Code/Pandas Apply.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Apply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import pandas\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import dataset\n",
    "loan = pd.read_csv('../Data/loan_train.csv', index_col = 'Loan_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define function\n",
    "def missing(x):\n",
    "    return sum(x.isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values per column\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Gender           13\n",
       "Married           3\n",
       "Dependents       15\n",
       "Education         0\n",
       "Self_Employed    32\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Apply per column\n",
    "print('Missing values per column')\n",
    "loan.apply(missing, axis = 0).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values per row\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Loan_ID\n",
       "LP001002    1\n",
       "LP001003    0\n",
       "LP001005    0\n",
       "LP001006    0\n",
       "LP001008    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Apply per row\n",
    "print('Missing values per row')\n",
    "loan.apply(missing, axis = 1).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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