W3PracticeQuestions.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\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>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>78</td>\n",
       "      <td>84</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85</td>\n",
       "      <td>94</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96</td>\n",
       "      <td>89</td>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>83</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86</td>\n",
       "      <td>86</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    X   Y   Z\n",
       "0  78  84  86\n",
       "1  85  94  97\n",
       "2  96  89  96\n",
       "3  80  83  72\n",
       "4  86  86  83"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = pd.DataFrame( {'X':[78,85,96,80,86], 'Y':[84,94,89,83,86],'Z':[86,97,96,72,83]})\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "a  Anastasia   12.5         1     yes\n",
       "b       Dima    9.0         3      no\n",
       "c  Katherine   16.5         2     yes\n",
       "d      James    NaN         3      no\n",
       "e      Emily    9.0         2      no\n",
       "f    Michael   20.0         3     yes\n",
       "g    Matthew   14.5         1     yes\n",
       "h      Laura    NaN         1      no\n",
       "i      Kevin    8.0         2      no\n",
       "j      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],\n",
    "'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']\n",
    "d = pd.DataFrame(exam_data, index=labels)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 10 entries, a to j\n",
      "Data columns (total 4 columns):\n",
      "name        10 non-null object\n",
      "score       8 non-null float64\n",
      "attempts    10 non-null int64\n",
      "qualify     10 non-null object\n",
      "dtypes: float64(1), int64(1), object(2)\n",
      "memory usage: 400.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "d.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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",
       "\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>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "a  Anastasia   12.5         1     yes\n",
       "b       Dima    9.0         3      no\n",
       "c  Katherine   16.5         2     yes"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# d.head(3)\n",
    "d[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score\n",
       "a  Anastasia   12.5\n",
       "b       Dima    9.0\n",
       "c  Katherine   16.5\n",
       "d      James    NaN\n",
       "e      Emily    9.0\n",
       "f    Michael   20.0\n",
       "g    Matthew   14.5\n",
       "h      Laura    NaN\n",
       "i      Kevin    8.0\n",
       "j      Jonas   19.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d[['name', 'score']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>score</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>9.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>20.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>14.5</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   score qualify\n",
       "b    9.0      no\n",
       "d    NaN      no\n",
       "f   20.0     yes\n",
       "g   14.5     yes"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select 'name' and 'score' columns in rows 1, 3, 5, 6 from the following data frame.\n",
    "\n",
    "d.iloc[[1, 3, 5, 6], [1, 3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name  score  attempts qualify\n",
       "b     Dima    9.0         3      no\n",
       "d    James    NaN         3      no\n",
       "f  Michael   20.0         3     yes"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of attempts in the examination is greater than 2:\n",
    "\n",
    "d.loc[d.attempts>2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Rows: 10\n",
      "Number of Columns: 4\n"
     ]
    }
   ],
   "source": [
    "# count the number of rows and columns of a DataFrame\n",
    "total_rows=len(d.axes[0])\n",
    "total_cols=len(d.axes[1])\n",
    "\n",
    "print(\"Number of Rows: \"+str(total_rows))\n",
    "print(\"Number of Columns: \"+str(total_cols))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], dtype='object')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.axes[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name  score  attempts qualify\n",
       "d  James    NaN         3      no\n",
       "h  Laura    NaN         1      no"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select the rows where the score is missing\n",
    "d[d.score.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "c  Katherine   16.5         2     yes\n",
       "f    Michael   20.0         3     yes\n",
       "j      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rows where score between 15 and 20 (inclusive):\n",
    "d[d.score.between(15, 20)]\n",
    "# d.drop([3], axis=1, inplace = True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "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",
       "    .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>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name  score  attempts qualify\n",
       "j  Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  number of attempts in the examination is less than 2 and score greater than 15\n",
    "d[(d.attempts<2) & (d.score>15)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        name  score  attempts qualify     4     4\n",
      "a  Anastasia   12.5         1     yes   NaN   NaN\n",
      "b       Dima    9.0         3      no   NaN   NaN\n",
      "c  Katherine   16.5         2     yes   NaN   NaN\n",
      "d      James   11.5         3      no  11.5  11.5\n",
      "e      Emily    9.0         2      no   NaN   NaN\n",
      "f    Michael   20.0         3     yes   NaN   NaN\n",
      "g    Matthew   14.5         1     yes   NaN   NaN\n",
      "h      Laura    NaN         1      no   NaN   NaN\n",
      "i      Kevin    8.0         2      no   NaN   NaN\n",
      "j      Jonas   19.0         1     yes   NaN   NaN\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>11.5</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "a  Anastasia   12.5         1     yes\n",
       "b       Dima    9.0         3      no\n",
       "c  Katherine   16.5         2     yes\n",
       "d      James   11.5         3      no\n",
       "e      Emily    9.0         2      no\n",
       "f    Michael   20.0         3     yes\n",
       "g    Matthew   14.5         1     yes\n",
       "h      Laura    NaN         1      no\n",
       "i      Kevin    8.0         2      no\n",
       "j      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.loc['d', 'score'] =11.5\n",
    "d.loc['d', '4'] =11.5\n",
    "d.loc['d', 4] =11.5\n",
    "\n",
    "print(d)\n",
    "d.drop(['4', 4], axis=1, inplace=True)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calculate the sum of the examination attempts by the students\n",
    "d['attempts'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13.333333333333334"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the mean score for each different student in DataFrame\n",
    "d['score'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Append a new row:\n",
      "Print all records after insert a new record:\n",
      "        name  score  attempts qualify\n",
      "a  Anastasia   12.5         1     yes\n",
      "b       Dima    9.0         3      no\n",
      "c  Katherine   16.5         2     yes\n",
      "d      James   11.5         3      no\n",
      "e      Emily    9.0         2      no\n",
      "f    Michael   20.0         3     yes\n",
      "g    Matthew   14.5         1     yes\n",
      "h      Laura    NaN         1      no\n",
      "i      Kevin    8.0         2      no\n",
      "j      Jonas   19.0         1     yes\n",
      "k     Suresh   15.5         1     yes\n",
      "\n",
      "Delete the new row and display the original  rows:\n",
      "        name  score  attempts qualify\n",
      "a  Anastasia   12.5         1     yes\n",
      "b       Dima    9.0         3      no\n",
      "c  Katherine   16.5         2     yes\n",
      "d      James   11.5         3      no\n",
      "e      Emily    9.0         2      no\n",
      "f    Michael   20.0         3     yes\n",
      "g    Matthew   14.5         1     yes\n",
      "h      Laura    NaN         1      no\n",
      "i      Kevin    8.0         2      no\n",
      "j      Jonas   19.0         1     yes\n"
     ]
    }
   ],
   "source": [
    "# o append a new row 'k' to data frame with given values for each column. Now delete the new row and return the original DataFrame\n",
    "print(\"\\nAppend a new row:\")\n",
    "d.loc['k'] = [ 'Suresh', 15.5, 1, 'yes', ]\n",
    "print(\"Print all records after insert a new record:\")\n",
    "print(d)\n",
    "print(\"\\nDelete the new row and display the original  rows:\")\n",
    "d = d.drop('k')\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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",
       "\n",
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       "        text-align: right;\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>name</th>\n",
       "      <th>score</th>\n",
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       "  </thead>\n",
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       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
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       "      <td>yes</td>\n",
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       "    <tr>\n",
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       "      <td>Laura</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
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       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
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       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>11.5</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "f    Michael   20.0         3     yes\n",
       "g    Matthew   14.5         1     yes\n",
       "h      Laura    NaN         1      no\n",
       "i      Kevin    8.0         2      no\n",
       "c  Katherine   16.5         2     yes\n",
       "j      Jonas   19.0         1     yes\n",
       "d      James   11.5         3      no\n",
       "e      Emily    9.0         2      no\n",
       "b       Dima    9.0         3      no\n",
       "a  Anastasia   12.5         1     yes"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sort the DataFrame first by 'name' in descending order, then by 'score' in ascending order.\n",
    "# d.loc['g','name']='Matthew'\n",
    "d.sort_values(by=['name', 'score'], ascending=[False, True])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    <tr>\n",
       "      <th>b</th>\n",
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       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>James</td>\n",
       "      <td>11.5</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts  qualify\n",
       "a  Anastasia   12.5         1     True\n",
       "b       Dima    9.0         3    False\n",
       "c  Katherine   16.5         2     True\n",
       "d      James   11.5         3    False\n",
       "e      Emily    9.0         2    False\n",
       "f    Michael   20.0         3     True\n",
       "g    Matthew   14.5         1     True\n",
       "h      Laura    NaN         1    False\n",
       "i      Kevin    8.0         2    False\n",
       "j      Jonas   19.0         1     True"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  replace the 'qualify' column contains the values 'yes' and 'no' with True and False.\n",
    "d['qualify'] = d['qualify'].map({'yes':True, 'no':False})\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>Suresh</td>\n",
       "      <td>11.5</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts  qualify\n",
       "a  Anastasia   12.5         1     True\n",
       "b       Dima    9.0         3    False\n",
       "c  Katherine   16.5         2     True\n",
       "d     Suresh   11.5         3    False\n",
       "e      Emily    9.0         2    False\n",
       "f    Michael   20.0         3     True\n",
       "g    Matthew   14.5         1     True\n",
       "h      Laura    NaN         1    False\n",
       "i      Kevin    8.0         2    False\n",
       "j      Jonas   19.0         1     True"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  change the name 'James' to 'Suresh' in name column of the DataFrame.\n",
    "d['name'] = d['name'].replace('James', 'Suresh')\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>Suresh</td>\n",
       "      <td>11.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  qualify\n",
       "a  Anastasia   12.5     True\n",
       "b       Dima    9.0    False\n",
       "c  Katherine   16.5     True\n",
       "d     Suresh   11.5    False\n",
       "e      Emily    9.0    False\n",
       "f    Michael   20.0     True\n",
       "g    Matthew   14.5     True\n",
       "h      Laura    NaN    False\n",
       "i      Kevin    8.0    False\n",
       "j      Jonas   19.0     True"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  delete the 'attempts' column from the DataFrame\n",
    "e = d.copy()\n",
    "\n",
    "d.drop('attempts', axis=1, inplace=True)\n",
    "e.pop('attempts')\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>Suresh</td>\n",
       "      <td>11.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  qualify\n",
       "a  Anastasia   12.5     True\n",
       "b       Dima    9.0    False\n",
       "c  Katherine   16.5     True\n",
       "d     Suresh   11.5    False\n",
       "e      Emily    9.0    False\n",
       "f    Michael   20.0     True\n",
       "g    Matthew   14.5     True\n",
       "h      Laura    NaN    False\n",
       "i      Kevin    8.0    False\n",
       "j      Jonas   19.0     True"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>qualify</th>\n",
       "      <th>color</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>True</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "      <td>Blue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>True</td>\n",
       "      <td>Orange</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>Suresh</td>\n",
       "      <td>11.5</td>\n",
       "      <td>False</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>True</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>True</td>\n",
       "      <td>Blue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>Green</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>False</td>\n",
       "      <td>Green</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>True</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  qualify   color\n",
       "a  Anastasia   12.5     True     Red\n",
       "b       Dima    9.0    False    Blue\n",
       "c  Katherine   16.5     True  Orange\n",
       "d     Suresh   11.5    False     Red\n",
       "e      Emily    9.0    False   White\n",
       "f    Michael   20.0     True   White\n",
       "g    Matthew   14.5     True    Blue\n",
       "h      Laura    NaN    False   Green\n",
       "i      Kevin    8.0    False   Green\n",
       "j      Jonas   19.0     True     Red"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['color']=['Red','Blue','Orange','Red','White','White','Blue','Green','Green', 'Red']\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n",
      "Anastasia 12.5\n",
      "<class 'pandas.core.series.Series'>\n",
      "Dima 9.0\n",
      "<class 'pandas.core.series.Series'>\n",
      "Katherine 16.5\n",
      "<class 'pandas.core.series.Series'>\n",
      "Suresh 11.5\n",
      "<class 'pandas.core.series.Series'>\n",
      "Emily 9.0\n",
      "<class 'pandas.core.series.Series'>\n",
      "Michael 20.0\n",
      "<class 'pandas.core.series.Series'>\n",
      "Matthew 14.5\n",
      "<class 'pandas.core.series.Series'>\n",
      "Laura nan\n",
      "<class 'pandas.core.series.Series'>\n",
      "Kevin 8.0\n",
      "<class 'pandas.core.series.Series'>\n",
      "Jonas 19.0\n"
     ]
    }
   ],
   "source": [
    "#  iterate over rows in a DataFrame.\n",
    "for index, row in d.iterrows():\n",
    "    print(type(row))\n",
    "    print(row['name'], row['score'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['name', 'score', 'qualify', 'color'], dtype='object')\n",
      "['name', 'score', 'qualify', 'color']\n"
     ]
    }
   ],
   "source": [
    "#  get list from DataFrame column headers. \n",
    "print(d.axes[1])\n",
    "print(list(d.columns.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   col1  col2  col3\n",
      "0     1     4     7\n",
      "1     2     5     8\n",
      "2     3     6     9\n"
     ]
    },
    {
     "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>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Column1  Column2  Column3\n",
       "0        1        4        7\n",
       "1        2        5        8\n",
       "2        3        6        9"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# rename columns of a given DataFrame\n",
    "d = {'col1': [1, 2, 3], 'col2': [4, 5, 6], 'col3': [7, 8, 9]}\n",
    "df = pd.DataFrame(data=d)\n",
    "print(df)\n",
    "df.columns = ['Column1', 'Column2', 'Column3']\n",
    "df = df.rename(columns={'col1': 'Column1', 'col2': 'Column2', 'col3': 'Column3'})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "1     4     5     8\n",
       "3     4     7     0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'col1': [1, 4, 3, 4, 5], 'col2': [4, 5, 6, 7, 8], 'col3': [7, 8, 9, 0, 1]}\n",
    "df = pd.DataFrame(data=d)\n",
    "df.loc[df.col1==4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrame\n",
      "   col3  col2  col1\n",
      "0     7     4     1\n",
      "1     8     5     4\n",
      "2     9     6     3\n",
      "3     0     7     4\n",
      "4     1     8     5\n"
     ]
    }
   ],
   "source": [
    "# change the order of a DataFrame columns\n",
    "d = {'col1': [1, 4, 3, 4, 5], 'col2': [4, 5, 6, 7, 8], 'col3': [7, 8, 9, 0, 1]}\n",
    "df = pd.DataFrame(data=d)\n",
    "print(\"Original DataFrame\")\n",
    "# print(df.loc[:,['col3', 'col2', 'col1']])\n",
    "df = df[['col3', 'col2', 'col1']]\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# count city wise number of people from a given of data set\n",
    "df1 = pd.DataFrame({'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "'city': ['California', 'Los Angeles', 'California', 'California', 'California', 'Los Angeles', 'Los Angeles', 'Georgia', 'Georgia', 'Los Angeles']})\n",
    "# g1 = df1.groupby([\"city\"]).size().reset_index(name='Number of people')\n",
    "# print(g1)\n",
    "g = df1.groupby([\"city\"]).size()\n",
    "# df1[\"city\"].size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "city\n",
       "California     4\n",
       "Georgia        2\n",
       "Los Angeles    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>city</th>\n",
       "      <th>Number of People</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>California</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          city  Number of People\n",
       "0   California                 4\n",
       "1      Georgia                 2\n",
       "2  Los Angeles                 4"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g.reset_index(name=\"Number of People\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "0     1     4     7\n",
       "2     3     6     9\n",
       "3     4     7     0\n",
       "4     5     8     1"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  delete DataFrame row(s) based on given column value.\n",
    "d = {'col1': [1, 4, 3, 4, 5], 'col2': [4, 5, 6, 7, 8], 'col3': [7, 8, 9, 0, 1]}\n",
    "df = pd.DataFrame(data=d)\n",
    "df = df[df.col2 != 5]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "0     1     4     7\n",
       "1     4     5     8\n",
       "2     3     6     9\n",
       "3     4     7     0\n",
       "4     5     8     1"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# widen output display to see more columns.\n",
    "d = {'col1': [1, 4, 3, 4, 5], 'col2': [4, 5, 6, 7, 8], 'col3': [7, 8, 9, 0, 1]}\n",
    "df = pd.DataFrame(data=d)\n",
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.width', 1000)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "2     3     6     9"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[[2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "2  Katherine   16.5         2     yes\n",
       "3      James    0.0         3      no\n",
       "4      Emily    9.0         2      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    0.0         1      no\n",
       "8      Kevin    8.0         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replace all the NaN values with Zero's in a column of a dataframe.\n",
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],\n",
    "        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "df = pd.DataFrame(exam_data)\n",
    "df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                name  score  attempts qualify\n",
      "Anastasia  Anastasia   12.5         1     yes\n",
      "Dima            Dima    9.0         3      no\n",
      "Katherine  Katherine   16.5         2     yes\n",
      "James          James    NaN         3      no\n",
      "Emily          Emily    9.0         2      no\n",
      "Michael      Michael   20.0         3     yes\n",
      "Matthew      Matthew   14.5         1     yes\n",
      "Laura          Laura    NaN         1      no\n",
      "Kevin          Kevin    8.0         2      no\n",
      "Jonas          Jonas   19.0         1     yes\n"
     ]
    }
   ],
   "source": [
    "# program to convert index in a column of the given dataframe\n",
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],\n",
    "        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "df = pd.DataFrame(exam_data, index=exam_data['name'])\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "2  Katherine   16.5         2     yes\n",
       "3      James    NaN         3      no\n",
       "4      Emily    9.0         2      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    NaN         1      no\n",
       "8      Kevin    8.0         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reset_index(level=0, inplace=True, drop=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "2  Katherine   16.5         2     yes\n",
       "3      James    NaN         3      no\n",
       "4      Emily    9.0         2      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    NaN         1      no\n",
       "8      Kevin    8.0         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set a given value for particular cell in DataFrame using index value.\n",
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],\n",
    "        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "df = pd.DataFrame(exam_data)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "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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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
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       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
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       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>10.2</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "2  Katherine   16.5         2     yes\n",
       "3      James    NaN         3      no\n",
       "4      Emily    9.0         2      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    NaN         1      no\n",
       "8      Kevin   10.2         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.set_value(8, 'score', 10.2)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
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       "      <td>yes</td>\n",
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       "      <td>3</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
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       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "2  Katherine   16.5         2     yes\n",
       "3      James    NaN         3      no\n",
       "4      Emily    9.0         2      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    NaN         1      no\n",
       "8      Kevin    8.0         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[8, 'score'] = 8\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
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       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
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       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
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       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "2  Katherine   16.5         2     yes\n",
       "3      James    NaN         3      no\n",
       "4      Emily    9.0         2      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    NaN         1      no\n",
       "8      Kevin   10.0         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.at[8, 'score'] =10\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],\n",
    "        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "df = pd.DataFrame(exam_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().values.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>1</td>\n",
       "      <td>Dima</td>\n",
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       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
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       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
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       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia   12.5         1     yes\n",
       "1       Dima    9.0         3      no\n",
       "3      James    NaN         3      no\n",
       "5    Michael   20.0         3     yes\n",
       "6    Matthew   14.5         1     yes\n",
       "7      Laura    NaN         1      no\n",
       "8      Kevin    8.0         2      no\n",
       "9      Jonas   19.0         1     yes"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop a list of rows from a specified DataFrame\n",
    "df=df.drop(df.index[[2, 4]])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          0         1\n",
      "0 -0.031815  0.974502\n",
      "1  0.246892  1.942115\n",
      "2 -0.442063  0.586975\n",
      "3  1.075334  0.354166\n",
      "4 -1.638499 -0.107473\n",
      "5  1.766559  0.397201\n",
      "6 -1.604861 -1.577927\n",
      "7 -0.068271 -0.085744\n",
      "8  0.498487 -0.461898\n",
      "9 -0.437444  1.882272\n",
      "          0         1\n",
      "8  0.498487 -0.461898\n",
      "2 -0.442063  0.586975\n",
      "5  1.766559  0.397201\n",
      "6 -1.604861 -1.577927\n",
      "3  1.075334  0.354166\n",
      "1  0.246892  1.942115\n",
      "0 -0.031815  0.974502\n",
      "          0         1\n",
      "4 -1.638499 -0.107473\n",
      "7 -0.068271 -0.085744\n",
      "9 -0.437444  1.882272\n"
     ]
    }
   ],
   "source": [
    "# Divide a DataFrame in a given ratio\n",
    "df = pd.DataFrame(np.random.randn(10, 2))\n",
    "print(df)\n",
    "\n",
    "part_70 = df.sample(frac=0.7,random_state=10)\n",
    "part_30 = df.drop(part_70.index)\n",
    "print(part_70)\n",
    "print(part_30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0       100\n",
      "1       200\n",
      "2    python\n",
      "3    300.12\n",
      "4       400\n",
      "dtype: object 0       10\n",
      "1       20\n",
      "2      php\n",
      "3    30.12\n",
      "4       40\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "# Combining two series into a DataFrame\n",
    "\n",
    "s1 = pd.Series(['100', '200', 'python', '300.12', '400'])\n",
    "s2 = pd.Series(['10', '20', 'php', '30.12', '40'])\n",
    "print(s1, s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>200</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>python</td>\n",
       "      <td>php</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>300.12</td>\n",
       "      <td>30.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>400</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0      1\n",
       "0     100     10\n",
       "1     200     20\n",
       "2  python    php\n",
       "3  300.12  30.12\n",
       "4     400     40"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([s1, s2], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       100\n",
       "1       200\n",
       "2    python\n",
       "3    300.12\n",
       "4       400\n",
       "0        10\n",
       "1        20\n",
       "2       php\n",
       "3     30.12\n",
       "4        40\n",
       "dtype: object"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = pd.concat([s1, s2], axis=0)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       100\n",
       "1       200\n",
       "2    python\n",
       "3    300.12\n",
       "4       400\n",
       "0        10\n",
       "1        20\n",
       "2       php\n",
       "3     30.12\n",
       "4        40\n",
       "dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
       "      <td>16.5</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Dima</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "5    Michael   20.0         3     yes\n",
       "2  Katherine   16.5         2     yes\n",
       "7      Laura    NaN         1      no\n",
       "6    Matthew   14.5         1     yes\n",
       "8      Kevin    8.0         2      no\n",
       "1       Dima    9.0         3      no\n",
       "9      Jonas   19.0         1     yes\n",
       "3      James    NaN         3      no\n",
       "4      Emily    9.0         2      no\n",
       "0  Anastasia   12.5         1     yes"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],\n",
    "        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "df = pd.DataFrame(exam_data)\n",
    "df = df.sample(frac=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3 entries, 0 to 2\n",
      "Data columns (total 1 columns):\n",
      "dates    3 non-null datetime64[ns]\n",
      "dtypes: datetime64[ns](1)\n",
      "memory usage: 152.0 bytes\n"
     ]
    }
   ],
   "source": [
    "# Convert DataFrame column type from string to datetime.\n",
    "s = pd.DataFrame({'dates': ['3/11/2000', '3/12/2000', '3/13/2000']})\n",
    "r = pd.DataFrame(pd.to_datetime(s['dates']))\n",
    "r.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrame\n",
      "   col1  col2  col3\n",
      "0     1     4     7\n",
      "1     2     5     8\n",
      "2     3     6     9\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[4, 5, 6]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'col1': [1, 2, 3], 'col2': [4, 5, 6], 'col3': [7, 8, 9]}\n",
    "df = pd.DataFrame(data=d)\n",
    "print(\"Original DataFrame\")\n",
    "print(df)\n",
    "col2_list = df[\"col2\"].tolist()\n",
    "col2_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4\n",
       "1    5\n",
       "2    6\n",
       "Name: col2, dtype: int64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['col2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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>Column1</th>\n",
       "      <th>Column2</th>\n",
       "      <th>Column3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Index1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index7</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index8</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index11</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index12</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index13</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Index15</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Column1  Column2  Column3\n",
       "Index1         0      0.0      0.0\n",
       "Index2         0      0.0      0.0\n",
       "Index3         0      0.0      0.0\n",
       "Index4         0      0.0      0.0\n",
       "Index5         0      0.0      0.0\n",
       "Index6         0      0.0      0.0\n",
       "Index7         0      0.0      0.0\n",
       "Index8         0      0.0      0.0\n",
       "Index9         0      0.0      0.0\n",
       "Index10        0      0.0      0.0\n",
       "Index11        0      0.0      0.0\n",
       "Index12        0      0.0      0.0\n",
       "Index13        0      0.0      0.0\n",
       "Index14        0      0.0      0.0\n",
       "Index15        0      0.0      0.0"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a DataFrame from a Numpy array and specify the index column and column headers\n",
    "dtype = [('Column1','int32'), ('Column2','float32'), ('Column3','float32')]\n",
    "values = np.zeros(15, dtype=dtype)\n",
    "values\n",
    "index = ['Index'+str(i) for i in range(1, len(values)+1)]\n",
    "df = pd.DataFrame(values, index=index)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pd' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-19-7f0134c8bb59>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0md\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;34m'col1'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m7\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'col2'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m6\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m9\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'col3'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m8\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m12\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m11\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'col1'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'col1'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'pd' is not defined"
     ]
    }
   ],
   "source": [
    "d = {'col1': [1, 2, 3, 4, 7], 'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}\n",
    "df = pd.DataFrame(data=d)\n",
    "print(df)\n",
    "print(df['col1'].max())\n",
    "print(df.iloc[df['col1'].values.argmax()])\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "print('col1' in df.columns.values)\n",
    "print('col4' in df.columns.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "col1    int64\n",
       "col2    int64\n",
       "col3    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get the datatypes of columns of a DataFrame\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After appending some data:\n"
     ]
    },
    {
     "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2\n",
       "0     0     0\n",
       "1     1     1\n",
       "2     2     2"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame()\n",
    "data = pd.DataFrame({\"col1\": range(3),\"col2\": range(3)})\n",
    "print(\"After appending some data:\")\n",
    "df = df.append(data)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name         object\n",
      "score       float64\n",
      "attempts      int64\n",
      "qualify      object\n",
      "dtype: object\n",
      "name        object\n",
      "score        int32\n",
      "attempts     int64\n",
      "qualify     object\n",
      "dtype: object\n"
     ]
    },
    {
     "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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>attempts</th>\n",
       "      <th>qualify</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Dima</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Katherine</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>James</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Emily</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Michael</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Laura</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Jonas</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name  score  attempts qualify\n",
       "0  Anastasia     12         1     yes\n",
       "1       Dima      9         3      no\n",
       "2  Katherine     16         2     yes\n",
       "3      James     12         3      no\n",
       "4      Emily      9         2      no\n",
       "5    Michael     20         3     yes\n",
       "6    Matthew     14         1     yes\n",
       "7      Laura     11         1      no\n",
       "8      Kevin      8         2      no\n",
       "9      Jonas     19         1     yes"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# program to convert the datatype of a given column \n",
    "exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],\n",
    "        'score': [12.5, 9.1, 16.5, 12.77, 9.21, 20.22, 14.5, 11.34, 8.8, 19.13],\n",
    "        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}\n",
    "df = pd.DataFrame(exam_data)\n",
    "print(df.dtypes)\n",
    "df = df.astype({\"score\": int})\n",
    "print(df.dtypes)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0\n",
      "0  1000.0\n",
      "1  2000.0\n",
      "2  3000.0\n",
      "3 -4000.0\n",
      "4     inf\n",
      "5    -inf\n",
      "        0\n",
      "0  1000.0\n",
      "1  2000.0\n",
      "2  3000.0\n",
      "3 -4000.0\n",
      "4     NaN\n",
      "5     NaN\n"
     ]
    }
   ],
   "source": [
    "# remove infinite values from a given DataFrame.\n",
    "df = pd.DataFrame([1000, 2000, 3000, -4000, np.inf, -np.inf])\n",
    "print(df)\n",
    "df = df.replace([np.inf, -np.inf], np.nan)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "0     1     4     7\n",
       "1     2     5     8\n",
       "2     3     6    12\n",
       "3     4     9     1\n",
       "4     7     5    11"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# insert a given column at a specific column index in a DataFrame.\n",
    "d = {'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}\n",
    "df = pd.DataFrame(data=d)\n",
    "idx = 0\n",
    "new_col = [1, 2, 3, 4, 7]  \n",
    "\n",
    "df.insert(loc=idx, column='col1', value=new_col)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2\n",
       "0     2     4\n",
       "1     1     3"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert a given list of lists into a Dataframe.\n",
    "my_lists = [['col1', 'col2'], [2, 4], [1, 3]]\n",
    "# sets the headers as list\n",
    "headers = my_lists.pop(0) \n",
    "df = pd.DataFrame(my_lists, columns = headers)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0  1\n",
       "0  2  4\n",
       "1  1  3"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert a given list of lists into a Dataframe.\n",
    "my_lists = [[2, 4], [1, 3]]\n",
    "# sets the headers as list\n",
    "# headers = my_lists.pop(0) \n",
    "df = pd.DataFrame(my_lists)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "col1\n",
       "C1          [1, 2]\n",
       "C2    [3, 3, 4, 5]\n",
       "C3             [6]\n",
       "Name: col2, dtype: object"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  a Pandas program to group by the first column and get second column as lists in rows\n",
    "df = pd.DataFrame( {'col1':['C1','C1','C2','C2','C2','C3','C2'], 'col2':[1,2,3,3,4,6,5]})\n",
    "# df = df.groupby('col1').size()#.apply(list)\n",
    "df = df.groupby('col1')['col2'].apply(list)\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "# Write a Pandas program to get column index from column name of a given DataFrame.\n",
    "d = {'col1': [1, 2, 3, 4, 7], 'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}\n",
    "df = pd.DataFrame(data=d)\n",
    "print(df.columns.get_loc(\"col2\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "3\n",
      "3\n"
     ]
    }
   ],
   "source": [
    "print(len(df.axes[1]))\n",
    "print(len(df.columns))\n",
    "print(len(df.columns.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   col1  col2\n",
      "0     1     4\n",
      "1     2     5\n",
      "2     3     6\n",
      "3     4     9\n",
      "4     7     5\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col1</th>\n",
       "      <th>col2</th>\n",
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      "text/plain": [
       "   col1  col2\n",
       "0     1     4\n",
       "1     2     5\n",
       "2     3     6"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Write a Pandas program to select all columns, except one given column in a DataFrame.\n",
    "d = {'col1': [1, 2, 3, 4, 7], 'col2': [4, 5, 6, 9, 5], 'col3': [7, 8, 12, 1, 11]}\n",
    "df = pd.DataFrame(data=d)\n",
    "df = df.loc[:, df.columns != 'col3']\n",
    "print(df)\n",
    "df.iloc[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "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",
       "    .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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2\n",
       "3     4     9\n",
       "4     7     5"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "0     1     4     7\n",
       "1     2     5     5\n",
       "2     3     6     8\n",
       "3     4     9    12\n",
       "4     7     5     1\n",
       "5    11     0    11"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'col1': [1, 2, 3, 4, 7, 11], 'col2': [4, 5, 6, 9, 5, 0], 'col3': [7, 5, 8, 12, 1,11]}\n",
    "df = pd.DataFrame(data=d)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
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       "      <td>11</td>\n",
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       "      <td>3</td>\n",
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       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "5    11     0    11\n",
       "4     7     5     1\n",
       "3     4     9    12"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df1 = df.nlargest(3, 'col1')\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
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       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1  col2  col3\n",
       "0     1     4     7\n",
       "1     2     5     5\n",
       "2     3     6     8\n",
       "3     4     9    12"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "color\n",
      "director_name\n",
      "num_critic_for_reviews\n",
      "duration\n",
      "director_facebook_likes\n",
      "actor_3_facebook_likes\n",
      "actor_2_name\n",
      "actor_1_facebook_likes\n",
      "gross\n",
      "genres\n",
      "actor_1_name\n",
      "movie_title\n",
      "num_voted_users\n",
      "cast_total_facebook_likes\n",
      "actor_3_name\n",
      "facenumber_in_poster\n",
      "plot_keywords\n",
      "movie_imdb_link\n",
      "num_user_for_reviews\n",
      "language\n",
      "country\n",
      "content_rating\n",
      "budget\n",
      "title_year\n",
      "actor_2_facebook_likes\n",
      "imdb_score\n",
      "aspect_ratio\n",
      "movie_facebook_likes\n"
     ]
    }
   ],
   "source": [
    "l = ['color', 'director_name', 'num_critic_for_reviews', 'duration', 'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name', 'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name', 'movie_title', 'num_voted_users', 'cast_total_facebook_likes', 'actor_3_name', 'facenumber_in_poster', 'plot_keywords', 'movie_imdb_link', 'num_user_for_reviews', 'language', 'country', 'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes', 'imdb_score', 'aspect_ratio', 'movie_facebook_likes']\n",
    "for i in l:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = {'a':1, 'b':3, 'c':4, 'd':23}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([('a', 1), ('b', 3), ('c', 4), ('d', 23)])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a', 'b', 'c', 'd']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(d.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 3, 4, 23]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(d.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'f': 2, 'g': 3, 'h': 3, 'j': 2, 'd': 2, 's': 1})"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = \"fghjhgfjhgdsd\"\n",
    "Counter(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=[1, 2, 31, 1, 2, 3, 5,2, 1, 56,3,21, 21]\n",
    "r= Counter(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(56, 1), (31, 1), (5, 1), (21, 2), (3, 2), (2, 3), (1, 3)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(r.items(), key=lambda xy:(xy[1], -xy[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[0. , 1. , 2. , 3. ],\n",
       "        [0.5, 1.5, 2.5, 3.5],\n",
       "        [1. , 2. , 3. , 4. ]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "x= 3\n",
    "y=4\n",
    "np.matrix([[i+j/2 for i in range(y)] for j in range(x)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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