aula05_imersao_alura_dados.ipynb

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    "colab": {
      "name": "imersao_alura_dados.ipynb",
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      "include_colab_link": true
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    "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/EnzoGolfetti/imersaoalura_dados_3/blob/main/aula05_imersao_alura_dados.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N52buX1ji_ME"
      },
      "source": [
        "#Análise de Drugs Discovery - Imersão Dados Alura\n",
        "Desafio 1: Investigar por que a classe tratamento é tão desbalanceada"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KMqQPNh9ZMsN"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "rYqEzQSYZYTt",
        "outputId": "77ba2e2c-f8f2-4d09-e9f1-c15adb98be5f"
      },
      "source": [
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "\n",
        "dados = pd.read_csv(url_dados, compression = 'zip') #compression = 'zip' serve par aarquivos que estejam comprimidos, isso é bom para arquivos muito grandes\n",
        "dados"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
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              "      <td>1.5540</td>\n",
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              "      <td>1.2390</td>\n",
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              "      <td>0.4780</td>\n",
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              "      <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",
              "    <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>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</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",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 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",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\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",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[23814 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 137
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kw6AmOaObOku"
      },
      "source": [
        "Cada linha é um experimento de cultura de células que foi submetida a alguma droga com determinada dosagem e por determinada quantidade de tempo."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JB0uLzpkZcij",
        "outputId": "5072d149-06b0-41a8-a419-fb10b8222f22"
      },
      "source": [
        "dados.info() #para ver as primeiras infos dos dados, número de index (linhas)\n",
        "#colunas\n",
        "# e tipo dos dados, no caso são 872 de float64, 1 de int64 e 4 object (string)"
      ],
      "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": {
        "id": "VLN2U49lZy7T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f4ba9e5f-157e-4b00-9db8-a1358dcfb514"
      },
      "source": [
        "dados.isnull().sum() #o .isnull .summ serve para somar por coluna os valores nulos, da um parecer inicial sobre quais colunas tem nulos e dar uma ideia\n",
        "#do que vamos precisar fazer"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id            0\n",
              "tratamento    0\n",
              "tempo         0\n",
              "dose          0\n",
              "droga         0\n",
              "             ..\n",
              "c-95          0\n",
              "c-96          0\n",
              "c-97          0\n",
              "c-98          0\n",
              "c-99          0\n",
              "Length: 877, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p3a0Ee6ycRnC",
        "outputId": "9c39a380-611d-480f-eef3-657b7be30e95"
      },
      "source": [
        "dados['tratamento']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           com_droga\n",
              "1           com_droga\n",
              "2           com_droga\n",
              "3           com_droga\n",
              "4           com_droga\n",
              "             ...     \n",
              "23809       com_droga\n",
              "23810       com_droga\n",
              "23811    com_controle\n",
              "23812       com_droga\n",
              "23813       com_droga\n",
              "Name: tratamento, Length: 23814, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 140
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t82S7QAkcz61",
        "outputId": "9ab775a2-5698-446d-892d-651c0ace19de"
      },
      "source": [
        "dados['tratamento'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       21948\n",
              "com_controle     1866\n",
              "Name: tratamento, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 141
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rf4D9wENc_qM"
      },
      "source": [
        "Os tratamentos tem expressiva quantidade de experimentos 'com_droga' e apenas 1866 de 23814 sendo 'com_controle'."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9mlrsJ5BdRTr"
      },
      "source": [
        "Com controle significa, aqueles que não recebem os tratamentos para testar como os com experimento reagiram a droga, para saber que foi a droga que mudou a resposta, temos que ter o grupo controle que esteja no mesmo ambiente, exceto a presença da droga para ver a resposta."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5l0Htb-dc6Or",
        "outputId": "ab1b3e98-c9d1-4f53-d701-9f37bb04a1ae"
      },
      "source": [
        "#próxima variável a ser analisada = tempo\n",
        "dados['tempo']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        24\n",
              "1        72\n",
              "2        48\n",
              "3        48\n",
              "4        72\n",
              "         ..\n",
              "23809    24\n",
              "23810    24\n",
              "23811    48\n",
              "23812    24\n",
              "23813    72\n",
              "Name: tempo, Length: 23814, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HZTPWpZHeVT_",
        "outputId": "37cd0ff0-e0a4-41cd-b375-94d06f894a23"
      },
      "source": [
        "dados['tempo'].value_counts() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "48    8250\n",
              "72    7792\n",
              "24    7772\n",
              "Name: tempo, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 143
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ju8bJV57ecFe"
      },
      "source": [
        "Podemos ver que o tempo está disposto em unidades de 'hora', respectivamente:\n",
        "24, 48, 72.\n",
        "48 horas foi a maioria do tempo observado nos experimentos, e 24 horas a que menos foi (segundo a bióloga da imersão, devido a que, muitas vezes, 24 horas não é o suficiente para as células desenvolverem respostas à droga aplicada."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SOUoRqs1fHUT",
        "outputId": "7fdb1ba6-3208-4347-f040-b4af6a988a17"
      },
      "source": [
        "dados['dose'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "D1    12147\n",
              "D2    11667\n",
              "Name: dose, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 144
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "11MejnShfb6J"
      },
      "source": [
        "Observamos que tem apenas dois tipos doses (D1, D2), D1 tendo a maioria dos registros - 12147"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PS2tEae9Z4Kj",
        "outputId": "98740fa8-a20a-4ac4-81bc-fcd8a8df0e92"
      },
      "source": [
        "dados['droga'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cacb2b860    1866\n",
              "87d714366     718\n",
              "9f80f3f77     246\n",
              "8b87a7a83     203\n",
              "5628cb3ee     202\n",
              "             ... \n",
              "00dba5599       1\n",
              "7c1e00d49       1\n",
              "b36078dd2       1\n",
              "98a2c9b21       1\n",
              "a90e40334       1\n",
              "Name: droga, Length: 3289, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 145
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vtejKSegcVEt"
      },
      "source": [
        "Nas drogas, podemos ver que a droga 'cacb2b860' foi a mais usada (1866 vezes)\n",
        "E a droga '87d714366' foi a segunda mais usada com 718 vezes.\n",
        "\n",
        "O nome das drogas, é \"confuso\", pois foram anonimizados para evitar vieses nas análises.\n",
        "\n",
        "O total de drogas investigados foi de 3289 (registrado em 'length')"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0PUcL72ChL-V",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "beed9e28-d472-43e6-c4c7-9f374a512354"
      },
      "source": [
        "dados['g-0'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              " 0.0000     22\n",
              "-0.3372     15\n",
              " 10.0000    14\n",
              "-1.0040     10\n",
              "-1.0850      9\n",
              "            ..\n",
              "-0.5619      1\n",
              " 0.5292      1\n",
              "-0.1732      1\n",
              "-0.3844      1\n",
              " 0.1284      1\n",
              "Name: g-0, Length: 14367, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 146
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uTjp0PwpiBY9"
      },
      "source": [
        "Os 'g' são abreviação de genes, portanto, existem observações das respostas de vários deles, que estão dispostos nas colunas, e os valores que vemos é a expressão dos genes frente à droga, dose e tempo de exposição."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zSjdqpHXj5Cx"
      },
      "source": [
        "Os valores provavelmente estão normalizados para permitir o entendimento e a comparação deles"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f7E7JLZYsGMr",
        "outputId": "ab93f2c2-12fb-436f-df5e-3d8dedc6c577"
      },
      "source": [
        "#contando quantos valores maiores que 0, temos em 'g-0'\n",
        "dados[dados['g-0'] > 0].count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id            11769\n",
              "tratamento    11769\n",
              "tempo         11769\n",
              "dose          11769\n",
              "droga         11769\n",
              "              ...  \n",
              "c-95          11769\n",
              "c-96          11769\n",
              "c-97          11769\n",
              "c-98          11769\n",
              "c-99          11769\n",
              "Length: 877, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 147
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "xbQ16rYQ31u-",
        "outputId": "8558654b-cf70-4438-ae30-216b6583fa06"
      },
      "source": [
        "#máscara para os dados g-0 maiores que '0'\n",
        "dados_g0_maior_zero = dados[dados['g-0'] > 0]\n",
        "dados_g0_maior_zero.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "<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>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
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              "      <th>g-14</th>\n",
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              "      <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>6</th>\n",
              "      <td>id_001bd861f</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>746ca1f5a</td>\n",
              "      <td>2.0440</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>5.9440</td>\n",
              "      <td>-2.1670</td>\n",
              "      <td>-4.0360</td>\n",
              "      <td>3.6950</td>\n",
              "      <td>1.4530</td>\n",
              "      <td>0.9724</td>\n",
              "      <td>-2.4380</td>\n",
              "      <td>5.1340</td>\n",
              "      <td>-4.6600</td>\n",
              "      <td>5.7960</td>\n",
              "      <td>4.9700</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>2.4790</td>\n",
              "      <td>-3.8010</td>\n",
              "      <td>-1.0230</td>\n",
              "      <td>5.3110</td>\n",
              "      <td>-0.5660</td>\n",
              "      <td>-4.4450</td>\n",
              "      <td>1.2210</td>\n",
              "      <td>1.3750</td>\n",
              "      <td>0.3932</td>\n",
              "      <td>0.3392</td>\n",
              "      <td>4.3510</td>\n",
              "      <td>5.7540</td>\n",
              "      <td>-1.6590</td>\n",
              "      <td>5.3000</td>\n",
              "      <td>5.6050</td>\n",
              "      <td>5.5320</td>\n",
              "      <td>3.7860</td>\n",
              "      <td>0.9197</td>\n",
              "      <td>1.9310</td>\n",
              "      <td>2.4870</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.8904</td>\n",
              "      <td>2.0590</td>\n",
              "      <td>0.5052</td>\n",
              "      <td>0.6890</td>\n",
              "      <td>0.5340</td>\n",
              "      <td>0.5135</td>\n",
              "      <td>0.6507</td>\n",
              "      <td>0.9838</td>\n",
              "      <td>0.4532</td>\n",
              "      <td>-0.3212</td>\n",
              "      <td>0.2662</td>\n",
              "      <td>0.6864</td>\n",
              "      <td>1.6300</td>\n",
              "      <td>1.3810</td>\n",
              "      <td>0.0061</td>\n",
              "      <td>0.2908</td>\n",
              "      <td>0.2598</td>\n",
              "      <td>0.1266</td>\n",
              "      <td>-0.3526</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>-1.1030</td>\n",
              "      <td>1.3650</td>\n",
              "      <td>1.0610</td>\n",
              "      <td>0.4034</td>\n",
              "      <td>1.0880</td>\n",
              "      <td>-0.4230</td>\n",
              "      <td>0.4013</td>\n",
              "      <td>0.1726</td>\n",
              "      <td>0.7464</td>\n",
              "      <td>0.9418</td>\n",
              "      <td>0.1855</td>\n",
              "      <td>1.1720</td>\n",
              "      <td>0.8325</td>\n",
              "      <td>0.6486</td>\n",
              "      <td>0.8090</td>\n",
              "      <td>1.5880</td>\n",
              "      <td>2.4670</td>\n",
              "      <td>0.0357</td>\n",
              "      <td>0.1351</td>\n",
              "      <td>-0.3179</td>\n",
              "    </tr>\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",
              "  </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",
              "6  id_001bd861f  com_droga     24   D2  ...  2.4670  0.0357  0.1351 -0.3179\n",
              "7  id_0020d0484  com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 148
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UfKSeo-QlmFp"
      },
      "source": [
        "###Desafio 2: Plotar as últimas 5 linhas do Dataframe"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SuJkniNZhQXB",
        "outputId": "92b4ddd6-256e-497f-f849-3aaa5a84e7bd"
      },
      "source": [
        "#plotando últimas 5 linhas\n",
        "dados.iloc[23809:,:]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <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>droga</th>\n",
              "      <th>g-0</th>\n",
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              "      <th>g-13</th>\n",
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              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
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              "      <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>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</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",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</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",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\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",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-87ZWVmpmA_5"
      },
      "source": [
        "###Desafio 3: Registrar a proporção da classe tratamento"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xi7zgc_lhjKZ",
        "outputId": "a4b82972-685f-4b39-edb8-f6e63da47562"
      },
      "source": [
        "#usando método matemático\n",
        "(dados['tratamento'].value_counts() * 100) / 23814"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       92.164273\n",
              "com_controle     7.835727\n",
              "Name: tratamento, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 150
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JkLr6dTfuCoQ",
        "outputId": "88e3b5b1-28c8-4454-8b1b-a45d35b9356d"
      },
      "source": [
        "#usando função value_counts do Pandas\n",
        "dados['tratamento'].value_counts(normalize=True) #o normalize nos dá os porcent deles"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       0.921643\n",
              "com_controle    0.078357\n",
              "Name: tratamento, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 151
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RfxAIqOZue_S"
      },
      "source": [
        "É interessante termos um comparativo com dados da própria tabela, porém de outras colunas, nesse caso, vamos comparar com a distribuição das doses"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RncNwpTcunW6",
        "outputId": "d7040437-3614-4dd3-cec9-2758c033f985"
      },
      "source": [
        "dados['dose'].value_counts(normalize=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "D1    0.510078\n",
              "D2    0.489922\n",
              "Name: dose, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 152
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QAfY8xyGuW5Y",
        "outputId": "197f44d2-bb9a-41e6-aead-1201a22c681e"
      },
      "source": [
        "#plotando gráfico de pizza para mostrar as proporções dos valores em tratamento\n",
        "fig, ax = plt.subplots(figsize=(20,6))\n",
        "labels = ['com_droga', 'com_controle']\n",
        "ax.pie(dados['tratamento'].value_counts(normalize=True), labels=labels, autopct='%1.1f%%')\n",
        "ax.set_title('Distribuição dos tipos de tratamentos')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distribuição dos tipos de tratamentos')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 153
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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+H4R930Zhq/qGGWPWRyz+GLafdHmf4T9hWwQfbIxZUFNc2PusK7Bdt97AHouazMUmuPLBNX6DveA6uULL/XXAMD/uUf5+HIRtVX5CRNXnemyjp/2w79vT/vqfw3afq7ZNhd+I73BsUrkA25o8FXtBUVDJ8v/xY56HTZrPAFdjP3P/B2yuxTGoz3EDexxexF5clu/n7djPaMU4p2O/N72xx+IN7AUS1OHz21CMMROBA7Gl71F+zDdiL7Ie5+cakrqu9wfsRUcL7Gf4DWzCrct3ry7nN9HAZOQ00aD8qumpgK7kfrGoIx0DTwwTQjQsKXGLBuX3m96E7X4jhBCigck9btEgtB27+lzs4B59sYNuCCGEaGCSuEVDScDe922HbeTTEH1zhRBCVCD3uIUQQogoIve4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIpK4hRBCiCgiiVsIIYSIIglBByCEAEABrYA0ID3iJ63C3wBF/k9hxN+V/b8b2ALsArwm2g8hRCOTxC1E02gB9AY00Bfo63qedl2vm1Iq3VG0VEpVWwPmejb3OkrVacOu6+32PG+j46gflFIbgA3AKv9nJZCNJHYhoobyPPm+CtFAFNCDiOTseV5f1/UGOI7qotTPGTcnryi8fmt+6MedheQXlbK7sJSCojJ2F5Wy2/9dUFTK7sIy+7uojMLiMgASQoqkxBBJCSESEx2SE0MkJjgkJYTs9ESHpMQQyYkhMtKSaZfegnbpKbRv08Lr2CbVTW+dHAo5Pyd/1/WKPLzVIcdZBswCZgCzgfymO3RCiNqSxC1E/bUAhgKHAIeGXffwkONklM8sLC5zN27NZ8O2PGfjtgI2bctn47Z8Nm0r+CkJByHkKDpktCCrXUuy2rekk/+7Z1ZauFO7liEAz/Nc12NJyFHfYhP5TGAp4AYWuBACkMQtRF20wCbpo1zXOxLFUEepBIDsHwvCS9ZsDy1bt5P1W/LYuC2fnLziYKOth9apifTtnkHf7hn065GB7tE23LJFYggg7Hr5jmKmUqo8kU8FcgINWIg4JIlbiKopbIn6eM/zjvI8DnEclRQOu96K9TksXr1dLV27g2Vrd7CroCToWBuFUtC5fauIRJ7h9uyc7oQched5YQ++cpT6APgQe+9cCNHIJHEL8UsK2Bc4K+y654QcpyfAmk257vzl25wFK7axZM2OQKu6g5acGKJ313QO6J/JIYM6h7t0bBUCcF1vjuOo94EPgGVIgzchGoUkbiGsfsBZYdc7N+SovmHX8xas2MaUeRvVrCWbY7ZE3RC6dmzF8H2yOHhQltu3e4YDEHbdlSHHeR8Yh61Wl3vjQjQQSdwinvXCJutzQo4a5Hkei1dt96bM36i+WbhJknU9tE1LYdjATgwflOUN3rs9oZCjwq67LeQ4bwPPAouDjlGIaCeJW8SbdOAi1/VGOY46AGDZ2h3ulHkbnekLN7FjV1HA4cWOlikJHNA/k+GDshg2MMtLTHCU63pTHUeNwVany5WREPUgiVvEi57ANa7rXe44quWqDTnu1/M2OtMWbGTbzsKgY4t5rVMTOfqg7px0aK9wZtvUUNj1toYc9Szwb2Bj0PEJEU0kcYtYN8zzvBuA013XU1Pmb1QfTlnFqg25QccVl5SC/XVHTjp0L++A/pkKe+/7A6XUM8BkpEGbEDWSxC1iUQg4zXW9GxxHHby7qNSd8M1a55Npq9meK1XhzUVm21ROOKQnxw3v4bZqkeSEXW95yFFPA//Fjq8uhKiEJG4RS1oDfwy77vUhx+mxZcfu8LivV4YmffcDRSXhoGMTVUhKcDhsvy6cdOhebt/uGY7renmOox4BnkQSuBC/IolbxILWwM2u613rOKr10jXbvfe/WqW++z4bVz7eUaVPtzaceXRfhu+TRdj1ckKOegh4Ghk3XYifSOIW0SwBuCTseveFHNV+2oKNfPDVKpb/sDPouMQe6t01nfOO6+cdOKCTCrvejpCjHgDGYB9dKkRck8QtotXxYdd7POSo/t+v3u698NFitWK9DJsda/p2z2DU8f28IbqjCrvuppDj/A14DZB7HyJuSeIW0WaQ63mPOUodk729IPyfj78PfbsoO+iYRCPbp3c7Ljl5H3fvbm2csOstCjnqRuCzoOMSIgiSuEW06ATc63nexbuLynh94jJnwjdrKAvL5zdeKAWHDu7MH08a6HZsm+q4rveF46i/YMdFFyJuSOIWzV0qcL3rere5npcyftoa9ebnhvzC0qDjEgFJCDmccEhPzjuun9siOaHMcdRo4FFAPhQiLkjiFs3ZCWHXfS7kOF2+WbiJlz5ZQvb2gqBjEs1Em9bJXDFyEIcN7oLregsdR10EzAs6LiEamyRu0RxlAI8DF63fkueOeXeB8/3q7UHHJJqp4ftkcdUZg8PprZKUUuph4B6k9bmIYZK4RXPzu7DrPgcq870vV6g3PjOUheWJkKJ6LVskcvHJAzl2WA/Crrcy5Kg/AtOCjkuIxiCJWzQX6cA/gQt+2LzLffyNuY6MJy7qanCfDlxz1n7hjhmpIWy/778BeQGHJUSDksQtmoPDw677mkJ1ffuL5eqtz420Fhf1lpwU4vzj+3PKb3rhet7GkONcBnwadFxCNBRJ3CJIicBdnuf9bevOQu+RV2aHjIx6JhqI7p7BtWcPcbtltnaAx4BbgbKAwxJij0niFkHp47reG46jhn7+3TqeG7eYwmI5p4qGlRByuPiUgZx8WC9c1/vacdSZwNag4xJiT0jiFkE4wXW9twuLy1L/+dY85xsZ+Uw0st8O7crVZ+7nOo7aEnKckcDMoGMSor4kcYumpIDrPc97eM2mXdz34kxnW4702hFNY6/Oadzxx2Hh9hktXEepq4F/A3ICFFFHErdoKsnAs8BF0xds4ok351Isz8gWTaxVi0RuHDXUG9ovUwH/Aa5C+nyLKCOJWzSFjq7rjXMcdfDrE5fx5ucG+diJoDgKzjm2H2cfq3Fdb77jqJHA2qDjEqK2JHGLxjY47LqfhMNe58dfn+tMX7gp6HiEAODAAZnceN5QNzkpYVfIUWchTxsTUUISt2hMI13Xez0nvzjxnudnhFZtlAFVRPOS1a4ld1x8kNsts7VSSl0LPBV0TELURBK3aAwKuB24d/kPO937Xpzp7MwrDjomISqVnBTihnOHcvCgLIA7gPuRRmuiGZPELRpaoud5/1FKnTd59nqeemc+pWUy1rho3hxHce1ZQzjygG4AjwC3IMlbNFOSuEVDSvQ87w2l1OmvTFjK218sDzoeIWpNKbhi5L6cdOheAP/CtjiXrg+i2ZHELRpKkud5byqlRj43bhEfTV0ddDxC1MsFJ/bnD0f1xfO815VSFwGlQcckRCRJ3KIhJHme95ZS6rR/f7CIj6dJ0hbR7Ywj+3DhSQPwPO8jpdRZQFHQMQlRThK32FNJnue9o5Q65dn3FzJ++pqg4xGiQZx4SE+uPH0wrud96Sh1KpAfdExCgCRusWeS/aR98tj3FzJBkraIMb8d2pXrzt7fA2Y5jjoekMfXicBJ4hb1lex53rtKqd+NfW8BE75ZG3Q8QjSK4ftkccsFB3hKqcUhRx2BJG8RMEncoj5SPM97Tyl14ph3F/C/b9cGHY8QjWqI7sCdlwz3HKW+cRx1DDK+uQiQE3QAIuoke573vlLqxKffmS9JW8SFeWYbj746RynFoZ7nvQUkBB2TiF+SuEVdKOB5pdQJT709n4kz1gUdjxBNZvrCTYx9byFKqZOx/bxV0DGJ+CSJW9TF34BRr3y6lM9mStIW8efTb9fy+sRlABdjh0YVoslJ4ha1dTrw98lz1vP2JBkRTcSvNz4zTPhmDcCtwJ8CDkfEIUncojaGuq732rJ1O9yn3p4fdCxCBO5f7y9k1pLNnud5Y4Djgo5HxBdJ3KImXcKu+8mOXUUJf3/xO0ceGCIEuB48/MpstTZ7F67rvQcMCjomET8kcYvqpLqu93Fpmdtx9HPfhnLy5dGcQpQrKglz9/MznNz84pSw634KZAUdk4gPkrhFVRzP815WiiEPvzzbWbc5L+h4hGh2tucWMfr5GaGyMi/Ldb2PgaSgYxKxTxK3qMo9SqnTX/joe2Yt3RJ0LEI0W6s35vLY63Mcx1FDgQeCjkfEPkncojKjgNsnzljLh1NWBR2LEM3et4uy+cQ+Fe964MSAwxExThK3qGiA63rPL1r5o/fs+wuDjkWIqPHix9+zNnuXG3a9V4DOQccjYpckbhEpJex6b+UXliY+/OpsVRaWceyFqK3SMpeHXp7llIXdNq7nvQaEgo5JxCZJ3CLSgyFH7fP463OcnDxpQS5EXW3Yms/Y9xY4jlIjsCMNCtHgJHGLcicC1340ZRVzlm0NOhYhotYXs9Yzec56PM+7Gzg86HhE7JHELQAyw6778trsXe5L45cEHYsQUW/sewvZsmO3F3bdN4G2QccjYoskbqE8z/uX69L2kVdmy8hoQjSAwuIyHnx5VsjzyPI870XkSWKiAUniFucppU59ecIS9cMWGWRFiIayakMuL33yvVJKnQr8Jeh4ROyQxB3fuoRdb8zSNdvdj6S/thAN7sMpq5m9dIvnut4jQI+g4xGxQRJ3/FKe5z0XDrutnnhznuNKzy8hGsUz7y5QpWE30fO8J4KORcQGSdzx6yKl1An/+eR7J/vHgqBjESJmbcsp5M3PjKOUGgmcEHQ8IvpJ4o5P6WHXe3TJmu3e+Olrgo5FiJg37uuVbNyW74ZdbwyQEnQ8IrpJ4o5PdziKtv/+YJHypIpciEZXFvYY+95CJ+SovYCbg45HRDdJ3PFnb9fzrps06wdWbcwNOhYh4saCFduYOn8jruvdDvQKOh4RvSRxxxnP8x4uLQ07r0xYGnQoQsSdFz5aTGlZOMHzvCeDjkVEL0nc8eW3SqmRb01a7uyUsciFaHLbc4t4beIyRyn1O+DkoOMR0UkSd/wIua73jx9zCsMffi19toUIykdTVrN+S54bdr2ngdSg4xHRRxJ3/LjIcdS+L3y8OFQiw5oKEZiw6/HMewuckKO6A7cGHY+IPpK440Na2HUfXLp2hztt/qagYxEi7i1etZ2v527A9bxbgKyg4xHRRRJ3fPhbyHHaPzdukbzfQjQTr/1vGXgkATcEHYuILnIij317ua53/Zez17NifU7QsQghfNnbC/h63gZc17sKaB90PCJ6SOKOfbeHXTfh5QnynG0hmpt3vliBUqQAfw06FhE9JHHHtk6u513w+cwfnO25RUHHIoSoYP2WPKYv3ITretcCGUHHI6KDJO7YdrWCxHHyyE4hmq23Pl+O46iWwNVBxyKigyTu2NUq7HpXfbsoG3n6lxDN19rsXcz8fjOu610PtA46HtH8SeKOXReHHJX+/lcrg45DCFGDtz43OI5KB/4cdCyi+ZPEHZsSwq57w9I12z2zbmfQsQgharBifQ7zzFYv7Ho3IaOpiRpI4o5Np4ccp/v7X61UQQcihKidNz83KuSodsDlQccimjdJ3LFHua53y6Zt+e7M7zcHHYsQopaWrNnB4lU/emHXuxVIDjoe0XxJ4o49RziOGvL+Vysdzws6FCFEXbzzxQoVclQmcFrQsYjmSxJ3jPE876ZdBSXhybPXBx2KEKKO5i3fyradu8Ou50l1uaiSJO7YMkApdeJHU1bJE8CEiEKeBxNnrAs5Sh0J9A46HtE8SeKOLX8Mh13v02/XBh2HEKKePv/uB1zXA7gk6FhE8ySJO3Y4Ydc9d86yrWpXQUnQsQgh6mnHriJmLd1C2PUuBRKDjkc0P5K4Y8dhIcfp/PW8DUHHIYTYQxNnrCXkqA7AiUHHIpofSdyx45zi0rB0ARMiBsxZtrqSeSMAACAASURBVJVdBSVhYFTQsYjmRxJ3bEgKu97ZMxZlO8Ul4aBjEULsIdf1+GrO+pDreqcAbYKORzQvcZO4tdae1np00HE0kmNCjmoj1eRCxI7JczbgOCoJOCPoWETzEjeJO8adU1BY6s4zW4OOQwjRQFZuyGHjtnzXdb0Lgo5FNC+SuKNfqut6v586f6NTFpah0oSIJV/OWu84jjoc6BF0LKL5kMQdQWvdMugY6uFkx1EtpJpciNgzdf7G8j9PCTIO0bwk1HZBrXU34B7geCAD2ACMN8Zc68/fH3gAOMR/yXTgFmPMgoh1jAbuAvoA92G7OhQCjxtjHtJa9wWeBg4FtgO3GWNercsOaa2TgQexrTFTgMlU8ozbiFj6RezXXOC3WusE4HbgQqCLv68vAfcbY8IR62gBPASci30owGTgSn/5u40xo/3legC3AEcB3YHdwJfATcaYtXXZv4o8zzt3Z15xeMnq7aE9WY8QovnJ3l7A5u0F4cy2qccppZ4KOh7RPNSqxK217gJ8B/wBeB24BngLOMmfPxCYAgzAJu8HgIHAVK11/0pW+S5Qhk1mC4EHtdZXAJ8Bi4GbgVzgJa11zzru0/PAdcD/gFuBUmB8Ncu/D4T8WMovEp4HRgMzgeuBWdjk/myF174EXA184r++sIptHYi9oHkTe+yexSbxr7TWe/Ls3QwPTvx67oaQK7XkQsSk2Uu3hDyPo5AnhglfbUvcDwIdgAOMMfPLJ2qt7/D/vA+b/A4zxqzz570OLPPnnV5hfdONMVf5y/0H2ASMBS4zxrzgT5/kv/584N7aBKm1Howtaf+zvCYAGKO1fg3Yt4qXzTHG/NT4w1/HhcCzxpgrI9aRA1yhtX7KGLPQr2E4E3jUGHOTv9wz/v4MrrCN8caYdyvE+jHwLfbYvFKb/avECY5SCdMWbKrny4UQzd1cs5XfHdYrBVsT+WXQ8Yjg1Vji1lo7wKnAuMikDWCM8bTWIeBY4P3ypO3PWwt8ABznLxPp+YjlioAFQBh4OWK6AXKAveqwP+WjDP2zwvR/VPOaiqXo8nU8XmH6ExXmH+//fqbCcr+qzjLGFJb/rbVO1Fq3A1Zi92//amKrydEFhaXuyvU792AVQojmbNHKHykLux5wXNCxiOahNlXlHYDW2CrsquanAqaSecuAlkD7CtN/qPB/LrDZGFNayfSMWsRYrge2Cn5NhemVxVau4rLl61hVYfpKf3qPCsutq2S5X9Bat9Ba36O1Xg8UAz8C27ADK6RXE1t1VNh1j5u3fKsj1eRCxK6ikjBL1+wg7Hoy/KkAgmtVXtnwXlUN+aUaMxDsfenG9hS2sdvb2Or1Y4FjsA3w6vse9A05TucFy7c1TIRCiGZrrtmqQo7aB8gKOhYRvNokjW1AHrBPNfN3A7qSeRoowJYwm8I67H37itXrlcVW0zoqPgu3tz99XYXlKvav3LuSdZ4B/NcYc4Mx5l1jzOfANPZsKMOjAeavkMQtRKyb+/PgSscGGYdoHmpM3MYYF/gQOE1rPSRyntZa+d2jPgN+r7XuHjGvOzASmBjZhaqRfer/vqbC9OvqsI4JVbymvLFbeavxif7vil3Nrq5knWF+XXNwNbZBX30ds3XH7vDm7bv3YBVCiGiwZlMuufnFYeQ+t6D2rcpvw17pTdVaP4u9Z9wNOBvoC9yBrfqdprUe67/mSuw94Dt+vbrGYYyZr7V+A7hGa50BzMB2u6qsFFzVOhZorf8L/NlfxzTgMOAc4AVjzCJ/uTla6/eAG7XWHbDd5Y7AHg+AyDvPnwDna61zgSXAwdgS8/Z67qoTdt0RC1Zuk77bQsQBz4M5y7aGjti/6/EhR4Wo+taiiAO1ur9qjFkPDAPGYbtKPYVNZOP9+d8Dv8E2Rrvd/1kKHG6MWdrwYVfrYmyr8hOBh7EPoj+pjuu4FNuP+2Bsi/SDgTuBKyosdwEwBjgZOxBLEnCWP68oYrlrsS3mzwMew96nOhrIr2Nc5fqFHCf9+9U76vlyIUS0mWu2EnJUBnvWE0XEAOV50iS5IWmt9wPmAaOMMa810mYuB/51+f2TyN5e0EibEEI0J+mtknj17hPADvb0cMDhiADJWOV7wB/ytKLrABc7klxjOTw3vzgsSVuI+JGbX8L23MIwsF/QsYhg1Xqs8qBprTvVsEihMSa3SYL52d/8kdYmY5P18cAJwL/92wuNIhx2j1i8SsYmFyLerNqQG2rTOnm/kCNlrngWNYkbyK5h/n+Bi5ogjkjfYBu/3Qm0wg4scxdwfyNuMysUcrotWVPfdm1CiGi1ZlMuBw7I1NgHKBXVtLyITdGUuI+pYX6TD9htjPkf9mEmTWkgwJpNu5p4s0KIoK3ZtAullIN9oNPcoOMRwYiaxG2MmRR0DM1EP4ANW/OCjkMI0cTWbPrpbuBgJHHHrahJ3OIn/XYXlbo784qb3U2unaunkbt+JniQ3v0gMnodzrYln5C/ZSnKCZGY2o5O+51JKPGXbfpKC3PYPP9NwsX5gCK9+zAyeh0GwLalEyjYuozktM5kDTkbgF0b5hIuKSCj1+FNvYtCBGrz9gKKS8NucmKo4hMIRRxpdid/UT3P8/qv35rf2OO311nxrs3krp9J98OupsdvrqNg61JKCn4ktUNfeh5xPT2PuJ6kVh3YsXLyr16rlEOHAb+j54gb6X7YVeSs+4bivC2ESwspzt1IzyOuRzkhindl44ZLyV0/mzY9DwlgL4UIluvB2uxdyvO8qh5TLOKAJO4o47rewA1b8ppd4i7J30pKm+44oSSUE6JF217kZy+mZYe+KMc2gE9p052ywpxfvTYhJY2U9K4AOAkpJLXqSFlRLkopPDeM53l44VKUE2Lnqq/J2OuQn9YpRLxZszFXuZ63P43/ACbRTEniji5poZCTuWFrfQdcazxJrTMp3LGGcEkBbriEgq3LKCv6ZZLetX4WLTv2q3Y9pbt3UJy7yV4EJKTQsmM/fpj6DxJSWuMkpFCU8wOtOlX1vBshYt+a7F2EHCcd6BJ0LCIYco87umhong3Tkltn0rb3CDbMfB4nlERyemdQP18Xbl/xBSiH1l2GVLkOt6yYTXNeocPAkwklpgDQdu8RtN17BACbF7xDO30suT/MpGDbCpLTsmjX56hG3S8hmpu1v2ygtiHAUERApMQdXfwW5c2vxA22QVqPw6+l2yFXEkpsQVLL9gDkrp9NwZalZO1/DkpVXrvnuWE2zXmFtC5DaJ016Ffzi3I3ApDUsiN52YvoPHQUpQXbKcmXx5qK+BLRFVQaqMUpSdzRpX847HrZPzbPoU7Liu0FRWnhTvKyF9O6yxAKthp2rvqKzgdehBNKqvR1nuexecE7JLXqSEav31S6zHYzkfb6WDwvDJ5rJyqF55Y2yr4I0VwVFpeRk1ccBnoFHYsIhlSVR5d+W3bsdsOu1yxbZmXPeZlwyW5QITIHnUYosQVbF4/Dc8vYOPM5wDZQy9z3dMqKctm84F26DruEop1ryds4l6TWnVg35QkA2unjaZXZH4D8zYtJTu9KQko6AMlpnVn79eMkt+5EclrnYHZWiADtzCtSbVonZwYdhwiGPB0sioTDrpm1dEvfv//nu6BDEUIEaPRlwxnSt+Nsx1EHBh2LaHpSVR49lHJUz+ZaTS6EaDo5ecW4npcVdBwiGJK4o0eKo1TSroKSoOMQQgRsZ14xjqM6In2545Ik7uiRAZBfKI2xhIh3OXnFOEolAulBxyKaniTu6OEnbilxCxHvcvKLy/+UBmpxSBJ39GgDUCAlbiHiXk7eT4m7U5BxiGBI4o4etsS9WxK3EPFuZ15R+Z9S4o5Dkrijh9zjFkIAvyhxS+KOQ5K4o4dUlQshAMjbXULY9UASd1ySxB09MkAStxACPA/ydpeEkXvccUkSd/TIKCopc/2rbCFEnCsuKQNICToO0fQkcUePNgWFpZK1hRAAhMMeyPMm4pIk7uiRkSctyoUQPr/2TRJ3HJLEHT2SS8vCMryhEAKAcNhVSOKOS/KmR4+SxJBcZwlISHBISpDPQrzzH+yYGHAYIgCSuKNHcUKCI/e4BWNv/I3bqUO6ZG7hAMOCDkI0PUnc0aMkMSEUdAyiGdiWW+pktndRyiFcmE/evM8JF8njXuNN+oEnkNC63Yag4xBNTxJ39CiWqnIBcNvY6Qzs1Y7rzh5CZtuWtN7/WHKmv8eu2Z/ilclDaOJFq/6HuJK445NkguhRkiD3NYXv+9Xbuez+STz8ymzyy0K0O+oCuv15DK0HHwlKPidxwXEAwkGHIZqefMOjR0lCSEmrcvEL0xZsYtRdE/n3uEWUJramw++uouvl/yC170FBhyYamXIcD3CDjkM0PUnc0aM4IcGRxC0q9fHU1Zx5+wTe+3IFKj2TTn+4hc4XPUBKt/5BhyYaiUpqAZAXdByi6Unijh4lCY4kblG9l8Yv4cw7PuXL2T+Q1Kk3nS+4j8wzbyOxQ/egQxMNLJScCpATdByi6Unijh7FjqOQ1C1qUlbm8sQb8xg1eiKzl24htfd+dL3scTqc/BcS0joEHZ5oEAqV1CIE5AYdiWh60qo8epQAJCaEKC6V9iiiZnm7S7n7+Rlktk3lpvOH0nfQEbQaeDi5sz8lZ/p7uIVSyxqtVFIKyjZOkxJ3HJISd/QoATtqlhB1sWXHbm58cio3/nMqG7cXkX7Q7+j+l7G0OfR0VGJy0OGJenBsNTlI4o5LkgWixw6A1qkywqGon+U/5HDlQ19w74szySmEtiPOpftVY2m9/3HgyOA+0cRJaVn+pyTuOCSJO3pkA7RNk8fvij0za8kWLrznM55+Zz5FTgs6nHA53f70T1r2PwSQRhTRICSJO65J4o4emwDapkviFg1j4ox1nH3Hp7w+cRley3Zk/v4GulzyMC167ht0aKIGESVuaZwWhyRxR49NAO2kxC0a2BufGc66fQKffruWhPY9yDrvLjqdcydJnfYKOjRRhYS0duV/bgwyDhEMSdzRY6freSVSVS4aQ5kLz7y7gHPv+h8zFm0ipcc+dL3kUTqe9lcSMjoFHZ6oICGtA57nlgJbgo5FND3pDhY9PM/1NrdNT5GRNESj2V1Uxt9fmkW79BRuGjWUAf0PoWX/g9k19zNypr1LuKB53FLdkFvMA1PW//R/dn4J5w/uyMgB7X+aVlAS5uFpG9hWUErY9Th9YHuO3TuDDbnFPDR1PWWuxzUHd6F/h1TCrscdk9Zy15E9SImCnhsJbTqC561HyZCn8UgSdxRxHLWmY0ZqN6QFkWhk23OLuHXMdHpmpXHjeUPpPvR4Wg8+ityZH5Lz7Yd4JYWBxtc1PZkxJ+8NQNj1OP9dwyHd036xzMdmO93Tk7n7yB7kFJVx2bgV/HavdCYs38EVB2aR2SqJf83K5o4R3fnE7ODIXm2iImkDJLTp6KGcVUHHIYIRHZ9SAYBSanXn9q3kCls0mbXZu/jLo5P5v399w/b8MjIO+wPd/zKWtANPglDzuO6fvzmfrNZJZLZK+sV0haKw1MXzPIpKXVonhwg5ipCjKA67FIddQo4ivyTMzA27OKp3m4D2oO4S22S6Sql1QcchgiGJO7qsbtM6OZQUJaUCETsWrPiRi+/7nEdfm81uN4n2x15M9z+PodWgIwJ/jOjXa3I5Yq/0X00/uV9b1ucWc967his/XsmfDszCUYqTdVveWrSNx6Zt4OxBHXhj4VbOHtQBJ0oevqcSkgilpoWAtUHHIoLRPC6ZRW2tAejYNpUNW/ODjkXEoa/nbuTruRs5/bd7c84xfel4yjW0Ofg0tn/5CoUr5zZ5PKVhl5kb8vjj/r9uQDdnUz692qbw4LE9yc4r4bZJaxnYcW86tkri4eN6AbBpVzE/FpTSLT2FR6atpyzscf6QTLqmNd8R5RLSfxpvXkrccUqKbtFlNUCndi1rWk6IRvXe5JWceccEPpyyCiejM1ln3U7W+feS3LlPk8Yxe2M+vdumkNHi12WQz1fu5NDuaSil6JyWTKdWSWzYVfyLZf47bwsXDMnkw2XbOW7vtlw8tBOvLdjaVOHXS0KbjuV/rg0wDBEgSdzRZTVA5/aSuEXwXBee/3AxZ93+KVPmbSC5i6bLHx8k84ybSWzXpUli+GptLiP2qvzedIeWSczPtjVTOwvL2JBbTKeI++ALNxfQNjWRLmnJFJe5OAocBcVlzbsZSdLPj2hdEmQcIjhSVR5dtoZdd1vvrm3k2Yyi2Sgpc3nk1Tk81yqJG84byuA+B5La50DyFn7JzilvEc7b0SjbLSp1mbcpn2uGd/5p2nhjt3WSbsu5+3bgsekbuPKjFXjAxUM7kZ5iT3me5/Hmoq387TfdADihTwYPT9tA2PX4S8T6mqOkzJ54bniTckKNc2BFs6c8zws6BlE3H23cmn/inx76Qp4KIZqlLh1acdOoofTqkgbhMLmzxpPzzQe4RdIuoyF0veLJcFL7rhOAU4KORQRDqsqjz3ddOrYKpaZIZYlonjZuy+e6J77mlqensTmnhPThp9L9L2NJP/g0VEJSzSsQVVIJSSS27RwC5gcdiwiOJO7o8x3A3t2ip8+piE9L1+7k8gcm8eB/Z7GrxKHdkefT7apnaL3f0YF3IYtWSR26oRwHJHHHNfn2RJ/ZAH27ZQQdhxC18s2ibM4fPZF/vb+Q0oSWdDjpSrr+6UlS9bCgQ4s6SZk/PfhlQZBxiGBJ4o4+O8Jhd00fKXGLKPPJ9DWcefunvPPFclTrjnQ642Y6X/QgKd0HBB1a1LAN09wC/DEdRHTQWo/WWjdYgzJJ3FEoFHJm9OvZNhx0HELUx8sTlnLmHZ8y6bt1JHbqRefz76XTWbeT1LFH0KE1e8mdenko5oM8XKShaa2H+wm22ZeKJHFHp+/apqWE5BGfIlqVlbk8+dZ8Rt35P75bspkWvQbT5dLH6HDKNSSkd6x5BXFIJSSRnNUbpZzpQccSo4YDdwGSuEWjmAUg1eUi2uUXlXHvCzO59P4vMD/spNXAw+l25VO0O+ZinNS0mlcQR5I790GFEhQwJehY4p3WOqS1DmxcXOlTFJ3meZ7n9unWxpn5/eagYxFij23dWchN/5zK3l3TueHcoXQ58ERa73cUOd+OI3fmx3ilRUGHGLiU7gPwPM9TStW7xK217gbcAxwPZAAbgPHGmGv9+fsDDwCH+C+ZDtxijFkQsY7R2JJpH+A+4ESgEHjcGPOQ1rov8DRwKLAduM0Y82o9Yr0QuBoYABQB84DRxpip/vwE4HbgQqCLvy8vAfcbY8IR6/GAJ4Gp/r7vDawEbjDG/K/CPgGs0VqXv3wvY8zaiHXMBW7z13E08FVtjlk1+/hHfx/7AwXAeOBmY8yW6l4nJe7otNvzWNy3u7QsF7Fl5YZcrnz4S+5+fgY7d7u0PeJs+xjRA04AJ77LGS16DPTw3MVATn1er7Xugu1O+gfgdeAa4C3gJH/+QGxpfgA2ET0ADASmaq37V7LKd4Ey4BZgIfCg1voK4DNgMXAzkAu8pLXuWcdY78Um4d3AHcC92IuAwyMWex4YDcwErsfWRN4DPFvJKo8A/unv981ACvCe1rqdP/99oPzi4q/A+f7Ptoh1HAs85C93HZBdj2MWuY93+fuwxN/mGOBUYLLWukV1r43vb0IUcxw1bUCvdvskJjhOaTMfW1mIupqzbCsX3fs5xxzUnUtOHkj74y4lfdgp7Jj8GgVLpgPxNeKjSkgipWs/lBOatAereRDoABxgjPmpH7jW+g7/z/uAEHCYMWadP+91YJk/7/QK65tujLnKX+4/wCZgLHCZMeYFf/ok//XnY5NvjbTWfbCl2neAs40x5Se4J7TWyl9mMLak/awx5kp//hitdQ5whdb6KWPMwojV9gf6G2PW+K+fjO1Sdw7wtDFmodZ6DjAKGGeMWVtJaH2BAcaY5RGxflDHY1b+up7A/2FL149FTP8U+KZ836o6RlLijl6fJCeGnH33bh90HEI0ms+/+4Gz/+9TXv10KW5qBpkj/0qXSx+hxV6Dgw6tSSV31aiERAV8UZ/Xa60dbGluXGTSBjDGeFrrELZE+X55AvLnrQU+AI7zl4n0fMRyRdhEGAZejphusDUEe1F7p2Fz0z0RSfunWP0/T/R/P17htU9UmF9uYnnS9tezENgF9KpDXF9WSNr1OWblRgIKeF9r3b78B1uFnw2MqC4QSdzR60vX9XYPG/jr5xALEWvemrScM2+fwITpawi160bWuXeSdd5okrN6Bx1ak2jRcxCe54Wpf8O0DkBrbBV2VfNTAVPJvGVAS6BiKeGHCv/nApuNMaWVTK/Lfb1e2AuAZdUs0wNbTb+qwvSV/vSKfQsrxgqws45xVew7X59jVq4PNv+uxlbHR/509tddJUnc0avYcdSnw/fJCisVdChCND7XhbHvL+Sc/5vI9AWbSO42gC4XP0zHkTeQ2DYr6PAaVWrvIS6eNxPICzqWCJWNJVHV+BJBn6UaIq7ChgjE52BjOhY4ppKfm6t7sdzjjm4fZaSlnN67SxtWbqhXexUhok5RSRkPvjyLtmkp3DhqKPv0G07LfsPJm/85O6e+TTg/tr4LCWkdSO7UywHG7cFqtmGT/j7VzN8N6ErmaWyL5x/3YPt1sQp737gfVdcQrMPmr97Aiojpvf3p6yp7UQ3q2nBiT45Z+T6uqOJ+erWkxB3dJnie5w7bR6rLRfzZsauI256Zzl8e/Yp1m/NoPeRYuv15LBkjzkUlpwYdXoNJ1QeV//lBfdfh3yv+EDhNaz0kcp7WWvndpz4Dfq+17h4xrzv2fuzEyC5WjexD7Mhwd/n35n8Rq//nBP/3dRVee63/e3w9tlvg/67VABl7eMw+wO7jnRVnaK0drXXb6rYtJe7o9qPnMX34PlmHvva/ZXIRJuLSD1vyuPqxrxjUux3Xnj2EzENPJ23o8eRMfYddc/6HF654yzW6tOw33PNcd6lynJV7uKrbsFWzU7XWz2LvzXYDzsa2mL4DW007TWs91n/Nldh7xnf8enWNwxizQmv9EPA3bD/pcX4MBwOLsP20F2it/wv8WWudAUwDDsO2En/BGLOoHpue4//+u9b6TaAU+NgYU1DNa+p1zIwxK7XWdwL3aa17Ax9jLxx6Y1ui/52Ixn8Vyck+yjmO+rBnVprTMaPabn9CxLxFq7Zz6d8n8eirsykoS6DdMRfR7c9P02rf30btY0Sd1DRSuvZTynHe3dN1GWPWA8OwVe4XAk9hE914f/73wG+wDatu93+WAocbY5bu6fbrGOttwOVAGnA/dnCUDsDXEYtdiu3HfTDwD//3ncAV9dzmPOzFzWBsH/I3qKGR2J4cM2PM34GzgETgbuBh4ATs+/N5da9Vnhdf/SFjUB9g+b8+WMgn0+SBQUKUO+2I3px3nCYlOZGSHzew48tX2L1idtBh1Unr/Y6iw0l/BhiCPINb+CRxx4Cw6y5bvGp73zue/SbolptCNDsXnzyQkw/tSUJiAkXrl7H9y5cp3lBZD57mp9NZt9Gi137rlBPai3gbdUZUSRJ3bHgwHHZvPu/OT1VBUVnQsQjR7CQlOFx95n78Zr/OOKEQBctnsWPya5T+uD7o0KqkklrQ8/qXPBVKeAK4Ieh4GoLWuqaWtIXGmNwmCSaKReeNH1HRh6GQo4YPiu2+rELUV0mZy2Ovz+X8uz9jrtlK6t5D6XrZ43T43VWE0prn6IOtBhxS/jSwd4KOpQFl1/DzZHChRQ8pcccGFXa9Zas25Ox9w5NT5GJMiBpktUvlpvMPYO+u6eCGyZ01gZxv3sctzA86tJ90vugBNzmr93LlhAYQI9XkWuuja1hkkzFmSZMEE8UkcceOa4F/XPv4V6zeKDVNQtSG7p7B9efuT1b7lnglReR88x65343HKysJNK7E9l3pdsWTYKvIK47HLeKcJO7YkeG6XvZnM9clj3m3xsfACiEiDNunE1edPpiMtBTK8nPYOeVN8hZ8CW5TjTnyS22PupD0Yb8rU8rpzC8fLSmEJO4Y82JxSdmF54+e6BQWSyM1IerqxEN6cuFJ/UlNSaJ0RzY7Jr9KwbIZTRuEk0CP6553nZRWHyilzmjajYtoIIk7thwEzHzm3QV8+u3agEMRInqNOr4fvx/Rm8TEBIqzV7L9i1coWlfVsNkNq6UeTuYZN4EdjON/TbJREVUkcccW5brevPVb8gb95dHJ0khNiD2Q4MCVZwzmqKFdCSUksHvVfHZMfpWSLY070FGns273WvQanK2cUHeqfqqViGNyco8tnuOoMT2y0px+PevymFkhREVlLjz19gLOvWsiM7/PJmWvQXS99FE6nnodCW0yG2WbCW0yadFrP6Wc0AtI0hZVkBJ37Gnlut7mr+duaPn4G3ODjkWImNGhTQo3jTqAfj0ywHPZNfczdk57B3f3rgbbRrvjLiVt6HGlSjk9gU0NtmIRUyRxx6YxpWXulRfdM1HtKgi2W4sQsaZX53RuOG9/umW2xistJnfGh+TM/AivpGiP1uu0aE33a/7tOglJLwGXNEiwIiZJ4o5Ng4CFL368mA++WhV0LELEpP11R64+czDt26QS3p3Hzqlvs2veZxCuX4+ONof/gba/ORtgAPYJU0JUShJ3jHJdb9qOXUXDL7v/81BZWN5jIRrLUQd049JTB9IqNZnS3K3snPw6+d9Poy6DnamEJLpf85zrpLQcr5Q6pfGiFbEgNHr06KBjEI1AKZWdmpJ4/radhaySkdSEaDRrNu3ivckrKQu7DNRdSB94KKn9hlGWs4WynZtrtY60IcfQqv/BSil1KfBD40Ysop2UuGOXcl1v5vbcwqGXPzDJkVK3EI3PceDSUwdxwvDuJCQkULjue3Z8+TLFm1ZW/SLl0O3PY8IJae1nK8c5mBgZl1w0Hkncse1EYPxTb8/js5lyES9EU0lJcrjmrP05dFAnnFCI/KXfsvOr1ynd8euG4i0HkB0FLgAAD2BJREFUHErmyOsBfg980NSxiugjiTu2Kdf1Zv2YWzjkCil1C9HkMlonc+N5QxnUux0AeQu+YOfUtwnn7bALKIduf/qnm9Am0yjHGYT03Ra1IIk79p0IjH/6nflMnLEu6FiEiEvdMltx43lD2atzGl64jNyZn5D77Qe07DecDr+7CmAkMC7gMEWUkMQd+5TretNzC4qHXfb3SU5xqVzQCxGUgb3acd3ZQ8hsm4pbvBvcsOektJqnHOcA5N62qCUZ8jT2eY6jbsloneKcfHivoGMRIq59v3o7l90/iYdfmU0JSYRS05RynDeRpC3qQBJ3fJjqed4nfziqj9uqRWLQsQgR9+Yv34YLrut53wKPBh2PiC6SuOOEUuq2FskJ6oyj+gQdihBx7+xjNKnJCThKXY6UtkUdSeKOH4uUUi+fcnhvr2NGi6BjESJuZbVryUmH7eUppV4EmuYh3yKmSOKOL/8XclTRlacPlit8IQJy4UkDcJQqAu4MOhYRnSRxx5f1jqNuPaB/pjpiSJegYxEi7gzu04FDB3fGcdRDQHbQ8YjoJIk7/oxxXe+7K0bu66a1TAo6FiHiRovkBK49az837HorgYeDjkdEL0nc8SfsOOrSVqmJ3sUnDww6FiHixgUn9qd9mxYq9P/t3XtwlfWdx/HP9/ucnJzk5H4lCdcAIYCwCeEOZbNCwVIFYQUtooIUEd3WbstaHd3xSrfT6k6nM7ZarTPtSsvULdp2uirYleKgbiUWpMhFQFwIECCBhEASkuf32z8Sdi2Lyi35neecz2vmGTLDZT7DHHjPec6T51FZBKDF9R4KLoY7MW0Vke9OHdMXlWX5rrcQxb2rSnNx7eRSiMgPAWx0vYeCjeFOXI/7xu7+h3kVfnLYc72FKG4lJ3m456ZK4xuzD8ADrvdQ8DHciavVU1lSkJPq3Tyj3PUWorh1y5eGolduVD3VxQBOud5DwcdwJ7YNAJ6dPWUgBvbOdL2FKO6U98/GrCmlAPAjAOvdrqF4wXDTvRY4cs+NlcZTcb2FKG6EQ4pv3DTKGGsPALjP9R6KHww3nfBU7hpQnKk3XM3boRJdKV+ZUY6S/DT1VG8HcNL1HoofDDcBwBpr7eoFM8oxcnCe6y1EgTe4TxbmVg8CgOcArHM8h+IMw00AYEVkqQV2fvuWMX5uZsT1HqLASktJwrdvHeNb2EMAVrjeQ/GH4aazmj2V69NSktruu3WMCXn8vJvoYqkAKxZW2fzsFOup/j2ARtebKP4w3PRJO1RlcXn/HF18Le+qRnSxbr5mKKrKC0VF7gbwtus9FJ8YbjrXrwD8YNaUgfhCBR9EQnShJo4owvxpZQDwLICfOJ5DcYzhpvO51xj71j03Vpo+hemutxDFvL6F6fjmglHGGPsnAF9zvYfiG8NN59OuKvNDIW14YNFYk5Iccr2HKGZFIyE8ePs4EwppvarMAdDmehPFN4abPk2tpzKvOD+Kr8+vcL2FKCaJACsWjra9clOtpzoHwEHXmyj+Mdz0WdaLyP2TK0owe8pA11uIYs6C6eUYPbRQRORr4FO/qIcw3PR5vm+tXbNk1nBMqeTFakRnjb+qF26aPgQAngfwtOM5lEAYbvo8VkQWWosN3/zKKFtVXuB6D5FzZX2z8a2bq4wxdhOAuwFY15socTDcdCFaVOU6EdnywOKxZtiAHNd7iJwZUJyBR5dNMEkh/VhVZgFodb2JEgvDTReqSVWmq8qeh5dOMKUlfAwoJZ4+helYeeckPxL2DnmqfwfgkOtNlHgYbroYRz3VqeEkPfTYsommOC/qeg9RjynKjWLl8ol+akpSvadaDeBjx5MoQTHcdLH2e6pToylJx1cun8QHklBCyM9OwXfumuRnRJObPJWrAex2vYkSF8NNl2KnpzI9JyPSsvLOSSYjGna9h6jbZKcnY+XySX5ORuS0pzIVwDbXmyixMdx0qd5TlS8X5UU7Hlk6gXdXo7iUEQ1j5fJJpjA7tU1VpgP4s+tNRAw3XY4NqjJ3YO9M+9BXx9vUCONN8SMaCeGxZRNNSX5au6rMBPCO601EAMNNl+/3IrJg2IAc8y93TTaZaTxtTsEXjYTwyB0TTP/iDKMq1wP4o+tNRGeJtbxvAF0R1xhjX65rOJ304NMb9cjxFtd7iC5JTkYEj94xwfTplW5UZB6Al11vIvokhpuupIm+sa80NrdFH3z6LW9/3UnXe4guSu+CNDy2bKKfkxFpU5XZAF53vYnoXAw3XWkjfWNeb2nryH30uf/S7fsaXO8huiBD+mXj4aXjTUpyqMFTnQHgPdebiM6H4abuMNA35jVjUPrkqhrZ+D6fdEixbdzwXrj3ltHG82Sfp/pFAHtdbyL6NAw3dZc8Y+xvVGXi87/bhpfW834VFJvmVA/E4muHw1rUdF09fsT1JqLPwnBTd4pYa38uIvP+Y+NHeOblrTCGrzeKDSFPcOfckZgxvj+stS+KyCIAp13vIvo8DDd1NwXwXQD/tHnXUfvkqho50dzmehMluLSUJNy/aKwdOShPADwO4CEAxvEsogvCcFNPWWKMfarp1JnQ91/Y5L2/+5jrPZSgBhRn4P7bxprC3FRfRW4H8ILrTUQXg+GmnjTCN/bfVVC2et1OrF67EzxzTj1p1hdKsfi64VYEdZ7qDQA2ut5EdLEYbuppaQCeAnDr1t3H7BOraqShqdX1JopzmWlhfOOmUXb00EKx1v5GRJYAqHe9i+hSMNzkyiJj7I+bW9qTnnhhk/fnXUdd76E4VTkkH99aUOWnp4Z9VflHAD8GwP/4KLAYbnJpWNep86Ev/uFDrHptB686pysm5ClunTkUc6oHwTd2u6cyH8BfXO8iulwMN7mWCuCHAJZ88FG9/d6/bZL6Rp46p8tTnBfFvbeMNgN7ZymAHwFYAYA30Ke4wHBTrLjZGPvs6bb25Od/u01ff/e/wZcmXYqpY/pi+dyRJhTSJk9lMfiQEIozDDfFkiHG2J+qyqTt+xrMUy9u1o8P80EldGEKslOw9PoRGH9VEYyxf1SVhQAOuN5FdKUx3BRrFMAi39gnAGT9dsMe+cVrO9B6xne9i2JUOKSYe/VgzJ862HiqZ1TlIQBPAuCLhuISw02xKhedd1z7an1ji//0mq3eO3855HoTxZhxw3vhjjkjTEF2qlprfyUiKwDsd72LqDsx3BTrJhljn1GV4e9+cNg+89JWqWvg7aQTXXFeFHfMGWGrygvFN3aHp3I3gP90vYuoJzDcFARJAL5ujH3MNybyy7U75aX1u9Hh87WbaCJhD/OnlWFO9SCrIqdU5Z/ReUOfdtfbiHoKw01B0sda+wMRmVt7tNmsenWHbtxSy9umJojJFcVYOnuEn5MR8QD8DMB9AA47nkXU4xhuCqKZvrH/6qkMOXDkpFm9dqe+uZkBj1dV5QW48YtD7ND+OeIbu8VTuQvAW653EbnCcFNQKYAbfGMf9lSG1h5tNqvX7tQNm2t597U4oAKMH1GEG6cNMaUlmeobc9BTfRTAc+DV4pTgGG4KOgUw1xj7sKoMP3TslFm9bqeuf+8AAx5Angqqq3pj3tQyU5Kfpr6xuz2V7wBYBeCM631EsYDhpnihAGZ3BXzk4fpTZvW6Xbq+Zj98BjzmhUOKaeP6Yd7Vg/28rBTPN3arp/I4gF+D77CJ/grDTfFGAFxnjH1EVSqONJz2f/3Gh94bNQfQ0tbhehudIyU5hJkT+2NO9SCTmZasxti3tTPYr4BP8CI6L4ab4pUAmNn1Dnx02xnfvFGzX199Zx/2HGh0vS3h9e2Vjulj+2HauL4mGklSY+1aFVkJ4E0w2ESfieGmeCcARgNYZoxdqCrJu/efMK+8/ZG+ufkg34X3oJTkEKZUlmD6uH6mrG+2Gms7VGQNgO8BqHG9jygoGG5KJFkAFvrGLvdUhp1p983G9w/qG5v2Y8uHR/ntZN1AVTByUB6qR/XG5IoSk5zkadezsX8C4AUAx1xvJAoahpsSkQAYB+A239gFnkrG8aZW/w+b9ntvbq7F3lqeSr9cg/tk4W9H9Ub1qN5nP7tuVpVfAvgpgD+Bp8OJLhnDTYkuAuBaa+1tAGaKiJ442ea/u/2wV7P9CDbvOoJTrTyd/nmSkzwMK81BZVkBxo8o8otyo56xtl2A34nILwD8HkCr651E8YDhJvo/BQBmAviSb+w1nkqGb6zd+XED3v2gTmp21OGjg02uN8YEEaC0OBMVZfmoHFJghw3IRVJIxVjbDmCDdsZ6DYATjqcSxR2Gm+j8Qug8nT7TN/bLnsrfAMDxk63+pu113qbtddiy62hCvRvPy4qgoqwAlZ2x9tNTwx4A+MZs81RfA7AOwAYAfHwbUTdiuIkuTBGAGej8FrNrVCXdWIu6+tP+ngMnvD21jdjbdZxobnO99bJFIyH0K8pA/65j5OB8U5KfpgDgG3PUU30VnaF+HQAflE7UgxhuoosXAjAeQDWASt83oz1P+579yRMnW/3dBxq9vbWN2FN7AntrG1HXcBqx+E8t5Cn6FKahX6+M/w11aXGmn5MZ8c7+Gt/YkyrYKCJr0RnrbeDFZUTOMNxEV0YWgIquo9I3pkpFykXEA4CWtg5z6Ngp1De2aENTK443taGhqRXHT7aioakNx7u+vpLPGE8Oe8iMhpGZltx1hJER7fyxIDsVA4oz/KK8NM9TAQAYa9utxQ5PZQuArZ84asFQE8UMhpuo+0QADAdQ2XX0940tgbXFqpIrInrub2g+fcZvaGpFfWOr19buo6PDoN038H2LDt+gwzcAABWBqkAEEBGEPEVGNIystGSTlZ5s06NhSU7y/t+fDwDG2jPW2EOep+cG+kMA7d3zV0FEVwrDTeRGCEA+gGJ0fn7+V4cxtsjCpsIi2QJJAMIChCFIgoUFYM45OkTkmKocBnC06zjyKV83g++giQKL4SYiIgqQ855KIyIiotjEcBMREQUIw01ERBQgDDcREVGAMNxEREQBwnATEREFCMNNREQUIAw3ERFRgDDcREREAcJwExERBQjDTUREFCAMNxERUYAw3ERERAHCcBMREQUIw01ERBQgDDcREVGAMNxEREQBwnATEREFCMNNREQUIAw3ERFRgDDcREREAcJwExERBQjDTUREFCAMNxERUYAw3ERERAHCcBMREQUIw01ERBQgDDcREVGAMNxEREQBwnATEREFCMNNREQUIAw3ERFRgDDcREREAcJwExERBQjDTUREFCAMNxERUYAw3ERERAHCcBMREQXI/wAVsCjZGtgWowAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NOXN9MfYyXOm"
      },
      "source": [
        "###Observando graficamente os valores de tempo"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_KVVmeatyWJg",
        "outputId": "617920d4-2463-44f2-8256-8b49c0858d5c"
      },
      "source": [
        "barplot_time = dados['tempo'].value_counts().plot.bar()\n",
        "barplot_time.set_title('Distribuição dos experimentos por tempo')\n",
        "barplot_time.set_xlabel('Tempo observado')\n",
        "barplot_time.set_ylabel('Nº de experimentos')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Nº de experimentos')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 154
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fxZmIz8hmxEnUsA5uv5ynic/5RUTNf12iCflu4hJJSaXHrCzV9Kb3e+LM/DKiSXIDYodv5O4bVvBB+4IYU7UYMSblPKKJ7yai6/E7mbR7ER+socRYkyurUP5DiQ/H3kTPym+Iru7Tdd919yuI5tb+xHW3bVP6soO489J1yZ8TNb2FicHB5xADirOdLg5k2pidvxBB5kLKdPVP+3YtorfmxkQvtY1Tmdb2CmaXcPcHiGP2UtrGYcT4ne3LpP2GuEZ3Yir3GcR+uJY4Vm9mkp9KjGnblzimexDjhNZw9ycrKNdRRI+4d4iOTucQQbN3yhMzWya95/vJTA+Vml5/D8zPjL3zPid6/PVO72MXYlzd2j5tKEgpn53Sfpia9kvpeHyWnnc5d7+U+PF6AtidGMv2B+JzegTRLb49+d5HfDeWAC4ivmtbpHWvA6sTx31b4nOwGlEr3ijT1P4m8Feig9PhxInj5im/tbyNAdEZlX5HzyXGHH5MfB7+nP4f5GUG9bfDlcTnem3iBPBK0oD19NlfhTi5XSelO4Y4mR1N1Mpr4XFin67JtAkHzgZ+lesVXukxK6upublqcyhLg0rNifcAVub6mNSApRlZ3H3RLi6KVMC64I4sPYm1MEtULaimJx2WxsW9QwwgFRHptnRNT9rNzBYmrnN+SVzzaG9HAxGRTqGgJx3Ri7gmNS9xYbyS+UFFRLqMrumJiEjDUE2vuiYT10nbmqpMRESmmZvoWVzzmKSaXnVNbW5ubqrXXdqUhpnX6/urZzp2PVu9H7+mJmhqamqmEzpXqqZXXZ80N9Pngw+660xPHdOnT0yUMXGibn7e0+jY9Wz1fvzmnXdOmpo6p4VMQxZERKRhKOiJiEjDUNATEZGGoaAnIiINQ0FPREQahoKeiIg0DAU9ERFpGBqn14PNMUdvevXqvPOWXr3ixt+lMUO1NnnyVD7//KtO2ZaINAYFvR6sV6+Z+HpKM6++3dGbKHc/i32vD7N2YkAXkcbQpUHPzJYCjiXumN0PeJ24Ff3p7v5VJt2awHBgZWJey6uBw/J3Kzaz3sTdiLdL+T0JDHX3O8psu6I8u7tX357In867r6uLUXXH77kW9n99u7oYIlJnuuxU2sy+BzxM3Pb9bOAA4DHilu8XZ9KtCNwBzAYcmNbtTgSpvBEpn8uB/YgJTG8xszVy2y6Sp4iI1ImurOltC/QF1nb3Z9OyC81sdmArM9vJ3b8Bjgc+AAa6+2cAZvYacJGZrefud6ZlqwFbAQe4+xlp2UjgGeAkYJ3MtivKU0RE6ktXXjSZOz2+m1v+P+AbYIqZzQ1sAIwsBadkJPAZsGVm2Rbpdd/WEt19EnAJsLaZ9QcomKeIiNSRrqzp3Q38CbjEzI4EPiRqY4OBk9x9qpn9gCjjo9kXuvvXZjYWWCmzeCXghVwgg2hCbQJWBMYDRfIsrKmp83o3lnpT1qtevWbutH1Z7zq7561UV70fv9KtkzpDl9X03P0/wBFErWss8AZxLe4kdz8qJeufHseXyWI8sFDmef9W0pFJWyRPERGpI109ZOFV4C7gBuIa2y+Bo8xsgrufD5ROa8oN1pqUWU/6v6V0ZNIWybOw5ubOu+dVvZ71lUyePKVu7x/W2er9fmz1rt6PX7qfXqfosqBnZlsBFwBLu/s7afH1ZjYTcIqZXQ2UjnDvMlnMlllP+r+ldGTSFslTRETqSFd2ZNkLeCwT8EpuAuYAfsi0Jsj+zKg/kH3t+FbSkUlbJE8REakjVQl6aVB4UQsA5XpizJIeexHDDSYDP8ptb1aiY8rYzOKxwDJmNmcuv9XT45PpsUieIiJSRypu3jSzjYDV3X1YZtlewInAd8zsGmCHNLauEi8CG5jZEu7+Smb574EpwFPuPtHMbge2M7PjMz0ztwPmBK7NvO464I/ALkBpnF5vYEfgvlKNsmCeIjVR7/OmQn3Pnarj13MVuaZ3MPBe6YmZDQDOBF4hOqT8jhgecEaF+Z0MbATcZ2ZnE0MWNknLznf30raGAvcDd5nZxcD3gYOAW9z99lJm7v6QmV0LDE9j8l4BdgAWIYZBZFWUp0it1PO8qVD/c6fq+PVcRYLeAOBfmee/Izp9rObun5jZ34kgU1HQc/cxaf7LYcDewLxE8DyMCIildI+b2frErCqnE/NkXpTS5W0PHJMe+wFPARu7+3STUxbMU6Qm6nXeVGiMuVN1/HqmIkGvH/B+5vn6wJ3u/kl6fhewcZGNu/vDlbzG3e8lJqVuK90kokZ6cLXyFBGR+lGk/vo+0VSImc0FrArck1k/C+U7poiIiHQLRWp6DwB7mNmzxHW3XsAtmfVLUn6WExERkW6hSND7M/Bf4Jr0/DJ3fw7AzJqAQWm9iIhIt1Rx0HP351KPzbWAie4+JrO6L9Eh5K7qFk9ERKR6Ck1D5u4fAqPLLP+IGL4gIiLSbRWee9PMlgA2AxZPi8YBN+YGmIuIiHQ7hYKemR0DDGHGXprD0+wmR1atZCIiIlVW8ZAFM9uJmMnkIWBzYKn0tznRs3OomQ2uQRlFRESqokhNb28i4A1098mZ5a+Y2b+IMXt/AEZUr3giIiLVU2Rw+gDgqlzAAyAtuyqlERER6ZaKBL2vibsQtGSulEZERKRbKhL0HgF2N7MF8ivMbH5gN6L5U0REpFsqck3vGOAO4HkzuwR4Li1fjrhn3VzANtUtnoiISPUUmZFljJn9GjibuPdc1hvEDWTvmfGVIiIi3UPRGVlGm9k/gVWAxdLiccDj7j612oUTERGppoqDnpmtAzzv7hOI63uP5NbPByybm5NTRESk2yjSkeW/wAatrP8ZusuCiIh0Y0WCXlMb62cG1MQpIiLdVpGgB9Dcyro1iburi4iIdEutXtMzs/2A/TKLzjCz48ok7QfMDfy1imUTERGpqrY6snwMvJ7+XxT4AHg3l6YZeAZ4kLiRrIiISLfUatBz98uAywDM7FVgiLvf1BkFExERqbYig9MXazuViIhI91X4zukAZvYdYF7K9Oh09zc6WigREZFaKDI4fSbgEOKeeQu2kjR/V3UREZFuoUhN70Tgj8CzwD+ITi0iIiI9RpGgty3wb3ffuFaFERERqaUig9P7ATfWqiAiIiK1ViToPQ30r1VBREREaq1I0DsK2MPMFq5VYURERGqpyDW9VYjZWZ4zsxuAV4EpuTTN7n5MtQonIiJSTUWC3rDM/9u2kKYZUNATEZFuqUjQ04wsIiLSoxWZhuz1tlOJiIh0X+2dhmxJYAHgGXefWN0iiYiI1EahoGdmmwBnErcZAtgAuNPM5gfuJ+7CcF1VSygiIlIlRebeHAjcAIwlbjc0rLTO3d8zs1eArYBCQc/MVk15rQnMArwCnO7uIzJpNk1plgXeAy4BjnP3ybm8+gLDgUHAd4CHgAPdfWyZ7VaUp4iI1I8i4/SOBJ4EVgfOKbP+AWDlIhs3s42A+4hgdwRwEHA7sHAuzSjgQ2Ky61GpLKfn8poJ+CcReP9CTI69AHCXmS1RZrtt5ikiIvWlSPPmqsCR7j7VzMqtf4vW774wHTPrA4wAznP3/VpJegrwBLChu09Jr/0EOMzMznL3l1K6LYja4iB3H5XSXQO8CPwZ2L4deYqISB0pUtObCfiqlfXzAV8XyG9roC9Rw8LM5jKz6e7PZ2bLEs2PF5SCU3JuKs9vMsu2AN4hMz+ou08ArgE2N7NZ2pGniIjUkSJB73ngJ62s34Ro/qzU+sALwMZm9ibwCfChmZ1oZqV78q2UHh/NvtDd3yFqlitlFq8EPObuzbntPAzMBSzZjjxFRKSOFGnevAQ4y8xuB25Ky5rTXdRPBNZg+ibEtixJXLsbQXQ+eYIInIcCswH7M22C6/FlXj8eWCjzvD9wZwvpSGmfL5hnYU1N0KfP7B3JomK9etX3/Xp79Zq50/ZlZ6v3Ywc6fj1dZx6/pqa201RLkcHp55nZWsBFwKnElGNXAvMSd0u/1N2vKLDtOYnbFQ1x95PSsuvNbE5gLzM7Fijt8XLNqpOIHpols7eSrrQ++1hJniIiUkcKjdNz923N7B/E3JvLAE3EsICR7v6Pgtv+Mj1emVt+BfBbYLVMmt5lXj9bZn0pv5bSZbdXJM/Cmpth4sQOZVGxej2LLpk8eUqn7cvOVu/HDnT8errOPH7zzjtnp9X2Cs/I4u43EOP1Omo8sBzwbm556Xk/pjVB9mfG5sj+xID4bH7l7vdXWvZOJl2leYqISB0p0pGl2h5Lj9/LLf9+epxADIQH+FE2gZktlNJlB52PBVbJ9wAlxhV+BrycSVdpniIiUkeKTkM2BzHUYCniWl4+wDS7+84VZnct0WllZ2Boyr8J2AX4HHjQ3T8xsxeA3czskswQgz2BqUC2SfU6YtjCZsRgc8xsPqKp9EZ3/wbA3Z8tkKeIiNSRItOQrUn02pynlWTNRBBrk7s/ZmYjiQHh8wOPA78ENgQOcfdPUtKD03ZvNbOrgeWBfYhxdi9msrwOeBAYaWanAO8DexG12WG5zVeap4iI1JEiNb2/EDWhzYB73P3jKmx/V+ANYIf0Nw7Yw90vKCVw95vN7NfErCp/IZo9jyV3s1p3n2JmGwMnA/sSvTQfBrZ395dzaSvKU0RE6kuRoLcsMQ3Z6Gpt3N2/JubcPKKNdKNITZZtpPuIaB7dpYK0FeUpIiL1o0hHlvHAN7UqiIiISK0VCXoXA1tnpggTERHpUYo0b55ATNH1gJmdB7wGTMkncvcx1SmaiIhIdRUJerMTwxRWIWp9eU1E703VBEVEpFsqEvTOAbYkOn/cA3xUkxKJiIjUSJGgtxnwV3fftVaFERERqaUiHVmagEdqVRAREZFaKxL07iLmsRQREemRigS9/YGBZnagmc1aqwKJiIjUSpFrev8F5iCm+TrRzMYz45CFZndfolqFExERqaYiQe8NYkiCiIhIj1Rx0HP3gTUsh4iISM115U1kRUREOpWCnoiINIwWmzfN7FXi/nnLuPs3ZjaugvzUkUVERLqt1q7pvU50XCl1XlFHFhER6dFaDHr5jivqyCIiIj1dRb03zWx24LeAu/tDtS2SiIhIbVTakeUr4nZCK9WwLCIiIjVVUdBz96nENb25a1scERGR2ikyZOEyYDsz612rwoiIiNRSkWnI7gd+DYw1s3OBl4Av8oncfUyVyiYiIlJVRYLebZn/z2TG4QtNadnMHS2UiIhILRQJejvWrBQiIiKdoMiE05fVsiAiIiK1prk3RUSkYRRp3sTMFgaOAn4OzA/8wt3vNLPvAicB57n7I9UvpoiISMdVXNMzs8WAR4HfAM+S6bDi7hOAHwG7VLuAIiIi1VKkpncccdeF5YEvgfdy6/8F/KpK5RIREam6Itf01gfOdfc3KX+3hdeB71elVCIiIjVQJOjNDYxvZf2sFLxGKCIi0pmKBL03geVaWf9j4OWOFUdERKR2igS964GdzGz5zLJmADP7DXHroWuqWDYREZGqKhL0jgPeAh4CLicC3hAze4AIdk8Cp1a9hCIiIlVScdBz90+ANYj76v2ImGtzA8CAc4F13X1SLQopIiJSDYU6nqTAtx+wXxqQ3gRMcPdyvTlFRES6lXb3tkwD0qvKzA4hZnZ50t1XzK1bExgOrAx8AlwNHObuX+TS9QaOBrYD+hHNrkPd/Y4y26soTxERqQ+Fg56ZbQkMAhZPi8YBN7h7hzqxmNmCwOHA52XWrQjcQcwEcyAxHvCPqQz5AfEjiFljziB6kw4GbjGzn7r7A+3MU0RE6kDFQc/M5gBGAesRzZofp1WrAlua2e7Apu4+Q9Cq0InENGczAX1z644HPgAGuvtnqTyvAReZ2XrufmdathqwFXCAu5+Rlo0EniFqkOsUzVNEROpH0d6bPwP+Aizk7vO4+zzAQmnZuilNYSlYbUvUuPLr5iY6zIwsBadkJPAZsGVm2RbAN0RnGwBS55pLgLXNrH878hQRkTpRJOj9DrjW3fd39/+VFrr7/9x9f+AfKU0hZtZEBM3L3H1smSQ/IGqkj2YXuvvXwFhgpczilYAXcoEM4GGidlq6TlgkTxERqRNFrunNDfy3lfV3Ahu3owzbA8sCm7ewvn96LDcF2nhiGEU27dstpIOolRbNs5CmJujTZ7cJuhQAABnMSURBVPb2vryQXr1mbjtRD9ar18ydti87W70fO9Dx6+k68/g1NXXKZoBiNb2ngKVaWb8U8HSRjZvZXMS1vBPdvaV5PUt7/asy6yZl1pfStpQum1eRPEVEpE4UqekdDtxgZne5++jsCjPbjLiXXku1tdby/Bo4rZU0X6bH3mXWzZZZX0rbUrpsXkXyLKS5GSZObPfLC6nXs+iSyZOndNq+7Gz1fuxAx6+n68zjN++8c3Zaba9I0NsGeBUYZWYOPJ+WDyBmZXka2NbMts28ptnddy6XWepUsj9wBLCAmZVWzQbMamaLAhOZ1gTZP59HWvZO5vn4VtKRSVskTxERqRNFgt7gzP/LpL+sFdJfVjNQNugBCxC3Izop/eW9mpafAEwmpj67vrTSzGYlOqb8PfOascRsMXPmOrOsnh6fTI/PFMhTRETqRMVBz92LXP+rxKvEIPe8Y4E5gAOAF919opndDmxnZsdngtl2wJzAtZnXXkcMMN+FGJxemqFlR+A+d38nvZcieYqISJ3ospu+uvtEYrD7dMxsf2Cyu2fXDQXuB+4ys4uJ2VMOAm5x99szeT5kZtcCw1Pz6SvADsAiTF9TrThPERGpHxXX3sxsvQrSHNCx4pTn7o8D6xO9LU8HdgUuIu7hl7c9cGZ6PAuYBdjY3e/rQJ4iIlIHitT0bjOzE4Aj3X1qdoWZzUfMZrIhEUDazd0HtrD8XmCtCl4/CTg4/bWVtqI8RUSkPhS5TncV8CdgjJktXFpoZusTY/h+Bhxa3eKJiIhUT5GbyG5DdBBZEXjSzLYys5OAW4EvgLXd/ZTaFFNERKTjCvXIdPe/AqsQU31dQfSUvBJYyd0fqX7xREREqqc9wxCWA74HTCUmcZ6P8jObiIiIdCtFem/2NrPziDFs44jg90dgINHc+bOalFBERKRKitT0HgV2B84G1nT3F939NKL34xfArWZ2fA3KKCIiUhVFgl5/4s7o+6X7zgHg7o8RnVuuRL03RUSkGysyTu+H7l7uXnW4++fElF7/qU6xREREqq/I3JvfBrw0n+V8wIRcre9v1S2eiIhI9RTqvWlmK5vZncCnwBvA2mn5/GZ2RxqoLiIi0i0V6b25InAPsAQx5di33P094m7jO1S1dCIiIlVUpKZ3NHFz1eWAIcQYvaw7gNWqVC4REZGqKxL0fgJclO4911xm/RvAQlUplYiISA0UCXqzARNbWT93B8siIiJSU0WC3ivEvJstWQ94rmPFERERqZ0iQe/vxFi8bA/NZgAzOwj4BaAhCyIi0m0VGZx+CrABcSuhF4iAd7qZfRdYELgNOLfqJRQREamSIvfT+5oIen8EvgQmAUsD7wOHAJvk76guIiLSnRSp6eHuk4HT05+IiEiP0p776YmIiPRICnoiItIwFPRERKRhKOiJiEjDUNATEZGGoaAnIiINo9CQhRIzWxJYAHjG3Vubj1NERKTbKBT0zGwT4Exg0bRoA+BOM5sfuB8Y4u7XVbWEIiIiVVLkJrIDgRuAD4GjyNxPL91E9hVgqyqXT0REpGqKXNM7EngSWB04p8z6B4CVq1EoERGRWigS9FYFrmhlfs23iImnRUREuqUiQW8m4KtW1s8HfN2x4oiIiNROkaD3PPCTVtZvQjR/ioiIdEtFem9eApxlZrcDN6VlzWb2HeBEYA1g+yqXT0REpGqK3E/vPOBq4CLgJeImslcCE4F9gBHufkUtCikiIlINhWZkcfdtgd8AdxB3T/8Q+BfwW3ffufrFExERqZ7CM7K4+w3EeD0REZEepV3TkFWDma0KDAbWBRYBPiBmdTnc3V/OpV0TGE6MA/yEaGY9zN2/yKXrDRwNbAf0IzrWDHX3O8psv6I8RUSkfrQY9MzsyHbk1+zux1SY9lBgLeBa4ClijN8+wBNmtpq7P5/KsSLRnPoscCDwfeCPwOLAr3J5jiCaX88AXiaC6i1m9lN3fyDz3orkKSIidaK1mt6wMsua02NTmeVN6bHSoHcasLW7fzu2z8yuBp4mAuLgtPh4ohY40N0/S+leAy4ys/Xc/c60bDViGrQD3P2MtGwk8AxwErBOZtsV5SkiIvWltY4si+X+fgCMBR4FtgZWTH/bAI8Bj6c0FXH3+7MBLy17iah9DQAws7mJSa1HloJTMhL4DNgys2wL4Bvg4kx+k4ihFmubWf925CkiInWkxZqeu7+efW5mZxEzsqzj7pMzq54ys+uAMcAewL7tLYyZNRG3LCoNcv9BKuOjubJ9bWZjgZUyi1cCXsgFMoCHiVroisD4gnmKiEgdKdKRZUvg+FzAA8DdvzGzq4AhdCDoEbXG7wFD0/P+6XF8mbTjiQHxZNK+3UI6gIXakWdhTU3Qp8/sHcmiYr16zdwp2+kqvXrN3Gn7srPV+7EDHb+erjOPX1P+glkNFRmnNzfQp5X1fdtY3yozW4a4e8O9wN/S4tIeLzfn56TM+lLaltJl8yqSp4iI1JEiNb0ngH3M7O/u/kp2RbqT+t7Edb3CzGxB4J/AR8RA99KdHL5Mj73LvGy2zPpS2pbSZfMqkmdhzc0wcWKHsqhYvZ5Fl0yePKXT9mVnq/djBzp+PV1nHr95552z02p7RYLeocBtwLNmNgrwtHwZYDOi5+aQogUwsz7ALUQtcS13/19mdakJsv8ML4xl7+TStpSOTNoieYqISB0pMvfmvcBAoja3JXBE+vttWrZuSlMxM5sNGA0sDWzi7p5L8gwwGfhR7nWzEh1TxmYWjwWWMbM5c3msnh5LnWOK5CkiInWk6NybD7n7mkQPyzXS34Luvqa7P1gkLzObmZgFZQ2iSXOG17v7ROB2YLtcMNsOmJMY2F5yHTALsEtmG72BHYH73P2dduQpIiJ1pF3TkLn7BGBCB7d9KrApUdObx8y2zaz7zN1Hpf+HEtOT3WVmFxOzpxwE3OLut2fK9JCZXQsMT2PyXgF2IKY4G5zbdkV5iohIfSlU06uyFdPjr4jemtm/M0qJ3P1xYH2it+XpwK7E7Y1+WybP7YEz0+NZRM1vY3e/L5uoYJ4iIlInumzCaXcfWCDtvcQ8nW2lmwQcnP6qkqeIiNSPrqzpiYiIdCoFPRERaRgKeiIi0jAqCnpmNkeZ8W8iIiI9SqtBz8z2NbM3iDuLTzSzt8xs/8z682pdQBERkWpp7c7pRwE7AecSs5g0E7flOcDM5nH3I8nNaiIiItKdtTZkYRtgNXfP3oLnZjO7FLgPOLKmJRMREamy1po3p+QCHgBpQuivy6QXERHp1lqr6Y03syOA4e7+FYCZzUIM/H4vpWmucflERESqprWgty9xy5+DzOwlIsAtSdxodaOUphPvdysiItIxLTZvuvtTRJA7GBhD3NH8UGBJdy/dpmf3mpdQRESkSlqde9PdvyQmYm5pfbvulC4iItIVNCOLiIg0jFZremZ2U8H8mt19sw6UR0REpGbaurXQJgXzU29OERHpttq6ptdm86eZ/RQYDqwKzDCuT0REpLto901kzWx54CTgF8CnwBHAaVUql4iISNUVDnpmtjBwDDFN2RTgLOBYd/+gymUTERGpqoqDnpn1A4YCewG9gSuBw939tdoUTUREpLraDHpm1hvYnxiY3he4DTjU3cfWuGwiIiJV1daQhZ2BYcBCwOPAEHe/oxPKJSIiUnVt1fQuIoYhPApcA/zQzH7YSvpmdz+9WoUTERGppkqu6TURwxFWrSBtM6CgJyIi3VJbQW/dTimFiIhIJ2hrcPrdnVUQERGRWtOE0yIi0jAU9EREpGEo6ImISMNQ0BMRkYahoCciIg1DQU9ERBqGgp6IiDQMBT0REWkYCnoiItIwFPRERKRhKOiJiEjDUNATEZGGUcmthepWuiv80cB2QD/gSWCobpQrIlKfGr2mNwI4ALgc2A+YCtxiZmt0ZaFERKQ2GramZ2arAVsBB7j7GWnZSOAZ4CRgnS4snoiI1EAj1/S2AL4BLi4tcPdJwCXA2mbWv6sKJiIitdHU3Nzc1WXoEmZ2G7CAu6+QW/4z4HZgY3e/pWC2U5ubm5uqVcaKNzq1/o7hTDN1+m7sEvV47EDHr6friuPX1NTUTCdUxBq2eRPoD7xdZvn49LhQO/Kc2tTUNBPwSbtL1Q4zz9wYPzD1SMeuZ9Pxq5q5iT4VNdfIQW924Ksyyydl1hfVyPtTRKTba+Rrel8Cvcssny2zXkRE6kgjB73xRBNnXmnZO51YFhER6QSNHPTGAsuY2Zy55aunxyc7uTwiIlJjjRz0rgNmAXYpLUgztOwI3OfuqumJiNSZhh2yAGBm1wCbA6cDrwA7AKsC67r7fV1ZNhERqb5G7224PXBMeuwHPEWMz1PAExGpQw1d0xMRkcbSyNf0RESkwSjoiYhIw1DQExGRhqGgJyIiDUNBT0REGoaCnoiINAwFPRERaRiNPjhdcsxsALAl8AUw0t3fNbO+wEHAWsRn5nHgLHcf13UlFWk8Zjaru3/d1eXoyTQ4Xb5lZqsA9zDt9kpvAz8BbgaWAp4n5is14FPgJ+7+TBcUVVphZosAywDvu/tjLaRZjDh+Izu1cNJu6biOAwa5+01dXZ6eSjU9yToSeBfYJD1eAtxCBMHl3P1lADNbGbiNmMJtUNcUVfLMbCbgAmCnzLKXgb3d/fZc8jWBSwEFvW7CzDZtI8n8QBOwupkBoOBXnIKeZK0KnOHuzwKY2ZHAE8CepYAH4O6Pm9nZwD5dU0xpwa7AzkQwu4G4N+T+wL/N7DB3P7krCydtGgWUmt6aWkjTDAxJ65uBmTuhXHVFQU+y5gI+zDz/ID3+r0zadyh/53npOrsB17v7zqUFZjYCOAc4ycy+7+77dVXhpE3vAd8BTgbGlFnfH/g7cDigSfHbSUFPsl4B1gYuTs/XSY/rAjfm0q4PvNpJ5ZLKLAWcn13g7t8Au5nZS8CJZrYAsF1XFE7atBRxiWEo8APgEHd/rbQyXdMDeMbd7+784tUHBT3JOh8418xmI846BxM9Nfua2anATURzylbAr4kvqHQfnwFzl1vh7ieb2QTgImBe4PrOLJi0zd0/BQ42s4uIe3w+b2ZnAce5+yddW7r6oaAnWRcASwB7EM0sDxK1gk+BO4jrQxDXE24DTumCMkrLngF+DpxabqW7jzCzj4ArgTU6s2BSOXd/EfilmW0MnAYMTtfX852RpB00ZEFmYGZNQK/UNFZaNjPR3LkA8KK7P95V5ZPyzGxv4CxgeXd/vpV06xC19rncXR0hujEz60WcbB4OfAwsjIYsdIhmZJEZuHtzNuClZVOInpwrEAPXpfv5K3F83mstkbuPSenW64xCSfu5+2R3P4UYG3tT+hvftaXq2VTTk4plBsdu7u6ju7o8Mj0z6+/u+kEUaYWCnnzLzNpqspwVWJbotTkRaHb3VWpeMKmImU0lrutdAVzp7m90cZGkIItR54cCA4D3gavd/fIy6TYDTnf3xTu5iD2emjcla0VgSSKglfv7NKX7Ij1Xj7LuZ3HgBGCcmd1tZruZWb+uLpS0zcyWAB4Bfk9M97ciMNLM7jKz+XPJ5wQWQQpT703JGkKMEZoCHOjuT2VXmtmiRPPmUF1I77Z2B14DtgF+SwxDOcvM/k3UAEe7+6SuK5604ljgc2JO1NKUf9sCZwMPmNmG2ZmRpH1U05NvuftwYGngLeBRM7swd4aptvDur9nd73P3vYgZPDYlxuStD1wFvGtml5rZ+qmXrnQfawJ/yU35dznw4/T0fjNbtUtKVkcU9GQ67v6uuw8mZmZZAXjJzIaYmaYc62FSz7+b3X1rYqjJDsD9RC3wVuIuGtJ9zEuZKf/c/QUiIL4N3GlmG3Z2weqJgp6U5e4Pu/uPgX3T3wtEc5lqez2Qu3/u7pe7+0bAQsB+RDOodB+vEyeaM3D3d4GfEsOGbiK+i9IOCnrSKne/jGjyvIa45qAmsR7O3d9397Pdfc2uLotM5y7gt2lA+gzSVGQbAP8mmq2lHRT0pE3u/pm7HwosCqxEfDml+7mMmDRceqZLiebnH7WUwN2/Iu5heRbl78QgbdA4PRERaRiq6YmISMNQ0BMRkYahoCdSx8xssJk1m9nAri5Ld2BmI8xM13QamGZkkR6j4I/VYtm7TouIgIKe9Czb5Z7/BNgNuBC4J7duQqeUSER6FAU96THys82n8Uy7AQ+Um4leuqd0Q+Le7q77MkqnU9CTupPmlNwD2IW4RctUYvb6o939v5l0ixK3SToKeA74E3GzzreB49z9UjP7P+A04oarswA3Anu6+6eZfEYQU3zND5wK/BKYDXgQODh/l/kUrA9Kr1mcmGR4DHCkuz9d4XucL5V7U2KKsXeJmTqOdPcPyrykl5kNA3YEFgQcON7dr8rluyZwBDEesy/wAfBk2ncPZtL1SfvrN8TdvD8BbicmIx+XSTeYGH+2AbAGMBj4P2BXM9uTGPv5PXefnCvHhsQg7APc/Qwzmwk4DNiQmCxhHmLKrn8Ch+ffs5nNBhxDTLnWD3iauPt4Welu8kcAqxG30HoeOMfdL2npNdIzqSOL1KO/ETPTvwwcAvwZ6APcZmblZrLYhBjsez1wMHELpb+a2TZEs+mnxA/8NcSP6OktbPffxCTPw4AziEHGd5vZ8rl0VwAnEhN7H0zcCWFdYib9ldp6cyng3A/sScyhuX/a9p7AvWY2V5mXnQRsBZwLHEn8sF+ZglIpXwNuI4LKmcBexH5sBn5YZvt7EUHnDyndesBD6WbDeaek7V9ETIHmxGD6+YFflEm/PTAZ+Ht6Piuxr14CTiamxrsN2Bm4y8xmzb3+SuCPwKPp8V7i+M5w/0cz+xVwJ3GCdCpxrL8BLjaz48qUTXow1fSkrpjZICIw7e7uF2aWn0nUvM40s9Hunu0UMwBY1t1fT2mvBt4kgucf3f20lO78dG+67c1sf3f/LLf514HflPI2s+uJGuYppB92M9sA2JIIoFtl0l4DPEYE35+08TYPAZYC9nb3czPvcSwRfA4hai1Z8wEruPvElPZ84CngNDO72t2/JGpR3wF+7+4Pt7L9o4ka6o/d/cnM9kcQNaqjiBpd1uzAStkmTTNz4gRie+DmzPK5gM2BW9z9vbT4K6B/KmfJ+WZ2P3BxSn9Nev3P0/PL0uTppXzHADdkC5WaWs8GPgNWc/d30vJzgP8CQ8xshLu/1Mr+kB5ENT2pN9sSNbNRZjZf6Y9oqhtNNKctlXvNqFLAA3D3CURNZCpwTi7tPUQz56Jltj08G0zd/TGiNrK+mc2ZFg9Kj8fl0j6Zyre2mX23jfc4iOioc2Fu+QVp+aAZXgHnlQJe2t5EoobZDxiYFpfWb5aaB2eQmo63IZpj387t48+JE4uft7D96a7hufuHxHv+lZn1zazaggi+l2XSNpcCnpnNbGZ90zbvTElWz7x+8/R4cm57o4jjmrUK0dz611LAS2m/BoYTv5GbldsX0jMp6Em9GQDMRVzjmpD7G5bSLJB7zThm9BEwPs11mF8OcRuYvOfLLHsOmJlpd7lejAim5dI+m0nTmsUAz18HS89fJGphlZaNTPqriOtyfwI+NLM7zezQXHPld4n3/nNm3L8TiGt3+f1LKlc5lxHXP7fMLNue2M+jswnNbEszewj4Mq2fwLRjl707/OLEPi63zfx+KO3rZ/MJM8vK7U/podS8KfWmifgx3LqVNM/knk9pIV1Ly0vbqSspwG9gZqsRTZ3rEE2Zw8xsa3e/gWnv+3biOmGlWuqpeQtxvLYHLkwdh34KnJ9qWwCY2a+Bq4GHiWuCbwKTiBOKf6MTeKmQgp7Um5eIjhgPlrnmVmsDiOa9rGWJ4FlqPh1H/EAPIK6p5dNC9ChtzTii30mvbG0v9QpdmvI11wFEz9Ny25sufbqe93DKc2HiHm7HEtfDJgAfA3O7++1tlLNN7j7ZzP4O7GdmiwO/JwLrZbmk2xFBbt3cdcFlymRb2sdLM2MNbkCZtADLlcmn7P6Rnk1nR1JvRhKf6xPKrTSzck1v1XJIuuZV2tbKwPrAHZkAPCo9HpZLuzwx/ODedE2xNaOIZsZdcst3TctvmOEVsGfqdVnaXh9iWMfHwN1p2XxlXvcWEejmAXD3qUTv09XMbItyhTOz+dsof14pwG1PBDd394dyaaYQvUi//c1K+6/cMIRScD84V67NiSEpWY8DbwA7mtmCmbSzpNc3M+PJgvRgqulJXXH368zsUmCfFHRuBt4Hvk+ME1uS2l2jWQS41cxuIoYu7ENcf/r2x9fdb0s9NbcC+pnZzcS4ub2Jmsy+FWxnOHHn7HPSe3yCGFe3M9FRY3iZ17xPDCe4ND3fkejAsUum5nR46vl4M1HbbAJ+BSyTy3MosBZwTXovDwJfp/e/MdELdXAF7wMAd3/CzJ4GDgDmJq4p5l1HjAm808xGEp2JNic6vOTzu9XMRgM7mNk8RPPnEsDuRNP28pm0U8xsH+JE4REzu5DoCPU74MfEWEb13KwjqulJ3XH3nYhaw1RiQPNfiIHgn6XntfILogPNUcQP+GPAT90934y5DTCECBKnEuPd7gbWcPcn2tpI6nm5FtFbc2NimMPGRG/MtbMD5zMOJa6J7U1cp/sG2CY3+HoUMeRgS2JA/rFEDW/XVN789v9MNAueQFzf25QIgOe19R7KuIwIeFOBGWbXSYPodwPmJIaAHEIE+A1byO936T2sRuzjnwC/Jo5JPu/RwM+AF4gTlBOJzjW7uPvQdrwX6cZ0E1mRDirNyOLudde5RaTeqKYnIiINQ0FPREQahoKeiIg0DF3TExGRhqGanoiINAwFPRERaRgKeiIi0jAU9EREpGEo6ImISMNQ0BMRkYbx/wuVzP64F/gFAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FgLpweUNDOn-",
        "outputId": "0f75819c-b0cd-40e7-cfe0-af006ed4725e"
      },
      "source": [
        "fig, ax = plt.subplots(figsize=(15,6))\n",
        "ax.bar(dados['tempo'].unique(), height=dados['tempo'].value_counts(ascending=True), width=20, color='red')\n",
        "ax.set_xticks(dados['tempo'].unique())\n",
        "ax.set_title('Distribuição dos experimentos por tempo')\n",
        "ax.set_xlabel('Tempo observado')\n",
        "ax.set_ylabel('Nº de experimentos')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Nº de experimentos')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 155
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qy5rBte-6QV7",
        "outputId": "8cbdcc53-bc98-4594-c2e5-12c22017b546"
      },
      "source": [
        "barplot_dose = dados['dose'].value_counts().plot.bar()\n",
        "barplot_dose.set_title('Distribuição dos experimentos por dose')\n",
        "barplot_dose.set_xlabel('Dose administrada')\n",
        "barplot_dose.set_ylabel('Nº de experimentos')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Nº de experimentos')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 156
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UZfmnIIRqYdB"
      },
      "source": [
        "###Desafio 4: Quantos tipos de drogas foram investigados?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S_PJIO0epPoF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2194ad49-2623-4a2f-e701-06132d85fba1"
      },
      "source": [
        "dados['droga'].nunique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3289"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 157
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-jQV4ZTQs5ex"
      },
      "source": [
        "###Desafio 5: Procurar a documentação do query (no pandas) e resolver o desafio de criar a máscara de valores g-0 maiores que zero"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "MQ485LoVtQFT",
        "outputId": "6ad62b86-2b97-4c6b-eded-82d404beac5c"
      },
      "source": [
        "dados.query('g0 > 0')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<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>droga</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
              "      <th>g4</th>\n",
              "      <th>g5</th>\n",
              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
              "      <th>g10</th>\n",
              "      <th>g11</th>\n",
              "      <th>g12</th>\n",
              "      <th>g13</th>\n",
              "      <th>g14</th>\n",
              "      <th>g15</th>\n",
              "      <th>g16</th>\n",
              "      <th>g17</th>\n",
              "      <th>g18</th>\n",
              "      <th>g19</th>\n",
              "      <th>g20</th>\n",
              "      <th>g21</th>\n",
              "      <th>g22</th>\n",
              "      <th>g23</th>\n",
              "      <th>g24</th>\n",
              "      <th>g25</th>\n",
              "      <th>g26</th>\n",
              "      <th>g27</th>\n",
              "      <th>g28</th>\n",
              "      <th>g29</th>\n",
              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</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>6</th>\n",
              "      <td>id_001bd861f</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>746ca1f5a</td>\n",
              "      <td>2.0440</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>5.9440</td>\n",
              "      <td>-2.1670</td>\n",
              "      <td>-4.0360</td>\n",
              "      <td>3.6950</td>\n",
              "      <td>1.4530</td>\n",
              "      <td>0.9724</td>\n",
              "      <td>-2.4380</td>\n",
              "      <td>5.1340</td>\n",
              "      <td>-4.6600</td>\n",
              "      <td>5.7960</td>\n",
              "      <td>4.9700</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>2.4790</td>\n",
              "      <td>-3.8010</td>\n",
              "      <td>-1.0230</td>\n",
              "      <td>5.3110</td>\n",
              "      <td>-0.5660</td>\n",
              "      <td>-4.4450</td>\n",
              "      <td>1.2210</td>\n",
              "      <td>1.3750</td>\n",
              "      <td>0.3932</td>\n",
              "      <td>0.3392</td>\n",
              "      <td>4.3510</td>\n",
              "      <td>5.7540</td>\n",
              "      <td>-1.6590</td>\n",
              "      <td>5.3000</td>\n",
              "      <td>5.6050</td>\n",
              "      <td>5.5320</td>\n",
              "      <td>3.7860</td>\n",
              "      <td>0.9197</td>\n",
              "      <td>1.9310</td>\n",
              "      <td>2.4870</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.8904</td>\n",
              "      <td>2.0590</td>\n",
              "      <td>0.5052</td>\n",
              "      <td>0.6890</td>\n",
              "      <td>0.5340</td>\n",
              "      <td>0.5135</td>\n",
              "      <td>0.6507</td>\n",
              "      <td>0.9838</td>\n",
              "      <td>0.4532</td>\n",
              "      <td>-0.3212</td>\n",
              "      <td>0.2662</td>\n",
              "      <td>0.6864</td>\n",
              "      <td>1.6300</td>\n",
              "      <td>1.3810</td>\n",
              "      <td>0.0061</td>\n",
              "      <td>0.2908</td>\n",
              "      <td>0.2598</td>\n",
              "      <td>0.1266</td>\n",
              "      <td>-0.3526</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>-1.1030</td>\n",
              "      <td>1.3650</td>\n",
              "      <td>1.0610</td>\n",
              "      <td>0.4034</td>\n",
              "      <td>1.0880</td>\n",
              "      <td>-0.4230</td>\n",
              "      <td>0.4013</td>\n",
              "      <td>0.1726</td>\n",
              "      <td>0.7464</td>\n",
              "      <td>0.9418</td>\n",
              "      <td>0.1855</td>\n",
              "      <td>1.1720</td>\n",
              "      <td>0.8325</td>\n",
              "      <td>0.6486</td>\n",
              "      <td>0.8090</td>\n",
              "      <td>1.5880</td>\n",
              "      <td>2.4670</td>\n",
              "      <td>0.0357</td>\n",
              "      <td>0.1351</td>\n",
              "      <td>-0.3179</td>\n",
              "    </tr>\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>...</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>23807</th>\n",
              "      <td>id_fff7e6992</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>a28556d51</td>\n",
              "      <td>0.1420</td>\n",
              "      <td>-0.3696</td>\n",
              "      <td>-0.0093</td>\n",
              "      <td>-0.2495</td>\n",
              "      <td>-0.0175</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>-0.2201</td>\n",
              "      <td>0.2443</td>\n",
              "      <td>0.4879</td>\n",
              "      <td>0.3432</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>0.9056</td>\n",
              "      <td>0.3538</td>\n",
              "      <td>0.5246</td>\n",
              "      <td>-0.4441</td>\n",
              "      <td>-0.1605</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-0.5619</td>\n",
              "      <td>-0.1409</td>\n",
              "      <td>0.1255</td>\n",
              "      <td>0.1214</td>\n",
              "      <td>-0.1975</td>\n",
              "      <td>-0.4367</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.4301</td>\n",
              "      <td>-0.7606</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>0.0270</td>\n",
              "      <td>-0.0367</td>\n",
              "      <td>-1.2480</td>\n",
              "      <td>0.0559</td>\n",
              "      <td>-0.0984</td>\n",
              "      <td>0.5537</td>\n",
              "      <td>0.1063</td>\n",
              "      <td>0.3893</td>\n",
              "      <td>...</td>\n",
              "      <td>0.5554</td>\n",
              "      <td>0.2225</td>\n",
              "      <td>-0.0903</td>\n",
              "      <td>0.9227</td>\n",
              "      <td>-0.0460</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>1.0730</td>\n",
              "      <td>-0.6904</td>\n",
              "      <td>0.9298</td>\n",
              "      <td>1.0500</td>\n",
              "      <td>0.4646</td>\n",
              "      <td>0.4481</td>\n",
              "      <td>0.9771</td>\n",
              "      <td>0.7187</td>\n",
              "      <td>0.5299</td>\n",
              "      <td>0.1079</td>\n",
              "      <td>1.2010</td>\n",
              "      <td>0.2529</td>\n",
              "      <td>-0.4546</td>\n",
              "      <td>0.7998</td>\n",
              "      <td>0.6401</td>\n",
              "      <td>-1.3370</td>\n",
              "      <td>0.6542</td>\n",
              "      <td>0.8561</td>\n",
              "      <td>0.4829</td>\n",
              "      <td>0.3213</td>\n",
              "      <td>-0.0177</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.4626</td>\n",
              "      <td>0.0030</td>\n",
              "      <td>0.8775</td>\n",
              "      <td>0.5230</td>\n",
              "      <td>0.1589</td>\n",
              "      <td>0.7715</td>\n",
              "      <td>0.5497</td>\n",
              "      <td>0.6929</td>\n",
              "      <td>0.3738</td>\n",
              "      <td>0.8636</td>\n",
              "      <td>0.4494</td>\n",
              "      <td>0.1218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23808</th>\n",
              "      <td>id_fff8c2444</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>6c3a459be</td>\n",
              "      <td>0.1608</td>\n",
              "      <td>-1.0500</td>\n",
              "      <td>0.2551</td>\n",
              "      <td>-0.2239</td>\n",
              "      <td>-0.2431</td>\n",
              "      <td>0.4256</td>\n",
              "      <td>-0.1166</td>\n",
              "      <td>-0.1777</td>\n",
              "      <td>-0.7480</td>\n",
              "      <td>0.1368</td>\n",
              "      <td>0.5493</td>\n",
              "      <td>-0.5083</td>\n",
              "      <td>0.4112</td>\n",
              "      <td>0.1181</td>\n",
              "      <td>0.7861</td>\n",
              "      <td>-0.1877</td>\n",
              "      <td>0.2476</td>\n",
              "      <td>0.1956</td>\n",
              "      <td>0.0273</td>\n",
              "      <td>0.1182</td>\n",
              "      <td>-0.5037</td>\n",
              "      <td>-0.5939</td>\n",
              "      <td>0.4825</td>\n",
              "      <td>-0.5187</td>\n",
              "      <td>0.1618</td>\n",
              "      <td>-0.2253</td>\n",
              "      <td>0.3153</td>\n",
              "      <td>0.4839</td>\n",
              "      <td>0.0520</td>\n",
              "      <td>1.3850</td>\n",
              "      <td>0.6502</td>\n",
              "      <td>-0.4198</td>\n",
              "      <td>0.2723</td>\n",
              "      <td>-0.3629</td>\n",
              "      <td>1.0820</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2720</td>\n",
              "      <td>-0.6021</td>\n",
              "      <td>0.2451</td>\n",
              "      <td>0.6607</td>\n",
              "      <td>-0.1849</td>\n",
              "      <td>-0.6546</td>\n",
              "      <td>-0.5798</td>\n",
              "      <td>0.3449</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>0.2949</td>\n",
              "      <td>0.4158</td>\n",
              "      <td>0.8586</td>\n",
              "      <td>0.3868</td>\n",
              "      <td>1.0030</td>\n",
              "      <td>-0.4593</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>0.8293</td>\n",
              "      <td>-0.7645</td>\n",
              "      <td>0.5379</td>\n",
              "      <td>0.5610</td>\n",
              "      <td>0.2577</td>\n",
              "      <td>-0.5493</td>\n",
              "      <td>0.2690</td>\n",
              "      <td>0.6392</td>\n",
              "      <td>-0.5774</td>\n",
              "      <td>-0.3393</td>\n",
              "      <td>0.5068</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-0.4559</td>\n",
              "      <td>0.3734</td>\n",
              "      <td>0.0789</td>\n",
              "      <td>0.3538</td>\n",
              "      <td>0.0558</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>-0.4753</td>\n",
              "      <td>-0.2504</td>\n",
              "      <td>-0.7415</td>\n",
              "      <td>0.8413</td>\n",
              "      <td>-0.4259</td>\n",
              "      <td>0.2434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</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>11769 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...     c96     c97     c98     c99\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",
              "6      id_001bd861f     com_droga     24   D2  ...  2.4670  0.0357  0.1351 -0.3179\n",
              "7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23807  id_fff7e6992     com_droga     48   D1  ...  0.3738  0.8636  0.4494  0.1218\n",
              "23808  id_fff8c2444     com_droga     72   D1  ... -0.7415  0.8413 -0.4259  0.2434\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\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",
              "[11769 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 161
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "cib53eYCH64W",
        "outputId": "b8f458b4-93d8-425d-d722-f1d5bcb5f7d0"
      },
      "source": [
        "dados.query('dose == \"D1\"') #fazendo mais um uso do Query"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>droga</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
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              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</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>5</th>\n",
              "      <td>id_001762a82</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>e06749542</td>\n",
              "      <td>-0.6111</td>\n",
              "      <td>0.2941</td>\n",
              "      <td>-0.9901</td>\n",
              "      <td>0.2277</td>\n",
              "      <td>1.2810</td>\n",
              "      <td>0.5203</td>\n",
              "      <td>0.0543</td>\n",
              "      <td>-0.2225</td>\n",
              "      <td>-0.1586</td>\n",
              "      <td>0.4289</td>\n",
              "      <td>0.0361</td>\n",
              "      <td>0.3543</td>\n",
              "      <td>0.8310</td>\n",
              "      <td>-0.9129</td>\n",
              "      <td>0.7677</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>0.7087</td>\n",
              "      <td>0.0481</td>\n",
              "      <td>-0.4486</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>1.2550</td>\n",
              "      <td>0.3359</td>\n",
              "      <td>-0.5103</td>\n",
              "      <td>-0.2993</td>\n",
              "      <td>-1.1950</td>\n",
              "      <td>-0.3208</td>\n",
              "      <td>-0.1187</td>\n",
              "      <td>1.0030</td>\n",
              "      <td>0.9133</td>\n",
              "      <td>0.0376</td>\n",
              "      <td>0.3015</td>\n",
              "      <td>-0.9578</td>\n",
              "      <td>0.5354</td>\n",
              "      <td>1.1360</td>\n",
              "      <td>1.1310</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6701</td>\n",
              "      <td>2.0780</td>\n",
              "      <td>1.3350</td>\n",
              "      <td>0.9889</td>\n",
              "      <td>0.5017</td>\n",
              "      <td>2.0020</td>\n",
              "      <td>0.8918</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.8465</td>\n",
              "      <td>0.6596</td>\n",
              "      <td>1.3710</td>\n",
              "      <td>1.0580</td>\n",
              "      <td>1.7570</td>\n",
              "      <td>1.0030</td>\n",
              "      <td>0.2152</td>\n",
              "      <td>1.6920</td>\n",
              "      <td>-0.2930</td>\n",
              "      <td>1.4590</td>\n",
              "      <td>1.0950</td>\n",
              "      <td>0.5854</td>\n",
              "      <td>1.7270</td>\n",
              "      <td>0.5580</td>\n",
              "      <td>1.3090</td>\n",
              "      <td>1.0100</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5455</td>\n",
              "      <td>1.0170</td>\n",
              "      <td>1.2910</td>\n",
              "      <td>1.5430</td>\n",
              "      <td>1.8390</td>\n",
              "      <td>1.1570</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>1.9010</td>\n",
              "      <td>1.4270</td>\n",
              "      <td>0.4519</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.3765</td>\n",
              "      <td>0.7848</td>\n",
              "      <td>1.3990</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>23804</th>\n",
              "      <td>id_fff506720</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>74515bfd2</td>\n",
              "      <td>-1.0140</td>\n",
              "      <td>0.1709</td>\n",
              "      <td>-0.4291</td>\n",
              "      <td>1.8750</td>\n",
              "      <td>0.9859</td>\n",
              "      <td>0.3009</td>\n",
              "      <td>0.0650</td>\n",
              "      <td>-1.3920</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>1.4790</td>\n",
              "      <td>-0.4459</td>\n",
              "      <td>0.7377</td>\n",
              "      <td>-0.0037</td>\n",
              "      <td>-0.0995</td>\n",
              "      <td>-0.2393</td>\n",
              "      <td>-1.1670</td>\n",
              "      <td>-0.9359</td>\n",
              "      <td>1.1260</td>\n",
              "      <td>0.3450</td>\n",
              "      <td>-1.0780</td>\n",
              "      <td>2.7230</td>\n",
              "      <td>0.5255</td>\n",
              "      <td>0.6368</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>-0.1172</td>\n",
              "      <td>0.8256</td>\n",
              "      <td>0.2120</td>\n",
              "      <td>2.1500</td>\n",
              "      <td>0.5925</td>\n",
              "      <td>-0.7637</td>\n",
              "      <td>0.1157</td>\n",
              "      <td>0.0919</td>\n",
              "      <td>-0.5855</td>\n",
              "      <td>-0.6233</td>\n",
              "      <td>-0.7982</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.6549</td>\n",
              "      <td>-1.0250</td>\n",
              "      <td>-2.6910</td>\n",
              "      <td>-0.6001</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>-1.5960</td>\n",
              "      <td>-0.3137</td>\n",
              "      <td>-0.4209</td>\n",
              "      <td>-0.9542</td>\n",
              "      <td>-1.4760</td>\n",
              "      <td>-1.0180</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>0.1523</td>\n",
              "      <td>-1.0130</td>\n",
              "      <td>-0.4065</td>\n",
              "      <td>0.8502</td>\n",
              "      <td>-0.0978</td>\n",
              "      <td>-0.7339</td>\n",
              "      <td>-0.5680</td>\n",
              "      <td>-0.5700</td>\n",
              "      <td>0.7834</td>\n",
              "      <td>-2.5930</td>\n",
              "      <td>-2.1570</td>\n",
              "      <td>-0.7917</td>\n",
              "      <td>-0.9154</td>\n",
              "      <td>1.5140</td>\n",
              "      <td>-3.1070</td>\n",
              "      <td>-0.2346</td>\n",
              "      <td>-0.2662</td>\n",
              "      <td>-0.6730</td>\n",
              "      <td>0.3175</td>\n",
              "      <td>-1.5510</td>\n",
              "      <td>-1.2800</td>\n",
              "      <td>-0.7632</td>\n",
              "      <td>-0.6736</td>\n",
              "      <td>-0.4097</td>\n",
              "      <td>0.2282</td>\n",
              "      <td>-0.3213</td>\n",
              "      <td>-0.0836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23807</th>\n",
              "      <td>id_fff7e6992</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>a28556d51</td>\n",
              "      <td>0.1420</td>\n",
              "      <td>-0.3696</td>\n",
              "      <td>-0.0093</td>\n",
              "      <td>-0.2495</td>\n",
              "      <td>-0.0175</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>-0.2201</td>\n",
              "      <td>0.2443</td>\n",
              "      <td>0.4879</td>\n",
              "      <td>0.3432</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>0.9056</td>\n",
              "      <td>0.3538</td>\n",
              "      <td>0.5246</td>\n",
              "      <td>-0.4441</td>\n",
              "      <td>-0.1605</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-0.5619</td>\n",
              "      <td>-0.1409</td>\n",
              "      <td>0.1255</td>\n",
              "      <td>0.1214</td>\n",
              "      <td>-0.1975</td>\n",
              "      <td>-0.4367</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.4301</td>\n",
              "      <td>-0.7606</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>0.0270</td>\n",
              "      <td>-0.0367</td>\n",
              "      <td>-1.2480</td>\n",
              "      <td>0.0559</td>\n",
              "      <td>-0.0984</td>\n",
              "      <td>0.5537</td>\n",
              "      <td>0.1063</td>\n",
              "      <td>0.3893</td>\n",
              "      <td>...</td>\n",
              "      <td>0.5554</td>\n",
              "      <td>0.2225</td>\n",
              "      <td>-0.0903</td>\n",
              "      <td>0.9227</td>\n",
              "      <td>-0.0460</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>1.0730</td>\n",
              "      <td>-0.6904</td>\n",
              "      <td>0.9298</td>\n",
              "      <td>1.0500</td>\n",
              "      <td>0.4646</td>\n",
              "      <td>0.4481</td>\n",
              "      <td>0.9771</td>\n",
              "      <td>0.7187</td>\n",
              "      <td>0.5299</td>\n",
              "      <td>0.1079</td>\n",
              "      <td>1.2010</td>\n",
              "      <td>0.2529</td>\n",
              "      <td>-0.4546</td>\n",
              "      <td>0.7998</td>\n",
              "      <td>0.6401</td>\n",
              "      <td>-1.3370</td>\n",
              "      <td>0.6542</td>\n",
              "      <td>0.8561</td>\n",
              "      <td>0.4829</td>\n",
              "      <td>0.3213</td>\n",
              "      <td>-0.0177</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.4626</td>\n",
              "      <td>0.0030</td>\n",
              "      <td>0.8775</td>\n",
              "      <td>0.5230</td>\n",
              "      <td>0.1589</td>\n",
              "      <td>0.7715</td>\n",
              "      <td>0.5497</td>\n",
              "      <td>0.6929</td>\n",
              "      <td>0.3738</td>\n",
              "      <td>0.8636</td>\n",
              "      <td>0.4494</td>\n",
              "      <td>0.1218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23808</th>\n",
              "      <td>id_fff8c2444</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>6c3a459be</td>\n",
              "      <td>0.1608</td>\n",
              "      <td>-1.0500</td>\n",
              "      <td>0.2551</td>\n",
              "      <td>-0.2239</td>\n",
              "      <td>-0.2431</td>\n",
              "      <td>0.4256</td>\n",
              "      <td>-0.1166</td>\n",
              "      <td>-0.1777</td>\n",
              "      <td>-0.7480</td>\n",
              "      <td>0.1368</td>\n",
              "      <td>0.5493</td>\n",
              "      <td>-0.5083</td>\n",
              "      <td>0.4112</td>\n",
              "      <td>0.1181</td>\n",
              "      <td>0.7861</td>\n",
              "      <td>-0.1877</td>\n",
              "      <td>0.2476</td>\n",
              "      <td>0.1956</td>\n",
              "      <td>0.0273</td>\n",
              "      <td>0.1182</td>\n",
              "      <td>-0.5037</td>\n",
              "      <td>-0.5939</td>\n",
              "      <td>0.4825</td>\n",
              "      <td>-0.5187</td>\n",
              "      <td>0.1618</td>\n",
              "      <td>-0.2253</td>\n",
              "      <td>0.3153</td>\n",
              "      <td>0.4839</td>\n",
              "      <td>0.0520</td>\n",
              "      <td>1.3850</td>\n",
              "      <td>0.6502</td>\n",
              "      <td>-0.4198</td>\n",
              "      <td>0.2723</td>\n",
              "      <td>-0.3629</td>\n",
              "      <td>1.0820</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2720</td>\n",
              "      <td>-0.6021</td>\n",
              "      <td>0.2451</td>\n",
              "      <td>0.6607</td>\n",
              "      <td>-0.1849</td>\n",
              "      <td>-0.6546</td>\n",
              "      <td>-0.5798</td>\n",
              "      <td>0.3449</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>0.2949</td>\n",
              "      <td>0.4158</td>\n",
              "      <td>0.8586</td>\n",
              "      <td>0.3868</td>\n",
              "      <td>1.0030</td>\n",
              "      <td>-0.4593</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>0.8293</td>\n",
              "      <td>-0.7645</td>\n",
              "      <td>0.5379</td>\n",
              "      <td>0.5610</td>\n",
              "      <td>0.2577</td>\n",
              "      <td>-0.5493</td>\n",
              "      <td>0.2690</td>\n",
              "      <td>0.6392</td>\n",
              "      <td>-0.5774</td>\n",
              "      <td>-0.3393</td>\n",
              "      <td>0.5068</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-0.4559</td>\n",
              "      <td>0.3734</td>\n",
              "      <td>0.0789</td>\n",
              "      <td>0.3538</td>\n",
              "      <td>0.0558</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>-0.4753</td>\n",
              "      <td>-0.2504</td>\n",
              "      <td>-0.7415</td>\n",
              "      <td>0.8413</td>\n",
              "      <td>-0.4259</td>\n",
              "      <td>0.2434</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",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12147 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id tratamento  tempo dose  ...     c96     c97     c98     c99\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",
              "5      id_001762a82  com_droga     24   D1  ...  1.2120  0.3765  0.7848  1.3990\n",
              "...             ...        ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23804  id_fff506720  com_droga     24   D1  ... -0.4097  0.2282 -0.3213 -0.0836\n",
              "23807  id_fff7e6992  com_droga     48   D1  ...  0.3738  0.8636  0.4494  0.1218\n",
              "23808  id_fff8c2444  com_droga     72   D1  ... -0.7415  0.8413 -0.4259  0.2434\n",
              "23812  id_fffcb9e7c  com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b  com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[12147 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 162
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9a1jDfZu5ICU"
      },
      "source": [
        "###Desafio 6: Renomear as colunas tirando o hífen"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5AlPyNUh5Q79"
      },
      "source": [
        "dados.columns = dados.columns.str.replace(\"-\",\"\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "brNGSNgB-ltg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "outputId": "6320fa37-6d6c-42e2-9c78-ae475ceaa387"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<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>droga</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
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              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
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              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</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  ...     c96     c97     c98     c99\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": 160
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DyTRlqBLGPUa"
      },
      "source": [
        "###Desafio 7: Fazer um resumo das descobertas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UKup-U-nGW6Z"
      },
      "source": [
        "Preferi deixar as anotações ao longo das células, se você leu até aqui, provavelmente viu minhas notas!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q330YruQxR2G"
      },
      "source": [
        "##Observando a distribuição dos genes g0 e g1"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZvleKDFgu5fh"
      },
      "source": [
        "#histograma da distribuição dos resultados de g0\n",
        "ax = sns.displot(data=dados, x='g0', kde=True)\n",
        "print(dados['g0'].min())\n",
        "print(dados['g0'].max())\n",
        "print(dados['g0'].mean())\n",
        "print(dados['g0'].median())\n",
        "print(dados['g0'].var())\n",
        "print(dados['g0'].skew())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k2Vm-da7vITQ"
      },
      "source": [
        "sns.displot(data=dados, x='g1', kde=True)\n",
        "print(dados['g1'].min())\n",
        "print(dados['g1'].max())\n",
        "print(dados['g1'].mean())\n",
        "print(dados['g1'].median())\n",
        "print(dados['g1'].var())\n",
        "print(dados['g1'].skew())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TfofAUI_WxDu"
      },
      "source": [
        "###Aula 02"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uj1AVfJZwXZH"
      },
      "source": [
        "#forma interessante de substituir nome de coluna\n",
        "#através de um mapa\n",
        "mapa = {'droga':'composto'}\n",
        "dados.rename(columns=mapa, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Nuax-XjaY8D"
      },
      "source": [
        "Criando um countplot com os primeiros 5 compostos mais usados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bQZjKv36ZNnb"
      },
      "source": [
        "comp = dados['composto'].value_counts().index[:5]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ktPCd8V4XnV3"
      },
      "source": [
        "#coletando as infos dos 5 compostos com o query\n",
        "d_comp = dados.query('composto in @comp') #o @ serve para declarar que a váriavel foi definida pelo python e não pelo dados"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H4Ec-8uTenHQ"
      },
      "source": [
        "###Desafio 9: Melhorar a visualização e estética dos gráficos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NdoCTkMAZBGS"
      },
      "source": [
        "#usando o Seaborn\n",
        "fig, ax = plt.subplots(figsize=(15,6))\n",
        "sns.set() #rodar pelo menos uma vez o .set() tras as novas configurações automáticas de estilização do Seaborn\n",
        "ax = sns.countplot(data=d_comp, x='composto')\n",
        "ax.set_title('5 compostos mais usados', )\n",
        "ax.set_xlabel('Composto')\n",
        "ax.set_ylabel('vezes usado')\n",
        "plt.show() #colocar ele mesmo com o matplotlib inline some com o text que vem em cima do gráfico"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sbnM3BOIbcNl"
      },
      "source": [
        "#loc nos genes 'g'\n",
        "dados.loc[:,'g0':'g771'].describe()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rq-0pC_VkeH3"
      },
      "source": [
        "Histograma das médias dos genes 'g'"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0km9hDrYkXkN"
      },
      "source": [
        "#com o .T fazemos a transposição do DataFrame\n",
        "describe_g = dados.loc[:,'g0':'g771'].describe().T"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qMXTiUrAkwxm"
      },
      "source": [
        "#plotando o histograma das médias\n",
        "hist_g = sns.histplot(describe_g, x='mean', kde=True)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XkvU9nIblA_u"
      },
      "source": [
        "#histograma dos desvios-padrão\n",
        "hist_g = sns.histplot(describe_g, x='std', kde=True)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xl8nvXOjnirM"
      },
      "source": [
        "Observando as variáveis 'c'"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FIS0w8VOnHoe"
      },
      "source": [
        "describe_c = dados.loc[:,'c0':'c99'].describe().T"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QrS_3vNlnYAf"
      },
      "source": [
        "#histograma das médias\n",
        "sns.histplot(data=describe_c, x='mean', kde=True)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rYaJB-G9oAcW"
      },
      "source": [
        "No Dataframe, cada 'c' respresenta linhagens de células, o pressuposto de ter vários tipos de células é para garantir a famosa independência estatística, e não gerar o viés de que o o medicamento agiu em determinado tipo, ou que foi o tipo que gerou o resultado da célula, e também garantir saber possíveis colaterais.\n",
        "\n",
        "Os valores registrados em c são as viabilidades, ou seja, \"o quanto as células sobreviveram\" à exposição daqueles compostos "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_8i--U8cpFxc"
      },
      "source": [
        "###Plotando Boxplots"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WREl6khpnyoc"
      },
      "source": [
        "sns.boxplot(data=dados, x='g0')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CsfABxZgpQM1"
      },
      "source": [
        "#boxplot da resposta de g0 por dose administrada\n",
        "plt.figure(figsize=(10,6))\n",
        "sns.boxplot(data=dados, x='g0', y='dose', )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hnbUu4fawZgv"
      },
      "source": [
        "#boxplot da resposta de g0 por tratamento\n",
        "sns.boxplot(data=dados, x='g0', y='tratamento')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z-Hb4s0g-QIJ"
      },
      "source": [
        "Plotando um boxplot mais bonito e mais completo"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z3UzqKxs6znZ"
      },
      "source": [
        "fig, ax = plt.subplots(figsize=(10,9))\n",
        "sns.set_style('darkgrid')\n",
        "sns.set_context('talk')\n",
        "ax = sns.boxplot(data=dados, x='tratamento', y='g0', hue='dose', palette='Paired')\n",
        "ax.set_xlabel('Tipo de tratamento', fontdict={'fontsize':20})\n",
        "ax.set_ylabel('gene g0')\n",
        "ax.set_title('Quartis e mediana por tratamento e dose', fontdict={'fontsize':20, 'verticalalignment':'center'})\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "38EMmWOdywwv"
      },
      "source": [
        "##Dia 3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lMLc6A5lzEJm"
      },
      "source": [
        "Função nova: \".crosstab\" que cria uma frequency table"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NfQP3GbH2zGN"
      },
      "source": [
        "Para filtrar mais de um dado, nas colunas ou linhas (e criar um MultiIndex) devemos inserir os **colchetes antes**(procedimento padrão no Pandas).\n",
        "\n",
        "Podemos normalizar os valores de várias formas (ver documetação) com o **'normalize='**.\n",
        "\n",
        "Para adicionar um valor específico que desejamos ver os dados correspondentes a ele, usar **'value='** e podemos inclusive, colocar uma função (média, mediana, std, etc.) com o **'aggfunc='**."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1yh_L3KX7NPY"
      },
      "source": [
        "pd.crosstab(dados['dose'], [dados['tratamento'], dados['tempo']])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NdbZHWn4zpxQ"
      },
      "source": [
        "#outra forma de fazer\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento']) "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MFrRbJ9U0lLD"
      },
      "source": [
        "#plotando as proporções\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize=True) * 100"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m1yFO36l1IUv"
      },
      "source": [
        "#plotando as proporções pelo index (nesse caso será em relação as linhas)\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize='index')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "26bK3JAo3pwF"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g0'], aggfunc='mean')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LQIeli7h1n-2"
      },
      "source": [
        "###Desafio 08: Fazer uma tabela parecida com a crosstab mas utilizando o Groupby"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FhEubU9k2FPd"
      },
      "source": [
        "Nota pessoal: Eu gosto muito de Groupby, ela é muito poderosa"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U4qRh93H1d4W"
      },
      "source": [
        "groupby = dados.groupby(by=['dose', 'tratamento','tempo']).count()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YbhkhU5NNmgI"
      },
      "source": [
        "groupby.iloc[:13,2:3]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BboLLTkSKfPI"
      },
      "source": [
        "groupby.iloc[:13,2:3].T"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4j7N_Yhw1_cy"
      },
      "source": [
        "###Desafio 9: Normalizar o crosstab pela coluna"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9h0EwyQ32Dxe"
      },
      "source": [
        "pd.crosstab([dados['dose'],dados['tempo']], dados['tratamento'], normalize='columns')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V2fJocV05ZBf"
      },
      "source": [
        "###Desafio 10: Quais outros agregadores existem?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4_m-ieF45lGc"
      },
      "source": [
        "Média"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZyogxPCg5dI4"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g0'], aggfunc='mean')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eDKAj8kX5mxE"
      },
      "source": [
        "Mediana"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JB-ry-x-5hBO"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g0'], aggfunc='median')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "za0e-u0e529c"
      },
      "source": [
        "Standard Deviation a.k.a Desvio-padrão"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QZluCJhZ5iO_"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g0'], aggfunc='std')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_zz-x_656Axt"
      },
      "source": [
        "Variância"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "giDma_nJ59i2"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g0'], aggfunc='var')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BuYKmyWi5tHe"
      },
      "source": [
        "###Desafio 11: Explorar o Melt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x02OPD4GOdUe"
      },
      "source": [
        "Esse método pode ser aplicado tanto em pd (pandas) quanto diretamente no Dataframe"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ikQ53kCr5kB_"
      },
      "source": [
        "pd.melt(dados, id_vars=['dose','tratamento', 'tempo'], value_vars=['g0'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E-3_xQtyPRQf"
      },
      "source": [
        "dados.melt(id_vars=['dose','tratamento','tempo'], value_vars=['g0'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RBoDJ1bPPlS4"
      },
      "source": [
        "dados.melt(id_vars=['dose','tratamento','tempo'], value_vars=['g0'])[:5]\n",
        "#podemos aplicar o index como sempre para dar uma filtrada"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MFrIHjjOQGl9"
      },
      "source": [
        "dados.melt(id_vars=['dose','tratamento','tempo'], value_vars=['g0'], value_name='respostas do gene 0').mean()\n",
        "#observando a média do gene 0 pela dose, tratamento e tempo"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QUOY6_5Q6SVd"
      },
      "source": [
        "###Explorando as correlações e variações de g0 e g1"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "svexdUcF6Vck"
      },
      "source": [
        "#usando a dispersão\n",
        "sns.scatterplot(data=dados, x='g0', y='g1')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Cj9DaZp6eLV"
      },
      "source": [
        "sns.scatterplot(data=dados, x='g0', y='g3', )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CJy2fVhH6kD-"
      },
      "source": [
        "#o jointplot mostra a distruibuição junto com a dispersão\n",
        "sns.jointplot(data=dados, x='g0', y='g3', kind='reg')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fA9W4STB7tqi"
      },
      "source": [
        "#outra forma de ver a linha de distribuição é com o lmplot\n",
        "sns.lmplot(data=dados, x='g0', y='g3', line_kws={'color':'red'})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yR3E99Qz_Z_5"
      },
      "source": [
        "sns.lmplot(data=dados, x='g0', y='g3', line_kws={'color':'red'}, hue='dose', col='tratamento', row='tempo')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1ftZ8GF7_ZTf"
      },
      "source": [
        "Observando as correlações"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IDaxPQF1_jAC"
      },
      "source": [
        "O Próprio Pandas pode nos mostrar as correlações"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ew_y62mo8Tme"
      },
      "source": [
        "#.corr()\n",
        "dados.loc[:,'g0':'g771'].corr()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LMOcMTX5AHQe"
      },
      "source": [
        "No geral, utilizamos um gráfico 'heatmap' para ver as correlações.\n",
        "\n",
        "Aqui, usaremos um ctrl+c ctrl+v da matriz diagonal de correlação"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LZrdAiyk-_59"
      },
      "source": [
        "corr = dados.loc[:,'g0':'g50'].corr()\n",
        "\n",
        "# Generate a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(30, 15))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-9gbHhUUBIBD"
      },
      "source": [
        "VELHO LEMBRETE: **Correlação não é causalidade!**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bjSvsHz5E3zw"
      },
      "source": [
        "Correlações de C"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "idm_inIDn8PL"
      },
      "source": [
        "corr_c = dados.loc[:,'c0':'c50'].corr()\n",
        "\n",
        "# Generate a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(corr_c, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(30, 15))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr_c, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rXuekuFRFAFI"
      },
      "source": [
        "###Desafio 12: Explorar a correlação entre expressões gênicas g e os tipos célulares c"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QFY-FNv_qveb"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aqT48csSxa-O"
      },
      "source": [
        "##Dia 4"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e1CMBMTh4RjL"
      },
      "source": [
        "###Hoje vamos observar os resultados dos testes experimentais"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "beEHbaxzxc9l"
      },
      "source": [
        "dados_resultados = pd.read_csv('https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_resultados.csv?raw=true')\n",
        "dados_resultados.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cHafcjoa5t2f"
      },
      "source": [
        "De forma superficial, essa base contém os mecanismos de ação, se 1, foi ativado pelo experimento, se 0 é que não foi ativado pelo experimento"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H77U3RC25GL9"
      },
      "source": [
        "dados_resultados.info()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pGsRjJsM5930"
      },
      "source": [
        "###Três formas de fazer a contagem dos mecanismos de ação"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rkuK20wu6K_y"
      },
      "source": [
        "Com o Iloc"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f-OLmg8I5WVp"
      },
      "source": [
        "contagem_moa = dados_resultados.iloc[:,1:].sum().sort_values(ascending=False)\n",
        "contagem_moa"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wa8XV5MZ6Mxh"
      },
      "source": [
        "COm o select_dtypes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WeDR3tAi5ptQ"
      },
      "source": [
        "contagem_moa = dados_resultados.select_dtypes('int64').sum().sort_values(ascending=False)\n",
        "contagem_moa"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6huaSPwh6PA8"
      },
      "source": [
        "Com o drop"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hb1Y8ZfV6Gbb"
      },
      "source": [
        "contagem_moa = dados_resultados.drop('id', axis=1).sum().sort_values(ascending=False)\n",
        "contagem_moa"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "khutHaVWH7UQ"
      },
      "source": [
        "dados_resultados['n_moa'] = dados_resultados.drop('id', axis=1).sum(axis=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2JWVkpLQIf1N"
      },
      "source": [
        "dados_resultados['moa_ativado'] = dados_resultados['n_moa'] != 0"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FdAGy0yFI9H7"
      },
      "source": [
        "dados_resultados.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u-bxXQrdJHK1"
      },
      "source": [
        "dados_final = pd.merge(dados, dados_resultados[['id', 'n_moa', 'moa_ativado']], on='id')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fj1DmfRoJfQd"
      },
      "source": [
        "dados_final.head(2)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8qlkK3ej65_2"
      },
      "source": [
        "###Desafio 01: Encontrar o top10 das ações do MoA (inibidor, agonista, etc.)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8gV3k51B6VEf"
      },
      "source": [
        "copy_dados = dados_resultados\n",
        "copy_dados"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QKgxS7-T7Ja6"
      },
      "source": [
        "#contando quantos tem inhibitor\n",
        "len(copy_dados.columns[copy_dados.columns.str.contains('inhibitor')])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1wxw82rlFCw4"
      },
      "source": [
        "#Contando quantos tem agonist\n",
        "len(copy_dados.columns[copy_dados.columns.str.contains('agonist')])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PFVZjl2Lf2S1"
      },
      "source": [
        "#vendo os que não contém nem inhibitor nem agonist\n",
        "copy_dados.columns[(copy_dados.columns.str.contains('agonist') == False) & (copy_dados.columns.str.contains('inhibitor')==False)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ybDHjA9C_YPr"
      },
      "source": [
        "###Desafio 2: Criar uma coluna True False (0,1) para a coluna tratamento"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k8OITKlaJvb_"
      },
      "source": [
        "dados_final['eh_controle'] = dados_final['tratamento'] == 'com_controle'\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OhJxrZOzKIUz"
      },
      "source": [
        "dados_final['eh_controle'].value_counts()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MuRmFwFa_sCr"
      },
      "source": [
        "###Desafio 3: Criar colunas para 24, 48 e 72 de True e False"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E5PWfDEoKXPg"
      },
      "source": [
        "dados_final['tempo'].dtype"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6dAyp-i-8Cch"
      },
      "source": [
        "dados_final['24h'] = dados_final['tempo'] == 24\n",
        "dados_final.head(2)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pVDZE1VlKnTD"
      },
      "source": [
        "dados_final['48h'] = dados_final['tempo'] == 48"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6U7RXzDbKtQK"
      },
      "source": [
        "dados_final['72h'] = dados_final['tempo'] == 72"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HBH5K1sFLatJ"
      },
      "source": [
        "###Desafio 4: Criar coluna para dose  "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ld_ETGS4Lhj9"
      },
      "source": [
        "dados_final['d1'] = dados_final['dose'] == 'D1'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rX9bxv44LxEg"
      },
      "source": [
        "dados_final['d2'] = dados_final['dose'] == 'D2'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6cXjIWNXLSbX"
      },
      "source": [
        "###Desafio 4: Análise mais profunda para quando há tempo e dose"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j74x6lntKvg6"
      },
      "source": [
        "dados_final['composto'].value_counts()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lRH2NMbEL5l5"
      },
      "source": [
        "#não esquecer: para teste boleano não aplicar o filtro (nome do dataset no início), para fazer slice ai sim se coloca o filtro, como no caso abaixo\n",
        "analise_comp = dados_final[(dados_final['composto'] == 'cacb2b860') | (dados_final['composto'] == '5628cb3ee')]\n",
        "analise_comp"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XC49L74jMUUi"
      },
      "source": [
        "sns.catplot(data=analise_comp, x='composto', y='g0', hue='tratamento', col='dose', row='tempo', kind='box')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dovMk2ijRI2Y"
      },
      "source": [
        "Observando a partir da coluna eh_controle True False que criamos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TfLWaevyRDXZ"
      },
      "source": [
        "sns.catplot(data=analise_comp, x='composto', y='g0', hue='eh_controle', col='dose', row='tempo', kind='box')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OHGVefVvROVk"
      },
      "source": [
        "Passando ordem explícita para o hue de como ordenar"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vqzS-bHPN94z"
      },
      "source": [
        "sns.catplot(data=analise_comp, x='composto', y='g0', hue='tratamento', col='dose', row='tempo', kind='box', hue_order=['com_droga','com_controle'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qbSFDyLoGCrm"
      },
      "source": [
        "##Dia 5"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QMC1tDNBHmVW"
      },
      "source": [
        "No último dia da imersão, estamos implementando alguns modelos de machine learning para auxiliar no Drug Discovery"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TGrX14AdHeah"
      },
      "source": [
        "dados_final.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NCj7P4NVPsl5"
      },
      "source": [
        "No train test split, podemos passar algumas variáveis, para que tenhamos um modelo de comparação para os outros modelos que vamos testar (a benchmark), são eles: random_state, que vai travar em determinada acurácia o modelo e stratify que vai garantir que a acurácia seja igual à realidade."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ztfSvPP_JUZM"
      },
      "source": [
        "from sklearn.model_selection import train_test_split #biblioteca para separar as bases de dados para treinar e testar a capacidade do modelo\n",
        "\n",
        "x = dados_final.select_dtypes('float64')\n",
        "y = dados_final['moa_ativado']\n",
        "\n",
        "x_treino, x_teste, y_treino, y_teste = train_test_split(x,y, test_size=0.2, stratify=y, random_state=350)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0owhAcfOGG2n"
      },
      "source": [
        "from sklearn.linear_model import LogisticRegression #modelo de regressão logística\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "modelo_rlogistica = LogisticRegression(max_iter=1000)\n",
        "modelo_rlogistica.fit(x_treino, y_treino)\n",
        "modelo_rlogistica.score(x_teste, y_teste)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hDqMXcdlQMhf"
      },
      "source": [
        "Um método interessante para comparar a capacidade do modelo é o uso de modelo Dummy (bobo e simples) para ver se nosso modelo realmente está fazendo uma previsão melhor que \"chutando\".\n",
        "\n",
        "Obs: na página do Sklearn sobre o Dummy há um alerta de não usá-lo para problemas reais."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lvL9ZIGqICR3"
      },
      "source": [
        "from sklearn.dummy import DummyClassifier\n",
        "from sklearn.metrics import accuracy_score\n",
        "dummy_model = DummyClassifier('most_frequent')\n",
        "dummy_model.fit(x_treino, y_treino)\n",
        "previsao_dummy = dummy_model.predict(x_teste)\n",
        "accuracy_score(y_teste, previsao_dummy)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lPmte0WrReuf"
      },
      "source": [
        "Com o benchmark feito, agora podemos construir nossa tentativa de um novo modelo com melhor capacidade de previsão, o proposto foi: árvore de decisão (Decision Tree)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S1M3TkOlRV5m"
      },
      "source": [
        "from sklearn.tree import DecisionTreeClassifier\n",
        "x = dados_final.select_dtypes('float64')\n",
        "y = dados_final['moa_ativado']\n",
        "\n",
        "x_treino, x_teste, y_treino, y_teste = train_test_split(x,y, test_size=0.2, stratify=y, random_state=350)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f5-gSVYQVQqo"
      },
      "source": [
        "tree = DecisionTreeClassifier(max_depth=3)\n",
        "\n",
        "tree.fit(x_treino, y_treino)\n",
        "tree.score(x_teste, y_teste)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RyI4mMi0VzVd"
      },
      "source": [
        "O max_depth é a profundidade dos níveis de decisão da árvore, nesse caso, ela está com 3, isso PODE SER um dos problemas da baixa acurácia.\n",
        "\n",
        "Vamos testar para uma profundidade maior e ver o que acontece."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RI8YNpSsVwYI"
      },
      "source": [
        "tree = DecisionTreeClassifier(max_depth=10)\n",
        "\n",
        "tree.fit(x_treino, y_treino)\n",
        "tree.score(x_teste, y_teste)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1UtcZsVkWLjS"
      },
      "source": [
        "teste=[]\n",
        "treino=[]\n",
        "for i in range(1,15):\n",
        "    modelo_arvore = DecisionTreeClassifier(max_depth = i)\n",
        "    modelo_arvore.fit(x_treino, y_treino)\n",
        "    teste.append(modelo_arvore.score(x_teste, y_teste))\n",
        "    treino.append(modelo_arvore.score(x_treino, y_treino))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B9JY3LdOW2jI"
      },
      "source": [
        "teste"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bUVm4QThW5JY"
      },
      "source": [
        "treino"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qXq9rIYZYVtq"
      },
      "source": [
        "sns.lineplot(x=range(1,15), y=treino, label='treino')\n",
        "sns.lineplot(x=range(1,15), y=teste, label='teste')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DxCrZiWIX31e"
      },
      "source": [
        "Podemos ver que ao contrário do esperado, o algoritmo passou a performar melhor no treino e pior no teste, esse é um processo conhecido como 'overfitting', ou uma especialização do algoritmo na base de treino e que portanto, perde a capacidade de generalização."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3u2f94TPY92q"
      },
      "source": [
        "Já que aprofundar não é uma forma sempre perfeita de aplicar, podemos fazer com que o dataset seja varrido por várias árvores de decisão, esse é o algoritmo chamado de Random Forest.\n",
        "\n",
        "Como funciona?\n",
        "\n",
        "Ele divide o dataset em várias amostras e aplica as árvores de decisão nelas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XVx6GKE2W6SZ"
      },
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "#aplicação é semelhante ao Decision Tree\n",
        "\n",
        "x = dados_final.drop(columns=['id', 'moa_ativado', 'n_moa', 'tratamento','tempo','dose','composto']) #podemos ver que o Random Forest consegue arcar com tipos diversos de dados\n",
        "y = dados_final['moa_ativado']\n",
        "\n",
        "x_treino, x_teste, y_treino, y_teste = train_test_split(x,y, test_size=0.2, stratify=y, random_state=350)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8xemOMmwkbme"
      },
      "source": [
        "Testei minha Random Forest para vários parâmetros e cheguei a esses resultados: "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qmr2p79HZdZs"
      },
      "source": [
        "random_forest = RandomForestClassifier(n_estimators=1000)\n",
        "random_forest.fit(x_treino, y_treino)\n",
        "random_forest.score(x_teste, y_teste)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T2_TAKURa3Jc"
      },
      "source": [
        "random_forest = RandomForestClassifier(n_estimators=1000, max_depth=8)\n",
        "random_forest.fit(x_treino, y_treino)\n",
        "random_forest.score(x_teste, y_teste)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UUOdzMNekq5L"
      },
      "source": [
        "random_forest = RandomForestClassifier()\n",
        "random_forest.fit(x_treino, y_treino)\n",
        "random_forest.score(x_teste, y_teste)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c9scIO8oktRO"
      },
      "source": [
        "lista_treino = []\n",
        "lista_teste = []\n",
        "for i in range(200,238):\n",
        "  random_forest = RandomForestClassifier(n_estimators=i)\n",
        "  random_forest.fit(x_treino, y_treino)\n",
        "  lista_treino.append(random_forest.score(x_treino, y_treino))\n",
        "  lista_teste.append(random_forest.score(x_teste, y_teste))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OCfaUTA3wtLs"
      },
      "source": [
        "lista_treino"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UF8_ZddGTtIz"
      },
      "source": [
        "lista_teste"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}