Pandas_Tutorial.ipynb

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    "colab": {
      "name": "Pandas Tutorial.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMZ1qeD4j0AhLXdG2qW342F",
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      "name": "python3",
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      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/philsaurabh/Tutorials/blob/main/Pandas_Tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "neRXSdutCiC1"
      },
      "source": [
        "# Pandas\n",
        "\n",
        "It is a Python library used for working with data sets. It has functions for analyzing, cleaning, exploring, and manipulating data.\n",
        "\n",
        "The name \"Pandas\" has a reference to both \"Panel Data\", and \"Python Data Analysis\" and was created by Wes McKinney in 2008."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fN2aMDgmC81o"
      },
      "source": [
        "# Uses\n",
        "\n",
        "It allows us to analyze big data and make conclusions based on statistical theories. It can clean messy data sets, and make them readable and relevant.\n",
        "\n",
        "Pandas can give you answers about the data.\n",
        "* Is there a correlation between two or more columns?\n",
        "* Average, Max or Min value?\n",
        "* Pandas are also able to delete rows that are not relevant, or contains wrong values, like empty or NULL values. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eTCHigPCCCFS"
      },
      "source": [
        "# Installing libraries\n",
        "Just type \n",
        "```\n",
        "!pip install pandas\n",
        "```\n",
        "and press shift + enter to install library if not available in your workspace."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o2mzBgA8B-2B"
      },
      "source": [
        "# Importing Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b2iRX35_B1ib"
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iadbtDfNFTDM"
      },
      "source": [
        "# Dataframe\n",
        "A Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Po3bju8yEGAT"
      },
      "source": [
        "# To read data as dataframe\n",
        "df = pd.read_csv('https://raw.githubusercontent.com/philsaurabh/Tutorials/main/Advertising.csv')\n",
        "# df = pd.read_csv('Advertising.csv', index_col =\"TV\" ) # For custom index column\n",
        "#print(df)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pJBs0IgsGdJN"
      },
      "source": [
        "#  Task 1: Understanding the dataset\n",
        "\n",
        "  *   Show the values(.head, .tail)\n",
        "  *   Column names(.columns)\n",
        "  *   Shape of data (.shape)\n",
        "  *   Informtion about data (.info)\n",
        "  *   Statistical description (.describe)\n",
        "  *   Check Missing (.isNull)\n",
        "  \n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "f0Vv-Y6FFO3g",
        "outputId": "20e74bc1-f5d2-449c-fbdd-f28a5329032a"
      },
      "source": [
        "df.head()# By default, shows first 5 rows of data\n",
        "#df.tail()# By default, shows last 5 rows of data "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>230.1</td>\n",
              "      <td>37.8</td>\n",
              "      <td>69.2</td>\n",
              "      <td>22.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>44.5</td>\n",
              "      <td>39.3</td>\n",
              "      <td>45.1</td>\n",
              "      <td>10.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>17.2</td>\n",
              "      <td>45.9</td>\n",
              "      <td>69.3</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>151.5</td>\n",
              "      <td>41.3</td>\n",
              "      <td>58.5</td>\n",
              "      <td>18.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>180.8</td>\n",
              "      <td>10.8</td>\n",
              "      <td>58.4</td>\n",
              "      <td>12.9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
            "text/plain": [
              "   Unnamed: 0     TV  radio  newspaper  sales\n",
              "0           1  230.1   37.8       69.2   22.1\n",
              "1           2   44.5   39.3       45.1   10.4\n",
              "2           3   17.2   45.9       69.3    9.3\n",
              "3           4  151.5   41.3       58.5   18.5\n",
              "4           5  180.8   10.8       58.4   12.9"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
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        "outputId": "125f7c7f-8b03-445f-f3eb-5ca8ee417265"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Unnamed: 0', 'TV', 'radio', 'newspaper', 'sales'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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          "base_uri": "https://localhost:8080/"
        },
        "id": "FlXpOO96Iyde",
        "outputId": "3b4721da-800b-404c-808a-88c7bef02177"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(200, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P4H6ghGqI8Dy",
        "outputId": "7dbc5fa1-2bc2-4cd5-d9aa-b001f927228d"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 200 entries, 0 to 199\n",
            "Data columns (total 5 columns):\n",
            " #   Column      Non-Null Count  Dtype  \n",
            "---  ------      --------------  -----  \n",
            " 0   Unnamed: 0  200 non-null    int64  \n",
            " 1   TV          200 non-null    float64\n",
            " 2   radio       200 non-null    float64\n",
            " 3   newspaper   200 non-null    float64\n",
            " 4   sales       200 non-null    float64\n",
            "dtypes: float64(4), int64(1)\n",
            "memory usage: 7.9 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
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        "id": "kbILvo4jI_AF",
        "outputId": "d9ce44fd-5b5f-41f0-c9e4-7d3a6b45ca2f"
      },
      "source": [
        "df.describe()\n",
        "# df.describe().T # For transpose view of the same"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>100.500000</td>\n",
              "      <td>147.042500</td>\n",
              "      <td>23.264000</td>\n",
              "      <td>30.554000</td>\n",
              "      <td>14.022500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>57.879185</td>\n",
              "      <td>85.854236</td>\n",
              "      <td>14.846809</td>\n",
              "      <td>21.778621</td>\n",
              "      <td>5.217457</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.700000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>1.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>50.750000</td>\n",
              "      <td>74.375000</td>\n",
              "      <td>9.975000</td>\n",
              "      <td>12.750000</td>\n",
              "      <td>10.375000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>100.500000</td>\n",
              "      <td>149.750000</td>\n",
              "      <td>22.900000</td>\n",
              "      <td>25.750000</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>150.250000</td>\n",
              "      <td>218.825000</td>\n",
              "      <td>36.525000</td>\n",
              "      <td>45.100000</td>\n",
              "      <td>17.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>200.000000</td>\n",
              "      <td>296.400000</td>\n",
              "      <td>49.600000</td>\n",
              "      <td>114.000000</td>\n",
              "      <td>27.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Unnamed: 0          TV       radio   newspaper       sales\n",
              "count  200.000000  200.000000  200.000000  200.000000  200.000000\n",
              "mean   100.500000  147.042500   23.264000   30.554000   14.022500\n",
              "std     57.879185   85.854236   14.846809   21.778621    5.217457\n",
              "min      1.000000    0.700000    0.000000    0.300000    1.600000\n",
              "25%     50.750000   74.375000    9.975000   12.750000   10.375000\n",
              "50%    100.500000  149.750000   22.900000   25.750000   12.900000\n",
              "75%    150.250000  218.825000   36.525000   45.100000   17.400000\n",
              "max    200.000000  296.400000   49.600000  114.000000   27.000000"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WyEZu9DFJEAD",
        "outputId": "2ffa960e-16d3-4c9d-d7d9-3f6c7cd136d5"
      },
      "source": [
        "df.isnull().values.any() # If any value is missing\n",
        "df.isnull().sum() # Total missing values"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unnamed: 0    0\n",
              "TV            0\n",
              "radio         0\n",
              "newspaper     0\n",
              "sales         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "75um4WepJvW_"
      },
      "source": [
        "# Task 2: Drop a row/column"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y0tIJzm3Jbep",
        "outputId": "0a80a054-ad9a-48ca-e15a-46ee83c52c81"
      },
      "source": [
        "df.drop([198,199], inplace =True) # rows with index labeled as 198 and 199 will be dropped\n",
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(198, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_uFxLg9eJtg6",
        "outputId": "df953b8f-c74a-44c9-9f66-0d58af71ad90"
      },
      "source": [
        "drop_list = [\"Unnamed: 0\"]\n",
        "df = df.drop(drop_list, axis=1)\n",
        "df.columns # Unnamed column will be dropped"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['TV', 'radio', 'newspaper', 'sales'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q1rZiWHpK3Y7",
        "outputId": "b95e90c7-1916-4d4d-b7a0-e9a9522ab427"
      },
      "source": [
        "df.drop(df.columns[[0, 2]], axis = 1, inplace = True)\n",
        "df.columns "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['radio', 'sales'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wuzAj5YENHfB"
      },
      "source": [
        "# Reloding the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f02ZJ-i2MKJE",
        "outputId": "cb55ecf6-a383-4b02-c5e1-f272698928b4"
      },
      "source": [
        "df = pd.read_csv('Advertising.csv')\n",
        "print(df.head())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   Unnamed: 0     TV  radio  newspaper  sales\n",
            "0           1  230.1   37.8       69.2   22.1\n",
            "1           2   44.5   39.3       45.1   10.4\n",
            "2           3   17.2   45.9       69.3    9.3\n",
            "3           4  151.5   41.3       58.5   18.5\n",
            "4           5  180.8   10.8       58.4   12.9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MyF_WCL2N0Kc"
      },
      "source": [
        "# Task4: View Selected columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "_9wIJfGZNzTO",
        "outputId": "6d892287-4442-4649-eb7f-0bf48b488d82"
      },
      "source": [
        "data = df[['TV', 'radio']]\n",
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>230.1</td>\n",
              "      <td>37.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>44.5</td>\n",
              "      <td>39.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>17.2</td>\n",
              "      <td>45.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>151.5</td>\n",
              "      <td>41.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>180.8</td>\n",
              "      <td>10.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>38.2</td>\n",
              "      <td>3.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>94.2</td>\n",
              "      <td>4.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>177.0</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>283.6</td>\n",
              "      <td>42.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>232.1</td>\n",
              "      <td>8.6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        TV  radio\n",
              "0    230.1   37.8\n",
              "1     44.5   39.3\n",
              "2     17.2   45.9\n",
              "3    151.5   41.3\n",
              "4    180.8   10.8\n",
              "..     ...    ...\n",
              "195   38.2    3.7\n",
              "196   94.2    4.9\n",
              "197  177.0    9.3\n",
              "198  283.6   42.0\n",
              "199  232.1    8.6\n",
              "\n",
              "[200 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IfkJ5y95vdYc"
      },
      "source": [
        "# Task 5: Sort by a given column order"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "tHFpHMv2vXaO",
        "outputId": "5e29307e-b335-43e7-9879-7c64565ae4ac"
      },
      "source": [
        "df.sort_values(['radio', 'TV'], ascending = False)# Set ascending true or false to get different order"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>59</td>\n",
              "      <td>210.8</td>\n",
              "      <td>49.6</td>\n",
              "      <td>37.7</td>\n",
              "      <td>23.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>56</td>\n",
              "      <td>198.9</td>\n",
              "      <td>49.4</td>\n",
              "      <td>60.0</td>\n",
              "      <td>23.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>38</td>\n",
              "      <td>74.7</td>\n",
              "      <td>49.4</td>\n",
              "      <td>45.7</td>\n",
              "      <td>14.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>148</td>\n",
              "      <td>243.2</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.3</td>\n",
              "      <td>25.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>129</td>\n",
              "      <td>220.3</td>\n",
              "      <td>49.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>24.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>158</td>\n",
              "      <td>149.8</td>\n",
              "      <td>1.3</td>\n",
              "      <td>24.3</td>\n",
              "      <td>10.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>118</td>\n",
              "      <td>76.4</td>\n",
              "      <td>0.8</td>\n",
              "      <td>14.8</td>\n",
              "      <td>9.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>109</td>\n",
              "      <td>13.1</td>\n",
              "      <td>0.4</td>\n",
              "      <td>25.6</td>\n",
              "      <td>5.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>108</td>\n",
              "      <td>90.4</td>\n",
              "      <td>0.3</td>\n",
              "      <td>23.2</td>\n",
              "      <td>8.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>128</td>\n",
              "      <td>80.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.2</td>\n",
              "      <td>8.8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio  newspaper  sales\n",
              "58           59  210.8   49.6       37.7   23.8\n",
              "55           56  198.9   49.4       60.0   23.7\n",
              "37           38   74.7   49.4       45.7   14.7\n",
              "147         148  243.2   49.0       44.3   25.4\n",
              "128         129  220.3   49.0        3.2   24.7\n",
              "..          ...    ...    ...        ...    ...\n",
              "157         158  149.8    1.3       24.3   10.1\n",
              "117         118   76.4    0.8       14.8    9.4\n",
              "108         109   13.1    0.4       25.6    5.3\n",
              "107         108   90.4    0.3       23.2    8.7\n",
              "127         128   80.2    0.0        9.2    8.8\n",
              "\n",
              "[200 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Mcha7wwwKu2"
      },
      "source": [
        "# Task 6: Filter radios with price >=49 "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "ApFrQwShvuOE",
        "outputId": "495d7c7d-664f-4365-c85b-0320dd1f9935"
      },
      "source": [
        "df[df.radio >= 49]# Can also use >,<, <=,=="
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>38</td>\n",
              "      <td>74.7</td>\n",
              "      <td>49.4</td>\n",
              "      <td>45.7</td>\n",
              "      <td>14.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>56</td>\n",
              "      <td>198.9</td>\n",
              "      <td>49.4</td>\n",
              "      <td>60.0</td>\n",
              "      <td>23.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>59</td>\n",
              "      <td>210.8</td>\n",
              "      <td>49.6</td>\n",
              "      <td>37.7</td>\n",
              "      <td>23.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>129</td>\n",
              "      <td>220.3</td>\n",
              "      <td>49.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>24.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>148</td>\n",
              "      <td>243.2</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.3</td>\n",
              "      <td>25.4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio  newspaper  sales\n",
              "37           38   74.7   49.4       45.7   14.7\n",
              "55           56  198.9   49.4       60.0   23.7\n",
              "58           59  210.8   49.6       37.7   23.8\n",
              "128         129  220.3   49.0        3.2   24.7\n",
              "147         148  243.2   49.0       44.3   25.4"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0vSn6snYypXY"
      },
      "source": [
        "# Task 7: Filter TVs in price range 239 to 248 \n",
        "There are many methods. Some are as follows."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "DvlhvJIgyzRg",
        "outputId": "2a4e76a9-8567-40de-c8a8-f13c4e6e8802"
      },
      "source": [
        "df[df['TV'].between(239,248)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>28</td>\n",
              "      <td>240.1</td>\n",
              "      <td>16.7</td>\n",
              "      <td>22.9</td>\n",
              "      <td>15.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>48</td>\n",
              "      <td>239.9</td>\n",
              "      <td>41.5</td>\n",
              "      <td>18.5</td>\n",
              "      <td>23.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>63</td>\n",
              "      <td>239.3</td>\n",
              "      <td>15.5</td>\n",
              "      <td>27.3</td>\n",
              "      <td>15.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>82</td>\n",
              "      <td>239.8</td>\n",
              "      <td>4.1</td>\n",
              "      <td>36.9</td>\n",
              "      <td>12.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>111</th>\n",
              "      <td>112</td>\n",
              "      <td>241.7</td>\n",
              "      <td>38.0</td>\n",
              "      <td>23.2</td>\n",
              "      <td>21.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>147</td>\n",
              "      <td>240.1</td>\n",
              "      <td>7.3</td>\n",
              "      <td>8.7</td>\n",
              "      <td>13.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>148</td>\n",
              "      <td>243.2</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.3</td>\n",
              "      <td>25.4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio  newspaper  sales\n",
              "27           28  240.1   16.7       22.9   15.9\n",
              "47           48  239.9   41.5       18.5   23.2\n",
              "62           63  239.3   15.5       27.3   15.7\n",
              "81           82  239.8    4.1       36.9   12.3\n",
              "111         112  241.7   38.0       23.2   21.8\n",
              "146         147  240.1    7.3        8.7   13.2\n",
              "147         148  243.2   49.0       44.3   25.4"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "5pMBX7CRzv6s",
        "outputId": "caf1c1ca-fa6c-4f30-8c6e-4c096d89550d"
      },
      "source": [
        "df.query('239 <= TV <= 248')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>28</td>\n",
              "      <td>240.1</td>\n",
              "      <td>16.7</td>\n",
              "      <td>22.9</td>\n",
              "      <td>15.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>48</td>\n",
              "      <td>239.9</td>\n",
              "      <td>41.5</td>\n",
              "      <td>18.5</td>\n",
              "      <td>23.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>63</td>\n",
              "      <td>239.3</td>\n",
              "      <td>15.5</td>\n",
              "      <td>27.3</td>\n",
              "      <td>15.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>82</td>\n",
              "      <td>239.8</td>\n",
              "      <td>4.1</td>\n",
              "      <td>36.9</td>\n",
              "      <td>12.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>111</th>\n",
              "      <td>112</td>\n",
              "      <td>241.7</td>\n",
              "      <td>38.0</td>\n",
              "      <td>23.2</td>\n",
              "      <td>21.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>147</td>\n",
              "      <td>240.1</td>\n",
              "      <td>7.3</td>\n",
              "      <td>8.7</td>\n",
              "      <td>13.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>148</td>\n",
              "      <td>243.2</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.3</td>\n",
              "      <td>25.4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio  newspaper  sales\n",
              "27           28  240.1   16.7       22.9   15.9\n",
              "47           48  239.9   41.5       18.5   23.2\n",
              "62           63  239.3   15.5       27.3   15.7\n",
              "81           82  239.8    4.1       36.9   12.3\n",
              "111         112  241.7   38.0       23.2   21.8\n",
              "146         147  240.1    7.3        8.7   13.2\n",
              "147         148  243.2   49.0       44.3   25.4"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "ghMR020Dz0V5",
        "outputId": "a3e2c26d-e078-49a5-d5bb-50e236f63ebf"
      },
      "source": [
        "df[(df['TV'] >= 239) & (df['TV'] <= 248)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>28</td>\n",
              "      <td>240.1</td>\n",
              "      <td>16.7</td>\n",
              "      <td>22.9</td>\n",
              "      <td>15.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>48</td>\n",
              "      <td>239.9</td>\n",
              "      <td>41.5</td>\n",
              "      <td>18.5</td>\n",
              "      <td>23.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>63</td>\n",
              "      <td>239.3</td>\n",
              "      <td>15.5</td>\n",
              "      <td>27.3</td>\n",
              "      <td>15.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>82</td>\n",
              "      <td>239.8</td>\n",
              "      <td>4.1</td>\n",
              "      <td>36.9</td>\n",
              "      <td>12.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>111</th>\n",
              "      <td>112</td>\n",
              "      <td>241.7</td>\n",
              "      <td>38.0</td>\n",
              "      <td>23.2</td>\n",
              "      <td>21.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>147</td>\n",
              "      <td>240.1</td>\n",
              "      <td>7.3</td>\n",
              "      <td>8.7</td>\n",
              "      <td>13.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>148</td>\n",
              "      <td>243.2</td>\n",
              "      <td>49.0</td>\n",
              "      <td>44.3</td>\n",
              "      <td>25.4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio  newspaper  sales\n",
              "27           28  240.1   16.7       22.9   15.9\n",
              "47           48  239.9   41.5       18.5   23.2\n",
              "62           63  239.3   15.5       27.3   15.7\n",
              "81           82  239.8    4.1       36.9   12.3\n",
              "111         112  241.7   38.0       23.2   21.8\n",
              "146         147  240.1    7.3        8.7   13.2\n",
              "147         148  243.2   49.0       44.3   25.4"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6-xJc95twt6F"
      },
      "source": [
        "# Task 8: Select the first 3 columns from the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "mEp90c1ewXr9",
        "outputId": "03a897de-ac2c-42f7-9fb9-50e6957cb00e"
      },
      "source": [
        "df.iloc[: , 0:3]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>230.1</td>\n",
              "      <td>37.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>44.5</td>\n",
              "      <td>39.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>17.2</td>\n",
              "      <td>45.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>151.5</td>\n",
              "      <td>41.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>180.8</td>\n",
              "      <td>10.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>196</td>\n",
              "      <td>38.2</td>\n",
              "      <td>3.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>197</td>\n",
              "      <td>94.2</td>\n",
              "      <td>4.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>198</td>\n",
              "      <td>177.0</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>199</td>\n",
              "      <td>283.6</td>\n",
              "      <td>42.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>200</td>\n",
              "      <td>232.1</td>\n",
              "      <td>8.6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio\n",
              "0             1  230.1   37.8\n",
              "1             2   44.5   39.3\n",
              "2             3   17.2   45.9\n",
              "3             4  151.5   41.3\n",
              "4             5  180.8   10.8\n",
              "..          ...    ...    ...\n",
              "195         196   38.2    3.7\n",
              "196         197   94.2    4.9\n",
              "197         198  177.0    9.3\n",
              "198         199  283.6   42.0\n",
              "199         200  232.1    8.6\n",
              "\n",
              "[200 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E7B5pm6exNJN"
      },
      "source": [
        "# Task 9: Select all columns except the last 3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "7nSjC1_3xH6b",
        "outputId": "ab531200-0a63-45e4-ba67-a877c1ea7ecc"
      },
      "source": [
        "# use negative to exclude the last 3 columns\n",
        "df.iloc[: , :-3]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>230.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>44.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>17.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>151.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>180.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>196</td>\n",
              "      <td>38.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>197</td>\n",
              "      <td>94.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>198</td>\n",
              "      <td>177.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>199</td>\n",
              "      <td>283.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>200</td>\n",
              "      <td>232.1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV\n",
              "0             1  230.1\n",
              "1             2   44.5\n",
              "2             3   17.2\n",
              "3             4  151.5\n",
              "4             5  180.8\n",
              "..          ...    ...\n",
              "195         196   38.2\n",
              "196         197   94.2\n",
              "197         198  177.0\n",
              "198         199  283.6\n",
              "199         200  232.1\n",
              "\n",
              "[200 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u25PYIVWxijQ"
      },
      "source": [
        "# Task 10: Select the first 3 rows from the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "5QD1vCtdx67V",
        "outputId": "5852cd2b-fd96-4dad-fca3-de5ac7b7e06b"
      },
      "source": [
        "df.iloc[0:3 , :]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>230.1</td>\n",
              "      <td>37.8</td>\n",
              "      <td>69.2</td>\n",
              "      <td>22.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>44.5</td>\n",
              "      <td>39.3</td>\n",
              "      <td>45.1</td>\n",
              "      <td>10.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>17.2</td>\n",
              "      <td>45.9</td>\n",
              "      <td>69.3</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0     TV  radio  newspaper  sales\n",
              "0           1  230.1   37.8       69.2   22.1\n",
              "1           2   44.5   39.3       45.1   10.4\n",
              "2           3   17.2   45.9       69.3    9.3"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OAheR8pgyCqz"
      },
      "source": [
        "# Task 11: Select the all rows from the dataset except last 3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "id": "QcBFS-RKx_z1",
        "outputId": "25d4c9db-20e1-4121-e88d-96c894e9ee01"
      },
      "source": [
        "df.iloc[:-3 , :]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
              "      <th>radio</th>\n",
              "      <th>newspaper</th>\n",
              "      <th>sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>230.1</td>\n",
              "      <td>37.8</td>\n",
              "      <td>69.2</td>\n",
              "      <td>22.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>44.5</td>\n",
              "      <td>39.3</td>\n",
              "      <td>45.1</td>\n",
              "      <td>10.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>17.2</td>\n",
              "      <td>45.9</td>\n",
              "      <td>69.3</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>151.5</td>\n",
              "      <td>41.3</td>\n",
              "      <td>58.5</td>\n",
              "      <td>18.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>180.8</td>\n",
              "      <td>10.8</td>\n",
              "      <td>58.4</td>\n",
              "      <td>12.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>192</th>\n",
              "      <td>193</td>\n",
              "      <td>17.2</td>\n",
              "      <td>4.1</td>\n",
              "      <td>31.6</td>\n",
              "      <td>5.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>194</td>\n",
              "      <td>166.8</td>\n",
              "      <td>42.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>19.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>195</td>\n",
              "      <td>149.7</td>\n",
              "      <td>35.6</td>\n",
              "      <td>6.0</td>\n",
              "      <td>17.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>196</td>\n",
              "      <td>38.2</td>\n",
              "      <td>3.7</td>\n",
              "      <td>13.8</td>\n",
              "      <td>7.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>197</td>\n",
              "      <td>94.2</td>\n",
              "      <td>4.9</td>\n",
              "      <td>8.1</td>\n",
              "      <td>9.7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>197 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0     TV  radio  newspaper  sales\n",
              "0             1  230.1   37.8       69.2   22.1\n",
              "1             2   44.5   39.3       45.1   10.4\n",
              "2             3   17.2   45.9       69.3    9.3\n",
              "3             4  151.5   41.3       58.5   18.5\n",
              "4             5  180.8   10.8       58.4   12.9\n",
              "..          ...    ...    ...        ...    ...\n",
              "192         193   17.2    4.1       31.6    5.9\n",
              "193         194  166.8   42.0        3.6   19.6\n",
              "194         195  149.7   35.6        6.0   17.3\n",
              "195         196   38.2    3.7       13.8    7.6\n",
              "196         197   94.2    4.9        8.1    9.7\n",
              "\n",
              "[197 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a8XTdqXkhTNO"
      },
      "source": [
        "# Additional: Operations on columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "07Y-Mb8ShShM",
        "outputId": "16455e38-50fc-43d5-a527-27e4f6af8334"
      },
      "source": [
        "df.sum(axis=0)#axis 1 for rows"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      360.2\n",
              "1      141.3\n",
              "2      144.7\n",
              "3      273.8\n",
              "4      267.9\n",
              "       ...  \n",
              "195    259.3\n",
              "196    313.9\n",
              "197    403.5\n",
              "198    616.3\n",
              "199    462.8\n",
              "Length: 200, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XXpI7ngnhauC",
        "outputId": "baa10680-ca53-4f97-9352-9abfe07c75c5"
      },
      "source": [
        "df['TV'].sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "29408.5"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D7tmocDlh5EB",
        "outputId": "c48052ba-8a15-48b5-9cda-5b423647c67d"
      },
      "source": [
        "df.TV.mean()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "147.0425"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yeu1fUZUh9pN",
        "outputId": "0d33c01a-1aab-4198-d534-107e5087d59e"
      },
      "source": [
        "df.TV.median()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "149.75"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HW7ZQo7-iA3a",
        "outputId": "e853c1a3-8509-471b-f7ec-b47905a85eae"
      },
      "source": [
        "df.TV.mode()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     17.2\n",
              "1     76.4\n",
              "2    109.8\n",
              "3    177.0\n",
              "4    184.9\n",
              "5    197.6\n",
              "6    199.8\n",
              "7    222.4\n",
              "8    237.4\n",
              "9    240.1\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "frnGzsdriC9K",
        "outputId": "e39b7ac9-8551-437b-b987-f0f46c2aeb9e"
      },
      "source": [
        "df['TV'].corr(df['radio'], method='kendall')# method pearson, spearman"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.04120237262928729"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    }
  ]
}