Pandas_Python.ipynb

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  "metadata": {
    "colab": {
      "name": "Pandas Python.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyPTjiVSySSHkS3vMOoNbLn/",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/natnew/Mini-Python-Projects/blob/main/Pandas_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Python Pandas"
      ],
      "metadata": {
        "id": "sdWUtvjahGf6"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
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        },
        "id": "RA8mJt8yg9zk",
        "outputId": "3e64f6f0-4637-4aec-c300-a5553815462f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "             Tag  number\n",
            "0           Geek      25\n",
            "1             is      30\n",
            "2            for      26\n",
            "3  Geeksforgeeks      22\n"
          ]
        }
      ],
      "source": [
        "# import pandas as pd \n",
        "import pandas as pd  \n",
        "      \n",
        "# List1  \n",
        "lst = [['Geek', 25], ['is', 30], \n",
        "       ['for', 26], ['Geeksforgeeks', 22]] \n",
        "  \n",
        "# creating df object with columns specified    \n",
        "df = pd.DataFrame(lst, columns =['Tag', 'number']) \n",
        "print(df )"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd  \n",
        "      \n",
        "# List1  \n",
        "lst = [['tom', 'reacher', 25], ['krish', 'pete', 30], \n",
        "       ['nick', 'wilson', 26], ['juli', 'williams', 22]] \n",
        "      \n",
        "df = pd.DataFrame(lst, columns =['FName', 'LName', 'Age'],\n",
        "                                           dtype = float) \n",
        "print(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LmtRpL-KhcNY",
        "outputId": "89ccee11-9223-444f-99fc-7804952873a5"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   FName     LName   Age\n",
            "0    tom   reacher  25.0\n",
            "1  krish      pete  30.0\n",
            "2   nick    wilson  26.0\n",
            "3   juli  williams  22.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Reset Index in Pandas Dataframe"
      ],
      "metadata": {
        "id": "ykPR3fI8hlPy"
      }
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    {
      "cell_type": "code",
      "source": [
        "# Import pandas package\n",
        "import pandas as pd\n",
        "    \n",
        "# Define a dictionary containing employee data\n",
        "data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],\n",
        "        'Age':[27, 24, 22, 32, 15],\n",
        "        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],\n",
        "        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }\n",
        "  \n",
        "# Convert the dictionary into DataFrame \n",
        "df = pd.DataFrame(data)\n",
        "  \n",
        "df"
      ],
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      "execution_count": 3,
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              "     Name  Age    Address Qualification\n",
              "0     Jai   27      Delhi           Msc\n",
              "1  Princi   24     Kanpur            MA\n",
              "2  Gaurav   22  Allahabad           MCA\n",
              "3    Anuj   32    Kannauj           Phd\n",
              "4   Geeku   15      Noida          10th"
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import pandas package\n",
        "import pandas as pd\n",
        "    \n",
        "# Define a dictionary containing employee data\n",
        "data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],\n",
        "        'Age':[27, 24, 22, 32, 15],\n",
        "        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],\n",
        "        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }\n",
        "  \n",
        "index = {'a', 'b', 'c', 'd', 'e'}\n",
        "  \n",
        "# Convert the dictionary into DataFrame \n",
        "df = pd.DataFrame(data, index)\n",
        "  \n",
        "# Make Own Index as index\n",
        "# In this case default index is exist \n",
        "df.reset_index(inplace = True)\n",
        "  \n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
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        "outputId": "b4bf00ca-46e4-442a-9026-9ff6b50e7a90"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            "text/plain": [
              "  index    Name  Age    Address Qualification\n",
              "0     a     Jai   27      Delhi           Msc\n",
              "1     d  Princi   24     Kanpur            MA\n",
              "2     e  Gaurav   22  Allahabad           MCA\n",
              "3     b    Anuj   32    Kannauj           Phd\n",
              "4     c   Geeku   15      Noida          10th"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import pandas package\n",
        "import pandas as pd\n",
        "    \n",
        "# Define a dictionary containing employee data\n",
        "data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],\n",
        "        'Age':[27, 24, 22, 32, 15],\n",
        "        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],\n",
        "        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }\n",
        "  \n",
        "# Create own index\n",
        "index = {'a', 'b', 'c', 'd', 'e'}\n",
        "  \n",
        "# Convert the dictionary into DataFrame \n",
        "# Make Own Index and Removing Default index\n",
        "df = pd.DataFrame(data, index)\n",
        "  \n",
        "df"
      ],
      "metadata": {
        "colab": {
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          "height": 206
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        "id": "9AMQkMHemSdG",
        "outputId": "a2130141-dff9-41bf-c69f-d368f3041a92"
      },
      "execution_count": 5,
      "outputs": [
        {
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>a</th>\n",
              "      <td>Jai</td>\n",
              "      <td>27</td>\n",
              "      <td>Delhi</td>\n",
              "      <td>Msc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>d</th>\n",
              "      <td>Princi</td>\n",
              "      <td>24</td>\n",
              "      <td>Kanpur</td>\n",
              "      <td>MA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>e</th>\n",
              "      <td>Gaurav</td>\n",
              "      <td>22</td>\n",
              "      <td>Allahabad</td>\n",
              "      <td>MCA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>b</th>\n",
              "      <td>Anuj</td>\n",
              "      <td>32</td>\n",
              "      <td>Kannauj</td>\n",
              "      <td>Phd</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>c</th>\n",
              "      <td>Geeku</td>\n",
              "      <td>15</td>\n",
              "      <td>Noida</td>\n",
              "      <td>10th</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8cb9df77-8047-486a-9393-4f9e60ee8f58')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-8cb9df77-8047-486a-9393-4f9e60ee8f58 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8cb9df77-8047-486a-9393-4f9e60ee8f58');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Name  Age    Address Qualification\n",
              "a     Jai   27      Delhi           Msc\n",
              "d  Princi   24     Kanpur            MA\n",
              "e  Gaurav   22  Allahabad           MCA\n",
              "b    Anuj   32    Kannauj           Phd\n",
              "c   Geeku   15      Noida          10th"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Randomly select rows from Pandas DataFrame"
      ],
      "metadata": {
        "id": "T8Y_gIPZmbQ7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Import pandas package\n",
        "import pandas as pd\n",
        "  \n",
        "# Define a dictionary containing employee data\n",
        "data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],\n",
        "        'Age':[27, 24, 22, 32, 15],\n",
        "        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],\n",
        "        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th']}\n",
        " \n",
        "# Convert the dictionary into DataFrame\n",
        "df = pd.DataFrame(data)\n",
        " \n",
        "# select all columns\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "0CDef7J4mfpP",
        "outputId": "e10a0bb6-2c0c-48a1-cfb5-fb0933b83324"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a6da89e6-bfe5-4da7-9db4-fe72406ebc6b\">\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Age</th>\n",
              "      <th>Address</th>\n",
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              "      <th>0</th>\n",
              "      <td>Jai</td>\n",
              "      <td>27</td>\n",
              "      <td>Delhi</td>\n",
              "      <td>Msc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Princi</td>\n",
              "      <td>24</td>\n",
              "      <td>Kanpur</td>\n",
              "      <td>MA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Gaurav</td>\n",
              "      <td>22</td>\n",
              "      <td>Allahabad</td>\n",
              "      <td>MCA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Anuj</td>\n",
              "      <td>32</td>\n",
              "      <td>Kannauj</td>\n",
              "      <td>Phd</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Geeku</td>\n",
              "      <td>15</td>\n",
              "      <td>Noida</td>\n",
              "      <td>10th</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a6da89e6-bfe5-4da7-9db4-fe72406ebc6b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      background-color: #E8F0FE;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a6da89e6-bfe5-4da7-9db4-fe72406ebc6b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a6da89e6-bfe5-4da7-9db4-fe72406ebc6b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Name  Age    Address Qualification\n",
              "0     Jai   27      Delhi           Msc\n",
              "1  Princi   24     Kanpur            MA\n",
              "2  Gaurav   22  Allahabad           MCA\n",
              "3    Anuj   32    Kannauj           Phd\n",
              "4   Geeku   15      Noida          10th"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Selects one row randomly using sample()\n",
        "# without give any parameters.\n",
        " \n",
        "# Import pandas package\n",
        "import pandas as pd\n",
        "  \n",
        "# Define a dictionary containing employee data\n",
        "data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],\n",
        "        'Age':[27, 24, 22, 32, 15],\n",
        "        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],\n",
        "        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th']}\n",
        " \n",
        "# Convert the dictionary into DataFrame\n",
        "df = pd.DataFrame(data)\n",
        " \n",
        "# Select one row randomly using sample()\n",
        "# without give any parameters\n",
        "df.sample()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "T0xwkdSomlvt",
        "outputId": "2d38e0f1-3b43-436b-c360-b365475627f2"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-fcaf9c35-d8e7-4bff-b9f4-f3bed0a15a8e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Age</th>\n",
              "      <th>Address</th>\n",
              "      <th>Qualification</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Anuj</td>\n",
              "      <td>32</td>\n",
              "      <td>Kannauj</td>\n",
              "      <td>Phd</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fcaf9c35-d8e7-4bff-b9f4-f3bed0a15a8e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fcaf9c35-d8e7-4bff-b9f4-f3bed0a15a8e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fcaf9c35-d8e7-4bff-b9f4-f3bed0a15a8e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   Name  Age  Address Qualification\n",
              "3  Anuj   32  Kannauj           Phd"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# To get 3 random rows\n",
        "# each time it gives 3 different rows\n",
        " \n",
        "# df.sample(3) or\n",
        "df.sample(n = 3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "3YrmasgRmsCa",
        "outputId": "8a17a8cd-f8b0-45a8-f295-c7cce64cdc54"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Age</th>\n",
              "      <th>Address</th>\n",
              "      <th>Qualification</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Jai</td>\n",
              "      <td>27</td>\n",
              "      <td>Delhi</td>\n",
              "      <td>Msc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Gaurav</td>\n",
              "      <td>22</td>\n",
              "      <td>Allahabad</td>\n",
              "      <td>MCA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Anuj</td>\n",
              "      <td>32</td>\n",
              "      <td>Kannauj</td>\n",
              "      <td>Phd</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Name  Age    Address Qualification\n",
              "0     Jai   27      Delhi           Msc\n",
              "2  Gaurav   22  Allahabad           MCA\n",
              "3    Anuj   32    Kannauj           Phd"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# To get 3 random rows\n",
        "# each time it gives 3 different rows\n",
        " \n",
        "# df.sample(3) or\n",
        "df.sample(n = 4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "85X3ErGCmvHR",
        "outputId": "61930c89-5141-4f70-dbd3-635aaf24bfe9"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "  <div id=\"df-71c3bc94-c2f5-4951-8427-f67f70c37e78\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Age</th>\n",
              "      <th>Address</th>\n",
              "      <th>Qualification</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Princi</td>\n",
              "      <td>24</td>\n",
              "      <td>Kanpur</td>\n",
              "      <td>MA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Gaurav</td>\n",
              "      <td>22</td>\n",
              "      <td>Allahabad</td>\n",
              "      <td>MCA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Geeku</td>\n",
              "      <td>15</td>\n",
              "      <td>Noida</td>\n",
              "      <td>10th</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Jai</td>\n",
              "      <td>27</td>\n",
              "      <td>Delhi</td>\n",
              "      <td>Msc</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "\n",
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              "          const element = document.querySelector('#df-71c3bc94-c2f5-4951-8427-f67f70c37e78');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Name  Age    Address Qualification\n",
              "1  Princi   24     Kanpur            MA\n",
              "2  Gaurav   22  Allahabad           MCA\n",
              "4   Geeku   15      Noida          10th\n",
              "0     Jai   27      Delhi           Msc"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Fraction of rows\n",
        " \n",
        "# here you get .50 % of the rows\n",
        "df.sample(frac = 0.5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "kqKGC5eGm0jv",
        "outputId": "2334a3d2-c4df-42b2-ed4e-0a4206b46349"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-ee8a3030-4593-432a-baf2-b890eeea18e6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
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              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Gaurav</td>\n",
              "      <td>22</td>\n",
              "      <td>Allahabad</td>\n",
              "      <td>MCA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Princi</td>\n",
              "      <td>24</td>\n",
              "      <td>Kanpur</td>\n",
              "      <td>MA</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ee8a3030-4593-432a-baf2-b890eeea18e6')\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    }\n",
              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ee8a3030-4593-432a-baf2-b890eeea18e6 button.colab-df-convert');\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ee8a3030-4593-432a-baf2-b890eeea18e6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Name  Age    Address Qualification\n",
              "2  Gaurav   22  Allahabad           MCA\n",
              "1  Princi   24     Kanpur            MA"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Apply uppercase to a column in Pandas dataframe"
      ],
      "metadata": {
        "id": "smRSkZaQm7mW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Import pandas package \n",
        "import pandas as pd \n",
        "    \n",
        "# making data frame \n",
        "data = pd.read_csv(\"https://media.geeksforgeeks.org/wp-content/uploads/nba.csv\") \n",
        "    \n",
        "# calling head() method  \n",
        "# storing in new variable \n",
        "data_top = data.head(10) \n",
        "    \n",
        "# display \n",
        "data_top"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "7RPfoJvqm-BX",
        "outputId": "ce463dda-63ec-4f5c-8e83-e0a8e56398c4"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-9cd76d12-6c35-4349-8585-5887594b3feb\">\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Team</th>\n",
              "      <th>Number</th>\n",
              "      <th>Position</th>\n",
              "      <th>Age</th>\n",
              "      <th>Height</th>\n",
              "      <th>Weight</th>\n",
              "      <th>College</th>\n",
              "      <th>Salary</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Avery Bradley</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>0.0</td>\n",
              "      <td>PG</td>\n",
              "      <td>25.0</td>\n",
              "      <td>6-2</td>\n",
              "      <td>180.0</td>\n",
              "      <td>Texas</td>\n",
              "      <td>7730337.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Jae Crowder</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>99.0</td>\n",
              "      <td>SF</td>\n",
              "      <td>25.0</td>\n",
              "      <td>6-6</td>\n",
              "      <td>235.0</td>\n",
              "      <td>Marquette</td>\n",
              "      <td>6796117.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>John Holland</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>30.0</td>\n",
              "      <td>SG</td>\n",
              "      <td>27.0</td>\n",
              "      <td>6-5</td>\n",
              "      <td>205.0</td>\n",
              "      <td>Boston University</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>R.J. Hunter</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>28.0</td>\n",
              "      <td>SG</td>\n",
              "      <td>22.0</td>\n",
              "      <td>6-5</td>\n",
              "      <td>185.0</td>\n",
              "      <td>Georgia State</td>\n",
              "      <td>1148640.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Jonas Jerebko</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>8.0</td>\n",
              "      <td>PF</td>\n",
              "      <td>29.0</td>\n",
              "      <td>6-10</td>\n",
              "      <td>231.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Amir Johnson</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>90.0</td>\n",
              "      <td>PF</td>\n",
              "      <td>29.0</td>\n",
              "      <td>6-9</td>\n",
              "      <td>240.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Jordan Mickey</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>55.0</td>\n",
              "      <td>PF</td>\n",
              "      <td>21.0</td>\n",
              "      <td>6-8</td>\n",
              "      <td>235.0</td>\n",
              "      <td>LSU</td>\n",
              "      <td>1170960.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Kelly Olynyk</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>41.0</td>\n",
              "      <td>C</td>\n",
              "      <td>25.0</td>\n",
              "      <td>7-0</td>\n",
              "      <td>238.0</td>\n",
              "      <td>Gonzaga</td>\n",
              "      <td>2165160.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Terry Rozier</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>12.0</td>\n",
              "      <td>PG</td>\n",
              "      <td>22.0</td>\n",
              "      <td>6-2</td>\n",
              "      <td>190.0</td>\n",
              "      <td>Louisville</td>\n",
              "      <td>1824360.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Marcus Smart</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>36.0</td>\n",
              "      <td>PG</td>\n",
              "      <td>22.0</td>\n",
              "      <td>6-4</td>\n",
              "      <td>220.0</td>\n",
              "      <td>Oklahoma State</td>\n",
              "      <td>3431040.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9cd76d12-6c35-4349-8585-5887594b3feb')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9cd76d12-6c35-4349-8585-5887594b3feb button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9cd76d12-6c35-4349-8585-5887594b3feb');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "            Name            Team  Number  ... Weight            College      Salary\n",
              "0  Avery Bradley  Boston Celtics     0.0  ...  180.0              Texas   7730337.0\n",
              "1    Jae Crowder  Boston Celtics    99.0  ...  235.0          Marquette   6796117.0\n",
              "2   John Holland  Boston Celtics    30.0  ...  205.0  Boston University         NaN\n",
              "3    R.J. Hunter  Boston Celtics    28.0  ...  185.0      Georgia State   1148640.0\n",
              "4  Jonas Jerebko  Boston Celtics     8.0  ...  231.0                NaN   5000000.0\n",
              "5   Amir Johnson  Boston Celtics    90.0  ...  240.0                NaN  12000000.0\n",
              "6  Jordan Mickey  Boston Celtics    55.0  ...  235.0                LSU   1170960.0\n",
              "7   Kelly Olynyk  Boston Celtics    41.0  ...  238.0            Gonzaga   2165160.0\n",
              "8   Terry Rozier  Boston Celtics    12.0  ...  190.0         Louisville   1824360.0\n",
              "9   Marcus Smart  Boston Celtics    36.0  ...  220.0     Oklahoma State   3431040.0\n",
              "\n",
              "[10 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import pandas package \n",
        "import pandas as pd \n",
        "    \n",
        "# making data frame \n",
        "data = pd.read_csv(\"https://media.geeksforgeeks.org/wp-content/uploads/nba.csv\") \n",
        "      \n",
        "# display \n",
        "data['Name'] = data['Name'].str.upper()\n",
        "  \n",
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "lfqBN-QsnFMX",
        "outputId": "fd16f85f-4031-4a80-f67c-b2859cdfd882"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-85ea6a51-6e59-4c3a-a214-a4a48ac23d30\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Team</th>\n",
              "      <th>Number</th>\n",
              "      <th>Position</th>\n",
              "      <th>Age</th>\n",
              "      <th>Height</th>\n",
              "      <th>Weight</th>\n",
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              "      <th>Salary</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>AVERY BRADLEY</td>\n",
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              "      <td>PG</td>\n",
              "      <td>25.0</td>\n",
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              "      <td>Texas</td>\n",
              "      <td>7730337.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>JAE CROWDER</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>99.0</td>\n",
              "      <td>SF</td>\n",
              "      <td>25.0</td>\n",
              "      <td>6-6</td>\n",
              "      <td>235.0</td>\n",
              "      <td>Marquette</td>\n",
              "      <td>6796117.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>JOHN HOLLAND</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>30.0</td>\n",
              "      <td>SG</td>\n",
              "      <td>27.0</td>\n",
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              "      <td>205.0</td>\n",
              "      <td>Boston University</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>R.J. HUNTER</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>28.0</td>\n",
              "      <td>SG</td>\n",
              "      <td>22.0</td>\n",
              "      <td>6-5</td>\n",
              "      <td>185.0</td>\n",
              "      <td>Georgia State</td>\n",
              "      <td>1148640.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>JONAS JEREBKO</td>\n",
              "      <td>Boston Celtics</td>\n",
              "      <td>8.0</td>\n",
              "      <td>PF</td>\n",
              "      <td>29.0</td>\n",
              "      <td>6-10</td>\n",
              "      <td>231.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5000000.0</td>\n",
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              "  </svg>\n",
              "      </button>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-85ea6a51-6e59-4c3a-a214-a4a48ac23d30 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-85ea6a51-6e59-4c3a-a214-a4a48ac23d30');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "            Name            Team  Number  ... Weight            College     Salary\n",
              "0  AVERY BRADLEY  Boston Celtics     0.0  ...  180.0              Texas  7730337.0\n",
              "1    JAE CROWDER  Boston Celtics    99.0  ...  235.0          Marquette  6796117.0\n",
              "2   JOHN HOLLAND  Boston Celtics    30.0  ...  205.0  Boston University        NaN\n",
              "3    R.J. HUNTER  Boston Celtics    28.0  ...  185.0      Georgia State  1148640.0\n",
              "4  JONAS JEREBKO  Boston Celtics     8.0  ...  231.0                NaN  5000000.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import pandas package \n",
        "import pandas as pd \n",
        "    \n",
        "# making data frame \n",
        "data = pd.read_csv(\"https://media.geeksforgeeks.org/wp-content/uploads/nba.csv\") \n",
        "      \n",
        "# display \n",
        "data['Team'] = data['Team'].str.upper()\n",
        "  \n",
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "_E_C8dvbnJ_0",
        "outputId": "4a92d687-5eee-4b9e-e005-808a66bc8f61"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-07e58856-20fa-4fe5-9f30-0d24b79f929b\">\n",
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              "      <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",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Name</th>\n",
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              "      <th>Number</th>\n",
              "      <th>Position</th>\n",
              "      <th>Age</th>\n",
              "      <th>Height</th>\n",
              "      <th>Weight</th>\n",
              "      <th>College</th>\n",
              "      <th>Salary</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Avery Bradley</td>\n",
              "      <td>BOSTON CELTICS</td>\n",
              "      <td>0.0</td>\n",
              "      <td>PG</td>\n",
              "      <td>25.0</td>\n",
              "      <td>6-2</td>\n",
              "      <td>180.0</td>\n",
              "      <td>Texas</td>\n",
              "      <td>7730337.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Jae Crowder</td>\n",
              "      <td>BOSTON CELTICS</td>\n",
              "      <td>99.0</td>\n",
              "      <td>SF</td>\n",
              "      <td>25.0</td>\n",
              "      <td>6-6</td>\n",
              "      <td>235.0</td>\n",
              "      <td>Marquette</td>\n",
              "      <td>6796117.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>John Holland</td>\n",
              "      <td>BOSTON CELTICS</td>\n",
              "      <td>30.0</td>\n",
              "      <td>SG</td>\n",
              "      <td>27.0</td>\n",
              "      <td>6-5</td>\n",
              "      <td>205.0</td>\n",
              "      <td>Boston University</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>R.J. Hunter</td>\n",
              "      <td>BOSTON CELTICS</td>\n",
              "      <td>28.0</td>\n",
              "      <td>SG</td>\n",
              "      <td>22.0</td>\n",
              "      <td>6-5</td>\n",
              "      <td>185.0</td>\n",
              "      <td>Georgia State</td>\n",
              "      <td>1148640.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Jonas Jerebko</td>\n",
              "      <td>BOSTON CELTICS</td>\n",
              "      <td>8.0</td>\n",
              "      <td>PF</td>\n",
              "      <td>29.0</td>\n",
              "      <td>6-10</td>\n",
              "      <td>231.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5000000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-07e58856-20fa-4fe5-9f30-0d24b79f929b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      fill: #1967D2;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-07e58856-20fa-4fe5-9f30-0d24b79f929b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-07e58856-20fa-4fe5-9f30-0d24b79f929b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "            Name            Team  Number  ... Weight            College     Salary\n",
              "0  Avery Bradley  BOSTON CELTICS     0.0  ...  180.0              Texas  7730337.0\n",
              "1    Jae Crowder  BOSTON CELTICS    99.0  ...  235.0          Marquette  6796117.0\n",
              "2   John Holland  BOSTON CELTICS    30.0  ...  205.0  Boston University        NaN\n",
              "3    R.J. Hunter  BOSTON CELTICS    28.0  ...  185.0      Georgia State  1148640.0\n",
              "4  Jonas Jerebko  BOSTON CELTICS     8.0  ...  231.0                NaN  5000000.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Capitalize first letter of a column in Pandas dataframe"
      ],
      "metadata": {
        "id": "7Rb1ZXwgnZEl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a simple dataframe\n",
        "   \n",
        "# importing pandas as pd\n",
        "import pandas as pd\n",
        "  \n",
        "   \n",
        "# creating a dataframe\n",
        "df = pd.DataFrame({'A': ['john', 'bODAY', 'minA', 'Peter', 'nicky'],\n",
        "                  'B': ['masters', 'graduate', 'graduate',\n",
        "                                   'Masters', 'Graduate'],\n",
        "                  'C': [27, 23, 21, 23, 24]})\n",
        "   \n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "r5sGCj0HncKx",
        "outputId": "b93b2c52-2d18-404a-ab20-1253b7229cc6"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-58084aaa-d1e7-435d-9227-c3f337f5bcb1\">\n",
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              "      <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>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>john</td>\n",
              "      <td>masters</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>bODAY</td>\n",
              "      <td>graduate</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>minA</td>\n",
              "      <td>graduate</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Peter</td>\n",
              "      <td>Masters</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>nicky</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-58084aaa-d1e7-435d-9227-c3f337f5bcb1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-58084aaa-d1e7-435d-9227-c3f337f5bcb1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-58084aaa-d1e7-435d-9227-c3f337f5bcb1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       A         B   C\n",
              "0   john   masters  27\n",
              "1  bODAY  graduate  23\n",
              "2   minA  graduate  21\n",
              "3  Peter   Masters  23\n",
              "4  nicky  Graduate  24"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a simple dataframe\n",
        "   \n",
        "# importing pandas as pd\n",
        "import pandas as pd\n",
        "  \n",
        "   \n",
        "# creating a dataframe\n",
        "df = pd.DataFrame({'A': ['john', 'bODAY', 'minA', 'Peter', 'nicky'],\n",
        "                  'B': ['masters', 'graduate', 'graduate',\n",
        "                                   'Masters', 'Graduate'],\n",
        "                  'C': [27, 23, 21, 23, 24]})\n",
        "   \n",
        "df['A'] = df['A'].str.capitalize()\n",
        "  \n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "qNZpiAqGnfWv",
        "outputId": "bdb3abc3-d214-4d5d-a11c-e99fccc2c435"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-72492991-b8bc-474c-9ed6-ed1597ff5590\">\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>0</th>\n",
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              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Boday</td>\n",
              "      <td>graduate</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Mina</td>\n",
              "      <td>graduate</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Peter</td>\n",
              "      <td>Masters</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nicky</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-72492991-b8bc-474c-9ed6-ed1597ff5590')\"\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       A         B   C\n",
              "0   John   masters  27\n",
              "1  Boday  graduate  23\n",
              "2   Mina  graduate  21\n",
              "3  Peter   Masters  23\n",
              "4  Nicky  Graduate  24"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a simple dataframe\n",
        "   \n",
        "# importing pandas as pd\n",
        "import pandas as pd\n",
        "  \n",
        "   \n",
        "# creating a dataframe\n",
        "df = pd.DataFrame({'A': ['john', 'bODAY', 'minA', 'Peter', 'nicky'],\n",
        "                  'B': ['masters', 'graduate', 'graduate',\n",
        "                                   'Masters', 'Graduate'],\n",
        "                  'C': [27, 23, 21, 23, 24]})\n",
        "   \n",
        "df['A'].apply(lambda x: x.capitalize())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qsrv7e5Enqts",
        "outputId": "4ee164e0-223f-4905-87ae-7222a4638702"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     John\n",
              "1    Boday\n",
              "2     Mina\n",
              "3    Peter\n",
              "4    Nicky\n",
              "Name: A, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Split a String into columns using regex in pandas DataFrame"
      ],
      "metadata": {
        "id": "BKEYKqUtn3x9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# import the regex library\n",
        "import pandas as pd\n",
        "import re\n",
        "  \n",
        "# Create a list with all the strings\n",
        "movie_data = [\"Name: The_Godfather Year: 1972 Rating: 9.2\",\n",
        "            \"Name: Bird_Box Year: 2018 Rating: 6.8\",\n",
        "            \"Name: Fight_Club Year: 1999 Rating: 8.8\"]\n",
        "  \n",
        "# Create a dictionary with the required columns \n",
        "# Used later to convert to DataFrame\n",
        "movies = {\"Name\":[], \"Year\":[], \"Rating\":[]}\n",
        "  \n",
        "for item in movie_data:\n",
        "      \n",
        "    # For Name field\n",
        "    name_field = re.search(\"Name: .*\",item)\n",
        "      \n",
        "    if name_field is not None:\n",
        "        name = re.search('\\w*\\s\\w*',name_field.group())\n",
        "    else:\n",
        "        name = None\n",
        "    movies[\"Name\"].append(name.group())\n",
        "      \n",
        "    # For Year field\n",
        "    year_field = re.search(\"Year: .*\",item)\n",
        "    if year_field is not None:\n",
        "        year = re.search('\\s\\d\\d\\d\\d',year_field.group())\n",
        "    else:\n",
        "        year = None\n",
        "    movies[\"Year\"].append(year.group().strip())\n",
        "      \n",
        "    # For rating field\n",
        "    rating_field = re.search(\"Rating: .*\",item)\n",
        "    if rating_field is not None: \n",
        "        rating = re.search('\\s\\d.\\d',rating_field.group())\n",
        "    else: \n",
        "        rating - None\n",
        "    movies[\"Rating\"].append(rating.group().strip())\n",
        "  \n",
        "# Creating DataFrame\n",
        "df = pd.DataFrame(movies)\n",
        "print(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2MO0Zxlyn8RA",
        "outputId": "37e58e20-622a-4123-d76d-5a52fbb9c512"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "             Name  Year Rating\n",
            "0   The_Godfather  1972    9.2\n",
            "1        Bird_Box  2018    6.8\n",
            "2      Fight_Club  1999    8.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "  \n",
        "dict = {'movie_data':['The Godfather 1972 9.2',\n",
        "                    'Bird Box 2018 6.8',\n",
        "                    'Fight Club 1999 8.8'] }\n",
        "  \n",
        "# Convert the dictionary to a dataframe\n",
        "df = pd.DataFrame(dict)\n",
        "  \n",
        "# Extract name from the string \n",
        "df['Name'] = df['movie_data'].str.extract('(\\w*\\s\\w*)', expand=True)\n",
        "   \n",
        "# Extract year from the string \n",
        "df['Year'] = df['movie_data'].str.extract('(\\d\\d\\d\\d)', expand=True)\n",
        "  \n",
        "# Extract rating from the string \n",
        "df['Rating'] = df['movie_data'].str.extract('(\\d\\.\\d)', expand=True)\n",
        "print(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u3mY7unzoB9U",
        "outputId": "6342528b-56bf-45b5-b3fb-50fadbbe362f"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "               movie_data           Name  Year Rating\n",
            "0  The Godfather 1972 9.2  The Godfather  1972    9.2\n",
            "1       Bird Box 2018 6.8       Bird Box  2018    6.8\n",
            "2     Fight Club 1999 8.8     Fight Club  1999    8.8\n"
          ]
        }
      ]
    }
  ]
}