bias_investiagtion.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "356015b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from aequitas.group import Group\n",
    "from aequitas.bias import Bias\n",
    "from aequitas.fairness import Fairness\n",
    "import aequitas.plot as ap\n",
    "import numpy as np\n",
    "\n",
    "# Enable Pandas to display dataframes without restriction.\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6bc9e4b5",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
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       "      <th>hours-per-week</th>\n",
       "      <th>native-country</th>\n",
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       "      <td>0</td>\n",
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       "      <td>Asian-Pac-Islander</td>\n",
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       "      <td>0</td>\n",
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       "      <td>Philippines</td>\n",
       "      <td>&lt;=50K</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>Private</td>\n",
       "      <td>188236</td>\n",
       "      <td>10th</td>\n",
       "      <td>6</td>\n",
       "      <td>Widowed</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
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       "      <td>87158</td>\n",
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       "      <td>Private</td>\n",
       "      <td>125000</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Unmarried</td>\n",
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       "      <td>United-States</td>\n",
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       "      <td>9</td>\n",
       "      <td>Never-married</td>\n",
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       "      <td>7</td>\n",
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       "      <td>163303</td>\n",
       "      <td>Assoc-voc</td>\n",
       "      <td>11</td>\n",
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       "      <th>9</th>\n",
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       "      <td>57</td>\n",
       "      <td>Federal-gov</td>\n",
       "      <td>414994</td>\n",
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      "text/plain": [
       "   Unnamed: 0  age         workclass   fnlgt     education  education-num  \\\n",
       "0           0   53  Self-emp-not-inc  168539           9th              5   \n",
       "1           1   49  Self-emp-not-inc   56841     Bachelors             13   \n",
       "2           2   28           Private  154571  Some-college             10   \n",
       "3           3   60           Private  188236          10th              6   \n",
       "4           4   53           Private   87158       HS-grad              9   \n",
       "5           5   55           Private  125000       Masters             14   \n",
       "6           6   27           Private  376936       HS-grad              9   \n",
       "7           7   31           Private  163303     Assoc-voc             11   \n",
       "8           8   30           Private  112650       HS-grad              9   \n",
       "9           9   57       Federal-gov  414994  Some-college             10   \n",
       "\n",
       "       marital-status       occupation   relationship                race  \\\n",
       "0  Married-civ-spouse  Farming-fishing        Husband               White   \n",
       "1  Married-civ-spouse  Farming-fishing        Husband               White   \n",
       "2  Married-civ-spouse  Exec-managerial        Husband  Asian-Pac-Islander   \n",
       "3             Widowed     Tech-support      Unmarried               White   \n",
       "4  Married-civ-spouse     Craft-repair        Husband               Black   \n",
       "5            Divorced  Exec-managerial      Unmarried               White   \n",
       "6       Never-married     Craft-repair  Not-in-family               White   \n",
       "7            Divorced            Sales      Own-child               White   \n",
       "8            Divorced     Craft-repair      Own-child               White   \n",
       "9  Married-civ-spouse  Exec-managerial        Husband               White   \n",
       "\n",
       "      sex  capital-gain  capital-loss  hours-per-week native-country salary  \\\n",
       "0    Male             0             0              70  United-States  <=50K   \n",
       "1    Male             0             0              70  United-States  <=50K   \n",
       "2    Male             0             0              40    Philippines  <=50K   \n",
       "3  Female             0             0              40  United-States  <=50K   \n",
       "4    Male             0             0              40  United-States  <=50K   \n",
       "5    Male             0             0              40  United-States   >50K   \n",
       "6    Male             0             0              40  United-States  <=50K   \n",
       "7  Female             0             0              38  United-States  <=50K   \n",
       "8    Male             0             0              40  United-States  <=50K   \n",
       "9    Male             0             0              40  United-States   >50K   \n",
       "\n",
       "   label_value  score  \n",
       "0            0      0  \n",
       "1            0      0  \n",
       "2            0      0  \n",
       "3            0      0  \n",
       "4            0      0  \n",
       "5            1      1  \n",
       "6            0      0  \n",
       "7            0      0  \n",
       "8            0      0  \n",
       "9            1      1  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"bias_analysis_data.csv\")\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "57419e8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "str_cols = [\"race\", \"sex\", \"native-country\", \"score\", \"label_value\"]\n",
    "df = df.astype({col:\"str\" for col in df.columns if col not in [\"score\", \"label_value\"]})\n",
    "df = df[str_cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "067b10ab",
   "metadata": {},
   "outputs": [
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       "      <td>Female</td>\n",
       "      <td>0.998876</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001124</td>\n",
       "      <td>0.999856</td>\n",
       "      <td>1.0</td>\n",
       "      <td>889</td>\n",
       "      <td>6932</td>\n",
       "      <td>0.148762</td>\n",
       "      <td>0.113668</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6931</td>\n",
       "      <td>889</td>\n",
       "      <td>890</td>\n",
       "      <td>6931</td>\n",
       "      <td>7821</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.113796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>sex</td>\n",
       "      <td>Male</td>\n",
       "      <td>0.999803</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.999911</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5087</td>\n",
       "      <td>11221</td>\n",
       "      <td>0.851238</td>\n",
       "      <td>0.311933</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11220</td>\n",
       "      <td>5087</td>\n",
       "      <td>5088</td>\n",
       "      <td>11220</td>\n",
       "      <td>16308</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.311994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>Cambodia</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.266667</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>15</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>Canada</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>0.005020</td>\n",
       "      <td>0.340909</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>58</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>88</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.340909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>China</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>0.003179</td>\n",
       "      <td>0.339286</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>56</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.339286</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   model_id score_threshold     k  attribute_name     attribute_value  \\\n",
       "0         0      binary 0/1  5976            race  Amer-Indian-Eskimo   \n",
       "1         0      binary 0/1  5976            race  Asian-Pac-Islander   \n",
       "2         0      binary 0/1  5976            race               Black   \n",
       "3         0      binary 0/1  5976            race               Other   \n",
       "4         0      binary 0/1  5976            race               White   \n",
       "5         0      binary 0/1  5976             sex              Female   \n",
       "6         0      binary 0/1  5976             sex                Male   \n",
       "7         0      binary 0/1  5976  native-country            Cambodia   \n",
       "8         0      binary 0/1  5976  native-country              Canada   \n",
       "9         0      binary 0/1  5976  native-country               China   \n",
       "\n",
       "        tpr  tnr       for  fdr  fpr       fnr       npv  precision    pp  \\\n",
       "0  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    28   \n",
       "1  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0   197   \n",
       "2  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0   290   \n",
       "3  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    15   \n",
       "4  0.999633  1.0  0.000131  0.0  0.0  0.000367  0.999869        1.0  5446   \n",
       "5  0.998876  1.0  0.000144  0.0  0.0  0.001124  0.999856        1.0   889   \n",
       "6  0.999803  1.0  0.000089  0.0  0.0  0.000197  0.999911        1.0  5087   \n",
       "7  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0     4   \n",
       "8  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    30   \n",
       "9  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    19   \n",
       "\n",
       "      pn       ppr     pprev  fp  fn     tn    tp  group_label_pos  \\\n",
       "0    204  0.004685  0.120690   0   0    204    28               28   \n",
       "1    511  0.032965  0.278249   0   0    511   197              197   \n",
       "2   1951  0.048527  0.129407   0   0   1951   290              290   \n",
       "3    176  0.002510  0.078534   0   0    176    15               15   \n",
       "4  15311  0.911312  0.262369   0   2  15309  5446             5448   \n",
       "5   6932  0.148762  0.113668   0   1   6931   889              890   \n",
       "6  11221  0.851238  0.311933   0   1  11220  5087             5088   \n",
       "7     11  0.000669  0.266667   0   0     11     4                4   \n",
       "8     58  0.005020  0.340909   0   0     58    30               30   \n",
       "9     37  0.003179  0.339286   0   0     37    19               19   \n",
       "\n",
       "   group_label_neg  group_size  total_entities      prev  \n",
       "0              204         232           24129  0.120690  \n",
       "1              511         708           24129  0.278249  \n",
       "2             1951        2241           24129  0.129407  \n",
       "3              176         191           24129  0.078534  \n",
       "4            15309       20757           24129  0.262466  \n",
       "5             6931        7821           24129  0.113796  \n",
       "6            11220       16308           24129  0.311994  \n",
       "7               11          15           24129  0.266667  \n",
       "8               58          88           24129  0.340909  \n",
       "9               37          56           24129  0.339286  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group = Group()\n",
    "xtab, _ = group.get_crosstabs(df)\n",
    "\n",
    "xtab.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4a8d5af2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "get_disparity_major_group()\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model_id</th>\n",
       "      <th>score_threshold</th>\n",
       "      <th>k</th>\n",
       "      <th>attribute_name</th>\n",
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       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>204</td>\n",
       "      <td>232</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.120690</td>\n",
       "      <td>0.005141</td>\n",
       "      <td>0.459999</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000131</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
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       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
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       "      <td>binary 0/1</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>1951</td>\n",
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       "      <td>1951</td>\n",
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       "      <td>1.000367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000131</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
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       "      <th>3</th>\n",
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       "      <td>binary 0/1</td>\n",
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       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
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       "      <td>5446</td>\n",
       "      <td>15311</td>\n",
       "      <td>0.911312</td>\n",
       "      <td>0.262369</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>15309</td>\n",
       "      <td>5446</td>\n",
       "      <td>5448</td>\n",
       "      <td>15309</td>\n",
       "      <td>20757</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.262466</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>sex</td>\n",
       "      <td>Female</td>\n",
       "      <td>0.998876</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001124</td>\n",
       "      <td>0.999856</td>\n",
       "      <td>1.0</td>\n",
       "      <td>889</td>\n",
       "      <td>6932</td>\n",
       "      <td>0.148762</td>\n",
       "      <td>0.113668</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6931</td>\n",
       "      <td>889</td>\n",
       "      <td>890</td>\n",
       "      <td>6931</td>\n",
       "      <td>7821</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.113796</td>\n",
       "      <td>0.174759</td>\n",
       "      <td>0.364400</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.618725</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.716854</td>\n",
       "      <td>0.999073</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.999945</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>sex</td>\n",
       "      <td>Male</td>\n",
       "      <td>0.999803</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.999911</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5087</td>\n",
       "      <td>11221</td>\n",
       "      <td>0.851238</td>\n",
       "      <td>0.311933</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11220</td>\n",
       "      <td>5087</td>\n",
       "      <td>5088</td>\n",
       "      <td>11220</td>\n",
       "      <td>16308</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.311994</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>Cambodia</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.266667</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>15</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.266667</td>\n",
       "      <td>0.000719</td>\n",
       "      <td>1.053628</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000122</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>Canada</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>0.005020</td>\n",
       "      <td>0.340909</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>58</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>88</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.340909</td>\n",
       "      <td>0.005393</td>\n",
       "      <td>1.346968</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000122</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>China</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>0.003179</td>\n",
       "      <td>0.339286</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>56</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.339286</td>\n",
       "      <td>0.003415</td>\n",
       "      <td>1.340554</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000122</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   model_id score_threshold     k  attribute_name     attribute_value  \\\n",
       "0         0      binary 0/1  5976            race  Amer-Indian-Eskimo   \n",
       "1         0      binary 0/1  5976            race  Asian-Pac-Islander   \n",
       "2         0      binary 0/1  5976            race               Black   \n",
       "3         0      binary 0/1  5976            race               Other   \n",
       "4         0      binary 0/1  5976            race               White   \n",
       "5         0      binary 0/1  5976             sex              Female   \n",
       "6         0      binary 0/1  5976             sex                Male   \n",
       "7         0      binary 0/1  5976  native-country            Cambodia   \n",
       "8         0      binary 0/1  5976  native-country              Canada   \n",
       "9         0      binary 0/1  5976  native-country               China   \n",
       "\n",
       "        tpr  tnr       for  fdr  fpr       fnr       npv  precision    pp  \\\n",
       "0  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    28   \n",
       "1  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0   197   \n",
       "2  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0   290   \n",
       "3  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    15   \n",
       "4  0.999633  1.0  0.000131  0.0  0.0  0.000367  0.999869        1.0  5446   \n",
       "5  0.998876  1.0  0.000144  0.0  0.0  0.001124  0.999856        1.0   889   \n",
       "6  0.999803  1.0  0.000089  0.0  0.0  0.000197  0.999911        1.0  5087   \n",
       "7  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0     4   \n",
       "8  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    30   \n",
       "9  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    19   \n",
       "\n",
       "      pn       ppr     pprev  fp  fn     tn    tp  group_label_pos  \\\n",
       "0    204  0.004685  0.120690   0   0    204    28               28   \n",
       "1    511  0.032965  0.278249   0   0    511   197              197   \n",
       "2   1951  0.048527  0.129407   0   0   1951   290              290   \n",
       "3    176  0.002510  0.078534   0   0    176    15               15   \n",
       "4  15311  0.911312  0.262369   0   2  15309  5446             5448   \n",
       "5   6932  0.148762  0.113668   0   1   6931   889              890   \n",
       "6  11221  0.851238  0.311933   0   1  11220  5087             5088   \n",
       "7     11  0.000669  0.266667   0   0     11     4                4   \n",
       "8     58  0.005020  0.340909   0   0     58    30               30   \n",
       "9     37  0.003179  0.339286   0   0     37    19               19   \n",
       "\n",
       "   group_label_neg  group_size  total_entities      prev  ppr_disparity  \\\n",
       "0              204         232           24129  0.120690       0.005141   \n",
       "1              511         708           24129  0.278249       0.036173   \n",
       "2             1951        2241           24129  0.129407       0.053250   \n",
       "3              176         191           24129  0.078534       0.002754   \n",
       "4            15309       20757           24129  0.262466       1.000000   \n",
       "5             6931        7821           24129  0.113796       0.174759   \n",
       "6            11220       16308           24129  0.311994       1.000000   \n",
       "7               11          15           24129  0.266667       0.000719   \n",
       "8               58          88           24129  0.340909       0.005393   \n",
       "9               37          56           24129  0.339286       0.003415   \n",
       "\n",
       "   pprev_disparity  precision_disparity  fdr_disparity  for_disparity  \\\n",
       "0         0.459999                  1.0            NaN       0.000000   \n",
       "1         1.060523                  1.0            NaN       0.000000   \n",
       "2         0.493223                  1.0            NaN       0.000000   \n",
       "3         0.299326                  1.0            NaN       0.000000   \n",
       "4         1.000000                  1.0            NaN       1.000000   \n",
       "5         0.364400                  1.0            NaN       1.618725   \n",
       "6         1.000000                  1.0            NaN       1.000000   \n",
       "7         1.053628                  1.0            NaN       0.000000   \n",
       "8         1.346968                  1.0            NaN       0.000000   \n",
       "9         1.340554                  1.0            NaN       0.000000   \n",
       "\n",
       "   fpr_disparity  fnr_disparity  tpr_disparity  tnr_disparity  npv_disparity  \\\n",
       "0            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "1            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "2            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "3            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "4            NaN       1.000000       1.000000            1.0       1.000000   \n",
       "5            NaN       5.716854       0.999073            1.0       0.999945   \n",
       "6            NaN       1.000000       1.000000            1.0       1.000000   \n",
       "7            NaN       0.000000       1.000360            1.0       1.000122   \n",
       "8            NaN       0.000000       1.000360            1.0       1.000122   \n",
       "9            NaN       0.000000       1.000360            1.0       1.000122   \n",
       "\n",
       "  ppr_ref_group_value pprev_ref_group_value precision_ref_group_value  \\\n",
       "0               White                 White                     White   \n",
       "1               White                 White                     White   \n",
       "2               White                 White                     White   \n",
       "3               White                 White                     White   \n",
       "4               White                 White                     White   \n",
       "5                Male                  Male                      Male   \n",
       "6                Male                  Male                      Male   \n",
       "7       United-States         United-States             United-States   \n",
       "8       United-States         United-States             United-States   \n",
       "9       United-States         United-States             United-States   \n",
       "\n",
       "  fdr_ref_group_value for_ref_group_value fpr_ref_group_value  \\\n",
       "0               White               White               White   \n",
       "1               White               White               White   \n",
       "2               White               White               White   \n",
       "3               White               White               White   \n",
       "4               White               White               White   \n",
       "5                Male                Male                Male   \n",
       "6                Male                Male                Male   \n",
       "7       United-States       United-States       United-States   \n",
       "8       United-States       United-States       United-States   \n",
       "9       United-States       United-States       United-States   \n",
       "\n",
       "  fnr_ref_group_value tpr_ref_group_value tnr_ref_group_value  \\\n",
       "0               White               White               White   \n",
       "1               White               White               White   \n",
       "2               White               White               White   \n",
       "3               White               White               White   \n",
       "4               White               White               White   \n",
       "5                Male                Male                Male   \n",
       "6                Male                Male                Male   \n",
       "7       United-States       United-States       United-States   \n",
       "8       United-States       United-States       United-States   \n",
       "9       United-States       United-States       United-States   \n",
       "\n",
       "  npv_ref_group_value  \n",
       "0               White  \n",
       "1               White  \n",
       "2               White  \n",
       "3               White  \n",
       "4               White  \n",
       "5                Male  \n",
       "6                Male  \n",
       "7       United-States  \n",
       "8       United-States  \n",
       "9       United-States  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_df = bias.get_disparity_major_group(xtab,\n",
    "                               original_df=df,\n",
    "                               alpha=0.05,\n",
    "                               mask_significance=True).head(10)\n",
    "bias_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5fdd5584",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model_id</th>\n",
       "      <th>score_threshold</th>\n",
       "      <th>k</th>\n",
       "      <th>attribute_name</th>\n",
       "      <th>attribute_value</th>\n",
       "      <th>tpr</th>\n",
       "      <th>tnr</th>\n",
       "      <th>for</th>\n",
       "      <th>fdr</th>\n",
       "      <th>fpr</th>\n",
       "      <th>fnr</th>\n",
       "      <th>npv</th>\n",
       "      <th>precision</th>\n",
       "      <th>pp</th>\n",
       "      <th>pn</th>\n",
       "      <th>ppr</th>\n",
       "      <th>pprev</th>\n",
       "      <th>fp</th>\n",
       "      <th>fn</th>\n",
       "      <th>tn</th>\n",
       "      <th>tp</th>\n",
       "      <th>group_label_pos</th>\n",
       "      <th>group_label_neg</th>\n",
       "      <th>group_size</th>\n",
       "      <th>total_entities</th>\n",
       "      <th>prev</th>\n",
       "      <th>ppr_disparity</th>\n",
       "      <th>pprev_disparity</th>\n",
       "      <th>precision_disparity</th>\n",
       "      <th>fdr_disparity</th>\n",
       "      <th>for_disparity</th>\n",
       "      <th>fpr_disparity</th>\n",
       "      <th>fnr_disparity</th>\n",
       "      <th>tpr_disparity</th>\n",
       "      <th>tnr_disparity</th>\n",
       "      <th>npv_disparity</th>\n",
       "      <th>ppr_ref_group_value</th>\n",
       "      <th>pprev_ref_group_value</th>\n",
       "      <th>precision_ref_group_value</th>\n",
       "      <th>fdr_ref_group_value</th>\n",
       "      <th>for_ref_group_value</th>\n",
       "      <th>fpr_ref_group_value</th>\n",
       "      <th>fnr_ref_group_value</th>\n",
       "      <th>tpr_ref_group_value</th>\n",
       "      <th>tnr_ref_group_value</th>\n",
       "      <th>npv_ref_group_value</th>\n",
       "      <th>Statistical Parity</th>\n",
       "      <th>Impact Parity</th>\n",
       "      <th>FDR Parity</th>\n",
       "      <th>FPR Parity</th>\n",
       "      <th>FOR Parity</th>\n",
       "      <th>FNR Parity</th>\n",
       "      <th>TPR Parity</th>\n",
       "      <th>TNR Parity</th>\n",
       "      <th>NPV Parity</th>\n",
       "      <th>Precision Parity</th>\n",
       "      <th>TypeI Parity</th>\n",
       "      <th>TypeII Parity</th>\n",
       "      <th>Equalized Odds</th>\n",
       "      <th>Unsupervised Fairness</th>\n",
       "      <th>Supervised Fairness</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>race</td>\n",
       "      <td>Amer-Indian-Eskimo</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28</td>\n",
       "      <td>204</td>\n",
       "      <td>0.004685</td>\n",
       "      <td>0.120690</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>204</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>204</td>\n",
       "      <td>232</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.120690</td>\n",
       "      <td>0.005141</td>\n",
       "      <td>0.459999</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000131</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>race</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>197</td>\n",
       "      <td>511</td>\n",
       "      <td>0.032965</td>\n",
       "      <td>0.278249</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>511</td>\n",
       "      <td>197</td>\n",
       "      <td>197</td>\n",
       "      <td>511</td>\n",
       "      <td>708</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.278249</td>\n",
       "      <td>0.036173</td>\n",
       "      <td>1.060523</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000131</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>race</td>\n",
       "      <td>Black</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>290</td>\n",
       "      <td>1951</td>\n",
       "      <td>0.048527</td>\n",
       "      <td>0.129407</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1951</td>\n",
       "      <td>290</td>\n",
       "      <td>290</td>\n",
       "      <td>1951</td>\n",
       "      <td>2241</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.129407</td>\n",
       "      <td>0.053250</td>\n",
       "      <td>0.493223</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000131</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>race</td>\n",
       "      <td>Other</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15</td>\n",
       "      <td>176</td>\n",
       "      <td>0.002510</td>\n",
       "      <td>0.078534</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>176</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>176</td>\n",
       "      <td>191</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.078534</td>\n",
       "      <td>0.002754</td>\n",
       "      <td>0.299326</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000131</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>race</td>\n",
       "      <td>White</td>\n",
       "      <td>0.999633</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000367</td>\n",
       "      <td>0.999869</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5446</td>\n",
       "      <td>15311</td>\n",
       "      <td>0.911312</td>\n",
       "      <td>0.262369</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>15309</td>\n",
       "      <td>5446</td>\n",
       "      <td>5448</td>\n",
       "      <td>15309</td>\n",
       "      <td>20757</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.262466</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>White</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>sex</td>\n",
       "      <td>Female</td>\n",
       "      <td>0.998876</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000144</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001124</td>\n",
       "      <td>0.999856</td>\n",
       "      <td>1.0</td>\n",
       "      <td>889</td>\n",
       "      <td>6932</td>\n",
       "      <td>0.148762</td>\n",
       "      <td>0.113668</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6931</td>\n",
       "      <td>889</td>\n",
       "      <td>890</td>\n",
       "      <td>6931</td>\n",
       "      <td>7821</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.113796</td>\n",
       "      <td>0.174759</td>\n",
       "      <td>0.364400</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.618725</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.716854</td>\n",
       "      <td>0.999073</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.999945</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>sex</td>\n",
       "      <td>Male</td>\n",
       "      <td>0.999803</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.999911</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5087</td>\n",
       "      <td>11221</td>\n",
       "      <td>0.851238</td>\n",
       "      <td>0.311933</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11220</td>\n",
       "      <td>5087</td>\n",
       "      <td>5088</td>\n",
       "      <td>11220</td>\n",
       "      <td>16308</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.311994</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>Male</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>Cambodia</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.266667</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>15</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.266667</td>\n",
       "      <td>0.000719</td>\n",
       "      <td>1.053628</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000122</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>Canada</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>0.005020</td>\n",
       "      <td>0.340909</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>58</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>88</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.340909</td>\n",
       "      <td>0.005393</td>\n",
       "      <td>1.346968</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000122</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>binary 0/1</td>\n",
       "      <td>5976</td>\n",
       "      <td>native-country</td>\n",
       "      <td>China</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>0.003179</td>\n",
       "      <td>0.339286</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>56</td>\n",
       "      <td>24129</td>\n",
       "      <td>0.339286</td>\n",
       "      <td>0.003415</td>\n",
       "      <td>1.340554</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000122</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>United-States</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   model_id score_threshold     k  attribute_name     attribute_value  \\\n",
       "0         0      binary 0/1  5976            race  Amer-Indian-Eskimo   \n",
       "1         0      binary 0/1  5976            race  Asian-Pac-Islander   \n",
       "2         0      binary 0/1  5976            race               Black   \n",
       "3         0      binary 0/1  5976            race               Other   \n",
       "4         0      binary 0/1  5976            race               White   \n",
       "5         0      binary 0/1  5976             sex              Female   \n",
       "6         0      binary 0/1  5976             sex                Male   \n",
       "7         0      binary 0/1  5976  native-country            Cambodia   \n",
       "8         0      binary 0/1  5976  native-country              Canada   \n",
       "9         0      binary 0/1  5976  native-country               China   \n",
       "\n",
       "        tpr  tnr       for  fdr  fpr       fnr       npv  precision    pp  \\\n",
       "0  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    28   \n",
       "1  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0   197   \n",
       "2  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0   290   \n",
       "3  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    15   \n",
       "4  0.999633  1.0  0.000131  0.0  0.0  0.000367  0.999869        1.0  5446   \n",
       "5  0.998876  1.0  0.000144  0.0  0.0  0.001124  0.999856        1.0   889   \n",
       "6  0.999803  1.0  0.000089  0.0  0.0  0.000197  0.999911        1.0  5087   \n",
       "7  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0     4   \n",
       "8  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    30   \n",
       "9  1.000000  1.0  0.000000  0.0  0.0  0.000000  1.000000        1.0    19   \n",
       "\n",
       "      pn       ppr     pprev  fp  fn     tn    tp  group_label_pos  \\\n",
       "0    204  0.004685  0.120690   0   0    204    28               28   \n",
       "1    511  0.032965  0.278249   0   0    511   197              197   \n",
       "2   1951  0.048527  0.129407   0   0   1951   290              290   \n",
       "3    176  0.002510  0.078534   0   0    176    15               15   \n",
       "4  15311  0.911312  0.262369   0   2  15309  5446             5448   \n",
       "5   6932  0.148762  0.113668   0   1   6931   889              890   \n",
       "6  11221  0.851238  0.311933   0   1  11220  5087             5088   \n",
       "7     11  0.000669  0.266667   0   0     11     4                4   \n",
       "8     58  0.005020  0.340909   0   0     58    30               30   \n",
       "9     37  0.003179  0.339286   0   0     37    19               19   \n",
       "\n",
       "   group_label_neg  group_size  total_entities      prev  ppr_disparity  \\\n",
       "0              204         232           24129  0.120690       0.005141   \n",
       "1              511         708           24129  0.278249       0.036173   \n",
       "2             1951        2241           24129  0.129407       0.053250   \n",
       "3              176         191           24129  0.078534       0.002754   \n",
       "4            15309       20757           24129  0.262466       1.000000   \n",
       "5             6931        7821           24129  0.113796       0.174759   \n",
       "6            11220       16308           24129  0.311994       1.000000   \n",
       "7               11          15           24129  0.266667       0.000719   \n",
       "8               58          88           24129  0.340909       0.005393   \n",
       "9               37          56           24129  0.339286       0.003415   \n",
       "\n",
       "   pprev_disparity  precision_disparity  fdr_disparity  for_disparity  \\\n",
       "0         0.459999                  1.0            NaN       0.000000   \n",
       "1         1.060523                  1.0            NaN       0.000000   \n",
       "2         0.493223                  1.0            NaN       0.000000   \n",
       "3         0.299326                  1.0            NaN       0.000000   \n",
       "4         1.000000                  1.0            NaN       1.000000   \n",
       "5         0.364400                  1.0            NaN       1.618725   \n",
       "6         1.000000                  1.0            NaN       1.000000   \n",
       "7         1.053628                  1.0            NaN       0.000000   \n",
       "8         1.346968                  1.0            NaN       0.000000   \n",
       "9         1.340554                  1.0            NaN       0.000000   \n",
       "\n",
       "   fpr_disparity  fnr_disparity  tpr_disparity  tnr_disparity  npv_disparity  \\\n",
       "0            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "1            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "2            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "3            NaN       0.000000       1.000367            1.0       1.000131   \n",
       "4            NaN       1.000000       1.000000            1.0       1.000000   \n",
       "5            NaN       5.716854       0.999073            1.0       0.999945   \n",
       "6            NaN       1.000000       1.000000            1.0       1.000000   \n",
       "7            NaN       0.000000       1.000360            1.0       1.000122   \n",
       "8            NaN       0.000000       1.000360            1.0       1.000122   \n",
       "9            NaN       0.000000       1.000360            1.0       1.000122   \n",
       "\n",
       "  ppr_ref_group_value pprev_ref_group_value precision_ref_group_value  \\\n",
       "0               White                 White                     White   \n",
       "1               White                 White                     White   \n",
       "2               White                 White                     White   \n",
       "3               White                 White                     White   \n",
       "4               White                 White                     White   \n",
       "5                Male                  Male                      Male   \n",
       "6                Male                  Male                      Male   \n",
       "7       United-States         United-States             United-States   \n",
       "8       United-States         United-States             United-States   \n",
       "9       United-States         United-States             United-States   \n",
       "\n",
       "  fdr_ref_group_value for_ref_group_value fpr_ref_group_value  \\\n",
       "0               White               White               White   \n",
       "1               White               White               White   \n",
       "2               White               White               White   \n",
       "3               White               White               White   \n",
       "4               White               White               White   \n",
       "5                Male                Male                Male   \n",
       "6                Male                Male                Male   \n",
       "7       United-States       United-States       United-States   \n",
       "8       United-States       United-States       United-States   \n",
       "9       United-States       United-States       United-States   \n",
       "\n",
       "  fnr_ref_group_value tpr_ref_group_value tnr_ref_group_value  \\\n",
       "0               White               White               White   \n",
       "1               White               White               White   \n",
       "2               White               White               White   \n",
       "3               White               White               White   \n",
       "4               White               White               White   \n",
       "5                Male                Male                Male   \n",
       "6                Male                Male                Male   \n",
       "7       United-States       United-States       United-States   \n",
       "8       United-States       United-States       United-States   \n",
       "9       United-States       United-States       United-States   \n",
       "\n",
       "  npv_ref_group_value  Statistical Parity  Impact Parity  FDR Parity  \\\n",
       "0               White               False          False         NaN   \n",
       "1               White               False           True         NaN   \n",
       "2               White               False          False         NaN   \n",
       "3               White               False          False         NaN   \n",
       "4               White                True           True         NaN   \n",
       "5                Male               False          False         NaN   \n",
       "6                Male                True           True         NaN   \n",
       "7       United-States               False           True         NaN   \n",
       "8       United-States               False          False         NaN   \n",
       "9       United-States               False          False         NaN   \n",
       "\n",
       "   FPR Parity  FOR Parity  FNR Parity  TPR Parity  TNR Parity  NPV Parity  \\\n",
       "0         NaN       False       False        True        True        True   \n",
       "1         NaN       False       False        True        True        True   \n",
       "2         NaN       False       False        True        True        True   \n",
       "3         NaN       False       False        True        True        True   \n",
       "4         NaN        True        True        True        True        True   \n",
       "5         NaN       False       False        True        True        True   \n",
       "6         NaN        True        True        True        True        True   \n",
       "7         NaN       False       False        True        True        True   \n",
       "8         NaN       False       False        True        True        True   \n",
       "9         NaN       False       False        True        True        True   \n",
       "\n",
       "   Precision Parity  TypeI Parity  TypeII Parity  Equalized Odds  \\\n",
       "0              True           NaN          False           False   \n",
       "1              True           NaN          False           False   \n",
       "2              True           NaN          False           False   \n",
       "3              True           NaN          False           False   \n",
       "4              True           NaN           True           False   \n",
       "5              True           NaN          False           False   \n",
       "6              True           NaN           True           False   \n",
       "7              True           NaN          False           False   \n",
       "8              True           NaN          False           False   \n",
       "9              True           NaN          False           False   \n",
       "\n",
       "   Unsupervised Fairness  Supervised Fairness  \n",
       "0                  False                False  \n",
       "1                  False                False  \n",
       "2                  False                False  \n",
       "3                  False                False  \n",
       "4                   True                False  \n",
       "5                  False                False  \n",
       "6                   True                False  \n",
       "7                  False                False  \n",
       "8                  False                False  \n",
       "9                  False                False  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fairness = Fairness()\n",
    "fairness_df = fairness.get_group_value_fairness(bias_df)\n",
    "fairness_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d0f03a36",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Unsupervised Fairness': False, 'Supervised Fairness': False, 'Overall Fairness': False}\n"
     ]
    }
   ],
   "source": [
    "overall_fairness = fairness.get_overall_fairness(fairness_df)\n",
    "print(overall_fairness)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84dc453e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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