01-Data-Preparation-04-Data-Formatting-For-Aequitas.ipynb

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   "source": [
    "# 01 Data Preparation\n",
    "\n",
    "We clean the predictions made by namsor"
   ]
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    "# >>> Import COMPAS data set\n",
    "\n",
    "print(\"Importing COMPAS data set... \")\n",
    "\n",
    "df = pd.read_csv(\"data/compas_with_predictions_cleaned.csv\")\n",
    "\n",
    "print(\"Data set imported. It is has {} entries and looks like this:\".format(df.shape[0]))\n",
    "df.head()"
   ]
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   "cell_type": "code",
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    "# get the parts we need\n",
    "# instead of the actual classifications for sex and race we want to keep only namsor's predictions\n",
    "df = df[['entity_id', 'score', 'label_value', 'race_pred', 'sex_pred', 'age_cat']]\n",
    "df = df.rename(columns={'race_pred':'race', \n",
    "                        'sex_pred':'sex'})"
   ]
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   "execution_count": null,
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   "source": [
    "df.head()"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving results to 'names_cat.csv'\n",
    "print(\"Saving compas dataframe with predictions for gender and ethnicity to CSV... \")\n",
    "df.to_csv(\"data/namsor_for_aequitas.csv\")\n",
    "print(\"CSV saved!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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