bias_mitigation.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "N4plGv2i1iua",
        "outputId": "0922c9a8-e634-4f98-9cf3-6fda03458198"
      },
      "outputs": [],
      "source": [
        "%load_ext autoreload\n",
        "%autoreload 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "knxx2sQd1iub"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From d:\\Anaconda\\Lib\\site-packages\\keras\\src\\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.\n",
            "\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:root:No module named 'fairlearn': ExponentiatedGradientReduction will be unavailable. To install, run:\n",
            "pip install 'aif360[Reductions]'\n",
            "WARNING:root:No module named 'fairlearn': GridSearchReduction will be unavailable. To install, run:\n",
            "pip install 'aif360[Reductions]'\n",
            "WARNING:root:No module named 'inFairness': SenSeI and SenSR will be unavailable. To install, run:\n",
            "pip install 'aif360[inFairness]'\n",
            "WARNING:root:No module named 'fairlearn': GridSearchReduction will be unavailable. To install, run:\n",
            "pip install 'aif360[Reductions]'\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import json\n",
        "import utils.functions as f"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "import warnings\n",
        "warnings.simplefilter(action='ignore', category=FutureWarning)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6cVx1b__nEM1"
      },
      "source": [
        "# Direct Dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "sQxoNvJN1iub"
      },
      "outputs": [],
      "source": [
        "dataset = \"direct_matching_20240213\"\n",
        "df_processed = pd.read_csv(f\"Data/{dataset}_processed.csv\", sep=\";\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-EX7CrTvs-bD"
      },
      "source": [
        "## Gender"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "DRmbew3Y3AFe",
        "outputId": "063eed92-54f6-499b-cf5f-56f8eb49533b"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
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              "    .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>cand_gender</th>\n",
              "      <th>cand_age_bucket</th>\n",
              "      <th>cand_domicile_province</th>\n",
              "      <th>cand_domicile_region</th>\n",
              "      <th>job_contract_type</th>\n",
              "      <th>job_work_province</th>\n",
              "      <th>Svedese</th>\n",
              "      <th>Spagnolo</th>\n",
              "      <th>Finlandese</th>\n",
              "      <th>Ebraico</th>\n",
              "      <th>...</th>\n",
              "      <th>Cinese</th>\n",
              "      <th>Arabo</th>\n",
              "      <th>Serbo</th>\n",
              "      <th>Albanese</th>\n",
              "      <th>Croato</th>\n",
              "      <th>Ceco</th>\n",
              "      <th>Danese</th>\n",
              "      <th>Rumeno</th>\n",
              "      <th>Macedone</th>\n",
              "      <th>Tedesco</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.08</td>\n",
              "      <td>1.69</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.00</td>\n",
              "      <td>7.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.80</td>\n",
              "      <td>13.69</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.82</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.36</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.50</td>\n",
              "      <td>16.75</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.25</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>62.76</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>61.48</td>\n",
              "      <td>26.67</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.41</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.74</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>37.74</td>\n",
              "      <td>44.57</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.61</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.35</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>49.52</td>\n",
              "      <td>9.47</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.41</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>39.26</td>\n",
              "      <td>10.74</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.48</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 22 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   cand_gender  cand_age_bucket  cand_domicile_province  cand_domicile_region  \\\n",
              "0          0.0              0.0                   11.08                  1.69   \n",
              "1          0.0              0.0                   20.00                  7.00   \n",
              "2          0.0              0.0                   45.80                 13.69   \n",
              "3          0.0              0.0                   21.50                 16.75   \n",
              "4          0.0              0.0                   62.76                  0.00   \n",
              "5          0.0              0.0                   20.09                  0.00   \n",
              "6          0.0              0.0                   61.48                 26.67   \n",
              "7          0.0              0.0                   37.74                 44.57   \n",
              "8          0.0              0.0                   49.52                  9.47   \n",
              "9          0.0              0.0                   39.26                 10.74   \n",
              "\n",
              "   job_contract_type  job_work_province  Svedese  Spagnolo  Finlandese  \\\n",
              "0                0.0               3.85     0.00       0.0        0.00   \n",
              "1                0.0               0.00     0.00       0.0        0.00   \n",
              "2                0.0               1.82     0.00       0.0        0.00   \n",
              "3                0.0               6.25     0.75       0.0        0.00   \n",
              "4                0.0               0.00     0.26       0.0        0.00   \n",
              "5                0.0               0.00     0.00       0.0        0.00   \n",
              "6                0.0               7.41     0.00       0.0        0.00   \n",
              "7                0.0              10.61     0.00       0.0        0.07   \n",
              "8                0.0              28.41     0.16       0.0        0.08   \n",
              "9                0.0               0.00     0.00       0.0        0.00   \n",
              "\n",
              "   Ebraico  ...  Cinese  Arabo  Serbo  Albanese  Croato  Ceco  Danese  Rumeno  \\\n",
              "0      0.0  ...    0.00   0.92    0.0      0.00    0.15  0.00    0.00     0.0   \n",
              "1      0.0  ...    0.00   0.00    0.0      0.00    2.00  0.00    0.00     0.0   \n",
              "2      0.0  ...    0.18   0.36    0.0      0.18    0.00  0.00    0.00     0.0   \n",
              "3      0.0  ...    0.50   0.25    0.0      0.00    0.00  0.00    0.25     0.0   \n",
              "4      0.0  ...    0.00   0.00    0.0      0.26    0.00  0.00    0.00     0.0   \n",
              "5      0.0  ...    0.00   0.00    0.0      0.32    0.00  0.00    0.00     0.0   \n",
              "6      0.0  ...    0.00   0.37    0.0      0.74    0.00  0.00    0.00     0.0   \n",
              "7      0.0  ...    0.00   0.35    0.0      0.00    0.00  0.04    0.00     0.0   \n",
              "8      0.0  ...    0.00   0.00    0.0      0.32    0.00  0.00    0.00     0.0   \n",
              "9      0.0  ...    0.00   0.37    0.0      0.00    1.48  0.00    0.00     0.0   \n",
              "\n",
              "   Macedone  Tedesco  \n",
              "0      0.15     0.00  \n",
              "1      0.00     0.00  \n",
              "2      0.00     0.00  \n",
              "3      0.00     0.00  \n",
              "4      0.13     0.00  \n",
              "5      0.00     0.00  \n",
              "6      0.00     0.00  \n",
              "7      0.07     0.00  \n",
              "8      0.00     0.00  \n",
              "9      0.00     1.11  \n",
              "\n",
              "[10 rows x 22 columns]"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "sectors = sorted(df_processed.job_sector.unique())\n",
        "protected_attribute_gender = \"cand_gender\"\n",
        "\n",
        "df_mitigation = df_processed.drop(columns=[\"distance_km\", \"match_score\", \"match_rank\", \"cand_id\", \"cand_education\", \"job_professional_category\"]).copy()\n",
        "columns = df_mitigation.columns\n",
        "columns = columns.drop([\"job_id\",\"job_sector\"])\n",
        "\n",
        "first_language_index = 6\n",
        "\n",
        "results_df_gender = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_gender,columns)\n",
        "results_df_gender.to_excel('Results/Mitigation_direct/results_df_gender_direct.xlsx', index=False)\n",
        "results_df_gender"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "data": {
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mjwkQERERmRzOA0REREQmhwkQERERmRx2gs5GRkYGrl+/DkdHxxeuzUNEREQ5i4jg4cOH8PT0hJnZy9t4mABl4/r161lWxCYiIqLc4cqVKyhYsOBL92EClI3MBR6vXLkCJycnI9eGiIiIXkViYiK8vb31Fmp+ESZA2ci87eXk5MQEiIiIKJd5le4r7ARNREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkciyMXQEiokxFvlmv2bFjxzXV7NhElPuwBYiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUyAiIiIyOQwASIiIiKTwwSIiIiITA4TICIiIjI5TICIiIjI5Bg1AQoPD0fVqlXh6OiIAgUKIDg4GOfOndPb58mTJ+jduzfy5csHBwcHfPTRR7h58+ZLjysiGD58ODw8PGBra4uAgABER0dreSpERESUixg1Adq1axd69+6NyMhIbNmyBU+fPkWjRo2QnJys7NO/f3/8+eefWLFiBXbt2oXr16+jVatWLz3ujz/+iKlTp2LWrFk4ePAg7O3tERgYiCdPnmh9SkRERJQL6EREjF2JTLdv30aBAgWwa9cu1K1bFwkJCXB1dcXSpUvRunVrAMDZs2dRsmRJHDhwADVq1MhyDBGBp6cnBg4ciEGDBgEAEhIS4ObmhoiICLRv3/4/65GYmAhnZ2ckJCTAyclJ3ZMkohfiavBE9DZe5/93juoDlJCQAADImzcvAODo0aN4+vQpAgIClH1KlCiBQoUK4cCBA9ke49KlS4iPj9d7jbOzM6pXr/7C1xAREZFpsTB2BTJlZGTgyy+/RK1atVCmTBkAQHx8PKysrODi4qK3r5ubG+Lj47M9Tma5m5vbK78mJSUFKSkpyvPExMQ3PQ0iIiLKBXJMC1Dv3r1x6tQpLFu2zOCxw8PD4ezsrDy8vb0NXgciIiIynByRAIWGhuKvv/7Cjh07ULBgQaXc3d0dqampePDggd7+N2/ehLu7e7bHyiz/90ixl71myJAhSEhIUB5Xrlx5i7MhIiKinM6oCZCIIDQ0FH/88Qe2b9+OokWL6m2vXLkyLC0tsW3bNqXs3LlziIuLQ82aNbM9ZtGiReHu7q73msTERBw8ePCFr7G2toaTk5Peg4iIiN5dRk2AevfujSVLlmDp0qVwdHREfHw84uPj8fjxYwDPOi93794dAwYMwI4dO3D06FF069YNNWvW1BsBVqJECfzxxx8AAJ1Ohy+//BJjxozBunXr8Pfff6NLly7w9PREcHCwMU6TiIiIchijdoKeOXMmAKB+/fp65QsWLEDXrl0BAJMmTYKZmRk++ugjpKSkIDAwED///LPe/ufOnVNGkAHA119/jeTkZHz22Wd48OABateujY0bN8LGxkbT8yEiIqLcIUfNA5RTcB4gIuPgPEBE9DZy7TxARERERIbABIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUyAiIiIyOQwASIiIiKTwwSIiIiITA4TICIiIjI5TICIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUyAiIiIyOQwASIiIiKTwwSIiIiITA4TICIiIjI5TICIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUZNgHbv3o1mzZrB09MTOp0Oa9as0duu0+myfYwfP/6Fxxw5cmSW/UuUKKHxmRAREVFuYtQEKDk5GeXLl8eMGTOy3X7jxg29x/z586HT6fDRRx+99LilS5fWe93evXu1qD4RERHlUhbGDB4UFISgoKAXbnd3d9d7vnbtWjRo0AA+Pj4vPa6FhUWW1xIRERFlyjV9gG7evIn169eje/fu/7lvdHQ0PD094ePjg44dOyIuLs4ANSQiIqLcwqgtQK9j4cKFcHR0RKtWrV66X/Xq1REREYHixYvjxo0bCAsLQ506dXDq1Ck4Ojpm+5qUlBSkpKQozxMTE1WtOxEREeUsuSYBmj9/Pjp27AgbG5uX7vf8LbVy5cqhevXqKFy4MJYvX/7C1qPw8HCEhYWpWl8iIiLKuXLFLbA9e/bg3Llz+PTTT1/7tS4uLihWrBhiYmJeuM+QIUOQkJCgPK5cufI21SUiIqIcLlckQPPmzUPlypVRvnz5135tUlISLly4AA8PjxfuY21tDScnJ70HERERvbuMmgAlJSXh+PHjOH78OADg0qVLOH78uF6n5cTERKxYseKFrT8NGzbE9OnTleeDBg3Crl27EBsbi/3796Nly5YwNzdHhw4dND0XIiIiyj2M2gfoyJEjaNCggfJ8wIABAICQkBBEREQAAJYtWwYReWECc+HCBdy5c0d5fvXqVXTo0AF3796Fq6srateujcjISLi6ump3IkRERJSr6EREjF2JnCYxMRHOzs5ISEjg7TAiAyryzXrNjh07rqlmxyainOF1/n/nij5ARERERGpiAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHAtjV4AotyryzXrNjh07rqlmxyYiIrYAERERkQliAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcoyZAu3fvRrNmzeDp6QmdToc1a9bobe/atSt0Op3eo3Hjxv953BkzZqBIkSKwsbFB9erVcejQIY3OgIiIiHIjoyZAycnJKF++PGbMmPHCfRo3bowbN24oj99+++2lx/z9998xYMAAjBgxAlFRUShfvjwCAwNx69YttatPREREuZRRV4MPCgpCUFDQS/extraGu7v7Kx9z4sSJ6NGjB7p16wYAmDVrFtavX4/58+fjm2++eav6EhER0bshx/cB2rlzJwoUKIDixYvj888/x927d1+4b2pqKo4ePYqAgAClzMzMDAEBAThw4MALX5eSkoLExES9BxEREb27cnQC1LhxYyxatAjbtm3DDz/8gF27diEoKAjp6enZ7n/nzh2kp6fDzc1Nr9zNzQ3x8fEvjBMeHg5nZ2fl4e3trep5EBERUc5i1Ftg/6V9+/bKz2XLlkW5cuXg6+uLnTt3omHDhqrFGTJkCAYMGKA8T0xMZBJERET0DsvRLUD/5uPjg/z58yMmJibb7fnz54e5uTlu3rypV37z5s2X9iOytraGk5OT3oOIiIjeXbkqAbp69Sru3r0LDw+PbLdbWVmhcuXK2LZtm1KWkZGBbdu2oWbNmoaqJhEREeVwRk2AkpKScPz4cRw/fhwAcOnSJRw/fhxxcXFISkrCV199hcjISMTGxmLbtm1o0aIF/Pz8EBgYqByjYcOGmD59uvJ8wIABmDt3LhYuXIgzZ87g888/R3JysjIqjIiIiMiofYCOHDmCBg0aKM8z++GEhIRg5syZOHnyJBYuXIgHDx7A09MTjRo1wujRo2Ftba285sKFC7hz547yvF27drh9+zaGDx+O+Ph4VKhQARs3bszSMZqIiIhMl1EToPr160NEXrh906ZN/3mM2NjYLGWhoaEIDQ19m6oRERHROyxX9QEiIiIiUgMTICIiIjI5TICIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUZdCoOIyNQU+Wa9ZseOHddUs2MTvWvYAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJMWoCtHv3bjRr1gyenp7Q6XRYs2aNsu3p06cYPHgwypYtC3t7e3h6eqJLly64fv36S485cuRI6HQ6vUeJEiU0PhMiIiLKTYyaACUnJ6N8+fKYMWNGlm2PHj1CVFQUhg0bhqioKKxevRrnzp1D8+bN//O4pUuXxo0bN5TH3r17tag+ERER5VIWxgweFBSEoKCgbLc5Oztjy5YtemXTp09HtWrVEBcXh0KFCr3wuBYWFnB3d1e1rkRERPTuyFV9gBISEqDT6eDi4vLS/aKjo+Hp6QkfHx907NgRcXFxL90/JSUFiYmJeg8iIiJ6d+WaBOjJkycYPHgwOnToACcnpxfuV716dURERGDjxo2YOXMmLl26hDp16uDhw4cvfE14eDicnZ2Vh7e3txanQERERDlErkiAnj59irZt20JEMHPmzJfuGxQUhDZt2qBcuXIIDAzEhg0b8ODBAyxfvvyFrxkyZAgSEhKUx5UrV9Q+BSIiIspBjNoH6FVkJj+XL1/G9u3bX9r6kx0XFxcUK1YMMTExL9zH2toa1tbWb1tVIiIiyiVydAtQZvITHR2NrVu3Il++fK99jKSkJFy4cAEeHh4a1JCIiIhyI6MmQElJSTh+/DiOHz8OALh06RKOHz+OuLg4PH36FK1bt8aRI0fw66+/Ij09HfHx8YiPj0dqaqpyjIYNG2L69OnK80GDBmHXrl2IjY3F/v370bJlS5ibm6NDhw6GPj0iIiLKoYx6C+zIkSNo0KCB8nzAgAEAgJCQEIwcORLr1q0DAFSoUEHvdTt27ED9+vUBABcuXMCdO3eUbVevXkWHDh1w9+5duLq6onbt2oiMjISrq6u2J0NERES5hlEToPr160NEXrj9ZdsyxcbG6j1ftmzZ21aLiIiI3nFvdAvMx8cHd+/ezVL+4MED+Pj4vHWliIiIiLT0RglQbGws0tPTs5SnpKTg2rVrb10pIiIiIi291i2wzD45ALBp0yY4Ozsrz9PT07Ft2zYUKVJEtcoRERERaeG1EqDg4GAAgE6nQ0hIiN42S0tLFClSBBMmTFCtckRERERaeK0EKCMjAwBQtGhRHD58GPnz59ekUkRERERaeqNRYJcuXVK7HkREREQG88bD4Ldt24Zt27bh1q1bSstQpvnz5791xYiIiIi08kYJUFhYGEaNGoUqVarAw8MDOp1O7XoRERERaeaNEqBZs2YhIiICnTt3Vrs+RERERJp7o3mAUlNT8d5776ldFyIiIiKDeKME6NNPP8XSpUvVrgsRERGRQbzRLbAnT55gzpw52Lp1K8qVKwdLS0u97RMnTlSlckRERERaeKME6OTJk8oK7adOndLbxg7RRERElNO9UQK0Y8cOtetBREREZDBv1AeIiIiIKDd7oxagBg0avPRW1/bt29+4QkRERERae6MEKLP/T6anT5/i+PHjOHXqVJZFUomIiIhymjdKgCZNmpRt+ciRI5GUlPRWFSIiIiLSmqp9gDp16sR1wIiIiCjHUzUBOnDgAGxsbNQ8JBEREZHq3ugWWKtWrfSeiwhu3LiBI0eOYNiwYapUjIiIiEgrb5QAOTs76z03MzND8eLFMWrUKDRq1EiVihERERFp5Y0SoAULFqhdDyIiIiKDeaMEKNPRo0dx5swZAEDp0qVRsWJFVSpFREREpKU3SoBu3bqF9u3bY+fOnXBxcQEAPHjwAA0aNMCyZcvg6uqqZh2JiIiIVPVGo8D69OmDhw8f4vTp07h37x7u3buHU6dOITExEX379lW7jkRERESqeqMWoI0bN2Lr1q0oWbKkUlaqVCnMmDGDnaCJiIgox3ujFqCMjAxYWlpmKbe0tERGRsZbV4qIiIhIS2+UAL3//vvo168frl+/rpRdu3YN/fv3R8OGDVWrHBEREZEW3igBmj59OhITE1GkSBH4+vrC19cXRYsWRWJiIqZNm6Z2HYmIiIhU9UZ9gLy9vREVFYWtW7fi7NmzAICSJUsiICBA1coRERERaeG1WoC2b9+OUqVKITExETqdDh988AH69OmDPn36oGrVqihdujT27NnzysfbvXs3mjVrBk9PT+h0OqxZs0Zvu4hg+PDh8PDwgK2tLQICAhAdHf2fx50xYwaKFCkCGxsbVK9eHYcOHXqd0yQiIqJ33GslQJMnT0aPHj3g5OSUZZuzszN69uyJiRMnvvLxkpOTUb58ecyYMSPb7T/++COmTp2KWbNm4eDBg7C3t0dgYCCePHnywmP+/vvvGDBgAEaMGIGoqCiUL18egYGBuHXr1ivXi4iIiN5tr5UAnThxAo0bN37h9kaNGuHo0aOvfLygoCCMGTMGLVu2zLJNRDB58mQMHToULVq0QLly5bBo0SJcv349S0vR8yZOnIgePXqgW7duKFWqFGbNmgU7OzvMnz//letFRERE77bXSoBu3ryZ7fD3TBYWFrh9+/ZbVwoALl26hPj4eL1+Rc7OzqhevToOHDiQ7WtSU1Nx9OhRvdeYmZkhICDgha8BgJSUFCQmJuo9iIiI6N31WgmQl5cXTp069cLtJ0+ehIeHx1tXCgDi4+MBAG5ubnrlbm5uyrZ/u3PnDtLT01/rNQAQHh4OZ2dn5eHt7f2WtSciIqKc7LUSoCZNmmDYsGHZ9sF5/PgxRowYgQ8//FC1yhnKkCFDkJCQoDyuXLli7CoRERGRhl5rGPzQoUOxevVqFCtWDKGhoShevDgA4OzZs5gxYwbS09Px3XffqVIxd3d3AM9uuz3fqnTz5k1UqFAh29fkz58f5ubmuHnzpl75zZs3leNlx9raGtbW1m9faSIiIsoVXqsFyM3NDfv370eZMmUwZMgQtGzZEi1btsS3336LMmXKYO/evVluP72pokWLwt3dHdu2bVPKEhMTcfDgQdSsWTPb11hZWaFy5cp6r8nIyMC2bdte+BoiIiIyPa89EWLhwoWxYcMG3L9/HzExMRAR+Pv7I0+ePK8dPCkpCTExMcrzS5cu4fjx48ibNy8KFSqEL7/8EmPGjIG/vz+KFi2KYcOGwdPTE8HBwcprGjZsiJYtWyI0NBQAMGDAAISEhKBKlSqoVq0aJk+ejOTkZHTr1u2160dERETvpjeaCRoA8uTJg6pVq75V8CNHjqBBgwbK8wEDBgAAQkJCEBERga+//hrJycn47LPP8ODBA9SuXRsbN26EjY2N8poLFy7gzp07yvN27drh9u3bGD58OOLj41GhQgVs3LhRtZYpIiIiyv3eOAFSQ/369SEiL9yu0+kwatQojBo16oX7xMbGZikLDQ1VWoSIiIiI/u2NFkMlIiIiys2YABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmJ8cnQEWKFIFOp8vy6N27d7b7R0REZNnXxsbGwLUmIiKinMzC2BX4L4cPH0Z6erry/NSpU/jggw/Qpk2bF77GyckJ586dU57rdDpN60hERES5S45PgFxdXfWejxs3Dr6+vqhXr94LX6PT6eDu7q511YiIiCiXyvG3wJ6XmpqKJUuW4JNPPnlpq05SUhIKFy4Mb29vtGjRAqdPn37pcVNSUpCYmKj3ICIiondXrkqA1qxZgwcPHqBr164v3Kd48eKYP38+1q5diyVLliAjIwPvvfcerl69+sLXhIeHw9nZWXl4e3trUHsiIiLKKXJVAjRv3jwEBQXB09PzhfvUrFkTXbp0QYUKFVCvXj2sXr0arq6umD179gtfM2TIECQkJCiPK1euaFF9IiIiyiFyfB+gTJcvX8bWrVuxevXq13qdpaUlKlasiJiYmBfuY21tDWtr67etIhEREeUSuaYFaMGCBShQoACaNm36Wq9LT0/H33//DQ8PD41qRkRERLlNrkiAMjIysGDBAoSEhMDCQr/RqkuXLhgyZIjyfNSoUdi8eTMuXryIqKgodOrUCZcvX8ann35q6GoTERFRDpUrboFt3boVcXFx+OSTT7Jsi4uLg5nZ/+dx9+/fR48ePRAfH488efKgcuXK2L9/P0qVKmXIKhMREVEOlisSoEaNGkFEst22c+dOveeTJk3CpEmTDFArIiIiyq1yxS0wIiIiIjUxASIiIiKTkytugb1rinyzXpPjxo57vRFyRGQatPrMAfi5Q7kXW4CIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUyAiIiIyOQwASIiIiKTwwSIiIiITA4TICIiIjI5TICIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUyAiIiIyOQwASIiIiKTwwSIiIiITA4TICIiIjI5TICIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjk5OgEaOXIkdDqd3qNEiRIvfc2KFStQokQJ2NjYoGzZstiwYYOBaktERES5RY5OgACgdOnSuHHjhvLYu3fvC/fdv38/OnTogO7du+PYsWMIDg5GcHAwTp06ZcAaExERUU6X4xMgCwsLuLu7K4/8+fO/cN8pU6agcePG+Oqrr1CyZEmMHj0alSpVwvTp0w1YYyIiIsrpcnwCFB0dDU9PT/j4+KBjx46Ii4t74b4HDhxAQECAXllgYCAOHDjw0hgpKSlITEzUexAREdG7K0cnQNWrV0dERAQ2btyImTNn4tKlS6hTpw4ePnyY7f7x8fFwc3PTK3Nzc0N8fPxL44SHh8PZ2Vl5eHt7q3YORERElPPk6AQoKCgIbdq0Qbly5RAYGIgNGzbgwYMHWL58uapxhgwZgoSEBOVx5coVVY9PREREOYuFsSvwOlxcXFCsWDHExMRku93d3R03b97UK7t58ybc3d1felxra2tYW1urVk8iIiLK2XJ0C9C/JSUl4cKFC/Dw8Mh2e82aNbFt2za9si1btqBmzZqGqB4RERHlEjk6ARo0aBB27dqF2NhY7N+/Hy1btoS5uTk6dOgAAOjSpQuGDBmi7N+vXz9s3LgREyZMwNmzZzFy5EgcOXIEoaGhxjoFIiIiyoFy9C2wq1evokOHDrh79y5cXV1Ru3ZtREZGwtXVFQAQFxcHM7P/z+Hee+89LF26FEOHDsW3334Lf39/rFmzBmXKlDHWKRAREVEOlKMToGXLlr10+86dO7OUtWnTBm3atNGoRkRERPQuyNG3wIiIiIi0wASIiIiITA4TICIiIjI5TICIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiExOjl4Kg4iIiJ4p8s16zY4dO66pZsfOqdgCRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJsTB2BejdVOSb9ZocN3ZcU02OS9nT6vcI8HdJlBu8y5/lbAEiIiIik8MEiIiIiEwOEyAiIiIyOTk6AQoPD0fVqlXh6OiIAgUKIDg4GOfOnXvpayIiIqDT6fQeNjY2BqoxERER5QY5OgHatWsXevfujcjISGzZsgVPnz5Fo0aNkJyc/NLXOTk54caNG8rj8uXLBqoxERER5QY5ehTYxo0b9Z5HRESgQIECOHr0KOrWrfvC1+l0Ori7u2tdPSIiIsqlcnQL0L8lJCQAAPLmzfvS/ZKSklC4cGF4e3ujRYsWOH369Ev3T0lJQWJiot6DiIiI3l25JgHKyMjAl19+iVq1aqFMmTIv3K948eKYP38+1q5diyVLliAjIwPvvfcerl69+sLXhIeHw9nZWXl4e3trcQpERESUQ+SaBKh37944deoUli1b9tL9atasiS5duqBChQqoV68eVq9eDVdXV8yePfuFrxkyZAgSEhKUx5UrV9SuPhEREeUgOboPUKbQ0FD89ddf2L17NwoWLPhar7W0tETFihURExPzwn2sra1hbW39ttUkIiKiXCJHtwCJCEJDQ/HHH39g+/btKFq06GsfIz09HX///Tc8PDw0qCERERHlRjm6Bah3795YunQp1q5dC0dHR8THxwMAnJ2dYWtrCwDo0qULvLy8EB4eDgAYNWoUatSoAT8/Pzx48ADjx4/H5cuX8emnnxrtPIiIiChnydEJ0MyZMwEA9evX1ytfsGABunbtCgCIi4uDmdn/N2Tdv38fPXr0QHx8PPLkyYPKlStj//79KFWqlKGqTURERDlcjk6AROQ/99m5c6fe80mTJmHSpEka1YiIiIjeBTm6DxARERGRFpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHKYABEREZHJYQJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRybEwdgWI6NUU+Wa9ZseOHddUs2OT6THGe5V/H/S62AJEREREJocJEBEREZkcJkBERERkcpgAERERkclhAkREREQmhwkQERERmRwmQERERGRymAARERGRyWECRERERCaHCRARERGZHCZAREREZHJyRQI0Y8YMFClSBDY2NqhevToOHTr00v1XrFiBEiVKwMbGBmXLlsWGDRsMVFMiIiLKDXJ8AvT7779jwIABGDFiBKKiolC+fHkEBgbi1q1b2e6/f/9+dOjQAd27d8exY8cQHByM4OBgnDp1ysA1JyIiopwqxydAEydORI8ePdCtWzeUKlUKs2bNgp2dHebPn5/t/lOmTEHjxo3x1VdfoWTJkhg9ejQqVaqE6dOnG7jmRERElFPl6AQoNTUVR48eRUBAgFJmZmaGgIAAHDhwINvXHDhwQG9/AAgMDHzh/kRERGR6LIxdgZe5c+cO0tPT4ebmplfu5uaGs2fPZvua+Pj4bPePj49/YZyUlBSkpKQozxMSEgAAiYmJb1r1l8pIeaTJcbWq75vgOb6d7M7T0PGMEdMY52ho/D2qH89YMQ3tXbquWl3TzOOKyH/um6MTIEMJDw9HWFhYlnJvb28j1ObNOU82dg20ZwrnCBj+PI1xXU3hHA2Nv8d3J6ahvWu/x4cPH8LZ2fml++ToBCh//vwwNzfHzZs39cpv3rwJd3f3bF/j7u7+WvsDwJAhQzBgwADleUZGBu7du4d8+fJBp9O9xRm8ncTERHh7e+PKlStwcnJ6J2PyHN+NmDzHdyMmz5Exc0u8FxERPHz4EJ6env+5b45OgKysrFC5cmVs27YNwcHBAJ4lJ9u2bUNoaGi2r6lZsya2bduGL7/8UinbsmULatas+cI41tbWsLa21itzcXF52+qrxsnJyeBvKEPH5Dm+GzF5ju9GTJ4jY+aWeNn5r5afTDk6AQKAAQMGICQkBFWqVEG1atUwefJkJCcno1u3bgCALl26wMvLC+Hh4QCAfv36oV69epgwYQKaNm2KZcuW4ciRI5gzZ44xT4OIiIhykByfALVr1w63b9/G8OHDER8fjwoVKmDjxo1KR+e4uDiYmf3/YLb33nsPS5cuxdChQ/Htt9/C398fa9asQZkyZYx1CkRERJTD5PgECABCQ0NfeMtr586dWcratGmDNm3aaFwr7VlbW2PEiBFZbs+9SzF5ju9GTJ7juxGT58iYuSWeGnTyKmPFiIiIiN4hOXoiRCIiIiItMAEiIiIik8MEiIiIiEwOEyAiIiIyObliFBgRkal58uQJbGxsjF0Nopc6evQozpw5AwAoVaoUKlWqZOQavTomQDnQnj17MHv2bFy4cAErV66El5cXFi9ejKJFi6J27dqqx9u1axd++uknvTfxV199hTp16qgei94thn6vAob/wE1PT8eaNWuUmKVLl0bz5s1hbm6ueqyMjAx8//33mDVrFm7evInz58/Dx8cHw4YNQ5EiRdC9e3fVYwKGPUdjxiT13Lp1C+3bt8fOnTuVlRMePHiABg0aYNmyZXB1dTVuBV+FUI6ycuVKsbW1lU8//VSsra3lwoULIiIybdo0CQoKUj3e4sWLxcLCQtq2bStTpkyRKVOmSNu2bcXS0lJ+/fVX1eM9LyUlRc6ePStPnz7VNM6/XblyRa5cufLOxjTUdTX0e/XmzZvSoEED0el0kidPHsmTJ4/odDp5//335datW6rHExGJjo6WYsWKiZ2dnVSsWFEqVqwodnZ2Urx4cYmJiVE9XlhYmPj4+MiSJUvE1tZWuabLli2TGjVqqB5PxPDnaKyYIiL379+XuXPnyjfffCN3794VEZGjR4/K1atXNYspYti//5iYGPnuu++kffv2cvPmTRER2bBhg5w6dUrVOG3btpUqVarIP//8o5SdPn1aqlSpIu3bt1c1llaYAOUwFSpUkIULF4qIiIODg/IBGBUVJW5ubqrHK1GihEycODFL+YQJE6REiRKqxxMRSU5Olk8++UTMzc3F3NxcOcfQ0FAJDw/XJGZ6erqEhYWJk5OTmJmZiZmZmTg7O8uoUaMkPT39nYhp6Otq6PeqMT5wg4KCpHHjxso/SxGRO3fuSOPGjaVJkyaqx/P19ZWtW7eKiP41PXPmjLi4uKgeT8Tw52ismCdOnBBXV1fx8/MTCwsL5dp+99130rlzZ9XjGeMzZ+fOnWJraysBAQFiZWWlnGN4eLh89NFHqsZycnKSQ4cOZSk/ePCgODs7qxpLK0yAchhbW1u5dOmSiOh/AF64cEGsra1Vj2dlZSXR0dFZyqOjozWJJyLSt29fqVy5suzZs0fs7e2Vc1yzZo1UqFBBk5jffPONuLq6ys8//ywnTpyQEydOyIwZM8TV1VW+/fbbdyKmoa+rod+rxvjAtbOzk5MnT2YpP378uNjb26sez8bGRmJjY0VE/5qePn1ak3gihj9HY8Vs2LChfPXVVyKif2337dsnhQsXVj2eMT5zatSoIRMmTBAR/XM8ePCgeHl5qRrLwcFBjh07lqU8KipKHB0dVY2lFSZAOUzRokVly5YtIqL/Bl64cKGULFlS9Xi+vr4ya9asLOUzZ84UPz8/1eOJiBQqVEgOHDggIvrnGB0drdkfjoeHh6xduzZL+Zo1a8TT0/OdiGno62ro96oxPnDz5Mkj+/bty1K+d+9eyZMnj+rxKlWqJIsXLxYR/WsaFhYmtWvXVj2eiOHP0VgxnZyclNtrz1/b2NhYTRJ2Y3zm2Nvby8WLF0VE/xwvXbqk+jk2b95c6tatK9euXVPKrl69KvXq1ZPg4GBVY2mFCVAOM3bsWClVqpRERkaKo6Oj7NmzR5YsWSKurq4ydepU1eP9/PPPYmVlJb169ZJFixbJokWLpGfPnmJtbZ1tYqSG5/s2PP9Hevz4cXFyctIkprW1tZw7dy5L+dmzZ8XGxuadiGno62ro96oxPnA7d+4spUuXlsjISMnIyJCMjAw5cOCAlClTRkJCQlSPt2bNGnF2dpZx48aJnZ2djB8/Xj799FOxsrKSzZs3qx5PxPDnaKyYrq6uEhUVJSL6fx+bN2+WggULqh7PGJ85Xl5eSmL5/DmuXr1afHx8VI0VFxcnFSpUEEtLS/Hx8REfHx+xtLSUihUrGryP5ZtiApTDZGRkyJgxY8Te3l50Op3odDqxsbGRoUOHahZz9erVUqtWLcmbN6/kzZtXatWqJWvWrNEsXp06dZR/kA4ODso3ltDQUAkMDNQkZrVq1aRPnz5ZykNDQ6V69ervRExDX1dDv1eN8YF7//59ad68ueh0OrGyshIrKysxMzOT4OBgefDggSYxd+/eLQEBAeLq6iq2trZSq1Yt2bRpkyaxRF5+jvfv3zd4TK2ua/fu3SU4OFhSU1OVv4/Lly9LxYoVpV+/fqrHM8ZnzsCBA6V27dpy48YNcXR0lOjoaNm7d6/4+PjIyJEjVY+XkZEhmzdvlqlTp8rUqVOVFuHcgouh5lCpqamIiYlBUlISSpUqBQcHB2NXSTV79+5FUFAQOnXqhIiICPTs2RP//PMP9u/fj127dqFy5cqqx9y1axeaNm2KQoUKoWbNmgCAAwcO4MqVK9iwYYMmQ/4NHdMY1xUw7HtVRLB161acPXsWAFCyZEkEBARoFi9TdHQ0zpw5A51Oh5IlS8LPz0/zmIYWExOjDEk31DkaMmZCQgJat26NI0eO4OHDh/D09ER8fDxq1qyJDRs2wN7eXtV4xvjMSU1NRe/evREREYH09HRYWFggPT0dH3/8MSIiIjjFwL8wAcrhEhMTsX37dhQvXhwlS5Y0dnVUc+HCBYwbNw4nTpxAUlISKlWqhMGDB6Ns2bKaxbx27Rp+/vlnvX+eX3zxBTw9PTWLef36dcyYMcNgMY1xXTO9q+/VTJkflTqdTrMYV65cgU6nQ8GCBQEAhw4dwtKlS1GqVCl89tlnmsQcNWoUBg0aBDs7O73yx48fY/z48Rg+fLgmcY1l3759en8fWibQhv77zxQXF4dTp04hKSkJFStWhL+/v+ox+vbtCz8/P/Tt21evfPr06YiJicHkyZNVj6k6YzY/UVZt2rSRadOmiYjIo0ePpFixYmJpaSkWFhaycuVKVWK4uLgo86j814PoRQzxXv23rVu3StOmTZVbYE2bNtW82f2XX36R0qVLK7dqSpcuLXPnztUkVu3atWXRokUiIsptjJo1a0r+/PklLCxMk5hmZmbKfDHPu3PnjpiZmWkSs1WrVjJu3Lgs5T/88IO0bt1ak5jZ0eoWnynw9PSUI0eOZCk/evSo6iPOtMKZoHOY3bt347vvvgMA/PHHH8jIyMCDBw+wcOFCjBkzBh999NFbxzB2Zh4VFQVLS0ulVWLt2rVYsGABSpUqhZEjR8LKykr1mAsWLICDgwPatGmjV75ixQo8evQIISEhqscEns2MeujQIdy6dQsZGRl627p06aJqLENfV0O8V5/3888/o1+/fmjdujX69esHAIiMjESTJk0wadIk9O7dW9V4ADB8+HBMnDgRffr00buN0b9/f8TFxWHUqFGqxjt16hSqVasGAFi+fDnKli2Lffv2YfPmzejVq5cmrTEikm2r1okTJ5A3b17V4wHP3jsjR47MUh4UFIQJEyZoEvOHH35AkSJF0K5dOwBA27ZtsWrVKri7u2PDhg0oX7686jEN+fcPPJtdOyIiAtu2bcs25vbt21WLdffuXTg7O2cpd3Jywp07d1SLoyljZ2Ckz8bGRuLi4kTk2UiJwYMHi4jI5cuXNZsfw9CqVKmitBBkzhnToUMH8fPz06QzooiIv7+/bN++PUv5zp07pVixYprEXLdunTg6OopOpxNnZ2dxcXFRHlq0rhn6uhr6verl5aW0OD1v+vTpmg0rzp8/vyxdujRL+dKlSyVfvnyqx7O3t1fmVmrWrJnSSnL58mXVRw5lvg/NzMyytApnTt73xRdfqBozk42NjZw9ezZL+ZkzZzQbIVWkSBFlhNTmzZvFxcVFNm3aJN27d5cPPvhA9XiG/vsXEendu7fY29tL27ZtpV+/fvLll1/qPdRUunTpbP8ep06dqsk0GFpgApTD+Pv7y++//y5JSUni6uoq27ZtE5FnQ5m1+MAVEUlLS5OVK1fK6NGjZfTo0bJ69WpJS0vTJJaI/nwc48aNk0aNGonIszlAtBiOKvJsSGrmP5bnXbp0SbMPXH9/f+nXr58kJydrcvx/M/R1NfR71d7ePttJO8+fP6/ZlwNnZ2c5f/58lvJz585pMvlitWrVZPDgwbJ7926xsbGR48ePi4jIgQMHVL+tEBERIQsWLBCdTidTpkyRiIgI5bF06VLZv3+/qvGeV7Vq1Wxv6Y0YMUIqVaqkScznE/a+ffvKZ599JiLPfpdazLJt6L9/EZF8+fLJ+vXrDRJr3rx5YmtrK8OHD5edO3fKzp07ZdiwYWJnZydz5swxSB3eFhOgHGbGjBliYWEhLi4uUq5cOWXK9KlTp0r9+vVVjxcdHS3+/v4GXZPH0dFR+acSEBAgkydPFhFtvuVm8vb2fuGkZFrdr7azs1Pm4TAEQ19XQ79XO3ToID/++GOW8vHjx0u7du1UjyfybMhy//79s5QPHDhQk9aRHTt2iIuLi5iZmUm3bt2U8iFDhkjLli1VjyfyrBU0NTVVk2O/yLp168TCwkK6dOmiJF2dO3cWCwsL+eOPPzSJ6eHhobQAFStWTJYvXy4iz+bl0WIiTUP//Ys8O8fs5h7Sys8//yxeXl7KNBhFixZVlsfJDTgKLAc6cuQIrly5gg8++EAZUrx+/Xq4uLigVq1aqsZq0qQJRAS//vqrcr//7t276NSpE8zMzLB+/XpV4wHA+++/D29vbwQEBKB79+74559/4Ofnh127diEkJASxsbGqxxw8eDB+//13LFiwAHXr1gXwbJjqJ598gtatW+Onn35SPWarVq3Qvn17tG3bVvVjZ8cY11Xr9+rUqVOVnxMTE/HTTz+hVq1aSn+cyMhI7Nu3DwMHDsTQoUPfOh4ADBgwQPk5LS0NERERKFSoEGrUqAEAOHjwIOLi4tClSxdMmzZNlZjPS09PR2JiIvLkyaOUxcbGws7ODgUKFFA93vOePHmC1NRUvTInJydNYq1fvx5jx47F8ePHYWtri3LlymHEiBGoV6+eJvFCQ0Px119/wd/fH8eOHUNsbCwcHBywbNky/Pjjj4iKilI1nqH//gFgwoQJuHjxIqZPn67paMV/u337NmxtbXPddC1MgHKo1NRUXLp0Cb6+vrCw0K6vur29PSIjI7MMkz5x4gRq1aqFpKQk1WOePHkSHTt2RFxcHAYMGIARI0YAAPr06YO7d+9i6dKlqsdMTU1F586dsWLFCuV6ZmRkoEuXLpg1a5YmHa/nzZuHUaNGoVu3bihbtiwsLS31tjdv3lzVeMa4roC279WiRYu+0n46nQ4XL15UJWaDBg1eOaaanUozpaWlYefOnbhw4QI+/vhjODo64vr163ByctLkH8yjR4/w9ddfY/ny5bh7926W7enp6arHNIanT59iypQpuHLlCrp27YqKFSsCACZNmgRHR0d8+umnqsYz9N8/ALRs2RI7duxA3rx5Ubp06SwxV69erVqsx48fQ0SU6RMuX76MP/74A6VKlUKjRo1Ui6MlJkA5zKNHj9CnTx8sXLgQAHD+/Hn4+PigT58+8PLywjfffKNqvLx58+Kvv/7Ce++9p1e+b98+NGvWDPfu3VM13ss8efIE5ubmWf5o1XT+/HmcOHECtra2KFu2LAoXLqxZLDMzsxdu0+l0BvvHotV1NfR71RRcvnwZjRs3RlxcHFJSUpRr2q9fP6SkpGDWrFmqx+zduzd27NiB0aNHo3PnzpgxYwauXbuG2bNnY9y4cejYsaPqMYFnI6RWrlyJixcvYtCgQcibNy+ioqLg5uYGLy8vTWIakjH+/rt16/bS7QsWLFAtVqNGjdCqVSv06tULDx48QPHixWFlZYU7d+5g4sSJ+Pzzz1WLpRnj3X2j7Bh6RW9jrMkj8mz+jblz58o333wjd+/eFZFn80dcvXpVs5imwJDX1dDvVUNLTU0Vc3Nz+fvvvw0Ws0WLFtKpUydJSUnRW8tpx44dmi1O7O3tLTt27BARUZZPEBFZtGiRBAUFaRLzxIkT4urqKn5+fmJhYaGc53fffSedO3fWJKbIs3OqVauWeHh4SGxsrIiITJo0SdOlf95V+fLlk1OnTomIyNy5c5V+gMuXL5cSJUoYuXavhvMA5TBr1qzB77//jho1aujdwy1dujQuXLigerypU6ciJCQENWvWVFoI0tLS0Lx5c0yZMkX1eMCzWzUNGzaEi4sLYmNj0aNHD+TNmxerV69GXFwcFi1apEqcAQMGYPTo0bC3t9fr15GdiRMnqhLTmAx1XTMZ+r0KAFevXsW6desQFxeXpa+K2r9DS0tLFCpUyKC3gPbs2YP9+/dnuSVbpEgRXLt2TZOY9+7dg4+PD4Bn/X0yW31r166t2bf4AQMGoGvXrvjxxx/h6OiolDdp0gQff/yxJjFnzpyJ4cOH48svv8T333+v/F5dXFwwefJktGjRQpO4wLNWWBsbG82O/2+3b9/GuXPnAADFixeHq6ur6jEePXqk/O42b96MVq1awczMDDVq1MDly5dVj6cFJkA5zO3bt7Pt6JicnKxJpzYXFxesXbsW0dHRetO1a7kmz4ABA9CtWzfNP/yOHTuGp0+fKj+/iJadBZOTk7Fr165s/2H/ewr5t2Wo65rJ0O/Vbdu2oXnz5vDx8cHZs2dRpkwZxMbGQkRQqVIl1eMBwHfffYdvv/0Wixcv1mxSwOdlZGRkm3BdvXpV73eqJh8fH1y6dAmFChVCiRIlsHz5clSrVg1//vknXFxcNIl5+PBhzJ49O0u5l5cX4uPjNYk5bdo0zJ07F8HBwRg3bpxSXqVKFQwaNEj1eOnp6Rg7dixmzZqFmzdvKrczhw0bhiJFiqB79+6qx0xOTkafPn2waNEiZRJEc3NzpcP+v5c7eRt+fn5Ys2YNWrZsiU2bNqF///4AgFu3bmnWcV51xm6CIn3GWCnd0J6fr+b5Zv7Y2FixtrY2ZtVUFRUVJe7u7uLk5CTm5ubi6uoqOp1O7O3tpWjRoqrHM/R1NfR7tWrVqjJ8+HAl3oULF+Thw4fSvHlz+fnnn1WPJyJSoUIFcXBwEGtraylWrJgyVUTmQ21t27aVHj16iMj/X9OHDx/K+++/L127dlU9nojIxIkTZcqUKSIismXLFrGxsRFra2sxMzNTplJQm6urq0RFRYmI/nt18+bNms0FZmNjo9z2ej7m+fPnNZkmIiwsTHx8fGTJkiVia2urxFu2bJnUqFFD9XgiIp999pn4+PjIhg0bJCEhQRISEmT9+vXi6+srvXr1UjXWihUrxNLSUszMzCQgIEApHzt2rDRu3FjVWFphC1AOM3bsWAQFBeGff/5BWloapkyZoreit9oMOXV6JmtrayQmJmYpP3/+vCZNtcbSv39/NGvWDLNmzYKzszMiIyNhaWmJTp06KUs5qMnQ19XQ79UzZ87gt99+AwBYWFjg8ePHcHBwwKhRo9CiRQtNbtcEBwerfsyXmTBhAgIDA1GqVCk8efIEH3/8MaKjo5E/f37l3NWW+c0dAAICAnDmzBlERUXBz88P5cqV0yRm8+bNMWrUKCxfvhzAs1bYuLg4DB48WPUlVDIVLVoUx48fzzLwYePGjZos3rto0SLMmTMHDRs2RK9evZTy8uXLK63talu1ahVWrlyJ+vXrK2VNmjSBra0t2rZti5kzZ6oWq3Xr1qhduzZu3Liht4xIw4YN0bJlS9XiaIkJUA5Tu3ZtHD9+HOPGjUPZsmWxefNmVKpUCQcOHNBkRe9+/fohIiICTZs2RZkyZQwyd4QxPvyAZ3PWLF++PNvbUWoOD810/PhxzJ49G2ZmZjA3N0dKSgp8fHzw448/IiQkBK1atVI1nqGvq6Hfq/b29srvzcPDAxcuXEDp0qUBQLO1hzKnEjCUggUL4sSJE1i2bBlOnjyJpKQkdO/eHR07doStra1B6lCkSBEUKVJE0xgTJkxA69atUaBAATx+/Bj16tVDfHw8atSoge+//16TmAMGDEDv3r3x5MkTiAgOHTqE3377DeHh4fjll19Uj3ft2rVsuxJkZGQot+bV9ujRI7i5uWUpL1CgAB49eqR6PHd3dyQlJWHLli2oW7cubG1tUbVqVYPOQfRWjN0ERcZlyKnTMz148EACAgLExcVFzM3NxdvbWywtLaVu3bqSlJSkSczffvtNLC0t5cMPPxQrKyv58MMPpVixYuLs7KzZrYX8+fMrMzP7+/vLxo0bReTZekd2dnaqxzPGdTWkFi1aKFPsDxw4UPz8/GTMmDFSqVIladiwoWZxTWHE4s6dO+XDDz8UX19f8fX1lWbNmsnu3bs1j7t3716ZMWOG/PDDD7JlyxbN4y1ZskT8/PyUmYu9vLzkl19+0SRWpUqVZPHixSKif8stLCxMateurUnM999/X9q0aSOPHz9Wyh49eiRt2rRR/W/kzp078v7774tOpxMzMzPl/Lp16yYDBgxQNZZW2AKUA2R32+JF1O5cZmVlpWmH5+w4Oztjy5Yt2Lt3r/Itt1KlSggICNAs5tixY5UVwx0dHTFlyhQULVoUPXv2hIeHhyYxK1asiMOHD8Pf3x/16tXD8OHDcefOHSxevBhlypRRPZ4xrmtGRgZiYmKyvX2aOeO2WiZOnKhMzBkWFoakpCT8/vvv8Pf312wU38mTJxEQEABnZ2eDjKwDgOjoaOzYsSPba6rFavBLlixBt27d0KpVK6Vj/t69e9GwYUNERESo2oF++/btCA0NRWRkJJycnFCrVi1lxvCEhASULl0as2bNQp06dVSL+byOHTuiY8eOePToEZKSkjSdWXv48OEICQnBtWvXkJGRgdWrV+PcuXNYtGgR/vrrL01iTpkyBYGBgShYsKByW+rEiROwsbHBpk2bVI3Vv39/WFpaIi4uTu8WYrt27TBgwABMmDBB1XiaMHYGRqJk0K/yUNtPP/0kX3zxhWRkZKh+7JzEzs5OWQw1b968cvLkSRER+eeff8Td3V2TmIcPH1ZWoL9586YEBgaKo6OjVKpUSVnkMjc7cOCAFC1aVMzMzJRv1JkPtd+raWlpsmvXLrl//76qx/0vDRs2lK+++kpE9L/F79u3TwoXLqx6vDlz5oi5ubm4ublJ+fLlpUKFCspDi07XIiIlSpSQiRMnZimfMGGC6vO5NGvWLNtYmaZMmSLBwcGqxjSm3bt3S0BAgLi6uoqtra3UqlVLNm3apGnM5ORkmTNnjgwYMEAGDBggc+fOlUePHqkex83NTfkce/5v48KFC5otTqw2tgDlADt27FB+jo2NxTfffIOuXbsq6x0dOHAACxcuRHh4uOqx9+7dix07duB///ufplOnP7+m039Re3g4AOTJkwcPHz4E8Gyo7alTp1C2bFk8ePBAk3vjwLPhtZkKFCiAjRs3ahLnedu2bXthh/b58+erGqtXr16oUqUK1q9fDw8PD03v+5ubm6NRo0Y4c+aMZkOzs2Po4dpjxozB999/j8GDB6t+7Be5ePEimjVrlqW8efPm+Pbbb1WNdeLECfzwww8v3N6oUSNN1uUDgJs3b2LQoEHK34f8axEELeZ7qlOnDrZs2aL6cV/Gzs4OPXr00DxOcnJytsPq7927B2tra83jq4EJUA7w/OJ/o0aNwsSJE9GhQwelrHnz5ihbtizmzJmDkJAQVWO7uLgYpMf+pEmT9J7fvn0bjx49Uv6ZPXjwQFnsUYsEqG7dutiyZQvKli2LNm3aoF+/fti+fTu2bNmChg0bqh7PGMLCwjBq1ChUqVJF84QEeHarZuXKlQa7hVqmTBlcvHjxldcHU4OhR9bdv38fbdq0Uf24L+Pt7Y1t27Zl+T1u3boV3t7eqsa6efPmS5dksbCwwO3bt1WNmalr166Ii4vDsGHDDPL38bykpKQsX0jU6s6wbt26V95XzfXH6tSpg0WLFmH06NEAng26yMjIwI8//vjK6+kZnbGboEifra2t0nH2eefOnRNbW1sj1Eh9v/76q9SqVUvOnj2rlJ09e1bq1KkjS5Ys0STm3bt35dq1ayIikp6eLuHh4dKsWTMZMGCA3Lt3T7U4FStWVI6XedviRQ+1ubu7y6JFi1Q/7os0aNBA/ve//xks3v/+9z+pUKGC/Pnnn3L9+nVlnpPMhxa6d+8uwcHBkpqaqszLc/nyZalYsaL069dP9XiffPKJzJw5U/XjvszPP/8sVlZW0qtXL1m0aJEsWrRIevbsKdbW1jJr1ixVY/n4+Mgff/zxwu2rVq3SZI4skWe3aY4dO6bJsbNz8eJFadKkidjZ2el1Y1D7FnF2t5+zK1P7tvTff/8tBQoUkMaNG4uVlZW0bt1aSpYsKW5ubsp8ZDkdW4ByGG9vb8ydOxc//vijXvkvv/yi+rcxYxk2bBhWrlyJ4sWLK2XFixfHpEmT0Lp1a9UXX0xLS8Nff/2FwMBAAM8WKdRqoc4WLVoozb+GnkMmNTU1y6K2WurTpw8GDhyI+Pj4bFe7VnsOmSZNmgB49i32+W/vIqLZ4pLZDde+ceMGatasqclwbT8/PwwbNgyRkZHZXlMtWkc///xzuLu7Y8KECcoUCiVLlsTvv/+u+vIQTZo0wbBhw9C4ceMsS0M8fvwYI0aMwIcffqhqzEze3t5ZbntpqVOnThARzJ8/H25ubpq1OD3fsrR161YMHjwYY8eO1etCMXToUIwdO1bVuGXKlMH58+cxffp0ODo6IikpCa1atULv3r01G1iiNq4Gn8Ns2LABH330Efz8/FC9enUAwKFDhxAdHY1Vq1Yp/wTUUrFixWz/MHU6HWxsbODn54euXbuq2qRpZ2eHXbt2oWrVqnrlhw4dQv369TXpk2NnZ4czZ85ouvq7sQ0ePBgODg4YNmyYQeJlt9q1TqfTLCF52eSKf//9N0JDQ1WN97znR9ZVrlxZs9umL7u9p9PpcPHiRVXjpaWlYezYsfjkk09QsGBBVY+dnZs3b6JSpUowNzdHaGio8iXo7NmzmDFjBtLT05UV4dW2efNmTJgwAbNnz9Z8niMAcHBwwNGjR/W+6GmtTJkymDVrFmrXrq1XvmfPHnz22Wc4c+aMweqSGzAByoGuXLmCmTNn6q3N1atXL01agIYMGYKZM2eibNmyqFatGoBnHT9PnjyJrl274p9//sG2bduwevVq1b4NNmvWDNeuXcMvv/yirOF09OhRfPbZZ/Dy8nqte9qvqn79+ujfv7+mCx7+25UrV6DT6ZR/LIcOHcLSpUtRqlQpfPbZZ6rEeH6R14yMDCxcuBDlypVDuXLlsrQeqD1U/L8WPNQ62Xz48CF+++03/PLLLzh69KiqCdeBAwdw9+5dvdaIhQsXYsSIEXj06BGCg4Mxbdq0XNPZ82UcHBxw6tQpgyQFwLP3zeeff45NmzYpLTI6nQ6BgYGYMWOGZn288uTJg0ePHiEtLQ12dnZZ/j4yF4FVS4MGDfDdd99pOg3Fv9na2uLw4cNZptk4efIkqlevjsePH7/V8U+ePPnK+2o1i7iamACZuB49eqBQoUJZWg3GjBmDy5cvY+7cuRgxYgTWr1+PI0eOqBLz9u3bCAkJwcaNG/VWoA8MDERERIQmc3MsX74cQ4YMQf/+/VG5cmXY29vrbdfij7VOnTr47LPP0LlzZ8THx6NYsWIoU6YMoqOj0adPH1XmdHnVljmdTqfJsibGsHv3bsybNw+rVq2Cp6cnWrVqhY8++ihLi+LbCAoKQv369ZXRWH///TcqV66MkJAQlCxZEuPHj0fPnj0xcuRI1WIaS4sWLdCqVSvVB1j8l/v37yMmJgYiAn9/f+TJk0fTeAsXLnzpdrXP/8KFC+jVqxc6deqEMmXKaH6LGHg22MPGxgaLFy9WWtFu3ryJLl264MmTJ2+9RI2ZmZleK2+m5xPZTFrcklYbE6AcaM+ePZg9ezYuXryIFStWwMvLC4sXL0bRokWzNG2+LWdnZxw9ejTLCJCYmBhUrlwZCQkJOHv2LKpWraoMI1fL+fPnlVauEiVKoFixYqoe/3mGvl0DPPvGGRkZieLFi2Pq1Kn4/fffsW/fPmzevBm9evVS/XaGIaxbtw5BQUGwtLT8z5Y6NUecxMfHIyIiAvPmzUNiYiLatm2LWbNm4cSJEyhVqpRqcTJ5eHjgzz//VKYy+O6777Br1y7s3bsXALBixQqMGDEC//zzj+qxr169inXr1mW7ZIsWEz7OmjULYWFh6NixY7ZfDtT8PZqSyMhIfPzxx4iNjVXKtP7MiYmJQcuWLXH+/HnljsGVK1fg7++PNWvWvPWIzedbfY8dO4ZBgwbhq6++0utvNGHCBPz4448G7wP5JtgJOodZtWoVOnfujI4dOyIqKgopKSkAns2SOnbsWGzYsEHVeDY2Nti/f3+WP4z9+/crnRQzMjKydFhUQ7FixTRNep536dIlg8R53tOnT5VbJFu3blX+kZQoUQI3btwweH3UEBwcjPj4eBQoUOClH3BqfsA3a9YMu3fvRtOmTTF58mQ0btwY5ubmmDVrlirHz879+/f1+qHs2rULQUFByvOqVaviypUrqsfdtm0bmjdvDh8fH5w9exZlypRBbGwsRES5Xay2L774AkD2yZVW/6iN7cmTJ1mSS7Vn2f/kk09QsWJF/Pbbb5p2gn6en58fTp48iS1btuh1oQgICFAl/vO3tdu0aYOpU6fq9UstV64cvL29MWzYMCZA9PrGjBmDWbNmoUuXLli2bJlSXqtWLYwZM0b1eH369EGvXr1w9OhR5RbC4cOH8csvvyiToG3atAkVKlRQLaYxVqA3RufnzGn9mzZtii1btijzZVy/fh358uVTPV7Lli3/s0P7xx9//FadMp//Xf3796aV//3vf+jbty8+//xz+Pv7GySmm5sbLl26BG9vb6SmpiIqKgphYWHK9ocPH750Pps3NWTIEAwaNAhhYWFwdHTEqlWrUKBAAXTs2BGNGzdWPR5guN+jsSUnJ2Pw4MFYvnw57t69m2W72one5cuXsW7dOoMvNaTT6dCoUSPUrVsX1tbWmiVef//9d7b9tYoWLapJy6gWst4XIKM6d+5ctmsoOTs748GDB6rHGzp0KObOnYtDhw6hb9++6Nu3Lw4dOoS5c+fiu+++A/Bsxt8///xTtZj9+vVDv379kJ6ejjJlyqB8+fJ6D62cO3cOoaGhaNiwIRo2bIjQ0FCcO3dOs3g//PADZs+ejfr166NDhw7Kua1bt07pcK4mZ2dnbN++HVFRUdDpdNDpdDh27Bi2b9+OtLQ0/P777yhfvjz27dv3VnG2b9+OUqVKZTtBYOZ6Tnv27HmrGM/bu3cvHj58iMqVK6N69eqYPn26Zqu/Z2rSpAm++eYb7NmzB0OGDIGdnZ3e+lQnT56Er6+v6nHPnDmDLl26AHg2KeDjx4/h4OCAUaNGvXQG5Tdh6N+jsX399dfYvn07Zs6cCWtra/zyyy8ICwuDp6enJmu6vf/++zhx4oTqx32ZjIwMjB49Gl5eXnBwcFBavocNG4Z58+apGqtkyZIIDw/Xa0lLTU1FeHi43tpgOZqB5x2i/1C0aFFlVeTn11dZuHChlCxZ0phVU40xVqBfuXKlWFhYSI0aNaR///7Sv39/qVmzplhYWMjKlStVj5eRkSGXL1+WxMTELBMtXrp0SW7evKl6zMGDB8vnn38u6enpSll6erqEhobKkCFDJCMjQz777DOpVavWW8Ux1npOSUlJMm/ePKlVq5ZYWlqKmZmZTJ48WRITE1WPdfv2balTp47odDpxdHSU1atX621///335dtvv1U9rpubm/zzzz8iIlKyZElZu3atiIgcP35c9fWVTG1dLm9vb9mxY4eIiDg6Okp0dLSIiCxatEiCgoJUjzd79mzx9vaWESNGyMqVK2Xt2rV6Dy2EhYWJj4+PLFmyRGxtbZX/H8uWLZMaNWqoGuvgwYNSoEABcXV1lYYNG0rDhg3F1dVVChQoIAcPHlQ1llaYAOUwY8eOlVKlSklkZKQ4OjrKnj17ZMmSJeLq6ipTp041dvVU4eHhIefOnTNoTB8fHxk2bFiW8uHDh4uPj4/q8dLT08XS0jLbWb21kj9//myv67lz5yRfvnwiInLy5ElxdnZ+qziFChVS/kln58yZM+Lt7f1WMf7L2bNn5auvvhJ3d3exsbGRZs2aaRLnwYMHkpaWlqX87t27kpKSonq8Fi1ayJw5c0REZODAgeLn5ydjxoyRSpUqScOGDVWNlRN+j4Zkb28vly9fFhERLy8v5Z/0xYsXNVm889+zMWu5WHAmX19f2bp1q4jof4E+c+aMuLi4qB4vKSlJZs+erXypnDNnjiQlJakeRytMgHKYjIwMGTNmjNjb2yt/LDY2NjJ06FBN4qWlpcn48eOlatWq4ubmJnny5NF7aMEYK9Db2toq3/ied/78ec2WGClVqpQcOHBAk2Nnx8XFJdtvlmvXrlU+/M6fP//WH4TW1tbZXstM0dHRYmNj81YxXlVaWpr88ccfmiVAhnbhwgU5ceKEiDz759KzZ08pW7astGrVSmJjY1WNlZN+j4ZQtmxZ2blzp4iINGzYUAYOHCgiz1q6vLy8jFk11djY2Cjvk+cToNOnT+eaFdoNiQlQDpWSkiKnT5+WgwcPysOHDzWLM2zYMPHw8JCffvpJbGxsZPTo0dK9e3fJly+fTJkyRZOYwcHB4uzsLEWLFpUPP/xQWrZsqffQQlBQkMyfPz9L+fz586VRo0aaxFy3bp3Url1b/v77b02O/299+vSR/Pnzy8SJE2XPnj2yZ88emThxouTPn1/69u0rIiJz585961tgxlzPidRjar/HiRMnKp9pW7ZsERsbG7G2tlZupb4LKlWqJIsXLxYR/QQoLCxMateurXq8RYsWSa1atcTDw0NJvCZOnChr1qxRPZYWOA9QDrNkyRK0atUKdnZ2Bonn6+uLqVOnomnTpnB0dMTx48eVssjISCxdulT1mN26dXvp9gULFqgS5/l5aq5fv47hw4ejbdu2qFGjBoBn83SsWLECYWFh6NWrlyoxn/f8zLNWVlawtbXV2672zLPp6ekYN24cpk+fjps3bwJ4NpqpT58+GDx4MMzNzREXFwczM7O3WvagT58+2LlzJw4fPpztek7VqlVDgwYNMHXq1Lc6H1N25MgRZdmCUqVKoXLlyqrHMPXf4+XLl5U50LSYlHDUqFEv3a7GRKj/tnbtWoSEhGDIkCEYNWoUwsLCcO7cOSxatAh//fUXPvjgA9VizZw5E8OHD8eXX36JMWPG4PTp0/Dx8UFERAQWLlyIHTt2qBZLK0yAchhXV1c8fvwYzZs3R6dOnRAYGAhzc3PN4tnb2+PMmTMoVKgQPDw8sH79elSqVAkXL15ExYoVkZCQoFlsrWU3+WF2tJrrxNAzzz4vc2SP2nObAMZdz+ldd/XqVXTo0AH79u2Di4sLAODBgwd47733sGzZMlXX6zKl32NGRgYiIiKwevVqxMbGQqfToWjRomjdujU6d+6syVDxihUr6j1/+vQpLl26BAsLC/j6+iIqKkr1mMCziXRHjRqFEydOICkpCZUqVcLw4cPRqFEjVeOUKlUKY8eORXBwMBwdHXHixAn4+Pjg1KlTqF+/vuYjNVVh3AYo+renT5/Kn3/+KR9//LHY29uLq6urfPHFF7Jv3z5N4hUrVkwiIyNFRKRWrVoSHh4uIs9GDbi6umoSk7R169Yt5RbY7du3NYkRGxsrQUFBYmZmptexMygoSC5evKhJTFMQGBgo1atXl7NnzyplZ8+elZo1a0pgYKDq8Uzh95iRkSFNmzYVnU4nFSpUkPbt20u7du2kXLlyotPppEWLFgarS0JCgrRs2VIWLVpksJhaeVF/o/Pnz+eavmNMgHKw5ORkWbJkiTRp0kSsrKw0Ga00ePBg+f7770XkWdJjYWEhfn5+YmVlJYMHD1Y9XqYVK1ZImzZtpHr16lKxYkW9h5qCgoLkwYMHyvPw8HC5f/++8vzOnTuaTi8QExMj3333nbRv314Z+r5hwwY5deqU6rGSkpKkW7duYm5urvwzs7CwkE8++USSk5NVjycicu/ePTl06JAcPHgwy3B/en02NjYSFRWVpfzIkSOaddYXebd/j/PnzxdHR0fZvn17lm3btm0TR0dHWbhwocHqc/LkSSlcuLAmxz506JDyhfZ5kZGRcvjwYVVjlSxZUunr83wCNHXqVNU/x7XCBCiHu337tkybNk1Kly6t2dDJ5+3fv18mTJgg69at0yzGlClTxMHBQUJDQ8XKykp69uwpAQEB4uzsrPrcKjqdTm/OHUdHR+UPVUQkPj5es+u6c+dOsbW1lYCAALGyslLihoeHy0cffaR6vM8++0x8fHxkw4YNkpCQIAkJCbJ+/Xrx9fWVXr16qR6P1Ofv75/tHCoHDx4UX19fI9Qo9/vggw+Ulu3sfP/995oNhMjOnj17NBmSLiJStWpVWbFiRZbyVatWSbVq1VSJERYWJsnJyTJ37lzx8vKSZcuWib29vfz222/KCObffvtNlVhaYwKUA2W2/AQFBYmVlZX4+vrK0KFD5cyZM8aumiqKFy8uS5cuFRH9bw7Dhg2T3r17qxrr3wnQ8/FEtE2AatSoIRMmTMgS9+DBg5oMu82XL58y0dvztm/fLvnz51c9HqlvzZo1Uq1aNb1v64cPH5YaNWq8dMQWvZibm5scO3bshdujoqLEzc1N9bhTpkzRe0yePFkGDx4snp6e0r59e9XjiTyb6+j5z7dMFy9eFAcHB1VimJmZKZ+pS5YsET8/P6XF2cvLS3755RdV4hgC1wLLYdq3b4+//voLdnZ2aNu2LYYNG6astKuVc+fOYdq0acqok5IlS6JPnz5vtWbUy8TFxeG9994DANja2iqrzHfu3Bk1atTA9OnTNYlraH///Xe2o+gKFCigSQfBR48eZdthtUCBAnj06JHq8UgdefLk0euEm5ycjOrVq8PC4tnHc1paGiwsLPDJJ5/kigUmc5p79+69tCO3m5sb7t+/r3rcSZMm6T03MzODq6urMkpLC9bW1rh58yZ8fHz0ym/cuKG8n96WPDduqmPHjujYsSMePXqEpKQkFChQQJUYhsIEKIcxNzfH8uXLNR/9lWnVqlVo3749qlSpoiRakZGRKFOmDJYtW4aPPvpI9Zju7u64d+8eChcujEKFCiEyMhLly5fHpUuX9P641JC5Jta/ywzBxcUFN27cyLJg4LFjx+Dl5aV6vJo1a2LEiBFYtGiRMqz58ePHCAsL0zyJpjc3efJkY1fhnZaenv7Sf/7m5uZIS0tTPW7mOlzPe/LkCWbMmAF/f3/Ex8erHrNRo0YYMmQI1q5dC2dnZwDPRhF+++23qg6B//dnqJ2dncGmblETE6Ac4sCBA7h79y5+/fVXpWzRokUYMWIEkpOTERwcjGnTpsHa2lrVuF9//bUyZ8TzRowYga+//lqTBOj999/HunXrULFiRXTr1g39+/fHypUrceTIEbRq1UrVWCKCrl27KtftyZMn6NWrF+zt7QEAKSkpqsZ7Xvv27TF48GCsWLECOp0OGRkZ2LdvHwYNGqQseKmmyZMno3HjxihYsKCy8OqJEydgY2ODTZs2qR6P1KHldAiU9TPg39T+DEhJScHIkSOxZcsWWFtb46uvvkJwcDAWLFiAoUOHwtzcHP3791c1ZqaffvoJdevWReHChZVh+MePH4ebmxsWL16sWpxixYr95xdJtec50wLnAcohgoKCUL9+fQwePBjAs9snlSpVQteuXVGyZEmMHz8ePXv2xMiRI1WNa2dnh5MnT8LPz0+vPDo6GuXLl9fk1klGRgYyMjKUb2XLli3D/v374e/vj549e8LKykq1WP816WImtSZffF5qaipCQ0MRERGh3MZIT0/Hxx9/jIiICE1a+B49eoRff/0VZ8+eBfDsdmbHjh2zTMJIOUd2q7G/iBbzOr3rDP0ZMHjwYMyePRsBAQHYv38/bt++jW7duiEyMhLffvst2rRpo2nrfnJyMn799VecOHECtra2KFeuHDp06ABLS0tVjm9mZobJkycrLUwvkhsSeyZAOYSHhwf+/PNPVKlSBQDw3XffYdeuXdi7dy8AYMWKFRgxYgT++ecfVeM2adIEbdq0yfIhsWDBAixbtowtB28gIyMD48ePx7p165Camopy5crho48+QlJSEipWrAh/f39N4u7evRvvvfdelub+tLQ07N+/H3Xr1tUkLr0dMzOz//w2LSKaTdhJ6vLx8cHkyZPRvHlznDp1CuXKlUPXrl0xb948g91+15KZmRni4+NzXX+f7PAWWA5x//59vY56u3btQlBQkPK8atWquHLliupxmzdvjsGDB+Po0aPZLhHx/HISzZs3f+M4J0+efOV9tZiW3pC+//57jBw5EgEBAbC1tcXSpUshIpg/f76mcRs0aIAbN25k+WBKSEhAgwYN+M8zh3rVJQP+/vtvjWtCarh69aqydEmZMmVgbW2N/v37GzT5+eeffxAXF4fU1FS98rf5DM/0LiRxCmMNPyN9hQoVkl27donIs4VQbW1tZevWrcr2kydParI6e+bwxf96vO1Q8cxjaB0nJ/Dz85NZs2Ypz7ds2SJWVlaSnp6uaVydTie3bt3KUn7u3DlxdHTUNDZpIzExUWbPni1Vq1Z9J/42TIGZmZne36GDg4PBZtW+cOGCMsP1v2f3Vuv98++pRXIztgDlEE2aNME333yDH374AWvWrIGdnR3q1KmjbD958iR8fX1Vj5uRkaH6MbOT3YiId1VcXByaNGmiPA8ICIBOp8P169dVXcspU2bHcZ1Ol6WzZ3p6Ok6ePKlMO0C5w+7duzFv3jysWrUKnp6eaNWqFWbMmGHsatErkP8YeJFp9erVqsfu168fihYtim3btqFo0aI4dOgQ7t69i4EDB+Knn35SJYah/mcYAhOgHGL06NFo1aoV6tWrBwcHByxcuFCvM/D8+fNVXcwuc9TZhx9+qJRpOeqscOHCqhwnN0hLS8uyuralpSWePn2qSbzMzogiAkdHR70Oz1ZWVqhRowZ69OihSWxST3x8PCIiIjBv3jwkJiaibdu2SElJwZo1a1CqVCljV49e0b87/3bq1MlgsQ8cOIDt27cjf/78MDMzg5mZGWrXro3w8HD07dsXx44dM1hdcgN2gs5hEhIS4ODgkGWUwL179+Dg4KDaCCljjTrLFB0djR07duDWrVtZvlEMHz5ck5iGYmZmhqCgIL3k8c8//8T777+v9y1QzW+AIoJPPvkE06ZNg4ODg2rHJcNo1qwZdu/ejaZNm6Jjx45o3LgxzM3NYWlpiRMnTjABoleSJ08eREVFoWjRovD19cUvv/yCBg0a4MKFCyhbtiwnRP0XJkAmylijzgBg7ty5+Pzzz5E/f364u7vrdarT6XSIiopSPaYhGWPofUZGBmxsbHD69GnNRpmRdiwsLNC3b198/vnner8/JkD0OurUqYOBAwciODgYH3/8Me7fv4+hQ4dizpw5OHr0KE6dOmXsKuYovAVmoow16gwAxowZg++//15pfXrXaDGn0H8xMzODv78/7t69ywQoF9q7dy/mzZuHypUro2TJkujcuTPat29v7GpRLjN06FAkJycDAMLCwtCsWTPUqVMH+fLlw7Jly4xcu5zHzNgVIONwc3NTOianpqYiKipKGQYPAA8fPlRt4qx/u3//Ptq0aaPJsU3ZuHHj8NVXX/FbXi5Uo0YNzJ07Fzdu3EDPnj2xbNkyeHp6IiMjA1u2bFHWyyN6mcDAQGVQhL+/P86ePYs7d+7g1q1baNiwoZFrl/PwFpiJ+vzzz3HixAll1NnChQtx/fp1pY/Rr7/+ismTJ+Pw4cOqx+7evTuqVq2KXr16qX5sU5YnTx48evQIaWlpsLKyyjL7c26Ymp7+37lz5zBv3jwsXrwYDx48wAcffKA3LxdRpk8++eSV9tN6LrLchrfATJShR509z8/PD8OGDUNkZCTKli2bpaWpb9++msR913FRzXdL8eLF8eOPPyI8PBx//vkn/3nRC0VERCjrf7FN49WxBcjEGWrU2fP+vTr683Q6HS5evKh6TCKid1Xv3r3x22+/oXDhwujWrRs6deqEvHnzGrtaOR4TIKJ3SHp6OtasWYMzZ84AAEqXLo3mzZtruvgiERlfSkoKVq9ejfnz52P//v1o2rQpunfvjkaNGr1by1eoiAkQ0TsiJiYGTZo0wbVr11C8eHEAz/qReHt7Y/369ZrMJE5EOc/ly5cRERGBRYsWIS0tDadPn+b8YNlgHyAyiAEDBmD06NGwt7fHgAEDXrrvxIkTDVSrd0vfvn3h6+uLyMhIpfn77t276NSpE/r27Yv169cbuYZEZAhmZmbQ6XQQES6C/BJMgMggjh07hrNnz6JixYovnY6dTbVvbteuXXrJDwDky5cP48aNQ61atYxYMyLS2vO3wPbu3YsPP/wQ06dPR+PGjWFmxhlvssMEiAxix44dMDc3x40bN7Bjxw4AQLt27TB16lS9CRnpzVlbW2c7X0xSUpImndmJKGf44osvsGzZMnh7e+OTTz7Bb7/9hvz58xu7Wjke+wCRwZiZmSE+Ph4FChQAADg5OeH48ePw8fExcs3eDV26dEFUVBTmzZuHatWqAQAOHjyIHj16oHLlyoiIiDBuBYlIE2ZmZihUqBAqVqz40lZ0LVagz83YAkRGw9xbXVOnTkXXrl3x3nvvwcLi2Z92WloamjdvjilTphi5dkSklS5durD7wBtgCxAZjLm5OeLj4+Hq6goAcHR0xMmTJ186LxD9t4yMDIwfPx7r1q1DamoqChUqhJCQEOh0OpQsWRJ+fn7GriIRUY7DFiAyGBFB165dYW1tDQB48uQJevXqBXt7e7392Ez7er7//nuMHDkSAQEBsLW1xYYNG+Ds7MyZg4mIXoItQGQw3bp1e6X9jLGaem7m7++PQYMGoWfPngCArVu3omnTpnj8+DFHfxARvQATIKJcztraGjExMfD29lbKbGxsEBMTg4IFCxqxZkREORe/HhLlcmlpabCxsdErs7S0xNOnT41UIyKinI99gIhyuX/3rQKy71/FvlVERP+PCRBRLhcSEpKlrFOnTkaoCRFR7sE+QERERGRy2AeIiIiITA4TICIiIjI5TICIiIjI5DABIiIiIpPDBIiINNW1a1cEBwcbuxpERHqYABEREZHJYQJEREYzceJElC1bFvb29vD29sYXX3yBpKQkZXtERARcXFywadMmlCxZEg4ODmjcuDFu3Lih7JOWloa+ffvCxcUF+fLlw+DBgxESEqLX6lSkSBFMnjxZL3aFChUwcuTIV64LAMydOxfe3t6ws7NDy5YtMXHiRLi4uOjts3btWlSqVAk2Njbw8fFBWFgY0tLSADybtHLkyJEoVKgQrK2t4enpib59+77dRSSiN8IEiIiMxszMDFOnTsXp06excOFCbN++HV9//bXePo8ePcJPP/2ExYsXY/fu3YiLi8OgQYOU7T/88AN+/fVXLFiwAPv27UNiYiLWrFmjel327duHXr16oV+/fjh+/Dg++OADfP/993rH2LNnD7p06YJ+/frhn3/+wezZsxEREaHst2rVKkyaNAmzZ89GdHQ01qxZg7Jly752XYlIBUJEpKGQkBBp0aLFK+27YsUKyZcvn/J8wYIFAkBiYmKUshkzZoibm5vy3M3NTcaPH688T0tLk0KFCunFLFy4sEyaNEkvVvny5WXEiBGvXJd27dpJ06ZN9fbp2LGjODs7K88bNmwoY8eO1dtn8eLF4uHhISIiEyZMkGLFiklqauoL4xKRYbAFiIiMZuvWrWjYsCG8vLzg6OiIzp074+7du3j06JGyj52dHXx9fZXnHh4euHXrFgAgISEBN2/eRLVq1ZTt5ubmqFy5sup1OXfunF4cAFmenzhxAqNGjYKDg4Py6NGjB27cuIFHjx6hTZs2ePz4MXx8fNCjRw/88ccfyu0xIjIsJkBEZBSxsbH48MMPUa5cOaxatQpHjx7FjBkzAACpqanKfpaWlnqv0+l0kNdcwcfMzCzLa54+ffradfkvSUlJCAsLw/Hjx5XH33//jejoaNjY2MDb2xvnzp3Dzz//DFtbW3zxxReoW7euXl2IyDC4GCoRGcXRo0eRkZGBCRMmwMzs2Xex5cuXv9YxnJ2d4ebmhsOHD6Nu3boAgPT0dERFRaFChQrKfq6urnodpxMTE3Hp0qXXqkvx4sVx+PBhvbJ/P69UqRLOnTsHPz+/F9bZ1tYWzZo1Q7NmzdC7d2+UKFECf//9NypVqvRa505Eb4cJEBFpLiEhAcePH9cry58/P54+fYpp06ahWbNm2LdvH2bNmvXax+7Tpw/Cw8Ph5+eHEiVKYNq0abh//z50Op2yz/vvv4+IiAg0a9YMLi4uGD58OMzNzZXtfn5+/1mXPn36oG7dupg4cSKaNWuG7du343//+59enOHDh+PDDz9EoUKF0Lp1a5iZmeHEiRM4deoUxowZg4iICKSnp6N69eqws7PDkiVLYGtri8KFC7/2eRPRWzJ2JyQiereFhIQIgCyP7t27y8SJE8XDw0NsbW0lMDBQFi1aJADk/v37IvKsE/TznYxFRP744w95/qPr6dOnEhoaKk5OTpInTx4ZPHiwtGnTRtq3b6/sk5CQIO3atRMnJyfx9vaWiIiILJ2g/6suIiJz5swRLy8vsbW1leDgYBkzZoy4u7vr1W/jxo3y3nvvia2trTg5OUm1atVkzpw5St2rV68uTk5OYm9vLzVq1JCtW7eqc6GJ6LXoRF7zZjoRUQ6WkZGBkiVLom3bthg9erSmsXr06IGzZ89iz549msYhIvXxFhgR5WqXL1/G5s2bUa9ePaSkpGD69Om4dOkSPv74Y9Vj/fTTT/jggw9gb2+P//3vf1i4cCF+/vln1eMQkfaYABFRrmZmZoaIiAgMGjQIIoIyZcpg69atKFmypOqxDh06hB9//BEPHz6Ej48Ppk6dik8//VT1OESkPd4CIyIiIpPDeYCIiIjI5DABIiIiIpPDBIiIiIhMDhMgIiIiMjlMgIiIiMjkMAEiIiIik8MEiIiIiEwOEyAiIiIyOUyAiIiIyOT8H2KbmcQ0SPTUAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "results_df_gender_total = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_gender,columns,'total')\n",
        "sums_gender = results_df_gender_total.iloc[:, first_language_index:].sum()\n",
        "f.plot_series(sums_gender,'Removed Languages','Languages')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "OorlExoEWjG3"
      },
      "outputs": [],
      "source": [
        "job_df_orig_gender, job_df_repaired_gender = f.compute_repaired_df(df_mitigation,7,protected_attribute_gender)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "Xub0KcF8W8ef"
      },
      "outputs": [],
      "source": [
        "with open('utils/encodings/direct_matching_20240213_cand_domicile_region_encoding.json', 'r') as file:\n",
        "    region_mapping = json.load(file)\n",
        "with open('utils/encodings/direct_matching_20240213_provinces_encoding.json', 'r') as file:\n",
        "    province_mapping = json.load(file)\n",
        "\n",
        "reversed_region_mapping = {v: k for k, v in region_mapping.items()}\n",
        "reversed_province_mapping = {v: k for k, v in province_mapping.items()}\n",
        "\n",
        "job_df_orig_gender['cand_domicile_region_str'] = job_df_orig_gender['cand_domicile_region'].map(reversed_region_mapping)\n",
        "job_df_repaired_gender['cand_domicile_region_str'] = job_df_repaired_gender['cand_domicile_region'].map(reversed_region_mapping)\n",
        "\n",
        "job_df_orig_gender['cand_domicile_province_str'] = job_df_orig_gender['cand_domicile_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_gender['cand_domicile_province_str'] = job_df_repaired_gender['cand_domicile_province'].map(reversed_province_mapping)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "IratwkMfQtAo",
        "outputId": "6f179371-d389-47c3-8101-5b27caca42a2"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_gender['cand_domicile_region_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_gender['cand_domicile_region_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Regions','Regions')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eB5zzbtBs8Xz"
      },
      "source": [
        "## Age"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "BgUWlBJjtAjE",
        "outputId": "1c3d4fb0-4743-4b87-c697-32049e1a764e"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cand_gender</th>\n",
              "      <th>cand_age_bucket</th>\n",
              "      <th>cand_domicile_province</th>\n",
              "      <th>cand_domicile_region</th>\n",
              "      <th>job_contract_type</th>\n",
              "      <th>job_work_province</th>\n",
              "      <th>Svedese</th>\n",
              "      <th>Spagnolo</th>\n",
              "      <th>Finlandese</th>\n",
              "      <th>Ebraico</th>\n",
              "      <th>...</th>\n",
              "      <th>Cinese</th>\n",
              "      <th>Arabo</th>\n",
              "      <th>Serbo</th>\n",
              "      <th>Albanese</th>\n",
              "      <th>Croato</th>\n",
              "      <th>Ceco</th>\n",
              "      <th>Danese</th>\n",
              "      <th>Rumeno</th>\n",
              "      <th>Macedone</th>\n",
              "      <th>Tedesco</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>69.08</td>\n",
              "      <td>7.69</td>\n",
              "      <td>0.0</td>\n",
              "      <td>12.62</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>1.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>76.00</td>\n",
              "      <td>26.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>5.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>8.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>75.91</td>\n",
              "      <td>33.76</td>\n",
              "      <td>0.0</td>\n",
              "      <td>61.31</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.36</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.18</td>\n",
              "      <td>1.82</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>82.75</td>\n",
              "      <td>66.75</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.75</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>57.76</td>\n",
              "      <td>56.71</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14.08</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.64</td>\n",
              "      <td>18.49</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.81</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.79</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.51</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.96</td>\n",
              "      <td>31.48</td>\n",
              "      <td>0.0</td>\n",
              "      <td>44.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>5.19</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.74</td>\n",
              "      <td>0.74</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>57.27</td>\n",
              "      <td>12.10</td>\n",
              "      <td>0.0</td>\n",
              "      <td>35.41</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.21</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>61.56</td>\n",
              "      <td>14.21</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.21</td>\n",
              "      <td>0.16</td>\n",
              "      <td>2.25</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.72</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>41.48</td>\n",
              "      <td>58.89</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.33</td>\n",
              "      <td>0.00</td>\n",
              "      <td>4.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>5.93</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.48</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>15.93</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 22 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   cand_gender  cand_age_bucket  cand_domicile_province  cand_domicile_region  \\\n",
              "0          0.0              0.0                   69.08                  7.69   \n",
              "1          0.0              0.0                   76.00                 26.00   \n",
              "2          0.0              0.0                   75.91                 33.76   \n",
              "3          0.0              0.0                   82.75                 66.75   \n",
              "4          0.0              0.0                   57.76                 56.71   \n",
              "5          0.0              0.0                   47.64                 18.49   \n",
              "6          0.0              0.0                   52.96                 31.48   \n",
              "7          0.0              0.0                   57.27                 12.10   \n",
              "8          0.0              0.0                   61.56                 14.21   \n",
              "9          0.0              0.0                   41.48                 58.89   \n",
              "\n",
              "   job_contract_type  job_work_province  Svedese  Spagnolo  Finlandese  \\\n",
              "0                0.0              12.62     0.00      0.00        0.00   \n",
              "1                0.0              30.00     0.00      5.00        0.00   \n",
              "2                0.0              61.31     0.00      0.00        0.00   \n",
              "3                0.0              32.75     0.75      0.00        0.00   \n",
              "4                0.0              14.08     0.26      0.00        0.00   \n",
              "5                0.0              21.81     0.00      0.00        0.00   \n",
              "6                0.0              44.07     0.00      0.00        0.00   \n",
              "7                0.0              35.41     0.07      0.00        0.07   \n",
              "8                0.0              29.21     0.16      2.25        0.08   \n",
              "9                0.0              23.33     0.00      4.07        0.00   \n",
              "\n",
              "   Ebraico  ...  Cinese  Arabo  Serbo  Albanese  Croato  Ceco  Danese  Rumeno  \\\n",
              "0     0.00  ...    0.00   0.92    0.0      0.00    0.15  0.00    0.00    0.00   \n",
              "1     8.00  ...    0.00   0.00    0.0      0.00    2.00  0.00    0.00    0.00   \n",
              "2     0.00  ...    0.18   0.36    0.0      0.18    1.82  0.00    0.00    0.00   \n",
              "3     0.00  ...    0.50   0.25    0.0      0.00    0.00  0.00    0.25    0.00   \n",
              "4     0.00  ...    0.00   0.39    0.0      0.26    0.53  0.00    0.00    0.00   \n",
              "5     0.00  ...    0.00   1.79    0.0      0.32    0.51  0.00    0.00    0.00   \n",
              "6     5.19  ...    0.00   0.37    0.0      0.74    0.74  0.00    0.00    0.00   \n",
              "7     0.00  ...    0.00   0.00    0.0      0.21    0.00  0.04    0.00    0.00   \n",
              "8     0.00  ...    0.00   0.72    0.0      0.32    0.00  0.00    0.00    0.00   \n",
              "9     5.93  ...    0.00   0.37    0.0      0.00    1.48  0.00    0.00   15.93   \n",
              "\n",
              "   Macedone  Tedesco  \n",
              "0      0.15     1.23  \n",
              "1      0.00     2.00  \n",
              "2      0.00     3.10  \n",
              "3      0.00     2.75  \n",
              "4      0.13     0.66  \n",
              "5      0.00     0.00  \n",
              "6      0.00     1.48  \n",
              "7      0.07     0.28  \n",
              "8      0.00     0.56  \n",
              "9      0.00     1.11  \n",
              "\n",
              "[10 rows x 22 columns]"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "protected_attribute_age = \"cand_age_bucket\"\n",
        "\n",
        "results_df_age = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_age,columns)\n",
        "results_df_age.to_excel('Results/Mitigation_direct/results_df_age_direct.xlsx', index=False)\n",
        "results_df_age"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 536
        },
        "id": "uUG1W3FnN8dP",
        "outputId": "734bccd7-be64-4ab0-c9ca-5a034ee06cda"
      },
      "outputs": [
        {
          "data": {
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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "results_df_age_total = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_age,columns,'total')\n",
        "sums_age = results_df_age_total.iloc[:, first_language_index:].sum()\n",
        "f.plot_series(sums_age,'Removed Languages','Languages')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "OxsxSWl5Z91P"
      },
      "outputs": [],
      "source": [
        "job_df_orig_age, job_df_repaired_age = f.compute_repaired_df(df_mitigation,3,protected_attribute_age)\n",
        "job_df_orig_age['job_work_province_str'] = job_df_orig_age['job_work_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_age['job_work_province_str'] = job_df_repaired_age['job_work_province'].map(reversed_province_mapping)\n",
        "\n",
        "job_df_orig_age['cand_domicile_region_str'] = job_df_orig_age['cand_domicile_region'].map(reversed_region_mapping)\n",
        "job_df_repaired_age['cand_domicile_region_str'] = job_df_repaired_age['cand_domicile_region'].map(reversed_region_mapping)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "id": "o475bCyhazgP",
        "outputId": "fa7d4ab7-404e-4606-88c8-c54f0267b58d"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_age['job_work_province_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_age['job_work_province_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Job Provinces','Provinces')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "-NxGUU1IbZQf",
        "outputId": "70b3c289-0ea7-4dcd-f102-d46bd4a392c0"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_age['cand_domicile_region_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_age['cand_domicile_region_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Regions','Regions')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qnIq7H2qN-q3"
      },
      "source": [
        "## Location"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "MmvkAlsutLk8",
        "outputId": "77140198-a3c1-49b8-8a68-58aa8fa420ad"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cand_gender</th>\n",
              "      <th>cand_age_bucket</th>\n",
              "      <th>cand_domicile_province</th>\n",
              "      <th>cand_domicile_region</th>\n",
              "      <th>job_contract_type</th>\n",
              "      <th>job_work_province</th>\n",
              "      <th>Svedese</th>\n",
              "      <th>Spagnolo</th>\n",
              "      <th>Finlandese</th>\n",
              "      <th>Ebraico</th>\n",
              "      <th>...</th>\n",
              "      <th>Arabo</th>\n",
              "      <th>Serbo</th>\n",
              "      <th>Albanese</th>\n",
              "      <th>Croato</th>\n",
              "      <th>Ceco</th>\n",
              "      <th>Danese</th>\n",
              "      <th>Rumeno</th>\n",
              "      <th>Macedone</th>\n",
              "      <th>Tedesco</th>\n",
              "      <th>same_location</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>63.38</td>\n",
              "      <td>32.77</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>64.00</td>\n",
              "      <td>57.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>65.15</td>\n",
              "      <td>6.20</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>79.00</td>\n",
              "      <td>50.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>24.75</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>54.87</td>\n",
              "      <td>64.87</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.16</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>72.39</td>\n",
              "      <td>2.10</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>66.30</td>\n",
              "      <td>44.81</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.74</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.74</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>53.94</td>\n",
              "      <td>46.16</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.69</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>73.43</td>\n",
              "      <td>12.36</td>\n",
              "      <td>0.0</td>\n",
              "      <td>18.46</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>57.04</td>\n",
              "      <td>47.04</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 23 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   cand_gender  cand_age_bucket  cand_domicile_province  cand_domicile_region  \\\n",
              "0          0.0              0.0                   63.38                 32.77   \n",
              "1          0.0              0.0                   64.00                 57.00   \n",
              "2          0.0              0.0                   65.15                  6.20   \n",
              "3          0.0              0.0                   79.00                 50.25   \n",
              "4          0.0              0.0                   54.87                 64.87   \n",
              "5          0.0              0.0                   72.39                  2.10   \n",
              "6          0.0              0.0                   66.30                 44.81   \n",
              "7          0.0              0.0                   53.94                 46.16   \n",
              "8          0.0              0.0                   73.43                 12.36   \n",
              "9          0.0              0.0                   57.04                 47.04   \n",
              "\n",
              "   job_contract_type  job_work_province  Svedese  Spagnolo  Finlandese  \\\n",
              "0                0.0               0.00     0.00       0.0        0.00   \n",
              "1                0.0               0.00     0.00       0.0        0.00   \n",
              "2                0.0               2.01     0.00       0.0        0.00   \n",
              "3                0.0              24.75     0.75       0.0        0.00   \n",
              "4                0.0              23.16     0.26       0.0        0.00   \n",
              "5                0.0               0.00     0.00       0.0        0.00   \n",
              "6                0.0              10.74     0.00       0.0        0.00   \n",
              "7                0.0              28.69     0.07       0.0        0.07   \n",
              "8                0.0              18.46     0.16       0.0        0.08   \n",
              "9                0.0               0.00     0.00       0.0        0.00   \n",
              "\n",
              "   Ebraico  ...  Arabo  Serbo  Albanese  Croato  Ceco  Danese  Rumeno  \\\n",
              "0      0.0  ...   0.00    0.0      0.00    0.15  0.00    0.00     0.0   \n",
              "1      0.0  ...   0.00    0.0      0.00    2.00  0.00    0.00     0.0   \n",
              "2      0.0  ...   0.00    0.0      0.18    0.00  0.00    0.00     0.0   \n",
              "3      0.0  ...   0.25    0.0      0.00    0.00  0.00    0.25     0.0   \n",
              "4      0.0  ...   0.00    0.0      0.26    0.00  0.00    0.00     0.0   \n",
              "5      0.0  ...   0.00    0.0      0.00    0.00  0.00    0.00     0.0   \n",
              "6      0.0  ...   0.37    0.0      0.00    0.74  0.00    0.00     0.0   \n",
              "7      0.0  ...   0.00    0.0      0.00    0.00  0.04    0.00     0.0   \n",
              "8      0.0  ...   0.00    0.0      0.32    0.00  0.00    0.00     0.0   \n",
              "9      0.0  ...   0.37    0.0      0.00    0.00  0.00    0.00     0.0   \n",
              "\n",
              "   Macedone  Tedesco  same_location  \n",
              "0      0.15     0.00            0.0  \n",
              "1      0.00     2.00            0.0  \n",
              "2      0.00     0.00            0.0  \n",
              "3      0.00     0.00            0.0  \n",
              "4      0.13     0.66            0.0  \n",
              "5      0.00     0.00            0.0  \n",
              "6      0.00     0.00            0.0  \n",
              "7      0.00     0.00            0.0  \n",
              "8      0.00     0.00            0.0  \n",
              "9      0.00     0.00            0.0  \n",
              "\n",
              "[10 rows x 23 columns]"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "protected_attribute_location = \"same_location\"\n",
        "results_df_location = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_location,columns)\n",
        "results_df_location.to_excel('Results/Mitigation_direct/results_df_location_direct.xlsx', index=False)\n",
        "results_df_location"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 536
        },
        "id": "oWe_xuL-OO7v",
        "outputId": "80fec0eb-8834-4594-d9c1-1eccc7029228"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "results_df_location_total = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_location,columns,'total')\n",
        "sums_location = results_df_location_total.iloc[:, first_language_index:-1].sum() #-1 since we add another column for location bias\n",
        "f.plot_series(sums_location,'Removed Languages','Languages')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "m2dOPf5ZcAxH"
      },
      "outputs": [],
      "source": [
        "job_df_orig_location, job_df_repaired_location = f.compute_repaired_df(df_mitigation,4,protected_attribute_location)\n",
        "job_df_orig_location['job_work_province_str'] = job_df_orig_location['job_work_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_location['job_work_province_str'] = job_df_repaired_location['job_work_province'].map(reversed_province_mapping)\n",
        "\n",
        "job_df_orig_location['cand_domicile_province_str'] = job_df_orig_location['cand_domicile_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_location['cand_domicile_province_str'] = job_df_repaired_location['cand_domicile_province'].map(reversed_province_mapping)\n",
        "\n",
        "job_df_orig_location['cand_domicile_region_str'] = job_df_orig_location['cand_domicile_region'].map(reversed_region_mapping)\n",
        "job_df_repaired_location['cand_domicile_region_str'] = job_df_repaired_location['cand_domicile_region'].map(reversed_region_mapping)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 678
        },
        "id": "eKFDq1NMcd7O",
        "outputId": "4102c6ba-fa8f-4e5a-a7e5-303476c49a80"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_location['job_work_province_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_location['job_work_province_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Job Provinces','Provinces',size=(12,8))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 678
        },
        "id": "A9SVUF70c24Y",
        "outputId": "eca959de-5009-4ece-b1b2-e2a05aac9feb"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_location['cand_domicile_province_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_location['cand_domicile_province_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Domicile Provinces','Provinces',size=(12,8))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "3F73KM3_c4S_",
        "outputId": "24e70a54-8f64-4ac9-a834-511a88d022fa"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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jRuPGjY3MmTMbefPmNYYOHZrk8lDDMIxp06YZJUqUMDw9PY3SpUsbYWFhjss+7/fZ/12XeFlsbGysMWDAAKNSpUpGtmzZjCxZshiVKlVKds6MOXPmGFWqVDE8PT2NnDlzGsHBwcY///yTZJvEfbldchnvZsKECUbp0qUNd3d3I2/evEbPnj2TzPXx3/d7kMtik9s2Ojra8PX1NerUqeNY9scffxitW7c2cuXKZXh6ehpFihQx2rVrZ6xevTrJa1evXm1UqVLF8PDwMIoVK2Z8/fXXxhtvvGF4eXkl2e72y2INwzCOHDlitG3b1siePbvh5eVl1KxZ8465VBIvi739ctfEP0NhYWGGYRjG0aNHje7duxvFihUzvLy8jJw5cxr16tUzVq1add+vDfAgbIbxEKPPAKQZXbt21fz585M9jI/0pVWrVtq3b98dY38AV8AYDgCwwO13Fj58+LCWLl2qunXrWhMIMBljOADAAkWLFlXXrl0dc4RMnjxZHh4eeuutt6yOBpiCwgEAFmjatKlmz56tiIgIeXp6KigoSCNGjFCJEiWsjgaYgjEcAADAdIzhAAAApqNwAAAA0zGGQ7emhT59+rSyZcuW4ntfAACAWzMbX7p0Sfnz57/nxHMUDkmnT5++466cAAAg5U6ePKmCBQvedT2FQ1K2bNkk3fpiJd6GHAAA3F9MTIwKFSrk+Fl6NxQO/d8txH18fCgcAAA8hPsNSWDQKAAAMB2FAwAAmI7CAQAATMcYDgCAU928eVM3btywOgZSyN3dXW5ubo/8PhQOAIBTGIahiIgIRUVFWR0FDyh79uzy9/d/pLmqKBwAAKdILBt58uRR5syZmWgxHTAMQ1evXlVkZKQkKV++fA/9XhQOAIDpbt686SgbuXLlsjoOHoC3t7ckKTIyUnny5Hno0ysMGgUAmC5xzEbmzJktToKHkfh9e5SxNxQOAIDTcBolfUqN7xuFAwAAmI7CAQCASY4fPy6bzabw8PAUv2b69OnKnj275TlSG4NGAQCW+viP8077rLer5H6o1508eVJDhw7V8uXLdf78eeXLl0+tWrXSkCFD7jkItlChQjpz5oxy507557Zv317Nmzd/qJxpGUc4AAC4h6NHj6p69eo6fPiwZs+erb/++ktTpkzR6tWrFRQUpAsXLiT7uri4OLm5ucnf31+ZMqX893tvb2/lyZMnteKnGRQOAADuoXfv3vLw8NAvv/yiOnXqqHDhwmrWrJlWrVqlU6dO6Z133pEkBQQE6MMPP1SXLl3k4+Ojl156KdlTGT///LNKlCghLy8v1atXTzNmzJDNZnNMiHb7KZX3339flStX1syZMxUQECBfX1916NBBly5dcmyzfPly/e9//1P27NmVK1cutWzZUkeOHHHGlyfFKBwAANzFhQsXtGLFCvXq1csxH0Uif39/BQcHa86cOTIMQ5I0evRoVapUSX/88Yfee++9O97v2LFjatu2rVq1aqVdu3bp5ZdfdhSWezly5Ih+/PFHLV68WIsXL9b69ev18ccfO9ZfuXJF/fv31/bt27V69WrZ7XY9++yzSkhIeMSvQOphDAcAAHdx+PBhGYahMmXKJLu+TJkyunjxos6dOydJql+/vt544w3H+uPHjyfZfurUqSpVqpQ+/fRTSVKpUqW0d+9effTRR/fMkZCQoOnTpytbtmySpM6dO2v16tWO17Vp0ybJ9qGhofLz89P+/ftVvnz5lO+wiTjCAQDAfSQewbif6tWr33P9wYMHVaNGjSTLatased/3DQgIcJQN6dYU44nTjUu3ilHHjh1VtGhR+fj4KCAgQJJ04sSJFOV2BgoHAAB3Ubx4cdlsNh04cCDZ9QcOHFCOHDnk5+cnScqSJYspOdzd3ZM8t9lsSU6XPPXUU7pw4YK++uorbdmyRVu2bJF0a+BqWkHhAADgLnLlyqVGjRpp0qRJunbtWpJ1ERER+u6779S+ffsUz8RZqlQpbd++Pcmybdu2PVLGf//9VwcPHtS7776rBg0aOE7zpDWM4QDSk1lOmBb6+ZQdOgYyigkTJuixxx5TkyZNNHz4cAUGBmrfvn0aMGCAChQocN/xF//18ssva8yYMRo4cKB69Oih8PBwTZ8+XdLDTx+eI0cO5cqVS19++aXy5cunEydO6O23336o9zIThQMAYKmHnYzLWUqUKKHt27dr6NChateunS5cuCB/f3+1atVKQ4cOVc6cOVP8XoGBgZo/f77eeOMNjRs3TkFBQXrnnXfUs2dPeXp6PlQ+u92u77//Xq+99prKly+vUqVKafz48apbt+5DvZ9ZbEZKR8K4sJiYGPn6+io6Olo+Pj5WxwHujiMcSKeuX7+uY8eOKTAwUF5eXlbHSVM++ugjTZkyRSdPnrQ6yl3d6/uX0p+hHOEAAMCJJk2apBo1aihXrlz6/fff9emnn6pPnz5WxzIdhQMAACc6fPiwhg8frgsXLqhw4cJ64403NGjQIKtjmY7CAQCAE40dO1Zjx461OobTcVksAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpuCwWwCP5+I/zpn9GWp/6GnCGunXrqnLlyvr8889T/b0DAgLUr18/9evXL9XfOxGFAwBgLWdM2Z/oIabu79q1q2bMmCFJypQpkwoWLKjnnntOw4YNc+o07QsWLLjjNvXpCYUDAID7aNq0qcLCwnTjxg3t2LFDISEhstls+uSTT5yW4X43iYuLi5OHh4eT0jw4xnAAAHAfnp6e8vf3V6FChdSqVSs1bNhQK1eulCQlJCRo5MiRCgwMlLe3typVqqT58+c7Xrtu3TrZbDYtWbJEFStWlJeXl2rXrq29e/c6tvn333/VsWNHFShQQJkzZ1aFChU0e/bsJBnq1q2b5JRHQECAPvzwQ3Xp0kU+Pj566aWXJEm//fabnnjiCXl7e6tQoUJ67bXXdOXKFcfrIiMj9dRTT8nb21uBgYH67rvvzPiS3YHCAQDAA9i7d682btzoOJowcuRIffPNN5oyZYr27dun119/XZ06ddL69euTvG7AgAH67LPPtG3bNvn5+empp57SjRs3JN26G2u1atW0ZMkS7d27Vy+99JI6d+6srVu33jPL6NGjValSJf3xxx967733dOTIETVt2lRt2rTR7t27NWfOHP32229Jbg7XtWtXnTx5UmvXrtX8+fM1adIkRUZGpvJX6U6cUgEA4D4WL16srFmzKj4+XrGxsbLb7ZowYYJiY2M1YsQIrVq1SkFBQZKkokWL6rffftPUqVNVp04dx3sMHTpUjRo1kiTNmDFDBQsW1MKFC9WuXTsVKFBAb775pmPbV199VStWrNDcuXNVs2bNu+aqX7++3njjDcfzF154QcHBwY4jISVKlND48eNVp04dTZ48WSdOnNCyZcu0detW1ahRQ5I0bdo0lSlTJtW+VndD4QAA4D7q1aunyZMn68qVKxo7dqwyZcqkNm3aaN++fbp69aqjSCSKi4tTlSpVkixLLCTSrfEYpUqV0oEDByRJN2/e1IgRIzR37lydOnVKcXFxio2NVebMme+Zq3r16kme79q1S7t3705ymsQwDCUkJOjYsWM6dOiQMmXKpGrVqjnWly5dWtmzZ3+gr8fDoHAAAHAfWbJkUfHixSVJoaGhqlSpkqZNm6by5ctLkpYsWaICBQokeY2np2eK3//TTz/VuHHj9Pnnn6tChQrKkiWL+vXrp7i4uPvm+q/Lly/r5Zdf1muvvXbHtoULF9ahQ4dSnCm1UTgAAHgAdrtdgwcPVv/+/XXo0CF5enrqxIkTSU6fJGfz5s0qXLiwJOnixYs6dOiQ41TG77//rmeeeUadOnWSdGsg6qFDh1S2bNkHyla1alXt37/fUY5uV7p0acXHx2vHjh2OUyoHDx5UVFTUA33Ow2DQKAAAD+i5556Tm5ubpk6dqjfffFOvv/66ZsyYoSNHjmjnzp364osvHHN3JBo2bJhWr16tvXv3qmvXrsqdO7datWol6dZYi5UrV2rjxo06cOCAXn75ZZ09e/aBcw0cOFAbN25Unz59FB4ersOHD+unn35yDBotVaqUmjZtqpdffllbtmzRjh079MILL8jb2/uRvyb3wxEOAIC1HmIyLqtlypRJffr00ahRo3Ts2DH5+flp5MiROnr0qLJnz66qVatq8ODBSV7z8ccfq2/fvjp8+LAqV66sRYsWOa50effdd3X06FE1adJEmTNn1ksvvaRWrVopOjr6gXJVrFhR69ev1zvvvKMnnnhChmGoWLFiat++vWObsLAwvfDCC6pTp47y5s2r4cOH67333nv0L8p92AzDSH/f6VQWExMjX19fRUdHy8fHx+o4wN05Y0bGB/zHn6nNkRLXr1/XsWPHFBgY6NTZOdOCdevWqV69erp48aJTBmea4V7fv5T+DOWUCgAAMB2FAwAAmI4xHAAAmKhu3bpi9AJHOAAAgBNQOAAATsNv+ulTanzfKBwAANO5u7tLkq5evWpxEjyMxO9b4vfxYTCGAwBgOjc3N2XPnt1xV9LMmTPLZnPCZd54JIZh6OrVq4qMjFT27Nnl5ub20O9F4QAAOIW/v78kOeVW6Ehd2bNnd3z/HhaFAwDgFDabTfny5VOePHl048YNq+Mghdzd3R/pyEaiNFM4Pv74Yw0aNEh9+/bV559/LunWzGZvvPGGvv/+e8XGxqpJkyaaNGmS8ubN63jdiRMn1LNnT61du1ZZs2ZVSEiIRo4cqUyZ0syuAQD+w83NLVV+gCF9SRODRrdt26apU6eqYsWKSZa//vrrWrRokebNm6f169fr9OnTat26tWP9zZs31aJFC8XFxWnjxo2aMWOGpk+friFDhjh7FwAAwD1YXjguX76s4OBgffXVV8qRI4djeXR0tKZNm6YxY8aofv36qlatmsLCwrRx40Zt3rxZkvTLL79o//79+vbbb1W5cmU1a9ZMH374oSZOnKi4uDirdgkAANzG8sLRu3dvtWjRQg0bNkyyfMeOHbpx40aS5aVLl1bhwoW1adMmSdKmTZtUoUKFJKdYmjRpopiYGO3bt++unxkbG6uYmJgkDwAAYB5LBzp8//332rlzp7Zt23bHuoiICHl4eNxxZ728efMqIiLCsc1/y0bi+sR1dzNy5Eh98MEHj5geAACklGVHOE6ePKm+ffvqu+++c/qtigcNGqTo6GjH4+TJk079fAAAMhrLCseOHTsUGRmpqlWrKlOmTMqUKZPWr1+v8ePHK1OmTMqbN6/i4uIUFRWV5HVnz551XAvs7++vs2fP3rE+cd3deHp6ysfHJ8kDAACYx7LC0aBBA+3Zs0fh4eGOR/Xq1RUcHOz4f3d3d61evdrxmoMHD+rEiRMKCgqSJAUFBWnPnj1JJpFZuXKlfHx8VLZsWafvEwAASJ5lYziyZcum8uXLJ1mWJUsW5cqVy7G8R48e6t+/v3LmzCkfHx+9+uqrCgoKUu3atSVJjRs3VtmyZdW5c2eNGjVKERERevfdd9W7d295eno6fZ8AAEDy0vTsWGPHjpXdblebNm2STPyVyM3NTYsXL1bPnj0VFBSkLFmyKCQkRMOGDbMwNQAAuJ3N4F7BiomJka+vr6KjoxnPgbRtlhNudvX8g/2T8PEf500K8n/erpLb9M8A8HBS+jPU8nk4AACA66NwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNZWjgmT56sihUrysfHRz4+PgoKCtKyZcsc669fv67evXsrV65cypo1q9q0aaOzZ88meY8TJ06oRYsWypw5s/LkyaMBAwYoPj7e2bsCAADuwdLCUbBgQX388cfasWOHtm/frvr16+uZZ57Rvn37JEmvv/66Fi1apHnz5mn9+vU6ffq0Wrdu7Xj9zZs31aJFC8XFxWnjxo2aMWOGpk+friFDhli1SwAAIBk2wzAMq0P8V86cOfXpp5+qbdu28vPz06xZs9S2bVtJ0p9//qkyZcpo06ZNql27tpYtW6aWLVvq9OnTyps3ryRpypQpGjhwoM6dOycPD48UfWZMTIx8fX0VHR0tHx8f0/YNeGSzbOZ/xvMP9k/Cx3+cNynI/3m7Sm7TPwPAw0npz9A0M4bj5s2b+v7773XlyhUFBQVpx44dunHjhho2bOjYpnTp0ipcuLA2bdokSdq0aZMqVKjgKBuS1KRJE8XExDiOkiQnNjZWMTExSR4AAMA8lheOPXv2KGvWrPL09NQrr7yihQsXqmzZsoqIiJCHh4eyZ8+eZPu8efMqIiJCkhQREZGkbCSuT1x3NyNHjpSvr6/jUahQodTdKQAAkITlhaNUqVIKDw/Xli1b1LNnT4WEhGj//v2mfuagQYMUHR3teJw8edLUzwMAIKPLZHUADw8PFS9eXJJUrVo1bdu2TePGjVP79u0VFxenqKioJEc5zp49K39/f0mSv7+/tm7dmuT9Eq9iSdwmOZ6envL09EzlPQEAAHdj+RGO2yUkJCg2NlbVqlWTu7u7Vq9e7Vh38OBBnThxQkFBQZKkoKAg7dmzR5GRkY5tVq5cKR8fH5UtW9bp2QEAQPIsPcIxaNAgNWvWTIULF9alS5c0a9YsrVu3TitWrJCvr6969Oih/v37K2fOnPLx8dGrr76qoKAg1a5dW5LUuHFjlS1bVp07d9aoUaMUERGhd999V7179+YIBgAAaYilhSMyMlJdunTRmTNn5Ovrq4oVK2rFihVq1KiRJGns2LGy2+1q06aNYmNj1aRJE02aNMnxejc3Ny1evFg9e/ZUUFCQsmTJopCQEA0bNsyqXQIAAMlIc/NwWIF5OJBuMA8HgDQm3c3DAQAAXBeFAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkeqnAULVpU//777x3Lo6KiVLRo0UcOBQAAXMtDFY7jx4/r5s2bdyyPjY3VqVOnHjkUAABwLZkeZOOff/7Z8f8rVqyQr6+v4/nNmze1evVqBQQEpFo4AADgGh6ocLRq1UqSZLPZFBISkmSdu7u7AgIC9Nlnn6VaOAAA4BoeqHAkJCRIkgIDA7Vt2zblzp3blFAAAMC1PFDhSHTs2LHUzgEAAFzYQxUOSVq9erVWr16tyMhIx5GPRKGhoY8cDAAAuI6HKhwffPCBhg0bpurVqytfvnyy2WypnQsAALiQhyocU6ZM0fTp09W5c+fUzgMAAFzQQ83DERcXp8ceeyy1swAAABf1UIXjhRde0KxZs1I7CwAAcFEPdUrl+vXr+vLLL7Vq1SpVrFhR7u7uSdaPGTMmVcIBAADX8FCFY/fu3apcubIkae/evUnWMYAUAADc7qEKx9q1a1M7BwAAcGHcnh4AAJjuoY5w1KtX756nTtasWfPQgQAAgOt5qMKROH4j0Y0bNxQeHq69e/fecVM3AACAhyocY8eOTXb5+++/r8uXLz9SIAAA4HpSdQxHp06duI8KAAC4Q6oWjk2bNsnLyys13xIAALiAhzql0rp16yTPDcPQmTNntH37dr333nupEgwAALiOhyocvr6+SZ7b7XaVKlVKw4YNU+PGjVMlGAAAcB0PVTjCwsJSOwcAAHBhD1U4Eu3YsUMHDhyQJJUrV05VqlRJlVAAAMC1PFThiIyMVIcOHbRu3Tplz55dkhQVFaV69erp+++/l5+fX2pmBAAA6dxDXaXy6quv6tKlS9q3b58uXLigCxcuaO/evYqJidFrr72W2hkBAEA691BHOJYvX65Vq1apTJkyjmVly5bVxIkTGTQKAADu8FBHOBISEuTu7n7Hcnd3dyUkJDxyKAAA4FoeqnDUr19fffv21enTpx3LTp06pddff10NGjRItXAAAMA1PFThmDBhgmJiYhQQEKBixYqpWLFiCgwMVExMjL744ovUzggAANK5hxrDUahQIe3cuVOrVq3Sn3/+KUkqU6aMGjZsmKrhAACAa3igIxxr1qxR2bJlFRMTI5vNpkaNGunVV1/Vq6++qho1aqhcuXL69ddfzcoKAADSqQcqHJ9//rlefPFF+fj43LHO19dXL7/8ssaMGZNq4QAAgGt4oMKxa9cuNW3a9K7rGzdurB07djxyKAAA4FoeqHCcPXs22cthE2XKlEnnzp175FAAAMC1PFDhKFCggPbu3XvX9bt371a+fPkeORQAAHAtD1Q4mjdvrvfee0/Xr1+/Y921a9c0dOhQtWzZMtXCAQAA1/BAl8W+++67WrBggUqWLKk+ffqoVKlSkqQ///xTEydO1M2bN/XOO++YEhQAAKRfD1Q48ubNq40bN6pnz54aNGiQDMOQJNlsNjVp0kQTJ05U3rx5TQkKAADSrwee+KtIkSJaunSpLl68qL/++kuGYahEiRLKkSOHGfkAAIALeKiZRiUpR44cqlGjRmpmAQAALuqh7qUCAADwICgcAADAdJYWjpEjR6pGjRrKli2b8uTJo1atWungwYNJtrl+/bp69+6tXLlyKWvWrGrTpo3Onj2bZJsTJ06oRYsWypw5s/LkyaMBAwYoPj7embsCAADuwdLCsX79evXu3VubN2/WypUrdePGDTVu3FhXrlxxbPP6669r0aJFmjdvntavX6/Tp0+rdevWjvU3b95UixYtFBcXp40bN2rGjBmaPn26hgwZYsUuAQCAZNiMxGtb04Bz584pT548Wr9+vZ588klFR0fLz89Ps2bNUtu2bSXdmvOjTJky2rRpk2rXrq1ly5apZcuWOn36tOOS3ClTpmjgwIE6d+6cPDw87vu5MTEx8vX1VXR0dLI3pgPSjFk28z/j+Qf7J+HjP86bFOT/vF0lt+mfAeDhpPRnaJoawxEdHS1JypkzpyRpx44dunHjhho2bOjYpnTp0ipcuLA2bdokSdq0aZMqVKiQZP6PJk2aKCYmRvv27XNiegAAcDcPfVlsaktISFC/fv30+OOPq3z58pKkiIgIeXh4KHv27Em2zZs3ryIiIhzb3D7ZWOLzxG1uFxsbq9jYWMfzmJiY1NoNAACQjDRzhKN3797au3evvv/+e9M/a+TIkfL19XU8ChUqZPpnAgCQkaWJwtGnTx8tXrxYa9euVcGCBR3L/f39FRcXp6ioqCTbnz17Vv7+/o5tbr9qJfF54ja3GzRokKKjox2PkydPpuLeAACA21laOAzDUJ8+fbRw4UKtWbNGgYGBSdZXq1ZN7u7uWr16tWPZwYMHdeLECQUFBUmSgoKCtGfPHkVGRjq2WblypXx8fFS2bNlkP9fT01M+Pj5JHgAAwDyWjuHo3bu3Zs2apZ9++knZsmVzjLnw9fWVt7e3fH191aNHD/Xv3185c+aUj4+PXn31VQUFBal27dqSpMaNG6ts2bLq3LmzRo0apYiICL377rvq3bu3PD09rdw9AADw/1laOCZPnixJqlu3bpLlYWFh6tq1qyRp7NixstvtatOmjWJjY9WkSRNNmjTJsa2bm5sWL16snj17KigoSFmyZFFISIiGDRvmrN0AAAD3kabm4bAK83Ag3WAeDgBpTLqchwMAALgmCgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA02WyOgAAAOnBx3+cN/0z3j7gZ/pn6HnD/M9IBkc4AACA6SgcAADAdBQOAABgOksLx4YNG/TUU08pf/78stls+vHHH5OsNwxDQ4YMUb58+eTt7a2GDRvq8OHDSba5cOGCgoOD5ePjo+zZs6tHjx66fPmyE/cCAADcj6WF48qVK6pUqZImTpyY7PpRo0Zp/PjxmjJlirZs2aIsWbKoSZMmun79umOb4OBg7du3TytXrtTixYu1YcMGvfTSS87aBQAAkAKWXqXSrFkzNWvWLNl1hmHo888/17vvvqtnnnlGkvTNN98ob968+vHHH9WhQwcdOHBAy5cv17Zt21S9enVJ0hdffKHmzZtr9OjRyp8/v9P2BQAA3F2aHcNx7NgxRUREqGHDho5lvr6+qlWrljZt2iRJ2rRpk7Jnz+4oG5LUsGFD2e12bdmy5a7vHRsbq5iYmCQPAABgnjRbOCIiIiRJefPmTbI8b968jnURERHKkydPkvWZMmVSzpw5HdskZ+TIkfL19XU8ChUqlMrpAQDAf6XZwmGmQYMGKTo62vE4efKk1ZEAAHBpabZw+Pv7S5LOnj2bZPnZs2cd6/z9/RUZGZlkfXx8vC5cuODYJjmenp7y8fFJ8gAAAOZJs4UjMDBQ/v7+Wr16tWNZTEyMtmzZoqCgIElSUFCQoqKitGPHDsc2a9asUUJCgmrVquX0zAAAIHmWXqVy+fJl/fXXX47nx44dU3h4uHLmzKnChQurX79+Gj58uEqUKKHAwEC99957yp8/v1q1aiVJKlOmjJo2baoXX3xRU6ZM0Y0bN9SnTx916NCBK1QAAEhDLC0c27dvV7169RzP+/fvL0kKCQnR9OnT9dZbb+nKlSt66aWXFBUVpf/9739avny5vLy8HK/57rvv1KdPHzVo0EB2u11t2rTR+PHjnb4vAADg7iwtHHXr1pVh3P2udTabTcOGDdOwYcPuuk3OnDk1a9YsM+IBAIBUkmbHcAAAANdB4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdJbeLRZwJR//cd70z3jb9E8AAHNwhAMAAJiOwgEAAExH4QAAAKajcAAAANMxaBTp0yyb+Z/xvGH+ZwBABsERDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0mawO4Mo+/uO86Z/x9gE/0z9DzxvmfwYAwKVxhAMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdNyeHgAewsd/nDf9M94+4Gf6Z+h5w/zPAMQRDgAA4AQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApuOyWADAAzH7kmAuB3ZNHOEAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJiOwgEAAExH4QAAAKajcAAAANNROAAAgOkoHAAAwHQUDgAAYDoKBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAAAA01E4AACA6SgcAADAdBQOAABgOgoHAAAwHYUDAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGC6TFYHgOv5+I/zpn/G26Z/AgAgNXGEAwAAmI7CAQAATOcyhWPixIkKCAiQl5eXatWqpa1bt1odCQAA/H8uUTjmzJmj/v37a+jQodq5c6cqVaqkJk2aKDIy0upoAABALlI4xowZoxdffFHdunVT2bJlNWXKFGXOnFmhoaFWRwMAAHKBq1Ti4uK0Y8cODRo0yLHMbrerYcOG2rRpU7KviY2NVWxsrON5dHS0JCkmJiZVs12/fClV3y85MVdN/wjpAb8u7Ld5Mux+x3iY/hkPKqN+vyXz9z2j7reUdvf93m936/0Mw7j3hkY6d+rUKUOSsXHjxiTLBwwYYNSsWTPZ1wwdOtSQxIMHDx48ePBIpcfJkyfv+fM63R/heBiDBg1S//79Hc8TEhJ04cIF5cqVSzabzcJkDyYmJkaFChXSyZMn5ePjY3Ucp2G/2e+MgP3OWPstpd99NwxDly5dUv78+e+5XbovHLlz55abm5vOnj2bZPnZs2fl7++f7Gs8PT3l6emZZFn27NnNimg6Hx+fdPWHM7Ww3xkL+52xZNT9ltLnvvv6+t53m3Q/aNTDw0PVqlXT6tWrHcsSEhK0evVqBQUFWZgMAAAkSvdHOCSpf//+CgkJUfXq1VWzZk19/vnnunLlirp162Z1NAAAIBcpHO3bt9e5c+c0ZMgQRUREqHLlylq+fLny5s1rdTRTeXp6aujQoXecHnJ17Df7nRGw3xlrvyXX33ebYdzvOhYAAIBHk+7HcAAAgLSPwgEAAExH4QAAAKajcAAA0qSbN29aHQGpiMLhAqKiojRhwgSrYzhdRt1vwNUdOnRIb731lgoWLGh1FKQiCkc6tnr1aj3//PPKly+fhg4danUcp8mo+w24sqtXryosLExPPPGEypYtqw0bNiS5BQXSPwpHOnPy5EkNGzZMgYGBaty4sWw2mxYuXKiIiAiro5kqo+63dOtIzvbt27V9+3ZFRUVZHcdSMTExmjx5sqpXr251FKSSzZs364UXXlC+fPk0ZswYbdq0SWvXrtXmzZs1YMAAq+OZJj4+Xp9++qmqVq2qrFmzKmvWrKpatapGjx6tGzduWB3PHKlzz1aYKS4uzpg7d67RuHFjw9vb23j22WeNefPmGZkyZTL27dtndTzTZNT9TnTs2DGjefPmhpubm2G32w273W64ubkZLVq0MI4dO2Z1PKdas2aN0alTJyNz5sxGvnz5jF69elkdKdX17NnTuHTpkuP5rFmzjMuXLzueX7x40WjWrJkV0UwxevRoo2zZskaBAgWMN9980wgPDzcMw8gQf7+vXr1qPP7444bdbjcaN25s9O3b1+jbt6/RuHFjw263G0888YRx7do1q2OmOgpHOuDn52c88cQTxtSpU40LFy44lrv6X8yMut+GYRgnTpww8ubNaxQsWNAYMWKEsXDhQmPhwoXGRx99ZBQsWNDw9/e/762g07t//vnHGD58uFGsWDEjV65cht1uN77//nsjISHB6mimsNvtxtmzZx3Ps2XLZhw5csTxPCIiwrDb7VZEM4Wbm5sxePBgIz4+PsnyjPD3e8iQIUbhwoWNXbt23bEuPDzcKFy4sDF06FDnBzMZp1TSgfj4eNlsNtlsNrm5uVkdx2ky6n5L0vvvv69SpUrp8OHDGjRokFq1aqVWrVpp8ODBOnTokEqWLKn333/f6pim+OGHH9S8eXOVKlVK4eHh+uyzz3T69GnZ7XZVqFBBNpvN6oimMG6b9Pn2567mww8/1Lx58xQYGKiBAwdq7969Vkdymu+//15jxoxRxYoV71hXqVIljR49WrNmzbIgmbkoHOnA6dOn9dJLL2n27Nny9/dXmzZttHDhQpf9hzdRRt1vSVq+fLk++ugjeXl53bHO29tbH374oZYuXWpBMvO1b99eVapU0ZkzZzRv3jw988wz8vDwsDoWUtmgQYN06NAhzZw5UxEREapVq5YqVaokwzB08eJFq+OZ6u+//1bNmjXvur527do6ceKEExM5B4UjHfDy8lJwcLDWrFmjPXv2qEyZMnrttdcUHx+vjz76SCtXrnTJ69Uz6n5L0vnz5xUQEHDX9UWLFtWFCxecF8iJevTooYkTJ6pp06aaMmWKy//wyejq1KmjGTNmKCIiQr169VK1atVUp04dPfbYYxozZozV8Uzh4+OjyMjIu66PiIhQtmzZnJjIObh5WzqVkJCgFStWaNq0aVq0aJGyZcum8+fPWx3LdBllvwMCAvTll1+qcePGya5fvny5XnnlFR0/fty5wZzk2rVrmjt3rkJDQ7VlyxY1adJES5YsUXh4uMqXL291PFPY7Xa99NJLypw5syRp4sSJ6tSpk3x9fSXdumz0q6++ctmS/V979uzRtGnTNGvWrHv+YE6v2rdvr/j4eP3www/Jrm/Tpo3c3Nw0d+5cJyczF4XDBZw7d04zZ87McNesu/J+9+vXT2vWrNHq1avl5+eXZF1kZKQaNWqkevXq6fPPP7cmoBMdPnxYYWFhmjFjhi5fvqwWLVqobdu2at26tdXRUlXdunVTdLpw7dq1TkiTNty4cUPu7u5Wx0h1+/fvV61atVSuXDn1799fpUuXlmEYOnDggMaOHav9+/dr8+bNKleunNVRUxWFA0iDLl68qFq1aikiIkKdOnVK8g/SrFmz5O/vr82bNytnzpxWR3WahIQELVmyRNOmTdOyZcsUGxtrdSQ8gm+++ea+29hsNnXu3NkJaZxv8+bN6tGjhw4cOOAomoZhqHTp0po2bZqCgoIsTpj6KBzpQGBg4H1/87HZbDpy5IiTEjlHjhw5UvQbn6uOZbh48aIGDx6sOXPmOCb8yp49u9q1a6cRI0ZkqLJxu8jISOXJk8fqGKmqaNGi2rZtm3LlymV1FKfIkSPHXdfZbDZduXJF8fHxLn8KKTw8XIcOHZIklSxZUpUrV7Y2kIkoHOnAuHHj7rru+PHjmjp1qmJjY13uL+aMGTNStF1ISIjJSaxlGIbOnTsnSfLz83P5q3R+/vnn+25js9n01FNPOSGN89jtdkVERLhckXpQZ86c0QcffKDQ0FDVr19fy5cvtzpSqsto5TIRhSOdunDhgj788ENNnjxZtWrV0ieffKLatWtbHcup4uPjFRkZqfz581sdBanIbr//xXM2m83lCnZGLxyXLl3SJ598onHjxqlcuXIaOXKk6tWrZ3UsU2TU73UmqwPgwVy7dk1jxozR6NGjVaRIES1YsEDNmze3OpYl9u3bp6pVq7rcDx5JqlKlSoqOZOzcudMJaZwrISHB6giWWbFiheOqlLt5+umnnZTGOW7cuKEvvvhCI0aMUK5cuRQWFqa2bdtaHQsmoHCkEzdv3tRXX32lDz74QF5eXho/frw6derk8ofXM6pWrVpZHQEWuN/pQVc6smMYhr755hsNGTJE8fHxGjFihHr06JFhZhXOiOWSUyrpwNy5c/Xuu+8qKipK77zzjnr27MnMi5J27drlskc4IK1Zs0YLFizQ8ePHZbPZFBgYqLZt2+rJJ5+0OpopMtph9goVKujo0aN69dVX1a9fP8f8I7fz8fFxcjLzZdTThhSOdMBut8vb21sdO3a8518+V52V725cuXDMnDlTLVq0uOuVKFeuXNFnn32mIUOGODmZc7zyyiv68ssvlSNHDpUsWVKGYejw4cOKiopSr1699MUXX1gdMdW5ubnpzJkzGaZw/PeHbnJHag3DcMkfulLGK5eJKBzpQEomBLLZbFqzZo2TEjnH7t2777n+zz//VMeOHV32H6SiRYvqxx9/THZmzbNnzyp//vwuue8LFy5Uhw4dNHXqVIWEhDj+7CckJGj69Onq2bOn5s2b53KHmzPaD6H169enaLs6deqYnMT5Mlq5TEThQJplt9tls9mSvWtm4nJX/g2oYcOG2rx5s6ZPn37HrJquXDiefvppx1UKyRk4cKD+/PNP/fTTT05OZq5u3bpp/PjxLnkPjYd14cIFl5xvJqOVy0QMGkWadezYMasjWMZms+nbb7/VV199pXbt2umdd97RBx98YHUsp9i5c6fefffdu65v3bq12rRp48REzhEWFmZ1hDTjl19+0ddff61Fixbp2rVrVsdJdSEhIfL29rY6htNRONKBqKgozZ49Wz179pQkBQcHJ/lL6Obmpq+++krZs2e3KKE5ihQpYnUEyyQe1XnnnXdUqVIlderUSbt379a3336rLFmyWJzOXOfPn1fBggXvur5gwYL6999/nZjIORKP6N2LzWZTfHy8kxI5199//63Q0FDNmDFDFy9eVLNmzVI0/Xl61KxZM3l6ejqe//PPP8qfP79jXMvVq1c1YcIEvfXWW1ZFNAWnVNKBTz/9VOHh4fruu+8kSdmyZVOTJk0ch143bdqkDh066P3337cwZeq724yTvr6+KlmypPLly+fkRM5z+yHXP//8U61atVKmTJn0888/K0uWLC57SsVut+vs2bN33LQukaueTvrxxx/vWjg2bdqk8ePHKyEhQdevX3dyMvPExcVpwYIF+vrrr/X777+rYcOGWrZsmf744w9VqFDB6nimuX0Mh4+Pj8LDw1W0aFFJrvtnnCMc6cD8+fP10UcfJVk2atQoxx/OhQsXatiwYS5XOO41F4XNZlOHDh301Vdf3fVyuvTs9h88pUuX1tatW9WxY0fVqFHD5e8S+9577931+3r16lUnp3GO5P68Hzx4UG+//bYWLVqk4OBgDRs2zPnBTPLqq69q9uzZKlGihDp16qQ5c+YoV65ccnd3d/m5OG7/PT+j/N5P4UgHjh49qlKlSjmelypVKsk8HJUqVdLhw4etiGaqu804GR0drR07dqh3794aPny4RowY4eRk5kvuHyAfHx8tXrxY77zzjrp27er8UE7y5JNP6uDBg/fdxpWdPn1aQ4cO1YwZM9SkSROFh4cne7VSejZ58mQNHDhQb7/9NgNlMwgKRzpw5coVRUdHq1ChQpKk7du337E+I00H7evrq/r162vs2LHq16+fSxaOuw0qs9lsGjFihCpXrqwpU6ZYkMx869atszqCZaKjozVixAh98cUXqly5slavXq0nnnjC6limmDlzpkJDQ5UvXz61aNFCnTt3VrNmzayOBRNRONKBokWLaufOnXf9DWf79u0KDAx0cirrlS5dWv/884/VMUxxvysW2rZt65KnklJq+/btql69utUxUtWoUaP0ySefyN/fX7Nnz9YzzzxjdSRTdezYUR07dtSxY8c0ffp09e7dW1evXlVCQoL279+vsmXLWh3RVP+d2jwhIUGrV6/W3r17Jd26UMAVMWg0HXjvvfc0Y8YMbdu2TXnz5k2yLiIiQjVr1lSXLl00fPhwixJaY82aNXrllVd06NAhq6M4zV9//aXQ0FBNnz5d586d040bN6yOZJrLly/Lzc0tyZGe8PBwvffee1q6dKnLDahLnFG4YcOG9xzDsGDBAiemch7DMPTLL79o2rRp+vnnn5U7d261bt1a48ePtzpaqsuoU5vff69hubfeektZs2ZViRIl1Lt3b40bN07jxo1Tr169VLJkSWXJkkUDBw60OqZThYeH680331SLFi2sjmK6a9eu6ZtvvtGTTz6pUqVKaePGjRoyZIjLHt05efKkgoKC5OvrK19fX/Xv319Xr15Vly5dVKtWLWXJkkUbN260Omaq69Kli9q1a6ecOXM69j25h6uy2Wxq0qSJ5s6dq9OnT+vNN99M8Wyk6U1CQsJ9H65WNiSOcKQbFy9e1KBBgzR37lzH4bbs2bOrXbt2GjFihEvOxpcjR45kLxO8cuWK4uPj1ahRI82dO9clb+4kSdu2bdPXX3+t77//XsWKFVNwcLAGDhyo3bt3u/Th5g4dOujgwYPq0aOHFixYoPXr16tq1aqqVauW3n777XvO0YH0JSYmRlmzZr3jN/6EhARdvnzZZf9uZ1QUjnTGMAydO3dOkuTn5+f4geyKUwDPmDEj2eU+Pj4qVaqUS//QrVixomJiYvT8888rODhY5cqVkyS5u7tr165dLr3v+fPn14IFC1S7dm1FRkbK399fY8aMUb9+/ayO5jRRUVH666+/JEnFixd3uUn9pFuX8w8cOFDh4eF3jEe6cuWKqlatqtGjR+upp56yKKF5NmzYkKLtXO1qLApHOufqUwBnVJ6enmrfvr06d+6shg0bOoplRigcbm5uOn36tGO8UtasWbVjx44kl4a7quPHj6t3795asWKF49Jom82mpk2basKECQoICLA2YCpq3Lix2rVrpxdeeCHZ9aGhoZozZ45WrFjh5GTmu9cYjsS/6644qyxXqaRDGWUK4JiYmBRt54qHXY8ePeq4M+q1a9fUsWNHBQcH33fqa1fx33+Q7XZ7knlnXNXJkydVu3Ztubu768MPP1SZMmUkSfv379fkyZMVFBSkbdu2ucwppb1792rSpEl3Xf/kk0/e85466dnFixeTXX716lWNGzdO48ePd0zs6FIMpAuxsbHG7NmzjQYNGhheXl5Gy5YtDTc3N2P37t1WRzONzWYz7Hb7XR+J613d6tWrjeDgYMPb29uw2WzGgAEDjIMHD1odyzQ2m83Inj27kSNHDiNHjhyGzWYzfH19Hc8TH66me/fuxpNPPmlcu3btjnVXr141nnzySaNHjx4WJDOHl5eXceDAgbuu379/v+Hl5eXERNa5efOm8dVXXxkFCxY0ChcubISGhho3b960Olaq4whHOpBRpwBeu3at1RHShPr166t+/fqKjo7Wd999p9DQUI0ePVrly5fX7t27rY6X6jLqXVOXL1+uOXPmyMvL64513t7e+vDDD9WhQwcLkpkjICBA27dvV+nSpZNdv3379gxxA8cFCxZo8ODBOnfunAYNGqRXX301yY3dXIrVjQf35+bmZgwePNiIiYlJsjxTpkzGvn37LEoFK23YsMHo3r271TEsEx8fb3WEVOfh4WGcPHnyrutPnjxpeHp6OjGRuQYPHmwULlzYiIiIuGPdmTNnjMKFCxuDBw+2IJlzrFu3zqhVq5aROXNmY9CgQUZUVJTVkUzHPBzpwMyZM7V161bly5dP7du31+LFi13yGu372bdvn3bv3u147Nu3z+pIlvHx8dH06dOtjuF0hw4d0sCBA11mHMN/5cuXT/v377/r+r1798rf39+JicyVeA+VEiVKqFevXo75hXr27KmSJUsqa9asevvtt62OaYrmzZurUaNGqly5so4cOaIRI0a49BwrDlY3HqTc0aNHjSFDhhiFCxc2cufObdjtdmPevHlWxzLNhg0bjOrVqzueZ82a1TF2I3H8xsqVKy1MaJ3w8PAMMX7FMAzjypUrRmhoqPG///3PcHNzM2rVqmWMGjXK6liprm/fvkaFChWMyMjIO9adPXvWqFixotG3b1/nBzNRVFSU0bNnTyNnzpyOv9c5cuQwevbsaVy4cMHqeKax2WyGu7t7krFKyT1cDZfFpkNGBpkCuGPHjgoKCtJrr70mScqWLZuWLFmiIkWKyDAMjR8/Xn///bd++OEHi5M6365du1S1alWXPtK1efNmff3115o3b54KFy6sAwcOaO3atS57M7OLFy+qVq1aioiIUKdOnVS6dGkZhqEDBw5o1qxZ8vf31+bNm11uvh3p1r9p58+fl2EYSeYXclV3m2PodiEhISYncS4KRzp34cIFffPNNwoLC9OuXbusjpOqSpQooYULFzpuWpctWzbt2rXLcbnYH3/8oRYtWuj06dNWxrSEKxeOzz77TKGhoYqOjlbHjh3VqVMnVapUKUPMQXLx4kUNHjxYc+bMyTAzCt9u/fr1unLlioKCgpQjRw6r4yAVUTiQZnl7e+vQoUMqVKiQpFujuZs2beqYlfDvv/9WyZIlFRsba2VMU7Ru3fqe66OiorR+/XqXLByZMmXSwIEDNWzYsCRXYWWEwpHIuMuMwq7kk08+0eXLl/Xhhx9KurXPzZo10y+//CJJypMnj1avXu2YZdeVbN26VdWqVbvrVYaxsbH66aef1K5dOycnMxeFIx0YNmzYfbex2Wx67733nJDGefLkyaO5c+eqbt26ya5ft26dnnvuOcc/zK6kW7duKdrOFS8hHTlypMLCwnT9+nV17NhRnTt3Vvny5TNU4cgIqlatqoEDB6p9+/aSpHnz5ikkJEQrV65UmTJl1KVLF2XOnFlz5861OGnqc3Nz05kzZ5QnTx5JtwaBh4eHO47enj17Vvnz53e5XygoHOmA3W5X/vz5lSdPHt3t22Wz2bRz504nJzPXU089JT8/P4WGhia7vmvXrjp//rwWL17s5GRwhvXr1ys0NFTz589X8eLFtW/fPq1fv16PP/641dFMUb9+/RRtt2bNGpOTOEeOHDm0ceNGx4yq3bp1082bNx2zJm/evFnPPfecTp48aWVMU9jtdkVERDgKx+2ni8+ePat8+fIpISHBypipjom/0oFmzZppzZo1ql69urp3766WLVvecy5+V9G/f381bNhQuXLl0oABAxx/OSMjI/XJJ5/o22+/dRx+heupU6eO6tSpowkTJmjWrFkKDQ1VnTp1VLNmTbVt21b9+/e3OmKqWrdunYoUKaIWLVrI3d3d6jimi4+PTzLB1aZNm5LcoC9//vw6f/68BcnSBlc8jcZlsenEqVOnjBEjRhglS5Y0/P39jbfeesv4888/rY5luokTJxoeHh6G3W53XEJmt9sNDw8P44svvrA6Hpxs9+7dRt++fQ0/Pz+ro6S6UaNGGWXKlDHy5MljvP7668aePXusjmSqSpUqGWFhYYZhGMbff/9t2Gy2JBMZ/v7770aBAgUsSmcum81mnD171vE8a9asxpEjRxzPIyIiXPKyd06ppEMbNmxQWFiYfvjhB1WoUEGrVq2St7e31bFMc/LkSc2fP1+HDx+WdOvqlbZt2zoGkyLjuXHjhsseBdi0aZNCQ0M1d+5clSpVSt27d9fzzz/vcjcp/Oqrr/T666+rffv22rx5s7Jnz67ff//dsX748OHasmWLFi1aZGFKc9jtdq1Zs8Zx1dFjjz2muXPnOia0O3/+vBo1asQYDljv2rVrmjdvniZOnKg9e/YoIiLC5f4xQsZ26dIlHTp0SKVKlVLWrFm1c+dOff7557p27ZpatWql4OBgqyOa7urVq46/5/v379fp06dd7u95aGioFi1aJH9/fw0dOjTJTKq9evVSo0aN9Oyzz1qY0Bz3uz29YRiy2WwUDljnv7/5lCxZUt26ddPzzz+v7NmzWx0NSDUbNmxQy5YtdfnyZeXIkUOzZ89W27ZtVaBAAbm5uenAgQOaMmWKXnzxRaujmuq3335TaGio5s2bp3Llymnt2rUufSQzI9mzZ0+KyqOr3byOwpEOjBo1StOnT9f58+cVHBysbt26qWLFilbHAkzx5JNPqkSJEho2bJhCQ0M1ZswY9ezZUyNGjJB061D7/PnzFR4ebm1QE5w+fVrTp0/X9OnTFRMTo06dOql79+4ufSnwqVOn9MMPP+jQoUOSpFKlSql169YqUKCAxcnMY7fbVbNmTfXo0UMdOnRQtmzZrI7kFBSOdMBut6tw4cJq2bKlPDw87rrdmDFjnJgKMEf27Nm1efNmlS5dWnFxcfL29tbOnTtVqVIlSdJff/2lKlWq6NKlSxYnTV3NmzfX2rVr1bhxY3Xv3l0tWrRQpkyufSHhpEmT1L9/f8XFxTl+44+JiZGHh4fGjBmjXr16WZzQHL/++qvCwsI0f/58JSQkqE2bNnrhhRdcdtr+RBSOdKBu3br3vUTKZrO5zPX5D+LmzZt3na0P6VNK5ihwxUmR7Ha78uXLpzx58tzz77urzLezZMkSPfPMM+rXr5/eeOMN5cuXT5J05swZffrpp/riiy/0008/qXnz5hYnNc+VK1c0d+5cTZ8+Xb/++quKFy+uHj16KCQkxKXuDJyIwoF06dChQ/r66681c+ZMnTlzxuo4SEVubm6KiIiQn5+fpFuzMO7atUuBgYGSXLdwfPDBBynabujQoSYncY66devqf//7n4YPH57s+nfffVe//fab1q1b59xgFvnrr78UFhammTNnKiIiQk2bNtXPP/9sdaxUReFIhxInw8mdO7fFSZzr6tWrmjNnjkJDQ7Vp0yZVr15dbdq00YABA6yOhlRkt9tVvnx5x+mE3bt3q3Tp0o7TifHx8dq3b5/LFY6MxsfHR9u2bVOpUqWSXX/w4EHVqFFDMTExTk5mnStXrui7777ToEGDFBUV5XJ/xl37BKELiYqK0jvvvKM5c+bo4sWLkm5NDdyhQwcNHz7cpa9UyWi3Kc/obv8N/plnnrljmzZt2jgrjtNERkY6TiMlJz4+Xjt37lTNmjWdmMo8N2/evOdcKu7u7i73A/duNmzYoNDQUP3www+y2+1q166devToYXWsVEfhSAcuXLigoKAgnTp1SsHBwY57D+zfv1/Tp0/X6tWrtXHjRpe7lfPttynfsGGD4zbluXLlsjoeTOIqpwweVL58+ZLc0KtChQpaunSpY4K7f//9V0FBQS7zQ7hcuXL66aef9Prrrye7/scff3TJO8Um+u8VSX/99Zcee+wxjR8/Xu3atVOWLFmsjmcOp89tigfWt29fo3z58kZERMQd686cOWNUqFDB6NevnwXJzOXm5mYMHjzYiI+PT7I8U6ZMSaZABlxBSqa7ttlsVkQzxfTp0w1vb29j4sSJxo0bNxzLb9y4YUyYMMHw9vZ2TH3uapo2bWpkypQpQ92mwjAMgyMc6cCPP/6oqVOnKm/evHes8/f316hRo/TKK69o7NixFqQzz4cffugYRPXf25TDtWW0u6Y+CFe6oVdISIj27NmjPn36aNCgQSpWrJgMw9DRo0d1+fJlvfbaa+ratavVMU3h7u6u+fPnq2XLlhnqKjsGjaYDnp6eOnLkiGOe/dv9888/Kl68uK5fv+7kZM6R0W5TntHZ7fYU3TXV1Qp2Rr0cePPmzZo9e7bjXkklS5ZUhw4dVLt2bYuTIbVxhCMdyJ07t44fP37XwnHs2DHHTYBcUUa7TXlG98knnygsLEzz5s1TcHCwunfvniGObNlsNl26dEleXl6Oe2lcvnzZcZWGq12tMWzYML355puqXbs25SKD4AhHOtC9e3cdOXJEK1euvGOm0djYWDVp0kRFixZVaGioRQmdb8+ePZo2bZpmzZqlyMhIq+PABBnlrqmJ7HZ7klMmiaXj9ueucoTDzc0tySBZuD4KRzrwzz//qHr16vL09FTv3r1VunRpGYahAwcOaNKkSYqNjdX27dsz5O3aXfk25bglI9w1Vbp16jAl6tSpY3IS57j9FBJcH6dU0oGCBQtq06ZN6tWrlwYNGqTEjmiz2dSoUSNNmDDBJcvG+PHj77uNzWbTq6++6oQ0sMrOnTu1fv16HThwQOXLl3fZgukqReJBuNIgWNwfRzjSmYsXLzoGVxUvXtylx24kTmV9LzabTUePHnVCGjhTRrxrakrHaLjK0R273S5fX9/7lo4LFy44KRHMRuFwEfPnz1fbtm2tjgE8sox411TpzjEct3O1MRx2u12ff/65fH1977ldSEiIkxLBbBSOdCI+Pl5//vmnPDw8VLJkScfyn376SUOGDNGff/6p2NhYCxM6n2EYOnnypAoXLmx1FKSijHbX1ESM4YCrc/1fG1zA3r171bJlS508eVLSrXtLTJ48We3atdPevXv14osvasmSJRanTH1ubm7q06ePxo4dK7vdfsf6yMhIBQYGusxvfLglo05t/sQTT+jTTz/Vzz//rLi4ODVo0EBDhw6Vt7e31dFMwfiNjIcjHOlAixYtFBsbq379+mn27NmaPXu2SpUqpR49eqh3794u+w+S3W5X1qxZVbNmTc2dO/eO8Spnz55Vvnz5lJCQYFFCIPV8+OGHev/999WwYUN5e3trxYoV6tixo8te7s4RjoyHwpEO5MmTR7/88osqV66s6Oho5ciRQzNmzFDnzp2tjmYqNzc3bdy4US+//LIuXbqkn376KckEUK468yL+z+7du3Xo0CFJt2agrFixosWJzFOiRAm9+eabevnllyVJq1atUosWLXTt2rVkj/AB6Q1/itOB8+fPK3/+/JIkX19fZcmSJUPMzGcYhgIDA7Vp0yZVr15djz32mBYsWGB1LDjB1q1bVaFCBVWpUkXt2rVTu3btVKVKFVWsWFHbtm2zOp4pTpw4oebNmzueN2zYUDabTadPn7YwFZB6KBzpQOKUxzExMYqOjpbNZtO1a9cUExOT5OGqvL29NWfOHA0aNEjt27fPsOf4M4r9+/erQYMG8vb21rfffqudO3dq586dmjlzpjw9PdWgQQPt37/f6pipLj4+Xl5eXkmWubu768aNGxYlAlIXp1TSgYw25XGi5M7xLl26VMHBwapbt65Gjx6tkiVLutx+Z3Tt2rVTfHy8fvjhhzsGFhqGodatW8vd3V1z5861KKE57Ha7mjVrJk9PT8eyRYsWqX79+sqSJYtjGUf5kF5RONKBjHa5XKK73Wvh0KFDatWqla5du6YTJ05QOFyMn5+fli1bpurVqye7ftu2bWrevLnOnTvn5GTm6tatW4q2CwsLMzkJYA4KB9Kse41iv3Tpkp5//nktWbKEq1RcjJeXlw4fPnzX6fpPnjypEiVK6Pr1605OBuBRMIYDaVZCQsJdL5nLli2bFi1apOPHjzs3FExXpEgRbd269a7rt2zZoiJFijgxEYDUQOFAmrV169Z7ni6JjY3V5s2bnZgIztChQwf1799fe/fuvWPdnj179Oabb6p9+/YWJAPwKDilgjTr9jEcPj4+Cg8PV9GiRSUxD4erun79uho0aKAtW7aoUaNGKlOmjAzD0IEDB7Rq1SrVrFlTa9asueOKDgBpG0c4kGbd3oWT68b0Zdfj5eWltWvX6qOPPtKZM2c0ZcoUTZ06VRERERo+fLjmzp2r1157zeqYAB4QRzjSOcMwtHz5ck2bNk3z58+3Ok6qun3QaLZs2bRr1y6OcGRwu3btUtWqVfm+A+kMRzjSqWPHjum9995T4cKF9eyzzzJiHwCQpnG32HQkNjZW8+fP17Rp0/Tbb7/p5s2bGj16tHr06CEfHx+r45li//79ioiIkHTraM6ff/6py5cvS7o15TsAIH3glEo6sGPHDk2bNk2zZ89W8eLF1blzZ7Vv314FCxbUrl27VLZsWasjmiJxhtXk/ogmLnfFGVZxb5xSAdInjnCkA7Vq1dKrr76qzZs3q1SpUlbHcZpjx45ZHQEWaN269T3XR0VFOScIgFRF4UgHGjRooGnTpikyMlKdO3dWkyZN7rjHhCticqeMydfX977ru3Tp4qQ0AFILhSMdWLFihU6ePKmwsDD17NlT165dc0x85MrF48SJEynarnDhwiYngTNxrxDANTGGIx1auXKlwsLCtHDhQhUqVEht27ZV27ZtVbVqVaujparb75Kb6L93y7XZbIqPj3d2NADAA6JwpGMXL17Ut99+q9DQUO3evdvlBtHt2rUr2eWGYej777/X+PHjlTVrVkVGRjo5GQDgQVE4XMTOnTtd7ghHclatWqW3335bhw4dUv/+/fXGG28oW7ZsVscCANwHYzjSgd27d993m0yZXPtbuXPnTg0cOFC//vqrXnjhBS1duvSud5IFAKQ9rv1TykVUrlz5rvNRJHLV+SiOHDmiwYMH64cfflC7du20f/9+x9TmAID0g8KRDmTU+Sh69eqladOmqV69etq+fbsqV65sdSQAwENiDIcLiIqK0tKlS/X8889bHSVV2e12eXl5qXTp0vfcbufOnU5KBAB4WBzhcAF///23Onfu7HKFY+jQoVZHAACkEo5wuADuLQEASOu4PT3SrPvNrxEfH6+tW7c6KQ0A4FFQOJBm5cuXL0npqFChgk6ePOl4/u+//yooKMiKaACAB8QYjnRg/Pjx91x/6tQpJyVxrtvP9h0/flw3bty45zYAgLSJwpEOjB079r7bZNQbmLnyzesAwJVQONKBjDoPBwDAdVA4kGbZbDZdunRJXl5ejjvEXr58WTExMZLk+C8AIO3jsth04H5jOBK99tprJidxrttvT//f29L/9zmXAwNA2kfhSAcCAwPvu43NZtPRo0edkMZ51q9fn6Lt6tSpY3ISAMCjonAgzbpw4YJy5sxpdQwAQCpgHg6kWfnz51eHDh20cuVKq6MAAB4RRzjSgW+++SZF23Xp0sXkJM41c+ZMTZ8+XevWrVOhQoXUtWtXde3aVQEBAVZHAwA8IApHOmC325U1a1ZlypTprhNd2Ww2XbhwwcnJnOPYsWOaPn26vvnmG508eVL16tXTCy+8oGeffVYeHh5WxwMApACFIx0oV66czp49q06dOql79+6qWLGi1ZEss2rVKoWFhenHH3+Ul5eXgoODU3wVDwDAOhSOdGLLli0KDQ3VnDlzVLx4cfXo0UPBwcHy8fGxOpolfvjhB7300kuKiorislgASAcYNJpO1KpVS1OnTtWZM2f02muvae7cucqXL5+Cg4MVGxtrdTyn+Pvvv/X+++8rMDBQ7du3V9WqVfXdd99ZHQsAkAIc4UinNmzYoKFDh2rDhg06f/68cuTIYXUkU8TGxuqHH35QaGio1q1bpwIFCqhr167q1q0bg0cBIB1havN05NSpU5oxY4bCwsJ05coVderUSZMnT3bZstGrVy99//33unr1qp555hktXbpUjRo14oZtAJAOcYQjHZg7d67CwsK0fv16NWnSRN26dVOLFi3k5uZmdTRTVaxYUT169FCnTp2UK1cuq+MAAB4BhSMdsNvtKly4sIKDg5U3b967budq91IBALgOCkc6EBAQcN/TCK54LxUAgOugcAAAANNxWSwAADAdhSMdaN68uaKjox3PP/74Y0VFRTme//vvvypbtqwFyQAASBlOqaQDbm5uOnPmjPLkySNJ8vHxUXh4uIoWLSpJOnv2rPLnz+9yM27u3r07Rdtl5KneASC9YB6OdOD2TphROmLlypVls9mS3d/E5TabzeWKFgC4IgoH0qxjx45ZHQEAkEooHOmAzWa747LYjDDbZpEiRe65PioqSkuXLr3vdgAA6zGGIx2w2+1q1qyZPD09JUmLFi1S/fr1lSVLFkm37jeyfPnyDHdqYdeuXapatWqG228ASI84wpEOhISEJHneqVOnO7bp0qWLs+IAAPDAKBzpQFhYmNURAAB4JMzDAQAATMcRDqRZ48ePv+f6U6dOOSkJAOBRMWgUaVZgYGCKtuPyWQBI+ygcAADAdIzhAAAApmMMB9Ks/v37J7vc19dXJUuWVOvWrR1zkwAA0jZOqSDNqlevXrLLo6Ki9Ndffylv3rxas2aNChcu7ORkAIAHReFAuhQTE6Pg4GBly5ZNs2bNsjoOAOA+KBxIt7Zu3arnnntOf//9t9VRAAD3waBRpFu5c+fWhQsXrI4BAEgBCgfSrc2bN6tYsWJWxwAApABXqSDN2r17d7LLo6OjtWPHDo0YMUJDhw51cioAwMNgDAfSLLvdLpvNpuT+iObOnVv9+/fXwIEDZbPZLEgHAHgQFA6kWXcbDOrj46McOXI4OQ0A4FFQOAAAgOkYw4E06+eff07Rdk8//bTJSQAAj4ojHEiz7Pb7X0Rls9l08+ZNJ6QBADwKCgcAADAd83AgXbt27ZrVEQAAKUDhQLoUGxurzz77TIGBgVZHAQCkAIUDaVZsbKwGDRqk6tWr67HHHtOPP/4oSQoLC1NgYKA+//xzvf7669aGBACkCGM4kGYNHDhQU6dOVcOGDbVx40adO3dO3bp10+bNmzV48GA999xzcnNzszomACAFuCwWada8efP0zTff6Omnn9bevXtVsWJFxcfHa9euXcwuCgDpDEc4kGZ5eHjo2LFjKlCggCTJ29tbW7duVYUKFSxOBgB4UIzhQJp18+ZNeXh4OJ5nypRJWbNmtTARAOBhcUoFaZZhGOratas8PT0lSdevX9crr7yiLFmyJNluwYIFVsQDADwACgfSrC5duiQZq9GpUycL0wAAHgVjOAAAgOkYw4E06+jRo6IPA4BroHAgzSpRooTOnTvneN6+fXudPXvWwkQAgIdF4UCadfvRjaVLl+rKlSsWpQEAPAoKBwAAMB2FA2mWzWa7Y0ZRZhgFgPSJy2KRZjEPBwC4DgoH0qyQkJAkz5mHAwDSL+bhAAAApmMMBwAAMB2FAwAAmI7CAQAATEfhAAAApqNwAEjTpk+fruzZs1sdA8AjonAAeGhdu3Z1TNDm7u6uwMBAvfXWW7p+/XqqfUb79u116NChVHs/ANZgHg4Aj6Rp06YKCwvTjRs3tGPHDoWEhMhms+mTTz5Jlff39vaWt7d3qrwXAOtwhAPAI/H09JS/v78KFSqkVq1aqWHDhlq5cqUkKSEhQSNHjlRgYKC8vb1VqVIlzZ8/P8nrf/75Z5UoUUJeXl6qV6+eZsyYIZvNpqioKEnJn1KZPHmyihUrJg8PD5UqVUozZ85Mst5ms+nrr7/Ws88+q8yZM6tEiRL6+eefHesvXryo4OBg+fn5ydvbWyVKlFBYWFjqf3EAOFA4AKSavXv3auPGjfLw8JAkjRw5Ut98842mTJmiffv26fXXX1enTp20fv16SdKxY8fUtm1btWrVSrt27dLLL7+sd955556fsXDhQvXt21dvvPGG9u7dq5dfflndunXT2rVrk2z3wQcfqF27dtq9e7eaN2+u4OBgXbhwQZL03nvvaf/+/Vq2bJkOHDigyZMnK3fu3CZ8RQA4GADwkEJCQgw3NzcjS5YshqenpyHJsNvtxvz5843r168bmTNnNjZu3JjkNT169DA6duxoGIZhDBw40ChfvnyS9e+8844hybh48aJhGIYRFhZm+Pr6OtY/9thjxosvvpjkNc8995zRvHlzx3NJxrvvvut4fvnyZUOSsWzZMsMwDOOpp54yunXr9sj7DyDlGMMB4JHUq1dPkydP1pUrVzR27FhlypRJbdq00b59+3T16lU1atQoyfZxcXGqUqWKJOngwYOqUaNGkvU1a9a85+cdOHBAL730UpJljz/+uMaNG5dkWcWKFR3/nyVLFvn4+CgyMlKS1LNnT7Vp00Y7d+5U48aN1apVKz322GMPtuMAHgiFA8AjyZIli4oXLy5JCg0NVaVKlTRt2jSVL19ekrRkyRIVKFAgyWsS7wBsJnd39yTPbTabEhISJEnNmjXT33//raVLl2rlypVq0KCBevfurdGjR5ueC8ioGMMBINXY7XYNHjxY7777rsqWLStPT0+dOHFCxYsXT/IoVKiQJKlUqVLavn17kvfYtm3bPT+jTJky+v3335Ms+/3331W2bNkHyurn56eQkBB9++23+vzzz/Xll18+0OsBPBiOcABIVc8995wGDBigqVOn6s0339Trr7+uhIQE/e9//1N0dLR+//13+fj4KCQkRC+//LLGjBmjgQMHqkePHgoPD9f06dMl3ToikZwBAwaoXbt2qlKliho2bKhFixZpwYIFWrVqVYozDhkyRNWqVVO5cuUUGxurxYsXq0yZMqmx+wDugsIBIFVlypRJffr00ahRo3Ts2DH5+flp5MiROnr0qLJnz66qVatq8ODBkqTAwEDNnz9fb7zxhsaNG6egoCC988476tmz511Pu7Rq1Urjxo3T6NGj1bdvXwUGBiosLEx169ZNcUYPDw8NGjRIx48fl7e3t5544gl9//33qbH7AO7CZhiGYXUIAEj00UcfacqUKTp58qTVUQCkIo5wALDUpEmTVKNGDeXKlUu///67Pv30U/Xp08fqWABSGYUDgKUOHz6s4cOH68KFCypcuLDeeOMNDRo0yOpYAFIZp1QAAIDpuCwWAACYjsIBAABMR+EAAACmo3AAAADTUTgAAIDpKBwAAMB0FA4AAGA6CgcAADAdhQMAAJju/wHQg50kySpYBQAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_location['cand_domicile_region_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_location['cand_domicile_region_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Regions','Regions')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "td9kHEq-nAT9"
      },
      "source": [
        "# Reverse Dataset\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "7oQMy9UgnB7U"
      },
      "outputs": [],
      "source": [
        "dataset = \"reverse_matching_20240213\"\n",
        "df_processed = pd.read_csv(f\"Data/{dataset}_processed.csv\", sep=\";\")\n",
        "df_mitigation = df_processed.drop(columns=[\"distance_km\", \"match_score\", \"match_rank\", \"cand_id\", \"cand_education\", \"job_professional_category\"]).copy()\n",
        "columns = df_mitigation.columns\n",
        "columns = columns.drop([\"job_id\",\"job_sector\"])\n",
        "sectors = sorted(df_processed.job_sector.unique())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NbZndLRGyxZ-"
      },
      "source": [
        "## Gender"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "rrCUhJxXqR8F",
        "outputId": "4d99fd80-cc4c-4f02-817a-2d454d1af013"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "        vertical-align: top;\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cand_gender</th>\n",
              "      <th>cand_age_bucket</th>\n",
              "      <th>cand_domicile_province</th>\n",
              "      <th>cand_domicile_region</th>\n",
              "      <th>job_contract_type</th>\n",
              "      <th>job_work_province</th>\n",
              "      <th>Norvegese</th>\n",
              "      <th>Catalano</th>\n",
              "      <th>Macedone</th>\n",
              "      <th>Portoghese</th>\n",
              "      <th>...</th>\n",
              "      <th>Finlandese</th>\n",
              "      <th>Albanese</th>\n",
              "      <th>Danese</th>\n",
              "      <th>Ebraico</th>\n",
              "      <th>Spagnolo</th>\n",
              "      <th>Serbo</th>\n",
              "      <th>Greco</th>\n",
              "      <th>Cinese</th>\n",
              "      <th>Bulgaro</th>\n",
              "      <th>Rumeno</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>39.19</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.10</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.07</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.09</td>\n",
              "      <td>34.20</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>33.83</td>\n",
              "      <td>15.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.16</td>\n",
              "      <td>...</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.80</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>22.84</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>61.22</td>\n",
              "      <td>48.83</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.92</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.15</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.91</td>\n",
              "      <td>40.98</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.98</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>55.62</td>\n",
              "      <td>31.28</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.58</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>34.77</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.45</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>...</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.32</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>16.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>...</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.12</td>\n",
              "      <td>13.23</td>\n",
              "      <td>0.0</td>\n",
              "      <td>37.57</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.58</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.03</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>38.58</td>\n",
              "      <td>25.94</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>37.59</td>\n",
              "      <td>39.49</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16 rows × 28 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    cand_gender  cand_age_bucket  cand_domicile_province  \\\n",
              "0           0.0              0.0                   39.19   \n",
              "1           0.0              0.0                   52.09   \n",
              "2           0.0              0.0                   33.83   \n",
              "3           0.0              0.0                   28.80   \n",
              "4           0.0              0.0                   22.84   \n",
              "5           0.0              0.0                   61.22   \n",
              "6           0.0              0.0                   32.91   \n",
              "7           0.0              0.0                   28.98   \n",
              "8           0.0              0.0                   55.62   \n",
              "9           0.0              0.0                   34.77   \n",
              "10          0.0              0.0                   23.45   \n",
              "11          0.0              0.0                   31.32   \n",
              "12          0.0              0.0                   31.12   \n",
              "13          0.0              0.0                   32.58   \n",
              "14          0.0              0.0                   38.58   \n",
              "15          0.0              0.0                   37.59   \n",
              "\n",
              "    cand_domicile_region  job_contract_type  job_work_province  Norvegese  \\\n",
              "0                   0.00                0.0              31.10       0.04   \n",
              "1                  34.20                0.0               0.00       0.00   \n",
              "2                  15.18                0.0               0.00       0.25   \n",
              "3                   0.00                0.0               0.00       0.00   \n",
              "4                   0.00                0.0               0.00       0.03   \n",
              "5                  48.83                0.0              31.92       0.00   \n",
              "6                  40.98                0.0               0.00       0.00   \n",
              "7                   0.00                0.0               0.00       0.02   \n",
              "8                  31.28                0.0               7.58       0.04   \n",
              "9                   0.00                0.0               0.00       0.01   \n",
              "10                  0.04                0.0               0.00       0.06   \n",
              "11                  0.00                0.0              16.26       0.00   \n",
              "12                 13.23                0.0              37.57       0.03   \n",
              "13                  0.00                0.0               0.00       0.00   \n",
              "14                 25.94                0.0               0.00       0.04   \n",
              "15                 39.49                0.0               0.00       0.00   \n",
              "\n",
              "    Catalano  Macedone  Portoghese  ...  Finlandese  Albanese  Danese  \\\n",
              "0       0.01      0.00        0.07  ...        0.00      0.00    0.00   \n",
              "1       0.00      0.39        0.00  ...        0.13      0.00    0.00   \n",
              "2       0.00      0.00        0.16  ...        0.03      0.16    0.00   \n",
              "3       0.03      0.00        0.00  ...        0.00      0.00    0.00   \n",
              "4       0.00      0.00        0.01  ...        0.00      0.00    0.03   \n",
              "5       0.00      0.15        0.15  ...        0.00      0.00    0.00   \n",
              "6       0.00      0.08        0.00  ...        0.00      0.00    0.00   \n",
              "7       0.00      0.00        0.04  ...        0.00      0.00    0.00   \n",
              "8       0.03      0.02        0.01  ...        0.01      0.00    0.00   \n",
              "9       0.01      0.00        0.01  ...        0.00      0.00    0.03   \n",
              "10      0.00      0.00        0.06  ...        0.08      0.00    0.00   \n",
              "11      0.00      0.00        0.03  ...        0.01      0.00    0.00   \n",
              "12      0.00      0.00        0.01  ...        0.00      0.00    0.00   \n",
              "13      0.00      0.03        0.03  ...        0.00      0.00    0.00   \n",
              "14      0.00      0.00        0.00  ...        0.04      0.00    0.00   \n",
              "15      0.09      0.00        0.00  ...        0.00      0.09    0.00   \n",
              "\n",
              "    Ebraico  Spagnolo  Serbo  Greco  Cinese  Bulgaro  Rumeno  \n",
              "0       0.0       0.0    0.0   0.00    0.00     0.00     0.0  \n",
              "1       0.0       0.0    0.0   0.00    0.00     0.00     0.0  \n",
              "2       0.0       0.0    0.0   0.00    0.00     0.00     0.0  \n",
              "3       0.0       0.0    0.0   0.00    0.00     0.00     0.0  \n",
              "4       0.0       0.0    0.0   0.02    0.00     0.05     0.0  \n",
              "5       0.0       0.0    0.0   0.00    0.29     0.29     0.0  \n",
              "6       0.0       0.0    0.0   0.00    0.08     0.00     0.0  \n",
              "7       0.0       0.0    0.0   0.03    0.00     0.00     0.0  \n",
              "8       0.0       0.0    0.0   0.01    0.00     0.00     0.0  \n",
              "9       0.0       0.0    0.0   0.01    0.00     0.00     0.0  \n",
              "10      0.0       0.0    0.0   0.00    0.00     0.02     0.0  \n",
              "11      0.0       0.0    0.0   0.04    0.00     0.00     0.0  \n",
              "12      0.0       0.0    0.0   0.00    0.00     0.00     0.0  \n",
              "13      0.0       0.0    0.0   0.03    0.00     0.00     0.0  \n",
              "14      0.0       0.0    0.0   0.04    0.00     0.11     0.0  \n",
              "15      0.0       0.0    0.0   0.00    0.18     0.00     0.0  \n",
              "\n",
              "[16 rows x 28 columns]"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "protected_attribute_gender = \"cand_gender\"\n",
        "\n",
        "results_df_gender = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_gender,columns)\n",
        "results_df_gender.to_excel('Results/Mitigation_reverse/results_df_gender_reverse.xlsx', index=False)\n",
        "results_df_gender"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 571
        },
        "id": "YE1s4iV2xhW9",
        "outputId": "4b5b93ce-d902-43fa-c48b-f24fa141c969"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "results_df_gender_total = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_gender,columns,'total')\n",
        "sums_gender = results_df_gender_total.iloc[:, first_language_index:].sum()\n",
        "f.plot_series(sums_gender,'Removed Languages','Languages')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "_wAm1I14xnj8"
      },
      "outputs": [],
      "source": [
        "job_df_orig_gender, job_df_repaired_gender = f.compute_repaired_df(df_mitigation,5,protected_attribute_gender)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "gAJlWq9ZyOQF"
      },
      "outputs": [],
      "source": [
        "with open('utils/encodings/reverse_matching_20240213_cand_domicile_region_encoding.json', 'r') as file:\n",
        "    region_mapping = json.load(file)\n",
        "with open('utils/encodings/reverse_matching_20240213_provinces_encoding.json', 'r') as file:\n",
        "    province_mapping = json.load(file)\n",
        "\n",
        "reversed_region_mapping = {v: k for k, v in region_mapping.items()}\n",
        "reversed_province_mapping = {v: k for k, v in province_mapping.items()}\n",
        "\n",
        "job_df_orig_gender['cand_domicile_region_str'] = job_df_orig_gender['cand_domicile_region'].map(reversed_region_mapping)\n",
        "job_df_repaired_gender['cand_domicile_region_str'] = job_df_repaired_gender['cand_domicile_region'].map(reversed_region_mapping)\n",
        "\n",
        "job_df_orig_gender['cand_domicile_province_str'] = job_df_orig_gender['cand_domicile_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_gender['cand_domicile_province_str'] = job_df_repaired_gender['cand_domicile_province'].map(reversed_province_mapping)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "AbRi8kncyeX1",
        "outputId": "ec9cc275-80f1-41e3-c0e2-ddb9d221b574"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_gender['cand_domicile_region_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_gender['cand_domicile_region_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Regions','Regions')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZJfqlUsFy0NN"
      },
      "source": [
        "## Age"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "Dvq7zoXEyqVF",
        "outputId": "569580d3-0798-4ae1-fe5f-53a146ba625a"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cand_gender</th>\n",
              "      <th>cand_age_bucket</th>\n",
              "      <th>cand_domicile_province</th>\n",
              "      <th>cand_domicile_region</th>\n",
              "      <th>job_contract_type</th>\n",
              "      <th>job_work_province</th>\n",
              "      <th>Norvegese</th>\n",
              "      <th>Catalano</th>\n",
              "      <th>Macedone</th>\n",
              "      <th>Portoghese</th>\n",
              "      <th>...</th>\n",
              "      <th>Finlandese</th>\n",
              "      <th>Albanese</th>\n",
              "      <th>Danese</th>\n",
              "      <th>Ebraico</th>\n",
              "      <th>Spagnolo</th>\n",
              "      <th>Serbo</th>\n",
              "      <th>Greco</th>\n",
              "      <th>Cinese</th>\n",
              "      <th>Bulgaro</th>\n",
              "      <th>Rumeno</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.80</td>\n",
              "      <td>14.61</td>\n",
              "      <td>0.42</td>\n",
              "      <td>20.76</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.07</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>68.54</td>\n",
              "      <td>47.91</td>\n",
              "      <td>0.00</td>\n",
              "      <td>18.41</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.57</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>59.88</td>\n",
              "      <td>32.56</td>\n",
              "      <td>0.00</td>\n",
              "      <td>50.43</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.16</td>\n",
              "      <td>...</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>48.70</td>\n",
              "      <td>23.25</td>\n",
              "      <td>0.09</td>\n",
              "      <td>10.49</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.10</td>\n",
              "      <td>11.77</td>\n",
              "      <td>0.00</td>\n",
              "      <td>22.23</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>68.37</td>\n",
              "      <td>58.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>32.51</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.15</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.44</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>63.61</td>\n",
              "      <td>29.75</td>\n",
              "      <td>0.79</td>\n",
              "      <td>29.51</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>42.73</td>\n",
              "      <td>23.12</td>\n",
              "      <td>0.00</td>\n",
              "      <td>18.48</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.04</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>56.27</td>\n",
              "      <td>44.09</td>\n",
              "      <td>0.05</td>\n",
              "      <td>27.63</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>50.90</td>\n",
              "      <td>43.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24.82</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>65.07</td>\n",
              "      <td>56.45</td>\n",
              "      <td>0.27</td>\n",
              "      <td>37.91</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.06</td>\n",
              "      <td>...</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.57</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>54.94</td>\n",
              "      <td>9.40</td>\n",
              "      <td>0.11</td>\n",
              "      <td>19.87</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.03</td>\n",
              "      <td>...</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>53.91</td>\n",
              "      <td>28.75</td>\n",
              "      <td>0.00</td>\n",
              "      <td>31.58</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>37.05</td>\n",
              "      <td>45.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>9.06</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.03</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.17</td>\n",
              "      <td>66.95</td>\n",
              "      <td>0.00</td>\n",
              "      <td>37.62</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.81</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>43.48</td>\n",
              "      <td>42.57</td>\n",
              "      <td>0.00</td>\n",
              "      <td>55.34</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16 rows × 28 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    cand_gender  cand_age_bucket  cand_domicile_province  \\\n",
              "0           0.0              0.0                   45.80   \n",
              "1           0.0              0.0                   68.54   \n",
              "2           0.0              0.0                   59.88   \n",
              "3           0.0              0.0                   48.70   \n",
              "4           0.0              0.0                   52.10   \n",
              "5           0.0              0.0                   68.37   \n",
              "6           0.0              0.0                   63.61   \n",
              "7           0.0              0.0                   42.73   \n",
              "8           0.0              0.0                   56.27   \n",
              "9           0.0              0.0                   50.90   \n",
              "10          0.0              0.0                   65.07   \n",
              "11          0.0              0.0                   54.94   \n",
              "12          0.0              0.0                   53.91   \n",
              "13          0.0              0.0                   37.05   \n",
              "14          0.0              0.0                   52.17   \n",
              "15          0.0              0.0                   43.48   \n",
              "\n",
              "    cand_domicile_region  job_contract_type  job_work_province  Norvegese  \\\n",
              "0                  14.61               0.42              20.76       0.04   \n",
              "1                  47.91               0.00              18.41       0.00   \n",
              "2                  32.56               0.00              50.43       0.25   \n",
              "3                  23.25               0.09              10.49       0.00   \n",
              "4                  11.77               0.00              22.23       0.03   \n",
              "5                  58.02               0.00              32.51       0.00   \n",
              "6                  29.75               0.79              29.51       0.00   \n",
              "7                  23.12               0.00              18.48       0.02   \n",
              "8                  44.09               0.05              27.63       0.04   \n",
              "9                  43.85               0.00              24.82       0.01   \n",
              "10                 56.45               0.27              37.91       0.06   \n",
              "11                  9.40               0.11              19.87       0.00   \n",
              "12                 28.75               0.00              31.58       0.03   \n",
              "13                 45.01               0.00               9.06       0.00   \n",
              "14                 66.95               0.00              37.62       0.04   \n",
              "15                 42.57               0.00              55.34       0.00   \n",
              "\n",
              "    Catalano  Macedone  Portoghese  ...  Finlandese  Albanese  Danese  \\\n",
              "0       0.01      0.07        0.07  ...        0.00      0.26    0.00   \n",
              "1       0.00      0.39        0.00  ...        0.13      0.39    0.00   \n",
              "2       0.00      0.00        0.16  ...        0.03      0.16    0.00   \n",
              "3       0.03      0.04        0.00  ...        0.00      0.25    0.00   \n",
              "4       0.05      0.15        0.01  ...        0.02      0.14    0.03   \n",
              "5       0.00      0.15        0.15  ...        0.00      0.44    0.00   \n",
              "6       0.00      0.08        0.00  ...        0.00      0.00    0.00   \n",
              "7       0.02      0.08        0.04  ...        0.00      0.00    0.00   \n",
              "8       0.03      0.02        0.01  ...        0.01      0.00    0.00   \n",
              "9       0.01      0.01        0.01  ...        0.03      0.00    0.03   \n",
              "10      0.00      0.15        0.06  ...        0.08      0.19    0.00   \n",
              "11      0.00      0.10        0.03  ...        0.01      0.00    0.00   \n",
              "12      0.00      0.09        0.01  ...        0.00      0.00    0.00   \n",
              "13      0.00      0.03        0.03  ...        0.00      0.00    0.00   \n",
              "14      0.00      0.15        0.00  ...        0.04      0.22    0.00   \n",
              "15      0.09      0.00        0.00  ...        0.00      0.09    0.00   \n",
              "\n",
              "    Ebraico  Spagnolo  Serbo  Greco  Cinese  Bulgaro  Rumeno  \n",
              "0       0.0      0.00    0.0   0.00    0.28     0.10     0.0  \n",
              "1       0.0      4.57    0.0   0.00    0.00     0.00     0.0  \n",
              "2       0.0      0.00    0.0   0.00    0.19     0.00     0.0  \n",
              "3       0.0      0.00    0.0   0.00    0.19     0.00     0.0  \n",
              "4       0.0      0.00    0.0   0.02    0.41     0.05     0.0  \n",
              "5       0.0      0.00    0.0   0.00    0.29     0.29     0.0  \n",
              "6       0.0      0.00    0.0   0.00    0.08     0.00     0.0  \n",
              "7       0.0      0.00    0.0   0.03    0.13     0.04     0.0  \n",
              "8       0.0      0.00    0.0   0.01    0.14     0.15     0.0  \n",
              "9       0.0      0.00    0.0   0.01    0.31     0.04     0.0  \n",
              "10      0.0      0.00    0.0   0.00    0.57     0.02     0.0  \n",
              "11      0.0      0.00    0.0   0.04    0.07     0.00     0.0  \n",
              "12      0.0      0.00    0.0   0.00    0.14     0.07     0.0  \n",
              "13      0.0      0.00    0.0   0.03    0.19     0.00     0.0  \n",
              "14      0.0      0.00    0.0   0.04    0.81     0.11     0.0  \n",
              "15      0.0      0.00    0.0   0.00    0.18     0.00     0.0  \n",
              "\n",
              "[16 rows x 28 columns]"
            ]
          },
          "execution_count": 28,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "protected_attribute_age = \"cand_age_bucket\"\n",
        "\n",
        "results_df_age = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_age,columns)\n",
        "results_df_age.to_excel('Results/Mitigation_reverse/results_df_age_reverse.xlsx', index=False)\n",
        "results_df_age"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 571
        },
        "id": "jSvvixxXzL0l",
        "outputId": "4f527e8c-6466-4004-ca98-c0c3707c96fa"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "results_df_age_total = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_age,columns,'total')\n",
        "sums_age = results_df_age_total.iloc[:, first_language_index:].sum()\n",
        "f.plot_series(sums_age,'Removed Languages','Languages')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "id": "fNImGpJEzPYV"
      },
      "outputs": [],
      "source": [
        "job_df_orig_age, job_df_repaired_age = f.compute_repaired_df(df_mitigation,14,protected_attribute_age)\n",
        "job_df_orig_age['job_work_province_str'] = job_df_orig_age['job_work_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_age['job_work_province_str'] = job_df_repaired_age['job_work_province'].map(reversed_province_mapping)\n",
        "\n",
        "job_df_orig_age['cand_domicile_region_str'] = job_df_orig_age['cand_domicile_region'].map(reversed_region_mapping)\n",
        "job_df_repaired_age['cand_domicile_region_str'] = job_df_repaired_age['cand_domicile_region'].map(reversed_region_mapping)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 713
        },
        "id": "2gZworNVzia9",
        "outputId": "391206cb-8e61-4ce6-e28b-192bc263648f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1400x1000 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_age['job_work_province_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_age['job_work_province_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Job Provinces','Provinces',size=(14,10))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "q23CTkbWzwT1",
        "outputId": "061d7cba-0fae-4359-a7c7-ef1f14fd0bbd"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_age['cand_domicile_region_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_age['cand_domicile_region_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Regions','Regions')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W81j6hwwy1ac"
      },
      "source": [
        "## Location"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "tJHM1yHlz2n8",
        "outputId": "4014a79c-8cfe-45b8-ea84-02c7b7fcfb2a"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cand_gender</th>\n",
              "      <th>cand_age_bucket</th>\n",
              "      <th>cand_domicile_province</th>\n",
              "      <th>cand_domicile_region</th>\n",
              "      <th>job_contract_type</th>\n",
              "      <th>job_work_province</th>\n",
              "      <th>Norvegese</th>\n",
              "      <th>Catalano</th>\n",
              "      <th>Macedone</th>\n",
              "      <th>Portoghese</th>\n",
              "      <th>...</th>\n",
              "      <th>Albanese</th>\n",
              "      <th>Danese</th>\n",
              "      <th>Ebraico</th>\n",
              "      <th>Spagnolo</th>\n",
              "      <th>Serbo</th>\n",
              "      <th>Greco</th>\n",
              "      <th>Cinese</th>\n",
              "      <th>Bulgaro</th>\n",
              "      <th>Rumeno</th>\n",
              "      <th>same_location</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>46.03</td>\n",
              "      <td>22.64</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14.21</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>76.50</td>\n",
              "      <td>74.67</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27.94</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.42</td>\n",
              "      <td>53.30</td>\n",
              "      <td>0.0</td>\n",
              "      <td>51.66</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.16</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>66.73</td>\n",
              "      <td>0.89</td>\n",
              "      <td>0.0</td>\n",
              "      <td>18.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.70</td>\n",
              "      <td>12.04</td>\n",
              "      <td>0.0</td>\n",
              "      <td>17.57</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>77.11</td>\n",
              "      <td>22.74</td>\n",
              "      <td>0.0</td>\n",
              "      <td>50.44</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.15</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>79.35</td>\n",
              "      <td>13.53</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.44</td>\n",
              "      <td>15.58</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>57.14</td>\n",
              "      <td>16.43</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.54</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>53.76</td>\n",
              "      <td>16.22</td>\n",
              "      <td>0.0</td>\n",
              "      <td>37.78</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>83.72</td>\n",
              "      <td>56.98</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.75</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>53.50</td>\n",
              "      <td>15.32</td>\n",
              "      <td>0.0</td>\n",
              "      <td>12.90</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>41.72</td>\n",
              "      <td>12.56</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.46</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>72.39</td>\n",
              "      <td>16.08</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.12</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.65</td>\n",
              "      <td>12.90</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.36</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>86.32</td>\n",
              "      <td>23.55</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.17</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16 rows × 29 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    cand_gender  cand_age_bucket  cand_domicile_province  \\\n",
              "0           0.0              0.0                   46.03   \n",
              "1           0.0              0.0                   76.50   \n",
              "2           0.0              0.0                   52.42   \n",
              "3           0.0              0.0                   66.73   \n",
              "4           0.0              0.0                   47.70   \n",
              "5           0.0              0.0                   77.11   \n",
              "6           0.0              0.0                   79.35   \n",
              "7           0.0              0.0                   47.44   \n",
              "8           0.0              0.0                   57.14   \n",
              "9           0.0              0.0                   53.76   \n",
              "10          0.0              0.0                   83.72   \n",
              "11          0.0              0.0                   53.50   \n",
              "12          0.0              0.0                   41.72   \n",
              "13          0.0              0.0                   72.39   \n",
              "14          0.0              0.0                   52.65   \n",
              "15          0.0              0.0                   86.32   \n",
              "\n",
              "    cand_domicile_region  job_contract_type  job_work_province  Norvegese  \\\n",
              "0                  22.64                0.0              14.21       0.00   \n",
              "1                  74.67                0.0              27.94       0.00   \n",
              "2                  53.30                0.0              51.66       0.00   \n",
              "3                   0.89                0.0              18.26       0.00   \n",
              "4                  12.04                0.0              17.57       0.00   \n",
              "5                  22.74                0.0              50.44       0.00   \n",
              "6                  13.53                0.0               0.00       0.00   \n",
              "7                  15.58                0.0              27.09       0.00   \n",
              "8                  16.43                0.0               1.54       0.00   \n",
              "9                  16.22                0.0              37.78       0.01   \n",
              "10                 56.98                0.0               9.75       0.00   \n",
              "11                 15.32                0.0              12.90       0.00   \n",
              "12                 12.56                0.0               9.46       0.00   \n",
              "13                 16.08                0.0               1.12       0.00   \n",
              "14                 12.90                0.0              45.36       0.04   \n",
              "15                 23.55                0.0               3.17       0.00   \n",
              "\n",
              "    Catalano  Macedone  Portoghese  ...  Albanese  Danese  Ebraico  Spagnolo  \\\n",
              "0       0.01      0.00        0.00  ...      0.00    0.00      0.0       0.0   \n",
              "1       0.00      0.39        0.00  ...      0.00    0.00      0.0       0.0   \n",
              "2       0.00      0.00        0.16  ...      0.00    0.00      0.0       0.0   \n",
              "3       0.00      0.00        0.00  ...      0.00    0.00      0.0       0.0   \n",
              "4       0.00      0.00        0.01  ...      0.00    0.03      0.0       0.0   \n",
              "5       0.00      0.15        0.15  ...      0.00    0.00      0.0       0.0   \n",
              "6       0.00      0.08        0.00  ...      0.00    0.00      0.0       0.0   \n",
              "7       0.02      0.00        0.00  ...      0.00    0.00      0.0       0.0   \n",
              "8       0.03      0.02        0.01  ...      0.00    0.00      0.0       0.0   \n",
              "9       0.00      0.00        0.01  ...      0.00    0.00      0.0       0.0   \n",
              "10      0.00      0.00        0.06  ...      0.00    0.00      0.0       0.0   \n",
              "11      0.00      0.00        0.03  ...      0.00    0.00      0.0       0.0   \n",
              "12      0.00      0.00        0.01  ...      0.00    0.00      0.0       0.0   \n",
              "13      0.00      0.00        0.03  ...      0.00    0.00      0.0       0.0   \n",
              "14      0.00      0.15        0.00  ...      0.00    0.00      0.0       0.0   \n",
              "15      0.09      0.00        0.00  ...      0.09    0.00      0.0       0.0   \n",
              "\n",
              "    Serbo  Greco  Cinese  Bulgaro  Rumeno  same_location  \n",
              "0     0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "1     0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "2     0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "3     0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "4     0.0   0.02    0.00     0.00     0.0            0.0  \n",
              "5     0.0   0.00    0.29     0.29     0.0            0.0  \n",
              "6     0.0   0.00    0.08     0.00     0.0            0.0  \n",
              "7     0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "8     0.0   0.01    0.00     0.00     0.0            0.0  \n",
              "9     0.0   0.01    0.00     0.00     0.0            0.0  \n",
              "10    0.0   0.00    0.00     0.02     0.0            0.0  \n",
              "11    0.0   0.04    0.00     0.00     0.0            0.0  \n",
              "12    0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "13    0.0   0.03    0.00     0.00     0.0            0.0  \n",
              "14    0.0   0.04    0.00     0.11     0.0            0.0  \n",
              "15    0.0   0.00    0.00     0.00     0.0            0.0  \n",
              "\n",
              "[16 rows x 29 columns]"
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "protected_attribute_location = \"same_location\"\n",
        "results_df_location = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_location,columns)\n",
        "results_df_location.to_excel('Results/Mitigation_reverse/results_df_location_reverse.xlsx', index=False)\n",
        "results_df_location"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 571
        },
        "id": "MzEJ3SJLy3V9",
        "outputId": "25c5719f-c2a8-4051-caf0-37ccf6d48eca"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "results_df_location_total = f.compute_bias_differences_percentage(df_mitigation,sectors,protected_attribute_location,columns,'total')\n",
        "sums_location = results_df_location_total.iloc[:, first_language_index:-1].sum()\n",
        "f.plot_series(sums_location,'Removed Languages','Languages')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "id": "6UALacFE0FHl"
      },
      "outputs": [],
      "source": [
        "job_df_orig_location, job_df_repaired_location = f.compute_repaired_df(df_mitigation,1,protected_attribute_location)\n",
        "job_df_orig_location['job_work_province_str'] = job_df_orig_location['job_work_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_location['job_work_province_str'] = job_df_repaired_location['job_work_province'].map(reversed_province_mapping)\n",
        "\n",
        "job_df_orig_location['cand_domicile_province_str'] = job_df_orig_location['cand_domicile_province'].map(reversed_province_mapping)\n",
        "job_df_repaired_location['cand_domicile_province_str'] = job_df_repaired_location['cand_domicile_province'].map(reversed_province_mapping)\n",
        "\n",
        "job_df_orig_location['cand_domicile_region_str'] = job_df_orig_location['cand_domicile_region'].map(reversed_region_mapping)\n",
        "job_df_repaired_location['cand_domicile_region_str'] = job_df_repaired_location['cand_domicile_region'].map(reversed_region_mapping)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 740
        },
        "id": "NM_1SHMH0LXN",
        "outputId": "5dcc148c-feb5-45b9-a13b-a8d5ca1eecec"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1600x1200 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_location['job_work_province_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_location['job_work_province_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Job Provinces','Provinces',size=(16,12))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "TQxvI2ho0Stm",
        "outputId": "b0ad8def-29b0-4784-ba25-8506aef9ab53"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "orig_counts = job_df_orig_location['cand_domicile_region_str'].value_counts()\n",
        "repaired_counts = job_df_repaired_location['cand_domicile_region_str'].value_counts()\n",
        "\n",
        "orig_counts,repaired_counts,all_index = f.prepare_different_series(orig_counts,repaired_counts)\n",
        "f.compare_plot(orig_counts,repaired_counts,all_index,'Comparison of Regions','Regions')"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "base",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.11.9"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}