8960_Candida_Practical_9.ipynb

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  "metadata": {
    "colab": {
      "name": "8960 Candida - Practical 9.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNm7uJ8uC6v2+HQnFH1ON8T",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Candida18/Python/blob/main/8960_Candida_Practical_9.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J2BLYLcF7nlw"
      },
      "source": [
        "**Name : Candida Ruth Noronha**\n",
        "\n",
        "**Class : SE COMPS B**\n",
        "\n",
        "**Roll No. : 8960**\n",
        "\n",
        "**Title : Python Experiment 9**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N7Jitm9Q7q6w"
      },
      "source": [
        "**Aim:** \n",
        "\n",
        "To explore pandas and its operations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9ENayDBFrkvt",
        "outputId": "2df9ba44-61a3-4258-cb64-fd0afdf67d1c"
      },
      "source": [
        "# importing pandas module\n",
        "import pandas as pd \n",
        "\n",
        "print(\"\\n 1. Merge dataframes \\n 2. Join dataframes\\n 3. Concatenate dataframes\\n 4. Exit\\n\" ) \n",
        "while True:   \n",
        "    print(\"\\n------------------------------------------------------------------------------------------------\\n\");\n",
        "    choice = int(input(\" Enter your choice : \"))\n",
        "    print(\"\\n\")\n",
        "    if(choice == 1) : #Merging a dataframe with one unique key combination\n",
        "      # Define a dictionary containing employee data \n",
        "      data1 = {'key': ['K0', 'K1', 'K2', 'K3'],\n",
        "              'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'], \n",
        "              'Age':[27, 24, 22, 32],} \n",
        "        \n",
        "      # Define a dictionary containing employee data \n",
        "      data2 = {'key': ['K0', 'K1', 'K2', 'K3'],\n",
        "              'Address':['Nagpur', 'Kanpur', 'Allahabad', 'Kannuaj'], \n",
        "              'Qualification':['Btech', 'B.A', 'Bcom', 'B.hons']} \n",
        "      \n",
        "      # Convert the dictionary into DataFrame  \n",
        "      df = pd.DataFrame(data1)\n",
        "      \n",
        "      # Convert the dictionary into DataFrame  \n",
        "      df1 = pd.DataFrame(data2)      \n",
        "      \n",
        "      print(df, \"\\n\\n\", df1) \n",
        "\n",
        "      # using .merge() function\n",
        "      print(\"\\n\\n Merged Dataframe : \\n\")\n",
        "      res = pd.merge(df, df1, on='key')\n",
        "      print(res)\n",
        "\n",
        "    elif (choice == 2):\n",
        "      #combining the columns of two potentially differently-indexed DataFrames into a single result DataFrame.\n",
        "      # Define a dictionary containing employee data \n",
        "      data1 = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'], \n",
        "              'Age':[27, 24, 22, 32]} \n",
        "          \n",
        "      # Define a dictionary containing employee data \n",
        "      data2 = {'Address':['Allahabad', 'Kannuaj', 'Allahabad', 'Kannuaj'], \n",
        "              'Qualification':['MCA', 'Phd', 'Bcom', 'B.hons']} \n",
        "        \n",
        "      # Convert the dictionary into DataFrame  \n",
        "      df = pd.DataFrame(data1,index=['K0', 'K1', 'K2', 'K3'])\n",
        "        \n",
        "      # Convert the dictionary into DataFrame  \n",
        "      df1 = pd.DataFrame(data2, index=['K0', 'K2', 'K3', 'K4'])\n",
        "        \n",
        "      print(df, \"\\n\\n\", df1)    \n",
        "\n",
        "      # joining dataframe\n",
        "      print(\"\\n\\n Joined Dataframe : \\n\")\n",
        "      res = df.join(df1)    \n",
        "      print(res) \n",
        "    \n",
        "    elif(choice == 3):#Concatenating DataFrame using .concat()\n",
        "      # Define a dictionary containing employee data \n",
        "      data1 = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'], \n",
        "              'Age':[27, 24, 22, 32], \n",
        "              'Address':['Nagpur', 'Kanpur', 'Allahabad', 'Kannuaj'], \n",
        "              'Qualification':['Msc', 'MA', 'MCA', 'Phd']} \n",
        "        \n",
        "      # Define a dictionary containing employee data \n",
        "      data2 = {'Name':['Abhi', 'Ayushi', 'Dhiraj', 'Hitesh'], \n",
        "              'Age':[17, 14, 12, 52], \n",
        "              'Address':['Nagpur', 'Kanpur', 'Allahabad', 'Kannuaj'], \n",
        "              'Qualification':['Btech', 'B.A', 'Bcom', 'B.hons']} \n",
        "      \n",
        "      # Convert the dictionary into DataFrame  \n",
        "      df = pd.DataFrame(data1,index=[0, 1, 2, 3])\n",
        "      \n",
        "      # Convert the dictionary into DataFrame  \n",
        "      df1 = pd.DataFrame(data2, index=[4, 5, 6, 7])\n",
        "      \n",
        "      print(df, \"\\n\\n\", df1) \n",
        "    \n",
        "      # using a .concat() method\n",
        "      frames = [df, df1]\n",
        "      \n",
        "      print(\"\\n\\n Concatenated Dataframe : \\n\")\n",
        "      res = pd.concat(frames)\n",
        "      print(res)\n",
        "\n",
        "    elif(choice == 4):\n",
        "      print (\"\\n Exiting!\")\n",
        "      break\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            " 1. Merge dataframes \n",
            " 2. Join dataframes\n",
            " 3. Concatenate dataframes\n",
            " 4. Exit\n",
            "\n",
            "\n",
            "------------------------------------------------------------------------------------------------\n",
            "\n",
            " Enter your choice : 1\n",
            "\n",
            "\n",
            "  key    Name  Age\n",
            "0  K0     Jai   27\n",
            "1  K1  Princi   24\n",
            "2  K2  Gaurav   22\n",
            "3  K3    Anuj   32 \n",
            "\n",
            "   key    Address Qualification\n",
            "0  K0     Nagpur         Btech\n",
            "1  K1     Kanpur           B.A\n",
            "2  K2  Allahabad          Bcom\n",
            "3  K3    Kannuaj        B.hons\n",
            "\n",
            "\n",
            " Merged Dataframe : \n",
            "\n",
            "  key    Name  Age    Address Qualification\n",
            "0  K0     Jai   27     Nagpur         Btech\n",
            "1  K1  Princi   24     Kanpur           B.A\n",
            "2  K2  Gaurav   22  Allahabad          Bcom\n",
            "3  K3    Anuj   32    Kannuaj        B.hons\n",
            "\n",
            "------------------------------------------------------------------------------------------------\n",
            "\n",
            " Enter your choice : 2\n",
            "\n",
            "\n",
            "      Name  Age\n",
            "K0     Jai   27\n",
            "K1  Princi   24\n",
            "K2  Gaurav   22\n",
            "K3    Anuj   32 \n",
            "\n",
            "       Address Qualification\n",
            "K0  Allahabad           MCA\n",
            "K2    Kannuaj           Phd\n",
            "K3  Allahabad          Bcom\n",
            "K4    Kannuaj        B.hons\n",
            "\n",
            "\n",
            " Joined Dataframe : \n",
            "\n",
            "      Name  Age    Address Qualification\n",
            "K0     Jai   27  Allahabad           MCA\n",
            "K1  Princi   24        NaN           NaN\n",
            "K2  Gaurav   22    Kannuaj           Phd\n",
            "K3    Anuj   32  Allahabad          Bcom\n",
            "\n",
            "------------------------------------------------------------------------------------------------\n",
            "\n",
            " Enter your choice : 3\n",
            "\n",
            "\n",
            "     Name  Age    Address Qualification\n",
            "0     Jai   27     Nagpur           Msc\n",
            "1  Princi   24     Kanpur            MA\n",
            "2  Gaurav   22  Allahabad           MCA\n",
            "3    Anuj   32    Kannuaj           Phd \n",
            "\n",
            "      Name  Age    Address Qualification\n",
            "4    Abhi   17     Nagpur         Btech\n",
            "5  Ayushi   14     Kanpur           B.A\n",
            "6  Dhiraj   12  Allahabad          Bcom\n",
            "7  Hitesh   52    Kannuaj        B.hons\n",
            "\n",
            "\n",
            " Concatenated Dataframe : \n",
            "\n",
            "     Name  Age    Address Qualification\n",
            "0     Jai   27     Nagpur           Msc\n",
            "1  Princi   24     Kanpur            MA\n",
            "2  Gaurav   22  Allahabad           MCA\n",
            "3    Anuj   32    Kannuaj           Phd\n",
            "4    Abhi   17     Nagpur         Btech\n",
            "5  Ayushi   14     Kanpur           B.A\n",
            "6  Dhiraj   12  Allahabad          Bcom\n",
            "7  Hitesh   52    Kannuaj        B.hons\n",
            "\n",
            "------------------------------------------------------------------------------------------------\n",
            "\n",
            " Enter your choice : 4\n",
            "\n",
            "\n",
            "\n",
            " Exiting!\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}