Querys.ipynb

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      "source": [
        "# @title Setup\n",
        "from google.colab import auth\n",
        "from google.cloud import bigquery\n",
        "from google.colab import data_table\n",
        "\n",
        "project = 'blotta' # Project ID inserted based on the query results selected to explore\n",
        "location = 'US' # Location inserted based on the query results selected to explore\n",
        "client = bigquery.Client(project=project, location=location)\n",
        "data_table.enable_dataframe_formatter()\n",
        "auth.authenticate_user()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pj42soltXW_H"
      },
      "source": [
        "## Reference SQL syntax from the original job\n",
        "Use the ```jobs.query```\n",
        "[method](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) to\n",
        "return the SQL syntax from the job. This can be copied from the output cell\n",
        "below to edit the query now or in the future. Alternatively, you can use\n",
        "[this link](https://console.cloud.google.com/bigquery?j=blotta:US:bquxjob_2097d0d8_1881b33988d)\n",
        "back to BigQuery to edit the query within the BigQuery user interface."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "KxSqPfAeXW_K",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3ffaf5fe-3e40-4772-d2ae-16ebf1b4ed51"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SELECT sexo, id_municipio, ano, tempo_emprego, quantidade_horas_contratadas, valor_remuneracao_media_sm, cbo_2002, idade, tipo_vinculo FROM `basedosdados.br_me_rais.microdados_vinculos` WHERE cbo_2002 LIKE \"2611%%\" OR cbo_1994 =\"15210\" OR cbo_1994 = \"15220\" OR cbo_1994 = \"15230\" OR cbo_1994 = \"15240\" OR cbo_1994 = \"15245\" OR cbo_1994 = \"15250\"\r\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Running this code will display the query used to generate your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_668d5903_18a65fffb4a') # Job ID inserted based on the query results selected to explore\n",
        "print(job.query)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eY-wNOGO11ON"
      },
      "source": [
        "# Result set loaded from BigQuery job as a DataFrame\n",
        "Query results are referenced from the Job ID ran from BigQuery and the query\n",
        "does not need to be re-run to explore results. The ```to_dataframe```\n",
        "[method](https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.job.QueryJob.html#google.cloud.bigquery.job.QueryJob.to_dataframe)\n",
        "downloads the results to a Pandas DataFrame by using the BigQuery Storage API.\n",
        "\n",
        "To edit query syntax, you can do so from the BigQuery SQL editor or in the\n",
        "```Optional:``` sections below."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
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          "height": 441
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        "outputId": "9de00d50-ec2b-4b27-dcca-4fe182b47f36"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Warning: total number of rows (1315053) exceeds max_rows (20000). Falling back to pandas display.\n"
          ]
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        sexo id_municipio   ano  tempo_emprego  quantidade_horas_contratadas  \\\n",
              "0          1      1200401  1985            0.6                          <NA>   \n",
              "1          1      1200401  1985            3.1                          <NA>   \n",
              "2          1      1200401  1985            0.0                          <NA>   \n",
              "3          1      1200401  1985            0.3                          <NA>   \n",
              "4          1      1400100  1991            0.8                          <NA>   \n",
              "...      ...          ...   ...            ...                           ...   \n",
              "1315048    2      3554102  2020          131.2                            30   \n",
              "1315049    2      3554102  2020           13.9                            30   \n",
              "1315050    2      3555000  2020            9.3                            40   \n",
              "1315051    2      3556453  2020          185.8                            40   \n",
              "1315052    2      3557105  2020           28.9                            44   \n",
              "\n",
              "         valor_remuneracao_media_sm cbo_2002  idade tipo_vinculo  \n",
              "0                             13.19     None   <NA>            1  \n",
              "1                              4.44     None   <NA>            1  \n",
              "2                              2.61     None   <NA>            1  \n",
              "3                              1.40     None   <NA>            1  \n",
              "4                              7.21     None   <NA>            1  \n",
              "...                             ...      ...    ...          ...  \n",
              "1315048                        5.47   261120     32           10  \n",
              "1315049                        2.84   261135     23           10  \n",
              "1315050                        2.37   261125     28           31  \n",
              "1315051                        6.88   261110     43           31  \n",
              "1315052                        2.21   261110     30           10  \n",
              "\n",
              "[1315053 rows x 9 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sexo</th>\n",
              "      <th>id_municipio</th>\n",
              "      <th>ano</th>\n",
              "      <th>tempo_emprego</th>\n",
              "      <th>quantidade_horas_contratadas</th>\n",
              "      <th>valor_remuneracao_media_sm</th>\n",
              "      <th>cbo_2002</th>\n",
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              "      <td>1200401</td>\n",
              "      <td>1985</td>\n",
              "      <td>0.6</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>13.19</td>\n",
              "      <td>None</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1200401</td>\n",
              "      <td>1985</td>\n",
              "      <td>3.1</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>4.44</td>\n",
              "      <td>None</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1200401</td>\n",
              "      <td>1985</td>\n",
              "      <td>0.0</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>2.61</td>\n",
              "      <td>None</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1200401</td>\n",
              "      <td>1985</td>\n",
              "      <td>0.3</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1.40</td>\n",
              "      <td>None</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1400100</td>\n",
              "      <td>1991</td>\n",
              "      <td>0.8</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>7.21</td>\n",
              "      <td>None</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>1315048</th>\n",
              "      <td>2</td>\n",
              "      <td>3554102</td>\n",
              "      <td>2020</td>\n",
              "      <td>131.2</td>\n",
              "      <td>30</td>\n",
              "      <td>5.47</td>\n",
              "      <td>261120</td>\n",
              "      <td>32</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1315049</th>\n",
              "      <td>2</td>\n",
              "      <td>3554102</td>\n",
              "      <td>2020</td>\n",
              "      <td>13.9</td>\n",
              "      <td>30</td>\n",
              "      <td>2.84</td>\n",
              "      <td>261135</td>\n",
              "      <td>23</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1315050</th>\n",
              "      <td>2</td>\n",
              "      <td>3555000</td>\n",
              "      <td>2020</td>\n",
              "      <td>9.3</td>\n",
              "      <td>40</td>\n",
              "      <td>2.37</td>\n",
              "      <td>261125</td>\n",
              "      <td>28</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1315051</th>\n",
              "      <td>2</td>\n",
              "      <td>3556453</td>\n",
              "      <td>2020</td>\n",
              "      <td>185.8</td>\n",
              "      <td>40</td>\n",
              "      <td>6.88</td>\n",
              "      <td>261110</td>\n",
              "      <td>43</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1315052</th>\n",
              "      <td>2</td>\n",
              "      <td>3557105</td>\n",
              "      <td>2020</td>\n",
              "      <td>28.9</td>\n",
              "      <td>44</td>\n",
              "      <td>2.21</td>\n",
              "      <td>261110</td>\n",
              "      <td>30</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1315053 rows × 9 columns</p>\n",
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              "\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5b931679-bf61-418f-8456-7d8506c2519e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-top-color: var(--fill-color);\n",
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              "    60% {\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "# Running this code will read results from your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_29f68e97_18a6d8b0de2') # Job ID inserted based on the query results selected to explore\n",
        "results = job.to_dataframe()\n",
        "results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "84Ub57pbB6EN"
      },
      "source": [
        "## Show descriptive statistics using describe()\n",
        "Use the ```pandas DataFrame.describe()```\n",
        "[method](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.describe.html)\n",
        "to generate descriptive statistics. Descriptive statistics include those that\n",
        "summarize the central tendency, dispersion and shape of a dataset’s\n",
        "distribution, excluding ```NaN``` values. You may also use other Python methods\n",
        "to interact with your data."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#importar bibliotecas\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "import statsmodels.api as sm\n",
        "import csv\n",
        "import pandas as pd"
      ],
      "metadata": {
        "id": "wlVt5AqsOSA6"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#estatísticas descritivas\n",
        "\n",
        "results.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "kE6GyjLAQCT4",
        "outputId": "c9ad3bfe-7f00-43ab-adf6-1467c182f457"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               ano  tempo_emprego  quantidade_horas_contratadas  \\\n",
              "count    1315053.0   1.315053e+06                     1188962.0   \n",
              "mean   2008.529676   4.702096e+01                     37.176779   \n",
              "std        9.03975   7.113133e+01                      7.672303   \n",
              "min         1985.0   0.000000e+00                           0.0   \n",
              "25%         2004.0   5.900000e+00                          30.0   \n",
              "50%         2010.0   1.980000e+01                          40.0   \n",
              "75%         2015.0   5.490000e+01                          44.0   \n",
              "max         2021.0   5.999000e+02                          60.0   \n",
              "\n",
              "       valor_remuneracao_media_sm      idade  \n",
              "count                1.315053e+06  1188962.0  \n",
              "mean                 6.845815e+00  35.037809  \n",
              "std                  8.835569e+00  10.924951  \n",
              "min                  0.000000e+00        0.0  \n",
              "25%                  1.980000e+00       27.0  \n",
              "50%                  4.090000e+00       33.0  \n",
              "75%                  8.110000e+00       41.0  \n",
              "max                  1.499700e+02      100.0  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ano</th>\n",
              "      <th>tempo_emprego</th>\n",
              "      <th>quantidade_horas_contratadas</th>\n",
              "      <th>valor_remuneracao_media_sm</th>\n",
              "      <th>idade</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1315053.0</td>\n",
              "      <td>1.315053e+06</td>\n",
              "      <td>1188962.0</td>\n",
              "      <td>1.315053e+06</td>\n",
              "      <td>1188962.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2008.529676</td>\n",
              "      <td>4.702096e+01</td>\n",
              "      <td>37.176779</td>\n",
              "      <td>6.845815e+00</td>\n",
              "      <td>35.037809</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.03975</td>\n",
              "      <td>7.113133e+01</td>\n",
              "      <td>7.672303</td>\n",
              "      <td>8.835569e+00</td>\n",
              "      <td>10.924951</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1985.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2004.0</td>\n",
              "      <td>5.900000e+00</td>\n",
              "      <td>30.0</td>\n",
              "      <td>1.980000e+00</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2010.0</td>\n",
              "      <td>1.980000e+01</td>\n",
              "      <td>40.0</td>\n",
              "      <td>4.090000e+00</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2015.0</td>\n",
              "      <td>5.490000e+01</td>\n",
              "      <td>44.0</td>\n",
              "      <td>8.110000e+00</td>\n",
              "      <td>41.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2021.0</td>\n",
              "      <td>5.999000e+02</td>\n",
              "      <td>60.0</td>\n",
              "      <td>1.499700e+02</td>\n",
              "      <td>100.0</td>\n",
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              "\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-97dc17cc-0691-410d-bbdc-dd5a066b298c button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-97dc17cc-0691-410d-bbdc-dd5a066b298c');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
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              "      spin 1s steps(1) infinite;\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "            'suggestCharts', [key], {});\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[\"count\",\n{\n            'v': 1315053.0,\n            'f': \"1315053.0\",\n        },\n{\n            'v': 1315053.0,\n            'f': \"1315053.0\",\n        },\n{\n            'v': 1188962.0,\n            'f': \"1188962.0\",\n        },\n{\n            'v': 1315053.0,\n            'f': \"1315053.0\",\n        },\n{\n            'v': 1188962.0,\n            'f': \"1188962.0\",\n        }],\n [\"mean\",\n{\n            'v': 2008.5296759902453,\n            'f': \"2008.5296759902453\",\n        },\n{\n            'v': 47.02095923130094,\n            'f': \"47.02095923130094\",\n        },\n{\n            'v': 37.17677856819646,\n            'f': \"37.17677856819646\",\n        },\n{\n            'v': 6.845815012778954,\n            'f': \"6.845815012778954\",\n        },\n{\n            'v': 35.03780860952663,\n            'f': \"35.03780860952663\",\n        }],\n [\"std\",\n{\n            'v': 9.039749560862406,\n            'f': \"9.039749560862406\",\n        },\n{\n            'v': 71.13133398684693,\n            'f': \"71.13133398684693\",\n        },\n{\n            'v': 7.672303188186001,\n            'f': \"7.672303188186001\",\n        },\n{\n            'v': 8.835568664705647,\n            'f': \"8.835568664705647\",\n        },\n{\n            'v': 10.92495081108321,\n            'f': \"10.92495081108321\",\n        }],\n [\"min\",\n{\n            'v': 1985.0,\n            'f': \"1985.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        }],\n [\"25%\",\n{\n            'v': 2004.0,\n            'f': \"2004.0\",\n        },\n{\n            'v': 5.9,\n            'f': \"5.9\",\n        },\n{\n            'v': 30.0,\n            'f': \"30.0\",\n        },\n{\n            'v': 1.98,\n            'f': \"1.98\",\n        },\n{\n            'v': 27.0,\n            'f': \"27.0\",\n        }],\n [\"50%\",\n{\n            'v': 2010.0,\n            'f': \"2010.0\",\n        },\n{\n            'v': 19.8,\n            'f': \"19.8\",\n        },\n{\n            'v': 40.0,\n            'f': \"40.0\",\n        },\n{\n            'v': 4.09,\n            'f': \"4.09\",\n        },\n{\n            'v': 33.0,\n            'f': \"33.0\",\n        }],\n [\"75%\",\n{\n            'v': 2015.0,\n            'f': \"2015.0\",\n        },\n{\n            'v': 54.9,\n            'f': \"54.9\",\n        },\n{\n            'v': 44.0,\n            'f': \"44.0\",\n        },\n{\n            'v': 8.11,\n            'f': \"8.11\",\n        },\n{\n            'v': 41.0,\n            'f': \"41.0\",\n        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      quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-824e58c4-3d86-4406-90c6-37f7c9aa27f1\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-824e58c4-3d86-4406-90c6-37f7c9aa27f1')\"\n            title=\"Suggest charts.\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-824e58c4-3d86-4406-90c6-37f7c9aa27f1 button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#limpeza 1\n",
        "\n",
        "results = results.drop(columns=['cbo_2002'])"
      ],
      "metadata": {
        "id": "FzHaNhoNthxA"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Plotagem dos boxplots"
      ],
      "metadata": {
        "id": "ghClcF5hecLU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "boxplot = results.drop(columns=['ano', 'tempo_emprego', 'idade', 'quantidade_horas_contratadas'])\n",
        "sns.boxplot(data=boxplot, orient='h', saturation=0.75, width=0.8)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "Aqa8uxOLOU5e",
        "outputId": "7558493f-e2b1-4405-9e0c-b3597be14d1d"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Limpeza 2\n",
        "\n",
        "idadeusar = results.dropna(subset=['idade'])\n",
        "horasusar = results.dropna(subset=['quantidade_horas_contratadas'])"
      ],
      "metadata": {
        "id": "KoQELP8HhxxP"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "boxplot = idadeusar.drop(columns=['ano', 'tempo_emprego', 'valor_remuneracao_media_sm', 'quantidade_horas_contratadas'])\n",
        "sns.boxplot(data=boxplot, orient='h', saturation=0.75, width=0.8)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "SahBLnC3ixYg",
        "outputId": "d998af36-a552-40a5-9772-06f2caf5a6b5"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "boxplot = horasusar.drop(columns=['ano', 'tempo_emprego', 'valor_remuneracao_media_sm', 'idade'])\n",
        "sns.boxplot(data=boxplot, orient='h', saturation=0.75, width=0.8)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "hdUITYvEi_sS",
        "outputId": "a097eb73-db45-4a19-9261-b5e3f91ea85f"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tempoempregousar = results.loc[results.ano >= 1994]\n",
        "tempoempregousar_plotar = tempoempregousar.drop(columns=['idade', 'quantidade_horas_contratadas', 'valor_remuneracao_media_sm', 'ano'])\n",
        "sns.boxplot(data=tempoempregousar_plotar, orient='h', saturation=0.75, width=0.8)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "rLIB_y6KaC6J",
        "outputId": "98fba3fe-fe23-429a-f50d-d86cba4fd627"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Remoção de Outliers"
      ],
      "metadata": {
        "id": "yZKaKdyXZWmV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "q25 = np.percentile(results.valor_remuneracao_media_sm, 25)\n",
        "q75 = np.percentile(results.valor_remuneracao_media_sm, 75)\n",
        "intr_qr = q75-q25\n",
        "\n",
        "max = q75+(1.5*intr_qr)\n",
        "min = q25-(1.5*intr_qr)\n",
        "\n",
        "results.loc[results.valor_remuneracao_media_sm < min] = np.nan\n",
        "results.loc[results.valor_remuneracao_media_sm > max] = np.nan"
      ],
      "metadata": {
        "id": "ptxCPWZfXwJS"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "q25 = np.percentile(idadeusar.idade, 25)\n",
        "q75 = np.percentile(idadeusar.idade, 75)\n",
        "intr_qr = q75-q25\n",
        "\n",
        "max = q75+(1.5*intr_qr)\n",
        "min = q25-(1.5*intr_qr)\n",
        "\n",
        "idadeusar.loc[idadeusar.idade < min] = np.nan\n",
        "idadeusar.loc[idadeusar.idade > max] = np.nan"
      ],
      "metadata": {
        "id": "2ccA7lqXUhQn"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "q25 = np.percentile(horasusar.quantidade_horas_contratadas, 25)\n",
        "q75 = np.percentile(horasusar.quantidade_horas_contratadas, 75)\n",
        "intr_qr = q75-q25\n",
        "\n",
        "max = q75+(1.5*intr_qr)\n",
        "min = q25-(1.5*intr_qr)\n",
        "\n",
        "horasusar.loc[horasusar.quantidade_horas_contratadas < min] = np.nan\n",
        "horasusar.loc[horasusar.quantidade_horas_contratadas > max] = np.nan"
      ],
      "metadata": {
        "id": "maJmuUhpW2dM"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "q25 = np.percentile(tempoempregousar.tempo_emprego, 25)\n",
        "q75 = np.percentile(tempoempregousar.tempo_emprego, 75)\n",
        "intr_qr = q75-q25\n",
        "\n",
        "max = q75+(1.5*intr_qr)\n",
        "min = q25-(1.5*intr_qr)\n",
        "\n",
        "tempoempregousar.loc[tempoempregousar.tempo_emprego < min] = np.nan\n",
        "tempoempregousar.loc[tempoempregousar.tempo_emprego > max] = np.nan"
      ],
      "metadata": {
        "id": "BXeHhLcSbgcI"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "idadeusar = idadeusar.dropna()\n",
        "remuneracao = results.dropna(subset=['valor_remuneracao_media_sm'])\n",
        "horasusar = horasusar.dropna()\n",
        "tempoempregousar = tempoempregousar.dropna()"
      ],
      "metadata": {
        "id": "cjL1iVNuX8Na"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#estatísticas descritivas\n",
        "\n",
        "idadeusar.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "0mRtthUHcMCG",
        "outputId": "b5a93de2-c4b1-42fd-ff34-232f0ce85bd3"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              ano  tempo_emprego  quantidade_horas_contratadas  \\\n",
              "count   1166053.0   1.166053e+06                     1166053.0   \n",
              "mean   2010.56267   4.921501e+01                     37.216351   \n",
              "std      6.761651   6.866996e+01                      7.645872   \n",
              "min        1994.0   0.000000e+00                           0.0   \n",
              "25%        2006.0   8.100000e+00                          30.0   \n",
              "50%        2011.0   2.290000e+01                          40.0   \n",
              "75%        2016.0   5.920000e+01                          44.0   \n",
              "max        2021.0   5.973000e+02                          60.0   \n",
              "\n",
              "       valor_remuneracao_media_sm      idade  \n",
              "count                1.166053e+06  1166053.0  \n",
              "mean                 6.476651e+00  34.413303  \n",
              "std                  8.575888e+00   9.986952  \n",
              "min                  0.000000e+00       10.0  \n",
              "25%                  1.890000e+00       27.0  \n",
              "50%                  3.830000e+00       32.0  \n",
              "75%                  7.550000e+00       41.0  \n",
              "max                  1.499700e+02       62.0  "
            ],
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              "      <th>ano</th>\n",
              "      <th>tempo_emprego</th>\n",
              "      <th>quantidade_horas_contratadas</th>\n",
              "      <th>valor_remuneracao_media_sm</th>\n",
              "      <th>idade</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1166053.0</td>\n",
              "      <td>1.166053e+06</td>\n",
              "      <td>1166053.0</td>\n",
              "      <td>1.166053e+06</td>\n",
              "      <td>1166053.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2010.56267</td>\n",
              "      <td>4.921501e+01</td>\n",
              "      <td>37.216351</td>\n",
              "      <td>6.476651e+00</td>\n",
              "      <td>34.413303</td>\n",
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              "      <td>7.645872</td>\n",
              "      <td>8.575888e+00</td>\n",
              "      <td>9.986952</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1994.0</td>\n",
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              "      <td>10.0</td>\n",
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              "      <th>25%</th>\n",
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              "      <td>27.0</td>\n",
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              "      <th>50%</th>\n",
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              "      <td>2.290000e+01</td>\n",
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              "      <td>3.830000e+00</td>\n",
              "      <td>32.0</td>\n",
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              "      <th>75%</th>\n",
              "      <td>2016.0</td>\n",
              "      <td>5.920000e+01</td>\n",
              "      <td>44.0</td>\n",
              "      <td>7.550000e+00</td>\n",
              "      <td>41.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2021.0</td>\n",
              "      <td>5.973000e+02</td>\n",
              "      <td>60.0</td>\n",
              "      <td>1.499700e+02</td>\n",
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            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[\"count\",\n{\n            'v': 1166053.0,\n            'f': \"1166053.0\",\n        },\n{\n            'v': 1166053.0,\n            'f': \"1166053.0\",\n        },\n{\n            'v': 1166053.0,\n            'f': \"1166053.0\",\n        },\n{\n            'v': 1166053.0,\n            'f': \"1166053.0\",\n        },\n{\n            'v': 1166053.0,\n            'f': \"1166053.0\",\n        }],\n [\"mean\",\n{\n            'v': 2010.5626699644013,\n            'f': \"2010.5626699644013\",\n        },\n{\n            'v': 49.215009180543206,\n            'f': \"49.215009180543206\",\n        },\n{\n            'v': 37.21635122931805,\n            'f': \"37.21635122931805\",\n        },\n{\n            'v': 6.476651129922908,\n            'f': 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  --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      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          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#estatísticas descritivas\n",
        "\n",
        "horasusar.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "p8cM7iZHkPa4",
        "outputId": "76cdda42-5d56-48ee-f7c5-a24e5a9f7f7e"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              ano  tempo_emprego  quantidade_horas_contratadas  \\\n",
              "count   1178699.0   1.178699e+06                     1178699.0   \n",
              "mean   2010.54771   5.143647e+01                     37.463152   \n",
              "std      6.763321   7.332964e+01                      7.036461   \n",
              "min        1994.0   0.000000e+00                           9.0   \n",
              "25%        2006.0   8.400000e+00                          30.0   \n",
              "50%        2011.0   2.320000e+01                          40.0   \n",
              "75%        2016.0   6.090000e+01                          44.0   \n",
              "max        2021.0   5.999000e+02                          60.0   \n",
              "\n",
              "       valor_remuneracao_media_sm      idade  \n",
              "count                1.178699e+06  1178699.0  \n",
              "mean                 6.545069e+00  35.005403  \n",
              "std                  8.672815e+00  10.906703  \n",
              "min                  0.000000e+00        0.0  \n",
              "25%                  1.900000e+00       27.0  \n",
              "50%                  3.860000e+00       33.0  \n",
              "75%                  7.630000e+00       41.0  \n",
              "max                  1.499700e+02      100.0  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ano</th>\n",
              "      <th>tempo_emprego</th>\n",
              "      <th>quantidade_horas_contratadas</th>\n",
              "      <th>valor_remuneracao_media_sm</th>\n",
              "      <th>idade</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1178699.0</td>\n",
              "      <td>1.178699e+06</td>\n",
              "      <td>1178699.0</td>\n",
              "      <td>1.178699e+06</td>\n",
              "      <td>1178699.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2010.54771</td>\n",
              "      <td>5.143647e+01</td>\n",
              "      <td>37.463152</td>\n",
              "      <td>6.545069e+00</td>\n",
              "      <td>35.005403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6.763321</td>\n",
              "      <td>7.332964e+01</td>\n",
              "      <td>7.036461</td>\n",
              "      <td>8.672815e+00</td>\n",
              "      <td>10.906703</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1994.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2006.0</td>\n",
              "      <td>8.400000e+00</td>\n",
              "      <td>30.0</td>\n",
              "      <td>1.900000e+00</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2011.0</td>\n",
              "      <td>2.320000e+01</td>\n",
              "      <td>40.0</td>\n",
              "      <td>3.860000e+00</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2016.0</td>\n",
              "      <td>6.090000e+01</td>\n",
              "      <td>44.0</td>\n",
              "      <td>7.630000e+00</td>\n",
              "      <td>41.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2021.0</td>\n",
              "      <td>5.999000e+02</td>\n",
              "      <td>60.0</td>\n",
              "      <td>1.499700e+02</td>\n",
              "      <td>100.0</td>\n",
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              "\n",
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              "        document.querySelector('#df-c084fbff-6c1e-4d19-96c2-54c89f596467 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c084fbff-6c1e-4d19-96c2-54c89f596467');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
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              "\n",
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              "    background-color: var(--bg-color);\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
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              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
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              "    animation:\n",
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              "  }\n",
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              "  @keyframes spin {\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    }\n",
              "  }\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[\"count\",\n{\n            'v': 1178699.0,\n            'f': \"1178699.0\",\n        },\n{\n            'v': 1178699.0,\n            'f': \"1178699.0\",\n        },\n{\n            'v': 1178699.0,\n            'f': \"1178699.0\",\n        },\n{\n            'v': 1178699.0,\n            'f': \"1178699.0\",\n        },\n{\n            'v': 1178699.0,\n            'f': \"1178699.0\",\n        }],\n [\"mean\",\n{\n            'v': 2010.5477098054719,\n            'f': \"2010.5477098054719\",\n        },\n{\n            'v': 51.43646791929067,\n            'f': \"51.43646791929067\",\n        },\n{\n            'v': 37.4631521703166,\n            'f': \"37.4631521703166\",\n        },\n{\n            'v': 6.545068503494109,\n            'f': \"6.545068503494109\",\n        },\n{\n            'v': 35.00540256672823,\n            'f': \"35.00540256672823\",\n        }],\n [\"std\",\n{\n            'v': 6.763321100014996,\n            'f': \"6.763321100014996\",\n        },\n{\n            'v': 73.32963758813415,\n            'f': \"73.32963758813415\",\n        },\n{\n            'v': 7.036460896386946,\n            'f': \"7.036460896386946\",\n        },\n{\n            'v': 8.67281496401267,\n            'f': \"8.67281496401267\",\n        },\n{\n            'v': 10.906702515412885,\n            'f': \"10.906702515412885\",\n        }],\n [\"min\",\n{\n            'v': 1994.0,\n            'f': \"1994.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 9.0,\n            'f': \"9.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        }],\n [\"25%\",\n{\n            'v': 2006.0,\n            'f': \"2006.0\",\n        },\n{\n            'v': 8.4,\n            'f': \"8.4\",\n        },\n{\n            'v': 30.0,\n            'f': \"30.0\",\n        },\n{\n            'v': 1.9,\n            'f': \"1.9\",\n        },\n{\n            'v': 27.0,\n            'f': \"27.0\",\n        }],\n [\"50%\",\n{\n            'v': 2011.0,\n            'f': \"2011.0\",\n        },\n{\n            'v': 23.2,\n            'f': \"23.2\",\n        },\n{\n            'v': 40.0,\n            'f': \"40.0\",\n        },\n{\n            'v': 3.86,\n            'f': \"3.86\",\n        },\n{\n            'v': 33.0,\n            'f': \"33.0\",\n        }],\n [\"75%\",\n{\n            'v': 2016.0,\n            'f': \"2016.0\",\n        },\n{\n            'v': 60.9,\n            'f': \"60.9\",\n        },\n{\n            'v': 44.0,\n            'f': \"44.0\",\n        },\n{\n            'v': 7.63,\n            'f': \"7.63\",\n        },\n{\n            'v': 41.0,\n            'f': \"41.0\",\n        }],\n [\"max\",\n{\n            'v': 2021.0,\n            'f': \"2021.0\",\n        },\n{\n            'v': 599.9,\n            'f': \"599.9\",\n        },\n{\n            'v': 60.0,\n            'f': \"60.0\",\n        },\n{\n            'v': 149.97,\n            'f': \"149.97\",\n        },\n{\n            'v': 100.0,\n            'f': \"100.0\",\n        }]],\n        columns: [[\"string\", \"index\"], [\"number\", \"ano\"], [\"number\", \"tempo_emprego\"], [\"number\", \"quantidade_horas_contratadas\"], [\"number\", \"valor_remuneracao_media_sm\"], [\"number\", \"idade\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n  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transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      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          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#estatísticas descritivas\n",
        "\n",
        "remuneracao.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "5ft_vNCjkQ1l",
        "outputId": "ca9e31f4-2e6a-428f-c53d-b4bd28fe6a08"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               ano  tempo_emprego  quantidade_horas_contratadas  \\\n",
              "count    1211291.0   1.211291e+06                     1103505.0   \n",
              "mean   2009.028888   4.389328e+01                     37.335878   \n",
              "std       8.854089   6.682123e+01                      7.704103   \n",
              "min         1985.0   0.000000e+00                           0.0   \n",
              "25%         2005.0   5.900000e+00                          30.0   \n",
              "50%         2011.0   1.890000e+01                          40.0   \n",
              "75%         2016.0   5.090000e+01                          44.0   \n",
              "max         2021.0   5.999000e+02                          60.0   \n",
              "\n",
              "       valor_remuneracao_media_sm      idade  \n",
              "count                1.211291e+06  1103505.0  \n",
              "mean                 4.871225e+00  34.479337  \n",
              "std                  3.857945e+00  10.743391  \n",
              "min                  0.000000e+00        0.0  \n",
              "25%                  1.860000e+00       26.0  \n",
              "50%                  3.670000e+00       32.0  \n",
              "75%                  6.800000e+00       40.0  \n",
              "max                  1.730000e+01      100.0  "
            ],
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ano</th>\n",
              "      <th>tempo_emprego</th>\n",
              "      <th>quantidade_horas_contratadas</th>\n",
              "      <th>valor_remuneracao_media_sm</th>\n",
              "      <th>idade</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1211291.0</td>\n",
              "      <td>1.211291e+06</td>\n",
              "      <td>1103505.0</td>\n",
              "      <td>1.211291e+06</td>\n",
              "      <td>1103505.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2009.028888</td>\n",
              "      <td>4.389328e+01</td>\n",
              "      <td>37.335878</td>\n",
              "      <td>4.871225e+00</td>\n",
              "      <td>34.479337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>8.854089</td>\n",
              "      <td>6.682123e+01</td>\n",
              "      <td>7.704103</td>\n",
              "      <td>3.857945e+00</td>\n",
              "      <td>10.743391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1985.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2005.0</td>\n",
              "      <td>5.900000e+00</td>\n",
              "      <td>30.0</td>\n",
              "      <td>1.860000e+00</td>\n",
              "      <td>26.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2011.0</td>\n",
              "      <td>1.890000e+01</td>\n",
              "      <td>40.0</td>\n",
              "      <td>3.670000e+00</td>\n",
              "      <td>32.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2016.0</td>\n",
              "      <td>5.090000e+01</td>\n",
              "      <td>44.0</td>\n",
              "      <td>6.800000e+00</td>\n",
              "      <td>40.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2021.0</td>\n",
              "      <td>5.999000e+02</td>\n",
              "      <td>60.0</td>\n",
              "      <td>1.730000e+01</td>\n",
              "      <td>100.0</td>\n",
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              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f45de183-2752-4e65-8251-74f0d044e768 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[\"count\",\n{\n            'v': 1211291.0,\n            'f': \"1211291.0\",\n        },\n{\n            'v': 1211291.0,\n            'f': \"1211291.0\",\n        },\n{\n            'v': 1103505.0,\n            'f': \"1103505.0\",\n        },\n{\n            'v': 1211291.0,\n            'f': \"1211291.0\",\n        },\n{\n            'v': 1103505.0,\n            'f': \"1103505.0\",\n        }],\n [\"mean\",\n{\n            'v': 2009.028888186241,\n            'f': \"2009.028888186241\",\n        },\n{\n            'v': 43.89328121813835,\n            'f': \"43.89328121813835\",\n        },\n{\n            'v': 37.335877952524,\n            'f': \"37.335877952524\",\n        },\n{\n            'v': 4.871224726345695,\n            'f': \"4.871224726345695\",\n        },\n{\n            'v': 34.47933720282192,\n            'f': \"34.47933720282192\",\n        }],\n [\"std\",\n{\n            'v': 8.854088924930412,\n            'f': \"8.854088924930412\",\n        },\n{\n            'v': 66.82122911015884,\n            'f': \"66.82122911015884\",\n        },\n{\n            'v': 7.704102954510394,\n            'f': \"7.704102954510394\",\n        },\n{\n            'v': 3.857945230976116,\n            'f': \"3.857945230976116\",\n        },\n{\n            'v': 10.743391027541694,\n            'f': \"10.743391027541694\",\n        }],\n [\"min\",\n{\n            'v': 1985.0,\n            'f': \"1985.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        }],\n [\"25%\",\n{\n            'v': 2005.0,\n            'f': \"2005.0\",\n        },\n{\n            'v': 5.9,\n            'f': \"5.9\",\n        },\n{\n            'v': 30.0,\n            'f': \"30.0\",\n        },\n{\n            'v': 1.86,\n            'f': \"1.86\",\n        },\n{\n            'v': 26.0,\n            'f': \"26.0\",\n        }],\n [\"50%\",\n{\n            'v': 2011.0,\n            'f': \"2011.0\",\n        },\n{\n            'v': 18.9,\n            'f': \"18.9\",\n        },\n{\n            'v': 40.0,\n            'f': \"40.0\",\n        },\n{\n            'v': 3.67,\n            'f': \"3.67\",\n        },\n{\n            'v': 32.0,\n            'f': \"32.0\",\n        }],\n [\"75%\",\n{\n            'v': 2016.0,\n            'f': \"2016.0\",\n        },\n{\n            'v': 50.9,\n            'f': \"50.9\",\n        },\n{\n            'v': 44.0,\n            'f': \"44.0\",\n        },\n{\n            'v': 6.8,\n            'f': \"6.8\",\n        },\n{\n            'v': 40.0,\n            'f': \"40.0\",\n        }],\n [\"max\",\n{\n            'v': 2021.0,\n            'f': \"2021.0\",\n        },\n{\n            'v': 599.9,\n            'f': \"599.9\",\n        },\n{\n            'v': 60.0,\n            'f': \"60.0\",\n        },\n{\n            'v': 17.3,\n            'f': \"17.3\",\n        },\n{\n            'v': 100.0,\n            'f': \"100.0\",\n        }]],\n        columns: [[\"string\", \"index\"], [\"number\", \"ano\"], [\"number\", \"tempo_emprego\"], [\"number\", \"quantidade_horas_contratadas\"], [\"number\", \"valor_remuneracao_media_sm\"], [\"number\", \"idade\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n        quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-13b4dc0a-ffee-4908-9226-0b6d9d19bf21\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-13b4dc0a-ffee-4908-9226-0b6d9d19bf21')\"\n            title=\"Suggest charts.\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-13b4dc0a-ffee-4908-9226-0b6d9d19bf21 button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#estatísticas descritivas\n",
        "\n",
        "tempoempregousar.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "EPNKFN0QkS8o",
        "outputId": "f4860b0a-fd5a-4eef-ef65-60a73c87ee83"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               ano  tempo_emprego  quantidade_horas_contratadas  \\\n",
              "count    1074521.0   1.074521e+06                     1074521.0   \n",
              "mean   2010.551341   3.158897e+01                     37.432033   \n",
              "std       6.720733   3.240777e+01                      7.643126   \n",
              "min         1994.0   0.000000e+00                           0.0   \n",
              "25%         2006.0   7.300000e+00                          30.0   \n",
              "50%         2011.0   1.980000e+01                          40.0   \n",
              "75%         2016.0   4.560000e+01                          44.0   \n",
              "max         2021.0   1.401000e+02                          60.0   \n",
              "\n",
              "       valor_remuneracao_media_sm      idade  \n",
              "count                1.074521e+06  1074521.0  \n",
              "mean                 6.006903e+00  33.549296  \n",
              "std                  8.172158e+00    9.95495  \n",
              "min                  0.000000e+00        0.0  \n",
              "25%                  1.800000e+00       26.0  \n",
              "50%                  3.560000e+00       31.0  \n",
              "75%                  6.900000e+00       39.0  \n",
              "max                  1.499700e+02      100.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8873455d-63c9-4f42-9c95-abcc43f710cc\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ano</th>\n",
              "      <th>tempo_emprego</th>\n",
              "      <th>quantidade_horas_contratadas</th>\n",
              "      <th>valor_remuneracao_media_sm</th>\n",
              "      <th>idade</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1074521.0</td>\n",
              "      <td>1.074521e+06</td>\n",
              "      <td>1074521.0</td>\n",
              "      <td>1.074521e+06</td>\n",
              "      <td>1074521.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2010.551341</td>\n",
              "      <td>3.158897e+01</td>\n",
              "      <td>37.432033</td>\n",
              "      <td>6.006903e+00</td>\n",
              "      <td>33.549296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6.720733</td>\n",
              "      <td>3.240777e+01</td>\n",
              "      <td>7.643126</td>\n",
              "      <td>8.172158e+00</td>\n",
              "      <td>9.95495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1994.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2006.0</td>\n",
              "      <td>7.300000e+00</td>\n",
              "      <td>30.0</td>\n",
              "      <td>1.800000e+00</td>\n",
              "      <td>26.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2011.0</td>\n",
              "      <td>1.980000e+01</td>\n",
              "      <td>40.0</td>\n",
              "      <td>3.560000e+00</td>\n",
              "      <td>31.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2016.0</td>\n",
              "      <td>4.560000e+01</td>\n",
              "      <td>44.0</td>\n",
              "      <td>6.900000e+00</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2021.0</td>\n",
              "      <td>1.401000e+02</td>\n",
              "      <td>60.0</td>\n",
              "      <td>1.499700e+02</td>\n",
              "      <td>100.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8873455d-63c9-4f42-9c95-abcc43f710cc')\"\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8873455d-63c9-4f42-9c95-abcc43f710cc button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-8873455d-63c9-4f42-9c95-abcc43f710cc');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "</svg>\n",
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              "\n",
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              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "  }\n",
              "\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c17f60b4-dff8-4197-b483-121545df2c4d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/881c4a0d49046431/data_table.js\";\n\n      const table = window.createDataTable({\n        data: [[\"count\",\n{\n            'v': 1074521.0,\n            'f': \"1074521.0\",\n        },\n{\n            'v': 1074521.0,\n            'f': \"1074521.0\",\n        },\n{\n            'v': 1074521.0,\n            'f': \"1074521.0\",\n        },\n{\n            'v': 1074521.0,\n            'f': \"1074521.0\",\n        },\n{\n            'v': 1074521.0,\n            'f': \"1074521.0\",\n        }],\n [\"mean\",\n{\n            'v': 2010.551340550813,\n            'f': \"2010.551340550813\",\n        },\n{\n            'v': 31.588974156856878,\n            'f': \"31.588974156856878\",\n        },\n{\n            'v': 37.4320325056467,\n            'f': \"37.4320325056467\",\n        },\n{\n            'v': 6.0069028804462645,\n            'f': \"6.0069028804462645\",\n        },\n{\n            'v': 33.54929591883267,\n            'f': \"33.54929591883267\",\n        }],\n [\"std\",\n{\n            'v': 6.720732568715551,\n            'f': \"6.720732568715551\",\n        },\n{\n            'v': 32.40776505076356,\n            'f': \"32.40776505076356\",\n        },\n{\n            'v': 7.643126156661599,\n            'f': \"7.643126156661599\",\n        },\n{\n            'v': 8.172157940216158,\n            'f': \"8.172157940216158\",\n        },\n{\n            'v': 9.954949852703564,\n            'f': \"9.954949852703564\",\n        }],\n [\"min\",\n{\n            'v': 1994.0,\n            'f': \"1994.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        },\n{\n            'v': 0.0,\n            'f': \"0.0\",\n        }],\n [\"25%\",\n{\n            'v': 2006.0,\n            'f': \"2006.0\",\n        },\n{\n            'v': 7.3,\n            'f': \"7.3\",\n        },\n{\n            'v': 30.0,\n            'f': \"30.0\",\n        },\n{\n            'v': 1.8,\n            'f': \"1.8\",\n        },\n{\n            'v': 26.0,\n            'f': \"26.0\",\n        }],\n [\"50%\",\n{\n            'v': 2011.0,\n            'f': \"2011.0\",\n        },\n{\n            'v': 19.8,\n            'f': \"19.8\",\n        },\n{\n            'v': 40.0,\n            'f': \"40.0\",\n        },\n{\n            'v': 3.56,\n            'f': \"3.56\",\n        },\n{\n            'v': 31.0,\n            'f': \"31.0\",\n        }],\n [\"75%\",\n{\n            'v': 2016.0,\n            'f': \"2016.0\",\n        },\n{\n            'v': 45.6,\n            'f': \"45.6\",\n        },\n{\n            'v': 44.0,\n            'f': \"44.0\",\n        },\n{\n            'v': 6.9,\n            'f': \"6.9\",\n        },\n{\n            'v': 39.0,\n            'f': \"39.0\",\n        }],\n [\"max\",\n{\n            'v': 2021.0,\n            'f': \"2021.0\",\n        },\n{\n            'v': 140.1,\n            'f': \"140.1\",\n        },\n{\n            'v': 60.0,\n            'f': \"60.0\",\n        },\n{\n            'v': 149.97,\n            'f': \"149.97\",\n        },\n{\n            'v': 100.0,\n            'f': \"100.0\",\n        }]],\n        columns: [[\"string\", \"index\"], [\"number\", \"ano\"], [\"number\", \"tempo_emprego\"], [\"number\", \"quantidade_horas_contratadas\"], [\"number\", \"valor_remuneracao_media_sm\"], [\"number\", \"idade\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n\n      function appendQuickchartButton(parentElement) {\n        let quickchartButtonContainerElement = document.createElement('div');\n        quickchartButtonContainerElement.innerHTML = `\n<div id=\"df-d739cc31-1bac-445f-8106-ab8a8f5a15da\">\n  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d739cc31-1bac-445f-8106-ab8a8f5a15da')\"\n            title=\"Suggest charts.\"\n            style=\"display:none;\">\n    \n<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n     width=\"24px\">\n    <g>\n        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n    </g>\n</svg>\n  </button>\n  \n<style>\n  .colab-df-quickchart {\n      --bg-color: #E8F0FE;\n      --fill-color: #1967D2;\n      --hover-bg-color: #E2EBFA;\n      --hover-fill-color: #174EA6;\n      --disabled-fill-color: #AAA;\n      --disabled-bg-color: #DDD;\n  }\n\n  [theme=dark] .colab-df-quickchart {\n      --bg-color: #3B4455;\n      --fill-color: #D2E3FC;\n      --hover-bg-color: #434B5C;\n      --hover-fill-color: #FFFFFF;\n      --disabled-bg-color: #3B4455;\n      --disabled-fill-color: #666;\n  }\n\n  .colab-df-quickchart {\n    background-color: var(--bg-color);\n    border: none;\n    border-radius: 50%;\n    cursor: pointer;\n    display: none;\n    fill: var(--fill-color);\n    height: 32px;\n    padding: 0;\n    width: 32px;\n  }\n\n  .colab-df-quickchart:hover {\n    background-color: var(--hover-bg-color);\n    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n    fill: var(--button-hover-fill-color);\n  }\n\n  .colab-df-quickchart-complete:disabled,\n  .colab-df-quickchart-complete:disabled:hover {\n    background-color: var(--disabled-bg-color);\n    fill: var(--disabled-fill-color);\n    box-shadow: none;\n  }\n\n  .colab-df-spinner {\n    border: 2px solid var(--fill-color);\n    border-color: transparent;\n    border-bottom-color: var(--fill-color);\n    animation:\n      spin 1s steps(1) infinite;\n  }\n\n  @keyframes spin {\n    0% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n      border-left-color: var(--fill-color);\n    }\n    20% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    30% {\n      border-color: transparent;\n      border-left-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n      border-right-color: var(--fill-color);\n    }\n    40% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-top-color: var(--fill-color);\n    }\n    60% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n    }\n    80% {\n      border-color: transparent;\n      border-right-color: var(--fill-color);\n      border-bottom-color: var(--fill-color);\n    }\n    90% {\n      border-color: transparent;\n      border-bottom-color: var(--fill-color);\n    }\n  }\n</style>\n\n  <script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-d739cc31-1bac-445f-8106-ab8a8f5a15da button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  </script>\n</div>`;\n        parentElement.appendChild(quickchartButtonContainerElement);\n      }\n\n      appendQuickchartButton(table);\n    "
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Correlações"
      ],
      "metadata": {
        "id": "bHStIbPqnt8F"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = tempoempregousar.corr()\n",
        "sns.heatmap(corr_matrix, annot = True)"
      ],
      "metadata": {
        "id": "fDb-UvJkny6q",
        "outputId": "1681578f-c777-4ea2-acea-33f468bec337",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        }
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-23-5b0c9da66bb2>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr_matrix = tempoempregousar.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = remuneracao.corr()\n",
        "sns.heatmap(corr_matrix, annot = True)"
      ],
      "metadata": {
        "id": "Ds2WnTkIom2-",
        "outputId": "0a4ba611-e65a-4603-e123-4fda1ce0b480",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        }
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-24-66634d3b482c>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr_matrix = remuneracao.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = horasusar.corr()\n",
        "sns.heatmap(corr_matrix, annot = True)"
      ],
      "metadata": {
        "id": "Iexq1O95o39p",
        "outputId": "c3b49228-5570-46b2-8f93-6f00a731485a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        }
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-25-eff8b5b4f8c2>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr_matrix = horasusar.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = idadeusar.corr()\n",
        "sns.heatmap(corr_matrix, annot = True)"
      ],
      "metadata": {
        "id": "wPQYHFNZpO41",
        "outputId": "9c8ffdf7-5ed0-4a41-a581-ea68efbffac8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        }
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-26-869ba13ccab3>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr_matrix = idadeusar.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix = results.corr()\n",
        "sns.heatmap(corr_matrix, annot = True)"
      ],
      "metadata": {
        "id": "WjtxVinLprQQ",
        "outputId": "e340aa96-1809-4396-9cf5-8c676bac4892",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        }
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-27-6637a8e5a363>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr_matrix = results.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Plotagens e produção de medidas agregadas"
      ],
      "metadata": {
        "id": "UeAIySFffmZL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Para plotagem\n",
        "\n",
        "def plot(x, y, ax, title, y_label):\n",
        "    ax.set_title(title)\n",
        "    ax.set_ylabel(y_label)\n",
        "    ax.plot(x, y)\n",
        "    ax.margins(x=0, y=0)"
      ],
      "metadata": {
        "id": "NqA_dUJXfhqA"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Tempo médio do funcionário na empresa\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = tempoempregousar.loc[:, ['ano', 'tempo_emprego']].groupby('ano')\n",
        "avgs = groupbyyear.mean()\n",
        "x = avgs.index\n",
        "y = avgs.tempo_emprego\n",
        "a = np.asarray(y)\n",
        "plot(x, y, ax, 'Mudanças no tempo do funcionário no emprego', 'Tempo médio (meses)')\n",
        "pd.DataFrame(a, index = x).to_csv('tempo.csv', sep = ';', header  = ['tempo_emprego'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "03G_yBCNfts_",
        "outputId": "85ec247c-34a4-41ec-c1ab-162ae8d309b3"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Idade\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = idadeusar.loc[:, ['ano', 'tempo_emprego', 'quantidade_horas_contratadas', 'valor_remuneracao_media_sm', 'idade']].groupby('ano')\n",
        "avgs = groupbyyear.mean()\n",
        "x1 = avgs.index\n",
        "y1 = avgs.idade\n",
        "a1 = np.asarray(y1)\n",
        "plot(x1, a1, ax, 'Mudanças na idade do funcionário', 'Idade média (anos)')\n",
        "pd.DataFrame(a1, index = x1).to_csv('idade.csv', sep = ';', header  = ['idade'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "UAAhcb91gI6D",
        "outputId": "6661161c-7cdb-46c1-c316-5e0f8c78b0cc"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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ymazaX9lJSUnYuHFjvc5FLpdj/Pjx+Ouvv3Ds2LG7Xq/6i9jIyOiuv9TXrFlzV41KVlZWteempqYIDg6GEALl5eX1ivF2VX+53x6LEAJLliypV3tdu3aFg4MDvvnmG82Qf6ByKPediWtNxz58+DAiIyOr7Tdy5EhUVFRUGzKtUqnwxRdfVNvP0dERAwYMwLfffou0tLS7Yrt+/fo9Y6/rcW7/fN1+TmfOnMH27dsxcuTIex6nNlW1Zbd/vgsLC7Fy5cp6tQcAEydOxKlTp2qcAqK2niJ9nF9Vgnv7Z/bGjRv48ccftW7rdiNHjsSRI0eqfWYKCwuxbNkyeHl51VjzR00be4Co2alpqPGdlEolHn74YXzxxReQyWTw9fXF5s2ba6zriIiIwKhRo9CnTx88/fTTyM7O1synU1BQoNlv1KhR+PTTTzF8+HA88cQTyMjIwFdffQU/Pz+cPn26XufywQcfYPv27ejfvz9mzJiBoKAgpKWlYc2aNTh48CBatWqF0aNH491338XUqVPRq1cvxMTE4Ndff72rTmbo0KFwdnZG79694eTkhPPnz+PLL7/EqFGjYG1tXa/4bhcYGAhfX1/MmzcPV69ehY2NDdatW1etdkMbJiYmeP/99zFz5kwMHDgQjz76KBITE7F8+fK7zm306NFYv349JkyYgFGjRiExMRHffPMNgoODq32NxowZg969e+O1115DUlISgoODsX79+hrrk7766iv06dMHHTp0wPTp0+Hj44P09HRERkYiJSWlxnmW6nOcjz/+GCNGjEBYWBimTZumGSauVCrx9ttv1+vaDR06FB4eHpg2bRrmz58PIyMj/Pjjj3BwcEBycnK92pw/fz7Wrl2Lhx9+GE8//TRCQ0ORnZ2NTZs24ZtvvqnWI6fP8xsyZAhMTEwwduxYzJw5E/n5+Vi2bBlcXV2Rnp5er3MDgNdee00zjcaLL74IW1tbrFy5EomJiVi3bh0n6GyOJBl7RqQjtw+Dv5c7h8ELIcT169fFxIkThYWFhWjdurWYOXOmOHPmzF3DeIUQYt26dSIoKEgoFAoRHBws1q9fLyZPnnzXMPgffvhB+Pv7C4VCIQIDA8Xy5ctrHJKMGoYuV8V5+9BcIYS4fPmymDRpknBwcBAAhLu7u3juuec0w75LSkrEyy+/LFxcXIS5ubno3bu3iIyMFP379682VPzbb78V/fr1E3Z2dkKhUAhfX18xf/58kZube89rVzU8fc2aNdW21zTk+dy5c2Lw4MHCyspK2Nvbi+nTp2uG9995TWs7zp1TE3z99dfC29tbKBQK0bVrV7F///67zk2tVosPPvhAeHp6CoVCITp37iw2b95c49coKytLPPXUU8LGxkYolUrx1FNPiZMnT9YYY0JCgpg0aZJwdnYWJiYmok2bNmL06NFi7dq19zwXbY+zc+dO0bt3b2Fubi5sbGzEmDFjxLlz5+57DCFq/ywdP35c9OjRQ5iamgoPDw/x6aef1joM/s7vDSHEXde46pyef/550aZNG2Fqairc3NzE5MmTRWZmphCi5s9EXc+v6vvk+vXr1bbXFPPGjRtFhw4dhJmZmfDx8RGffPKJ+PHHH+t8blWv3fm9lpCQIB566CHRqlUrYWZmJrp37y42b95c4/up6ZMJIUGVGxHVyzPPPIPu3btjxowZUodCRNSksU+PqAkZM2YMfvnlF6nDICJq8lgDRNQE/P3330hNTcXmzZur1bQQEVH9MAEiagJSUlIwd+5cWFtb17joIxERaYc1QERERNTisAaIiIiIWhwmQERERNTiMAEiIiKiFodF0DVQq9VITU2FtbV1rYsKEhERkWERQiA/Px+urq73nb2bCVANUlNT4e7uLnUYREREVA9XrlyBm5vbPfdhAlSDqnWRrly5AhsbG4mjISIiap42RV/F6xvOwM7SBL880xO7L6Tj79PXcC4tT7OPuakcAwMcMaqjK3r52MHYqPaenby8PLi7u9dpfUMOg69BXl4elEolcnNzmQARERHpgVotMHTxfsRnFGD+sAA894Cf5rX4jAJsir6KjdGpSM4u0my3szTF6BAXjOvcBp3dW91VpqLN728mQDVgAkRERKRf285ew8yfj8NaYYx/wwfCxszkrn2EEDiRnIM/o69i8+k0ZBeWaV7ztLPAuE5tML6TK3wcrAAwAWowJkBERET6I4TA+K/+xamUXDw7wBevDA+873vKVWocjMvExuir2H42HcXlKs1rIW5KjOvUBgO8LeHn5lSn39+sASIiIqJGdSghC6dScqEwluPpPt51eo+JkRwPBDrigUBHFJZWYMe5dGyMvooDcZk4nZKL0ym5eK+s6P4N3cQEiIiIiBrVV3viAQCPdXOHvZVC6/dbKowxvnMbjO/cBpkFpfj7dBo2Rl/F8TgmQERERGSATibfwKGELBjLZZjez6fB7dlbKTC5lxcm9/JCTGIaQhbX7X2cCZqIiIgazdd7EwAA4zq1gVtrC5227WlnWed9mQARERFRo7iYno8d59IhkwGzBzS896chmAARERFRo1h6s/dnWLAz/BzvP1mhPjEBIiIiIr27kl2ETadSAQDPPuArcTRMgIiIiKgRfLs/ASq1QF9/e4S4tZI6HCZAREREpF8Z+SX441gKAODZAX732btxMAEiIiIivfrhYCLKKtTo4tEKPX1spQ4HABMgIiIi0qPconL8GpUMoLL3584FTKXCBIiIiIj05qfIJBSUViDQ2RoDAx2lDkeDCRARERHpRVFZBZYfSgIAzB7gC7ncMHp/ACZAREREpCerj1xBdmEZPGwtMKqDi9ThVMMEiIiIiHSurEKN7w5cAgDM7O8DYyPDSjkMKxoiIiJqFjaevIq03BI4WiswsYub1OHchQkQERER6ZRKLfDNvsplL57p6w0zEyOJI7obEyAiIiLSqa1nruFSZiGU5iZ4ooen1OHUiAkQERER6YwQAl/vjQcATO7lBSuFscQR1YwJEBEREenMvovXcTY1DxamRpjay0vqcGrFBIiIiIh05uu9lbU/j3f3QGtLU4mjqZ2kCdDSpUsREhICGxsb2NjYICwsDFu2bKm2T2RkJAYOHAhLS0vY2NigX79+KC4urrXNt99+GzKZrNojMDBQ36dCRETU4h1LysaRxGyYGMkwva+P1OHck6Q35tzc3LBo0SL4+/tDCIGVK1di3LhxOHnyJNq1a4fIyEgMHz4c4eHh+OKLL2BsbIxTp05BLr933tauXTvs3LlT89zY2DDvPxIRETUnVb0/E7u4wVlpJnE09yZpZjBmzJhqzxcuXIilS5ciKioK7dq1w0svvYQXX3wRr732mmafgICA+7ZrbGwMZ2dnncdLRERENTuXmofdFzIglwEz+/tKHc59GUwNkEqlwurVq1FYWIiwsDBkZGTg8OHDcHR0RK9eveDk5IT+/fvj4MGD920rLi4Orq6u8PHxwZNPPonk5OR77l9aWoq8vLxqDyIiIqq7pTfn/RnZwQXe9pYSR3N/kidAMTExsLKygkKhwKxZs7BhwwYEBwfj0qXK6bPffvttTJ8+HVu3bkWXLl0waNAgxMXF1dpejx49sGLFCmzduhVLly5FYmIi+vbti/z8/FrfExERAaVSqXm4u7vr/DyJiIiaq6TMQvx9OhUA8OwAP4mjqRuZEEJIGUBZWRmSk5ORm5uLtWvX4vvvv8e+ffuQk5OD3r17Izw8HB988IFm/5CQEIwaNQoRERF1aj8nJweenp749NNPMW3atBr3KS0tRWlpqeZ5Xl4e3N3dkZubCxsbm4adIBERUTMXvv40fjtyBQ8EOGD51O6SxZGXlwelUlmn39+SVwebmprCz68yWwwNDcXRo0exZMkSTd1PcHBwtf2DgoLue0vrdq1atULbtm0RHx9f6z4KhQIKhaIe0RMREbVs13JLsPZ4CgDguQeaRu8PYAC3wO6kVqtRWloKLy8vuLq6IjY2ttrrFy9ehKdn3afVLigoQEJCAlxcXHQdKhERUYv3/YFLKFcJdPeyRVcvW6nDqTNJe4DCw8MxYsQIeHh4ID8/H6tWrcLevXuxbds2yGQyzJ8/HwsWLEDHjh3RqVMnrFy5EhcuXMDatWs1bQwaNAgTJkzA888/DwCYN28exowZA09PT6SmpmLBggUwMjLC448/LtVpEhERNUs3Csuw6kjlXZlnHzD8kV+3kzQBysjIwKRJk5CWlgalUomQkBBs27YNQ4YMAQDMmTMHJSUleOmll5CdnY2OHTtix44d8PW9dZETEhKQmZmpeZ6SkoLHH38cWVlZcHBwQJ8+fRAVFQUHB4dGPz8iIqLmbMWhJBSVqdDO1Qb92zat37OSF0EbIm2KqIiIiFqigtIK9F60G7nF5fjqiS4YFSJ9qYk2v78NrgaIiIiIDN8vUZeRW1wOH3tLDG/f9CYfZgJEREREWtkbm4FPtlcOUprV3xdGcpnEEWmPCRARERHV2dGkbMz65TjKVQKjQlwwMdRN6pDqhQkQERER1cmZq7l4evlRlJSrMSDAAZ890qlJ9v4ATICIiIioDuIzCjDpxyPIL61Ad29bLH0yFKbGTTeNaLqRExERUaO4kl2E/3x/GNmFZejQRokfJneFuamR1GE1CBMgIiIiqlVGfgme+uEwruWVwM/RCiuf7g5rMxOpw2owJkBERERUo5yiMjz1/REkZRXBrbU5fpnWA7aWplKHpRNMgIiIiOguBaUVmLL8KGLT8+ForcCvz/SAs9JM6rB0hgkQERERVVNSrsKMn44h+koOWlmY4OdpPeBpZyl1WDrFBIiIiIg0ylVqvPDbSRxKyIKlqRFWTO2OAGdrqcPSOSZAREREBABQqwVeWXsaO86lw9RYju8nd0Mn91ZSh6UXTICIiIgIQggs2HQWG05ehbFchqVPdkGYr53UYekNEyAiIiLCx9ti8XPUZchkwCePdMSgICepQ9IrJkBEREQt3NK9Cfh6bwIA4P3x7TGuUxuJI9I/JkBEREQt2K+HL+PDrRcAAK+NCMSTPTwljqhxMAEiIiJqof6Mvoo3Np4BADw7wBez+vtKHFHjYQJERETUAu08l465f5yCEMBTPT0xf1iA1CE1KiZARERELcyhhEw8u+oEVGqBCZ3b4J2x7SCTyaQOq1ExASIiImpBoq/kYPrKYyirUGNIsBM+figEcnnLSn4AJkBEREQtRlZBKaYuP4LCMhV6+drhi8c7w9ioZaYCLfOsiYiIWqAvdsfjRlE5Ap2tsWxSV5iZGEkdkmSYABEREbUAyVlF+PXwZQDAm6ODYaUwljgiaTEBIiIiagE+3RGLcpVAX3979PazlzocyTEBIiIiaubOXM3FxuhUAMCrwwMljsYwMAEiIiJq5j7aFgsAGNvRFe3bKCWOxjAwASIiImrG/o3PxP6L12FiJMO8oS1rssN7YQJERETUTAkhNOt8PdHdAx52FhJHZDiYABERETVT/8Rcw+mUXFiaGuGFQf5Sh2NQmAARERE1Q+UqNT7eVtn7M72fD+ytFBJHZFiYABERETVDq49eQVJWEeytTPFMXx+pwzE4TICIiIiamcLSCizZGQcAeHGQf4uf9LAmTICIiIiamR8OJiKzoBQethZ4rJuH1OEYJEkToKVLlyIkJAQ2NjawsbFBWFgYtmzZUm2fyMhIDBw4EJaWlrCxsUG/fv1QXFx8z3a/+uoreHl5wczMDD169MCRI0f0eRpEREQGI6ugFMv2XwIAzBsWAFNj9nXURNKr4ubmhkWLFuH48eM4duwYBg4ciHHjxuHs2bMAKpOf4cOHY+jQoThy5AiOHj2K559/HnJ57WH//vvvmDt3LhYsWIATJ06gY8eOGDZsGDIyMhrrtIiIiCTz5Z54FJRWoH0bG4zu4CJ1OAZLJoQQUgdxO1tbW3z88ceYNm0aevbsiSFDhuC9996r8/t79OiBbt264csvvwQAqNVquLu744UXXsBrr71Wpzby8vKgVCqRm5sLGxubep0HERFRY7uSXYSBn+xFuUrgl2k90Me/Za35pc3vb4PpF1OpVFi9ejUKCwsRFhaGjIwMHD58GI6OjujVqxecnJzQv39/HDx4sNY2ysrKcPz4cQwePFizTS6XY/DgwYiMjGyM0yAiIpLMJ9tvLXja0pIfbUmeAMXExMDKygoKhQKzZs3Chg0bEBwcjEuXKu9fvv3225g+fTq2bt2KLl26YNCgQYiLi6uxrczMTKhUKjg5OVXb7uTkhGvXrtUaQ2lpKfLy8qo9iIiImpKzqVzwVBuSJ0ABAQGIjo7G4cOHMXv2bEyePBnnzp2DWq0GAMycORNTp05F586d8dlnnyEgIAA//vijTmOIiIiAUqnUPNzd3XXaPhERkb59tLVywdMxXPC0TiRPgExNTeHn54fQ0FBERESgY8eOWLJkCVxcKgu3goODq+0fFBSE5OTkGtuyt7eHkZER0tPTq21PT0+Hs7NzrTGEh4cjNzdX87hy5UoDz4qIiKjxHIrPxL6L12Esl2He0LZSh9MkSJ4A3UmtVqO0tBReXl5wdXVFbGxstdcvXrwIT0/PGt9ramqK0NBQ7Nq1q1p7u3btQlhYWK3HVCgUmqH4VQ8iIqKmQAiBRTcXPH2yhwc87SwljqhpkHRqyPDwcIwYMQIeHh7Iz8/HqlWrsHfvXmzbtg0ymQzz58/HggUL0LFjR3Tq1AkrV67EhQsXsHbtWk0bgwYNwoQJE/D8888DAObOnYvJkyeja9eu6N69OxYvXozCwkJMnTpVqtMkIiLSm6oFTy1MjfD8QC54WleSJkAZGRmYNGkS0tLSoFQqERISgm3btmHIkCEAgDlz5qCkpAQvvfQSsrOz0bFjR+zYsQO+vr6aNhISEpCZmal5/uijj+L69et46623cO3aNXTq1Albt269qzCaiIioqStXqfG/7ZV3Sqb39YGDNRc8rSuDmwfIEHAeICIiagp+ibqMNzaegZ2lKfa98kCLX/OrSc4DRERERHVXWFqBxVzwtN6YABERETVBP9624Onj3bngqbaYABERETUxWQWl+PbmgqcvD23LBU/rgVeMiIioiflqTwIKSivQztUGY0JcpQ6nSWICRERE1IRcyS7Cz1FJAIDXRgRCLpdJG1ATxQSIiIioCfl0x0WUqwT6+Nmjr7+D1OE0WUyAiIiImojKBU+vAuCCpw3FBIiIiKiJ+GhrLIQARoe4oIMbFzxtCCZARERETcChhNsXPA2QOpwmjwkQERGRgRNC4MMtlQuePtHDA172XPC0oZgAERERGbi/Y9Jw6uaCpy9wwVOdYAJERERkwIrKKvDB3+cBcMFTXWICREREZMC+3B2P1NwSuLU2x6z+vlKH02wwASIiIjJQCdcL8N2ByiUv3hodDHNTI4kjaj6YABERERkgIQTe3nQW5SqBBwIcMCTYSeqQmhUmQERERAZoy5lrOBCXCVNjOd4e2w4yGZe80CUmQERERAamqKwC720+BwCY1d8XnnYc9q5rTICIiIgMzBe745F2s/D52QEsfNYHJkBEREQGJD6jAN/fLHxeMKYdzExY+KwPTICIiIgMxO2FzwMDHTE4yFHqkJotJkBEREQGYsuZazgYX1n4vGBMMAuf9YgJEBERkQEoLGXhc2NiAkRERGQAWPjcuJgAERERSSw+owA/HKwsfH6bhc+NggkQERGRhG4vfB4U6IjBnPG5UTABIiIiktA/MbcXPreTOpwWgwkQERGRRG4vfJ7d3xcedhYSR9RyMAEiIiKSyBe743EtrwTutuaYzcLnRsUEiIiISALxGfm3ZnwezcLnxsYEiIiIqJEJIbBg01lUqFn4LBUmQERERI3s75g0/BufxcJnCTEBIiIiakSFpRV4f/N5AMCzA1j4LBUmQERERI3o891xmsLnWf1Z+CwVJkBERESNJD4jHz8cSATAGZ+lJmkCtHTpUoSEhMDGxgY2NjYICwvDli1bNK8PGDAAMpms2mPWrFn3bHPKlCl3vWf48OH6PhUiIqJ7ur3weXCQIwYFsfBZSsZSHtzNzQ2LFi2Cv78/hBBYuXIlxo0bh5MnT6Jdu8qisOnTp+Pdd9/VvMfC4v73SocPH47ly5drnisUCt0HT0REpIWqwmcFC58NgqQJ0JgxY6o9X7hwIZYuXYqoqChNAmRhYQFnZ2et2lUoFFq/h4iISF8Kbp/xeYAv3G1Z+Cw1g6kBUqlUWL16NQoLCxEWFqbZ/uuvv8Le3h7t27dHeHg4ioqK7tvW3r174ejoiICAAMyePRtZWVn33L+0tBR5eXnVHkRERLryxa44pOeVwsPWgoXPBkKrHiC1Wo19+/bhwIEDuHz5MoqKiuDg4IDOnTtj8ODBcHd31zqAmJgYhIWFoaSkBFZWVtiwYQOCg4MBAE888QQ8PT3h6uqK06dP49VXX0VsbCzWr19fa3vDhw/Hgw8+CG9vbyQkJOD111/HiBEjEBkZCSOjmovNIiIi8M4772gdOxER0f3EZ+Tjh4M3C5/HBrPw2UDIhBDifjsVFxfjk08+wdKlS5GdnY1OnTrB1dUV5ubmyM7OxpkzZ5CamoqhQ4firbfeQs+ePescQFlZGZKTk5Gbm4u1a9fi+++/x759+zRJ0O12796NQYMGIT4+Hr6+dcugL126BF9fX+zcuRODBg2qcZ/S0lKUlpZqnufl5cHd3R25ubmwsbGp87kQERHdTgiBJ78/jEMJWRgc5ITvJ3eVOqRmLS8vD0qlsk6/v+vUA9S2bVuEhYXhu+++w5AhQ2BiYnLXPpcvX8aqVavw2GOP4f/+7/8wffr0OgVramoKPz8/AEBoaCiOHj2KJUuW4Ntvv71r3x49egCAVgmQj48P7O3tER8fX2sCpFAoWChNREQ6t/l0Gg4lVBU+3/2HPUmnTgnQ9u3bERQUdM99PD09ER4ejnnz5iE5ObneAanV6mq9MbeLjo4GALi4uNS5vZSUFGRlZWn1HiIiooaqUKnx4dYLAIBnB/ix8NnA1KkI+n7Jz+1MTEzq3DsTHh6O/fv3IykpCTExMQgPD8fevXvx5JNPIiEhAe+99x6OHz+OpKQkbNq0CZMmTUK/fv0QEhKiaSMwMBAbNmwAABQUFGD+/PmIiopCUlISdu3ahXHjxsHPzw/Dhg2r8zkQERE11PZz6Ui5UQxbS1PM7O8jdTh0B61HgW3duhUHDx7UPP/qq6/QqVMnPPHEE7hx44ZWbWVkZGDSpEkICAjAoEGDcPToUWzbtg1DhgyBqakpdu7ciaFDhyIwMBAvv/wyJk6ciL/++qtaG7GxscjNzQUAGBkZ4fTp0xg7dizatm2LadOmITQ0FAcOHOAtLiIialQ/3ix8/k8PDxY+G6A6FUHfrkOHDvjwww8xcuRIxMTEoFu3bpg7dy727NmDwMDAahMQNlXaFFERERHd6dSVHIz76l+YGMnw76sD4WhjJnVILYLOi6Bvl5iYqBmhtW7dOowePRoffPABTpw4gZEjR9YvYiIiombkx38re3/GdHRl8mOgtL4FZmpqqpmMsOoWFQDY2tpyAkEiImrxruWW4O/TaQCAp3t7SxwN1UbrHqA+ffpg7ty56N27N44cOYLff/8dAHDx4kW4ubnpPEAiIqKm5KfIJFSoBbp726J9G6XU4VAttO4B+vLLL2FsbIy1a9di6dKlaNOmDQBgy5YtXHWdiIhatOIyFVYdqZwKZlof9v4YMq17gDw8PLB58+a7tn/22Wc6CYiIiKipWn8yBTlF5fCwtcDgICepw6F7qNdq8CqVChs3bsT58+cBAO3atcPYsWNrXWuLiIiouVOrhWbo+5ReXjCSyySOiO5F6wQoPj4eI0eOxNWrVxEQEACgcjFRd3d3/P3333WeBJGIiKg52R93HQnXC2GlMMbDXVkTa+i0rgF68cUX4evriytXruDEiRM4ceIEkpOT4e3tjRdffFEfMRIRERm8H/9NAgA80tUd1mZ3r5lJhkXrHqB9+/YhKioKtra2mm12dnZYtGgRevfurdPgiIiImoK49Hzsv3gdchkwtbeX1OFQHWjdA6RQKJCfn3/X9oKCApiamuokKCIioqakqvdnSLATFz1tIrROgEaPHo0ZM2bg8OHDEEJACIGoqCjMmjULY8eO1UeMREREButGYRnWn0gBAEzrw0VPmwqtE6DPP/8cvr6+CAsLg5mZGczMzNC7d2/4+flhyZIl+oiRiIjIYK06kozSCjXat7FBN6/WUodDdaR1DVCrVq3w559/Ii4uDhcuXAAABAUFwc/PT+fBERERGbKyCjV+ikwCULnshUzGoe9NRb3mAQIAf39/+Pv76zIWIiKiJuWfmDSk55XCwVqB0SGuUodDWtA6AVKpVFixYgV27dqFjIwMqNXqaq/v3r1bZ8EREREZKiGEZtX3ST09YWqsdVUJSUjrBOi///0vVqxYgVGjRqF9+/bs7iMiohbp2OUbOJ2SC4WxHE/08JA6HNKS1gnQ6tWr8ccff2DkyJH6iIeIiKhJqFr2YkLnNrCzUkgcDWlL6/46U1NTFjwTEVGLdiW7CNvOXgMAPM1V35skrROgl19+GUuWLIEQQh/xEBERGbyVh5KgFkBff3u0dbKWOhyqB61vgR08eBB79uzBli1b0K5dO5iYVF/vZP369ToLjoiIyNAUlFbg96NXAFQOfaemqV7zAE2YMEEfsRARERm8NceuIL+0Aj4Olujf1kHqcKietE6Ali9fro84iIiIDJ5KLbDiUBIAYGpvb8jlHAndVHHSAiIiojradT4dl7OKoDQ3wcQubaQOhxqgXjNBr127Fn/88QeSk5NRVlZW7bUTJ07oJDAiIiJDUzXx4ePdPWBhWu/FFMgA1Gsx1KlTp8LJyQknT55E9+7dYWdnh0uXLmHEiBH6iJGIiEhyZ1NzEXUpG0ZyGSaFeUodDjWQ1gnQ119/jWXLluGLL76AqakpXnnlFezYsQMvvvgicnNz9REjERGR5H48mAQAGNnBBa6tzKUNhhpM6wQoOTkZvXr1AgCYm5sjPz8fAPDUU0/ht99+0210REREBiAjvwR/nUoFADzd20vaYEgntE6AnJ2dkZ2dDQDw8PBAVFQUACAxMZGTIxIRUbP0S1QyylRqdPFohc4eraUOh3RA6wRo4MCB2LRpEwBg6tSpeOmllzBkyBA8+uijnB+IiIianZJyFX6NugyAy140J1qXsC9btgxqtRoA8Nxzz8HOzg6HDh3C2LFjMXPmTJ0HSEREJKVN0anIKiyDq9IMw9s5Sx0O6YjWCZBcLodcfqvj6LHHHsNjjz2m06CIiIgMgRBCM/R9ci8vGBtx+rzmok5fyeTkZK0avXr1ar2CISIiMiSRCVm4cC0f5iZGeKybh9ThkA7VKQHq1q0bZs6ciaNHj9a6T25uLr777ju0b98e69at01mAREREUvnhYGXvz8Nd3aC0MLnP3tSU1OkW2Llz57Bw4UIMGTIEZmZmCA0NhaurK8zMzHDjxg2cO3cOZ8+eRZcuXfDRRx9h5MiR+o6biIhIrxIzC7HrQgYAYEovL2mDIZ2rUw+QnZ0dPv30U6SlpeHLL7+Ev78/MjMzERcXBwB48skncfz4cURGRmqV/CxduhQhISGwsbGBjY0NwsLCsGXLFs3rAwYMgEwmq/aYNWvWPdsUQuCtt96Ci4sLzM3NMXjwYE2cREREdbX8Zu3PwEBH+DhYSRwN6ZpMSDh5z19//QUjIyP4+/tDCIGVK1fi448/xsmTJ9GuXTsMGDAAbdu2xbvvvqt5j4WFBWxsbGpt88MPP0RERARWrlwJb29vvPnmm4iJicG5c+dgZmZWp7jy8vKgVCqRm5t7z2MREVHzlFtUjp4Ru1BcrsKvz/RAbz97qUOiOtDm97ekK7mNGTOm2vOFCxdi6dKliIqKQrt27QBUJjzOznUbdiiEwOLFi/HGG29g3LhxAICffvoJTk5O2LhxI0erERFRnaw+mozichUCna3Ry9dO6nBIDwxmPJ9KpcLq1atRWFiIsLAwzfZff/0V9vb2aN++PcLDw1FUVFRrG4mJibh27RoGDx6s2aZUKtGjRw9ERkbW+r7S0lLk5eVVexARUctUoVJj5aEkAMDTvb0hk8mkDYj0QtIeIACIiYlBWFgYSkpKYGVlhQ0bNiA4OBgA8MQTT8DT0xOurq44ffo0Xn31VcTGxmL9+vU1tnXt2jUAgJOTU7XtTk5OmtdqEhERgXfeeUdHZ0RERE3ZzvMZSM0tga2lKcZ2cpU6HNITyROggIAAREdHIzc3F2vXrsXkyZOxb98+BAcHY8aMGZr9OnToABcXFwwaNAgJCQnw9fXVWQzh4eGYO3eu5nleXh7c3d111j4RETUdvx+tnPvu4a5uMDMxkjga0hfJb4GZmprCz88PoaGhiIiIQMeOHbFkyZIa9+3RowcAID4+vsbXq2qF0tPTq21PT0+/Zx2RQqHQjESrehARUcuTmlOMfRevAwAnPmzm6t0DdO7cOSQnJ6OsrKza9rFjxzYoILVajdLS0hpfi46OBgC4uLjU+Lq3tzecnZ2xa9cudOrUCUBlb87hw4cxe/bsBsVFRETN35pjKVALoIe3LbztLaUOh/RI6wTo0qVLmDBhAmJiYiCTyVA1ir6qSEylUtW5rfDwcIwYMQIeHh7Iz8/HqlWrsHfvXmzbtg0JCQlYtWoVRo4cCTs7O5w+fRovvfQS+vXrh5CQEE0bgYGBiIiIwIQJEyCTyTBnzhy8//778Pf31wyDd3V1xfjx47U9VSIiakFUaoE/jl0BADzenb0/zZ3WCdB///tfeHt7Y9euXfD29saRI0eQlZWFl19+Gf/73/+0aisjIwOTJk1CWloalEolQkJCsG3bNgwZMgRXrlzBzp07sXjxYhQWFsLd3R0TJ07EG2+8Ua2N2NhY5Obmap6/8sorKCwsxIwZM5CTk4M+ffpg69atdZ4DiIiIWqaD8Zm4mlMMGzNjDG/PVd+bO60nQrS3t8fu3bsREhICpVKJI0eOICAgALt378bLL7+MkydP6ivWRsOJEImIWp5nfz2Of2KuYUovL7w9tp3U4VA9aPP7W+siaJVKBWtrawCVyVBqaioAwNPTE7GxsfUIl4iISFqZBaXYca5yAM2j3TgKuCXQ+hZY+/btcerUKXh7e6NHjx746KOPYGpqimXLlsHHx0cfMRIREenV+hMpKFcJdHRTIsiFPf8tgdYJ0BtvvIHCwkIAwLvvvovRo0ejb9++sLOzw++//67zAImIiPRJCIHVRyuLnx9j8XOLoXUCNGzYMM3//fz8cOHCBWRnZ6N169acLpyIiJqco0k3cOl6ISxMjTCmI2d+bil0MhO0ra2tLpohIiJqdKtvzvw8JsQVVgrJF0igRlKnr/SDDz6IFStWwMbGBg8++OA9961tnS4iIiJDk1tcjn9i0gAAj3Zn8XNLUqcESKlUam5vKZVKvQZERETUWDZFX0VJuRoBTtbo7N5K6nCoEdUpAVq+fHmN/yciImqqhBD47Uhl8fOj3dxZx9rCSL4YKhERkRTOXM3DubQ8mBrJMaFzG6nDoUZWpx6gzp071zkzPnHiRIMCIiIiagy/3Sx+Ht7eGa0tTSWOhhpbnRKg2xcSLSkpwddff43g4GCEhYUBAKKionD27Fk8++yzegmSiIhIl4rKKrApunIlg8c483OLVKcEaMGCBZr/P/PMM3jxxRfx3nvv3bXPlStXdBsdERGRHmw+nYaC0gp42lmgp4+d1OGQBLSuAVqzZg0mTZp01/b//Oc/WLdunU6CIiIi0qffb878/EhXd8jlLH5uibROgMzNzfHvv//etf3ff/+FmZmZToIiIiLSl7j0fBy/fANGchkeDnWTOhySiNZTXs6ZMwezZ8/GiRMn0L17dwDA4cOH8eOPP+LNN9/UeYBERES6VLXu18BARzja8A/3lkrrBOi1116Dj48PlixZgl9++QUAEBQUhOXLl+ORRx7ReYBERES6UlqhwvoTKQCAxznzc4tWr0VPHnnkESY7RETU5Gw/m44bReVwtjFDP38HqcMhCdVrIsScnBx8//33eP3115GdnQ2gcv6fq1ev6jQ4IiIiXaoqfn64qxuMjTgXcEt23x6g9PR0ODk5aZ6fPn0agwcPhlKpRFJSEp555hnY2tpi/fr1SE5Oxk8//aTXgImIiOojOasIB+MzIZNVjv6ilu2+6e+3336L119/XfN87ty5mDJlCuLi4qqN+ho5ciT279+vnyiJiIga6I9jlb0/ffzs4W5rIXE0JLX7JkAvvvgizp49i8mTJwMAjh49ipkzZ961X5s2bXDt2jXdR0hERNRAFSo11hyvTIAe6+YhcTRkCO6bALVq1Qp//vkn2rdvDwBQKBTIy8u7a7+LFy/CwYEFZUREZHj2xl5Hel4pbC1NMTjYUepwyADUuQJs/vz5AICxY8fi3XffRXl5OQBAJpMhOTkZr776KiZOnKifKImIiBqgau6fiV3aQGFsJHE0ZAi0LoH/5JNPUFBQAEdHRxQXF6N///7w8/ODtbU1Fi5cqI8YiYiI6i09rwR7YjMAAI9y4VO6Set5gJRKJXbs2IGDBw/i9OnTKCgoQJcuXTB48GB9xEdERNQga4+nQKUW6OrZGn6O1lKHQwaiXhMhAkCfPn3Qp08fXcZCRESkU2q1wOqjyQCAx7qz+JluqVcCdPToUezZswcZGRlQq9XVXvv00091EhgREVFDRV7KwpXsYlgrjDGyg7PU4ZAB0ToB+uCDD/DGG28gICAATk5OkMlkmtdu/z8REZHUqoqfx3V2hYVpvW96UDOk9adhyZIl+PHHHzFlyhQ9hENERKQb2YVl2Hamcn46zv1Dd9J6FJhcLkfv3r31EQsREZHObDh5FWUqNdq3sUH7NkqpwyEDo3UC9NJLL+Grr77SRyxEREQ6IYTA6iOVxc+PsveHaqD1LbB58+Zh1KhR8PX1RXBwMExMTKq9vn79ep0FR0REVB8nknMQl1EAMxM5xnVylTocMkBaJ0Avvvgi9uzZgwceeAB2dnYsfCYiIoNT1fszqoMrbMxM7rM3tURa3wJbuXIl1q1bhy1btmDFihVYvnx5tYc2li5dipCQENjY2MDGxgZhYWHYsmXLXfsJITBixAjIZDJs3Ljxnm1OmTIFMpms2mP48OFaxUVERE1Xfkk5Np9OAwA81p0zP1PNtO4BsrW1ha+vr04O7ubmhkWLFsHf3x9CCKxcuRLjxo3DyZMn0a5dO81+ixcv1qqnafjw4dWSMYVCoZN4iYjI8P11Kg3F5Sr4Oliiq2drqcMhA6V1AvT2229jwYIFWL58OSwsLBp08DFjxlR7vnDhQixduhRRUVGaBCg6OhqffPIJjh07BhcXlzq1q1Ao4OzMCa+IiFoizczP3TxYpkG10joB+vzzz5GQkAAnJyd4eXndVQR94sSJegWiUqmwZs0aFBYWIiwsDABQVFSEJ554Al999ZVWCc3evXvh6OiI1q1bY+DAgXj//fdhZ2dXr7iIiKjpOJuai9MpuTAxkuHBLm2kDocMmNYJ0Pjx43UaQExMDMLCwlBSUgIrKyts2LABwcHBACqH3Pfq1Qvjxo2rc3vDhw/Hgw8+CG9vbyQkJOD111/HiBEjEBkZCSMjoxrfU1paitLSUs3zvLy8hp0UERFJ4vebMz8PDXaGnRXLH6h2WidACxYs0GkAAQEBiI6ORm5uLtauXYvJkydj3759iI+Px+7du3Hy5Emt2nvsscc0/+/QoQNCQkLg6+uLvXv3YtCgQTW+JyIiAu+8806DzoOIiKRVUq7ChpNXAbD4me5PJoQQUgdxu8GDB8PX1xfm5ub4/PPPIZffGqimUqkgl8vRt29f7N27t85tOjg44P3338fMmTNrfL2mHiB3d3fk5ubCxsam3udCRESNZ/2JFMz94xTatDLHgVcegFzO+p+WJi8vD0qlsk6/vw1uZTi1Wo3S0lK88847eOaZZ6q91qFDB3z22Wd3FU/fS0pKCrKysu5ZQK1QKDhSjIioCcsvKcf/tsUCAB7v7s7kh+5L0gQoPDwcI0aMgIeHB/Lz87Fq1Srs3bsX27Ztg7Ozc42Fzx4eHvD29tY8DwwMREREBCZMmICCggK88847mDhxIpydnZGQkIBXXnkFfn5+GDZsWGOeGhERNaIP/rmA1NwSeNha4Ok+3vd/A7V4kiZAGRkZmDRpEtLS0qBUKhESEoJt27ZhyJAhdW4jNjYWubm5AAAjIyOcPn0aK1euRE5ODlxdXTF06FC899577OEhImqmDsRdx283Z37+6KEQWJga3M0NMkD1rgEqKytDYmIifH19YWzcvD5s2txDJCIi6eSXlGP44gO4mlOMKb288PbYdvd/EzVb2vz+1nopjKKiIkybNg0WFhZo164dkpMrs+4XXngBixYtql/ERERE9RCx5QKu5hTDw9YCrwwPkDocakK0ToDCw8Nx6tQp7N27F2ZmZprtgwcPxu+//67T4IiIiGpzMC4Tqw5X/hH+4UTe+iLtaP1p2bhxI37//Xf07Nmz2hTj7dq1Q0JCgk6DIyIiqklBaQVeXXcaADApzBNhvpztn7SjdQ/Q9evX4ejoeNf2wsJCrrlCRESNIuKf87iaUwx3W3O8OjxQ6nCoCdI6AeratSv+/vtvzfOqpOf777/XrOFFVFdlFWpEbDmPNceuSB0KETUR/8Zn4tfbbn1ZKnjri7Sn9afmgw8+wIgRI3Du3DlUVFRgyZIlOHfuHA4dOoR9+/bpI8YmKy49H+ev5aO3rx3XpKmBEAJv/XkGq49egbFcht5+9nBtZS51WERkwApKK/DK2spbX0/19EQvX3uJI6KmSuseoD59+iA6OhoVFRXo0KEDtm/fDkdHR0RGRiI0NFQfMTYpuUXl+DnqMsZ9eRBDPtuPF387ibBFu/HK2lM4n8ZFVm+34lASVt9cuLBCLbDiUJK0ARGRwVu0pfLWl1trc7w2gre+qP4Mbi0wQ6DtPEAVKjUOxGdi7fEU7DibjjKVGgBgJJfBvbU5krKKNPv29LHF1N7eGBzkBKMWPFX7/ovXMWX5EagFMKydE7adTYeVwhiHwgfCxsxE6vCIyAAdis/EE98fBgCseqYHevmx94eq0/laYHl5de+5aEkTB8Zn5GPN8RRsOHEVGfm3FlMNdLbGQ6FuGNepDeytTHH88g0s/zcJW89eQ9SlbERdyoZba3NMDvPCI93coTRvWb/wE64X4LlVJ6AWwMOhbvhwYgiGLd6PuIwC/H7kCqb385E6RCIyMIWlFXjl5qiv//T0YPJDDVanHiC5XF7nEV4qlarBQUntXhlkblE5Np1OxdrjKTh1JUezvbWFCcZ1aoOHQt3QztWmxuuVmlOMn6Mu47cjycgpKgcAWJgaYWIXN0zu5QU/Ryu9npchyC0qx/iv/0ViZiG6erbGr9N7QGFshD+OXsEr607DRWmG/a88ABMjre/OElEz9ubGM/g56jLatDLHtpf6wYqFz1QDbXqA6pQA3V7cnJSUhNdeew1TpkzRjPqKjIzEypUrERERgcmTJzcwfOndeQFVaoEDcdex9ngKtp9LR1nFrVtcDwQ44qFQNwwMdISpcd1+aReXqbAx+ipW/JuE2PR8zfZ+bR0wtbcX+vs7NMuVjCtUakxdcRQH4jLRppU5/ny+N+xvFoeXVqjQe9EeZBaUYvGjnTC+cxuJoyUiQ3EoIRNPfFd56+vXZ3qgN3t/qBY6T4BuN2jQIDzzzDN4/PHHq21ftWoVli1bhr1792odsKGpuoAn4lOw7WI+NpxMQXpezbe4HKzrP7pLCIHIhCz8+G8Sdl1IR9VXwsfeEpN7eeGhULdmNbzz7U1nseJQEixMjbB2Vi8Eu1b/cH65Ow7/234RwS42+PvFPpxXiohQWFqB4Uv240p2MZ7o4YEPJnSQOiQyYHpNgCwsLHDq1Cn4+/tX237x4kV06tQJRUVFtbyz6ai6gO5z/oBcYQGgbre4GuJyViF+iryMP45eQX5pBQDAWmGMR7q5Y3KYFzzsLHR6vMa26nAyXt8QAwD45j+hGN7e+a59bhSWodei3SguV/GvPCICACz48wxWRlbe+to6py+sOUiC7kGvi6G6u7vju+++u2v7999/D3d3d22bM2hGchkGBznhm/+E4vDrg/H22HZo30apl54JTztLvDk6GJGvD8I7Y9vB294S+aUV+OFgIvr/bw+m/3QM0bfVHDUlUZey8NafZwAA84a2rTH5AYDWlqZ4pKsbAGDZ/kuNFh8RGabIhCysjLwMoHLCQyY/pEta9wD9888/mDhxIvz8/NCjRw8AwJEjRxAXF4d169Zh5MiRegm0MVVlkAkpGfBp4yBJDGq1wL6461j+bxL2X7yu2f5YN3e8MjwQtpamksSlreSsIoz76iBuFJVjTEdXfP5Yp3smkJezCvHA//ZCLYBtc/ohwNm6EaMlIkNRVFaBYYsrb3093t0DEQ/y1hfdn157gEaOHIm4uDiMHTsW2dnZyM7OxpgxY3Dx4sVmkfzczr4B9T0NJb9ZYP3T092xc24/PNilsih49dErGPjJXqw6nAy12rCncMovKcczPx3FjaJyhLgp8fFDIfftPfO0s9T0EH13gL1ARC3VR1tjcSW7GK5KM7w+khMeku5xIsQaaDsRYmM5lpSNNzaewYVrlSPHOrop8d749ghxayVtYDVQqQVm/HQMuy5kwMlGgU3P94GTjVmd3nsy+QYmfH0IJkYyHHx1YJ3fR0TNQ9SlLDy2LAoA8NPT3dGvrTQ98dT06LUHqEpRUREuXLiA06dPV3uQ/nT1ssXmF/pgwZhgWCuMcSolF+O++hf/tyEGOUVlUodXzcfbYrHrQgYUxnIse6qrVklMZ4/W6ObVGuUqLo9B1NIUld1a6+vx7u5MfkhvtE6Arl+/jtGjR8Pa2hrt2rVD586dqz1Iv4yN5Jja2xu75vXHhM5tIATw6+FkDPxkH/44esUgboutP5GCb/YlAAA+eigEHd1bad3G9L6Vs0H/GnUZBTdHxRFR8/fR1lgkZxfdvPUVJHU41IxpnQDNmTMHOTk5OHz4MMzNzbF161asXLkS/v7+2LRpkz5ipBo4Wpvhs0c74fcZPdHWyQrZhWV4Zd1pPPTNIZy5mitZXCeSb+C1dZXD3Z9/wA/jOtVvQsPBQU7wtrdEXkkF/ri5YCoRNW+HL2Vpen0jOOqL9EzrBGj37t349NNP0bVrV8jlcnh6euI///kPPvroI0REROgjRrqHHj52+PvFvnhjVBAsTY1wIjkHY788iAV/nkFucXmjxpKaU4wZPx1HmUqNocFOmDukbb3bkstleKavNwDgh4OJqLi5wCwRNU/FZSrNWl+PdnVHf976Ij3TOgEqLCyEo6MjAKB169a4fr1yiHaHDh1w4sQJ3UZHdWJiJMczfX2we94AjOnoCrUAVkZexqBP9mLd8RQ0Rp17UVkFpv90DJkFpQh0tsZnj3Zq8HIeE7u4wdbSFFdzirHlzDUdRUpEhuijbRdwOasILkoz/N9o3voi/dM6AQoICEBsbCwAoGPHjvj2229x9epVfPPNN3BxcdF5gFR3TjZm+OLxzlj1TA/4Olgis6AML685hUe+jcSFa3l6O65aLTBvzSmcTc2DnaUpvp/cVSdLeJiZGGFSmCeAyokROWCRqHk6kph969bXgx1gw1tf1Ai0ToD++9//Ii0tDQCwYMECbNmyBR4eHvj888/xwQcf6DxA0l4vP3ts+W8/vDYiEOYmRjiadAOjPj+Id/86h/wS3d8W+3x3HP6JuQYTIxm+fSoUbq11t2zHUz09oTCWI+ZqLg4nZuusXSIyDCXlKryy9hSEAB7p6oYBAY5Sh0QtRIPnAaoaDu/h4QF7++axdpOhzgNUH6k5xXj/73P4J6byFpKDtQLPP+AHP0crONmYwclG0aBCw79Pp+G5VZW3Pj+aGIJHuul+OZT/2xCDXw8nY1CgI36Y0k3n7RORdCK2nMe3+y7ByUaB7S/1h9KcvT9Uf3pdDLUlaE4JUJX9F69jwaazSMwsvOs1S1Ojm8lQZUJ06/9mcFYq4GhtBkcbBRTGRtXed+ZqLh765hBKytV4po833hgdrJfYL10vwKBP90EIYOfcfvBz5PIYRM3BmauVc5mp1ALfTeqKIcFOUodETZw2v7/rVKgxd+7cOh/8008/rfO+1Hj6tXXA1jl9seLfJOyPu470vFKk55Ugv6QChWUqXMosxKUakqPb2Vqa3kqSrM2w7+J1lJSr0b+tA8L1OF+Hj4MVhgQ5Yfu5dHx/IBGLJobo7VhE1DgqVGq8uu40VGqBUR1cmPxQo6tTAnTy5Mlqz0+cOIGKigoEBAQAAC5evAgjIyOEhobqPkLSGYWxEWb298XM/r6abUVlFZpkqOpxLbcU6fklSM8tqfw3rxRlFWpkF5Yhu7AM59NutenrYIkvnugMowaO+LqfGf18sP1cOtafuIq5Q9vC0Vp/y2OcupKDRVsuoItnK0zt7Q17K+nWhCNqrr47kIizqXlQmpvg7bHtpA6HWqA6JUB79uzR/P/TTz+FtbU1Vq5cidatWwMAbty4galTp6Jv3776iZL0xsLUGN72xvC2t6x1HyEEcorKce1mgpSRV4preSXILynH5F5ejTJiI9SzNTp7tMLJ5Bz8HHkZLw8N0MtxjiRm4+kVR1FQWoHIS1n44WAiHuvmgRn9fODaylwvx7yfG4VlWHs8BQnXCxA+IghKC9ZIUNOWmFmIxTsvAgDeGBUEBwkXnqaWS+saoDZt2mD79u1o1656xn7mzBkMHToUqampOg1QCs2xBqg52BKThtm/nkArCxMcem0gLEwbPtT+dgfjMjH9p2MoLlehq2drlKvUOJVSOau2sVyGCZ3bYNYAX/g6WOn0uLU5dSUHP0ddxl+nUlFaUTkR5LyhbfH8QP9GOT6RPqjVAo9/F4XDidno62+Pn57uDplMvz3I1HLovAbozsarJj+83fXr15Gfn69tc0R1NrSdMzxsLZCcXYS1x1MwKcxLZ23vvpCOWb+cQFlFZU3Tt0+FQmEsx6GELHy1Jx6HErKw5ngK1p5Iwcj2Lpg9wBft2yh1dvwqJeUq/HUqFT9HXcbplFtLmthamiK7sAxRl7Lx/ECdH5ao0fx+7AoOJ2bD3MQIH0zowOSHJKN1AjRhwgRMnToVn3zyCbp37w4AOHz4MObPn48HH3xQ5wESVTG6uTzGW3+exfcHEvFkD0+d1B5tiUnDi6tPolwlMDTYCV880Vkz4q23nz16+9njZPINfL03ATvOpePvmDT8HZOG/m0d8NwDfujubdvgGC5nFeLXw8n449gV5BRVztVkaiTHqBAXPBXmCUtTYwxbvB/HLmejtEJ114g8oqYgPa8EH/xzHgDw8tC2cLfV3ZxhRNrSOgH65ptvMG/ePDzxxBMoL6/8QW1sbIxp06bh448/1nmARLd7KNQNn+64iOTsImw/ew0jOjRs9vGNJ6/i5TWnoFILjOnoik8f6QgTo7vnB+3s0RrfTeqK2Gv5WLo3HptOpWLfxevYd/E6unq2xnMP+GFAgINWf82q1AJ7YzPwU+Rl7Lt4q1e1TStz/KenJx7p6ga7mwXYQgjYWZoiq7AMp1Ny0c2r4UkXUWN7688zyC+pQEc3Jab29pY6HGrh6j0PUGFhIRISEgAAvr6+sLSsvYi2qWENkGH7ZHssvtgdj07urbDh2V717kL//WgyXlsfAyEqE6sPJ4bUuUcpOasI3+5PwJpjKSi7uVBrkIsNnh3gi5EdXO7ZTlZBKX4/dgW/RiXjak4xAEAmA/q3dcBTPT0xIMCxxvc/9+sJ/B2ThrlD2uLFQawDoqalqobPWC7DXy/0QZALf7aS7mnz+1vrpTCqWFpaIiQkBCEhIfVOfpYuXYqQkBDY2NjAxsYGYWFh2LJly137CSEwYsQIyGQybNy48Z5tCiHw1ltvwcXFBebm5hg8eDDi4uLqFR8ZpklhXjA1kiP6Sg6OX75RrzZW/JuIV9dVJj//6emBj7RIfgDAw84CCyd0wIFXH8CMfj6wMDXC+bQ8vPDbSQz+dB9+P5qMsopbK9gLIXD88g289Hs0wiJ246OtsbiaU4xWFiaY0c8He+cNwIqp3TEoyKnWOHr62gEAoi5l1euciaSSW1SOtzadBQDMHuDL5IcMQp1vgdW1vmf9+vV1PribmxsWLVoEf39/CCGwcuVKjBs3DidPnqw2ymzx4sV1/iv/o48+wueff46VK1fC29sbb775JoYNG4Zz587BzEx/c8dQ43GwVuDBLm2w+ugVLNt/CV21vB30zb4ELNpyAQDwTB9v/N+ooHr3IjnZmOH1kUF4doAvVhxKwopDSUjMLMSr62KweGccnunrA0tTI/wcdRlnU28tSNvRTYn/9PTEmI6uMDOpWz1PmE/leR6/fIN1QNSkLPznHK7nl8LHwRLPPeAndThEALRIgJRK3Y94GTNmTLXnCxcuxNKlSxEVFaVJgKKjo/HJJ5/g2LFj911tXgiBxYsX44033sC4ceMAAD/99BOcnJywceNGPPbYYzo/B5LGM329sfroFew4n45L1wvgU4eh6UIILN4ZhyW7KnsEXxjoh7lD2upkFEorC1PMGdwW0/v64LcjyVi2/xLSckvw3uZzmn0UxnKM6eiKp3p6oqN7K62P4etgBXsrBTILShGdnIMePnYNjptI3/6Nz8Qfx1IAAB9ODKlzwk+kb3VOgJYvX67POKBSqbBmzRoUFhYiLCwMQOVCq0888QS++uorODs737eNxMREXLt2DYMHD9ZsUyqV6NGjByIjI2tNgEpLS1FaWqp5npeXV+N+ZDj8HK0xKNARuy5k4IeDiVg4ocM99xdCYNHWC/h23yUAwPxhAXr5S9RSYYxn+vrgqTBPrDt+FSsOJUJ9c5Xrh0Pd0drStN5ty2Qy9PSxxebTaYi8lMUEiAxecZkK4etjAABP9fRk8T4ZlHrXAOlKTEwMrKysoFAoMGvWLGzYsAHBwZWLar700kvo1auXpjfnfq5dq1zx3Mmp+poyTk5OmtdqEhERAaVSqXm4u+t+RXPSven9fAAAa4+nIKugtNb91GqBtzed1SQ/b44O1ns3vMLYCE/08MD2l/pj59z+mNHPt0HJT5Wwm3VAkQmsAyLD99nOyhGbLkozvDJcP7O3E9WX5AlQQEAAoqOjcfjwYcyePRuTJ0/GuXPnsGnTJuzevRuLFy/Wewzh4eHIzc3VPK5cuaL3Y1LD9fC2RYibEqUVavwcdbnGfVRqgdc3xGBl5GXIZMAHEzpgWp+mO/y2581en5NXclBSrpI4GqLanU7JwfcHKv/oeH98e1g3wpI5RNqQPAEyNTWFn58fQkNDERERgY4dO2LJkiXYvXs3EhIS0KpVKxgbG8PYuPJu3cSJEzFgwIAa26q6TZaenl5te3p6+j1voSkUCs1ItKoHGT6ZTIbpfSt7gX6KvHxXQlChUuPlP6Kx+ugVyGXA/x7qiCd6eEgRqs742FvC0VqBsgo1TiTXbwQckb6Vq9R4dV0M1AIY09EVg4K40jsZHskToDup1WqUlpbitddew+nTpxEdHa15AMBnn31Waz2St7c3nJ2dsWvXLs22vLw8HD58WFNXRM3LiPbOaNPKHNmFZVh3IkWzvaxCjRd+O4mN0akwlsvwxeNdMDHUTcJIdaOyDqhqOHy2xNEQ1WzZ/ks4n5aHVhYmWDAmWOpwiGokaQIUHh6O/fv3IykpCTExMQgPD8fevXvx5JNPwtnZGe3bt6/2AAAPDw94e9+6hREYGIgNGzYAqPzlMGfOHLz//vvYtGkTYmJiMGnSJLi6umL8+PFSnCLpmbGRXHNL6/sDiVCrBUrKVZj1y3FsOXMNpkZyLP1PKEaFNGzGaENSVQcUxTogMkAJ1ws0Iy3fGh0Meyuu9E6GSbfLaWspIyMDkyZNQlpaGpRKJUJCQrBt2zYMGTKkzm3ExsYiN/fWopGvvPIKCgsLMWPGDOTk5KBPnz7YunUr5wBqxh7p5o7FOy8iMbMQf51OxZpjKTgYnwkzEzmWPdUV/do6SB2iTlX1AEVfyUFxmQrmphxWTIZBrRYIXxeDsgo1+rV1wITObaQOiahW9V4KoznjUhhNz4dbL2Dp3gTIZIAQgIWpEX6c0k2TLDQnQgiERezGtbwS/PpMD/T2s5c6JCIAwK+HL+P/NpyBhakRts3px8VOqdE1ylIYRIZkSi8vmBjJIARgbWaMn6f1aJbJD1B5qzeMy2KQgbmWW4JF/1TOsD5vaACTHzJ4TICoWXCyMcOLA/0R6GyN36b3RKhna6lD0queN5fF4HxAZAiEEHhj4xnkl1agk3srTO7lJXVIRPclaQ0QkS69MMgfL7SQVdLDfCpve51KyUFRWQUsTPmtTNL5OyYNO8+nw8RIho8e0m5hYSKpsAeIqAlytzWHq9IM5arKVeaJpJJTVIa3NSu9+6Gtk7XEERHVDRMgoiZIJpOhJ+uAyAC8//d5ZBaUwc/RCs894Ct1OER1xgSIqImqKvJmHRBJ5UDcdaw9ngKZrHKld4Uxp2SgpoMJEFETFXYzATqdkovC0gqJo6GaqNUCu86nI7+kXOpQdK6orAKvb6hc6X1ymFezH3hAzQ8TIKImyt3WAm1amaNCLXCMdUAGacWhJExbeQyfbL8odSg6983eBFzJLkabVuaYN4wrvVPTwwSIqAnjfECG7e+YNABodoXqqTnFWHZzpfc3RgXBSsFRiNT0MAEiasJYB2S4MgtKcSK5MvGJTc9HhUotcUS68/G2WJSUq9Hd2xbD2ztLHQ5RvTABImrCqiZEjLmaiwLWARmUPRcyULXQUFmFGklZhdIGpCOnruRgw8mrAIA3RwVDJuOcP9Q0MQEiasLcWlvA3dYcKrXA0aRsqcOh2+w8n17t+fm0fIki0R0hBN7bfA4A8GCXNujgppQ4IqL6YwJE1MRVjQaL4m0wg1FSrsL+i5kAgJCbScKFa3lShqQTW85cw7HLN2BmIsd8Fj5TE8cEiKiJYyG04Ym8lIXichWcbczwUKgbgKbfA1RaoULElvMAgJn9fOGiNJc4IqKGYQJE1MRVFULHXM1FXjOcb6Yp2nmu8vbXoCBHBLnYAAAupDXtHqAV/ybhSnYxHK0VmNnfR+pwiBqMCRBRE+eiNIeXnQXUAjjGOiDJCSGw63wGAGBwkBMCnCvXxkrNLUFuUdNMULMKSvHl7ngAwPxhAVx8l5oFJkBEzQCHwxuOs6l5uJZXAnMTI4T52sHGzARtWlXeLmqqdUCLd8Yhv7QC7dvYYGIXN6nDIdIJJkBEzcCtOiD2AEmtavRXX397mJlUro1VdRvsfBO8DRaXno9VR5IBAG+MCoZczmHv1DwwASJqBqp6gM6m5iK3uGneZmkuqhKgwcFOmm1BLpW3wS5ca3qF0Av/OQ+VWmBYOyfN54yoOWACRNQMONmYwcfeEmoBHE1kL5BU0nKLceZqHmQyYGCgo2Z7oPPNHqAmlgDtu3gde2Ovw8RIhtdGBEkdDpFOMQEiaiZ6VNUBcTi8ZKqKnzu7t4K9lUKzPfBmD9DFa/lQqYUksWmrQqXGwr8rJz2cFOYFb3tLiSMi0i0mQETNBOcDkl5Nt78AwMvOEmYmchSXq3C5iSyJ8fuxK7iYXoBWFiZ4caC/1OEQ6RwTIKJmoqd35bpg59LykFNUJnE0LU9haQUO3RyFNzioegJkJJchwKnp1AHllZTj0+0XAQBzBvlDaWEicUREuscEiKiZcLQxg6+DJYQAjrAOqNEdiMtEWYUaHrYW8He0uuv1qjqgpjAh4td7EpBVWAYfB0s82dNT6nCI9IIJEFEzUnUbjHVAjW/X+VuzP9e0QnpVHdA5A18S40p2EX48mAgA+L+RQTAx4q8Jap74ySZqRqqGKXM+oMalUgvsvlBZAD3kjttfVTRLYhj4ZIiLtl5AmUqN3n521UayETU3TICImpGqBOh8Wh5uFLIOqLFEX7mBrMIyWJsZo9vNWqw7Bd5cEiPlRrHBrtl2/HI2/j6dBpkM+L+RwTX2ZBE1F0yAiJoReyuFpv7kcCJvgzWWnTeHvw8IcKz1llErC1O4KM0AVA6HNzRqtcC7mytXe3+0qzuCXW0kjohIv5gAETUzXBaj8VWt/j446N63jKp6gQxxSYy/Tqfi1JUcWJgaYe7QtlKHQ6R3TICImhkujNq4LmcVIi6jAEZyGQa0vXcCpFkTzMB6gErKVfhwywUAwLMDfOFobSZxRET6xwSIqJnpcbMGJTY9H1kFpRJH0/xV3f7q7mV73/lyAl0Mcyj8DwcTkZpbAlelGZ7p6yN1OESNggkQUTNjZ6XQTLp3mPMB6d3tw9/vJ+jmLbDYa/lQG8iSGBn5Jfh6TzwA4NURgZoV7ImaOyZARM0Ql8VoHLnF5ZpJJ4cE1zz8/Xbe9pYwNZajsEyFKzeK9B1enXy6/SIKy1To5N4KYzu6Sh0OUaORNAFaunQpQkJCYGNjAxsbG4SFhWHLli2a12fOnAlfX1+Ym5vDwcEB48aNw4ULF+7Z5pQpUyCTyao9hg8fru9TITIoPX0qb4OxDki/9l28jgq1gL+jFTzt7r9YqLGRHG2dKkfpnTeACRHPpebh92NXAABvjg7isHdqUSRNgNzc3LBo0SIcP34cx44dw8CBAzFu3DicPXsWABAaGorly5fj/Pnz2LZtG4QQGDp0KFQq1T3bHT58ONLS0jSP3377rTFOh8hg9PC2g0wGxGUUIJN1QHpTNfprUC2TH9ZEsySGxBMiCiHw/t/nIAQwKsQFoZ41z19E1FwZS3nwMWPGVHu+cOFCLF26FFFRUWjXrh1mzJihec3Lywvvv/8+OnbsiKSkJPj6+tbarkKhgLOzs97iJjJ0rS1NEehsg/NpeYi6lIXRIby1oWvlKjX2xN6c/Tm47jMmG8pQ+N0XMnAoIQumxnK8NjxQ0liIpGAwNUAqlQqrV69GYWEhwsLC7nq9sLAQy5cvh7e3N9zd3e/Z1t69e+Ho6IiAgADMnj0bWVm8DUAtT9VtMNYB6cfRpGzkl1TA1tIUndxb1/l9t5bEkO4WWLlKjYX/VE56+HRvb7jbWkgWC5FUJE+AYmJiYGVlBYVCgVmzZmHDhg0IDg7WvP7111/DysoKVlZW2LJlC3bs2AFTU9Na2xs+fDh++ukn7Nq1Cx9++CH27duHESNG3PO2WWlpKfLy8qo9iJq6MM4HpFc7z1X2/gwMdISRvO61M1U9QJezilBYWqGX2O7n16jLuHS9EHaWpnjugdp704maM8kToICAAERHR+Pw4cOYPXs2Jk+ejHPnzmlef/LJJ3Hy5Ens27cPbdu2xSOPPIKSkpJa23vssccwduxYdOjQAePHj8fmzZtx9OhR7N27t9b3REREQKlUah7362Eiagqq6oASrhciI7/27xnSnhACuy7UbfbnO9lZKeBorQBQOVdTY8stKsfiXXEAgLlD28La7N5zFxE1V5InQKampvDz80NoaCgiIiLQsWNHLFmyRPO6UqmEv78/+vXrh7Vr1+LChQvYsGFDndv38fGBvb094uPja90nPDwcubm5mseVK1cadE5EhkBpYYLgm7dbuCyGbsVnFOByVhFMjeTo6++g9furJkSUog7o633xyCkqR1snKzzalX/sUcsleQJ0J7VajdLSmketCCEghKj19ZqkpKQgKysLLi4ute6jUCg0Q/GrHkTNQdWyGKwD0q2q2Z97+dnBUqH9WJIgl8rbYBcaeSi8EAKbT6UBAOYOaQvjWhZuJWoJJP30h4eHY//+/UhKSkJMTAzCw8Oxd+9ePPnkk7h06RIiIiJw/PhxJCcn49ChQ3j44Ydhbm6OkSNHatoIDAzU9AgVFBRg/vz5iIqKQlJSEnbt2oVx48bBz88Pw4YNk+o0iSRTVQcUxTogndp5Xvvh77cLkmgofHJ2Ea7mFMPESFavniui5kTSYfAZGRmYNGkS0tLSoFQqERISgm3btmHIkCFITU3FgQMHsHjxYty4cQNOTk7o168fDh06BEfHW/fcY2NjkZubCwAwMjLC6dOnsXLlSuTk5MDV1RVDhw7Fe++9B4VCIdVpEkmmm7ct5DLgUmYh0vNK4GTDRS4bKrOgFCeSbwDQvv6nSuBtPUBCiEabgPBgfCYAoLNH63r1XBE1J5J+B/zwww+1vubq6op//vnnvm0IcWs9HXNzc2zbtk0nsRE1B0pzE7RzVSLmai6iLmVhXKc2UofU5O25kAEhgHauNnBRmterDR97K5gYyZBfWoGUG8WNNgz935sJUB8/+0Y5HpEh4w1gomaOy2LoVtXtr8H1vP0FAKbGcvg53uwFaqT5gFRqgUM3PwO9mQARMQEiau64MKrulJSrcCCushelIQkQcGtl+AuNNBLsXGoecorKYaUwRkc3ZaMck8iQMQEiaua6eVXWASVlFSEtt1jqcJq0yEtZKCpTwclGgfZtGjZatKoO6HwjFUJX1f/09LHj6C8iMAEiavaszUzQoU3lX/zsBWqYXbfd/mpo4bJmUdRGGgp/q/7HrlGOR2TomAARtQA9fbksRkMJITTLXzT09hdwa02wxKxCFJfVvlSPLpSUq3AkqXIyTNb/EFViAkTUAtyaEJEzQtfX2dQ8XMsrgbmJkaauqiEcrBWwtzKFEMBFPS+JcfzyDZRVqOForYCfo5Vej0XUVDABImoBunnZwkgu00yER9qrGv3V198eZiZGOmmz6jaYvpfEuH34e2PNOURk6JgAEbUAVgrjW3VAvA1WL5rh78ENv/1VpWpleH0Pha9KgHj7i+gWJkBELUTVbZtIFkJrLS23GGeu5kEmAwYG1m/255oENcKiqLlF5Th9tXK2fCZARLcwASJqIbgwav3turn4aWf3VrC30t2yOpolMa7lV5vVXpciL2VCCMDP0QrOSi6FQlSFCRBRC9HVszWM5TKk3CjGlewiqcNpUnY1cPHT2vg5WsFILkNucTnSckt02naVg1z+gqhGTICIWghLhTFC3DgfkLYKSyvw7826qSE6rP8BAIWxEXwdLAHob2X4f+O5/AVRTZgAEbUgVXVAh1gIXWcH4jJRVqGGh60F/PUwhPxWHZDuC6FTbhQhMbMQRnIZetxcE46IKjEBImpB+retLODdfDoViZmFEkfTNNy6/eWolyHkmhmh9TAS7NDN3p+ObkrYmJnovH2ipowJEFEL0s2rNfq3dUC5SuDdv85KHY7BU6kFdl+oLIAeouP6nyqaNcH0MBKM9T9EtWMCRNSCyGQyLBgTDBMjGfbEXtf0blDNoq/kIKuwDNZmxujmrZ9bSEE3e4AuXS9ASbnulsRQqwXn/yG6ByZARC2Mj4MVnu7jDQB4d/M5lFbodx2qpqxq8sMBAY4w0dMK6k42CrS2MIFaAPEZBTprNzY9H1mFZTA3MUJnj9Y6a5eouWACRNQCvTDQH47WClzOKsL3BxKlDsdg3Vr9XXeTH95JJpNp6oDO6fA2WFXvTw8fW5ga80c90Z34XUHUAlkpjBE+MhAA8OXueKTlcn2wOyVnFeFiegGM5DIMaKu/BAi4bUJEHY4EY/0P0b0xASJqocZ3aoNQz9YoLlch4p8LUodjcKpuf3X3soXSQr8jqKqGwutqLqCyCjUOX8oGwPofotowASJqoWQyGd4Z2w4yGbDpVCoOc3LEanbeNvxd34JuWxVeF0tinEy+geJyFeytTBHgZN3g9oiaIyZARC1Y+zZKPN7dAwCwYNNZVKjUEkdkGHKLy3EksbIHRdezP9fE38kKchlwo6gcGfmlDW6vqv6nl6895HLdz11E1BwwASJq4eYNDYDS3AQXruXjtyPJUodTb8VlKqTcKMLlrEJczSlGRl4JsgvLkF9SjpJyFSpU6jr3ruy7eB0VagE/Ryt42lnqOXLAzMQI3vaVx9HFfECs/yG6P2OpAyAiadlamuLloW3x1p9n8b/tFzE6xBWtLU2lDgulFSpkF5Yhq6AMWYVlyCooRXZhGTILbvt/YRmyC0uRVVCGorK6Dec3MZLBWC6HsZEMJkZyGMtv/msk0/w/s6AMADBYT5Mf1iTIxQYJ1wtx4Vo+BgTU/7Zbfkk5TqXkAgB6+zMBIqoNEyAiwhPdPbDqcDIuXMvH/7bHYuGEDo127OSsIvxw8BJSc0tuJjyVCU1+aYXWbZneTGQqVALlajVq6vApVwmUq1RA+b3bksmAUR1ctI6hvoJcbLD5dBouNLAH6PClbKjUAl52FmjTylxH0RE1P0yAiAjGRnK8PbYdHlsWhVVHkvF4dw+0b6PU+3GTMgvxyLeRtda9GMtlsLU0ha2lKeytFLCzuvV/W0tT2Fmaws7KFHaWla9ZKYyrrdelUguUq9SoUAtUqNQoVwlUqNWVCdLN7eWqyucV6puv33zNwVrRKNegSqBz1ZIYDRsKf5CzPxPVCRMgIgIA9PSxw5iOrvjrVCre3nQWa2aF6WXxzyopN4rw5PeHkZFfirZOVpgU5gV7K1PY3kxm7C0VsDE3blAMRnIZjORGOoxafwJvDoVPuF6A0goVFMb1i/tf1v8Q1QkTICLSeH1kIHaeS8exyzfwZ3Qqxnduo5fjpOUW44nvDuNqTjF8HCzx6zM94WCt0MuxmgpXpRlszIyRV1KBhIxCBLvaaN1Gel4J4jIKIJMBYb52eoiSqPngKDAi0nBRmuP5gX4AgA/+OY+CetTh3E9Gfgme/O4wkrOL4GFrgVVMfgDcXBLD5dZ8QPVR1fvToY0SrSykL2QnMmRMgIiomml9vOFpZ4GM/FJ8uTtep21nFZTiye8O41JmIdq0Mseq6T3grDTT6TGasqCbdUD1nRGa9T9EdccEiIiqMTMxwpujggEAPxy8hEvXdbNCeU5RGZ764QjiMgrgZKPAquk94NbaQidtNxeBmiUxtC+EFkKw/odIC0yAiOgug4IcMSDAAeUqgfc2n2twe3kl5Zj84xGcS8uDvZUCq6b3bJQJBpuaIM0tMO0ToITrBUjPK4XCWI5Qz9a6Do2o2WECRER3kclkeGt0MEyMZNgTex27bq6LVR+FpRV4evlRnErJRWsLE/z6TA/4OljpMNrmo62TFWQyILOgFNe1XBLjYFxl7083L1uYmTSNkW9EUmICREQ18nGwwtN9vAEA724+h5Lyus20fLviMhWmrTyKY5dvwMbMGD9P64EAZy7OWRsLU2N43ewZ07YO6GB85WK2rP8hqhtJE6ClS5ciJCQENjY2sLGxQVhYGLZs2aJ5febMmfD19YW5uTkcHBwwbtw4XLhw4Z5tCiHw1ltvwcXFBebm5hg8eDDi4uL0fSpEzdILA/3haK3A5awi/HAwUav3lpSrMOPnY4i6lA0rhTF+mtajUScWbKqqJkS8oMVtsAqVGlGXKhMg1v8Q1Y2kCZCbmxsWLVqE48eP49ixYxg4cCDGjRuHs2fPAgBCQ0OxfPlynD9/Htu2bYMQAkOHDoVKVftfoh999BE+//xzfPPNNzh8+DAsLS0xbNgwlJSUNNZpETUbVgpjhI8MBAB8uTseabnFdXpfWYUaz686gQNxmTA3McLyqd3Qyb2VHiNtPjR1QFr0AJ1KyUVBaQVaWZjUa/4gopZI0gRozJgxGDlyJPz9/dG2bVssXLgQVlZWiIqKAgDMmDED/fr1g5eXF7p06YL3338fV65cQVJSUo3tCSGwePFivPHGGxg3bhxCQkLw008/ITU1FRs3bmy8EyNqRsZ3aoOunq1RXK5CxD/37oEFKnsj/rv6JHaez4DCWI4fJndFNy/bRoi0eajPkhhVo796+drBSK6/2buJmhODqQFSqVRYvXo1CgsLERYWdtfrhYWFWL58Oby9veHu7l5jG4mJibh27RoGDx6s2aZUKtGjRw9ERkbWeuzS0lLk5eVVexBRJZlMhrfHtoNMBmw6lYrDN2+11ESlFnh5zSlsOXMNpkZyfPtUKHrxloxWqnqA4jPyUa5S1+k9nP+HSHuSJ0AxMTGwsrKCQqHArFmzsGHDBgQHB2te//rrr2FlZQUrKyts2bIFO3bsgKlpzTOcXrt2DQDg5ORUbbuTk5PmtZpERERAqVRqHrUlWEQtVfs2Sjze3QMAsGDTWVTU8ItZrRZ4bd1p/BmdCmO5DF892QUDAhwbO9Qmr00rc1gpjFGuErh0vfC++xeWVuBk8g0ArP8h0obkCVBAQACio6Nx+PBhzJ49G5MnT8a5c7fmHXnyySdx8uRJ7Nu3D23btsUjjzyi83qe8PBw5Obmah5XrlzRaftEzcH8oQFQmpvgwrV8/HYkudprQgi8+ecZrDmeArkM+PzxzhgS7FRLS3Qvcrnstttg9++NPpKUjXKVgFtrc3jYcmJJorqSPAEyNTWFn58fQkNDERERgY4dO2LJkiWa15VKJfz9/dGvXz+sXbsWFy5cwIYNG2psy9nZGQCQnl59zpL09HTNazVRKBSakWhVDyKqrrWlKeYNbQsA+N/2i8guLANQmfy8t/k8fj2cDJkM+PSRThjZwUXKUJu8QJebCVAdCqEP3Tb7s0zG+h+iupI8AbqTWq1GaWnNE4AJISCEqPV1b29vODs7Y9euXZpteXl5OHz4cI11RUSknce7eyDQ2Rq5xeX4ZHsshBD4aFssfvy3coj8hw+G6G0F+ZYk0Pnmkhh1KITm/D9E9WMs5cHDw8MxYsQIeHh4ID8/H6tWrcLevXuxbds2XLp0Cb///juGDh0KBwcHpKSkYNGiRTA3N8fIkSM1bQQGBiIiIgITJkyATCbDnDlz8P7778Pf3x/e3t5488034erqivHjx0t3okTNhLGRHO+MbYdHl0Vh1ZFklFaosfZ4CgDgvfHt8Ug31s/pQpBmTbB79wBlFpRqbpP18rXTe1xEzYmkCVBGRgYmTZqEtLQ0KJVKhISEYNu2bRgyZAhSU1Nx4MABLF68GDdu3ICTkxP69euHQ4cOwdHxVmFlbGwscnNzNc9feeUVFBYWYsaMGcjJyUGfPn2wdetWmJlxxWkiXejhY4cxHV3x16lUTfLzxqggPNXTU+LImo+q2bLT80qRXVgGW8uaB34cSqjs/Ql2sYGdlaLR4iNqDmRCCCF1EIYmLy8PSqUSubm5rAciqkFabjEGfbIPRWUqvDI8AM8O8JM6pGan30d7kJxdhFXP9Kh1KoFX157G78euYHpfb/zfqOAa9yFqSbT5/S1pDxARNU0uSnNsfK43MvNLOc+PngQ6WyM5uwjnr+XXeI2FEJz/h6gBDK4ImoiahrZO1kx+9EhTB1TLUPjLWUW4mlMMEyMZuntzpm0ibTEBIiIyQEH3GQpf1fvTxaM1LEzZmU+kLSZAREQGqGoo/MX0ghpn3v73tvl/iEh7TICIiAyQh60FLEyNUFahRlJW9SUxVGqhGQHW258JEFF9MAEiIjJAcrlMMxz+zpXhz6bmIre4HNYKY4S0UUoRHlGTxwSIiMhAVd0Gu3NNsKr6n56+djA24o9xovrgdw4RkYGqKoS+cK16DxDrf4gajgkQEZGBurUm2K0eoJJyFY4m3QDA+X+IGoIJEBGRgapaFT41twQ5RWUAgGNJN1BWoYazjRl8HSylDI+oSWMCRERkoGzMTNCmlTmAW7fBbp/9WSaTSRYbUVPHBIiIyIBp6oBu3gbT1P/4c/V3ooZgAkREZMA0dUDX8pFTVIYzqbkAgN6+rP8haggmQEREBqxqTbDzaXmITMiCEEBbJys42phJHBlR08YEiIjIgFUVQsem52N/3HUAHP1FpAtMgIiIDJiXnSUUxnKUlKuxKToVAOf/IdIFJkBERAbM6LYlMQrLVDCSy9DDhwXQRA3FBIiIyMAF3SyEBoDO7q1gpTCWMBqi5oEJEBGRgauqAwJY/0OkK/wzogZCCABAXl7effYkItI/d0sZ1KVFAICOTqb82URUi6rvjarf4/ciE3XZq4VJSUmBu7u71GEQERFRPVy5cgVubm733IcJUA3UajVSU1NhbW3doKnm8/Ly4O7ujitXrsDGxub+b6AG4fVuXLzejYvXu3HxejcuXV1vIQTy8/Ph6uoKufzeVT68BVYDuVx+38xRGzY2NvwGakS83o2L17tx8Xo3Ll7vxqWL661UKuu0H4ugiYiIqMVhAkREREQtDhMgPVIoFFiwYAEUCoXUobQIvN6Ni9e7cfF6Ny5e78YlxfVmETQRERG1OOwBIiIiohaHCRARERG1OEyAiIiIqMVhAkREREQtDhOg+9i/fz/GjBkDV1dXyGQybNy4sdrr6enpmDJlClxdXWFhYYHhw4cjLi6u2j4JCQmYMGECHBwcYGNjg0ceeQTp6enV9vHy8oJMJqv2WLRokb5Pz+BERESgW7dusLa2hqOjI8aPH4/Y2Nhq+5SUlOC5556DnZ0drKysMHHixLuuZ3JyMkaNGgULCws4Ojpi/vz5qKioqLbP3r170aVLFygUCvj5+WHFihX6Pj2D01jXe+/evXd9vmUyGa5du9Yo52kIdHWtX3zxRYSGhkKhUKBTp041Huv06dPo27cvzMzM4O7ujo8++khfp2WwGut6JyUl1fjZjoqK0ufpGRxdXO9Tp07h8ccfh7u7O8zNzREUFIQlS5bcdSxd/exmAnQfhYWF6NixI7766qu7XhNCYPz48bh06RL+/PNPnDx5Ep6enhg8eDAKCws17x86dChkMhl2796Nf//9F2VlZRgzZgzUanW19t59912kpaVpHi+88EKjnKMh2bdvH5577jlERUVhx44dKC8vx9ChQzXXEwBeeukl/PXXX1izZg327duH1NRUPPjgg5rXVSoVRo0ahbKyMhw6dAgrV67EihUr8NZbb2n2SUxMxKhRo/DAAw8gOjoac+bMwTPPPINt27Y16vlKrbGud5XY2Nhqn3FHR8dGOU9DoItrXeXpp5/Go48+WuNx8vLyMHToUHh6euL48eP4+OOP8fbbb2PZsmV6OzdD1FjXu8rOnTurfbZDQ0N1fk6GTBfX+/jx43B0dMQvv/yCs2fP4v/+7/8QHh6OL7/8UrOPTn92C6ozAGLDhg2a57GxsQKAOHPmjGabSqUSDg4O4rvvvhNCCLFt2zYhl8tFbm6uZp+cnBwhk8nEjh07NNs8PT3FZ599pvdzaGoyMjIEALFv3z4hROW1MzExEWvWrNHsc/78eQFAREZGCiGE+Oeff4RcLhfXrl3T7LN06VJhY2MjSktLhRBCvPLKK6Jdu3bVjvXoo4+KYcOG6fuUDJq+rveePXsEAHHjxo3GOxkDV59rfbsFCxaIjh073rX966+/Fq1bt9ZceyGEePXVV0VAQIDuT6IJ0df1TkxMFADEyZMn9RV6k9TQ613l2WefFQ888IDmuS5/drMHqAFKS0sBAGZmZpptcrkcCoUCBw8e1Owjk8mqTe5kZmYGuVyu2afKokWLYGdnh86dO+Pjjz++65ZNS5SbmwsAsLW1BVD5F0J5eTkGDx6s2ScwMBAeHh6IjIwEAERGRqJDhw5wcnLS7DNs2DDk5eXh7Nmzmn1ub6Nqn6o2Wip9Xe8qnTp1gouLC4YMGYJ///1X36dj0OpzresiMjIS/fr1g6mpqWbbsGHDEBsbixs3bugo+qZHX9e7ytixY+Ho6Ig+ffpg06ZNugm6CdPV9c7NzdW0Aej2ZzcToAao+uKFh4fjxo0bKCsrw4cffoiUlBSkpaUBAHr27AlLS0u8+uqrKCoqQmFhIebNmweVSqXZB6i8z7x69Wrs2bMHM2fOxAcffIBXXnlFqlMzCGq1GnPmzEHv3r3Rvn17AMC1a9dgamqKVq1aVdvXyclJU09y7dq1ar+Mq16veu1e++Tl5aG4uFgfp2Pw9Hm9XVxc8M0332DdunVYt24d3N3dMWDAAJw4cULPZ2WY6nut66IuX4+WRp/X28rKCp988gnWrFmDv//+G3369MH48eNbdBKkq+t96NAh/P7775gxY4Zmmy5/dnM1+AYwMTHB+vXrMW3aNNja2sLIyAiDBw/GiBEjIG5OsO3g4IA1a9Zg9uzZ+PzzzyGXy/H444+jS5cukMtv5Z9z587V/D8kJASmpqaYOXMmIiIiWuxU7M899xzOnDlzV08Z6Yc+r3dAQAACAgI0z3v16oWEhAR89tln+Pnnn3V+PEPHz3bj0uf1tre3r/bzu1u3bkhNTcXHH3+MsWPH6vx4TYEurveZM2cwbtw4LFiwAEOHDtVhdLewB6iBQkNDER0djZycHKSlpWHr1q3IysqCj4+PZp+hQ4ciISEBGRkZyMzMxM8//4yrV69W2+dOPXr0QEVFBZKSkhrhLAzP888/j82bN2PPnj1wc3PTbHd2dkZZWRlycnKq7Z+eng5nZ2fNPneO5Kh6fr99bGxsYG5uruvTMXj6vt416d69O+Lj43V0Bk1HQ651XdT369Fc6ft616RHjx4t8rMN6OZ6nzt3DoMGDcKMGTPwxhtvVHtNlz+7mQDpiFKphIODA+Li4nDs2DGMGzfurn3s7e3RqlUr7N69GxkZGff86yA6OhpyubxFjZIBKkfWPf/889iwYQN2794Nb2/vaq+HhobCxMQEu3bt0myLjY1FcnIywsLCAABhYWGIiYlBRkaGZp8dO3bAxsYGwcHBmn1ub6Nqn6o2WorGut41iY6OhouLi47PyHDp4lrXRVhYGPbv34/y8nLNth07diAgIACtW7du+Ik0EY11vWvS0j7bgO6u99mzZ/HAAw9g8uTJWLhw4V3H0enPbq3LpluY/Px8cfLkSXHy5EkBQHz66afi5MmT4vLly0IIIf744w+xZ88ekZCQIDZu3Cg8PT3Fgw8+WK2NH3/8UURGRor4+Hjx888/C1tbWzF37lzN64cOHRKfffaZiI6OFgkJCeKXX34RDg4OYtKkSY16roZg9uzZQqlUir1794q0tDTNo6ioSLPPrFmzhIeHh9i9e7c4duyYCAsLE2FhYZrXKyoqRPv27cXQoUNFdHS02Lp1q3BwcBDh4eGafS5duiQsLCzE/Pnzxfnz58VXX30ljIyMxNatWxv1fKXWWNf7s88+Exs3bhRxcXEiJiZG/Pe//xVyuVzs3LmzUc9XSrq41kIIERcXJ06ePClmzpwp2rZtq/n5VDXqKycnRzg5OYmnnnpKnDlzRqxevVpYWFiIb7/9tlHPV2qNdb1XrFghVq1aJc6fPy/Onz8vFi5cKORyufjxxx8b9XylpovrHRMTIxwcHMR//vOfam1kZGRo9tHlz24mQPdRNXz3zsfkyZOFEEIsWbJEuLm5CRMTE+Hh4SHeeOONasNPhagcgurk5CRMTEyEv7+/+OSTT4Rarda8fvz4cdGjRw+hVCqFmZmZCAoKEh988IEoKSlpzFM1CDVdawBi+fLlmn2Ki4vFs88+K1q3bi0sLCzEhAkTRFpaWrV2kpKSxIgRI4S5ubmwt7cXL7/8sigvL6+2z549e0SnTp2Eqamp8PHxqXaMlqKxrveHH34ofH19hZmZmbC1tRUDBgwQu3fvbqzTNAi6utb9+/evsZ3ExETNPqdOnRJ9+vQRCoVCtGnTRixatKiRztJwNNb1XrFihQgKChIWFhbCxsZGdO/evdpQ75ZCF9d7wYIFNbbh6elZ7Vi6+tktuxk4ERERUYvBGiAiIiJqcZgAERERUYvDBIiIiIhaHCZARERE1OIwASIiIqIWhwkQERERtThMgIiIiKjFYQJERERELQ4TICIiImpxmAARERFRi8MEiIiIiFocJkBERETU4vw/wb5WqpSAd1UAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Análise de horas contratadas\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = horasusar.loc[:, ['ano', 'tempo_emprego', 'quantidade_horas_contratadas', 'valor_remuneracao_media_sm', 'idade']].groupby('ano')\n",
        "avgs = groupbyyear.mean()\n",
        "x2 = avgs.index\n",
        "y2 = avgs.quantidade_horas_contratadas\n",
        "a2 = np.asarray(y2)\n",
        "plot(x2, a2, ax, 'Mudanças na quantidade de horas contratadas', 'Horas contratadas (semanais)')\n",
        "pd.DataFrame(a2, index = x2).to_csv('horas.csv', sep = ';', header  = ['quantidade_horas_contratadas'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "UQ5pliyigUgr",
        "outputId": "768720ef-616a-4829-8dca-a636b1f18b4e"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Análise de remuneração\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = remuneracao.loc[:, ['ano', 'tempo_emprego', 'quantidade_horas_contratadas', 'valor_remuneracao_media_sm', 'idade']].groupby('ano')\n",
        "avgs = groupbyyear.mean()\n",
        "x3 = avgs.index\n",
        "y3 = avgs.valor_remuneracao_media_sm\n",
        "a3 = np.asarray(y3)\n",
        "plot(x3, a3, ax, 'Mudanças na remuneração', 'Remuneração mensal média (em nº de salários mínimos)')\n",
        "pd.DataFrame(a3, index  = x3).to_csv('salário.csv', sep = ';', header  = ['remuneracao'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "ozwq_yNrSb0D",
        "outputId": "e09128cd-7c7e-4a66-ffdf-74e0f80a665b"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Análise do número de profissionais\n",
        "\n",
        "profissionais = results.dropna(subset=['ano'])\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = profissionais.loc[:, ['ano']].groupby('ano')\n",
        "counts1 = groupbyyear.ano.value_counts()\n",
        "a4 = np.asarray(counts1)\n",
        "plot(x3, a4, ax, 'Mudanças na quantidade de profissionais', 'Número de profissionais')\n",
        "pd.DataFrame(a4).to_csv('profissionais.csv', sep = ';', header = ['total'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "SFUWP3qaUsLd",
        "outputId": "9a982176-e116-4292-aeb0-9549a06b193a"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Running this code will display the query used to generate your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_62de1648_18a6d9d843d') # Job ID inserted based on the query results selected to explore\n",
        "print(job.query)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r0DsZ9DoU73m",
        "outputId": "249d7f83-848e-4847-ce2a-70c9aaeb81f5"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SELECT ano, tipo_vinculo FROM `blotta._d731c8db3b43ddb417ba10d6e72a9c633c4d7cfd.anon86d4c960bfeaa1af3f114c70fe6c962edfa8e7593ff67477392ac48fa598f5c2` WHERE tipo_vinculo='95' OR tipo_vinculo='90' OR tipo_vinculo='50' OR tipo_vinculo='40' OR tipo_vinculo='5' OR tipo_vinculo='4' OR tipo_vinculo='3'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Running this code will read results from your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_62de1648_18a6d9d843d') # Job ID inserted based on the query results selected to explore\n",
        "results1 = job.to_dataframe()\n",
        "results1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "P9Pp25lRZ1MB",
        "outputId": "4477e908-8112-4aa6-9949-e20b91cdfc7c"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Warning: total number of rows (44260) exceeds max_rows (20000). Falling back to pandas display.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        ano tipo_vinculo\n",
              "0      1991            4\n",
              "1      1993            5\n",
              "2      1993            5\n",
              "3      2003           95\n",
              "4      1992            5\n",
              "...     ...          ...\n",
              "44255  2020           50\n",
              "44256  2020           90\n",
              "44257  2020           50\n",
              "44258  2020           90\n",
              "44259  2020           90\n",
              "\n",
              "[44260 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-007126cb-866b-4731-a820-56f874d5b91e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "      <th>tipo_vinculo</th>\n",
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              "  </thead>\n",
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              "      <td>4</td>\n",
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              "      <th>1</th>\n",
              "      <td>1993</td>\n",
              "      <td>5</td>\n",
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              "      <th>2</th>\n",
              "      <td>1993</td>\n",
              "      <td>5</td>\n",
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              "      <td>2003</td>\n",
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              "      <td>1992</td>\n",
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              "      <th>44255</th>\n",
              "      <td>2020</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44256</th>\n",
              "      <td>2020</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44257</th>\n",
              "      <td>2020</td>\n",
              "      <td>50</td>\n",
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              "    <tr>\n",
              "      <th>44258</th>\n",
              "      <td>2020</td>\n",
              "      <td>90</td>\n",
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              "    <tr>\n",
              "      <th>44259</th>\n",
              "      <td>2020</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>44260 rows × 2 columns</p>\n",
              "</div>\n",
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              "\n",
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              "        document.querySelector('#df-007126cb-866b-4731-a820-56f874d5b91e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-007126cb-866b-4731-a820-56f874d5b91e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-42e7a87e-4a07-42fd-9dc4-dcab9d26df82 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Análise do número de vínculos precários\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = results1.loc[:, ['ano', 'tipo_vinculo']].groupby('ano')\n",
        "counts2 = groupbyyear.ano.value_counts()\n",
        "a5 = np.asarray(counts2)\n",
        "plot(x3, a5, ax, 'Mudanças no número de vínculos precários', 'Número de vínculos precários')\n",
        "pd.DataFrame(a5).to_csv('precários.csv', sep = ';', header = ['total'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "N2xHav4je3Dk",
        "outputId": "3a122c18-86f7-47df-c80f-622d04bba1b4"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Análise da prevalência de vínculos precários\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "a6 = a5/a4\n",
        "plot(x3, a6, ax, 'Prevalência dos vínculos precários', 'Fração de vínculos precários')\n",
        "pd.DataFrame(a6).to_csv('precários_prevalencia.csv', sep = ';', header = ['fracao'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "TYs844EYi3MD",
        "outputId": "ac0726e1-22b8-410f-b3db-c13c6930a34c"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Running this code will display the query used to generate your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_5527a83b_18a6d9e3124') # Job ID inserted based on the query results selected to explore\n",
        "print(job.query)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7nR5VcENjtDM",
        "outputId": "fafc89aa-e214-4aab-a5ba-ea775be0a3dc"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SELECT ano FROM `blotta._d731c8db3b43ddb417ba10d6e72a9c633c4d7cfd.anon86d4c960bfeaa1af3f114c70fe6c962edfa8e7593ff67477392ac48fa598f5c2` WHERE cbo_2002='261110'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Running this code will read results from your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_5527a83b_18a6d9e3124') # Job ID inserted based on the query results selected to explore\n",
        "results2 = job.to_dataframe()\n",
        "results2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "5by9qq94kek_",
        "outputId": "c37c918a-70eb-4907-ae55-10570bde6cfe"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Warning: total number of rows (213593) exceeds max_rows (20000). Falling back to pandas display.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         ano\n",
              "0       2004\n",
              "1       2004\n",
              "2       2005\n",
              "3       2006\n",
              "4       2008\n",
              "...      ...\n",
              "213588  2020\n",
              "213589  2020\n",
              "213590  2020\n",
              "213591  2020\n",
              "213592  2020\n",
              "\n",
              "[213593 rows x 1 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-26573ba0-4a5d-49eb-9114-7266e8f03cd4\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ano</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2004</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2004</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2005</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213588</th>\n",
              "      <td>2020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213589</th>\n",
              "      <td>2020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213590</th>\n",
              "      <td>2020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213591</th>\n",
              "      <td>2020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213592</th>\n",
              "      <td>2020</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>213593 rows × 1 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-26573ba0-4a5d-49eb-9114-7266e8f03cd4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-26573ba0-4a5d-49eb-9114-7266e8f03cd4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-26573ba0-4a5d-49eb-9114-7266e8f03cd4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-0db4318f-5696-465e-b1ca-964daef31d18\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0db4318f-5696-465e-b1ca-964daef31d18')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0db4318f-5696-465e-b1ca-964daef31d18 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Análise do número de assessores de imprensa\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "groupbyyear = results2.loc[:, ['ano']].groupby('ano')\n",
        "avgs = groupbyyear.mean()\n",
        "x_2 = avgs.index\n",
        "counts3 = groupbyyear.ano.value_counts()\n",
        "a7 = np.asarray(counts3)\n",
        "plot(x_2, a7, ax, 'Mudanças no número de assessores de imprensa', 'Número de assessores')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "83TddQ-ikoy4",
        "outputId": "1b32a519-6cb0-4c91-8db1-b751937a03c2"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#criação da medida de prevalência de assessores\n",
        "\n",
        "a4 = pd.DataFrame(a4, columns = ['total'])\n",
        "a4['ano'] = range(1985, 2022)\n",
        "a4_assessores = a4.loc[(a4['ano'] > 2002)]\n",
        "a8 = a7/a4_assessores['total']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qvFZERepnukh",
        "outputId": "f35b10b9-99f7-4290-afc3-be7b360c75bd"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "18    0.107289\n",
            "19    0.150762\n",
            "20    0.190712\n",
            "21    0.191940\n",
            "22    0.194357\n",
            "23    0.183266\n",
            "24    0.174710\n",
            "25    0.248236\n",
            "26    0.204634\n",
            "27    0.185922\n",
            "28    0.217598\n",
            "29    0.221395\n",
            "30    0.223048\n",
            "31    0.238703\n",
            "32    0.249865\n",
            "33    0.253620\n",
            "34    0.266017\n",
            "35    0.270015\n",
            "36    0.262551\n",
            "Name: total, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plotagem da prevalência\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "plot(x_2, a8, ax, 'Mudanças na proporção de assessores de imprensa', 'Proporção de assessores')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "GwS5d_nYpV_k",
        "outputId": "5381db7f-5d27-4431-815e-5ebbaabe10cf"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#produção do .csv da prevalência\n",
        "\n",
        "assessores = pd.DataFrame(a7, columns = ['total'])\n",
        "a8 = pd.DataFrame(a8, columns = ['total'])\n",
        "a8 = a8.reset_index()\n",
        "assessores['prevalencia'] = a8['total']\n",
        "print(assessores)\n",
        "pd.DataFrame(assessores).to_csv('assessores.csv', sep = ';')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_lxbuXh9qFiR",
        "outputId": "4ed7a625-1f7f-40c3-843f-4e0d91d53ca6"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    total  prevalencia\n",
            "0    3138     0.107289\n",
            "1    5144     0.150762\n",
            "2    7708     0.190712\n",
            "3    8502     0.191940\n",
            "4    9554     0.194357\n",
            "5    9714     0.183266\n",
            "6    9040     0.174710\n",
            "7   15265     0.248236\n",
            "8   12753     0.204634\n",
            "9   11775     0.185922\n",
            "10  14084     0.217598\n",
            "11  14117     0.221395\n",
            "12  13440     0.223048\n",
            "13  13455     0.238703\n",
            "14  13426     0.249865\n",
            "15  12980     0.253620\n",
            "16  13569     0.266017\n",
            "17  13059     0.270015\n",
            "18  12870     0.262551\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "cell_execution_strategy": "setup",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}