pandas_tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore all pandas library using tutorial\n",
    "\n",
    "### Import all necessary libraries "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sum Row wise or column wise in pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('algorithms/FuelConsumption.csv')\n",
    "df_index = pd.read_csv('algorithms/FuelConsumption.csv', index_col='MODELYEAR')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Row wise sum() in dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MAKE                        ACURAACURAACURAACURAACURAACURAACURAACURAACURAA...\n",
       "MODEL                       ILXILXILX HYBRIDMDX 4WDRDX AWDRLXTLTL AWDTL AW...\n",
       "VEHICLECLASS                COMPACTCOMPACTCOMPACTSUV - SMALLSUV - SMALLMID...\n",
       "ENGINESIZE                                                             3570.5\n",
       "CYLINDERS                                                                6183\n",
       "TRANSMISSION                AS5M6AV7AS6AS6AS6AS6AS6M6AS5M6AS5A6A6AM7M6AM7M...\n",
       "FUELTYPE                    ZZZZZZZZZZZZZZZZZZZZZZZZZZZDZDZZDZZZDZZZZDZDZZ...\n",
       "FUELCONSUMPTION_CITY                                                  14187.4\n",
       "FUELCONSUMPTION_HWY                                                   10109.4\n",
       "FUELCONSUMPTION_COMB                                                  12356.8\n",
       "FUELCONSUMPTION_COMB_MPG                                                28213\n",
       "CO2EMISSIONS                                                           273396\n",
       "dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sum(axis=0)\n",
    "df.sum(axis='index')\n",
    "df_index.sum(axis=0)\n",
    "df_index.sum(axis='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Columns wise sum() in dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.sum(axis=1)\n",
    "df.sum(axis='columns')\n",
    "df_index.sum(axis=1)\n",
    "df_index.sum(axis='columns')\n",
    "\n",
    "Output=None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select Single Columns in Data Frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2014\n",
       "1    2014\n",
       "2    2014\n",
       "3    2014\n",
       "4    2014\n",
       "Name: MODELYEAR, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.MAKE\n",
    "df.MODELYEAR\n",
    "df['MAKE']\n",
    "df['MODELYEAR'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select Two or More Columns from DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>MAKE</th>\n",
       "      <th>MODELYEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    MAKE  MODELYEAR\n",
       "0  ACURA       2014\n",
       "1  ACURA       2014\n",
       "2  ACURA       2014\n",
       "3  ACURA       2014\n",
       "4  ACURA       2014"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['MAKE','MODELYEAR']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select Multiple columns in an elegent way"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\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>MAKE</th>\n",
       "      <th>MODELYEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    MAKE  MODELYEAR\n",
       "0  ACURA       2014\n",
       "1  ACURA       2014\n",
       "2  ACURA       2014\n",
       "3  ACURA       2014\n",
       "4  ACURA       2014"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select = ['MAKE','MODELYEAR']\n",
    "df[select].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add new columns in DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>MODELYEAR</th>\n",
       "      <th>MAKE</th>\n",
       "      <th>MODELNAME</th>\n",
       "      <th>MODEL</th>\n",
       "      <th>VEHICLECLASS</th>\n",
       "      <th>ENGINESIZE</th>\n",
       "      <th>CYLINDERS</th>\n",
       "      <th>TRANSMISSION</th>\n",
       "      <th>FUELTYPE</th>\n",
       "      <th>FUELCONSUMPTION_CITY</th>\n",
       "      <th>FUELCONSUMPTION_HWY</th>\n",
       "      <th>FUELCONSUMPTION_COMB</th>\n",
       "      <th>FUELCONSUMPTION_COMB_MPG</th>\n",
       "      <th>CO2EMISSIONS</th>\n",
       "      <th>SUMOFCOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "      <td>ILX</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4</td>\n",
       "      <td>AS5</td>\n",
       "      <td>Z</td>\n",
       "      <td>9.9</td>\n",
       "      <td>6.7</td>\n",
       "      <td>8.5</td>\n",
       "      <td>33</td>\n",
       "      <td>196</td>\n",
       "      <td>34825.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "      <td>ILX</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>2.4</td>\n",
       "      <td>4</td>\n",
       "      <td>M6</td>\n",
       "      <td>Z</td>\n",
       "      <td>11.2</td>\n",
       "      <td>7.7</td>\n",
       "      <td>9.6</td>\n",
       "      <td>29</td>\n",
       "      <td>221</td>\n",
       "      <td>35073.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "      <td>ILX HYBRID</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4</td>\n",
       "      <td>AV7</td>\n",
       "      <td>Z</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>5.9</td>\n",
       "      <td>48</td>\n",
       "      <td>136</td>\n",
       "      <td>34296.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "      <td>MDX 4WD</td>\n",
       "      <td>SUV - SMALL</td>\n",
       "      <td>3.5</td>\n",
       "      <td>6</td>\n",
       "      <td>AS6</td>\n",
       "      <td>Z</td>\n",
       "      <td>12.7</td>\n",
       "      <td>9.1</td>\n",
       "      <td>11.1</td>\n",
       "      <td>25</td>\n",
       "      <td>255</td>\n",
       "      <td>35448.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>2014</td>\n",
       "      <td>RDX AWD</td>\n",
       "      <td>SUV - SMALL</td>\n",
       "      <td>3.5</td>\n",
       "      <td>6</td>\n",
       "      <td>AS6</td>\n",
       "      <td>Z</td>\n",
       "      <td>12.1</td>\n",
       "      <td>8.7</td>\n",
       "      <td>10.6</td>\n",
       "      <td>27</td>\n",
       "      <td>244</td>\n",
       "      <td>35343.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MODELYEAR   MAKE  MODELNAME       MODEL VEHICLECLASS  ENGINESIZE  \\\n",
       "0       2014  ACURA       2014         ILX      COMPACT         2.0   \n",
       "1       2014  ACURA       2014         ILX      COMPACT         2.4   \n",
       "2       2014  ACURA       2014  ILX HYBRID      COMPACT         1.5   \n",
       "3       2014  ACURA       2014     MDX 4WD  SUV - SMALL         3.5   \n",
       "4       2014  ACURA       2014     RDX AWD  SUV - SMALL         3.5   \n",
       "\n",
       "   CYLINDERS TRANSMISSION FUELTYPE  FUELCONSUMPTION_CITY  FUELCONSUMPTION_HWY  \\\n",
       "0          4          AS5        Z                   9.9                  6.7   \n",
       "1          4           M6        Z                  11.2                  7.7   \n",
       "2          4          AV7        Z                   6.0                  5.8   \n",
       "3          6          AS6        Z                  12.7                  9.1   \n",
       "4          6          AS6        Z                  12.1                  8.7   \n",
       "\n",
       "   FUELCONSUMPTION_COMB  FUELCONSUMPTION_COMB_MPG  CO2EMISSIONS  SUMOFCOL  \n",
       "0                   8.5                        33           196   34825.0  \n",
       "1                   9.6                        29           221   35073.0  \n",
       "2                   5.9                        48           136   34296.0  \n",
       "3                  11.1                        25           255   35448.0  \n",
       "4                  10.6                        27           244   35343.0  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['SUMOFCOL']=df.sum(axis=1)\n",
    "\n",
    "# it is possible to add new column in a specific position\n",
    "# using following: df.insert(loc,column='column_name',value='column_value')\n",
    "\n",
    "# df.insert(2, column='MODELNAME', value=df.MODELYEAR)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Broadcasting Operations\n",
    "\n",
    "\n",
    "#### add value or some operation in a specific columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    34885.0\n",
       "1    35133.0\n",
       "2    34356.0\n",
       "3    35508.0\n",
       "4    35403.0\n",
       "Name: SUMOFCOL, dtype: float64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df['SUMOFCOL'].add(15)\n",
    "df['SUMOFCOL']+15\n",
    "df['SUMOFCOL'] = df['SUMOFCOL'].add(15)\n",
    "df['SUMOFCOL'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Subtract or minus operation in a specific columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    34855.0\n",
       "1    35103.0\n",
       "2    34326.0\n",
       "3    35478.0\n",
       "4    35373.0\n",
       "Name: SUMOFCOL, dtype: float64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['SUMOFCOL'].sub(15)\n",
    "df['SUMOFCOL']-15\n",
    "df['SUMOFCOL'] = df['SUMOFCOL'].sub(15)\n",
    "df['SUMOFCOL'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiplication operation in a specific columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    13954.0\n",
       "1    14053.2\n",
       "2    13742.4\n",
       "3    14203.2\n",
       "4    14161.2\n",
       "Name: SUMOFCOL, dtype: float64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['SUMOFCOL'].mul(0.4)\n",
    "df['SUMOFCOL'] = df['SUMOFCOL'].mul(0.4)\n",
    "df['SUMOFCOL'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    ".mul(0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Division operation in a specific columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    545078.125\n",
       "1    548953.125\n",
       "2    536812.500\n",
       "3    554812.500\n",
       "4    553171.875\n",
       "Name: SUMOFCOL, dtype: float64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['SUMOFCOL'].div(0.4)\n",
    "df['SUMOFCOL'] = df['SUMOFCOL'].div(0.4)\n",
    "df['SUMOFCOL'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Value Count in Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SANTA FE SPORT         1\n",
       "Q7 TDI CLEAN DIESEL    1\n",
       "CHALLENGER SRT         1\n",
       "RAV4                   1\n",
       "TITAN 4WD              1\n",
       "Name: MODEL, dtype: int64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['MAKE'].value_counts()\n",
    "df['MODELYEAR'].value_counts()\n",
    "df['MODELNAME'].value_counts()\n",
    "df['MODEL'].value_counts().tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drop Column or Rows if Contains NaN Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1067, 13)"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dropna(axis=0,how=\"all\",subset=['MAKE','MODEL'],inplace=True)\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fill the value if not available using _fillna()_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.fillna(0,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert columns data type to another data types using _astype()_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1067 entries, 0 to 1066\n",
      "Data columns (total 13 columns):\n",
      "MODELYEAR                   1067 non-null int64\n",
      "MAKE                        1067 non-null object\n",
      "MODEL                       1067 non-null object\n",
      "VEHICLECLASS                1067 non-null object\n",
      "ENGINESIZE                  1067 non-null float64\n",
      "CYLINDERS                   1067 non-null float64\n",
      "TRANSMISSION                1067 non-null object\n",
      "FUELTYPE                    1067 non-null object\n",
      "FUELCONSUMPTION_CITY        1067 non-null float64\n",
      "FUELCONSUMPTION_HWY         1067 non-null float64\n",
      "FUELCONSUMPTION_COMB        1067 non-null float64\n",
      "FUELCONSUMPTION_COMB_MPG    1067 non-null int64\n",
      "CO2EMISSIONS                1067 non-null int64\n",
      "dtypes: float64(5), int64(3), object(5)\n",
      "memory usage: 116.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df['CYLINDERS'] = df['CYLINDERS'].astype(\"float\")\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['MODELYEAR'].astype('category')\n",
    "Output=None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sorting data using sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>MODELYEAR</th>\n",
       "      <th>MAKE</th>\n",
       "      <th>MODEL</th>\n",
       "      <th>VEHICLECLASS</th>\n",
       "      <th>ENGINESIZE</th>\n",
       "      <th>CYLINDERS</th>\n",
       "      <th>TRANSMISSION</th>\n",
       "      <th>FUELTYPE</th>\n",
       "      <th>FUELCONSUMPTION_CITY</th>\n",
       "      <th>FUELCONSUMPTION_HWY</th>\n",
       "      <th>FUELCONSUMPTION_COMB</th>\n",
       "      <th>FUELCONSUMPTION_COMB_MPG</th>\n",
       "      <th>CO2EMISSIONS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>2014</td>\n",
       "      <td>SCION</td>\n",
       "      <td>xD</td>\n",
       "      <td>SUBCOMPACT</td>\n",
       "      <td>1.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>M5</td>\n",
       "      <td>X</td>\n",
       "      <td>8.6</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.9</td>\n",
       "      <td>36</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>936</th>\n",
       "      <td>2014</td>\n",
       "      <td>SCION</td>\n",
       "      <td>xD</td>\n",
       "      <td>SUBCOMPACT</td>\n",
       "      <td>1.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>A4</td>\n",
       "      <td>X</td>\n",
       "      <td>8.8</td>\n",
       "      <td>7.1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>35</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>934</th>\n",
       "      <td>2014</td>\n",
       "      <td>SCION</td>\n",
       "      <td>xB</td>\n",
       "      <td>STATION WAGON - SMALL</td>\n",
       "      <td>2.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>AS4</td>\n",
       "      <td>X</td>\n",
       "      <td>10.9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>9.9</td>\n",
       "      <td>29</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>935</th>\n",
       "      <td>2014</td>\n",
       "      <td>SCION</td>\n",
       "      <td>xB</td>\n",
       "      <td>STATION WAGON - SMALL</td>\n",
       "      <td>2.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>M5</td>\n",
       "      <td>X</td>\n",
       "      <td>10.9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>9.9</td>\n",
       "      <td>29</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>2014</td>\n",
       "      <td>SCION</td>\n",
       "      <td>tC</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>2.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>AS6</td>\n",
       "      <td>X</td>\n",
       "      <td>10.2</td>\n",
       "      <td>7.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     MODELYEAR   MAKE MODEL           VEHICLECLASS  ENGINESIZE  CYLINDERS  \\\n",
       "937       2014  SCION    xD             SUBCOMPACT         1.8        4.0   \n",
       "936       2014  SCION    xD             SUBCOMPACT         1.8        4.0   \n",
       "934       2014  SCION    xB  STATION WAGON - SMALL         2.4        4.0   \n",
       "935       2014  SCION    xB  STATION WAGON - SMALL         2.4        4.0   \n",
       "932       2014  SCION    tC                COMPACT         2.5        4.0   \n",
       "\n",
       "    TRANSMISSION FUELTYPE  FUELCONSUMPTION_CITY  FUELCONSUMPTION_HWY  \\\n",
       "937           M5        X                   8.6                  7.1   \n",
       "936           A4        X                   8.8                  7.1   \n",
       "934          AS4        X                  10.9                  8.6   \n",
       "935           M5        X                  10.9                  8.6   \n",
       "932          AS6        X                  10.2                  7.5   \n",
       "\n",
       "     FUELCONSUMPTION_COMB  FUELCONSUMPTION_COMB_MPG  CO2EMISSIONS  \n",
       "937                   7.9                        36           182  \n",
       "936                   8.0                        35           184  \n",
       "934                   9.9                        29           228  \n",
       "935                   9.9                        29           228  \n",
       "932                   9.0                        31           207  "
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('MODEL',ascending=False)\n",
    "df.sort_values('ENGINESIZE',ascending=True)\n",
    "df.sort_values('MODEL',ascending=False,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sorting multiple columns using  sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MODELYEAR</th>\n",
       "      <th>MAKE</th>\n",
       "      <th>MODEL</th>\n",
       "      <th>VEHICLECLASS</th>\n",
       "      <th>ENGINESIZE</th>\n",
       "      <th>CYLINDERS</th>\n",
       "      <th>TRANSMISSION</th>\n",
       "      <th>FUELTYPE</th>\n",
       "      <th>FUELCONSUMPTION_CITY</th>\n",
       "      <th>FUELCONSUMPTION_HWY</th>\n",
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       "      <th>FUELCONSUMPTION_COMB_MPG</th>\n",
       "      <th>CO2EMISSIONS</th>\n",
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       "      <th>910</th>\n",
       "      <td>2014</td>\n",
       "      <td>RAM</td>\n",
       "      <td>1500 (MDS)</td>\n",
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       "      <td>5.7</td>\n",
       "      <td>8.0</td>\n",
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       "      <td>X</td>\n",
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       "      <td>2014</td>\n",
       "      <td>RAM</td>\n",
       "      <td>1500 (MDS)</td>\n",
       "      <td>PICKUP TRUCK - STANDARD</td>\n",
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       "      <td>8.0</td>\n",
       "      <td>A6</td>\n",
       "      <td>X</td>\n",
       "      <td>17.1</td>\n",
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       "      <td>19</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>912</th>\n",
       "      <td>2014</td>\n",
       "      <td>RAM</td>\n",
       "      <td>1500 4X4 (MDS)</td>\n",
       "      <td>PICKUP TRUCK - STANDARD</td>\n",
       "      <td>5.7</td>\n",
       "      <td>8.0</td>\n",
       "      <td>A8</td>\n",
       "      <td>X</td>\n",
       "      <td>16.3</td>\n",
       "      <td>11.5</td>\n",
       "      <td>14.1</td>\n",
       "      <td>20</td>\n",
       "      <td>324</td>\n",
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       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>2014</td>\n",
       "      <td>RAM</td>\n",
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       "      <td>5.7</td>\n",
       "      <td>8.0</td>\n",
       "      <td>A6</td>\n",
       "      <td>X</td>\n",
       "      <td>17.6</td>\n",
       "      <td>12.7</td>\n",
       "      <td>15.4</td>\n",
       "      <td>18</td>\n",
       "      <td>354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>913</th>\n",
       "      <td>2014</td>\n",
       "      <td>RAM</td>\n",
       "      <td>1500 4X4 DIESEL</td>\n",
       "      <td>PICKUP TRUCK - STANDARD</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>A8</td>\n",
       "      <td>D</td>\n",
       "      <td>12.1</td>\n",
       "      <td>8.8</td>\n",
       "      <td>10.6</td>\n",
       "      <td>27</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     MODELYEAR MAKE            MODEL             VEHICLECLASS  ENGINESIZE  \\\n",
       "910       2014  RAM       1500 (MDS)  PICKUP TRUCK - STANDARD         5.7   \n",
       "909       2014  RAM       1500 (MDS)  PICKUP TRUCK - STANDARD         5.7   \n",
       "912       2014  RAM   1500 4X4 (MDS)  PICKUP TRUCK - STANDARD         5.7   \n",
       "911       2014  RAM   1500 4X4 (MDS)  PICKUP TRUCK - STANDARD         5.7   \n",
       "913       2014  RAM  1500 4X4 DIESEL  PICKUP TRUCK - STANDARD         3.0   \n",
       "\n",
       "     CYLINDERS TRANSMISSION FUELTYPE  FUELCONSUMPTION_CITY  \\\n",
       "910        8.0           A8        X                  15.8   \n",
       "909        8.0           A6        X                  17.1   \n",
       "912        8.0           A8        X                  16.3   \n",
       "911        8.0           A6        X                  17.6   \n",
       "913        6.0           A8        D                  12.1   \n",
       "\n",
       "     FUELCONSUMPTION_HWY  FUELCONSUMPTION_COMB  FUELCONSUMPTION_COMB_MPG  \\\n",
       "910                 10.9                  13.6                        21   \n",
       "909                 12.0                  14.8                        19   \n",
       "912                 11.5                  14.1                        20   \n",
       "911                 12.7                  15.4                        18   \n",
       "913                  8.8                  10.6                        27   \n",
       "\n",
       "     CO2EMISSIONS  \n",
       "910           313  \n",
       "909           340  \n",
       "912           324  \n",
       "911           354  \n",
       "913           286  "
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(['MODEL','ENGINESIZE'],ascending=['False','False'],inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reset or sort index using sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "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>MODELYEAR</th>\n",
       "      <th>MAKE</th>\n",
       "      <th>MODEL</th>\n",
       "      <th>VEHICLECLASS</th>\n",
       "      <th>ENGINESIZE</th>\n",
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       "      <th>TRANSMISSION</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>2014</td>\n",
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       "      <td>COMPACT</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>8.5</td>\n",
       "      <td>33</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>ILX</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>2.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>M6</td>\n",
       "      <td>Z</td>\n",
       "      <td>11.2</td>\n",
       "      <td>7.7</td>\n",
       "      <td>9.6</td>\n",
       "      <td>29</td>\n",
       "      <td>221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>ILX HYBRID</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>AV7</td>\n",
       "      <td>Z</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>5.9</td>\n",
       "      <td>48</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>MDX 4WD</td>\n",
       "      <td>SUV - SMALL</td>\n",
       "      <td>3.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>AS6</td>\n",
       "      <td>Z</td>\n",
       "      <td>12.7</td>\n",
       "      <td>9.1</td>\n",
       "      <td>11.1</td>\n",
       "      <td>25</td>\n",
       "      <td>255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>ACURA</td>\n",
       "      <td>RDX AWD</td>\n",
       "      <td>SUV - SMALL</td>\n",
       "      <td>3.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>AS6</td>\n",
       "      <td>Z</td>\n",
       "      <td>12.1</td>\n",
       "      <td>8.7</td>\n",
       "      <td>10.6</td>\n",
       "      <td>27</td>\n",
       "      <td>244</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MODELYEAR   MAKE       MODEL VEHICLECLASS  ENGINESIZE  CYLINDERS  \\\n",
       "0       2014  ACURA         ILX      COMPACT         2.0        4.0   \n",
       "1       2014  ACURA         ILX      COMPACT         2.4        4.0   \n",
       "2       2014  ACURA  ILX HYBRID      COMPACT         1.5        4.0   \n",
       "3       2014  ACURA     MDX 4WD  SUV - SMALL         3.5        6.0   \n",
       "4       2014  ACURA     RDX AWD  SUV - SMALL         3.5        6.0   \n",
       "\n",
       "  TRANSMISSION FUELTYPE  FUELCONSUMPTION_CITY  FUELCONSUMPTION_HWY  \\\n",
       "0          AS5        Z                   9.9                  6.7   \n",
       "1           M6        Z                  11.2                  7.7   \n",
       "2          AV7        Z                   6.0                  5.8   \n",
       "3          AS6        Z                  12.7                  9.1   \n",
       "4          AS6        Z                  12.1                  8.7   \n",
       "\n",
       "   FUELCONSUMPTION_COMB  FUELCONSUMPTION_COMB_MPG  CO2EMISSIONS  \n",
       "0                   8.5                        33           196  \n",
       "1                   9.6                        29           221  \n",
       "2                   5.9                        48           136  \n",
       "3                  11.1                        25           255  \n",
       "4                  10.6                        27           244  "
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_index(ascending=True, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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