job_recommender_system.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "job_recommender_system.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMzdC/p+lsIMwqGgOpYcx9O",
      "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/Neel7317/NLP/blob/main/job_recommender_system.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oT2ro5YjRRUa"
      },
      "source": [
        "from google.colab import drive"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LaNopGbDQdOl",
        "outputId": "14ea66d3-3d64-4a15-e50f-6c7e26056b8e"
      },
      "source": [
        "drive.mount('/content/Recommender_system')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/Recommender_system\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RHAcq8CAQl8C"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import nltk"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LIK8xFBpRaYh"
      },
      "source": [
        "df_job=pd.read_csv('/content/Recommender_system/MyDrive/Recommender_system/Combined_Jobs_Final.csv')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "HlRJv-4JRjyV",
        "outputId": "d2ef7f42-ae91-4df5-9b6d-154b9bb65ea1"
      },
      "source": [
        "df_job.head(20)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Job.ID</th>\n",
              "      <th>Provider</th>\n",
              "      <th>Status</th>\n",
              "      <th>Slug</th>\n",
              "      <th>Title</th>\n",
              "      <th>Position</th>\n",
              "      <th>Company</th>\n",
              "      <th>City</th>\n",
              "      <th>State.Name</th>\n",
              "      <th>State.Code</th>\n",
              "      <th>Address</th>\n",
              "      <th>Latitude</th>\n",
              "      <th>Longitude</th>\n",
              "      <th>Industry</th>\n",
              "      <th>Job.Description</th>\n",
              "      <th>Requirements</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Listing.Start</th>\n",
              "      <th>Listing.End</th>\n",
              "      <th>Employment.Type</th>\n",
              "      <th>Education.Required</th>\n",
              "      <th>Created.At</th>\n",
              "      <th>Updated.At</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>111</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>palo-alto-ca-tacolicious-server</td>\n",
              "      <td>Server @ Tacolicious</td>\n",
              "      <td>Server</td>\n",
              "      <td>Tacolicious</td>\n",
              "      <td>Palo Alto</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.443346</td>\n",
              "      <td>-122.161170</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>Tacolicious' first Palo Alto store just opened...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-03-12 02:08:28 UTC</td>\n",
              "      <td>2014-08-16 15:35:36 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>113</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>san-francisco-ca-claude-lane-kitchen-staff-chef</td>\n",
              "      <td>Kitchen Staff/Chef @ Claude Lane</td>\n",
              "      <td>Kitchen Staff/Chef</td>\n",
              "      <td>Claude Lane</td>\n",
              "      <td>San Francisco</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.789830</td>\n",
              "      <td>-122.404268</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>\\r\\n\\r\\nNew French Brasserie in S.F. Financia...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-04-12 08:36:36 UTC</td>\n",
              "      <td>2014-08-16 15:35:36 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>117</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>san-francisco-ca-machka-restaurants-corp-barte...</td>\n",
              "      <td>Bartender @ Machka Restaurants Corp.</td>\n",
              "      <td>Bartender</td>\n",
              "      <td>Machka Restaurants Corp.</td>\n",
              "      <td>San Francisco</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.795597</td>\n",
              "      <td>-122.402963</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>We are a popular Mediterranean wine bar and re...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-07-16 09:34:10 UTC</td>\n",
              "      <td>2014-08-16 15:35:37 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>121</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>brisbane-ca-teriyaki-house-server</td>\n",
              "      <td>Server @ Teriyaki House</td>\n",
              "      <td>Server</td>\n",
              "      <td>Teriyaki House</td>\n",
              "      <td>Brisbane</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.685073</td>\n",
              "      <td>-122.400275</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>● Serve food/drinks to customers in a profess...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.55</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-09-04 15:40:30 UTC</td>\n",
              "      <td>2014-08-16 15:35:38 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>127</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>los-angeles-ca-rosa-mexicano-sunset-kitchen-st...</td>\n",
              "      <td>Kitchen Staff/Chef @ Rosa Mexicano - Sunset</td>\n",
              "      <td>Kitchen Staff/Chef</td>\n",
              "      <td>Rosa Mexicano - Sunset</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.073384</td>\n",
              "      <td>-118.460439</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>Located at the heart of Hollywood, we are one ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.55</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-07-17 15:26:18 UTC</td>\n",
              "      <td>2014-08-16 15:35:40 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>129</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>los-altos-ca-mind-of-beauty-day-spa-receptionist</td>\n",
              "      <td>Receptionist @ Mind of Beauty Day Spa</td>\n",
              "      <td>Receptionist</td>\n",
              "      <td>Mind of Beauty Day Spa</td>\n",
              "      <td>Los Altos</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.385218</td>\n",
              "      <td>-122.114130</td>\n",
              "      <td>Retail</td>\n",
              "      <td>We are a group of professional massage therapi...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-03-12 03:01:36 UTC</td>\n",
              "      <td>2014-08-16 15:35:40 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>131</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>los-angeles-ca-roy-s-woodland-hills-server</td>\n",
              "      <td>Server @ Roy's Woodland Hills</td>\n",
              "      <td>Server</td>\n",
              "      <td>Roy's Woodland Hills</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.186297</td>\n",
              "      <td>-118.606370</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>● Serve food/drinks to customers in a profess...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-09-27 17:46:47 UTC</td>\n",
              "      <td>2014-08-16 15:36:13 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>133</td>\n",
              "      <td>1</td>\n",
              "      <td>open</td>\n",
              "      <td>berkeley-ca-koja-kitchen-driver</td>\n",
              "      <td>Driver @ KoJa Kitchen</td>\n",
              "      <td>Driver</td>\n",
              "      <td>KoJa Kitchen</td>\n",
              "      <td>Berkeley</td>\n",
              "      <td>California</td>\n",
              "      <td>CA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.867213</td>\n",
              "      <td>-122.258611</td>\n",
              "      <td>Food and Beverages</td>\n",
              "      <td>KoJa Kitchen:\\r\\nPART-TIME LOCAL HELP NEEDED W...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013-05-15 01:58:55 UTC</td>\n",
              "      <td>2014-08-16 15:35:41 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>134273</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>mendham-nj-king-s-food-markets-assistant-store...</td>\n",
              "      <td>Assistant Store Manager @ King's Food Markets</td>\n",
              "      <td>Assistant Store Manager</td>\n",
              "      <td>King's Food Markets</td>\n",
              "      <td>Mendham</td>\n",
              "      <td>New Jersey</td>\n",
              "      <td>NJ</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.776000</td>\n",
              "      <td>-74.601000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>\\r\\nAssistant Store Manager\\r\\n\\r\\nNow Hiring ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:06 UTC</td>\n",
              "      <td>2014-12-05 16:55:06 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>134274</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>onalaska-wi-aldi-store-associate-retail-sales-...</td>\n",
              "      <td>Store Associate - Retail Sales (Customer Servi...</td>\n",
              "      <td>Store Associate - Retail Sales (Customer Service)</td>\n",
              "      <td>ALDI</td>\n",
              "      <td>Onalaska</td>\n",
              "      <td>Wisconsin</td>\n",
              "      <td>WI</td>\n",
              "      <td>NaN</td>\n",
              "      <td>43.906500</td>\n",
              "      <td>-91.233400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Hiring Event Details\\r\\nStore Associate\\r\\n\\r\\...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Full-Time/Part-Time</td>\n",
              "      <td>High School Diploma</td>\n",
              "      <td>2014-12-05 16:55:07 UTC</td>\n",
              "      <td>2014-12-05 16:55:07 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>134275</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>skokie-il-macy-s-macy-s-seasonal-retail-commis...</td>\n",
              "      <td>Macy's Seasonal Retail Commission Sales Women'...</td>\n",
              "      <td>Macy's Seasonal Retail Commission Sales Women'...</td>\n",
              "      <td>Macy's</td>\n",
              "      <td>Skokie</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>IL</td>\n",
              "      <td>NaN</td>\n",
              "      <td>42.034500</td>\n",
              "      <td>-87.757800</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Overview:\\r\\n\\r\\nThe Seasonal Draw Commission ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Seasonal/Temp</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:08 UTC</td>\n",
              "      <td>2014-12-05 16:55:08 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>134276</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>louisville-ky-kroger-louisville-part-time-cler...</td>\n",
              "      <td>Part Time Clerks Needed @ Kroger - Louisville</td>\n",
              "      <td>Part Time Clerks Needed</td>\n",
              "      <td>Kroger - Louisville</td>\n",
              "      <td>Louisville</td>\n",
              "      <td>Kentucky</td>\n",
              "      <td>KY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>38.254860</td>\n",
              "      <td>-85.766400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Exciting Job Opportunities Await YOU at KROGER...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:09 UTC</td>\n",
              "      <td>2014-12-05 16:55:09 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>134277</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>mullins-sc-coca-cola-bottling-company-consolid...</td>\n",
              "      <td>Flex (Part Time) Merchandiser - Mullins, SC @ ...</td>\n",
              "      <td>Flex (Part Time) Merchandiser - Mullins, SC</td>\n",
              "      <td>Coca-Cola Bottling Company Consolidated</td>\n",
              "      <td>Mullins</td>\n",
              "      <td>South Carolina</td>\n",
              "      <td>SC</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.189300</td>\n",
              "      <td>-79.258900</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Click here to view a video about this position...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:10 UTC</td>\n",
              "      <td>2014-12-05 16:55:10 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>134278</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>philadelphia-pa-catch-inc-child-psychotherapis...</td>\n",
              "      <td>Child Psychotherapist @ CATCH, Inc.</td>\n",
              "      <td>Child Psychotherapist</td>\n",
              "      <td>CATCH, Inc.</td>\n",
              "      <td>Philadelphia</td>\n",
              "      <td>Pennsylvania</td>\n",
              "      <td>PA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>39.938900</td>\n",
              "      <td>-75.182400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>&amp;nbsp;\\r\\n\\r\\n\\r\\n    \\r\\n    Complete\\r\\n    ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Full-Time/Part-Time</td>\n",
              "      <td>Master's Degree</td>\n",
              "      <td>2014-12-05 16:55:11 UTC</td>\n",
              "      <td>2014-12-05 16:55:11 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>134279</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>louisville-ky-kroger-louisville-part-time-cler...</td>\n",
              "      <td>Part Time Clerks Needed @ Kroger - Louisville</td>\n",
              "      <td>Part Time Clerks Needed</td>\n",
              "      <td>Kroger - Louisville</td>\n",
              "      <td>Louisville</td>\n",
              "      <td>Kentucky</td>\n",
              "      <td>KY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>38.254860</td>\n",
              "      <td>-85.766400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Exciting Job Opportunities Await YOU at KROGER...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:12 UTC</td>\n",
              "      <td>2014-12-05 16:55:12 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>134280</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>southern-pines-nc-longhorn-steakhouse-hiring-k...</td>\n",
              "      <td>Hiring Kitchen Positions - Experienced Line Co...</td>\n",
              "      <td>Hiring Kitchen Positions - Experienced Line Cooks</td>\n",
              "      <td>LongHorn Steakhouse</td>\n",
              "      <td>Southern Pines</td>\n",
              "      <td>North Carolina</td>\n",
              "      <td>NC</td>\n",
              "      <td>NaN</td>\n",
              "      <td>35.174400</td>\n",
              "      <td>-79.391490</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Steer YOUR Success\\r\\n\\r\\nAt LongHorn, team me...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Full-Time/Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:13 UTC</td>\n",
              "      <td>2014-12-05 16:55:13 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>134281</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>elizabeth-nj-new-york-community-bank-hr-admini...</td>\n",
              "      <td>HR Administrator @ New York Community Bank</td>\n",
              "      <td>HR Administrator</td>\n",
              "      <td>New York Community Bank</td>\n",
              "      <td>Elizabeth</td>\n",
              "      <td>New Jersey</td>\n",
              "      <td>NJ</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.670900</td>\n",
              "      <td>-74.179000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>JOB SUMMARY Provides administrative support fo...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:14 UTC</td>\n",
              "      <td>2014-12-05 16:55:14 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>134282</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>dayton-oh-macy-s-retail-gift-registry-advisor-...</td>\n",
              "      <td>Retail Gift Registry Advisor, Full Time/Part T...</td>\n",
              "      <td>Retail Gift Registry Advisor, Full Time/Part T...</td>\n",
              "      <td>Macy's</td>\n",
              "      <td>Dayton</td>\n",
              "      <td>Ohio</td>\n",
              "      <td>OH</td>\n",
              "      <td>NaN</td>\n",
              "      <td>39.646800</td>\n",
              "      <td>-84.168300</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Job Overview:\\r\\n\\r\\nAs a Gift Registry Adviso...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Full-Time/Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:16 UTC</td>\n",
              "      <td>2014-12-05 16:55:16 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>134283</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>bloomington-mn-holiday-inn-express-independent...</td>\n",
              "      <td>Weekend Breakfast Attendant @ Holiday Inn Expr...</td>\n",
              "      <td>Weekend Breakfast Attendant</td>\n",
              "      <td>Holiday Inn Express- Independently Owned &amp; Ope...</td>\n",
              "      <td>Bloomington</td>\n",
              "      <td>Minnesota</td>\n",
              "      <td>MN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>44.873700</td>\n",
              "      <td>-93.334300</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Holiday Inn Express and Suites Bloomington Mpl...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:16 UTC</td>\n",
              "      <td>2014-12-05 16:55:16 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>134284</td>\n",
              "      <td>2</td>\n",
              "      <td>open</td>\n",
              "      <td>louisville-ky-kroger-louisville-part-time-cler...</td>\n",
              "      <td>Part Time Clerks Needed @ Kroger - Louisville</td>\n",
              "      <td>Part Time Clerks Needed</td>\n",
              "      <td>Kroger - Louisville</td>\n",
              "      <td>Louisville</td>\n",
              "      <td>Kentucky</td>\n",
              "      <td>KY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>38.254860</td>\n",
              "      <td>-85.766400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Exciting Job Opportunities Await YOU at KROGER...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12-05-2014</td>\n",
              "      <td>01-04-2015</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Not Specified</td>\n",
              "      <td>2014-12-05 16:55:18 UTC</td>\n",
              "      <td>2014-12-05 16:55:18 UTC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Job.ID  Provider  ...               Created.At               Updated.At\n",
              "0      111         1  ...  2013-03-12 02:08:28 UTC  2014-08-16 15:35:36 UTC\n",
              "1      113         1  ...  2013-04-12 08:36:36 UTC  2014-08-16 15:35:36 UTC\n",
              "2      117         1  ...  2013-07-16 09:34:10 UTC  2014-08-16 15:35:37 UTC\n",
              "3      121         1  ...  2013-09-04 15:40:30 UTC  2014-08-16 15:35:38 UTC\n",
              "4      127         1  ...  2013-07-17 15:26:18 UTC  2014-08-16 15:35:40 UTC\n",
              "5      129         1  ...  2013-03-12 03:01:36 UTC  2014-08-16 15:35:40 UTC\n",
              "6      131         1  ...  2013-09-27 17:46:47 UTC  2014-08-16 15:36:13 UTC\n",
              "7      133         1  ...  2013-05-15 01:58:55 UTC  2014-08-16 15:35:41 UTC\n",
              "8   134273         2  ...  2014-12-05 16:55:06 UTC  2014-12-05 16:55:06 UTC\n",
              "9   134274         2  ...  2014-12-05 16:55:07 UTC  2014-12-05 16:55:07 UTC\n",
              "10  134275         2  ...  2014-12-05 16:55:08 UTC  2014-12-05 16:55:08 UTC\n",
              "11  134276         2  ...  2014-12-05 16:55:09 UTC  2014-12-05 16:55:09 UTC\n",
              "12  134277         2  ...  2014-12-05 16:55:10 UTC  2014-12-05 16:55:10 UTC\n",
              "13  134278         2  ...  2014-12-05 16:55:11 UTC  2014-12-05 16:55:11 UTC\n",
              "14  134279         2  ...  2014-12-05 16:55:12 UTC  2014-12-05 16:55:12 UTC\n",
              "15  134280         2  ...  2014-12-05 16:55:13 UTC  2014-12-05 16:55:13 UTC\n",
              "16  134281         2  ...  2014-12-05 16:55:14 UTC  2014-12-05 16:55:14 UTC\n",
              "17  134282         2  ...  2014-12-05 16:55:16 UTC  2014-12-05 16:55:16 UTC\n",
              "18  134283         2  ...  2014-12-05 16:55:16 UTC  2014-12-05 16:55:16 UTC\n",
              "19  134284         2  ...  2014-12-05 16:55:18 UTC  2014-12-05 16:55:18 UTC\n",
              "\n",
              "[20 rows x 23 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yJ-lwakPRmEm",
        "outputId": "f6989a4c-bad5-4109-9a35-aa9b66b15b18"
      },
      "source": [
        "df_job.info()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 84090 entries, 0 to 84089\n",
            "Data columns (total 23 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   Job.ID              84090 non-null  int64  \n",
            " 1   Provider            84090 non-null  int64  \n",
            " 2   Status              84090 non-null  object \n",
            " 3   Slug                84090 non-null  object \n",
            " 4   Title               84090 non-null  object \n",
            " 5   Position            84090 non-null  object \n",
            " 6   Company             81819 non-null  object \n",
            " 7   City                83955 non-null  object \n",
            " 8   State.Name          83919 non-null  object \n",
            " 9   State.Code          83919 non-null  object \n",
            " 10  Address             36 non-null     object \n",
            " 11  Latitude            84090 non-null  float64\n",
            " 12  Longitude           84090 non-null  float64\n",
            " 13  Industry            267 non-null    object \n",
            " 14  Job.Description     84034 non-null  object \n",
            " 15  Requirements        0 non-null      float64\n",
            " 16  Salary              229 non-null    float64\n",
            " 17  Listing.Start       83407 non-null  object \n",
            " 18  Listing.End         83923 non-null  object \n",
            " 19  Employment.Type     84080 non-null  object \n",
            " 20  Education.Required  83823 non-null  object \n",
            " 21  Created.At          84090 non-null  object \n",
            " 22  Updated.At          84090 non-null  object \n",
            "dtypes: float64(4), int64(2), object(17)\n",
            "memory usage: 14.8+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E8_-L-ToT0bT"
      },
      "source": [
        "\n",
        "For this example we only consider the columns: 'Job.ID', 'Title', 'Position', 'Company','City', 'Empl_type','Job_Description"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        },
        "id": "nOCkpOvTSJlK",
        "outputId": "8c6555be-f7f1-461b-efb8-cd3c1986f2c5"
      },
      "source": [
        "cols = ['Job.ID']+['Title']+['Position']+ ['Company']+['City']+['Employment.Type']+['Job.Description']\n",
        "df_jobs =df_job[cols]\n",
        "df_jobs.columns = ['Job.ID', 'Title', 'Position', 'Company','City', 'Empl_type','Job_Description']\n",
        "df_jobs.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Job.ID</th>\n",
              "      <th>Title</th>\n",
              "      <th>Position</th>\n",
              "      <th>Company</th>\n",
              "      <th>City</th>\n",
              "      <th>Empl_type</th>\n",
              "      <th>Job_Description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>111</td>\n",
              "      <td>Server @ Tacolicious</td>\n",
              "      <td>Server</td>\n",
              "      <td>Tacolicious</td>\n",
              "      <td>Palo Alto</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Tacolicious' first Palo Alto store just opened...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>113</td>\n",
              "      <td>Kitchen Staff/Chef @ Claude Lane</td>\n",
              "      <td>Kitchen Staff/Chef</td>\n",
              "      <td>Claude Lane</td>\n",
              "      <td>San Francisco</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>\\r\\n\\r\\nNew French Brasserie in S.F. Financia...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>117</td>\n",
              "      <td>Bartender @ Machka Restaurants Corp.</td>\n",
              "      <td>Bartender</td>\n",
              "      <td>Machka Restaurants Corp.</td>\n",
              "      <td>San Francisco</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>We are a popular Mediterranean wine bar and re...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>121</td>\n",
              "      <td>Server @ Teriyaki House</td>\n",
              "      <td>Server</td>\n",
              "      <td>Teriyaki House</td>\n",
              "      <td>Brisbane</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>● Serve food/drinks to customers in a profess...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>127</td>\n",
              "      <td>Kitchen Staff/Chef @ Rosa Mexicano - Sunset</td>\n",
              "      <td>Kitchen Staff/Chef</td>\n",
              "      <td>Rosa Mexicano - Sunset</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Located at the heart of Hollywood, we are one ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Job.ID  ...                                    Job_Description\n",
              "0     111  ...  Tacolicious' first Palo Alto store just opened...\n",
              "1     113  ...   \\r\\n\\r\\nNew French Brasserie in S.F. Financia...\n",
              "2     117  ...  We are a popular Mediterranean wine bar and re...\n",
              "3     121  ...   ● Serve food/drinks to customers in a profess...\n",
              "4     127  ...  Located at the heart of Hollywood, we are one ...\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VP3Udb81T98n",
        "outputId": "c91a2ef1-44cc-4f50-ad1a-1c67fdf6cae8"
      },
      "source": [
        "df_jobs.isnull().sum()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Job.ID                0\n",
              "Title                 0\n",
              "Position              0\n",
              "Company            2271\n",
              "City                135\n",
              "Empl_type            10\n",
              "Job_Description      56\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 523
        },
        "id": "7RaevnRmUMnL",
        "outputId": "5617d83a-66b4-4f71-93ca-55b18ee3a633"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline\n",
        "x = df_jobs.columns\n",
        "y = df_jobs.isnull().sum()\n",
        "plt.figure(figsize=(10,6))\n",
        "sns.set()\n",
        "sns.barplot(x,y)\n",
        "ax = plt.gca()\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    ax.text(p.get_x(),\n",
        "            height + 2,\n",
        "            str(100*round(int(height)/df_jobs.shape[0], 3)) +\"%\",\n",
        "            fontsize=10, ha='center', va='bottom')\n",
        "ax.set_xlabel(\"Columns\")\n",
        "ax.set_ylabel(\"NA's\")\n",
        "plt.xticks(rotation=80)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_1nm-ehwUegy",
        "outputId": "b318a4fd-934a-411c-8bb3-8ee7c157bc81"
      },
      "source": [
        "df_nan_city = df_jobs[pd.isnull(df_jobs['City'])]\n",
        "print(df_nan_city.shape)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(135, 7)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AejtJdanVQcW",
        "outputId": "0e2b70af-d518-4aec-e90c-163b1a6494f7"
      },
      "source": [
        "df_nan_city.groupby(['Company'])['City'].count()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Company\n",
              "Academic Year In America                0\n",
              "CBS Healthcare Services and Staffing    0\n",
              "CHI Payment Systems                     0\n",
              "Driveline Retail                        0\n",
              "Educational Testing Services            0\n",
              "Genesis Health System                   0\n",
              "Genesis Health Systems                  0\n",
              "Home Instead Senior Care                0\n",
              "St. Francis Hospital                    0\n",
              "Volvo Group                             0\n",
              "Name: City, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F-P6IuN7WC1F"
      },
      "source": [
        "# **Note**: We see that there are only 9 companies cities that are having NaN values so it must be manually adding their head quarters (by simply searching at google)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bd-Cpw8zVnv_",
        "outputId": "74f01f40-f77a-40df-acbe-718d9535467c"
      },
      "source": [
        "#replacing nan with thier headquarters location\n",
        "df_jobs['Company'] = df_jobs['Company'].replace(['Genesis Health Systems'], 'Genesis Health System')\n",
        "df_jobs.loc[df_jobs.Company == 'CHI Payment Systems', 'City'] = 'Illinois'\n",
        "df_jobs.loc[df_jobs.Company == 'Academic Year In America', 'City'] = 'Stamford'\n",
        "df_jobs.loc[df_jobs.Company == 'CBS Healthcare Services and Staffing ', 'City'] = 'Urbandale'\n",
        "df_jobs.loc[df_jobs.Company == 'Driveline Retail', 'City'] = 'Coppell'\n",
        "df_jobs.loc[df_jobs.Company == 'Educational Testing Services', 'City'] = 'New Jersey'\n",
        "df_jobs.loc[df_jobs.Company == 'Genesis Health System', 'City'] = 'Davennport'\n",
        "df_jobs.loc[df_jobs.Company == 'Home Instead Senior Care', 'City'] = 'Nebraska'\n",
        "df_jobs.loc[df_jobs.Company == 'St. Francis Hospital', 'City'] = 'New York'\n",
        "df_jobs.loc[df_jobs.Company == 'Volvo Group', 'City'] = 'Washington'\n",
        "df_jobs.loc[df_jobs.Company == 'CBS Healthcare Services and Staffing', 'City'] = 'Urbandale'"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1763: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(loc, value)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0kOgLAUYXL-G",
        "outputId": "3f9a8e4c-360c-447a-922e-c1b32e55be2f"
      },
      "source": [
        "df_jobs.isnull().sum()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Job.ID                0\n",
              "Title                 0\n",
              "Position              0\n",
              "Company            2271\n",
              "City                  0\n",
              "Empl_type            10\n",
              "Job_Description      56\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J_AChj98XSGE"
      },
      "source": [
        "#The employement type NA are from Uber so I assume as part-time and full time"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "p-QvWFHfXQuM",
        "outputId": "8f661db4-f633-4a1a-e686-1633507abc79"
      },
      "source": [
        "df_nan_emp = df_jobs[pd.isnull(df_jobs['Empl_type'])]\n",
        "df_nan_emp.head()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Job.ID</th>\n",
              "      <th>Title</th>\n",
              "      <th>Position</th>\n",
              "      <th>Company</th>\n",
              "      <th>City</th>\n",
              "      <th>Empl_type</th>\n",
              "      <th>Job_Description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>10768</th>\n",
              "      <td>153197</td>\n",
              "      <td>Driving Partner @ Uber</td>\n",
              "      <td>Driving Partner</td>\n",
              "      <td>Uber</td>\n",
              "      <td>San Francisco</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Uber is changing the way the world moves. From...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10769</th>\n",
              "      <td>153198</td>\n",
              "      <td>Driving Partner @ Uber</td>\n",
              "      <td>Driving Partner</td>\n",
              "      <td>Uber</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Uber is changing the way the world moves. From...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10770</th>\n",
              "      <td>153199</td>\n",
              "      <td>Driving Partner @ Uber</td>\n",
              "      <td>Driving Partner</td>\n",
              "      <td>Uber</td>\n",
              "      <td>Chicago</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Uber is changing the way the world moves. From...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10771</th>\n",
              "      <td>153200</td>\n",
              "      <td>Driving Partner @ Uber</td>\n",
              "      <td>Driving Partner</td>\n",
              "      <td>Uber</td>\n",
              "      <td>Boston</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Uber is changing the way the world moves. From...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10772</th>\n",
              "      <td>153201</td>\n",
              "      <td>Driving Partner @ Uber</td>\n",
              "      <td>Driving Partner</td>\n",
              "      <td>Uber</td>\n",
              "      <td>Ann Arbor</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Uber is changing the way the world moves. From...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Job.ID  ...                                    Job_Description\n",
              "10768  153197  ...  Uber is changing the way the world moves. From...\n",
              "10769  153198  ...  Uber is changing the way the world moves. From...\n",
              "10770  153199  ...  Uber is changing the way the world moves. From...\n",
              "10771  153200  ...  Uber is changing the way the world moves. From...\n",
              "10772  153201  ...  Uber is changing the way the world moves. From...\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HM6FdLKnXrM7",
        "outputId": "5205e578-63d3-49b3-c446-a1ff7e836551"
      },
      "source": [
        "df_jobs['Empl_type'].unique()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Part-Time', 'Full-Time/Part-Time', 'Seasonal/Temp', 'Per Diem',\n",
              "       'Intern', nan, 'Full-Time', 'Contract', 'Temporary/seasonal'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1n-SUTVyXzBB",
        "outputId": "f88dfabd-cade-46fd-ef0f-d0c206fa5168"
      },
      "source": [
        "#replacing na values with part time/full time\n",
        "df_jobs['Empl_type']=df_jobs['Empl_type'].fillna('Full-Time/Part-Time')\n",
        "df_jobs.groupby(['Empl_type'])['Company'].count()\n"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empl_type\n",
              "Contract                  14\n",
              "Full-Time                 37\n",
              "Full-Time/Part-Time    16771\n",
              "Intern                   904\n",
              "Part-Time              32188\n",
              "Per Diem                4514\n",
              "Seasonal/Temp          27390\n",
              "Temporary/seasonal         1\n",
              "Name: Company, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 244
        },
        "id": "zn3MJN27Y4k4",
        "outputId": "680d98fa-288c-4926-85da-3c64a52ea9a6"
      },
      "source": [
        "df_jobs['text']=df_jobs['Position'].map(str) +\" \"+df_jobs['Company'] +\" \"+ df_jobs['City'] +\" \"+df_jobs['Empl_type']+\" \"+df_jobs['Job_Description'] +\" \"+df_jobs['Title']\n",
        "df_jobs.head(2)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Job.ID</th>\n",
              "      <th>Title</th>\n",
              "      <th>Position</th>\n",
              "      <th>Company</th>\n",
              "      <th>City</th>\n",
              "      <th>Empl_type</th>\n",
              "      <th>Job_Description</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>111</td>\n",
              "      <td>Server @ Tacolicious</td>\n",
              "      <td>Server</td>\n",
              "      <td>Tacolicious</td>\n",
              "      <td>Palo Alto</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>Tacolicious' first Palo Alto store just opened...</td>\n",
              "      <td>Server Tacolicious Palo Alto Part-Time Tacolic...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>113</td>\n",
              "      <td>Kitchen Staff/Chef @ Claude Lane</td>\n",
              "      <td>Kitchen Staff/Chef</td>\n",
              "      <td>Claude Lane</td>\n",
              "      <td>San Francisco</td>\n",
              "      <td>Part-Time</td>\n",
              "      <td>\\r\\n\\r\\nNew French Brasserie in S.F. Financia...</td>\n",
              "      <td>Kitchen Staff/Chef Claude Lane San Francisco P...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Job.ID  ...                                               text\n",
              "0     111  ...  Server Tacolicious Palo Alto Part-Time Tacolic...\n",
              "1     113  ...  Kitchen Staff/Chef Claude Lane San Francisco P...\n",
              "\n",
              "[2 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "Ga1PrzGNZKIQ",
        "outputId": "44ee49bb-e402-49d9-83bf-413c45a2ae9a"
      },
      "source": [
        "df_all = df_jobs[['Job.ID', 'text', 'Title']]\n",
        "\n",
        "df_all = df_all.fillna(\" \")\n",
        "\n",
        "df_all.head()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Job.ID</th>\n",
              "      <th>text</th>\n",
              "      <th>Title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>111</td>\n",
              "      <td>Server Tacolicious Palo Alto Part-Time Tacolic...</td>\n",
              "      <td>Server @ Tacolicious</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>113</td>\n",
              "      <td>Kitchen Staff/Chef Claude Lane San Francisco P...</td>\n",
              "      <td>Kitchen Staff/Chef @ Claude Lane</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>117</td>\n",
              "      <td>Bartender Machka Restaurants Corp. San Francis...</td>\n",
              "      <td>Bartender @ Machka Restaurants Corp.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>121</td>\n",
              "      <td>Server Teriyaki House Brisbane Part-Time  ● Se...</td>\n",
              "      <td>Server @ Teriyaki House</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>127</td>\n",
              "      <td>Kitchen Staff/Chef Rosa Mexicano - Sunset Los ...</td>\n",
              "      <td>Kitchen Staff/Chef @ Rosa Mexicano - Sunset</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Job.ID  ...                                        Title\n",
              "0     111  ...                         Server @ Tacolicious\n",
              "1     113  ...             Kitchen Staff/Chef @ Claude Lane\n",
              "2     117  ...         Bartender @ Machka Restaurants Corp.\n",
              "3     121  ...                      Server @ Teriyaki House\n",
              "4     127  ...  Kitchen Staff/Chef @ Rosa Mexicano - Sunset\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v1wgYT21ckwM",
        "outputId": "3b14c7a3-faae-405c-d085-c574e89cb1ca"
      },
      "source": [
        "df_all.shape"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(84090, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lNjkm9XicoQt",
        "outputId": "c8338a5c-3fb0-490e-f8b2-0a20ebfc1001"
      },
      "source": [
        "nltk.download('punkt')\n",
        "nltk.download('stopwords')\n",
        "nltk.download('wordnet')\n",
        "nltk.download('averaged_perceptron_tagger')"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n",
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/wordnet.zip.\n",
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     /root/nltk_data...\n",
            "[nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DDG3PyWHcuwB"
      },
      "source": [
        "from nltk.corpus import stopwords\n",
        "import re\n",
        "import string\n",
        "from nltk.stem import WordNetLemmatizer\n",
        "from nltk import word_tokenize\n",
        "from nltk.corpus import stopwords\n",
        "stop = stopwords.words('english')\n",
        "stop_words_ = set(stopwords.words('english'))\n",
        "wn = WordNetLemmatizer()\n",
        "\n",
        "def black_txt(token):\n",
        "    return  token not in stop_words_ and token not in list(string.punctuation)  and len(token)>2   \n",
        "  \n",
        "def clean_txt(text):\n",
        "  clean_text = []\n",
        "  clean_text2 = []\n",
        "  text = re.sub(\"'\", \"\",text)\n",
        "  text=re.sub(\"(\\\\d|\\\\W)+\",\" \",text) \n",
        "  text = text.replace(\"nbsp\", \"\")\n",
        "  clean_text = [ wn.lemmatize(word, pos=\"v\") for word in word_tokenize(text.lower()) if black_txt(word)]\n",
        "  clean_text2 = [word for word in clean_text if black_txt(word)]\n",
        "  return \" \".join(clean_text2)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HPdlq1yrda5g"
      },
      "source": [
        "df_all['text'] = df_all['text'].apply(clean_txt)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "0RLU2FM0dhG4",
        "outputId": "fd2a3b24-389a-401e-d292-c3e22bde7c03"
      },
      "source": [
        "df_all.head()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .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>Job.ID</th>\n",
              "      <th>text</th>\n",
              "      <th>Title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>111</td>\n",
              "      <td>server tacolicious palo alto part time tacolic...</td>\n",
              "      <td>Server @ Tacolicious</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>113</td>\n",
              "      <td>kitchen staff chef claude lane san francisco p...</td>\n",
              "      <td>Kitchen Staff/Chef @ Claude Lane</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>117</td>\n",
              "      <td>bartender machka restaurants corp san francisc...</td>\n",
              "      <td>Bartender @ Machka Restaurants Corp.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>121</td>\n",
              "      <td>server teriyaki house brisbane part time serve...</td>\n",
              "      <td>Server @ Teriyaki House</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>127</td>\n",
              "      <td>kitchen staff chef rosa mexicano sunset los an...</td>\n",
              "      <td>Kitchen Staff/Chef @ Rosa Mexicano - Sunset</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Job.ID  ...                                        Title\n",
              "0     111  ...                         Server @ Tacolicious\n",
              "1     113  ...             Kitchen Staff/Chef @ Claude Lane\n",
              "2     117  ...         Bartender @ Machka Restaurants Corp.\n",
              "3     121  ...                      Server @ Teriyaki House\n",
              "4     127  ...  Kitchen Staff/Chef @ Rosa Mexicano - Sunset\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nrD81jgrgVRd",
        "outputId": "37b62396-ac55-4c4c-aeff-d2d547d9c72e"
      },
      "source": [
        "#initializing tfidf vectorizer\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "tfidf_vectorizer = TfidfVectorizer()\n",
        "\n",
        "tfidf_jobid = tfidf_vectorizer.fit_transform((df_all['text'])) #fitting and transforming the vector\n",
        "tfidf_jobid"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<84090x50754 sparse matrix of type '<class 'numpy.float64'>'\n",
              "\twith 8263698 stored elements in Compressed Sparse Row format>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M_vlaeyRh31R"
      },
      "source": [
        "# Cretating the User Corpus"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "FPRqr0VBhoNG",
        "outputId": "f6593b1d-2cb2-4fd5-bc92-79c557288b4e"
      },
      "source": [
        "df_job_view = pd.read_csv(\"/content/Recommender_system/MyDrive/Recommender_system/Job_Views.csv\")\n",
        "df_job_view.head(2)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Job.ID</th>\n",
              "      <th>Title</th>\n",
              "      <th>Position</th>\n",
              "      <th>Company</th>\n",
              "      <th>City</th>\n",
              "      <th>State.Name</th>\n",
              "      <th>State.Code</th>\n",
              "      <th>Industry</th>\n",
              "      <th>View.Start</th>\n",
              "      <th>View.End</th>\n",
              "      <th>View.Duration</th>\n",
              "      <th>Created.At</th>\n",
              "      <th>Updated.At</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10000</td>\n",
              "      <td>73666</td>\n",
              "      <td>Cashiers &amp; Valets Needed! @ WallyPark</td>\n",
              "      <td>Cashiers &amp; Valets Needed!</td>\n",
              "      <td>WallyPark</td>\n",
              "      <td>Newark</td>\n",
              "      <td>New Jersey</td>\n",
              "      <td>NJ</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2014-12-12 20:12:35 UTC</td>\n",
              "      <td>2014-12-12 20:31:24 UTC</td>\n",
              "      <td>1129.0</td>\n",
              "      <td>2014-12-12 20:12:35 UTC</td>\n",
              "      <td>2014-12-12 20:12:35 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10000</td>\n",
              "      <td>96655</td>\n",
              "      <td>Macy's Seasonal Retail Fragrance Cashier  - Ga...</td>\n",
              "      <td>Macy's Seasonal Retail Fragrance Cashier  - Ga...</td>\n",
              "      <td>Macy's</td>\n",
              "      <td>Garden City</td>\n",
              "      <td>New York</td>\n",
              "      <td>NY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2014-12-12 20:08:50 UTC</td>\n",
              "      <td>2014-12-12 20:10:15 UTC</td>\n",
              "      <td>84.0</td>\n",
              "      <td>2014-12-12 20:08:50 UTC</td>\n",
              "      <td>2014-12-12 20:08:50 UTC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID  Job.ID  ...               Created.At               Updated.At\n",
              "0         10000   73666  ...  2014-12-12 20:12:35 UTC  2014-12-12 20:12:35 UTC\n",
              "1         10000   96655  ...  2014-12-12 20:08:50 UTC  2014-12-12 20:08:50 UTC\n",
              "\n",
              "[2 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "id": "95JM2FMkknRT",
        "outputId": "3d9bc435-ae4a-427c-e50b-e19a34f0b5b0"
      },
      "source": [
        "df_job_view = df_job_view[['Applicant.ID', 'Job.ID', 'Position', 'Company','City']]\n",
        "df_job_view[\"select_pos_com_city\"] = df_job_view[\"Position\"].map(str) + \"  \" + df_job_view[\"Company\"] +\"  \"+ df_job_view[\"City\"]\n",
        "df_job_view['select_pos_com_city'] = df_job_view['select_pos_com_city'].map(str).apply(clean_txt)\n",
        "df_job_view['select_pos_com_city'] = df_job_view['select_pos_com_city'].str.lower()\n",
        "df_job_view = df_job_view[['Applicant.ID','select_pos_com_city']]\n",
        "df_job_view.head()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>select_pos_com_city</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10000</td>\n",
              "      <td>cashier valet need wallypark newark</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10000</td>\n",
              "      <td>macys seasonal retail fragrance cashier garden...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10001</td>\n",
              "      <td>part time showroom sales cashier grizzly indus...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10002</td>\n",
              "      <td>event specialist part time advantage sales mar...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10002</td>\n",
              "      <td>bonefish kitchen staff bonefish grill greenville</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID                                select_pos_com_city\n",
              "0         10000                cashier valet need wallypark newark\n",
              "1         10000  macys seasonal retail fragrance cashier garden...\n",
              "2         10001  part time showroom sales cashier grizzly indus...\n",
              "3         10002  event specialist part time advantage sales mar...\n",
              "4         10002   bonefish kitchen staff bonefish grill greenville"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x1YSgj7xm0XS"
      },
      "source": [
        "#Experience Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "qW-rmLjak2VL",
        "outputId": "662f3628-8c01-4fed-956a-b189189b1081"
      },
      "source": [
        "#Experience\n",
        "df_experience = pd.read_csv(\"/content/Recommender_system/MyDrive/Recommender_system/Experience.csv\")\n",
        "df_experience.head(2)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Name</th>\n",
              "      <th>Employer.Name</th>\n",
              "      <th>City</th>\n",
              "      <th>State.Name</th>\n",
              "      <th>State.Code</th>\n",
              "      <th>Start.Date</th>\n",
              "      <th>End.Date</th>\n",
              "      <th>Job.Description</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Can.Contact.Employer</th>\n",
              "      <th>Created.At</th>\n",
              "      <th>Updated.At</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10001</td>\n",
              "      <td>Account Manager / Sales Administration / Quali...</td>\n",
              "      <td>Barcode Resourcing</td>\n",
              "      <td>Bellingham</td>\n",
              "      <td>Washington</td>\n",
              "      <td>WA</td>\n",
              "      <td>2012-10-15</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2014-12-12 20:10:02 UTC</td>\n",
              "      <td>2014-12-12 20:10:02 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10001</td>\n",
              "      <td>Electronics Technician / Item Master Controller</td>\n",
              "      <td>Ryzex Group</td>\n",
              "      <td>Bellingham</td>\n",
              "      <td>Washington</td>\n",
              "      <td>WA</td>\n",
              "      <td>2001-12-01</td>\n",
              "      <td>2012-04-01</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2014-12-12 20:10:02 UTC</td>\n",
              "      <td>2014-12-12 20:10:02 UTC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID  ...               Updated.At\n",
              "0         10001  ...  2014-12-12 20:10:02 UTC\n",
              "1         10001  ...  2014-12-12 20:10:02 UTC\n",
              "\n",
              "[2 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "qD6BY3yim8Vw",
        "outputId": "a802a450-f1b6-44e3-e440-556c7d2b5030"
      },
      "source": [
        "#taking only Position\n",
        "df_experience= df_experience[['Applicant.ID','Position.Name']]\n",
        "#cleaning the text\n",
        "df_experience['Position.Name'] = df_experience['Position.Name'].map(str).apply(clean_txt)\n",
        "df_experience.head()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10001</td>\n",
              "      <td>account manager sales administration quality a...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10001</td>\n",
              "      <td>electronics technician item master controller</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10001</td>\n",
              "      <td>machine operator</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10003</td>\n",
              "      <td>maintenance technician</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10003</td>\n",
              "      <td>electrical helper</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID                                      Position.Name\n",
              "0         10001  account manager sales administration quality a...\n",
              "1         10001      electronics technician item master controller\n",
              "2         10001                                   machine operator\n",
              "3         10003                             maintenance technician\n",
              "4         10003                                  electrical helper"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "EBXwULj3nBb1",
        "outputId": "daebbaff-b874-4473-a75b-5f183000f991"
      },
      "source": [
        "df_experience =  df_experience.sort_values(by='Applicant.ID')\n",
        "df_experience = df_experience.fillna(\" \")\n",
        "df_experience.head()\n"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2763</th>\n",
              "      <td>2</td>\n",
              "      <td>volunteer</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2762</th>\n",
              "      <td>2</td>\n",
              "      <td>writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3759</th>\n",
              "      <td>3</td>\n",
              "      <td>market intern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3758</th>\n",
              "      <td>3</td>\n",
              "      <td>server</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3757</th>\n",
              "      <td>3</td>\n",
              "      <td>prep cook</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Applicant.ID      Position.Name\n",
              "2763             2          volunteer\n",
              "2762             2  writer uloop blog\n",
              "3759             3      market intern\n",
              "3758             3             server\n",
              "3757             3          prep cook"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "e18DX59knlsP",
        "outputId": "1a8267c7-d938-4c2a-caed-c6269d6d68af"
      },
      "source": [
        "#adding same rows to a single row\n",
        "df_experience = df_experience.groupby('Applicant.ID', sort=False)['Position.Name'].apply(' '.join).reset_index()\n",
        "df_experience.head(5)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>market intern server prep cook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6</td>\n",
              "      <td>project assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>deli clerk server cashier food prep order taker</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID                                    Position.Name\n",
              "0             2                      volunteer writer uloop blog\n",
              "1             3                   market intern server prep cook\n",
              "2             6                                project assistant\n",
              "3             8  deli clerk server cashier food prep order taker\n",
              "4            11                                          cashier"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2TgcDdVCpEGg"
      },
      "source": [
        "#postion of interest DataSet"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "fk2tefSMomlO",
        "outputId": "c1bee883-f11e-461c-b3af-625f92c91d0b"
      },
      "source": [
        "#Position of interest\n",
        "df_poi =  pd.read_csv(\"/content/Recommender_system/MyDrive/Recommender_system/Positions_Of_Interest.csv\", sep=',')\n",
        "df_poi = df_poi.sort_values(by='Applicant.ID')\n",
        "df_poi.head()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Of.Interest</th>\n",
              "      <th>Created.At</th>\n",
              "      <th>Updated.At</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>6437</th>\n",
              "      <td>96</td>\n",
              "      <td>Server</td>\n",
              "      <td>2014-08-14 15:56:42 UTC</td>\n",
              "      <td>2015-02-26 20:35:12 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1156</th>\n",
              "      <td>153</td>\n",
              "      <td>Barista</td>\n",
              "      <td>2014-08-14 15:56:43 UTC</td>\n",
              "      <td>2015-02-18 02:35:06 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1155</th>\n",
              "      <td>153</td>\n",
              "      <td>Host</td>\n",
              "      <td>2014-08-14 15:56:42 UTC</td>\n",
              "      <td>2015-02-26 20:35:12 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1154</th>\n",
              "      <td>153</td>\n",
              "      <td>Server</td>\n",
              "      <td>2014-08-14 15:56:42 UTC</td>\n",
              "      <td>2015-02-26 20:35:12 UTC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1158</th>\n",
              "      <td>153</td>\n",
              "      <td>Sales Rep</td>\n",
              "      <td>2014-08-14 15:56:47 UTC</td>\n",
              "      <td>2015-03-02 02:13:08 UTC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Applicant.ID  ...               Updated.At\n",
              "6437            96  ...  2015-02-26 20:35:12 UTC\n",
              "1156           153  ...  2015-02-18 02:35:06 UTC\n",
              "1155           153  ...  2015-02-26 20:35:12 UTC\n",
              "1154           153  ...  2015-02-26 20:35:12 UTC\n",
              "1158           153  ...  2015-03-02 02:13:08 UTC\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "wLeeR0HZpPVp",
        "outputId": "9b8b7285-8543-4668-a891-f241c265c697"
      },
      "source": [
        "df_poi = df_poi.drop('Updated.At', 1)\n",
        "df_poi = df_poi.drop('Created.At', 1)\n",
        "\n",
        "#cleaning the text\n",
        "df_poi['Position.Of.Interest']=df_poi['Position.Of.Interest'].map(str).apply(clean_txt)\n",
        "df_poi = df_poi.fillna(\" \")\n",
        "df_poi.head(10)"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Of.Interest</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>6437</th>\n",
              "      <td>96</td>\n",
              "      <td>server</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1156</th>\n",
              "      <td>153</td>\n",
              "      <td>barista</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1155</th>\n",
              "      <td>153</td>\n",
              "      <td>host</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1154</th>\n",
              "      <td>153</td>\n",
              "      <td>server</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1158</th>\n",
              "      <td>153</td>\n",
              "      <td>sales rep</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1157</th>\n",
              "      <td>153</td>\n",
              "      <td>customer service rep</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1952</th>\n",
              "      <td>256</td>\n",
              "      <td>host</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1957</th>\n",
              "      <td>256</td>\n",
              "      <td>production area</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1956</th>\n",
              "      <td>256</td>\n",
              "      <td>sales rep</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1955</th>\n",
              "      <td>256</td>\n",
              "      <td>customer service rep</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Applicant.ID  Position.Of.Interest\n",
              "6437            96                server\n",
              "1156           153               barista\n",
              "1155           153                  host\n",
              "1154           153                server\n",
              "1158           153             sales rep\n",
              "1157           153  customer service rep\n",
              "1952           256                  host\n",
              "1957           256       production area\n",
              "1956           256             sales rep\n",
              "1955           256  customer service rep"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "gjruA73oq19I",
        "outputId": "af4d1f31-7d73-472e-9b0c-e36bc9d686fb"
      },
      "source": [
        "df_poi = df_poi.groupby('Applicant.ID', sort=True)['Position.Of.Interest'].apply(' '.join).reset_index()\n",
        "df_poi.head()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>Position.Of.Interest</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>96</td>\n",
              "      <td>server</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>153</td>\n",
              "      <td>barista host server sales rep customer service...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>256</td>\n",
              "      <td>host production area sales rep customer servic...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>438</td>\n",
              "      <td>customer service rep barista host server</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>568</td>\n",
              "      <td>receptionist customer service rep book keeper</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID                               Position.Of.Interest\n",
              "0            96                                             server\n",
              "1           153  barista host server sales rep customer service...\n",
              "2           256  host production area sales rep customer servic...\n",
              "3           438           customer service rep barista host server\n",
              "4           568      receptionist customer service rep book keeper"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XO8oWuUks359"
      },
      "source": [
        "#Creating the final user dataset by merging all the users datasets"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t5BZgjnrs6pC"
      },
      "source": [
        "Merging jobs and experience dataframes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "42G2x4HCrCWB",
        "outputId": "305e1635-fac3-4099-8dd4-5972490b42b9"
      },
      "source": [
        "df_jobs_exp = df_job_view.merge(df_experience, left_on='Applicant.ID', right_on='Applicant.ID', how='outer')\n",
        "df_jobs_exp = df_jobs_exp.fillna(' ')\n",
        "df_jobs_exp = df_jobs_exp.sort_values(by='Applicant.ID')\n",
        "df_jobs_exp.head()"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>select_pos_com_city</th>\n",
              "      <th>Position.Name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12370</th>\n",
              "      <td>2</td>\n",
              "      <td></td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12371</th>\n",
              "      <td>3</td>\n",
              "      <td></td>\n",
              "      <td>market intern server prep cook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12372</th>\n",
              "      <td>6</td>\n",
              "      <td></td>\n",
              "      <td>project assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12373</th>\n",
              "      <td>8</td>\n",
              "      <td></td>\n",
              "      <td>deli clerk server cashier food prep order taker</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12374</th>\n",
              "      <td>11</td>\n",
              "      <td></td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Applicant.ID  ...                                    Position.Name\n",
              "12370             2  ...                      volunteer writer uloop blog\n",
              "12371             3  ...                   market intern server prep cook\n",
              "12372             6  ...                                project assistant\n",
              "12373             8  ...  deli clerk server cashier food prep order taker\n",
              "12374            11  ...                                          cashier\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "obwD7LuVtrE4",
        "outputId": "912f2183-c569-4caa-9517-e35bd32818f1"
      },
      "source": [
        "df_jobs_exp_poi = df_jobs_exp.merge(df_poi, left_on='Applicant.ID', right_on='Applicant.ID', how='outer')\n",
        "df_jobs_exp_poi = df_jobs_exp_poi.fillna(' ')\n",
        "df_jobs_exp_poi = df_jobs_exp_poi.sort_values(by='Applicant.ID')\n",
        "df_jobs_exp_poi.head()"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>select_pos_com_city</th>\n",
              "      <th>Position.Name</th>\n",
              "      <th>Position.Of.Interest</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td></td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td></td>\n",
              "      <td>market intern server prep cook</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6</td>\n",
              "      <td></td>\n",
              "      <td>project assistant</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td></td>\n",
              "      <td>deli clerk server cashier food prep order taker</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td></td>\n",
              "      <td>cashier</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID  ... Position.Of.Interest\n",
              "0             2  ...                     \n",
              "1             3  ...                     \n",
              "2             6  ...                     \n",
              "3             8  ...                     \n",
              "4            11  ...                     \n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "x2qnu_-xul7n",
        "outputId": "97e58618-8f81-48a2-c44c-bb8d2105b2f8"
      },
      "source": [
        "df_jobs_exp_poi[\"text\"] = df_jobs_exp_poi[\"select_pos_com_city\"].map(str) + df_jobs_exp_poi[\"Position.Name\"] +\" \"+ df_jobs_exp_poi[\"Position.Of.Interest\"]\n",
        "\n",
        "df_jobs_exp_poi.head()"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>select_pos_com_city</th>\n",
              "      <th>Position.Name</th>\n",
              "      <th>Position.Of.Interest</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td></td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "      <td></td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td></td>\n",
              "      <td>market intern server prep cook</td>\n",
              "      <td></td>\n",
              "      <td>market intern server prep cook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6</td>\n",
              "      <td></td>\n",
              "      <td>project assistant</td>\n",
              "      <td></td>\n",
              "      <td>project assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td></td>\n",
              "      <td>deli clerk server cashier food prep order taker</td>\n",
              "      <td></td>\n",
              "      <td>deli clerk server cashier food prep order tak...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td></td>\n",
              "      <td>cashier</td>\n",
              "      <td></td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID  ...                                               text\n",
              "0             2  ...                      volunteer writer uloop blog  \n",
              "1             3  ...                   market intern server prep cook  \n",
              "2             6  ...                                project assistant  \n",
              "3             8  ...   deli clerk server cashier food prep order tak...\n",
              "4            11  ...                                          cashier  \n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "eDigp94quwM6",
        "outputId": "b4f9b50c-6a25-440f-8072-939596f2b8d1"
      },
      "source": [
        "df_final_person= df_jobs_exp_poi[['Applicant.ID','text']]\n",
        "df_final_person.head()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant.ID</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>market intern server prep cook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6</td>\n",
              "      <td>project assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>deli clerk server cashier food prep order tak...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant.ID                                               text\n",
              "0             2                      volunteer writer uloop blog  \n",
              "1             3                   market intern server prep cook  \n",
              "2             6                                project assistant  \n",
              "3             8   deli clerk server cashier food prep order tak...\n",
              "4            11                                          cashier  "
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "10cMOoqTu0lB",
        "outputId": "f81dd345-ddf8-4f1d-95b0-8e205c0052f0"
      },
      "source": [
        "df_final_person.columns = ['Applicant_id','text']\n",
        "df_final_person.head()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant_id</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>market intern server prep cook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6</td>\n",
              "      <td>project assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>deli clerk server cashier food prep order tak...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Applicant_id                                               text\n",
              "0             2                      volunteer writer uloop blog  \n",
              "1             3                   market intern server prep cook  \n",
              "2             6                                project assistant  \n",
              "3             8   deli clerk server cashier food prep order tak...\n",
              "4            11                                          cashier  "
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 919
        },
        "id": "1-e7U1ttu5gT",
        "outputId": "24f4cd3a-215b-41cc-81f9-f127f6c31e89"
      },
      "source": [
        "df_final_person['text'] = df_final_person['text'].apply(clean_txt)\n",
        "df_final_person.head(25)"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant_id</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>volunteer writer uloop blog</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>market intern server prep cook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6</td>\n",
              "      <td>project assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>deli clerk server cashier food prep order taker</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>12</td>\n",
              "      <td>server rec leader program management intern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>13</td>\n",
              "      <td>offica assistant cashier assistant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>14</td>\n",
              "      <td>waitress host lifeguard</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>15</td>\n",
              "      <td>nan nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>18</td>\n",
              "      <td>barista cashier server receptionist</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>21</td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>22</td>\n",
              "      <td>sandwich artist shift leader personal home</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>23</td>\n",
              "      <td>waiter server film editor waiter server</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>24</td>\n",
              "      <td>volunteer</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>26</td>\n",
              "      <td>cashier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>27</td>\n",
              "      <td>farm intern event organizer lifeguard children...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>30</td>\n",
              "      <td>server barback expediter</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>32</td>\n",
              "      <td>roundup newspaper intern intern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>33</td>\n",
              "      <td>waitress host softlines team trainer nanny</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>34</td>\n",
              "      <td>nan server server host</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>37</td>\n",
              "      <td>server food runner boh</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>38</td>\n",
              "      <td>sales person phone receptionist</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>39</td>\n",
              "      <td>waiter red cross certify lifeguard</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>40</td>\n",
              "      <td>food server lead</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>41</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Applicant_id                                               text\n",
              "0              2                        volunteer writer uloop blog\n",
              "1              3                     market intern server prep cook\n",
              "2              6                                  project assistant\n",
              "3              8    deli clerk server cashier food prep order taker\n",
              "4             11                                            cashier\n",
              "5             12        server rec leader program management intern\n",
              "6             13                 offica assistant cashier assistant\n",
              "7             14                            waitress host lifeguard\n",
              "8             15                                            nan nan\n",
              "9             18                barista cashier server receptionist\n",
              "10            21                                            cashier\n",
              "11            22         sandwich artist shift leader personal home\n",
              "12            23            waiter server film editor waiter server\n",
              "13            24                                          volunteer\n",
              "14            26                                            cashier\n",
              "15            27  farm intern event organizer lifeguard children...\n",
              "16            30                           server barback expediter\n",
              "17            32                    roundup newspaper intern intern\n",
              "18            33         waitress host softlines team trainer nanny\n",
              "19            34                             nan server server host\n",
              "20            37                             server food runner boh\n",
              "21            38                    sales person phone receptionist\n",
              "22            39                 waiter red cross certify lifeguard\n",
              "23            40                                   food server lead\n",
              "24            41                                                nan"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qgXEVJVLwJpT"
      },
      "source": [
        "For test the recommender we select the user which ID is 326"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 79
        },
        "id": "dxohgkVWvwGI",
        "outputId": "e14a3ed5-fb8e-48c1-9bc8-8cb76bd86a54"
      },
      "source": [
        "u=326\n",
        "index=np.where(df_final_person['Applicant_id']==u)[0][0]\n",
        "user_q=df_final_person.iloc[[index]]\n",
        "user_q"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Applicant_id</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>326</td>\n",
              "      <td>java developer</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Applicant_id            text\n",
              "186           326  java developer"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uovtEJcHx95N"
      },
      "source": [
        "computing cosin similarity"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XHs1q4RZwnoN",
        "outputId": "1a4d9c5c-c7ba-49ff-ce0a-cb52e5f21d9c"
      },
      "source": [
        "tfidf_jobid"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<84090x50754 sparse matrix of type '<class 'numpy.float64'>'\n",
              "\twith 8263698 stored elements in Compressed Sparse Row format>"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lq_CxsZ9wPyC",
        "outputId": "56309f94-1830-4288-9a08-ec033bafd23b"
      },
      "source": [
        "from sklearn.metrics.pairwise import cosine_similarity\n",
        "user_tfidf = tfidf_vectorizer.transform(user_q['text'])\n",
        "print(user_tfidf)\n",
        "cos_similarity_tfidf = map(lambda x: cosine_similarity(user_tfidf, x),tfidf_jobid)\n",
        "print(cos_similarity_tfidf)"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  (0, 23985)\t0.7479647932040747\n",
            "  (0, 12245)\t0.6637384033843347\n",
            "<map object at 0x7ff9f72b6fd0>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CppsFX0sxV5P"
      },
      "source": [
        "output2 = list(cos_similarity_tfidf)\n"
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z9vAnQi7xn9b"
      },
      "source": [
        "output2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2CVNVOrwyFju"
      },
      "source": [
        "#Function to get the top-N recomendations order by score"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FBUrQB6tx4ut"
      },
      "source": [
        "def get_recommendation(top, df_all, scores):\n",
        "  recommendation = pd.DataFrame(columns = ['ApplicantID', 'JobID',  'title', 'score'])\n",
        "  count = 0\n",
        "  for i in top:\n",
        "      recommendation.at[count, 'ApplicantID'] = u\n",
        "      recommendation.at[count, 'JobID'] = df_all['Job.ID'][i]\n",
        "      recommendation.at[count, 'title'] = df_all['Title'][i]\n",
        "      recommendation.at[count, 'score'] =  scores[count]\n",
        "      count += 1\n",
        "  return recommendation"
      ],
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yrC1TPytyHWm",
        "outputId": "39773efe-6e1d-4849-eefc-d1493fe4c7ff"
      },
      "source": [
        "top = sorted(range(len(output2)), key=lambda i: output2[i], reverse=True)[:10]\n",
        "top"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[69346, 63958, 40385, 3231, 40634, 71496, 76180, 16225, 7108, 10301]"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5VvzX2iFyUYW",
        "outputId": "9abb8058-8920-411d-c104-c645c0ee7f88"
      },
      "source": [
        "list_scores = [output2[i][0][0] for i in top]\n",
        "list_scores"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.7494775251900346,\n",
              " 0.7408859264648847,\n",
              " 0.7370067616428033,\n",
              " 0.6716673937124861,\n",
              " 0.6450373772174958,\n",
              " 0.6255315736496132,\n",
              " 0.5922913263911141,\n",
              " 0.5302305793452344,\n",
              " 0.5105340708444382,\n",
              " 0.4867887337500865]"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "DZg4Rm9HyRIq",
        "outputId": "11430765-47cf-43df-b713-71a6ac355b46"
      },
      "source": [
        "top = sorted(range(len(output2)), key=lambda i: output2[i], reverse=True)[:10]\n",
        "list_scores = [output2[i][0][0] for i in top]\n",
        "get_recommendation(top,df_all, list_scores)"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ApplicantID</th>\n",
              "      <th>JobID</th>\n",
              "      <th>title</th>\n",
              "      <th>score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>326</td>\n",
              "      <td>303112</td>\n",
              "      <td>Java Developer @ TransHire</td>\n",
              "      <td>0.749478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>326</td>\n",
              "      <td>294684</td>\n",
              "      <td>Java Developer @ Kavaliro</td>\n",
              "      <td>0.740886</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>326</td>\n",
              "      <td>269922</td>\n",
              "      <td>Entry Level Java Developer / Jr. Java Develope...</td>\n",
              "      <td>0.737007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>326</td>\n",
              "      <td>141831</td>\n",
              "      <td>Lead Java/J2EE Developer - Contract to Hire @ ...</td>\n",
              "      <td>0.671667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>326</td>\n",
              "      <td>270171</td>\n",
              "      <td>Senior Java Developer - Contract to Hire - Gre...</td>\n",
              "      <td>0.645037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>326</td>\n",
              "      <td>305264</td>\n",
              "      <td>Sr. Java Developer @ Paladin Consulting Inc</td>\n",
              "      <td>0.625532</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>326</td>\n",
              "      <td>309945</td>\n",
              "      <td>Java Software Engineer @ iTech Solutions, Inc.</td>\n",
              "      <td>0.592291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>326</td>\n",
              "      <td>245753</td>\n",
              "      <td>Java Administrator @ ConsultNet</td>\n",
              "      <td>0.530231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>326</td>\n",
              "      <td>146640</td>\n",
              "      <td>Jr. Java Developer @ Paladin Consulting Inc</td>\n",
              "      <td>0.510534</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>326</td>\n",
              "      <td>150882</td>\n",
              "      <td>Java Consultant - Mobile Apps Development @ Co...</td>\n",
              "      <td>0.486789</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  ApplicantID  ...     score\n",
              "0         326  ...  0.749478\n",
              "1         326  ...  0.740886\n",
              "2         326  ...  0.737007\n",
              "3         326  ...  0.671667\n",
              "4         326  ...  0.645037\n",
              "5         326  ...  0.625532\n",
              "6         326  ...  0.592291\n",
              "7         326  ...  0.530231\n",
              "8         326  ...  0.510534\n",
              "9         326  ...  0.486789\n",
              "\n",
              "[10 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7lu9OqLhzHQl"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}