZ1CNF4+tNjY2N1fAl5Knx8wsyeBXYj+1PPVkDT4Ug2G2zZmGbR3rYeu9dAd762FNAhT/pV+A+hcM/IGYmqEgZdEpHk0RBsEMxtvZnPM7Mfp+65mdlq94yUig8/MDgc+BbzL3dflwseZWUv6/FqiMfJTaaCmTjPb38wy4GTg1jpEXUREZFhqiAQC0bPJImIERoieTD5at9iIyKBIgy/9Jj7a0pQRcAXQBiw2s4fM7Jtp8oOAh83sIeAm4Ax3LzZwPhO4CniC6Br1x0O5HSIiUp0si9dgTS+Do1GqGG3v7jea2SwAd+8ys+56R0pEBlYtgy+5+w+AH1T47bfA7gMYNRERGWBZBu3t04ExVc7RRlvbdAA6O7/V9FUBm1mjJBD+YmbbEcO3Y2b7A2v6msnMlgBrgW6gy933MbNtiV5QJhJDwR/v7qtSVYTLgCOBdcAp7v5gWs5U4Ly02Avdfd6AbZmIiIjIiNVJPN5V2w6mcxDjItVqlCpGHwcWAK8zs7uJfs0/XOW8B6dBlPZJ388F7nD3ScAd6TvAEWwYVOl0YqAlUoJiNrAfsC8w28y22fxNEhERERFpPg2RQEg5+W8F3gxMB3Zz94f7ubgpQLEEYB4bBlCaAsx394K73wN0pAGX3gEsdveV7r6KGNVVo7KKiIiIyIhU1ypGZnZshZ92MTPc/eY+FlEAfmJmBeBb7v5tYHzq5QTgOWB8+rwD8Gxu3uLgSpXCRURERERGnHq3QTg6vb+KKD24M30/GPg10FcC4Z/dfZmZvYroAeUP+R/dvZASDwOqWQZcUhwaIw6traPIsvoPzlTv/SAiIiLNoa4JBHefBmBmPwF2Leb8p6o/V1cx/7L0vsLMbiHaEDxvZhPcfXlazoo0+TJgp9zsxcGVlgGTS8Lv6m29zTLgkuJQ/zhkGXR1bUVrawtr6jw400DtBw24JCIiMrw1RBsEYKdctSCA54G/720GM9vazNqKn4HDgEeIxs5T02RT2TCA0gLgZDPLir0kpXUuAg4zs21S4+TDUpiIiIiIyIhT7ypGRXeY2SLguvT9vcBP+5hnPHCLmUFsx7XufruZ3Q/cmAZgegY4Pk2/kOji9Amim9NpAO6+0swuAO5P030uNxiTiIiIiMiI0hAJBHefmRosvyUFfdvdb+ljnqeAPcqEvwAcWia8AMyosKy5wNxa4y0iIs2nOEqrBmESESmvIRIIQLHHor4aJYuIiPRfWxttM9JIrVdopFYRkXIaIoGQ2gRcDrwB2BJoAf7i7u11jZiIiDSsLNtQGlCTTo3UKiLSm4ZIIABXACcA3wf2AU4GdqlrjEREpGFlGbTPnA5jxtQ7KiIiw06j9GKEuz8BtLh7t7t/F41mLCIivenshLVr6x0LEZFhp1FKENaZ2ZbAQ2b2RWA5DZR4EREREREZKRrlIfwkot3BTOAvxIBm/1LXGImIiIiIjEANUYLg7s+kj38FPlvPuIiIiIiIjGR1TSCY2e+Bip3MufsbhzA6IiIiIiIjXr1LEI5K78UBzL6X3j9ALwkHEREREREZHHVNIBSrFpnZ2919r9xP55jZg8C59YmZiIiIiMjI1CiNlDMzO7D4xczeTOPETURERERkxKh3FaOi04C5ZjYWyIBVwKn1jZKIDDQzm0tULVzh7runsG2BG4CJwBLgeHdfZWYZcBlwJLAOOMXdH0zzTAXOS4u90N3nDeV2iIiIDGcNkUvv7g+4+x7AHsAb3X3P4oOAiAwrV7PpIIjnAne4+yTgDjZULTwCmJRepwNXQk+CYjawH7AvMNvMthn0mIuIiIwQ9e7F6APu/v/M7OMl4QC4+yV1iZiIDAp3/4WZTSwJngJMTp/nAXcB56Tw+e5eAO4xsw4zm5CmXezuKwHMbDGR6LhusOMvIiIyEtS7itHW6b2tzG/qxUhkZBjv7svT5+eA8enzDsCzuemWprBK4SIiIjIA6t2L0bfSx5+6+9353/KNlkVkZHD3gpkNSuZAS0tGR8foPqYZ1ec0zW44bWNL6yjIv1riPcsyWiv81vMCxo5t3v0wnP5HEWk89S5BKLoceFMVYSIy/DxvZhPcfXmqQrQihS8DdspNt2MKW8aGKknF8Lv6Wkl3d4HVq9f1Ok1Hx+g+p2l2w2Ubswzau9ZD/tUd762FAl0Vfut5AZ1r1lFo0rLqWv/HcePKFdSLiJRX7zYIBwBvBsaVtENoB1rqEysRGWILgKnAxen91lz4TDO7nmiQvCYlIhYBn881TD4MmDXEcRYRERm26l2CsCUwJsUjn73RCRxXzQLMrAX4LbDM3Y8ys52B64HtgAeAk9z9ZTN7BTAf2Bt4AXivuy9Jy5hFdLXaDZzl7osGYNtEpISZXUfk/m9vZkuJ3oguBm40s9OAZ4Dj0+QLiS5OnyC6OZ0G4O4rzewC4P403eeKDZZFRERk89W7DcLPgZ+b2dXFUZX74SPA40SpA8AXgEvd/Xoz+ybx4H9lel/l7q83sxPSdO81s12BE4DdgFcDPzWzXdy9u/9bJiLluPuJFX46tMy0BWBGheXMBeYOYNREREQkqXcJQtErzOzbxEBJPXFy90N6m8nMdgTeCVwEfDwNrHQI8L40yTzgfCKBMCV9BrgJuCJNPwW43t1fAp42syeIvtV/MxAbJiIiIjLSZFm8pDk1SgLh+8A3gauIaj7V+irwKTZUT9oOWO3uXel7vvvDnq4R3b3LzNak6XcA7sktU10mioiIiPRTlkF7+3SiFrk0o0ZJIHS5+5W1zGBmRwEr3P0BM5s8ONEqr1m6S1QcGiMOra2jyLL6d6lY7/0gIiIjSSca0qp5NUoC4T/N7EzgFuClYmAfDQ8PBN5lZkcCryTaIFwGdJhZaypFKHaLCBu6TFxqZq3AWKKxcqWuFCtqlu4SFYf6xyHLoKtrK1pbW1hT5y4VB2o/qLtEEREZbFlG03ZDPBw0SgJhanr/ZC6sALy20gzuPovUtWEqQfiEu7/fzL5P9IB0PZt2mTiVaFtwHHBnGpRpAXCtmV1CNFKeBNw3QNslIiLSdMxsLlAsqd89hW0L3EC0F1wCHO/uq1J7vsuIXsfWAae4+4NpnqnAeWmxF7r7vKHcDmlWbbS3f4I1a76sREKdNEQCwd13HsDFnQNcb2YXAr8D5qTwOcD3UiPklUTPRbj7o2Z2I/AY0AXMUA9GIiIywl0NXEF0D150LnCHu19sZuem7+cARxCZa5OIMUuuBPZLCYrZwD5Ept8DZrbA3VcN2VZI0yoU1tY7CiNaQyQQAMxsd2BXoroQAO4+v/IcG7j7XaSRVN39KaIXotJp/ga8p8L8FxE9IYmIiIx47v4LM5tYEjyFDaOYzyPuu+ek8Pmpa+J7zKwjjYo+GVhcrC5sZouBw4HrBjv+IrJ5GiKBYGaziQvJrsTgSEcAv2LjnAsRERGpn/Huvjx9fg4Ynz739BKYFHsDrBQuIg2uIRIIRJuAPYDfufs0MxsP/L86x0lERIaxYh/tquNcu9SGb1D2XLP0FDiYhsP2tbSMAsq/siyjtbXy7/HK6t77X38Nh/+vURIIf3X39WbWZWbtwAo27llIRERk4LS10TZjOgCdV3xLiYTqPG9mE9x9eapCtCKFV+oNcBkbqiQVw+/qayXN0lPgYGr27YtxENYD5V+trQW6uir/Hq+Mzs769v7XX5v7/zVCb4Gj6h2B5Ldm1gF8B3gAeBCNZCwiIoOpszNeUq1ib4CwaS+BJ5tZZmb7A2tSVaRFwGFmto2ZbQMclsJEpME1RAmCu5+ZPn7TzG4H2t394XrGSUREZKQys+uI3P/tzWwp0RvRxcCNZnYa8AxwfJp8IdHF6RNEN6fTIMYyMrMLgPvTdJ/rY3wjEWkQDZFAMLODyoW5+y/qER8REZGRzN1PrPDToWWmLQAzKixnLjB3AKMmIkOgIRIIbDxA2iuJbkofAA6pT3REREREREamhkgguPvR+e9mthPw1TpFR0RERERkxGqURsqllgJvqHckRERERERGmoYoQTCzy4lh2CESLXsRPRmJiIiIiMgQaogEAvAHoCV9fgG4zt3vrmN8RESkQWXZhkHORERk4NU1gWBmWwBfAk4GlqTg8cDlwN1mtqe7P1Sn6ImISIPJMmifOR3GjKl3VEREhq16lyB8BRgNvMbd1wKkkZS/bGZXAocDO9cxfiIi0mg6O2nK4VVFRJpEvRMIRwKTUh/KALh7p5n9K/Bn4Ii6xUxEhoyZGXBDLui1wGeADuBDwJ9S+KfdfWGaZxZwGtANnOXuGqFVRERkANQ7gbA+nzgocvduM/uTu99Tj0iJyNBydwf2BDCzFmAZcAsxIuul7v7l/PRmtitwArAb8Grgp2a2i7t3D2nERUREhqF6d3P6mJmdXBpoZh8AHq9DfESk/g4FnnT3Z3qZZgpwvbu/5O5PA08QAyyKiIjIZqp3CcIM4GYzO5UYORlgH2Ar4N11i5WI1NMJwHW57zNTRsJvgbPdfRWwA5AvYVyawkRERGQz1TWB4O7LgP3M7BCiqgDAQne/o47REpE6MbMtgXcBs1LQlcAFxDgpFxAdG5zan2W3tGR0dIzuY5pRfU7T7IbDNra0joJyr5Z4z7KM1gq/bfICxo5tvv0xHP5HEWlc9S5BAMDd7wTurHc8RKTujgAedPfnAYrvAGb2HeBH6esyYKfcfDumsIq6uwusXr2u15V3dIzuc5pm1+zbmGXQ3rUeyr264721UKCrwm+bvIDONeuarlOkWv/HcePaBjE2IhtonJLhoSESCP1hZq8EfgG8gtiOm9x9tpntDFwPbEdUWzrJ3V82s1cA84G9icHY3uvuS9Ky1BuKSGM4kVz1IjOb4O7L09d3A4+kzwuAa83sEqKR8iTgvqGMqIiIbCzLoL19OqBxSppdvRspb46XgEPcfQ+i95PDzWx/4AtEryevB1YRD/6k91Up/NI0XWlvKIcD30i9qIjIEDKzrYG3Azfngr9oZr83s4eBg4GPAbj7o8CNwGPA7cAM9WAkItIIOoG19Y6EbKamLUFI3aO+mL5ukV4F4BDgfSl8HnA+UY95SvoMcBNwhZll5HpDAZ42s2JvKL8Z/K0QkSJ3/wtR8pcPO6mX6S8CLhrseImIiIw0TZtAgJ7+0h8AXg98HXgSWO3uXWmSfM8mOwDPArh7l5mtIR5Gau4NpVkaOyoOjRGH1tZRZFn9G0LWez+IiIhIc2jqBEKqUrCnmXUQgyr9w1Cst1kaOyoO9Y9DlkFX11a0trawps4NIQdqP6ixo4iIyPDWzG0Qerj7auBnwAFAh5kVEz75nk16ej1Jv48lGivX3BuKiIiIiMhw1bQJBDMbl0oOMLOtiMaNjxMJhePSZFOBW9PnBek76fc7UzuGBcAJZvaK1AOSekMREWlQ6j5RRGTwNW0CAZgA/Cz1bnI/sNjdfwScA3w8NTbeDpiTpp8DbJfCPw6cC+oNRUSkWWQZtF84u97REJEhojEV6qdp2yC4+8PAXmXCnyJ6ISoN/xvwngrLUm8oIiJNoPDii31PJCLDwBja2qYD0Nn5raYbzLDZNW0CQURERESGs856R2DEauYqRiIiIiIiMsCUQBARERERkR5KIIiIiIiISA8lEEREREREpIcSCCIiIiIi0kMJBBERERER6aEEgoiIiIiI9FACQUREREREeiiBICIiIiIiPZRAEBERERGRHkogiIhIw8uyeIlI49I5Ony01jsCIiIivckyaJ85HcaMAT2AiDSkLIP29tkUCvWOiQwElSCIiEjj6+yEtWvrHQsR6UWh8GK9oyADRCUIItIQzGwJsBboBrrcfR8z2xa4AZgILAGOd/dVZpYBlwFHAuuAU9z9wTpEW0REZNhRCYKINJKD3X1Pd98nfT8XuMPdJwF3pO8ARwCT0ut04Mohj6kMG6o3LSKyMSUQRKSRTQHmpc/zgGNy4fPdveDu9wAdZjahHhGUJtfWRvusTyiRICKSowSCiDSKAvATM3vAzE5PYePdfXn6/BwwPn3eAXg2N+/SFCZSs4LaNoiIbKRp2yCY2U7AfOKBoQB8290v60+dZTObCpyXFn2hu89DRIbaP7v7MjN7FbDYzP6Q/9HdC2bW7/4xWloyOjpG9zHNqD6naXbNuo0traOgdRS0pPdyr/RblmW0Vvit7CvLGDu2ufZJs/6PItIcmjaBAHQBZ7v7g2bWBjxgZouBU4g6yxeb2blEneVz2LjO8n5EneX9UoJiNrAPkdB4wMwWuPuqId8ikRHM3Zel9xVmdguwL/C8mU1w9+WpCtGKNPkyYKfc7DumsIq6uwusXr2u1zh0dIzuc5pm14zbmGXQ3rUeutZDd3ov90q/tRYKdFX4rexrVEbnmnVN1T1jrf/juHFtgxgbERlumraKkbsvL5YAuPta4HGiikGtdZbfASx295UpUbAYOHwIN0VkxDOzrVNCHzPbGjgMeARYAExNk00Fbk2fFwAnm1lmZvsDa3JVkURERGQzNHMJQg8zmwjsBdxL7XWWa67L3CxVFRSHxohDa+sosoy6V2Go937ow3jgFjODuC5d6+63m9n9wI1mdhrwDHB8mn4hUV3wCaLK4LShj7LIyKQuiUWGv6ZPIJjZGOAHwEfdvTM9YACbX2e5kmapqqA41D8OWQZdXVvR2trCmjpXYRio/TAYVRXc/SlgjzLhLwCHlgkvADMGPCIiUq2D3f3Pue/FLomrqt471JEVkdo0bRUjADPbgkgcXOPuN6fg54vdHVZZZ7nmuswiIiKyEXVJLDKMNG0JQiq2nAM87u6X5H4q1lm+mE3rLM80s+uJ3Is1qeHjIuDzZrZNmu4wYNZQbIOIiPQuyzSQWQMqdklcAL7l7t+m9uq9FdsMNUs13sHUrNvX0jKKRKKpPAAAIABJREFUyHvu/dXT01gV00L9q+jWqln/v7ymTSAABwInAb83s4dS2KeJhEHVdZbdfaWZXQDcn6b7nLuvHJpNEBGRSrIM2mdOhzFj6h0V2digdkncLNV4B1Mzbl+WQXv7eqDvV2tr6mmsimkBOjuHdy9jpRqh17GmTSC4+6+ASvlKNdVZdve5wNyBi52IiAyIzk6a6slgBBjsLolFpP6aug2CiIiIDB11SSwyMjRtCYKIiIgMOXVJLJtQW6HhRwkEERERqYq6JJZS0fZgOqC2QsOJqhiJiIiIyGboJMbOGxwqoRh6SiCIiIiISINqo61tOu3t05VIGEKqYiQiIiIiDayz3hEYcVSCICIiDUdVCkRE6kclCCIi0lA0QJqISH0pgSAiIg0lyxjyAdKKpRUak01ERFWMRESkgWQZtF84e2hXOmYMbTOm0z5TjSBFREAlCCIi0mAKL7449CvtVCPIZpNlKvERGSwqQRAREZGmkWXQ0nKyur1sAOpMYPhSCYKIiIg0mbXA+npHYkTTCMrDmxIIInWgBpEiItL8OgHdyIYjVTESGWJZBjNnbsXMmVupaFZEREQajkoQROpA7SFFRESkUSmBICJ1Z2Y7AfOB8UR59bfd/TIzO///s3f38XLW9Z3/X9eZIcjJOcnhJqYxsIWu8dMCjwUrBSptF4lgYGmDuwqhKwSkhdZE6qo/IWg3AknELULzEERQUkKrBKRQsjYNxgil+pMbSakQ8LONECTZQNQk5yQ5GDKT2T+u75xMJjPnzDlnbq5r5v18POYxM9/rZj7XzFwz1+e6vjfAnwI/D7Ne5+6rwjILgCuAPHC1uz/a9MBFRETakBIEkSZRdaJh5YBPufs6M+sFnjWzNWHare5+c+nMZnY8MAc4AXgH8F0ze5e755satYiISBtKbYJgZsuA84Gt7n5iKDsCuB84FtgIXOju280sApYC5wGDwGXuvi4sMxf4XFjtIndf3sztkM7Q2wvz5h0GwO23v9niaJLH3bcAW8LjnWb2EjB9mEVmAyvcfQ/wipltAE4FftjwYKVh1GWiiEgypLmR8j3ArLKya4G17j4DWBueA5wLzAi3K4E7YCihWAicRnxwsdDMDm945NKRBgbU9qAWZnYs8G7gqVA038x+bGbLSvbP6cBrJYttYviEQhIuimDS/KvoveZTrQ5FRBJKJxGaJ7VXENz9iXAgUWo2cGZ4vBx4HLgmlN/r7gXgSTPrM7NpYd417r4NIFRpmAXc1+j4pXPpx606M+sB/h74hLsPmNkdwI3E7RJuBL4EfHQs685kIvr6ukeYp2vEedIuyduYGdwFmSi+5JbtqnzLVCkvmRZFEdkxLAcweXIy35tySf4cRRqjl97eqwAYGLhT3YQ3WGoThCqmhqoKAK8TN3iE6mcbdRZSmqq3F2688bBWh5FIZnYIcXLwDXd/CMDd3yiZ/jXg2+HpZuCYksWPDmVV5fMFduwYHDaGvr7uEedJuyRtY/FsYO+8q6Cnh1xuH+T2QT7cV7rVMC1bKOxf12jWCQz0D6biwGO0n+OUKb0NjEakWXQZvlnaLUEY4u4FM2vIz3xazkQqhmTEkM12EUWQzWbIZuHNNyEb9rxmnq1s9fswnNBO6G7gJXe/paR8WknS/0HghfB4JfBNM7uFuJHyDODpJoYs41SsUkRPT1z3Lg1H5SICqKpPJ2i3BOGN4gFFqEK0NZRXO9u4mf1Vkorlj4/0Imk5E6kYWhdDcTC0nh7I5fIUChlyuTy5HOTzkMvF8/X3v9m046J6vQ8NOhN5BnAJ8LyZPRfKrgMuNrOTiasYbQSuAnD39Wb2APAicQ9I89SDUbpEEUoMRFIoimDSpKuAnlaHIg3UbgnCSmAucFO4f6SkfL6ZrSBukNwfkohHgSUlDR/PARY0OWZpUzr2qZ27fx+odD5q1TDLLAYWNywoaYjimcdJixai3UMkrQZAe3BbS22CYGb3EZ/9P8rMNhH3RnQT8ICZXQG8ClwYZl9F3MXpBuJuTi8HcPdtZnYj8EyY74Zig2UREamf8vYGBVVPEBFJrNQmCO5+cZVJMyvMWwDmVVnPMmBZHUMTUd1MEeL9oFCo0t5gkhrNiqSR/t86Q5rHQRBJpCiCRYvUU1HaRBFkrp6vP786iSKYfN2n97+fAwOwc2dLY6qFGl+KVBe3P1jY6jCkCZQgiDTArl2tjkDGJAUHsGlSSNv72dtL77yrmDT/KiUJIlUUCvqD6wSprWIkIiLJVHoWPnUH2hruXERECYJIPY22ekJxXvV2JO3igPYGPT1DjZJFROql2L5JGkcJgkidlI59UEuS0NsL8+bFbRVuu6154yGI1FPpH/VQglzaEFn9/YpIXfUyadKn6e+/WT8tDaQEQaSOho6LJtU+v0ialF71KjZEHvjCzQC6WiDSxpLUgL9QSFn7phRSgiAiIiM6YBwDYOC2OwEoFAr7EwNdLRBpSxo9ufMoQRAZh9KzKeM5s6K2CJJkB41jQNn3XYmBSAcojp6sMUw6gRIEkTHq6orbEPT0xN2ajrVmhdoiSCqUJgGhO9C4wU1rwxIRkfpTgiAyBsXB0IrHTDt3ju8EqtoiSOpoRGSRtqYr251NCYI0TFIaMzWKBkOTdqUDA70H0tn2tzmAnTvvbHE0lWkfbSyNpCwNEUVw3XWHtTqMuio20kxSTw4i41X+fS62NygdTbjjvu8aUVk61IG/B3Gbg97eq+jt/VQLo6qkh97eq5g0Sftoo+gKgjTMzjbqhax0jINie4NG/Chp8Bdplmq9Eg2NY1Ayz6RFC+m4r6Xq/UkHGfo96I1/D3btKr1qUGycnDTaRxtJCYLIMEoP2MvbG9Q61kGtenthwYLDWLJEDZWlvsovxVfqlairC3o+VjKOQUlD5ILO0Im0rQO7MB0AeuntXaj/oQ6nKkbSsSpVFSqtQtTVFVeT6upqXhWLdrrqIslQWmWoq2t/GQMD+79wvb303rjwwDI4+HkHUvUFSbPhvr8HVpkdAPbv64VCehrZqdpvY+gKgnSM8nrWxa5Fb7/9zaFRYcu7LS0ta0WcoCpHUgcDA9Dby6RFC8lsfYPewyYeNEtBre4P1tvLpAWfpn/JzdoPpSWGa4g70rT4ysCnGRg4+PsbT1tIofA66R78rHeoWtTAwJ3aT+tICYJ0hEptCMIxE4sWHcaWLQcOBFtajaiZY0D19ByYpIDGRpDhjaYnj8KuXfGXO7evsUG1kUKHX0FpF2M58TLWNmEjLVepyl+luLq6OODgt3Se8l6GissdOK2HQqG4jh5g1wH38TJJbV8wGmqL0AhKEKSpGt0tWbXLjFF08MF/0a5dyRoItjROUFdu7ajSZ1rpu1vtMy/tXajYyHjn7fFBQvEAYbj1yuhoH0yuWs6wQ2kd+/jMS/lBdfm6oggmTz747PtIB/7Fs/b9/TcfsC8Wlys96C92H1o8gI+iiIGBmwHIZC6lt3cixYPfri7o6SnvdjRuL7D/SkBpIlE66nHx8c6ye41hItUpQQjMbBawFMgAX3f3m1ocUtsoPZipx4jBwyUB5VWEdu2CyZO76O5OZ5erpaMsF6tClerkA5ak7bPVvpflSUClg/qhspIvb9QVMfCFKlUDFi2ksOX1Ay6FFde56yt37m9sPJ4hviXW03NAT0+dvM+NR2P2194DDrbL97UDe+QpPUjurXhQXn7gXigUys6+H/w6B79eD4XCroN6BSquMz6YLzYELm0YXKBQKC3bCRSv9BUbDZcvR4hzF8VEopNPCCiRry8lCICZZYDbgbOBTcAzZrbS3V9sbWTpVPxh7OmByy7r4rDDDjugWk9xnrGuu1IS0NMTH0yXXyXYuRMyGdiX4hoVlapCdXr1o2bss6P5jlY6wC9+SBWTgJI2AQcc6Jd8eQuTeiuvs9irUPllr2KicONCCvUa4ltiAwcefOktHZ3G7q/lZ9FLq9IM1yNPpYPySgfg1RKLniqvV+Dgg//ekuTh4BgqxVXuwEbD1aoFHZw8dI4Dk8U0/+cnhRKE2KnABnd/GcDMVgCzgXH9eKWpT/ta60zWsp7iAXwUherOuQOPUyod7JYf6A83rVISUF6toh2VVoUqr35UKi3fuXFqyD4LZWf5S8/o9/bsP5gv+2JGvT0HH5Tv3Fk9CQgKI9Vvq/Zln1S9aoAaGzdIyVWa0upcUpOG7a9F+8+il1ahKZ02nPID7tLqOZXnPbD+/oGvN/p11lM7tCkYq2KyWLlhdpH229ooQYhNB14reb4JOG2sK4siuPrqLvL5w/jCF1p7hreWg+YogsWLu/nsZwerXjpdsOAwJk6E3bs54H7ixIitWwsHlBX19MDgIBx22P4rCsX78Zg06cB1Fe97eqpP6+4e23L1nJbP13+dt97afcD7Dwz7navl+5CSH8+67rNDfu3XmLTg0zBx4uj/Yqt9cMPME/X0UKiyXKOmMdgLh01s2uu1bFq+UP91hoRw0oJPA1SsAtZM1Rq3JlAD9tdeYCIQsf+M/iTis+fRAffpnNbV8ds31teBiUya9Omw/t1l9xEDA59vyv5SS7XTJFOCMAaHHJL5xZQpva8ON88dd0D89ra2EdBRR9X2+rfcAsPFetdd44kiCV+zToqh+udY6/dhBL9ej5U0Wy37LTff3BGDw0xodQBN0IxtPLIJrzGcUe7Pqdlva9pX+QYT2vyLrO1rjCObtOOO8/+25ftrEo6akmAzcEzJ86NDWTVTGhuOiIxgtPssaL8VaRX9x4qkjBKE2DPADDM7jvhHaw7wx60NSUSGoX1WJD20v4qkTCdcTR+Ru+eA+cCjwEvAA+6+vrVRiUg12mdF0kP7q0j6RIW0tJYQEREREZGG0xUEEREREREZogRBRERERESGqJHyOJjZh4HPA78FnOruPyqZtgC4AsgDV7v7oxWWPw5YQdxb3rPAJe7+1jjiuR+w8LQP2OHuJ1eYbyPxyC55IOfup4z1NSus+/PAnwI/D0XXufuqCvPNApYCGeDr7n5THWP4K+APgbeAnwKXu/uOCvNtpM7vw0jbZWaHAvcC7wF+CVzk7hvH+7ol6z8mrH8q8Wg5d7n70rJ5zgQeAV4JRQ+5+w31iiFtxrsfp1Gt+2kaNfK3JSka+RuedJ20v7brftru+2i77J9KEMbnBeC/AneWFprZ8cS9NJwAvAP4rpm9y93zZct/EbjV3VeY2VeJf9juGGsw7n5RSQxfAvqHmf197v6Lsb7WCG5195urTTSzDHA7cDbxgDnPmNlKd6/XqJprgAXunjOzLwILgGuqzFu396HG7boC2O7u7zSzOcTfgYsOXtuY5YBPufs6M+sFnjWzNRXe239x9/Pr+LppNt79OK2G3U/TqAm/LUnSyN/wJOu0/bWt9tMO2kdTv3+qitE4uPtL7u4VJs0GVrj7Hnd/BdhAPNT8EDOLgLOAB0PRcuCCesQV1n0hcF891tcApwIb3P3lcMVkBfF7Vhfu/p3QawbAk8R9bjdDLds1m/izhviznxk+r7pw9y3uvi483kncY8j0eq2/HY1nP5bEaehvi7Se9tfU0z6aEkoQGqPSsPLlB2lHElcByg0zz1j9PvCGu/97lekF4Dtm9qyZXVmn1yw138x+bGbLzOzwCtNreX/q5aPAP1WZVu/3oZbtGponfPb9NGhAVjM7Fng38FSFyb9rZv9mZv9kZic04vXbQDO/p60w0n6aRu3+mRU1+jc8jdr1s2+3/bRdP6dSbbF/qorRCMzsu8CvVZj0WXd/JKHxXMzwVw9+z903m9nbgTVm9hN3f6IeMRBXkbqReAe5EfgS8UF6XdXyPpjZZ4mr3HyjymrG9T4kmZn1AH8PfMLdB8omrwN+3d13mdl5wD8AM5odYzMlbT9uhiTsp9IwbfvbBZ21v2o/bUttsX8qQRiBu79/DIvVMqz8L4E+M8uGM8kjDT1fUzxmliWun/meYdaxOdxvNbOHiS/51fzlrfU9MbOvAd+uMKmW92dcMZjZZcD5wEx3rzjYx3jfhwpq2a7iPJvCZzWZ+LtQN2Z2CHFy8A13f6h8emnC4O6rzOwrZnZU2utLDqeB+3Fi1WE/TaNUf2a1asBvV6J00v7agftpKj+n0WiX/VNVjBpjJTDHzA4NPRXNAJ4unSEctD4GfCgUzSXuWWa83g/8xN03VZpoZhND41XMbCJwDnGjr7ows2klTz9YZd3PADPM7Dgzm0DcsGxlHWOYBXwG+CN3H6wyTyPeh1q2ayXxZw3xZ/+9agnMWIT2DHcDL7n7LVXm+bViuwczO5X4d6CuSUqbGHE/Tqsa99M0auhvSxI0+jc8xdpuf23T/bSt99F22j91BWEczOyDwJeBKcA/mtlz7v4Bd19vZg8ALxJXcZlX7EnBzFYBf+Lu/5e4Z50VZrYI+FfiA7vxmkNZ9SIzewdxV2LnEXd/+bCZQfz5f9PdV9fhdYv+l5mdTHxJdCNwVXkMoXeh+cCjxN2cLXP39XWM4TbgUOJLewBPuvufNfp9qLZdZnYD8CN3X0n8Gf+tmW0AthF/XvV0BnAJ8LyZPRfKrgP+Q4jxq8SJyZ+bWQ54E5hTzyQlbcayH7eBivtp2jXhtyUJGv0bnmgdtr+23X7aAfto2+yfUaHQsccFIiIiIiJSRlWMRERERERkiBIEEREREREZogRBRERERESGKEEQEREREZEhShBERERERGSIujmVRDOztxEPMHIo8ff1QXdfGKb9C9AbZn078LS7XxD6+F8KnAcMApe5+7qmBy/SwcxsI7ATyAM5dz8llB8B3A8cS9x144Xuvt3MJgN/R9wlbxa42d3/pumBi3SwsfzntiRQaThdQZCk2wOc5e4nAScDs8zsdAB3/313P9ndTwZ+CBRHDT6XeJCcGcCVxMPVi0jzvS/so6eUlF0LrHX3GcDa8BxgHvBi2NfPBL4UBlISkeYZy3+utCFdQZCWMrO/BD4C/Bx4DXjW3W8uTg8DeO0KTw8Jt0LZOiYBZwGXh6LZwL1h2SfNrM/Mprn7loZujEiHGGm/HcFs4gQAYDnwOPGgkQWgN1wB7CEeSDBXv6hFpEH/udKGlCBIy5jZ7wD/DTiJ+EdoHfBshfkyofydwO3u/lTZLBcQn5EcCM+nE//wFW0KZUoQRMap1v2W+KDiO2ZWAO5097tC+dSSZP114pFHIR4BfSXwf4mrMVzk7vsasxUinaeB/7nShlTFSFrpDOARd/+Vu+8E/nelmdw9Hy5pHg2camYnls1yMXBfY0MVkaCm/Rb4PXf/beIqf/PM7A/KZwhnK4tnJz8APAe8g7hqw23hTKWI1If+c6VmShAkaQ4zs+fC7c9KJ7j7DuAxYFaxzMyOAk4F/rFk1s3AMSXPjw5lItIYB+237r453G8FHibeTwHeMLNpAOF+ayi/HHjI3QvuvgF4BfjNZm6ESAeqx3+utCFVMZJW+gFwp5l9gfi7eD5wVzhzAYCZTQH2uvsOMzsMOBv4Ysk6PgR8291/VVK2EphvZiuA04B+tT8QqZta9tuJQJe77wyPzwFuCJNXAnOBm8L9I6H8Z8BM4F/MbCpgwMtN2B6RTtGo/1xpQ7qCIC3j7s8QHyz8GPgn4Hmgv2y2acBjZvZj4Blgjbt/u2T6HA6+1LmK+MBiA/A14GP1j16kM9W4304Fvm9m/wY8Dfyju68O024CzjazfwfeH54D3Ai818yeJ+7d6Bp3/0VDN0akgzTwP1faUFQoFEaeS6RBzKzH3XeZWTdx38tXaswCkWTTfiuSTtp3pVaqYiStdpeZHQ+8DViuHyqRVNB+K5JO2nelJrqCICIiIiIiQ9QGQUREREREhihBEBERERGRIUoQRERERERkiBIEEREREREZogRBRERERESGKEEQEREREZEhShBERERERGSIEgQRERERERmiBEFERERERIYoQRARERERkSFKEEREREREZEi21QGk0b59+wr5fKHVYZDJRCQhjlJJjAmSGVcSY4KR4zrkkMwvgCnNi6g+6rnfJvWzqwdtWzq10347nn01KZ9xEuJIQgyKY2xxJGF/VYIwBvl8gR07BlsdBn193YmIo1QSY4JkxpXEmGDkuKZM6X21ieHUTT3326R+dvWgbUundtpvx7OvJuUzTkIcSYhBcYwtjiTsr6piJCIiIiIiQ5QgiIiIiIjIECUIIiIiIiIyRAmCiIiIiIgMSXUjZTP7H8CfAAXgeeByYBqwAjgSeBa4xN3fMrNDgXuB9wC/BC5y941hPQuAK4A8cLW7P9rkTRERERERSYTUXkEws+nA1cAp7n4ikAHmAF8EbnX3dwLbiQ/8CffbQ/mtYT7M7Piw3AnALOArZpZp5raIiIiIiCRFahOEIAscZmZZoBvYApwFPBimLwcuCI9nh+eE6TPNLArlK9x9j7u/AmwATm1S/CIiIiIiiZLaKkbuvtnMbgZ+BrwJfIe4StEOd8+F2TYB08Pj6cBrYdmcmfUTV0OaDjxZsurSZSrKZCL6+rrrtSljlsl0JSKOUkmMCZIZVxJjguTGJSIiIs2R2gTBzA4nPvt/HLAD+BZxFaGGS8JAaVEEkycnY9CPUkkZiKRcEuNKYkxQ04BLTYxGGi2K4vtC6wcYFUkl7UPSjtJcxej9wCvu/nN33ws8BJwB9IUqRwBHA5vD483AMQBh+mTixspD5RWWSaQogvlrr+KylZcO/TCJiIxWFMHa+atZO381XWn+NxBpkSiC9UuuZ/2S6+nqQv/J0jbS/JfwM+B0M+sObQlmAi8CjwEfCvPMBR4Jj1eG54Tp33P3QiifY2aHmtlxwAzg6SZtw5gN7Blg556drQ5DRFJuz8AeKBT4/oLHdHAjMgZ7d+8G4IXFcaKg/UjaQWoTBHd/irix8TriLk67gLuAa4BPmtkG4jYGd4dF7gaODOWfBK4N61kPPECcXKwG5rl7vombIiLScnt27ml1CCKptnf37qFkQSTtUtsGAcDdFwILy4pfpkIvRO7+K+DDVdazGFhc9wBFRERERFImtVcQRERERESk/pQgiIiIiIjIECUIIiIiIiIyRAmCiIiIiIgMUYIgIiIiIiJDlCCIiIiIiMiQVHdzKiIiIvVnZsuA84Gt7n5iSfnHgXlAHvhHd/9MKF8AXBHKr3b3R0P5LGApkAG+7u43NXVDRGRMdAVBREREyt0DzCotMLP3AbOBk9z9BODmUH48MAc4ISzzFTPLmFkGuB04FzgeuDjMKyIJpwRBREREDuDuTwDbyor/HLjJ3feEebaG8tnACnff4+6vABuIByw9Fdjg7i+7+1vAijCviCScEgQRERGpxbuA3zezp8zsn83sd0L5dOC1kvk2hbJq5SKScGqDICJNY2bHAPcCU4ECcJe7LzWzI4D7gWOBjcCF7r7dzCLi+svnAYPAZe6+LqxrLvC5sOpF7r68mdsi0oGywBHA6cDvAA+Y2W/U+0UymYi+vu4xLts15mXHKpvpIpPpopCJz7lOntzdkjjKJSEGxZHcOEaiBEFEmikHfMrd15lZL/Csma0BLgPWuvtNZnYtcC1wDXHd5RnhdhpwB3BaSCgWAqcQJxrPmtlKd9/e9C0S6RybgIfcvQA8bWb7gKOAzcAxJfMdHcoYpryqfL7Ajh2DYwqwr697zMuORhTB+iXXk+3uJpffR5TfRy6/D4D+/kEmT25OHMNp1nuhOOofx5QpvU2KpjpVMRKRpnH3LcUrAO6+E3iJuMrBbKB4BWA5cEF4PBu4190L7v4k0Gdm04APAGvcfVtICtZQ1qBSROruH4D3AZjZu4AJwC+AlcAcMzvUzI4jTuifBp4BZpjZcWY2gbgh88qWRN4Ae3fvJjfY+gNOkUbQFQQRaQkzOxZ4N/AUMNXdt4RJrxNXQQLVbRZpCTO7DzgTOMrMNhFfsVsGLDOzF4C3gLnhasJ6M3sAeJH4KuE8d8+H9cwHHiXu5nSZu69v+sY0WRS1OgKR8VOCICJNZ2Y9wN8Dn3D3ATMbmubuBTMr1Ps1x1Ov+eB1paMOaS2y2QyZbIYoihJTd7pRtG21c/eLq0z6SJX5FwOLK5SvAlbVLbCEO2TiRHzpl/idv/zLVociMi5KEESkqczsEOLk4Bvu/lAofsPMprn7llCFqNh9YrW6zZuJz26Wlj8+3OuOp15zuaTUZR2vKIJcLk8mlyfqihJTd7pR2uVzq2SkbUtCneZOsXf37laHIDJuaoMgIk0TeiW6G3jJ3W8pmbQSmBsezwUeKSm/1MwiMzsd6A9VkR4FzjGzw83scOCcUCYiIiLjpCsIItJMZwCXAM+b2XOh7DrgJuIuE68AXgUuDNNWEXdxuoG4m9PLAdx9m5ndSNwIEuAGdy8f1ElERETGQAmCiDSNu38fqNaEb2aF+QvAvCrrWkbcaFJERETqKLUJgsWtGu8vKfoN4H8SD8KkAZdERERERMYgtW0QPHayu58MvIf4oP9h4gGW1rr7DGBteA4HDrh0JfGAS5QMuHQacCqwMNRpFhFpW1Gk7hhFRKSy1CYIZWYCP3X3V9GASyIiw4oiWDt/NU9c872q9b1EZHyUgEuapbaKUZk5wH3hccMHXKpnf+pjlc12DfVbniRJ7Wc8iXElMSZIblxSX3sG9kCh7sNNiHS8bHc3T3/2OnK5PCdct1C7maRS6hOEMHz7HwELyqc1asClevanPhZx3+X7yGa76O8fTNSPT1L7GU9iXEmMCdSfuojIeO3dtYtcfl+rwxAZs3aoYnQusM7d3wjP3whVhxjFgEuVykVEOoqqRIiICLRHgnAx+6sXgQZcEhEZtQk9E1g7bzUrL/sHJQoiIh0u1QmCmU0EzgYeKim+CTjbzP4deH94DvGASy8TD7j0NeBjEA+4BBQHXHoGDbgkIh1qz8Ae9ux8q9VhiIhIi6W6DYK77waOLCv7JRpwSURERERkTFJ9BUFEREREROpLCYKIiIiIiAxRgiAiIiIyCmo7S0DvAAAgAElEQVTIL+1OCYKIiIhIjaIIfnrXV1odhkhDpbqRsoiIiNSfmS0Dzge2uvuJZdM+BdwMTHH3X5hZBCwFzgMGgcvcfV2Ydy7wubDoIndf3qxtaKS9g8kb5FKknnQFQURERMrdA8wqLzSzY4jHC/pZSfG5wIxwuxK4I8x7BLAQOA04FVgYxhsSkYRTgiAiIiIHcPcngEpjAt0KfAYolJTNBu5194K7Pwn0mdk04APAGnff5u7bgTVUSDpEJHmUIIiIiMiIzGw2sNnd/61s0nTgtZLnm0JZtXIRSTi1QRAREZFhmVk3cB1x9aKGymQi+vq6x7hs15iXHY1spotspotMpotC2X0200UuiueZPLnxsVTTrPdCcaQzjpEoQRAREZGR/EfgOODfzAzgaGCdmZ0KbAaOKZn36FC2GTizrPzxkV4ony+wY8fYGgH39XWPedlaRRHk8vvI5fcRVbiP8vsoFOJ5+vsHKRRGXmcjNOO9UByNiWPKlN4mRVOdEgQRkQ4SRerDXUbP3Z8H3l58bmYbgVNCL0YrgflmtoK4QXK/u28xs0eBJSUNk88BFjQ3chEZCyUIIiIdIopg7fzVTOiZgHIEGY6Z3Ud89v8oM9sELHT3u6vMvoq4i9MNxN2cXg7g7tvM7EbgmTDfDe5eqeGziCSMEgQRkQ6yZ2APLavzIKnh7hePMP3YkscFYF6V+ZYBy+oanIg0nHoxEhERERGRIUoQRERERERkiBIEEREREREZogRBRERERESGKEEQEREREZEhqe7FyMz6gK8DJwIF4KOAA/cDxwIbgQvdfbuZRcBS4q7YBoHL3H1dWM9c4HNhtYvcfXkTN0NEREREJDHSfgVhKbDa3X8TOAl4CbgWWOvuM4C14TnAucCMcLsSuAPAzI4AFhIP7nIqsLBkUBcRERERkY6S2gTBzCYDfwDcDeDub7n7DmA2ULwCsBy4IDyeDdzr7gV3fxLoM7NpwAeANe6+zd23A2uAWU3cFBERERGRxEhzFaPjgJ8Df2NmJwHPAn8BTHX3LWGe14Gp4fF04LWS5TeFsmrlIiIiIiIdJ80JQhb4beDj7v6UmS1lf3UiIB7d0czqPmRoJhPR19dd79WOSjbbRRRFTJ7c2jjKZTJdLX9vKkliXEmMCZIbl4iIiDRHmhOETcAmd38qPH+QOEF4w8ymufuWUIVoa5i+GTimZPmjQ9lm4Myy8seHe+F8vsCOHYPj3oCxiiLI5faRzXbR3z9Ioe4p0Nj19XW39L2pJolxJTEmGDmuKVN6mxiNtEIUxfdJ+m0REZHmSW0bBHd/HXjNzCwUzQReBFYCc0PZXOCR8HglcKmZRWZ2OtAfqiI9CpxjZoeHxsnnhDIRkY4zoXcCa+etZu381UOJgoiIdJY0X0EA+DjwDTObALwMXE6c9DxgZlcArwIXhnlXEXdxuoG4m9PLAdx9m5ndCDwT5rvB3bc1bxNERJJlz8AedPFAZPx0NU7SKtUJgrs/B5xSYdLMCvMWgHlV1rMMWFbf6ERERKSdRBE1X1k7ZOJEXlh8PQAnXLdQSYKkSqoTBBEREZFmiCJYv+R6st3dNWcJe3fvbnBUIo2R2jYIIiIiIs20d/ducoPJ61xCpN6UIIiIiIiIyBBVMRIREZEDmNky4Hxgq7ufGMr+CvhD4C3gp8Dl7r4jTFsAXAHkgavd/dFQPgtYCmSAr7v7Tc3eFhEZPV1BEBERkXL3ALPKytYAJ7r7fwL+D7AAwMyOB+YAJ4RlvmJmGTPLALcD5wLHAxeHeUUk4ZQgiIiIyAHc/QlgW1nZd9w9F54+STywKMBsYIW773H3V4i7Ez813Da4+8vu/hawIswrIgmnKkYi0jRVqi18HvhT4OdhtuvcfVWYpmoLIsn0UeD+8Hg6ccJQtCmUAbxWVn5a40MTkfFSgiAizXQPcBtwb1n5re5+c2lBWbWFdwDfNbN3hcm3A2cTH3A8Y2Yr3f3FRgYuIjEz+yyQA77RiPVnMhF9fd1jXLZrzMvWIpvpIpPpIhtumUwXhbL7bKaLXMRQGcDkyY2LqZpGvxeKI91xjEQJgog0jbs/YWbH1jj7ULUF4BUzK1ZbgFBtAcDMitUWlCCINJiZXUZ8FXBmGIAUYDNwTMlsR4cyhimvKp8vsGPH2LoS7evrHvOyI4kiyOX3EYVbrsp9lN9HoQD5UAbQ3z/Y9IHSGvleKI7GxjFlSm+ToqlOCYKIJMF8M7sU+BHwKXffTp2rLYznrOTB60rHGaBKstkMmUq3THwfRZDJZoDWnPVspDR/biNpxraFqn2fAf6zu5ce4awEvmlmtxBf7ZsBPA1EwAwzO444MZgD/HFDgxSRulCCICKtdgdwI1AI918irt9cV+M5K1kuKWeiRiuKIJfLk8nlyZff8vF9oUB8T2vOejZSWj+3Woy0baM9I2lm9wFnAkeZ2SZgIXGvRYcCa8wM4El3/zN3X29mDxBfxcsB89w9H9YzH3iUuL3QMndfP8pNE5EWUIIgIi3l7m8UH5vZ14Bvh6d1rbYgIrVz94srFN89zPyLgcUVylcBq+oYmog0gRIEEWkpM5vm7lvC0w8CL4THqrYgIiLSAkoQRKRpqlRbONPMTiauYrQRuApA1RZERERaQwmCiDSNqi2IiIgkn0ZSFhERERGRIUoQRERERERkiBIEEREREREZogRBREREpIGiKL6JpEUiGimb2VRgCfAOdz/XzI4HftfdqzZeDMttBHYCeSDn7qeY2RHA/cCxxD2iXOju280sApYC5wGDwGXuvi6sZy7wubDaRe6+vL5bKCIiIp3okIkTeWHx9QCccN3Cthp8UNpXUq4g3EPcZeE7wvP/A3yixmXf5+4nu/sp4fm1wFp3nwGsDc8BziXuR30GcCXx6K2EhGIhcBpwKrDQzA4f19aIiIiIBHt372bv7t2tDkOkZklJEI5y9weAfQDuniO+KjAWs4HiFYDlwAUl5fe6e8HdnwT6zGwa8AFgjbtvc/ftwBpg1hhfW0REREQk1ZKSIOw2syOJB0rCzE4H+mtYrgB8x8yeNbMrQ9nUklFZXwemhsfTgddKlt0UyqqVi4iIiIh0nES0QQA+CawE/qOZ/QCYAnyohuV+z903m9nbgTVm9pPSie5eMLO61/bLZCL6+rrrvdpRyWa7iKKIyZNbG0e5TKar5e9NJUmMK4kxQXLjEhERkeZIRILg7uvM7D8DBkRxke+tYbnN4X6rmT1M3IbgDTOb5u5bQhWirWH2zcAxJYsfHco2A2eWlT8+3Ovm8wV27BisZdMaIoogl9tHNttFf/9goho89fV1t/S9qSaJcSUxJhg5rilTepsYjYiIiDRbSxMEM/uvVSa9y8xw94eGWXYi0OXuO8Pjc4AbiK9EzAVuCvePhEVWAvPNbAVxg+T+kEQ8CiwpaZh8DrBgvNsmIiIiIpJGrb6C8Ifh/u3Ae4HvhefvA/5/oGqCQNy24GEzg3g7vunuq83sGeABM7sCeBW4MMy/iriL0w3E3ZxeDuDu28zsRuCZMN8N7r6tDtsmIiIiIpI6LU0Q3P1yADP7DnB8sXFxqBp0zwjLvgycVKH8l8DMCuUFYF6VdS0Dlo0yfBGRtlYc2ClJ1RhFRKTxktKL0TElPQ8BvAH8h1YFIyLS6Q7tncDaeatZO3+1RoAVEekwra5iVLQ2tAW4Lzy/CPhuC+MREel4ewb2oIsHncnMlgHnA1vd/cRQdgRwP3AssBG40N23m1kELCWuxjsIXObu68Iyc4HPhdUucvflpFAUoURZOkoiriC4+3zgTuIqQycBd7n7x1sblYiISMe6h4MHDb0WWOvuM4C14TnAucCMcLsSuAOGEoqFxB2DnAosLOkQJDWiCNYvuZ6f3PpXrQ5FpGmScgWh2GPRcI2SRURkHHQGVGrl7k+Y2bFlxbPZ3y34cuIuwa8J5feGtn5PmllfaEt4JrCm2PGHma0hTjruI2X27t7d6hBEmioRCUIYOfnLwG8BE4AMsNvdJ7U0MBGRNhFF8OSi76McQcZhakl7wdeJexMEmA68VjLfplBWrXxY4xmMtFEDPWYzXWQyXRTCfTbcSstKp+UiDpoGNHVw06QMeqk4khnHSBKRIAC3AXOAbwGnAJcC72ppRCIibWbvrrdaHYK0CXcvmFlDmqiMZzDSRgxAGUWQy+8jyu8bui99XGlaoQD5smlAUwc3TcpgnIpj9HEkYUDSRLRBAHD3DUDG3fPu/jccXPdRREREWueNUHWo2B351lC+GTimZL6jQ1m1chFJuKRcQRg0swnAc2b2v4AtJCh5EREREVYCc4Gbwv0jJeXzzWwFcYPkfnffEnonXFLSMPkcYEGTYxaRMUjKQfglxO0O5gO7ic84/LeWRiQiItKhzOw+4IfxQ9tkZlcQJwZnm9m/A+8PzwFWAS8DG4CvAR8DCI2TbwSeCbcbig2WRSTZEnEFwd1fDQ/fBK5vZSwiIiKdzt0vrjJpZoV5C8C8KutZBiyrY2gi0gQtTRDM7HmoPg6Pu/+nJoYjIiIiItLxWn0F4fxwXzzz8Lfh/iMMkziIiIiIpE0U0bRejETGo6UJQrFqkZmd7e7vLpl0jZmtY/8ojSIiIiKpdcjEifjSL/Guqz+lJEESLymNlCMzO6P4xMzeS3JiExERERk3jcgsadHqKkZFVwDLzGwyEAHbgY+2NiQRERERkc6TiATB3Z8FTgoJAu7e3+KQREREREQ6Uqt7MfqIu/+dmX2yrBwAd7+lJYGJiIiIiHSoVl9BmBjueytMUxMeEREREZEma3UvRneGh9919x+UTitttCwiIiIiIs3R6isIRV8GfruGsoOYWQb4EbDZ3c83s+OAFcCRwLPAJe7+lpkdCtwLvAf4JXCRu28M61hA3FA6D1zt7o/WZatERERERFKm1W0Qfhd4LzClrB3CJCBT42r+AngpLAPwReBWd19hZl8lPvC/I9xvd/d3mtmcMN9FZnY8MAc4AXgH8F0ze5e758e5eSIiIiIiqdPqsQYmAD3EiUpvyW0A+NBIC5vZ0cB/Ab4enkfAWcCDYZblwAXh8ezwnDB9Zph/NrDC3fe4+yvABuDUcW+ZiIiIiEgKtboNwj8D/2xm9xRHVR6lvwY+w/5GzkcCO9w9F55vAqaHx9OB18Lr5sysP8w/HXiyZJ2ly4iIiIiIdJSktEE41MzuAo6lJCZ3P6vaAmZ2PrDV3Z81szMbHmGJTCair6+7mS95kGy2iyiKmDy5tXGUy2S6Wv7eVJLEuJIYEyQ3LhEREWmOpCQI3wK+SlxVqNa6/2cAf2Rm5wFvI26DsBToM7NsuIpwNLA5zL8ZOAbYZGZZYDJxY+VieVHpMhXl8wV27BisMcz6iyLI5faRzXbR3z9IIUEdwvb1dbf0vakmiXElMSYYOa4pUyr1SiwiIiLtIikJQs7d7xjNAu6+AFgAEK4gfNrd/7uZfYu4/cIKYC7wSFhkZXj+wzD9e+5eMLOVwDfN7BbiRsozgKfHv0kiIiIiIumTlAThf5vZx4CHgT3FQnffNoZ1XQOsMLNFwL8Cd4fyu4G/NbMNwDbinotw9/Vm9gDwIpAD5qkHIxERERHpVElJEOaG+/+vpKwA/EYtC7v748Dj4fHLVOiFyN1/BXy4yvKLgcU1RysiItKhzOx/AH9C/D/9PHA5MI1RjkEkIsmViATB3Y9rdQwiIiIyPDObDlwNHO/ub4Yr8HOA8xjFGEQtCl9EapSIBAHAzE4EjiducAyAu9/buohEpN7MbBlQ7IHsxFB2BHA/cS9mG4EL3X17GKdkKfGBxyBwmbuvC8vMBT4XVrvI3ZcjIs2SBQ4zs71AN7CFeAyiPw7TlwOfJ04QZofHEI9BdJuZRe6eoO41RKRcIhIEM1sInEmcIKwCzgW+T3xZUkTaxz3AbRy4b18LrHX3m8zs2vD8GuLfgRnhdhrxwcZpIaFYCJxCXMXhWTNb6e7bm7YVHSaKSFRvadI67r7ZzG4Gfga8CXyHuErRaMcg+kW11xhPV+KN6qY5m+kik+miEO6z4VZaVjotF1FxWjO7J09Kl9WKI5lxjCQRCQJxr0InAf/q7peb2VTg71ock4jUmbs/YWbHlhXPJj5BAPGZx8eJE4TZwL3hTOOTZtZnZtPCvGuKnRiY2RpgFnBfo+PvRIf2TuD7Cx7jjCXvU5IgmNnhxPvmccAO4m7KZ9XzNcbTlXgjuo+OIsjl9xHl9w3dlz6uNK1QgHyFaURR07onT0pX2opj9HEkoTvxpCQIb7r7PjPLmdkkYCsHjk0gIu1rqrtvCY9fB6aGx0NnHoPiWclq5cOq5wCHaTkDVC6TyZDJVrmFaVHEQdNyg7nEDco4Fmn93GrRxG17P/CKu/8cwMweIh6XaLRjEKVCFMU3kU6TlAThR2bWB3yN+FLlLuLxCkSkg4SxSRpybq2eAxwm5UzUaEQR5PN58rkqtzCtUOCgaVFX8856NlIaP7daNXGAw58Bp5tZN3EVo5nAj4DHGMUYRPUKppGiCNYvuZ5sd30Tr2LCkfb9SdpbV6sDAHD3j7n7Dnf/KnA2MNfdL291XCLSFG+EqkOE+62hvNoo56Me/VxE6sPdnyJubLyOuIvTLuAu4mqBnwxjDR3JgWMQHRnKP0ncxig19u7eTW6wfklltrubFxZfz/ol1+vKhCRaIq4gmNkfVCpz9ydaEY+INFXxDONNHHzmcb6ZrSBupNzv7lvM7FFgSagLDXAOYVR1qUzVJKSe3H0hcUcBpUY9BlGn2rt7d6tDEBlRIhIEDhwg7W3EPzLPEnebJiJtwszuI25kfJSZbSI+yLgJeMDMrgBeBS4Ms68i7uJ0A3E3p5dDPMK6md0IPBPmu2GMo653hCiCtfNXM6FngpIEERGpSSISBHf/w9LnZnYM8NctCkdEGsTdL64yaWaFeQvAvCrrWQYsq2NobW3PwB4oFDh00qGtDkVERFIgEW0QKtgE/FargxARERER6TSJuIJgZl8mHvAI4qTl3cQNoEREREREpIkSkSAAPwEy4fEvgfvc/QctjEdEREREpCO1NEEws0OAvwIuBTaG4qnAl4EfmNnJ7v5ci8ITEREREek4rb6C8CWgG/h1d98JEEZSvtnM7iAevv24FsYnIiIiItJRWp0gnAfMKB1V0d0HzOzPgV8A57YsMhERERGRDtTqXoz2VRpy3d3zwM/d/ckWxCQiIiIi0rFanSC8aGaXlhea2UeAl1oQj4iIiIhIR2t1FaN5wENm9lHikZMBTgEOAz7YsqhERERERDpUSxMEd98MnGZmZwEnhOJV7r52pGXN7G3AE8ChxNvxoLsvNLPjgBXAkcRJxyXu/paZHQrcC7yHuCvVi9x9Y1jXAuAKIA9c7e6P1nEzRURERA4QRfF94aCK1iKt1+oqRgC4+/fc/cvhNmJyEOwBznL3k4CTgVlmdjrwReBWd38nsJ34wJ9wvz2U3xrmw8yOB+YQJyizgK+YWQYRERGRBjhk4kReWHw965dcP5QoiCRJIhKEsXD3grvvCk8PCbcCcBbwYChfDlwQHs8OzwnTZ5pZFMpXuPsed38F2ACc2oRNEBERkQ61d/du9u7e3eowRCpqdRuEcQln+p8F3gncDvwU2OHuuTDLJmB6eDwdeA3A3XNm1k9cDWk6UNpbUukyFWUyEX193fXajDHJZruIoojJk1sbR7lMpqvl700lSYwriTFBcuMSERGR5kh1ghC6Qz3ZzPqAh4HfbMbr5vMFduwYbMZLVRRFkMvtI5vtor9/MFH1F/v6ulv63lSTxLiSGBOMHNeUKb1NjEZERESaLbVVjEq5+w7gMeB3gT4zKyY+RwObw+PNwDEAYfpk4sbKQ+UVlhERERER6SipvYJgZlOAve6+w8wOA84mbnj8GPAh4p6M5gKPhEVWhuc/DNO/5+4FM1sJfNPMbgHeAcwAnm7qxoiIiKREuGr/deBE4rZ/HwUcuB84FtgIXOju20Nbv6XAecAgcJm7r2tB2CIyCmm+gjANeMzMfgw8A6xx928D1wCfNLMNxG0M7g7z3w0cGco/CVwL4O7rgQeAF4HVwLxQdUlEREQOthRY7e6/CZxEPLDptcBad58BrA3PAc4lPvE2A7gSuKP54YrIaKX2CoK7/xh4d4Xyl6nQC5G7/wr4cJV1LQYW1ztGERGRdmJmk4E/AC4DcPe3gLfMbDZwZphtOfA48Qm72cC97l4AnjSzPjOb5u5bmhy6iIxCahMEERERabrjgJ8Df2NmJxH3JPgXwNSSg/7Xganh8VAPgkGxp8CqCcJ4egqsdy9s2UwXmUwXhbL7bLhVm5aLqGk5oGG9ESalRzrFkcw4RqIEQURERGqVBX4b+Li7P2VmS9lfnQiIxykyszH3rzeengLr2TtcFEEuv48ov++g+0plpdMKBcjXsBzQsN4Ik9JTnuIYfRxJ6C0wzW0QREREpLk2AZvc/anw/EHihOENM5sGEO63hump7SlQIxxLJ1OCICIiIjVx99eB18zMQtFM4k4+ij0FwsE9CF5qZpGZnQ70p6H9QRTBT+/6SqvDEGkZVTESERGR0fg48A0zmwC8DFxOfMLxATO7AngVuDDMu4q4i9MNxN2cXt78cMdm72Drq6OItIoSBBERGVGxukWSRm6X1nD354BTKkyaWWHeAjCv4UGJSF2pipGIiAxrQs8E1s5bzdr5q1UvW6TOokjtHSR5dAVBRERGtGdgD7p4IFJfh0ycyAuLrwfghOsW6gqdJIYSBBEREZEW2bt7d6tDEDmIqhiJiIiIiMgQJQgiIm1KdZtFRGQsVMVIRKQNRRGsnb+aCT0TUI4gIiKjoQRBRKRN7RnYo35JRURk1FTFSEREREREhihBEBERERGRIUoQRERERERkiBIEEREREREZogRBRERERESGKEEQEREREZEhqe3m1MyOAe4FpgIF4C53X2pmRwD3A8cCG4EL3X27mUXAUuA8YBC4zN3XhXXNBT4XVr3I3Zc3c1tERERERJIizVcQcsCn3P144HRgnpkdD1wLrHX3GcDa8BzgXGBGuF0J3AEQEoqFwGnAqcBCMzu8mRsiIiIiIpIUqU0Q3H1L8QqAu+8EXgKmA7OB4hWA5cAF4fFs4F53L7j7k0CfmU0DPgCscfdt7r4dWAPMauKmiIiIiIgkRmqrGJUys2OBdwNPAVPdfUuY9DpxFSSIk4fXShbbFMqqlVeVyUT09XWPP/BxyGa7iKKIyZNbG0e5TKar5e9NJUmMK4kxQXLjEpHkMLMM8CNgs7ufb2bHASuAI4FngUvc/S0zO5S4OvB7gF8CF7n7xhaFLSI1Sn2CYGY9wN8Dn3D3ATMbmubuBTMr1Ps18/kCO3YM1nu1NYsiyOX2kc120d8/SKHuWzh2fX3dLX1vqkliXEmMCUaOa8qU3oa8rpltBHYCeSDn7qeMpU2RiDTFXxBfuZ8Unn8RuNXdV5jZV4EriKvyXgFsd/d3mtmcMN9FrQg46aKIRP2fS2dLbRUjADM7hDg5+Ia7PxSK3whVhwj3W0P5ZuCYksWPDmXVykWk+d7n7ie7+ynh+ajaFIlI45nZ0cB/Ab4enkfAWcCDYZby6r3Far8PAjPD/FLikIkT8aVfItI7IwmR2gQh/MDcDbzk7reUTFoJzA2P5wKPlJRfamaRmZ0O9IeqSI8C55jZ4aFx8jmhTERab7RtiqTBoggdxMhfA58B9oXnRwI73D0XnpdW1R2qxhum94f5pcze3btbHYLIkDRXMToDuAR43syeC2XXATcBD5jZFcCrwIVh2iri6ggbiKskXA7g7tvM7EbgmTDfDe6+rTmbICIlCsB3QrXAO939LkbfpmgL0jCH9k5g7bzVFICZt81SdYgOZGbnA1vd/VkzO7MRrzGedn71bEOVzXSRzXSRyXRRKLsfaVouYtTL1btdYVLakymOZMYxktQmCO7+faDaeayZFeYvAPOqrGsZsKx+0YnIGPyeu282s7cDa8zsJ6UTx9umqJ6dC6TmBz6bIVN6y5Q9rzAtiqg6LZPN8NbOtwAS10FCLdLyuY1FE7ftDOCPzOw84G3EbRCWEl/Fy4arBKVVdYvVeDeZWRaYTNxYuarxtPOrV9uuKIJcfh+5/D6iCveVykqnFQqQH+VyRFFd2xUmpZ2b4hh9HI1q6zcaqU0QRKS9uPvmcL/VzB4mHpfkDTOb5u5bamxTVFU9OxdIyh9NNcVqQLlcnkwuT754y5c8Lr+FaYUCVacVbwVIXAcJtUj65zYezepcwN0XAAsAwhWET7v7fzezbwEfIu7JqLx671zgh2H698IJu8RSNToRJQipUPyhStufsUitzGwi0OXuO8Pjc4Ab2H9wcRMHH3TMN7MVxIMc9pdURepoUQRr569mQs+EqpdYRRrgGmCFmS0C/pW4jSDh/m/NbAOwDZjTovhqEkWwfsn1ZLu7lSVIR1OCkHBRBPPXXgXAbTPvVJIg7Woq8HDopjgLfNPdV5vZM4yiTZHE9gzs0RkFaTh3fxx4PDx+mfiqX/k8vwI+3NTAxqnYWDg7cWKLIxFpHSUIKTCwZ6DVIYg0VDi4OKlC+S8ZZZsiERERGZ/UdnMqIiIiIiL1pwRBRERERESGKEEQEREREZEhShBEREREEkBdrEpSKEEQEZFR04GMSH1lu7t5YfH1rF9yvfYtaTn1YiQiIqNyaO8E1s5bTQGYedss9agqUifFLlal/aQt6VOCICIio7ZnYA/KC0RERlYcgA/gvV/8YoujqY0SBBERERGRBkrb1SG1QUg51QMWERERkXpSgpBivRN6mbf2KuavvUpJgoiIiIjUhaoYpdzAngFUEVhEinSyQCT9ivuxOgCQVtEVhBTSAYCIVBJF8OSi76OfCJH0OmTiRHV3Ki2nKwgpE0Ww6MmF6AhARCrZu+utVocgIv+vvXsPkqws7zj+PXNl57KgsgECRNSQpwIkYkTUQBKoBQKWsoWjUN0AABVYSURBVFixCCYhYIiA7sZYhRF2IS43F1S8kHAJa6SAlAEvgG4sRJaNBtfKKpFSgVCPAbPE3VpYDMhclszs7Hb+OOf0nj7TPdMz06fPOT2/T9VUd59L9zvd/Z63n/O873sWqGwDWqXzKINQQmO7x/IugoiISEcp4qQfRSyTLA6lzSCY2e3AO4Gd7n5MtOzVwJeAI4CtwNnu/pKZBcCNwDuAXcD57v5YtM95wBXR017r7ne28/+YCx0kREREWi+ep75nYCDvolTFXY0Ajl6zVuMRpK3KnEG4Azg9tewyYJO7Hwlsih4DnAEcGf1dCNwK1YBiLfBW4HhgrZm9KvOSz8Nwfzhj0aWPXJJ3UURERDrO7vFxpnbtyrsYNXaPj6u7keSitBkEd3/EzI5ILV4BnBTdvxP4DnBptPwud68AW8zsADM7JNp2o7u/CGBmGwmDjruzLv98jEyMUKlUWNo/nHdRRESA8MyrzmwuHmZ2OHAXcBDhHHrr3f3G+WTwRaS4ypxBqOcgd98R3X+O8AAGcCjw88R226JljZaLiMgs+of72Lz62+r+uLhMAZe4+1HA24CVZnYUc8zgi0ixlTaDMBt3r5hZJue1ursDDjigff0Ue3q66One99cd3QZBQE93GOPtv38x+k12d3e19b1pVhHLVcQyQXHLJcU0MTqRdxGkjaKTcDui+6Nm9hThibU5ZfATJ/NEpIA6LUB4Pj7wRF2IdkbLtwOHJ7Y7LFq2nX0HtHj5d2Z7kT17Kvzyl+3ppxgEMDW1l6nuvUztCf/2RLeVSoWpPXsZ7hvm3PvPhQrctPy2XNP9Bxww0Lb3Zi6KWK4ilglmL9eyZeriJiIQdfN9E/B95p7BV4AgUmCdFiBsAM4Dro9uv55YvsrM7iEckPxyFER8C1iXGJh8GrC6zWVuCV1RWURE2sXMhoB7gQ+7+4iZVdctNIO/kCz9QjKgcYa+ksjUp5c1u24qYF771VsH8+slUJRssMoRint85F2OZpU2QDCzuwnP/h9oZtsIZyO6HviymV0APAucHW3+AOEAqacJB0m9D8DdXzSza4BHo+2ujgcsl5UGDIosTpovXdrFzHoJg4Mvuvt90eK5ZvAbWkiWfr6Z2SCAqT17CaIMfZC6P9d1lQrVbP9CnxNgZGQXe/e2571oNZVj3/cLwu/FbOUoQqa+tAGCu7+3warldbatACsbPM/twO0tLFpuhvuHWb35I6w74QYFCSKLSBDAplUP0jfUpyBBMhXNSvQF4Cl3/0xi1Zwy+G0scun1Dg7iN36a3/jQJWrbpW1KGyBIfaMTo3kXQURyMDEyAZUK/Uv78y6KdLYTgHOBx83sR9GyNcwxgy9zo2shSLspQBAREZGmuPtmoFGeak4ZfJmbODuoLIK0Q6ddB0FERESko/QMDPDEx6/iyXVX0dWl8UaSPQUIIiKyIPEAaQ2UFslO3M0oDhRU1yRL6mIkIiLz1jfUx6aVD9I71MfusUkqwPKbTlc3CCmNsgW2Go8g7aAAQUSkxIrw42ZiZIJKpcLk6KQuxyKlEgTw5Lqr6Bko/rz0aRqTIFlSgCAiUlI105vmXRiRkirjGfnewUGe+PhVABy9Zq2CBGk5BQgiIiUWT28qi1Pe2SPJTxzY6AKpkgUNUu5gReh6ICIi2YgzSJtWPZh3USQn8UXUNLORtJoyCB0qCGDVposAuGn5bTq7ICJto77R7TMxMpF3ESRnlUpF3Y2k5RQgdKC4cR6ZGMm3ICKy6PQPh7MaVYBTbt43m5F+tIhkJ9ndSKQVFCB0mKG+IVZuuoih3qHwWpdqlEWkzSZGJugb7uP7125mbMdYTbCgQEEkG/HA5Z6BAaZ27aKnpxv76BWqczIvChAKphWp+ZGJESo6Ioh0tDKMMZocm6wGC+msQqWirkiSv6LXobmKMwm7x8epdGuYqcyfAoQCyWrcQPIAqIZYpPzKOL1pOlA49ZbT2fjBcHCtsguShyCAZ9bfkncxMpWc4UgBucyFAoSCSY4baMUZwuH+4WqXo66ugOtOvEENsUgHKOv0pnGgsOWazUymgob4Csz1TmrM9UTHTD+G9ENJ4vZ1965deRclMz3RDEf215cAVAcyH3P59IHMqguSpgChoLq64IMbL2KoLxpLsABxl6OlUbBABW4+ZXqGYj6NrrITIjIfk2OT1fsTIxNU2Pejbcu1mxmPxi4sv+l0YF/GpKsr4MTrTq57oiM+WxpnWGBf0JHcJr2u2bOsCiw6Q83Vkzutj1FKPMNRz8AAu8fHa8Yp9A4O8soLLwDTg4aZugDquguLgwKEAhruH+aaLWsZmRyh0uJRxiMTIwz37csqjO0em5ZdaCQIYOXDYReom0+5DYBrt6xlx/hz1aAj3i4tz4NJEMCHHlzFNW//pA5q0hE68TdNPPtR71AfQVAbNMC+jEn/0v66syQFAXx39bc5cd3J+7Zn+nsVP3d8P71fo+BhIYHFXOjHV3vEffV7BgdzLkn20leKrj4OgmlBw1SUUfmtK9by+LW1GYf4O//TvwuzEumAYib6XpePAoSCGpscy/T546zC6ORoTXYhGTTEt8P9Q+wYe46h3iFGJmsDjCCoDTr2XzLMy6+M1uyXzFjklXkYnRzN/kVE2iA+w96BMUIYFERBAKSChtR2fYl1u8cmw9vxyZpjS3L//uE+Xtm5i64lPQRQu39iv+R1BYIANq/5Nr933cmzrnt45fTxFI0CuXRGI14WP+eJ607Wjylpq+Tg5t7BQZ6+7Zaa4AHCQAFqsxJxQNGo21IQwA8uX8PU1B6OXrO2Zh0oK1dkChCkKh00xLdxEJCcGSnZbSm5rLsrqK5LBw/JLEM686BxESKzq/abTnTP6XRx0DDTusnRyWpgkQ4o4m2CACZGJ+me2jNt//R+ycwFlUpT69LjKeJB2H3JAGZssqbbVBDUBhYAk6MTDbty6hi5cGWY/asIkmMz0lmGOPNQb12y21IcEOweG2Nqz166uqhmJeJ1T65rblzEfLs3q+7MnwKEiJmdDtwIdAP/6O7X51ykjpLu2tQoeGimEutgILC46mz8o+bhldHMRfqB09BMAUWz+9Xt7tTEuvh5koOwSQQwk6NhgNDVRTV4mExlQ/qGaqeEhenZiViZvgdFqK81Yw9kzmbqlpXuthTdrUpmJZLr4gDjmfW38MoLL9TNSgQB07IY8fbJ7dLq7TfbBAgLVW+8Rqtfo10UIABm1g3cDJwKbAMeNbMN7v6f+Zas8zTKPCSDh2SXpnR3p5nGSqTHSCgr0bkWS51NBwaTiX74kq10d6dm18UmG2R5+lPBQ73nTHehioOI+MJzyW5VZbgeZhHqazX7luqPL9moyThE4qxEo3XprEQyaGiUxZh2cbhEFiO9335Lhwn696sJLIBp2Y/kc9V7zkbr4udMBh7J/6FsFCCEjgeedvefAZjZPcAKINODV3qAWxkjzFZKd02q191ptrESyTESyS5N0Nz7O1P6cq6fj4KTTOVSZ7PQ6HtVLzCQztAoeEhLZyfiC88lu1WVROb1td6A8eS69A9Syd5MwVgzgVoyaEjvl8xiJAMLoCaLkdymu7uLYM/eaYFFvf1mes5G6+oFK/XKUhYKEEKHAj9PPN4GvHUhTzjbj8kggI//4EouP/5KAFZ/9yMM9g6ydL+lDPUOMdQ3xNL+pVF3nKDmtrquf4g9eyv11820X5brEmXK6vVGZxjAHe83tnuMob4hVm/+CIM9gxw8eHD1/vjUeM3tYP8gO8d3QgWu+70baj6PoCuY9hml96v3nPF+zczsIPPS8joLc/s8WvHZxTPo9A72MjW+m57Ebf/gvn70/Uv7oy4tQbUbSnpZq9b1D/Wxd8/etr1eO9ft2TUVDlIuQFlaua4EYUKmbWwQwM8+fyuvf/8HgHCWnZ4lS5h65RV6liyhZ8mS6ra9g4PVQKFnYIDegQGmUstasY6JIejrb+lzznVd7+AgQf9+bXu9hut6uqGvf877Zf1+TCUyGq16vanUdTXS+5WJAoR56O3t/sWyZcPPLvR5PnPGp6v315912wxbSrvV+zyy+IwOPHB49o1ysGzZjOV6bbvK0UqtqrexVn12Z60/syXPI9Ip9XY+dfU1l320ev93r76y1UUSaalZ6ioUoL4qQAhtBw5PPD4sWtbIsmyLIyKzmGudBdVbkbyojRUpGQUIoUeBI83sdYQHrXOAP8m3SCIyA9VZkfJQfRUpma68C1AE7j4FrAK+BTwFfNndn8y3VCLSiOqsSHmovoqUT1CiWRBERERERCRjyiCIiIiIiEiVAgQREREREanSIOUSmO0S9WbWD9wFvBn4X+CP3X1rhuU5PHq9gwgv4rne3W9MbXMS8HXgv6NF97n71VmVKfG6W4FRYA8w5e7HpdYHhO/lO4BdwPnu/liG5THgS4lFrwc+5u6fS2xzEm14r8zsduCdwE53PyZa9uqofEcAW4Gz3f2lOvueB1wRPbzW3e9sdfnKxMyuBN4PvBAtWuPuD+RXooWb7ThTZrMdF8pkIfW4E5nZp4B3AZPAM8D73P2XdbbbSou/A0Vom4vUHheh/c2zze20NlYZhIJLXKL+DOAo4L1mdlRqswuAl9z914HPAp/IuFhTwCXufhTwNmBlnTIBfNfdj43+Mg8OEk6OXrNeA3AGcGT0dyFwa5YF8dCx7n4sYSOxC7i/zqbteK/uAE5PLbsM2OTuRwKbosc1ogPcWsILGx0PrDWzV2VUxjL5bOIzK3tw0MxxpuxmOi6UyR3Mox53sI3AMe7+28BPgdUzbNuy70CB2uaitce5tr85t7l30EFtrAKE4qteot7dJ4H4EvVJK4A42vwqsDyK1DPh7jviqN/dRwlnpTg0q9drsRXAXe5ecfctwAFmdkibXns58Iy7t+xiXXPh7o8AL6YWJ787dwJn1dn1D4GN7v5idOZjI9MPglJuzRxnpAAWUI87krs/FM2SBLCF8BoL7VCItrlk7XG729+2trmd1sYqQCi+epeoT1f+6jbRgfJl4DXtKJyZHQG8Cfh+ndVvN7Mfm9k3zezodpSHMMX6kJn90MwurLO+mfczK+cAdzdYl8d7BXCQu++I7j9HmKZOy/M9K7JVZvYTM7u9CGd7FqjTP+PZjgtl10w9Xgz+Avhmg3Wt/g4Urm0uQHtctPa3CG1uadtYBQgyb2Y2BNwLfNjdR1KrHwNe6+5vBP4e+FqbinWiu/8OYSpzpZn9fpted0Zm1gecCXylzuq83qsa7l4hPMALYGYPm9kTdf5WEKbG3wAcC+wAPp1rYWU2hTwuZKET6/EsdTHe5nLC7jZfbPA0Hf0dKEh7XJj3uIhtbtnqpgYpF18zl6iPt9lmZj3A/oQDojJjZr2EB6Mvuvt96fXJA5S7P2Bmt5jZge7+iyzL5e7bo9udZnY/YRr4kcQmzbyfWTgDeMzdn0+vyOu9ijxvZoe4+44o1buzzjbbgZMSjw8DvtOGsuXK3U9pZjsz+zzwjYyLk7W86kVbNHFcKLtm6nFpzVYXzex8wsGhy6MfYfWeo9XfgcK0zUVpjwvW/halzS1tG6sMQvFVL1EfRcTnABtS22wAzovuvwf410YHyVaI+lB+AXjK3T/TYJuD476WZnY84Xct66Bl0MyG4/vAacATqc02AH9uZoGZvQ14OZH+y9J7aZDqzOO9Skh+d84jnNkh7VvAaWb2qqgrzWnRskUr1W/23Uz/npVNM8eZUmryuFB2zdTjjhTNJPRR4Ex339Vgmyy+A4Vom4vSHhew/S1Km1vaNlYZhIJz9ykziy9R3w3c7u5PmtnVwH+4+wbCg8M/mdnThANkzsm4WCcA5wKPm9mPomVrgF+LyvwPhAfDD5jZFPAKcE6WQUvkIOB+M4Pwu/3P7v6gmV2cKNcDhFOsPU04u8H7Mi5TfLA8FbgosSxZpra8V2Z2N+FZigPNbBvhrAnXA182swuAZ4Gzo22PAy5297909xfN7BrCBhHgandPD8RabD5pZscSpou3kvhsy6jRcSbnYrVK3eNCvkWav7nU40XiJqAf2Bh9xlvc/WIz+1XCqUffQQbfgQK1zUVpjwvT/ubV5nZaGxtUKqXpDiUiIiIiIhlTFyMREREREalSgCAiIiIiIlUKEEREREREpEoBgoiIiIiIVClAEBERERGRKk1zKoVm4ZxpX0osej3wMXf/nJm9Olp3BOFUk2e7+0tm9jfAn0bb9wC/CSwrwrRhIouFmd1OePGqne5+TGJ5o3obADcSToO4Czjf3R9rd7lFFpuZ2tnENpcANxC2pb9ILH8L8O+EU4V+tU1FljZQBkEKzUPHuvuxwJsJfzjcH62+DNjk7kcCm6LHuPunEvusBv5NwYFI290BnF5ned16S3jl0yOjvwuBW9tQRpFFb5Z2FjM7nPDiXf+T3M/MuoFPAA+1sbjSJsogSK7M7G+BPwNeAH4O/NDdb2iw+XLgGXd/Nnq8gn2XJ7+T8NLkl6b2aXg1RRGZn2bqrbs/YmZH1Nm9Ub1dAdwVXbBoi5kdYGaHtOlK5yIda4HtLMBnCa9Wnb4K8F8B9wJvaW2JpQiUQZDcRKnJPwLeSHj28LhZdjmH2h/7ByV+PDxHeCXH5PMPEJ7BvLclBRaR+dTbtEb19lDCHy+xbdEyEZmnhbazZrYC2O7uP04976HAu1Gmr2MpQJA8nQB83d3/z91HgX9ptKGZ9QFnAl+ptz4665i+LPi7gO+pe5FISzVdb2fToN6KSOvMu52NTrKtAT5WZ/PPAZe6+97WF1mKQAGCFM0SM/tR9HdxYvkZwGPu/nxi2fNmdghAdLsz9VzpjIOIZKNRva2nUb3dDhye2O6waJmItFaz7ewbgNcBPzazrYR18jEzO5gwE3FPtPw9wC1mdlabyi9toDEIkqfvAbeZ2XWE38V3AuujgVJp9cYSbADOA66Pbqv9I81sf+APCPtdikjrzKXe1tOo3m4AVpnZPcBbgZc1/kBkwebdzrr748CvxI+jYOC4aBaj1yWW3wF8w92/lkH5JSfKIEhu3P1Rwh8FPwG+CTwOvJzezswGgVOB+1KrrgdONbP/Ak6JHsfeDTzk7uMZFF1k0ZpDvb2bcPpDM7NtZnZBtKpRvX0A+BnwNPB54INZ/h8ii0EL2llZpIJKRd0/JT9mNuTuY1Ffx0eACzX3uUixqd6KlIfqq8yHuhhJ3tab2VHAfsCdOmiJlILqrUh5qL7KnCmDICIiIiIiVRqDICIiIiIiVQoQRERERESkSgGCiIiIiIhUKUAQEREREZEqBQgiIiIiIlKlAEFERERERKr+Hzxqsp3iVe9tAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x576 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DKBTNOx0BIFC"
      },
      "source": [
        "#Desafio 07: Resumo do que você aprendeu com os dados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WuODimgzCkW5"
      },
      "source": [
        "Para realizar melhores visualizações, a biblioteca Seaborn oferece vários tipos de gráficos, utilizando matplotlib como base. Além de filtrar os dados para obter informações relevantes, um bom cientista de dados deve ser capaz de gerar figuras e gráficos que revelam os diferentes padrões e comportamentos dos resultados obtidos."
      ]
    }
  ]
}