18_pandas_dataframes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas DataFrame\n",
    "    Pandas dataframe extends numpy two-dimensional arrays by giving labels to the columns and in case explicit indices are provided to the rows as well\n",
    "## Learning Objectives\n",
    "    1. Creating DataFrames from Series objects\n",
    "    2. Reading DataFrames from an external file...\n",
    "    3. Setting Indexes\n",
    "    4. Numeric Operations for Selecting, combining, and creating colums\n",
    "    5. Concatenate dataframes\n",
    "    6. How to iterate over a dataframe's items\n",
    "    7. Drop and inplace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports, follow the conventions...\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating a DataFrame from series \n",
    "    Note: This way of creating dataframes is not common!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "keys of the above dictionary are used as column names\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>2020</th>\n",
       "      <th>2021</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>91.3</td>\n",
       "      <td>99.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>83.0</td>\n",
       "      <td>91.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>99.4</td>\n",
       "      <td>99.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>99.9</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>84.5</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matlab</th>\n",
       "      <td>76.2</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHP</th>\n",
       "      <td>72.4</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>84.8</td>\n",
       "      <td>84.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ruby</th>\n",
       "      <td>96.5</td>\n",
       "      <td>76.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             2020   2021\n",
       "C            91.3   99.9\n",
       "C#           83.0   91.3\n",
       "C++          99.4   99.4\n",
       "Java         99.9   92.0\n",
       "JavaScript   84.5   83.0\n",
       "Matlab       76.2   53.0\n",
       "PHP          72.4   83.0\n",
       "Python      100.0  100.0\n",
       "R            84.8   84.8\n",
       "Ruby         96.5   76.2"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creating from two series objects\n",
    "pop2020 = pd.Series([99.9, 91.3, 99.4, 100, 83, 72.4, 84.5, 96.5, 84.8, 76.2],\n",
    "                    index=['Java','C','C++','Python','C#','PHP','JavaScript','Ruby','R','Matlab'], name='2014')\n",
    "pop2021 = pd.Series({\"C\" : 99.9, \"C#\" : 91.3, \"C++\" : 99.4, \"Java\" : 92, \"JavaScript\" : 83, \n",
    "                     \"Matlab\" : 53, \"PHP\" : 83, \"Python\" : 100, \"R\" : 84.8, \"Ruby\" : 76.2}, name='2015')\n",
    "programming_languages_popularity_df = pd.DataFrame({'2020':pop2020, '2021':pop2021})\n",
    "print(\"keys of the above dictionary are used as column names\")\n",
    "programming_languages_popularity_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading DataFrames from an external file...\n",
    "    Note: This is the most common way of reading dataframes, which I'm aware of..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>95.5</td>\n",
       "      <td>91.3</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.4</td>\n",
       "      <td>99.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>95.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>84.5</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matlab</th>\n",
       "      <td>56.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHP</th>\n",
       "      <td>84.8</td>\n",
       "      <td>83.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>74.3</td>\n",
       "      <td>84.8</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ruby</th>\n",
       "      <td>78.9</td>\n",
       "      <td>76.2</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             2020   2021   2022\n",
       "C            95.5   99.9   98.0\n",
       "C#           95.5   91.3   90.0\n",
       "C++          95.5   99.4   99.5\n",
       "Java         95.0   92.0   91.0\n",
       "JavaScript   84.5   83.0   83.0\n",
       "Matlab       56.0   53.0   49.0\n",
       "PHP          84.8   83.0   86.0\n",
       "Python      100.0  100.0  100.0\n",
       "R            74.3   84.8   85.0\n",
       "Ruby         78.9   76.2   80.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_path = \"files/programming_languages_popularity.csv\"\n",
    "# file_path = r\"C:\\Users\\pooya\\projects\\PythonSchool\\files\\programming_languages_popularity.csv\"\n",
    "# column one or column at index zero is used as index!\n",
    "popularity_df = pd.read_csv(file_path, index_col=0)\n",
    "popularity_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extracting array values: \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 95.5,  99.9,  98. ],\n",
       "       [ 95.5,  91.3,  90. ],\n",
       "       [ 95.5,  99.4,  99.5],\n",
       "       [ 95. ,  92. ,  91. ],\n",
       "       [ 84.5,  83. ,  83. ],\n",
       "       [ 56. ,  53. ,  49. ],\n",
       "       [ 84.8,  83. ,  86. ],\n",
       "       [100. , 100. , 100. ],\n",
       "       [ 74.3,  84.8,  85. ],\n",
       "       [ 78.9,  76.2,  80. ]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"extracting array values: \")\n",
    "popularity_df.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extracting index values\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['C', 'C#', 'C++', 'Java', 'JavaScript', 'Matlab', 'PHP', 'Python', 'R',\n",
       "       'Ruby'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"extracting index values\")\n",
    "popularity_df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extracting columns\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['2020', '2021', '2022'], dtype='object')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"extracting columns\")\n",
    "popularity_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extracting columns\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['2020', '2021', '2022'], dtype='object')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"extracting columns\")\n",
    "popularity_df.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Getting a column\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "C              95.5\n",
       "C#             95.5\n",
       "C++            95.5\n",
       "Java           95.0\n",
       "JavaScript     84.5\n",
       "Matlab         56.0\n",
       "PHP            84.8\n",
       "Python        100.0\n",
       "R              74.3\n",
       "Ruby           78.9\n",
       "Name: 2020, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Getting a column\")\n",
    "popularity_df['2020']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>95.5</td>\n",
       "      <td>91.3</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    2020  2021  2022\n",
       "C   95.5  99.9  98.0\n",
       "C#  95.5  91.3  90.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# integer location\n",
    "popularity_df.iloc[0: 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The first slicing is for the indices(first dimension) and the second one is for the columns(second dimension)\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>2020</th>\n",
       "      <th>2021</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>95.5</td>\n",
       "      <td>91.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>95.0</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>84.5</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            2020  2021\n",
       "C           95.5  99.9\n",
       "C#          95.5  91.3\n",
       "C++         95.5  99.4\n",
       "Java        95.0  92.0\n",
       "JavaScript  84.5  83.0"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# integer location\n",
    "print(\"The first slicing is for the indices(first dimension) and the second one is for the columns(second dimension)\")\n",
    "popularity_df.iloc[:5, :2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Getting a series and then, getting its values using an integer index:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "95.5"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Getting a series and then, getting its values using an integer index:\")\n",
    "popularity_df['2020'][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Numeric Operations for Selecting, combining, and creating colums"
   ]
  },
  {
   "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>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>98.0</td>\n",
       "      <td>97.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>95.5</td>\n",
       "      <td>91.3</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.4</td>\n",
       "      <td>99.5</td>\n",
       "      <td>98.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>95.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>92.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>84.5</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            2020  2021  2022    Average\n",
       "C           95.5  99.9  98.0  97.800000\n",
       "C#          95.5  91.3  90.0  92.266667\n",
       "C++         95.5  99.4  99.5  98.133333\n",
       "Java        95.0  92.0  91.0  92.666667\n",
       "JavaScript  84.5  83.0  83.0  83.500000"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popularity_df['Average'] = (popularity_df['2020'] + popularity_df['2021'] + popularity_df['2022']) / 3\n",
    "# head is used to show the by default first 5 rows. Use tail for showing items from the end of file \n",
    "popularity_df.head() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sorting a dataframe based on a column\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>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>98.0</td>\n",
       "      <td>97.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>95.5</td>\n",
       "      <td>91.3</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.4</td>\n",
       "      <td>99.5</td>\n",
       "      <td>98.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>95.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>92.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHP</th>\n",
       "      <td>84.8</td>\n",
       "      <td>83.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>84.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>84.5</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ruby</th>\n",
       "      <td>78.9</td>\n",
       "      <td>76.2</td>\n",
       "      <td>80.0</td>\n",
       "      <td>78.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>74.3</td>\n",
       "      <td>84.8</td>\n",
       "      <td>85.0</td>\n",
       "      <td>81.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matlab</th>\n",
       "      <td>56.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>52.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             2020   2021   2022     Average\n",
       "Python      100.0  100.0  100.0  100.000000\n",
       "C            95.5   99.9   98.0   97.800000\n",
       "C#           95.5   91.3   90.0   92.266667\n",
       "C++          95.5   99.4   99.5   98.133333\n",
       "Java         95.0   92.0   91.0   92.666667\n",
       "PHP          84.8   83.0   86.0   84.600000\n",
       "JavaScript   84.5   83.0   83.0   83.500000\n",
       "Ruby         78.9   76.2   80.0   78.366667\n",
       "R            74.3   84.8   85.0   81.366667\n",
       "Matlab       56.0   53.0   49.0   52.666667"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Sorting a dataframe based on a column\")\n",
    "popularity_df = popularity_df.sort_values('2020', ascending=False)\n",
    "popularity_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sorting based on more than one column with varying strategies of odering for each of the columns\n",
      "orders of the columns for sorting matters!\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>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Matlab</th>\n",
       "      <td>56.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>52.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>74.3</td>\n",
       "      <td>84.8</td>\n",
       "      <td>85.0</td>\n",
       "      <td>81.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ruby</th>\n",
       "      <td>78.9</td>\n",
       "      <td>76.2</td>\n",
       "      <td>80.0</td>\n",
       "      <td>78.366667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>84.5</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHP</th>\n",
       "      <td>84.8</td>\n",
       "      <td>83.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>84.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>95.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>92.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>98.0</td>\n",
       "      <td>97.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>95.5</td>\n",
       "      <td>99.4</td>\n",
       "      <td>99.5</td>\n",
       "      <td>98.133333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>95.5</td>\n",
       "      <td>91.3</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             2020   2021   2022     Average\n",
       "Matlab       56.0   53.0   49.0   52.666667\n",
       "R            74.3   84.8   85.0   81.366667\n",
       "Ruby         78.9   76.2   80.0   78.366667\n",
       "JavaScript   84.5   83.0   83.0   83.500000\n",
       "PHP          84.8   83.0   86.0   84.600000\n",
       "Java         95.0   92.0   91.0   92.666667\n",
       "C            95.5   99.9   98.0   97.800000\n",
       "C++          95.5   99.4   99.5   98.133333\n",
       "C#           95.5   91.3   90.0   92.266667\n",
       "Python      100.0  100.0  100.0  100.000000"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"sorting based on more than one column with varying strategies of odering for each of the columns\")\n",
    "print(\"orders of the columns for sorting matters!\")\n",
    "popularity_df = popularity_df.sort_values(['2020', '2021'], ascending=[1, 0])\n",
    "popularity_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020       56.000000\n",
       "2021       53.000000\n",
       "2022       49.000000\n",
       "Average    52.666667\n",
       "dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popularity_df.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020       86.000000\n",
       "2021       86.260000\n",
       "2022       86.150000\n",
       "Average    86.136667\n",
       "dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean over rows\n",
    "popularity_df.mean(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Matlab         52.666667\n",
       "R              81.366667\n",
       "Ruby           78.366667\n",
       "JavaScript     83.500000\n",
       "PHP            84.600000\n",
       "Java           92.666667\n",
       "C              97.800000\n",
       "C++            98.133333\n",
       "C#             92.266667\n",
       "Python        100.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean over columns\n",
    "popularity_df.mean(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Matlab</th>\n",
       "      <td>3146.00</td>\n",
       "      <td>2819.00</td>\n",
       "      <td>2411.00</td>\n",
       "      <td>2783.777778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>5530.49</td>\n",
       "      <td>7201.04</td>\n",
       "      <td>7235.00</td>\n",
       "      <td>6630.534444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ruby</th>\n",
       "      <td>6235.21</td>\n",
       "      <td>5816.44</td>\n",
       "      <td>6410.00</td>\n",
       "      <td>6151.334444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>7150.25</td>\n",
       "      <td>6899.00</td>\n",
       "      <td>6899.00</td>\n",
       "      <td>6982.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHP</th>\n",
       "      <td>7201.04</td>\n",
       "      <td>6899.00</td>\n",
       "      <td>7406.00</td>\n",
       "      <td>7167.160000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>9035.00</td>\n",
       "      <td>8474.00</td>\n",
       "      <td>8291.00</td>\n",
       "      <td>8597.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>9130.25</td>\n",
       "      <td>9990.01</td>\n",
       "      <td>9614.00</td>\n",
       "      <td>9574.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>9130.25</td>\n",
       "      <td>9890.36</td>\n",
       "      <td>9910.25</td>\n",
       "      <td>9640.151111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>9130.25</td>\n",
       "      <td>8345.69</td>\n",
       "      <td>8110.00</td>\n",
       "      <td>8523.137778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>10010.00</td>\n",
       "      <td>10010.00</td>\n",
       "      <td>10010.00</td>\n",
       "      <td>10010.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                2020      2021      2022       Average\n",
       "Matlab       3146.00   2819.00   2411.00   2783.777778\n",
       "R            5530.49   7201.04   7235.00   6630.534444\n",
       "Ruby         6235.21   5816.44   6410.00   6151.334444\n",
       "JavaScript   7150.25   6899.00   6899.00   6982.250000\n",
       "PHP          7201.04   6899.00   7406.00   7167.160000\n",
       "Java         9035.00   8474.00   8291.00   8597.111111\n",
       "C            9130.25   9990.01   9614.00   9574.840000\n",
       "C++          9130.25   9890.36   9910.25   9640.151111\n",
       "C#           9130.25   8345.69   8110.00   8523.137778\n",
       "Python      10010.00  10010.00  10010.00  10010.000000"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Apply a function along an axis of the DataFrame.\n",
    "popularity_df.apply(lambda l: l**2 + 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 10 entries, Matlab to Python\n",
      "Data columns (total 4 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   2020     10 non-null     float64\n",
      " 1   2021     10 non-null     float64\n",
      " 2   2022     10 non-null     float64\n",
      " 3   Average  10 non-null     float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 700.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "# get info\n",
    "popularity_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 10 entries, Matlab to Python\n",
      "Data columns (total 4 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   2020     10 non-null     float32\n",
      " 1   2021     10 non-null     float32\n",
      " 2   2022     10 non-null     float32\n",
      " 3   Average  10 non-null     float32\n",
      "dtypes: float32(4)\n",
      "memory usage: 540.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "# change data type of a pandas dataframe!\n",
    "popularity_df = popularity_df.astype(np.float32)\n",
    "popularity_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>86.000000</td>\n",
       "      <td>86.259995</td>\n",
       "      <td>86.150002</td>\n",
       "      <td>86.136673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>13.493784</td>\n",
       "      <td>14.285439</td>\n",
       "      <td>14.824997</td>\n",
       "      <td>14.004139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>56.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>52.666668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>80.300001</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>83.500000</td>\n",
       "      <td>81.900002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>89.900002</td>\n",
       "      <td>88.050003</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>88.433334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>95.500000</td>\n",
       "      <td>97.550001</td>\n",
       "      <td>96.250000</td>\n",
       "      <td>96.516668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             2020        2021        2022     Average\n",
       "count   10.000000   10.000000   10.000000   10.000000\n",
       "mean    86.000000   86.259995   86.150002   86.136673\n",
       "std     13.493784   14.285439   14.824997   14.004139\n",
       "min     56.000000   53.000000   49.000000   52.666668\n",
       "25%     80.300001   83.000000   83.500000   81.900002\n",
       "50%     89.900002   88.050003   88.000000   88.433334\n",
       "75%     95.500000   97.550001   96.250000   96.516668\n",
       "max    100.000000  100.000000  100.000000  100.000000"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get description\n",
    "popularity_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Manipulating the order of columns in a dataframe\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>Average</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Matlab</th>\n",
       "      <td>52.666668</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>81.366669</td>\n",
       "      <td>74.300003</td>\n",
       "      <td>84.800003</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ruby</th>\n",
       "      <td>78.366669</td>\n",
       "      <td>78.900002</td>\n",
       "      <td>76.199997</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>83.500000</td>\n",
       "      <td>84.500000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHP</th>\n",
       "      <td>84.599998</td>\n",
       "      <td>84.800003</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Java</th>\n",
       "      <td>92.666664</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>92.000000</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>97.800003</td>\n",
       "      <td>95.500000</td>\n",
       "      <td>99.900002</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C++</th>\n",
       "      <td>98.133331</td>\n",
       "      <td>95.500000</td>\n",
       "      <td>99.400002</td>\n",
       "      <td>99.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C#</th>\n",
       "      <td>92.266670</td>\n",
       "      <td>95.500000</td>\n",
       "      <td>91.300003</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Average        2020        2021   2022\n",
       "Matlab       52.666668   56.000000   53.000000   49.0\n",
       "R            81.366669   74.300003   84.800003   85.0\n",
       "Ruby         78.366669   78.900002   76.199997   80.0\n",
       "JavaScript   83.500000   84.500000   83.000000   83.0\n",
       "PHP          84.599998   84.800003   83.000000   86.0\n",
       "Java         92.666664   95.000000   92.000000   91.0\n",
       "C            97.800003   95.500000   99.900002   98.0\n",
       "C++          98.133331   95.500000   99.400002   99.5\n",
       "C#           92.266670   95.500000   91.300003   90.0\n",
       "Python      100.000000  100.000000  100.000000  100.0"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Manipulating the order of columns in a dataframe\")\n",
    "cols = popularity_df.columns.tolist() # get columns\n",
    "cols = [cols[-1], *cols[0:3]] # reorder them as you desire\n",
    "popularity_reordered_df = popularity_df[cols] # you are creating another dataframe!\n",
    "popularity_reordered_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Concatenate dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>id</th>\n",
       "      <th>Feature_1</th>\n",
       "      <th>Feature_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>G</td>\n",
       "      <td>H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I</td>\n",
       "      <td>J</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  id Feature_1 Feature_2\n",
       "0  1         A         B\n",
       "1  2         C         D\n",
       "2  3         E         F\n",
       "3  4         G         H\n",
       "4  5         I         J"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_data_1 = {\n",
    "        'id':        ['1', '2', '3', '4', '5'],\n",
    "        'Feature_1': ['A', 'C', 'E', 'G', 'I'],\n",
    "        'Feature_2': ['B', 'D', 'F', 'H', 'J']\n",
    "}\n",
    "df1 = pd.DataFrame(dummy_data_1)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>id</th>\n",
       "      <th>Feature_1</th>\n",
       "      <th>Feature_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>K</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>O</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>Q</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>S</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id Feature_1 Feature_2\n",
       "0   6         K         L\n",
       "1   7         M         N\n",
       "2   8         O         P\n",
       "3   9         Q         R\n",
       "4  10         S         T"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_data_2 = {\n",
    "        'id':        ['6', '7', '8', '9', '10'],\n",
    "        'Feature_1': ['K', 'M', 'O', 'Q', 'S'],\n",
    "        'Feature_2': ['L', 'N', 'P', 'R', 'T']}\n",
    "df2 = pd.DataFrame(dummy_data_2)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>Feature_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Feature_3\n",
       "0         12\n",
       "1         13\n",
       "2         14\n",
       "3         15\n",
       "4         16\n",
       "5         17\n",
       "6         15\n",
       "7         12\n",
       "8         13\n",
       "9         -1"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_data_3 = {'Feature_3': [12, 13, 14, 15, 16, 17, 15, 12, 13, -1]}\n",
    "df3 = pd.DataFrame(dummy_data_3)\n",
    "df3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### concatenate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Feature_1</th>\n",
       "      <th>Feature_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>G</td>\n",
       "      <td>H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I</td>\n",
       "      <td>J</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>K</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>O</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>Q</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>S</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id Feature_1 Feature_2\n",
       "0   1         A         B\n",
       "1   2         C         D\n",
       "2   3         E         F\n",
       "3   4         G         H\n",
       "4   5         I         J\n",
       "0   6         K         L\n",
       "1   7         M         N\n",
       "2   8         O         P\n",
       "3   9         Q         R\n",
       "4  10         S         T"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_row = pd.concat([df1, df2], axis=0)\n",
    "df_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "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>id</th>\n",
       "      <th>Feature_1</th>\n",
       "      <th>Feature_2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>G</td>\n",
       "      <td>H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I</td>\n",
       "      <td>J</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>K</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>O</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>Q</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>S</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id Feature_1 Feature_2\n",
       "                         \n",
       "0   1         A         B\n",
       "1   2         C         D\n",
       "2   3         E         F\n",
       "3   4         G         H\n",
       "4   5         I         J\n",
       "0   6         K         L\n",
       "1   7         M         N\n",
       "2   8         O         P\n",
       "3   9         Q         R\n",
       "4  10         S         T"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_row = df_row.reset_index().set_index(\"index\")\n",
    "df_row.index.name = \"\"\n",
    "df_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Feature_1</th>\n",
       "      <th>Feature_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>D</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>G</td>\n",
       "      <td>H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I</td>\n",
       "      <td>J</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>K</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>O</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Q</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>S</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id Feature_1 Feature_2\n",
       "0   1         A         B\n",
       "1   2         C         D\n",
       "2   3         E         F\n",
       "3   4         G         H\n",
       "4   5         I         J\n",
       "5   6         K         L\n",
       "6   7         M         N\n",
       "7   8         O         P\n",
       "8   9         Q         R\n",
       "9  10         S         T"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reindexes the index \n",
    "# df_row = df_row.reset_index()\n",
    "df_row = pd.concat([df1, df2], axis=0, ignore_index=True)\n",
    "\n",
    "df_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Feature_1</th>\n",
       "      <th>Feature_2</th>\n",
       "      <th>Feature_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>C</td>\n",
       "      <td>D</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>G</td>\n",
       "      <td>H</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I</td>\n",
       "      <td>J</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>K</td>\n",
       "      <td>L</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>O</td>\n",
       "      <td>P</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Q</td>\n",
       "      <td>R</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>S</td>\n",
       "      <td>T</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id Feature_1 Feature_2  Feature_3\n",
       "0   1         A         B         12\n",
       "1   2         C         D         13\n",
       "2   3         E         F         14\n",
       "3   4         G         H         15\n",
       "4   5         I         J         16\n",
       "5   6         K         L         17\n",
       "6   7         M         N         15\n",
       "7   8         O         P         12\n",
       "8   9         Q         R         13\n",
       "9  10         S         T         -1"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# concat vertically\n",
    "\n",
    "pd.concat([df_row, df3], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to iterate over a dataframe's items"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "# read a csv file\n",
    "tips_df = pd.read_csv('files/tips.csv')\n",
    "tips_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>25.29</td>\n",
       "      <td>4.71</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.77</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>26.88</td>\n",
       "      <td>3.12</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>15.04</td>\n",
       "      <td>1.96</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>14.78</td>\n",
       "      <td>3.23</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4\n",
       "5       25.29  4.71    Male     No  Sun  Dinner     4\n",
       "6        8.77  2.00    Male     No  Sun  Dinner     2\n",
       "7       26.88  3.12    Male     No  Sun  Dinner     4\n",
       "8       15.04  1.96    Male     No  Sun  Dinner     2\n",
       "9       14.78  3.23    Male     No  Sun  Dinner     2"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# heads with argument\n",
    "tips_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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",
       "\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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>15.53</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>10.07</td>\n",
       "      <td>1.25</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>12.60</td>\n",
       "      <td>1.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>32.83</td>\n",
       "      <td>1.17</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>35.83</td>\n",
       "      <td>4.67</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "234       15.53  3.00    Male    Yes   Sat  Dinner     2\n",
       "235       10.07  1.25    Male     No   Sat  Dinner     2\n",
       "236       12.60  1.00    Male    Yes   Sat  Dinner     2\n",
       "237       32.83  1.17    Male    Yes   Sat  Dinner     2\n",
       "238       35.83  4.67  Female     No   Sat  Dinner     3\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tail with argument\n",
    "tips_df.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gets the column names: total_bill\n",
      "gets the column names: tip\n",
      "gets the column names: sex\n",
      "gets the column names: smoker\n",
      "gets the column names: day\n",
      "gets the column names: time\n",
      "gets the column names: size\n"
     ]
    }
   ],
   "source": [
    "for column in tips_df:\n",
    "    print(f\"gets the column names: {column}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gets whole the row: [16.99 1.01 'Female' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [10.34 1.66 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [21.01 3.5 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [23.68 3.31 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [24.59 3.61 'Female' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [25.29 4.71 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [8.77 2.0 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [26.88 3.12 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [15.04 1.96 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [14.78 3.23 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [10.27 1.71 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [35.26 5.0 'Female' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [15.42 1.57 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [18.43 3.0 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [14.83 3.02 'Female' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [21.58 3.92 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [10.33 1.67 'Female' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [16.29 3.71 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [16.97 3.5 'Female' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [20.65 3.35 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [17.92 4.08 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [20.29 2.75 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [15.77 2.23 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [39.42 7.58 'Male' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [19.82 3.18 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [17.81 2.34 'Male' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [13.37 2.0 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [12.69 2.0 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [21.7 4.3 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [19.65 3.0 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [9.55 1.45 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [18.35 2.5 'Male' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [15.06 3.0 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [20.69 2.45 'Female' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [17.78 3.27 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [24.06 3.6 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [16.31 2.0 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [16.93 3.07 'Female' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [18.69 2.31 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [31.27 5.0 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [16.04 2.24 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [17.46 2.54 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [13.94 3.06 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [9.68 1.32 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [30.4 5.6 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [18.29 3.0 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [22.23 5.0 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [32.4 6.0 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [28.55 2.05 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [18.04 3.0 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [12.54 2.5 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [10.29 2.6 'Female' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [34.81 5.2 'Female' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [9.94 1.56 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [25.56 4.34 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [19.49 3.51 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [38.01 3.0 'Male' 'Yes' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [26.41 1.5 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [11.24 1.76 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [48.27 6.73 'Male' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [20.29 3.21 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [13.81 2.0 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [11.02 1.98 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [18.29 3.76 'Male' 'Yes' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [17.59 2.64 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [20.08 3.15 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [16.45 2.47 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [3.07 1.0 'Female' 'Yes' 'Sat' 'Dinner' 1]\n",
      "gets whole the row: [20.23 2.01 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [15.01 2.09 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [12.02 1.97 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [17.07 3.0 'Female' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [26.86 3.14 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [25.28 5.0 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [14.73 2.2 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [10.51 1.25 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [17.92 3.08 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [27.2 4.0 'Male' 'No' 'Thur' 'Lunch' 4]\n",
      "gets whole the row: [22.76 3.0 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [17.29 2.71 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [19.44 3.0 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [16.66 3.4 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [10.07 1.83 'Female' 'No' 'Thur' 'Lunch' 1]\n",
      "gets whole the row: [32.68 5.0 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [15.98 2.03 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [34.83 5.17 'Female' 'No' 'Thur' 'Lunch' 4]\n",
      "gets whole the row: [13.03 2.0 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [18.28 4.0 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [24.71 5.85 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [21.16 3.0 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [28.97 3.0 'Male' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [22.49 3.5 'Male' 'No' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [5.75 1.0 'Female' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [16.32 4.3 'Female' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [22.75 3.25 'Female' 'No' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [40.17 4.73 'Male' 'Yes' 'Fri' 'Dinner' 4]\n",
      "gets whole the row: [27.28 4.0 'Male' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [12.03 1.5 'Male' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [21.01 3.0 'Male' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [12.46 1.5 'Male' 'No' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [11.35 2.5 'Female' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [15.38 3.0 'Female' 'Yes' 'Fri' 'Dinner' 2]\n",
      "gets whole the row: [44.3 2.5 'Female' 'Yes' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [22.42 3.48 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [20.92 4.08 'Female' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [15.36 1.64 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [20.49 4.06 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [25.21 4.29 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [18.24 3.76 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [14.31 4.0 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [14.0 3.0 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [7.25 1.0 'Female' 'No' 'Sat' 'Dinner' 1]\n",
      "gets whole the row: [38.07 4.0 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [23.95 2.55 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [25.71 4.0 'Female' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [17.31 3.5 'Female' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [29.93 5.07 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [10.65 1.5 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [12.43 1.8 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [24.08 2.92 'Female' 'No' 'Thur' 'Lunch' 4]\n",
      "gets whole the row: [11.69 2.31 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [13.42 1.68 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [14.26 2.5 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [15.95 2.0 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [12.48 2.52 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [29.8 4.2 'Female' 'No' 'Thur' 'Lunch' 6]\n",
      "gets whole the row: [8.52 1.48 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [14.52 2.0 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [11.38 2.0 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [22.82 2.18 'Male' 'No' 'Thur' 'Lunch' 3]\n",
      "gets whole the row: [19.08 1.5 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [20.27 2.83 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [11.17 1.5 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [12.26 2.0 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [18.26 3.25 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [8.51 1.25 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [10.33 2.0 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [14.15 2.0 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [16.0 2.0 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [13.16 2.75 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [17.47 3.5 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [34.3 6.7 'Male' 'No' 'Thur' 'Lunch' 6]\n",
      "gets whole the row: [41.19 5.0 'Male' 'No' 'Thur' 'Lunch' 5]\n",
      "gets whole the row: [27.05 5.0 'Female' 'No' 'Thur' 'Lunch' 6]\n",
      "gets whole the row: [16.43 2.3 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [8.35 1.5 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [18.64 1.36 'Female' 'No' 'Thur' 'Lunch' 3]\n",
      "gets whole the row: [11.87 1.63 'Female' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [9.78 1.73 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [7.51 2.0 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [14.07 2.5 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [13.13 2.0 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [17.26 2.74 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [24.55 2.0 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [19.77 2.0 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [29.85 5.14 'Female' 'No' 'Sun' 'Dinner' 5]\n",
      "gets whole the row: [48.17 5.0 'Male' 'No' 'Sun' 'Dinner' 6]\n",
      "gets whole the row: [25.0 3.75 'Female' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [13.39 2.61 'Female' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [16.49 2.0 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [21.5 3.5 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [12.66 2.5 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [16.21 2.0 'Female' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [13.81 2.0 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [17.51 3.0 'Female' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [24.52 3.48 'Male' 'No' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [20.76 2.24 'Male' 'No' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [31.71 4.5 'Male' 'No' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [10.59 1.61 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [10.63 2.0 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [50.81 10.0 'Male' 'Yes' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [15.81 3.16 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [7.25 5.15 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [31.85 3.18 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [16.82 4.0 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [32.9 3.11 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [17.89 2.0 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [14.48 2.0 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [9.6 4.0 'Female' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [34.63 3.55 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [34.65 3.68 'Male' 'Yes' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [23.33 5.65 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [45.35 3.5 'Male' 'Yes' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [23.17 6.5 'Male' 'Yes' 'Sun' 'Dinner' 4]\n",
      "gets whole the row: [40.55 3.0 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [20.69 5.0 'Male' 'No' 'Sun' 'Dinner' 5]\n",
      "gets whole the row: [20.9 3.5 'Female' 'Yes' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [30.46 2.0 'Male' 'Yes' 'Sun' 'Dinner' 5]\n",
      "gets whole the row: [18.15 3.5 'Female' 'Yes' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [23.1 4.0 'Male' 'Yes' 'Sun' 'Dinner' 3]\n",
      "gets whole the row: [15.69 1.5 'Male' 'Yes' 'Sun' 'Dinner' 2]\n",
      "gets whole the row: [19.81 4.19 'Female' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [28.44 2.56 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [15.48 2.02 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [16.58 4.0 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [7.56 1.44 'Male' 'No' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [10.34 2.0 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [43.11 5.0 'Female' 'Yes' 'Thur' 'Lunch' 4]\n",
      "gets whole the row: [13.0 2.0 'Female' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [13.51 2.0 'Male' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [18.71 4.0 'Male' 'Yes' 'Thur' 'Lunch' 3]\n",
      "gets whole the row: [12.74 2.01 'Female' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [13.0 2.0 'Female' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [16.4 2.5 'Female' 'Yes' 'Thur' 'Lunch' 2]\n",
      "gets whole the row: [20.53 4.0 'Male' 'Yes' 'Thur' 'Lunch' 4]\n",
      "gets whole the row: [16.47 3.23 'Female' 'Yes' 'Thur' 'Lunch' 3]\n",
      "gets whole the row: [26.59 3.41 'Male' 'Yes' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [38.73 3.0 'Male' 'Yes' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [24.27 2.03 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [12.76 2.23 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [30.06 2.0 'Male' 'Yes' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [25.89 5.16 'Male' 'Yes' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [48.33 9.0 'Male' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [13.27 2.5 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [28.17 6.5 'Female' 'Yes' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [12.9 1.1 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [28.15 3.0 'Male' 'Yes' 'Sat' 'Dinner' 5]\n",
      "gets whole the row: [11.59 1.5 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [7.74 1.44 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [30.14 3.09 'Female' 'Yes' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [12.16 2.2 'Male' 'Yes' 'Fri' 'Lunch' 2]\n",
      "gets whole the row: [13.42 3.48 'Female' 'Yes' 'Fri' 'Lunch' 2]\n",
      "gets whole the row: [8.58 1.92 'Male' 'Yes' 'Fri' 'Lunch' 1]\n",
      "gets whole the row: [15.98 3.0 'Female' 'No' 'Fri' 'Lunch' 3]\n",
      "gets whole the row: [13.42 1.58 'Male' 'Yes' 'Fri' 'Lunch' 2]\n",
      "gets whole the row: [16.27 2.5 'Female' 'Yes' 'Fri' 'Lunch' 2]\n",
      "gets whole the row: [10.09 2.0 'Female' 'Yes' 'Fri' 'Lunch' 2]\n",
      "gets whole the row: [20.45 3.0 'Male' 'No' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [13.28 2.72 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [22.12 2.88 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [24.01 2.0 'Male' 'Yes' 'Sat' 'Dinner' 4]\n",
      "gets whole the row: [15.69 3.0 'Male' 'Yes' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [11.61 3.39 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [10.77 1.47 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [15.53 3.0 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [10.07 1.25 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [12.6 1.0 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [32.83 1.17 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [35.83 4.67 'Female' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [29.03 5.92 'Male' 'No' 'Sat' 'Dinner' 3]\n",
      "gets whole the row: [27.18 2.0 'Female' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [22.67 2.0 'Male' 'Yes' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [17.82 1.75 'Male' 'No' 'Sat' 'Dinner' 2]\n",
      "gets whole the row: [18.78 3.0 'Female' 'No' 'Thur' 'Dinner' 2]\n"
     ]
    }
   ],
   "source": [
    "for column in tips_df.values:\n",
    "    print(f\"gets whole the row: {column}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total bill for row: 0 is: 16.99\n",
      "total bill for row: 1 is: 10.34\n",
      "total bill for row: 2 is: 21.01\n",
      "total bill for row: 3 is: 23.68\n",
      "total bill for row: 4 is: 24.59\n",
      "total bill for row: 5 is: 25.29\n",
      "total bill for row: 6 is: 8.77\n",
      "total bill for row: 7 is: 26.88\n",
      "total bill for row: 8 is: 15.04\n",
      "total bill for row: 9 is: 14.78\n",
      "total bill for row: 10 is: 10.27\n",
      "total bill for row: 11 is: 35.26\n",
      "total bill for row: 12 is: 15.42\n",
      "total bill for row: 13 is: 18.43\n",
      "total bill for row: 14 is: 14.83\n",
      "total bill for row: 15 is: 21.58\n",
      "total bill for row: 16 is: 10.33\n",
      "total bill for row: 17 is: 16.29\n",
      "total bill for row: 18 is: 16.97\n",
      "total bill for row: 19 is: 20.65\n",
      "total bill for row: 20 is: 17.92\n",
      "total bill for row: 21 is: 20.29\n",
      "total bill for row: 22 is: 15.77\n",
      "total bill for row: 23 is: 39.42\n",
      "total bill for row: 24 is: 19.82\n",
      "total bill for row: 25 is: 17.81\n",
      "total bill for row: 26 is: 13.37\n",
      "total bill for row: 27 is: 12.69\n",
      "total bill for row: 28 is: 21.7\n",
      "total bill for row: 29 is: 19.65\n",
      "total bill for row: 30 is: 9.55\n",
      "total bill for row: 31 is: 18.35\n",
      "total bill for row: 32 is: 15.06\n",
      "total bill for row: 33 is: 20.69\n",
      "total bill for row: 34 is: 17.78\n",
      "total bill for row: 35 is: 24.06\n",
      "total bill for row: 36 is: 16.31\n",
      "total bill for row: 37 is: 16.93\n",
      "total bill for row: 38 is: 18.69\n",
      "total bill for row: 39 is: 31.27\n",
      "total bill for row: 40 is: 16.04\n",
      "total bill for row: 41 is: 17.46\n",
      "total bill for row: 42 is: 13.94\n",
      "total bill for row: 43 is: 9.68\n",
      "total bill for row: 44 is: 30.4\n",
      "total bill for row: 45 is: 18.29\n",
      "total bill for row: 46 is: 22.23\n",
      "total bill for row: 47 is: 32.4\n",
      "total bill for row: 48 is: 28.55\n",
      "total bill for row: 49 is: 18.04\n",
      "total bill for row: 50 is: 12.54\n",
      "total bill for row: 51 is: 10.29\n",
      "total bill for row: 52 is: 34.81\n",
      "total bill for row: 53 is: 9.94\n",
      "total bill for row: 54 is: 25.56\n",
      "total bill for row: 55 is: 19.49\n",
      "total bill for row: 56 is: 38.01\n",
      "total bill for row: 57 is: 26.41\n",
      "total bill for row: 58 is: 11.24\n",
      "total bill for row: 59 is: 48.27\n",
      "total bill for row: 60 is: 20.29\n",
      "total bill for row: 61 is: 13.81\n",
      "total bill for row: 62 is: 11.02\n",
      "total bill for row: 63 is: 18.29\n",
      "total bill for row: 64 is: 17.59\n",
      "total bill for row: 65 is: 20.08\n",
      "total bill for row: 66 is: 16.45\n",
      "total bill for row: 67 is: 3.07\n",
      "total bill for row: 68 is: 20.23\n",
      "total bill for row: 69 is: 15.01\n",
      "total bill for row: 70 is: 12.02\n",
      "total bill for row: 71 is: 17.07\n",
      "total bill for row: 72 is: 26.86\n",
      "total bill for row: 73 is: 25.28\n",
      "total bill for row: 74 is: 14.73\n",
      "total bill for row: 75 is: 10.51\n",
      "total bill for row: 76 is: 17.92\n",
      "total bill for row: 77 is: 27.2\n",
      "total bill for row: 78 is: 22.76\n",
      "total bill for row: 79 is: 17.29\n",
      "total bill for row: 80 is: 19.44\n",
      "total bill for row: 81 is: 16.66\n",
      "total bill for row: 82 is: 10.07\n",
      "total bill for row: 83 is: 32.68\n",
      "total bill for row: 84 is: 15.98\n",
      "total bill for row: 85 is: 34.83\n",
      "total bill for row: 86 is: 13.03\n",
      "total bill for row: 87 is: 18.28\n",
      "total bill for row: 88 is: 24.71\n",
      "total bill for row: 89 is: 21.16\n",
      "total bill for row: 90 is: 28.97\n",
      "total bill for row: 91 is: 22.49\n",
      "total bill for row: 92 is: 5.75\n",
      "total bill for row: 93 is: 16.32\n",
      "total bill for row: 94 is: 22.75\n",
      "total bill for row: 95 is: 40.17\n",
      "total bill for row: 96 is: 27.28\n",
      "total bill for row: 97 is: 12.03\n",
      "total bill for row: 98 is: 21.01\n",
      "total bill for row: 99 is: 12.46\n",
      "total bill for row: 100 is: 11.35\n",
      "total bill for row: 101 is: 15.38\n",
      "total bill for row: 102 is: 44.3\n",
      "total bill for row: 103 is: 22.42\n",
      "total bill for row: 104 is: 20.92\n",
      "total bill for row: 105 is: 15.36\n",
      "total bill for row: 106 is: 20.49\n",
      "total bill for row: 107 is: 25.21\n",
      "total bill for row: 108 is: 18.24\n",
      "total bill for row: 109 is: 14.31\n",
      "total bill for row: 110 is: 14.0\n",
      "total bill for row: 111 is: 7.25\n",
      "total bill for row: 112 is: 38.07\n",
      "total bill for row: 113 is: 23.95\n",
      "total bill for row: 114 is: 25.71\n",
      "total bill for row: 115 is: 17.31\n",
      "total bill for row: 116 is: 29.93\n",
      "total bill for row: 117 is: 10.65\n",
      "total bill for row: 118 is: 12.43\n",
      "total bill for row: 119 is: 24.08\n",
      "total bill for row: 120 is: 11.69\n",
      "total bill for row: 121 is: 13.42\n",
      "total bill for row: 122 is: 14.26\n",
      "total bill for row: 123 is: 15.95\n",
      "total bill for row: 124 is: 12.48\n",
      "total bill for row: 125 is: 29.8\n",
      "total bill for row: 126 is: 8.52\n",
      "total bill for row: 127 is: 14.52\n",
      "total bill for row: 128 is: 11.38\n",
      "total bill for row: 129 is: 22.82\n",
      "total bill for row: 130 is: 19.08\n",
      "total bill for row: 131 is: 20.27\n",
      "total bill for row: 132 is: 11.17\n",
      "total bill for row: 133 is: 12.26\n",
      "total bill for row: 134 is: 18.26\n",
      "total bill for row: 135 is: 8.51\n",
      "total bill for row: 136 is: 10.33\n",
      "total bill for row: 137 is: 14.15\n",
      "total bill for row: 138 is: 16.0\n",
      "total bill for row: 139 is: 13.16\n",
      "total bill for row: 140 is: 17.47\n",
      "total bill for row: 141 is: 34.3\n",
      "total bill for row: 142 is: 41.19\n",
      "total bill for row: 143 is: 27.05\n",
      "total bill for row: 144 is: 16.43\n",
      "total bill for row: 145 is: 8.35\n",
      "total bill for row: 146 is: 18.64\n",
      "total bill for row: 147 is: 11.87\n",
      "total bill for row: 148 is: 9.78\n",
      "total bill for row: 149 is: 7.51\n",
      "total bill for row: 150 is: 14.07\n",
      "total bill for row: 151 is: 13.13\n",
      "total bill for row: 152 is: 17.26\n",
      "total bill for row: 153 is: 24.55\n",
      "total bill for row: 154 is: 19.77\n",
      "total bill for row: 155 is: 29.85\n",
      "total bill for row: 156 is: 48.17\n",
      "total bill for row: 157 is: 25.0\n",
      "total bill for row: 158 is: 13.39\n",
      "total bill for row: 159 is: 16.49\n",
      "total bill for row: 160 is: 21.5\n",
      "total bill for row: 161 is: 12.66\n",
      "total bill for row: 162 is: 16.21\n",
      "total bill for row: 163 is: 13.81\n",
      "total bill for row: 164 is: 17.51\n",
      "total bill for row: 165 is: 24.52\n",
      "total bill for row: 166 is: 20.76\n",
      "total bill for row: 167 is: 31.71\n",
      "total bill for row: 168 is: 10.59\n",
      "total bill for row: 169 is: 10.63\n",
      "total bill for row: 170 is: 50.81\n",
      "total bill for row: 171 is: 15.81\n",
      "total bill for row: 172 is: 7.25\n",
      "total bill for row: 173 is: 31.85\n",
      "total bill for row: 174 is: 16.82\n",
      "total bill for row: 175 is: 32.9\n",
      "total bill for row: 176 is: 17.89\n",
      "total bill for row: 177 is: 14.48\n",
      "total bill for row: 178 is: 9.6\n",
      "total bill for row: 179 is: 34.63\n",
      "total bill for row: 180 is: 34.65\n",
      "total bill for row: 181 is: 23.33\n",
      "total bill for row: 182 is: 45.35\n",
      "total bill for row: 183 is: 23.17\n",
      "total bill for row: 184 is: 40.55\n",
      "total bill for row: 185 is: 20.69\n",
      "total bill for row: 186 is: 20.9\n",
      "total bill for row: 187 is: 30.46\n",
      "total bill for row: 188 is: 18.15\n",
      "total bill for row: 189 is: 23.1\n",
      "total bill for row: 190 is: 15.69\n",
      "total bill for row: 191 is: 19.81\n",
      "total bill for row: 192 is: 28.44\n",
      "total bill for row: 193 is: 15.48\n",
      "total bill for row: 194 is: 16.58\n",
      "total bill for row: 195 is: 7.56\n",
      "total bill for row: 196 is: 10.34\n",
      "total bill for row: 197 is: 43.11\n",
      "total bill for row: 198 is: 13.0\n",
      "total bill for row: 199 is: 13.51\n",
      "total bill for row: 200 is: 18.71\n",
      "total bill for row: 201 is: 12.74\n",
      "total bill for row: 202 is: 13.0\n",
      "total bill for row: 203 is: 16.4\n",
      "total bill for row: 204 is: 20.53\n",
      "total bill for row: 205 is: 16.47\n",
      "total bill for row: 206 is: 26.59\n",
      "total bill for row: 207 is: 38.73\n",
      "total bill for row: 208 is: 24.27\n",
      "total bill for row: 209 is: 12.76\n",
      "total bill for row: 210 is: 30.06\n",
      "total bill for row: 211 is: 25.89\n",
      "total bill for row: 212 is: 48.33\n",
      "total bill for row: 213 is: 13.27\n",
      "total bill for row: 214 is: 28.17\n",
      "total bill for row: 215 is: 12.9\n",
      "total bill for row: 216 is: 28.15\n",
      "total bill for row: 217 is: 11.59\n",
      "total bill for row: 218 is: 7.74\n",
      "total bill for row: 219 is: 30.14\n",
      "total bill for row: 220 is: 12.16\n",
      "total bill for row: 221 is: 13.42\n",
      "total bill for row: 222 is: 8.58\n",
      "total bill for row: 223 is: 15.98\n",
      "total bill for row: 224 is: 13.42\n",
      "total bill for row: 225 is: 16.27\n",
      "total bill for row: 226 is: 10.09\n",
      "total bill for row: 227 is: 20.45\n",
      "total bill for row: 228 is: 13.28\n",
      "total bill for row: 229 is: 22.12\n",
      "total bill for row: 230 is: 24.01\n",
      "total bill for row: 231 is: 15.69\n",
      "total bill for row: 232 is: 11.61\n",
      "total bill for row: 233 is: 10.77\n",
      "total bill for row: 234 is: 15.53\n",
      "total bill for row: 235 is: 10.07\n",
      "total bill for row: 236 is: 12.6\n",
      "total bill for row: 237 is: 32.83\n",
      "total bill for row: 238 is: 35.83\n",
      "total bill for row: 239 is: 29.03\n",
      "total bill for row: 240 is: 27.18\n",
      "total bill for row: 241 is: 22.67\n",
      "total bill for row: 242 is: 17.82\n",
      "total bill for row: 243 is: 18.78\n"
     ]
    }
   ],
   "source": [
    "for row_index, row in tips_df.iterrows():\n",
    "#     print(f\"gets whole the row: {row_index}, {row}\")\n",
    "    print(f\"total bill for row: {row_index} is: {row['total_bill']}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip\n",
       "0       16.99  1.01\n",
       "1       10.34  1.66\n",
       "2       21.01  3.50\n",
       "3       23.68  3.31\n",
       "4       24.59  3.61"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get columns\n",
    "inner_df = tips_df[['total_bill', \"tip\"]]\n",
    "inner_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[16.99,  1.01],\n",
       "       [10.34,  1.66],\n",
       "       [21.01,  3.5 ],\n",
       "       [23.68,  3.31],\n",
       "       [24.59,  3.61]])"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# numpy nd-array\n",
    "inner_df.values[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "whole bill: 18.0\n",
      "whole bill: 12.0\n",
      "whole bill: 24.51\n",
      "whole bill: 26.99\n",
      "whole bill: 28.2\n",
      "whole bill: 30.0\n",
      "whole bill: 10.77\n",
      "whole bill: 30.0\n",
      "whole bill: 17.0\n",
      "whole bill: 18.009999999999998\n",
      "whole bill: 11.98\n",
      "whole bill: 40.26\n",
      "whole bill: 16.99\n",
      "whole bill: 21.43\n",
      "whole bill: 17.85\n",
      "whole bill: 25.5\n",
      "whole bill: 12.0\n",
      "whole bill: 20.0\n",
      "whole bill: 20.47\n",
      "whole bill: 24.0\n",
      "whole bill: 22.0\n",
      "whole bill: 23.04\n",
      "whole bill: 18.0\n",
      "whole bill: 47.0\n",
      "whole bill: 23.0\n",
      "whole bill: 20.15\n",
      "whole bill: 15.37\n",
      "whole bill: 14.69\n",
      "whole bill: 26.0\n",
      "whole bill: 22.65\n",
      "whole bill: 11.0\n",
      "whole bill: 20.85\n",
      "whole bill: 18.060000000000002\n",
      "whole bill: 23.14\n",
      "whole bill: 21.05\n",
      "whole bill: 27.66\n",
      "whole bill: 18.31\n",
      "whole bill: 20.0\n",
      "whole bill: 21.0\n",
      "whole bill: 36.269999999999996\n",
      "whole bill: 18.28\n",
      "whole bill: 20.0\n",
      "whole bill: 17.0\n",
      "whole bill: 11.0\n",
      "whole bill: 36.0\n",
      "whole bill: 21.29\n",
      "whole bill: 27.23\n",
      "whole bill: 38.4\n",
      "whole bill: 30.6\n",
      "whole bill: 21.04\n",
      "whole bill: 15.04\n",
      "whole bill: 12.889999999999999\n",
      "whole bill: 40.010000000000005\n",
      "whole bill: 11.5\n",
      "whole bill: 29.9\n",
      "whole bill: 23.0\n",
      "whole bill: 41.01\n",
      "whole bill: 27.91\n",
      "whole bill: 13.0\n",
      "whole bill: 55.0\n",
      "whole bill: 23.5\n",
      "whole bill: 15.81\n",
      "whole bill: 13.0\n",
      "whole bill: 22.049999999999997\n",
      "whole bill: 20.23\n",
      "whole bill: 23.229999999999997\n",
      "whole bill: 18.919999999999998\n",
      "whole bill: 4.07\n",
      "whole bill: 22.240000000000002\n",
      "whole bill: 17.1\n",
      "whole bill: 13.99\n",
      "whole bill: 20.07\n",
      "whole bill: 30.0\n",
      "whole bill: 30.28\n",
      "whole bill: 16.93\n",
      "whole bill: 11.76\n",
      "whole bill: 21.0\n",
      "whole bill: 31.2\n",
      "whole bill: 25.76\n",
      "whole bill: 20.0\n",
      "whole bill: 22.44\n",
      "whole bill: 20.06\n",
      "whole bill: 11.9\n",
      "whole bill: 37.68\n",
      "whole bill: 18.01\n",
      "whole bill: 40.0\n",
      "whole bill: 15.03\n",
      "whole bill: 22.28\n",
      "whole bill: 30.560000000000002\n",
      "whole bill: 24.16\n",
      "whole bill: 31.97\n",
      "whole bill: 25.99\n",
      "whole bill: 6.75\n",
      "whole bill: 20.62\n",
      "whole bill: 26.0\n",
      "whole bill: 44.900000000000006\n",
      "whole bill: 31.28\n",
      "whole bill: 13.53\n",
      "whole bill: 24.01\n",
      "whole bill: 13.96\n",
      "whole bill: 13.85\n",
      "whole bill: 18.380000000000003\n",
      "whole bill: 46.8\n",
      "whole bill: 25.900000000000002\n",
      "whole bill: 25.0\n",
      "whole bill: 17.0\n",
      "whole bill: 24.549999999999997\n",
      "whole bill: 29.5\n",
      "whole bill: 22.0\n",
      "whole bill: 18.310000000000002\n",
      "whole bill: 17.0\n",
      "whole bill: 8.25\n",
      "whole bill: 42.07\n",
      "whole bill: 26.5\n",
      "whole bill: 29.71\n",
      "whole bill: 20.81\n",
      "whole bill: 35.0\n",
      "whole bill: 12.15\n",
      "whole bill: 14.23\n",
      "whole bill: 27.0\n",
      "whole bill: 14.0\n",
      "whole bill: 15.1\n",
      "whole bill: 16.759999999999998\n",
      "whole bill: 17.95\n",
      "whole bill: 15.0\n",
      "whole bill: 34.0\n",
      "whole bill: 10.0\n",
      "whole bill: 16.52\n",
      "whole bill: 13.38\n",
      "whole bill: 25.0\n",
      "whole bill: 20.58\n",
      "whole bill: 23.1\n",
      "whole bill: 12.67\n",
      "whole bill: 14.26\n",
      "whole bill: 21.51\n",
      "whole bill: 9.76\n",
      "whole bill: 12.33\n",
      "whole bill: 16.15\n",
      "whole bill: 18.0\n",
      "whole bill: 15.91\n",
      "whole bill: 20.97\n",
      "whole bill: 41.0\n",
      "whole bill: 46.19\n",
      "whole bill: 32.05\n",
      "whole bill: 18.73\n",
      "whole bill: 9.85\n",
      "whole bill: 20.0\n",
      "whole bill: 13.5\n",
      "whole bill: 11.51\n",
      "whole bill: 9.51\n",
      "whole bill: 16.57\n",
      "whole bill: 15.13\n",
      "whole bill: 20.0\n",
      "whole bill: 26.55\n",
      "whole bill: 21.77\n",
      "whole bill: 34.99\n",
      "whole bill: 53.17\n",
      "whole bill: 28.75\n",
      "whole bill: 16.0\n",
      "whole bill: 18.49\n",
      "whole bill: 25.0\n",
      "whole bill: 15.16\n",
      "whole bill: 18.21\n",
      "whole bill: 15.81\n",
      "whole bill: 20.51\n",
      "whole bill: 28.0\n",
      "whole bill: 23.0\n",
      "whole bill: 36.21\n",
      "whole bill: 12.2\n",
      "whole bill: 12.63\n",
      "whole bill: 60.81\n",
      "whole bill: 18.97\n",
      "whole bill: 12.4\n",
      "whole bill: 35.03\n",
      "whole bill: 20.82\n",
      "whole bill: 36.01\n",
      "whole bill: 19.89\n",
      "whole bill: 16.48\n",
      "whole bill: 13.6\n",
      "whole bill: 38.18\n",
      "whole bill: 38.33\n",
      "whole bill: 28.979999999999997\n",
      "whole bill: 48.85\n",
      "whole bill: 29.67\n",
      "whole bill: 43.55\n",
      "whole bill: 25.69\n",
      "whole bill: 24.4\n",
      "whole bill: 32.46\n",
      "whole bill: 21.65\n",
      "whole bill: 27.1\n",
      "whole bill: 17.189999999999998\n",
      "whole bill: 24.0\n",
      "whole bill: 31.0\n",
      "whole bill: 17.5\n",
      "whole bill: 20.58\n",
      "whole bill: 9.0\n",
      "whole bill: 12.34\n",
      "whole bill: 48.11\n",
      "whole bill: 15.0\n",
      "whole bill: 15.51\n",
      "whole bill: 22.71\n",
      "whole bill: 14.75\n",
      "whole bill: 15.0\n",
      "whole bill: 18.9\n",
      "whole bill: 24.53\n",
      "whole bill: 19.7\n",
      "whole bill: 30.0\n",
      "whole bill: 41.73\n",
      "whole bill: 26.3\n",
      "whole bill: 14.99\n",
      "whole bill: 32.06\n",
      "whole bill: 31.05\n",
      "whole bill: 57.33\n",
      "whole bill: 15.77\n",
      "whole bill: 34.67\n",
      "whole bill: 14.0\n",
      "whole bill: 31.15\n",
      "whole bill: 13.09\n",
      "whole bill: 9.18\n",
      "whole bill: 33.230000000000004\n",
      "whole bill: 14.36\n",
      "whole bill: 16.9\n",
      "whole bill: 10.5\n",
      "whole bill: 18.98\n",
      "whole bill: 15.0\n",
      "whole bill: 18.77\n",
      "whole bill: 12.09\n",
      "whole bill: 23.45\n",
      "whole bill: 16.0\n",
      "whole bill: 25.0\n",
      "whole bill: 26.01\n",
      "whole bill: 18.689999999999998\n",
      "whole bill: 15.0\n",
      "whole bill: 12.24\n",
      "whole bill: 18.53\n",
      "whole bill: 11.32\n",
      "whole bill: 13.6\n",
      "whole bill: 34.0\n",
      "whole bill: 40.5\n",
      "whole bill: 34.95\n",
      "whole bill: 29.18\n",
      "whole bill: 24.67\n",
      "whole bill: 19.57\n",
      "whole bill: 21.78\n"
     ]
    }
   ],
   "source": [
    "# iterate on a dataframe\n",
    "for total_bill, tip in tips_df[['total_bill', \"tip\"]].values:\n",
    "    print(f\"whole bill: {total_bill + tip}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Task\n",
    "    Task: Save the total paid money by costumers in a new column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>total_paid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>18.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>12.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>24.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>26.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "      <td>28.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size  total_paid\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2       18.00\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3       12.00\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3       24.51\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2       26.99\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4       28.20"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_paid = []\n",
    "for total_bill, tip in tips_df[['total_bill', \"tip\"]].values:\n",
    "    total_paid.append(total_bill + tip)\n",
    "tips_df['total_paid'] = total_paid\n",
    "tips_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# list comprehension usage!\n",
    "# tips_df['total_paid'] = [total_bill + tip for total_bill, tip in tips_df[['total_bill', \"tip\"]].values]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Task: Drop\n",
    "    Drop the previously created column\n",
    "   "
   ]
  },
  {
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "0         16.99  1.01  Female     No   Sun  Dinner     2\n",
       "1         10.34  1.66    Male     No   Sun  Dinner     3\n",
       "2         21.01  3.50    Male     No   Sun  Dinner     3\n",
       "3         23.68  3.31    Male     No   Sun  Dinner     2\n",
       "4         24.59  3.61  Female     No   Sun  Dinner     4\n",
       "..          ...   ...     ...    ...   ...     ...   ...\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2\n",
       "\n",
       "[244 rows x 7 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips_df.drop(\"total_paid\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>total_paid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>18.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>12.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>24.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>26.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "      <td>28.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>34.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>29.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>24.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>19.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>21.78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size  total_paid\n",
       "0         16.99  1.01  Female     No   Sun  Dinner     2       18.00\n",
       "1         10.34  1.66    Male     No   Sun  Dinner     3       12.00\n",
       "2         21.01  3.50    Male     No   Sun  Dinner     3       24.51\n",
       "3         23.68  3.31    Male     No   Sun  Dinner     2       26.99\n",
       "4         24.59  3.61  Female     No   Sun  Dinner     4       28.20\n",
       "..          ...   ...     ...    ...   ...     ...   ...         ...\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3       34.95\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2       29.18\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2       24.67\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2       19.57\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2       21.78\n",
       "\n",
       "[244 rows x 8 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total_paid is not dropped?!\n",
    "tips_df "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inplace argument\n",
    "    when `inplace` argument is set to True, it means there would be no output and the df will be changed. Otherwise, the modified df is returned but the main df is not modified.\n",
    "    One can overwrite main df with the returned modified df, or simply set the inplace argument to True. I, however, prefer the former one :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "tips_df.drop(\"total_paid\", axis=1, inplace=True)\n",
    "# or\n",
    "# tips_df = tips_df.drop(\"total_paid\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['total_paid'] not found in axis\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Input \u001b[1;32mIn [107]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mtips_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtotal_paid\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\miniconda3\\envs\\intro_py\\lib\\site-packages\\pandas\\util\\_decorators.py:311\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    305\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[0;32m    306\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[0;32m    307\u001b[0m         msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39marguments),\n\u001b[0;32m    308\u001b[0m         \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[0;32m    309\u001b[0m         stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[0;32m    310\u001b[0m     )\n\u001b[1;32m--> 311\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\miniconda3\\envs\\intro_py\\lib\\site-packages\\pandas\\core\\frame.py:4954\u001b[0m, in \u001b[0;36mDataFrame.drop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   4806\u001b[0m \u001b[38;5;129m@deprecate_nonkeyword_arguments\u001b[39m(version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, allowed_args\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mself\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabels\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m   4807\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdrop\u001b[39m(\n\u001b[0;32m   4808\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   4815\u001b[0m     errors: \u001b[38;5;28mstr\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraise\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m   4816\u001b[0m ):\n\u001b[0;32m   4817\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m   4818\u001b[0m \u001b[38;5;124;03m    Drop specified labels from rows or columns.\u001b[39;00m\n\u001b[0;32m   4819\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   4952\u001b[0m \u001b[38;5;124;03m            weight  1.0     0.8\u001b[39;00m\n\u001b[0;32m   4953\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 4954\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   4955\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlabels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4956\u001b[0m \u001b[43m        \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4957\u001b[0m \u001b[43m        \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4958\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4959\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4960\u001b[0m \u001b[43m        \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minplace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4961\u001b[0m \u001b[43m        \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4962\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\miniconda3\\envs\\intro_py\\lib\\site-packages\\pandas\\core\\generic.py:4267\u001b[0m, in \u001b[0;36mNDFrame.drop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   4265\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m axis, labels \u001b[38;5;129;01min\u001b[39;00m axes\u001b[38;5;241m.\u001b[39mitems():\n\u001b[0;32m   4266\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m labels \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 4267\u001b[0m         obj \u001b[38;5;241m=\u001b[39m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_drop_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlevel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   4269\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m inplace:\n\u001b[0;32m   4270\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_update_inplace(obj)\n",
      "File \u001b[1;32m~\\miniconda3\\envs\\intro_py\\lib\\site-packages\\pandas\\core\\generic.py:4311\u001b[0m, in \u001b[0;36mNDFrame._drop_axis\u001b[1;34m(self, labels, axis, level, errors, consolidate, only_slice)\u001b[0m\n\u001b[0;32m   4309\u001b[0m         new_axis \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mdrop(labels, level\u001b[38;5;241m=\u001b[39mlevel, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[0;32m   4310\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 4311\u001b[0m         new_axis \u001b[38;5;241m=\u001b[39m \u001b[43maxis\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   4312\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m axis\u001b[38;5;241m.\u001b[39mget_indexer(new_axis)\n\u001b[0;32m   4314\u001b[0m \u001b[38;5;66;03m# Case for non-unique axis\u001b[39;00m\n\u001b[0;32m   4315\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[1;32m~\\miniconda3\\envs\\intro_py\\lib\\site-packages\\pandas\\core\\indexes\\base.py:6644\u001b[0m, in \u001b[0;36mIndex.drop\u001b[1;34m(self, labels, errors)\u001b[0m\n\u001b[0;32m   6642\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mask\u001b[38;5;241m.\u001b[39many():\n\u001b[0;32m   6643\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m errors \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m-> 6644\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlist\u001b[39m(labels[mask])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not found in axis\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m   6645\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m indexer[\u001b[38;5;241m~\u001b[39mmask]\n\u001b[0;32m   6646\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdelete(indexer)\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['total_paid'] not found in axis\""
     ]
    }
   ],
   "source": [
    "tips_df.drop(\"total_paid\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how to check a column exists in a df\n",
    "\"total_paid\" in tips_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"total_bill\" in tips_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>25.29</td>\n",
       "      <td>4.71</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>243 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "1         10.34  1.66    Male     No   Sun  Dinner     3\n",
       "2         21.01  3.50    Male     No   Sun  Dinner     3\n",
       "3         23.68  3.31    Male     No   Sun  Dinner     2\n",
       "4         24.59  3.61  Female     No   Sun  Dinner     4\n",
       "5         25.29  4.71    Male     No   Sun  Dinner     4\n",
       "..          ...   ...     ...    ...   ...     ...   ...\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2\n",
       "\n",
       "[243 rows x 7 columns]"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop a row/sample\n",
    "tips_df.drop(0, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.77</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>242 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "0         16.99  1.01  Female     No   Sun  Dinner     2\n",
       "1         10.34  1.66    Male     No   Sun  Dinner     3\n",
       "3         23.68  3.31    Male     No   Sun  Dinner     2\n",
       "4         24.59  3.61  Female     No   Sun  Dinner     4\n",
       "6          8.77  2.00    Male     No   Sun  Dinner     2\n",
       "..          ...   ...     ...    ...   ...     ...   ...\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2\n",
       "\n",
       "[242 rows x 7 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop several rows/samples\n",
    "tips_df.drop([2, 5], axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*:)*"
   ]
  }
 ],
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