Py_Lab-8.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#            Python for DataScience"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "                                                                                                                                                                  M.R.Naveen Kumar\n",
    "                                                                                                                                                                        19BTRCR005"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write python program using python\n",
    "\n",
    "a.\tTo handle missing values in a dataset.\n",
    "\n",
    "b.\tTo remove duplicate values in a dataset.\n",
    "\n",
    "c.\tTo count the NaN values in a dataset.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/5/2021</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/6/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/7/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/8/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021         NaN        9.0   Sunny\n",
       "2   1/5/2021        28.0        NaN    Snow\n",
       "3   1/6/2021         NaN        7.0     NaN\n",
       "4   1/7/2021        32.0        NaN    Rain\n",
       "5   1/8/2021         NaN        NaN   Sunny\n",
       "6   1/9/2021         NaN        NaN     NaN\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df = pd.read_csv('DataFrames/weather.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\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>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     day  temprature  windspeed  event\n",
       "0  False       False      False  False\n",
       "1  False        True      False  False\n",
       "2  False       False       True  False\n",
       "3  False        True      False   True\n",
       "4  False       False       True  False\n",
       "5  False        True       True  False\n",
       "6  False        True       True   True\n",
       "7  False       False      False  False\n",
       "8  False       False      False  False"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day           False\n",
       "temprature     True\n",
       "windspeed      True\n",
       "event          True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().any() #or isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day           0\n",
       "temprature    4\n",
       "windspeed     4\n",
       "event         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    day  temprature  windspeed  event\n",
       "0  True        True       True   True\n",
       "1  True       False       True   True\n",
       "2  True        True      False   True\n",
       "3  True       False       True  False\n",
       "4  True        True      False   True\n",
       "5  True       False      False   True\n",
       "6  True       False      False  False\n",
       "7  True        True       True   True\n",
       "8  True        True       True   True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.notnull() # reverse of isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9 entries, 0 to 8\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   day         9 non-null      object \n",
      " 1   temprature  5 non-null      float64\n",
      " 2   windspeed   5 non-null      float64\n",
      " 3   event       7 non-null      object \n",
      "dtypes: float64(2), object(2)\n",
      "memory usage: 416.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.00000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>33.20000</td>\n",
       "      <td>8.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.38178</td>\n",
       "      <td>2.302173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>28.00000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>32.00000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>32.00000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>34.00000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>40.00000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       temprature  windspeed\n",
       "count     5.00000   5.000000\n",
       "mean     33.20000   8.400000\n",
       "std       4.38178   2.302173\n",
       "min      28.00000   6.000000\n",
       "25%      32.00000   7.000000\n",
       "50%      32.00000   8.000000\n",
       "75%      34.00000   9.000000\n",
       "max      40.00000  12.000000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         day  temprature  windspeed   event\n",
      "0   1/1/2021        32.0        6.0    Rain\n",
      "1   1/4/2021         NaN        9.0   Sunny\n",
      "2   1/5/2021        28.0        NaN    Snow\n",
      "3   1/6/2021         NaN        7.0     NaN\n",
      "4   1/7/2021        32.0        NaN    Rain\n",
      "5   1/8/2021         NaN        NaN   Sunny\n",
      "6   1/9/2021         NaN        NaN     NaN\n",
      "7  1/10/2021        34.0        8.0  Cloudy\n",
      "8  1/11/2021        40.0       12.0   Sunny\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df)\n",
    "df1 = df.dropna()\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.dropna(how='any')\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         day  temprature  windspeed   event\n",
      "0   1/1/2021        32.0        6.0    Rain\n",
      "1   1/4/2021         NaN        9.0   Sunny\n",
      "2   1/5/2021        28.0        NaN    Snow\n",
      "3   1/6/2021         NaN        7.0     NaN\n",
      "4   1/7/2021        32.0        NaN    Rain\n",
      "5   1/8/2021         NaN        NaN   Sunny\n",
      "6   1/9/2021         NaN        NaN     NaN\n",
      "7  1/10/2021        34.0        8.0  Cloudy\n",
      "8  1/11/2021        40.0       12.0   Sunny\n"
     ]
    },
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1/1/2021</td>\n",
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       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>1/5/2021</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/6/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/7/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/8/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021         NaN        9.0   Sunny\n",
       "2   1/5/2021        28.0        NaN    Snow\n",
       "3   1/6/2021         NaN        7.0     NaN\n",
       "4   1/7/2021        32.0        NaN    Rain\n",
       "5   1/8/2021         NaN        NaN   Sunny\n",
       "6   1/9/2021         NaN        NaN     NaN\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df)\n",
    "df3 = df.dropna(how='all')\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>temprature</th>\n",
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       "      <td>1/5/2021</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>32.0</td>\n",
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       "      <td>Rain</td>\n",
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       "      <th>7</th>\n",
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       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021         NaN        9.0   Sunny\n",
       "2   1/5/2021        28.0        NaN    Snow\n",
       "4   1/7/2021        32.0        NaN    Rain\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4 = df.dropna(how='all', thresh= 3)\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Sunny</td>\n",
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       "      <th>2</th>\n",
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       "      <td>28.0</td>\n",
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       "      <td>Snow</td>\n",
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       "      <td>32.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/8/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021        28.0        9.0   Sunny\n",
       "2   1/5/2021        28.0        7.0    Snow\n",
       "3   1/6/2021        32.0        7.0    Rain\n",
       "4   1/7/2021        32.0        8.0    Rain\n",
       "5   1/8/2021        34.0        8.0   Sunny\n",
       "6   1/9/2021        34.0        8.0  Cloudy\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5 = df.fillna(method='bfill')\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Sunny</td>\n",
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       "      <th>2</th>\n",
       "      <td>1/5/2021</td>\n",
       "      <td>28.0</td>\n",
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       "      <td>Snow</td>\n",
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       "      <th>3</th>\n",
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       "      <td>28.0</td>\n",
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       "      <td>Snow</td>\n",
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       "      <th>4</th>\n",
       "      <td>1/7/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/8/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021        32.0        9.0   Sunny\n",
       "2   1/5/2021        28.0        9.0    Snow\n",
       "3   1/6/2021        28.0        7.0    Snow\n",
       "4   1/7/2021        32.0        7.0    Rain\n",
       "5   1/8/2021        32.0        NaN   Sunny\n",
       "6   1/9/2021         NaN        NaN   Sunny\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df6 = df.fillna(method='ffill', limit = 1)\n",
    "df6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\chinn\\AppData\\Local\\Temp/ipykernel_12068/2603784110.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
      "  mean = df.fillna(df.mean())\n"
     ]
    },
    {
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       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/5/2021</td>\n",
       "      <td>28.0</td>\n",
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       "      <td>Snow</td>\n",
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       "      <th>3</th>\n",
       "      <td>1/6/2021</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>1/7/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8.4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/8/2021</td>\n",
       "      <td>33.2</td>\n",
       "      <td>8.4</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2021</td>\n",
       "      <td>33.2</td>\n",
       "      <td>8.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021        33.2        9.0   Sunny\n",
       "2   1/5/2021        28.0        8.4    Snow\n",
       "3   1/6/2021        33.2        7.0     NaN\n",
       "4   1/7/2021        32.0        8.4    Rain\n",
       "5   1/8/2021        33.2        8.4   Sunny\n",
       "6   1/9/2021        33.2        8.4     NaN\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean = df.fillna(df.mean())\n",
    "mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\chinn\\AppData\\Local\\Temp/ipykernel_12068/429729123.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
      "  median = df.fillna(df.median())\n"
     ]
    },
    {
     "data": {
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       "      <td>1/7/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Rain</td>\n",
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       "      <th>5</th>\n",
       "      <td>1/8/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Sunny</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2021</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2021</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2021</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "         day  temprature  windspeed   event\n",
       "0   1/1/2021        32.0        6.0    Rain\n",
       "1   1/4/2021        32.0        9.0   Sunny\n",
       "2   1/5/2021        28.0        8.0    Snow\n",
       "3   1/6/2021        32.0        7.0     NaN\n",
       "4   1/7/2021        32.0        8.0    Rain\n",
       "5   1/8/2021        32.0        8.0   Sunny\n",
       "6   1/9/2021        32.0        8.0     NaN\n",
       "7  1/10/2021        34.0        8.0  Cloudy\n",
       "8  1/11/2021        40.0       12.0   Sunny"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "median = df.fillna(df.median())\n",
    "median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      Rain\n",
       "1     Sunny\n",
       "2      Snow\n",
       "3     Sunny\n",
       "4      Rain\n",
       "5     Sunny\n",
       "6     Sunny\n",
       "7    Cloudy\n",
       "8     Sunny\n",
       "Name: event, dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mode=df.fillna(df.mode())\n",
    "mode=df['event'].fillna(df['event'].mode()[0])\n",
    "mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "   A  B  C  D\n",
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       "2  0  0  1  1\n",
       "3  1  1  1  1"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "data = {'A' : [1,0,0,1], 'B' : [1,0,0,1], 'C' : [1,1,1,1], \"D\" : [1,0,1,1]}\n",
    "d = pd.DataFrame(data)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "0    False\n",
       "1    False\n",
       "2    False\n",
       "3     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   A  B  C  D\n",
      "3  1  1  1  1\n"
     ]
    }
   ],
   "source": [
    "print(d[d.duplicated()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "0    False\n",
       "1    False\n",
       "2    False\n",
       "3     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.duplicated(keep='first')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     True\n",
       "1    False\n",
       "2    False\n",
       "3    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.duplicated(keep='last')"
   ]
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   "execution_count": 49,
   "metadata": {},
   "outputs": [
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    "d[d.duplicated(keep='last')]"
   ]
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   "cell_type": "code",
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   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   A  B  C  D\n",
      "0  1  1  1  1\n",
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     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "print(d)\n",
    "d.duplicated(subset='A')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
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     "metadata": {},
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    "d.drop_duplicates(inplace=True)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
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    "d.drop_duplicates(keep=False)"
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   "execution_count": 56,
   "metadata": {},
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   "outputs": [],
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