Pandas_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame_data = {\n",
    "    'name' : ['Ali','Ahmed','Waqar','Yawar'],\n",
    "    'gender' : ['male','male','male','male'],\n",
    "    'salary' : [15000,20000,17000,18000],\n",
    "    'year'   : ['2010','2012','2104','2011'],\n",
    "    \n",
    "               }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>15000</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmed</td>\n",
       "      <td>male</td>\n",
       "      <td>20000</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Waqar</td>\n",
       "      <td>male</td>\n",
       "      <td>17000</td>\n",
       "      <td>2104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yawar</td>\n",
       "      <td>male</td>\n",
       "      <td>18000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name gender  salary  year\n",
       "0    Ali   male   15000  2010\n",
       "1  Ahmed   male   20000  2012\n",
       "2  Waqar   male   17000  2104\n",
       "3  Yawar   male   18000  2011"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame = pd.DataFrame(frame_data)\n",
    "data_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name      Waqar\n",
       "gender     male\n",
       "salary    17000\n",
       "year       2104\n",
       "Name: 2, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame.loc[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      Ali\n",
       "1    Ahmed\n",
       "2    Waqar\n",
       "3    Yawar\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    15000\n",
       "1    20000\n",
       "2    17000\n",
       "3    18000\n",
       "Name: salary, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame['salary']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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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       "        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>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "      <th>debt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>15000</td>\n",
       "      <td>2010</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmed</td>\n",
       "      <td>male</td>\n",
       "      <td>20000</td>\n",
       "      <td>2012</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Waqar</td>\n",
       "      <td>male</td>\n",
       "      <td>17000</td>\n",
       "      <td>2104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yawar</td>\n",
       "      <td>male</td>\n",
       "      <td>18000</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name gender  salary  year debt\n",
       "0    Ali   male   15000  2010  NaN\n",
       "1  Ahmed   male   20000  2012  NaN\n",
       "2  Waqar   male   17000  2104  NaN\n",
       "3  Yawar   male   18000  2011  NaN"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame2 = pd.DataFrame(frame_data, columns = ['name','gender','salary','year','debt'])\n",
    "data_frame2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_frame2['debt'] = 14000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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",
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       "        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>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "      <th>debt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>15000</td>\n",
       "      <td>2010</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmed</td>\n",
       "      <td>male</td>\n",
       "      <td>20000</td>\n",
       "      <td>2012</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Waqar</td>\n",
       "      <td>male</td>\n",
       "      <td>17000</td>\n",
       "      <td>2104</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yawar</td>\n",
       "      <td>male</td>\n",
       "      <td>18000</td>\n",
       "      <td>2011</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name gender  salary  year   debt\n",
       "0    Ali   male   15000  2010  14000\n",
       "1  Ahmed   male   20000  2012  14000\n",
       "2  Waqar   male   17000  2104  14000\n",
       "3  Yawar   male   18000  2011  14000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "series_to_insert = pd.Series(data = [15000,17000], index = [1,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\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>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "      <th>debt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>15000</td>\n",
       "      <td>2010</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmed</td>\n",
       "      <td>male</td>\n",
       "      <td>20000</td>\n",
       "      <td>2012</td>\n",
       "      <td>15000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Waqar</td>\n",
       "      <td>male</td>\n",
       "      <td>17000</td>\n",
       "      <td>2104</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yawar</td>\n",
       "      <td>male</td>\n",
       "      <td>18000</td>\n",
       "      <td>2011</td>\n",
       "      <td>17000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name gender  salary  year     debt\n",
       "0    Ali   male   15000  2010      NaN\n",
       "1  Ahmed   male   20000  2012  15000.0\n",
       "2  Waqar   male   17000  2104      NaN\n",
       "3  Yawar   male   18000  2011  17000.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame2['debt'] = series_to_insert\n",
    "data_frame2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assigning a column that doesn’t exist will create a new column but you cannot do it with a dot notation as\n",
    "data_frame2.result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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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>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>salary</th>\n",
       "      <th>debt</th>\n",
       "      <th>result</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>15000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pass</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmed</td>\n",
       "      <td>male</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>fail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Waqar</td>\n",
       "      <td>male</td>\n",
       "      <td>17000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pass</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yawar</td>\n",
       "      <td>male</td>\n",
       "      <td>18000</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>fail</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name gender  salary     debt result\n",
       "0    Ali   male   15000      NaN   pass\n",
       "1  Ahmed   male   20000  15000.0   fail\n",
       "2  Waqar   male   17000      NaN   pass\n",
       "3  Yawar   male   18000  17000.0   fail"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame2['result'] = pd.Series(data = ['pass','fail','pass','fail'])\n",
    "data_frame2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    pass\n",
      "1    fail\n",
      "2    pass\n",
      "3    fail\n",
      "Name: result, dtype: object\n",
      "0    pass\n",
      "1    fail\n",
      "2    pass\n",
      "3    fail\n",
      "Name: result, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(data_frame2['result'])\n",
    "print(data_frame2.result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The del method can then be used to remove this column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>salary</th>\n",
       "      <th>debt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali</td>\n",
       "      <td>male</td>\n",
       "      <td>15000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmed</td>\n",
       "      <td>male</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Waqar</td>\n",
       "      <td>male</td>\n",
       "      <td>17000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yawar</td>\n",
       "      <td>male</td>\n",
       "      <td>18000</td>\n",
       "      <td>17000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name gender  salary     debt\n",
       "0    Ali   male   15000      NaN\n",
       "1  Ahmed   male   20000  15000.0\n",
       "2  Waqar   male   17000      NaN\n",
       "3  Yawar   male   18000  17000.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del data_frame2['result']\n",
    "data_frame2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['name', 'gender', 'salary', 'debt'], dtype='object')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame2.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dictionary of Dictionaries when passed to data frame "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>salary</th>\n",
       "      <th>bonus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       salary   bonus\n",
       "2001  15000.0  3000.0\n",
       "2002   3000.0     NaN\n",
       "2003  40000.0  2000.0\n",
       "2007      NaN  1000.0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = {\n",
    "    'salary' : {2001: 15000, 2002:3000, 2003:40000},\n",
    "    'bonus' : {2003 : 2000, 2001 : 3000, 2007 : 1000},\n",
    "    \n",
    "}\n",
    "data_frame4 = pd.DataFrame(data)\n",
    "data_frame4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
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       "      <th>2007</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>salary</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>bonus</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           2001    2002     2003    2007\n",
       "salary  15000.0  3000.0  40000.0     NaN\n",
       "bonus    3000.0     NaN   2000.0  1000.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
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    "data_frame4.T"
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  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>bonus</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
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       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
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       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>2000.0</td>\n",
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       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       salary   bonus\n",
       "2001  15000.0  3000.0\n",
       "2002   3000.0     NaN\n",
       "2003  40000.0  2000.0\n",
       "2007      NaN  1000.0"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "data_frame4"
   ]
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  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_frame4.columns.name = \"pay_parameters\"\n",
    "data_frame4.index.name = \"years\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>pay_parameters</th>\n",
       "      <th>salary</th>\n",
       "      <th>bonus</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>years</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "pay_parameters   salary   bonus\n",
       "years                          \n",
       "2001            15000.0  3000.0\n",
       "2002             3000.0     NaN\n",
       "2003            40000.0  2000.0\n",
       "2007                NaN  1000.0"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_frame4.loc[2008] = [12000,3000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>pay_parameters</th>\n",
       "      <th>salary</th>\n",
       "      <th>bonus</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>years</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>12000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "pay_parameters   salary   bonus\n",
       "years                          \n",
       "2001            15000.0  3000.0\n",
       "2002             3000.0     NaN\n",
       "2003            40000.0  2000.0\n",
       "2007                NaN  1000.0\n",
       "2008            12000.0  3000.0"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
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    "data_frame4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_frame4['increment'] = pd.Series(data = [1200,1300,1000,1400,1500], index = [2001,2002,2003,2007,2008])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>pay_parameters</th>\n",
       "      <th>salary</th>\n",
       "      <th>bonus</th>\n",
       "      <th>increment</th>\n",
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       "    <tr>\n",
       "      <th>years</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>1200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>12000.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>1500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "pay_parameters   salary   bonus  increment\n",
       "years                                     \n",
       "2001            15000.0  3000.0       1200\n",
       "2002             3000.0     NaN       1300\n",
       "2003            40000.0  2000.0       1000\n",
       "2007                NaN  1000.0       1400\n",
       "2008            12000.0  3000.0       1500"
      ]
     },
     "execution_count": 44,
     "metadata": {},
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   "source": [
    "data_frame4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data_frame4['increment']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>12000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "pay_parameters   salary   bonus\n",
       "years                          \n",
       "2001            15000.0  3000.0\n",
       "2002             3000.0     NaN\n",
       "2003            40000.0  2000.0\n",
       "2007                NaN  1000.0\n",
       "2008            12000.0  3000.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
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    "data_frame4"
   ]
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  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pay_parameters\n",
       "salary    12000.0\n",
       "bonus      3000.0\n",
       "Name: 2008, dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame4.loc[2008]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th>pay_parameters</th>\n",
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       "      <th>2001</th>\n",
       "      <td>15000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
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       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>12000.0</td>\n",
       "      <td>3000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "pay_parameters   salary   bonus\n",
       "years                          \n",
       "2001            15000.0  3000.0\n",
       "2003            40000.0  2000.0\n",
       "2007                NaN  1000.0\n",
       "2008            12000.0  3000.0"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame4.drop(2002, axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2001</th>\n",
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       "      <th>2002</th>\n",
       "      <td>3000.0</td>\n",
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       "      <th>2003</th>\n",
       "      <td>40000.0</td>\n",
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       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>12000.0</td>\n",
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      ],
      "text/plain": [
       "pay_parameters   salary\n",
       "years                  \n",
       "2001            15000.0\n",
       "2002             3000.0\n",
       "2003            40000.0\n",
       "2007                NaN\n",
       "2008            12000.0"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame4.drop('bonus', axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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