pandas_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    4\n",
       "3   -6\n",
       "4    0\n",
       "5   -3\n",
       "6    8\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj = pd.Series([1,2,4,-6,0,-3,8])\n",
    "obj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  4, -6,  0, -3,  8])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=7, step=1)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_1 = pd.Series??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_1 = pd.Series( data = [\"Waqar\",\"Yawar\",\"Ali\",\"Ahmed\"], index = [\"W\",\"Y\",\"A\",\"Ah\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "W     Waqar\n",
       "Y     Yawar\n",
       "A       Ali\n",
       "Ah    Ahmed\n",
       "dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waqar\n",
      "Ahmed\n",
      "Yawar\n"
     ]
    }
   ],
   "source": [
    "print(obj_1['W'])\n",
    "print(obj_1['Ah'])\n",
    "print(obj_1['Y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Y    Yawar\n",
       "A      Ali\n",
       "W    Waqar\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_1[['Y','A','W']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1\n",
       "2     7\n",
       "5     4\n",
       "7     6\n",
       "8     7\n",
       "10    5\n",
       "11    8\n",
       "dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_2 = pd.Series(data = [1,-2,7,-1,0,4,-3,6,7,-1,5,8])\n",
    "obj_2[obj_2 > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      2\n",
       "1     -4\n",
       "2     14\n",
       "3     -2\n",
       "4      0\n",
       "5      8\n",
       "6     -6\n",
       "7     12\n",
       "8     14\n",
       "9     -2\n",
       "10    10\n",
       "11    16\n",
       "dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_2 * 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_3 = pd.Series(data =, index = ['first','second','third'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('second' in obj_3)\n",
    "print('third' in obj_3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can create a series using python dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = { 'w':'waqar',\n",
    "          'y':'yawar',\n",
    "          'a': 'ali',}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_names = pd.Series(names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "w    waqar\n",
       "y    yawar\n",
       "a      ali\n",
       "dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Balochistan    150000\n",
       "Giglit         200000\n",
       "Punjab         300000\n",
       "Sindh          800000\n",
       "dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_4 = pd.Series(data = [150000,200000,300000,800000], index = ['Balochistan','Giglit','Punjab','Sindh'])\n",
    "obj_4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Provinces\n",
       "Balochistan    150000\n",
       "Giglit         200000\n",
       "Punjab         300000\n",
       "Sindh          800000\n",
       "Name: province_population, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj_4.name = 'province_population'\n",
    "obj_4.index.name = \"Provinces\"\n",
    "obj_4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = { 'names' : ['waqar','ali','ahmed','yawar','malik','haider'],\n",
    "         'salaries' : [15000,20000,30000,40000,60000,70000],\n",
    "         'tax':['n/a','n/a','given','given','n/a','given'],\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "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>names</th>\n",
       "      <th>salaries</th>\n",
       "      <th>tax</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>waqar</td>\n",
       "      <td>15000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ali</td>\n",
       "      <td>20000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ahmed</td>\n",
       "      <td>30000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>yawar</td>\n",
       "      <td>40000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>malik</td>\n",
       "      <td>60000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>haider</td>\n",
       "      <td>70000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    names  salaries    tax\n",
       "0   waqar     15000    n/a\n",
       "1     ali     20000    n/a\n",
       "2   ahmed     30000  given\n",
       "3   yawar     40000  given\n",
       "4   malik     60000    n/a\n",
       "5  haider     70000  given"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame = pd.DataFrame(data)\n",
    "frame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For large DataFrames, the head method selects only the first five rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "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>names</th>\n",
       "      <th>salaries</th>\n",
       "      <th>tax</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>waqar</td>\n",
       "      <td>15000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ali</td>\n",
       "      <td>20000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ahmed</td>\n",
       "      <td>30000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>yawar</td>\n",
       "      <td>40000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>malik</td>\n",
       "      <td>60000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   names  salaries    tax\n",
       "0  waqar     15000    n/a\n",
       "1    ali     20000    n/a\n",
       "2  ahmed     30000  given\n",
       "3  yawar     40000  given\n",
       "4  malik     60000    n/a"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you specify a sequence of columns, the DataFrame’s columns will be arranged in\n",
    "that order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "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>names</th>\n",
       "      <th>salaries</th>\n",
       "      <th>tax</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>waqar</td>\n",
       "      <td>15000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ali</td>\n",
       "      <td>20000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ahmed</td>\n",
       "      <td>30000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>yawar</td>\n",
       "      <td>40000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>malik</td>\n",
       "      <td>60000</td>\n",
       "      <td>n/a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>haider</td>\n",
       "      <td>70000</td>\n",
       "      <td>given</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    names  salaries    tax\n",
       "4   waqar     15000    n/a\n",
       "3     ali     20000    n/a\n",
       "1   ahmed     30000  given\n",
       "2   yawar     40000  given\n",
       "0   malik     60000    n/a\n",
       "5  haider     70000  given"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(data, index = [4,3,1,2,0,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "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>names</th>\n",
       "      <th>tax</th>\n",
       "      <th>salaries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>waqar</td>\n",
       "      <td>n/a</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ali</td>\n",
       "      <td>n/a</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ahmed</td>\n",
       "      <td>given</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>yawar</td>\n",
       "      <td>given</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>malik</td>\n",
       "      <td>n/a</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>haider</td>\n",
       "      <td>given</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    names    tax  salaries\n",
       "0   waqar    n/a     15000\n",
       "1     ali    n/a     20000\n",
       "2   ahmed  given     30000\n",
       "3   yawar  given     40000\n",
       "4   malik    n/a     60000\n",
       "5  haider  given     70000"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(data, columns = ['names','tax','salaries'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you pass a column that isn’t contained in the dict, it will appear with missing values\n",
    "in the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame_2 = pd.DataFrame(data, columns = ['names','salaries','tax','debt'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A column in a DataFrame can be retrieved as a Series either by dict-like notation or\n",
    "by attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    15000\n",
      "1    20000\n",
      "2    30000\n",
      "3    40000\n",
      "4    60000\n",
      "5    70000\n",
      "Name: salaries, dtype: int64\n",
      "0     waqar\n",
      "1       ali\n",
      "2     ahmed\n",
      "3     yawar\n",
      "4     malik\n",
      "5    haider\n",
      "Name: names, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(frame['salaries'])\n",
    "print(frame.names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rows can also be retrieved by position or name with the special loc attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "names       malik\n",
       "salaries    60000\n",
       "tax           n/a\n",
       "Name: 4, dtype: object"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.loc[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "    names  salaries    tax   debt\n",
       "0   waqar     15000    n/a  15000\n",
       "1     ali     20000    n/a  15000\n",
       "2   ahmed     30000  given  15000\n",
       "3   yawar     40000  given  15000\n",
       "4   malik     60000    n/a  15000\n",
       "5  haider     70000  given  15000"
      ]
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     "execution_count": 91,
     "metadata": {},
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   ],
   "source": [
    "frame_2.debt = 15000\n",
    "frame_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you are assigning lists or arrays to a column, the value’s length must match the\n",
    "length of the DataFrame. If you assign a Series, its labels will be realigned exactly to\n",
    "the DataFrame’s index, inserting missing values in any holes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "values_for_debt = pd.Series(data = [1200,100,2000,3560,4000,2500], index = [3,2,1,4,5,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame_2.debt = values_for_debt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
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       "    names  salaries    tax  debt\n",
       "0   waqar     15000    n/a  2500\n",
       "1     ali     20000    n/a  2000\n",
       "2   ahmed     30000  given   100\n",
       "3   yawar     40000  given  1200\n",
       "4   malik     60000    n/a  3560\n",
       "5  haider     70000  given  4000"
      ]
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    "frame_2"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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