handling missing values continues.ipynb

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 "cells": [
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   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      democrat\n",
       "1    republican\n",
       "2           NaN\n",
       "Name: party, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dask_df['party'].unique().compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filling the missing values with 'not recorded'\n",
    "dask_df[\"party\"] = dask_df[\"party\"].fillna('Others')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year              0\n",
       "state             0\n",
       "county            0\n",
       "FIPS              0\n",
       "office            0\n",
       "candidate         0\n",
       "party             0\n",
       "candidatevotes    0\n",
       "totalvotes        0\n",
       "version           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dask_df.isnull().sum().compute()"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  }
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