92 lines (91 with data), 2.1 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "import pandas as pd\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the noisy dataset.\n",
    "original = pd.read_csv('../../data/raw/original.csv')\n",
    "synthetic = pd.read_csv('../../data/raw/synthetic.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Process the the datasets.\n",
    "original = original.drop_duplicates().dropna()\n",
    "synthetic = synthetic.drop_duplicates().dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature engineering\n",
    "original[['GENDER', 'LUNG_CANCER']] = original[['GENDER', 'LUNG_CANCER']].replace({'M': 1, 'F': 2, 'YES': 1, 'NO': 0})\n",
    "synthetic[['GENDER', 'LUNG_CANCER']] = synthetic[['GENDER', 'LUNG_CANCER']].replace({'M': 1, 'F': 2, 'YES': 1, 'NO': 0})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset processed.\n"
     ]
    }
   ],
   "source": [
    "# Saved dataset\n",
    "original.to_csv('../../data/processed/original.csv', index=False)\n",
    "synthetic.to_csv('../../data/processed/synthetic.csv', index=False)\n",
    "\n",
    "print('Dataset processed.')"
   ]
  }
 ],
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