2022/2207-gender-pay-gap/GenderPayGap.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d617ba0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import math\n",
    "import matplotlib as mpl\n",
    "from matplotlib import font_manager\n",
    "import os, glob\n",
    "import json\n",
    "\n",
    "# define project directories \n",
    "root = os.path.abspath(os.getcwd())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3271349c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LISA~1.HOR\\AppData\\Local\\Temp/ipykernel_7636/2524972240.py:2: DtypeWarning: Columns (2,3,7) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  cc_df = pd.read_csv(\"registered-charity_20220724.csv\")\n"
     ]
    }
   ],
   "source": [
    "#read in charity data\n",
    "cc_df = pd.read_csv(\"registered-charity_20220724.csv\")\n",
    "cc_ch = cc_df[~cc_df[\"companyNumber\"].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9b5ed8c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "sic_section_names = {\n",
    "    \"A\": \"Agriculture (A)\",\n",
    "    \"B\": \"Mining (B)\",\n",
    "    \"C\": \"Manufacturing (C)\",\n",
    "    \"D\": \"Electricity and Gas (D)\", \n",
    "    \"E\": \"Water and waste management (E)\",\n",
    "    \"F\": \"Construction (F)\",\n",
    "    \"G\": \"Retail (G)\",\n",
    "    \"H\": \"Transportation (H)\",\n",
    "    \"I\": \"Accommodation and food services (I)\",\n",
    "    \"J\": \"Information and communication (J)\",\n",
    "    \"K\": \"Finance and insurance (K)\",\n",
    "    \"L\": \"Real estate (L)\",\n",
    "    \"M\": \"Scientific and technical activities (M)\",\n",
    "    \"N\": \"Administrative activities (N)\",\n",
    "    \"O\": \"Public administration (O)\",\n",
    "    \"P\": \"Education (P)\",\n",
    "    \"Q\": \"Health and social work (Q)\",\n",
    "    \"R\": \"Arts, entertainment and recreation (R)\",\n",
    "    \"S\": \"Other service activities (S)\",\n",
    "    \"T\": \"Households as employers (T)\",\n",
    "    \"U\": \"Extraterritorial organisations (U)\"\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8cc7a3ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "sic_section_names_chart = {\n",
    "    \"A\": \"Agriculture\",\n",
    "    \"B\": \"Mining\",\n",
    "    \"C\": \"Manufacturing\",\n",
    "    \"D\": \"Electricity\\nand gas\", \n",
    "    \"E\": \"Water and waste\",\n",
    "    \"F\": \"Construction\",\n",
    "    \"G\": \"Retail\",\n",
    "    \"H\": \"Transportation\",\n",
    "    \"I\": \"Accommodation/food\",\n",
    "    \"J\": \"Information\\n/communication\",\n",
    "    \"K\": \"Finance\",\n",
    "    \"L\": \"Real estate\",\n",
    "    \"M\": \"Scientific and\\ntechnical activities\",\n",
    "    \"N\": \"Administration\",\n",
    "    \"O\": \"Public administration\",\n",
    "    \"P\": \"Education\",\n",
    "    \"Q\": \"Health and\\nsocial work\",\n",
    "    \"R\": \"Arts and\\nrecreation\",\n",
    "    \"S\": \"Other services\",\n",
    "    \"T\": \"Households\",\n",
    "    \"U\": \"Extraterritorial orgs\"\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d2433275",
   "metadata": {},
   "outputs": [],
   "source": [
    "f = open('codes.json') \n",
    "sic_dict = json.load(f) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "79caa77f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in gender pay gap data and merge files\n",
    "all_files = glob.glob(os.path.join(root, \"UK Gender Pay Gap Data*.csv\"))\n",
    "\n",
    "all_df = []\n",
    "for f in all_files:\n",
    "    df = pd.read_csv(f, sep=',')\n",
    "    df['file'] = f.split('\\\\')[-1][-16:-4]\n",
    "    df = pd.merge(df, cc_ch, left_on=\"CompanyNumber\", right_on=\"companyNumber\", how='left')\n",
    "    all_df.append(df)\n",
    "    \n",
    "pay_df = pd.concat(all_df, ignore_index=True, sort=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "91c72c91",
   "metadata": {},
   "outputs": [],
   "source": [
    "pay_df.to_csv(\"test.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79709266",
   "metadata": {},
   "source": [
    "# Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb9134db",
   "metadata": {},
   "source": [
    "### SIC codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "id": "7ad345d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#clean up SIC codes a bit\n",
    "pay_df[\"SIC_clean\"] = pay_df[\"SicCodes\"].str.replace(\"1,\", \"\").str.replace(\"\\n\", \"\")\n",
    "pay_df[\"SIC_clean\"] = pay_df[\"SIC_clean\"].fillna(\"\")\n",
    "pay_df[\"SIC_clean\"] = pay_df[\"SIC_clean\"].str.split(\",\")\n",
    "pay_df[\"SIC_count\"] = pay_df[\"SIC_clean\"].str.len()\n",
    "\n",
    "#map against section and industry name from dictionary\n",
    "\n",
    "section_all = []\n",
    "name_all = []\n",
    "\n",
    "for i in range(len(pay_df[\"SIC_clean\"])):\n",
    "    section = []\n",
    "    name = []\n",
    "    for k in range(len(pay_df[\"SIC_clean\"][i])):\n",
    "        try:\n",
    "            section.append(sic_dict[pay_df[\"SIC_clean\"][i][k]][\"section\"])\n",
    "            name.append(sic_dict[pay_df[\"SIC_clean\"][i][k]][\"industry\"])\n",
    "        except KeyError:\n",
    "            pass\n",
    "    section_all.append(section)\n",
    "    name_all.append(name)\n",
    "\n",
    "#add to dataframe\n",
    "pay_df[\"SIC_sections\"] = section_all\n",
    "pay_df[\"SIC_names\"] = name_all\n",
    "\n",
    "#select first one as the main SIC\n",
    "pay_df[\"SIC_section\"] = pay_df[\"SIC_sections\"].str[0]\n",
    "pay_df[\"SIC_name\"] = pay_df[\"SIC_names\"].str[0]\n",
    "\n",
    "pay_df[\"SIC_section_name\"] = pay_df[\"SIC_section\"].map(sic_section_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "id": "3482674f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pay_df[\"NiceName\"] = pay_df[\"EmployerName\"].str.title()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "id": "cb129645",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Tech specific codes\n",
    "tech = [ \"58290\", \"62011\", \"62012\", \"62020\", \"62030\",  \"63110\", \"63120\"]\n",
    "\n",
    "#62090 exclude other technology services \n",
    "\n",
    "for code in tech:\n",
    "    pay_df.loc[pay_df[\"SicCodes\"].str.contains(code, na=False), \"Sector\"] = \"Tech\"\n",
    "\n",
    "pay_df.loc[(pay_df[\"SicCodes\"].str.contains(\"78300\", na=False)) & \n",
    "           (len(pay_df[\"SIC_sections\"])==1), \"Sector\"] = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "b4024d4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CompanyLinkToGPGInfo</th>\n",
       "      <th>CompanyNumber</th>\n",
       "      <th>CurrentName</th>\n",
       "      <th>SicCodes</th>\n",
       "      <th>Sector</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>https://www.allegisglobalsolutions.com/en-gb/c...</td>\n",
       "      <td>03550830</td>\n",
       "      <td>ALLEGIS GLOBAL SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n78109,\\n78200,\\n78300</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>https://www.allegisgroup.com/en-gb/legal</td>\n",
       "      <td>02876353</td>\n",
       "      <td>ALLEGIS GROUP LIMITED</td>\n",
       "      <td>62030,\\n78109,\\n78200,\\n78300</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>https://www.ans.co.uk/about/</td>\n",
       "      <td>03176761</td>\n",
       "      <td>ANS GROUP LIMITED</td>\n",
       "      <td>61900,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1722</th>\n",
       "      <td>https://www.ccsmedia.com/media/CCS-Media-Our-G...</td>\n",
       "      <td>01693516</td>\n",
       "      <td>CCS BOTTOMCO LIMITED</td>\n",
       "      <td>62030</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2950</th>\n",
       "      <td>https://www.ensono.com/uk/about-us/careers/gen...</td>\n",
       "      <td>03276974</td>\n",
       "      <td>ENSONO LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4333</th>\n",
       "      <td>https://cic-uk.eu-gb.mybluemix.net/pages/repor...</td>\n",
       "      <td>09360752</td>\n",
       "      <td>IBM SERVICES CENTRE UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63120</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4344</th>\n",
       "      <td>NaN</td>\n",
       "      <td>02758710</td>\n",
       "      <td>IDE GROUP MANAGE LIMITED</td>\n",
       "      <td>62030</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4572</th>\n",
       "      <td>https://www.itcinfotech.com/wp-content/uploads...</td>\n",
       "      <td>02777705</td>\n",
       "      <td>ITC INFOTECH LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4901</th>\n",
       "      <td>https://www.cloud9umbrella.com/modern-slavery-...</td>\n",
       "      <td>08156779</td>\n",
       "      <td>HAMRAN MANAGEMENT LIMITED</td>\n",
       "      <td>62030</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6496</th>\n",
       "      <td>https://www.oracle.com/goto/gpg-report</td>\n",
       "      <td>01782505</td>\n",
       "      <td>ORACLE CORPORATION UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7179</th>\n",
       "      <td>http://www.redcentricplc.com/about-us/gender-p...</td>\n",
       "      <td>08322856</td>\n",
       "      <td>REDCENTRIC SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8151</th>\n",
       "      <td>http://www.ssp-worldwide.com/wp-content/upload...</td>\n",
       "      <td>04234499</td>\n",
       "      <td>SSP LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8467</th>\n",
       "      <td>http://www.synectics-solutions.com</td>\n",
       "      <td>02685135</td>\n",
       "      <td>SYNECTICS SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10590</th>\n",
       "      <td>https://www.allegisgroup.com/-/media/files/all...</td>\n",
       "      <td>02876353</td>\n",
       "      <td>ALLEGIS GROUP LIMITED</td>\n",
       "      <td>62030,\\n78109,\\n78200,\\n78300</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13302</th>\n",
       "      <td>https://www.ensono.com/sites/default/files/Ens...</td>\n",
       "      <td>03276974</td>\n",
       "      <td>ENSONO LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13419</th>\n",
       "      <td>https://www.everis.co.uk/newsroom/2019-gender-...</td>\n",
       "      <td>07235059</td>\n",
       "      <td>EVERISCONSULTANCY LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n70229</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13444</th>\n",
       "      <td>https://www.excelredstone.com/</td>\n",
       "      <td>02027207</td>\n",
       "      <td>EXCELREDSTONE CONVERGED SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14724</th>\n",
       "      <td>http://uk.ciceurope.com/pages/reporting2018</td>\n",
       "      <td>09360752</td>\n",
       "      <td>IBM SERVICES CENTRE UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63120</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14976</th>\n",
       "      <td>https://www.itcinfotech.com/docs/resources/Gen...</td>\n",
       "      <td>02777705</td>\n",
       "      <td>ITC INFOTECH LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16504</th>\n",
       "      <td>https://www.netapp.com/us/media/netapp-gender-...</td>\n",
       "      <td>02998329</td>\n",
       "      <td>NETAPP UK LTD</td>\n",
       "      <td>46510,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16915</th>\n",
       "      <td>https://www.oracle.com/a/ocom/docs/oracle-gend...</td>\n",
       "      <td>01782505</td>\n",
       "      <td>ORACLE CORPORATION UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17616</th>\n",
       "      <td>https://www.redcentricplc.com/about-us/gender-...</td>\n",
       "      <td>08322856</td>\n",
       "      <td>REDCENTRIC SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18093</th>\n",
       "      <td>https://www.scisys.co.uk/who-we-are/csr/gender...</td>\n",
       "      <td>04373530</td>\n",
       "      <td>SCISYS UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18616</th>\n",
       "      <td>http://www.ssp-worldwide.com/wp-content/upload...</td>\n",
       "      <td>04234499</td>\n",
       "      <td>SSP LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18936</th>\n",
       "      <td>https://www.synectics-solutions.com/our-thinki...</td>\n",
       "      <td>02685135</td>\n",
       "      <td>SYNECTICS SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22820</th>\n",
       "      <td>https://www.everis.co.uk/newsroom/2020-gender-...</td>\n",
       "      <td>07235059</td>\n",
       "      <td>EVERISCONSULTANCY LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n70229</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23640</th>\n",
       "      <td>https://www.ibm.com/employment/ciceurope/uk-en...</td>\n",
       "      <td>09360752</td>\n",
       "      <td>IBM SERVICES CENTRE UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63120</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24820</th>\n",
       "      <td>https://www.netapp.com/pdf.html?item=/media/11...</td>\n",
       "      <td>02998329</td>\n",
       "      <td>NETAPP UK LTD</td>\n",
       "      <td>46510,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25565</th>\n",
       "      <td>https://www.redcentricplc.com/wp-content/uploa...</td>\n",
       "      <td>08322856</td>\n",
       "      <td>REDCENTRIC SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25898</th>\n",
       "      <td>https://www.cgi-group.co.uk/sites/default/file...</td>\n",
       "      <td>04373530</td>\n",
       "      <td>SCISYS UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26265</th>\n",
       "      <td>https://www.ssp-worldwide.com/about-us/gender-...</td>\n",
       "      <td>04234499</td>\n",
       "      <td>SSP LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26488</th>\n",
       "      <td>https://www.synectics-solutions.com/our-thinki...</td>\n",
       "      <td>02685135</td>\n",
       "      <td>SYNECTICS SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n63110,\\n82302</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28017</th>\n",
       "      <td>https://www.allegisglobalsolutions.com/en-gb/a...</td>\n",
       "      <td>03550830</td>\n",
       "      <td>ALLEGIS GLOBAL SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n78109,\\n78200,\\n78300</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28196</th>\n",
       "      <td>https://www.ans.co.uk/wp-content/uploads/2021/...</td>\n",
       "      <td>03176761</td>\n",
       "      <td>ANS GROUP LIMITED</td>\n",
       "      <td>61900,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30718</th>\n",
       "      <td>https://www.ensono.com/ensono-gender-pay-gap-r...</td>\n",
       "      <td>03276974</td>\n",
       "      <td>ENSONO LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30841</th>\n",
       "      <td>https://www.everis.co.uk/newsroom/2021-gender-...</td>\n",
       "      <td>07235059</td>\n",
       "      <td>EVERISCONSULTANCY LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n70229</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32137</th>\n",
       "      <td>https://www.ibm.com/employment/ciceurope/uk-en...</td>\n",
       "      <td>09360752</td>\n",
       "      <td>IBM SERVICES CENTRE UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63120</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32150</th>\n",
       "      <td>https://www.idegroup.com/</td>\n",
       "      <td>02758710</td>\n",
       "      <td>IDE GROUP MANAGE LIMITED</td>\n",
       "      <td>62030</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33939</th>\n",
       "      <td>https://www.netapp.com/pdf.html?item=/media/60...</td>\n",
       "      <td>02998329</td>\n",
       "      <td>NETAPP UK LTD</td>\n",
       "      <td>46510,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34380</th>\n",
       "      <td>https://www.oracle.com/uk/a/ocom/docs/oracle-g...</td>\n",
       "      <td>01782505</td>\n",
       "      <td>ORACLE CORPORATION UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35107</th>\n",
       "      <td>https://careers.redcentricplc.com/wp-content/u...</td>\n",
       "      <td>08322856</td>\n",
       "      <td>REDCENTRIC SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35570</th>\n",
       "      <td>https://www.cgi-group.co.uk/sites/default/file...</td>\n",
       "      <td>04373530</td>\n",
       "      <td>SCISYS UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36110</th>\n",
       "      <td>https://www.ssp-worldwide.com/wp-content/uploa...</td>\n",
       "      <td>04234499</td>\n",
       "      <td>SSP LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36445</th>\n",
       "      <td>https://www.synectics-solutions.com/our-thinki...</td>\n",
       "      <td>02685135</td>\n",
       "      <td>SYNECTICS SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n63110,\\n82302</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38570</th>\n",
       "      <td>https://www.allegisglobalsolutions.com/en-gb/l...</td>\n",
       "      <td>03550830</td>\n",
       "      <td>ALLEGIS GLOBAL SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n78109,\\n78200,\\n78300</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38747</th>\n",
       "      <td>https://www.ans.co.uk/policies/</td>\n",
       "      <td>03176761</td>\n",
       "      <td>ANS GROUP LIMITED</td>\n",
       "      <td>61900,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41283</th>\n",
       "      <td>https://www.ensono.com/wp-content/uploads/2022...</td>\n",
       "      <td>03276974</td>\n",
       "      <td>ENSONO LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41407</th>\n",
       "      <td>https://uk.nttdata.com/insights/reports/gender...</td>\n",
       "      <td>07235059</td>\n",
       "      <td>EVERISCONSULTANCY LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n70229</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41435</th>\n",
       "      <td>https://www.excelredstone.com</td>\n",
       "      <td>02027207</td>\n",
       "      <td>EXCELREDSTONE CONVERGED SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42677</th>\n",
       "      <td>https://www.ibm.com/employment/ciceurope/uk-en...</td>\n",
       "      <td>09360752</td>\n",
       "      <td>IBM SERVICES CENTRE UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63120</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44448</th>\n",
       "      <td>NaN</td>\n",
       "      <td>02998329</td>\n",
       "      <td>NETAPP UK LTD</td>\n",
       "      <td>46510,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44883</th>\n",
       "      <td>https://www-sites.oracle.com/uk/corporate/cont...</td>\n",
       "      <td>01782505</td>\n",
       "      <td>ORACLE CORPORATION UK LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45611</th>\n",
       "      <td>https://careers.redcentricplc.com/our-values/</td>\n",
       "      <td>08322856</td>\n",
       "      <td>REDCENTRIC SOLUTIONS LIMITED</td>\n",
       "      <td>62020,\\n62030,\\n62090,\\n63110</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46586</th>\n",
       "      <td>https://www.ssp-worldwide.com/ssp-gender-pay-g...</td>\n",
       "      <td>04234499</td>\n",
       "      <td>SSP LIMITED</td>\n",
       "      <td>62012,\\n62020,\\n62030,\\n62090</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46919</th>\n",
       "      <td>https://www.synectics-solutions.com/our-thinki...</td>\n",
       "      <td>02685135</td>\n",
       "      <td>SYNECTICS SOLUTIONS LIMITED</td>\n",
       "      <td>62030,\\n63110,\\n82302</td>\n",
       "      <td>Tech</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    CompanyLinkToGPGInfo CompanyNumber  \\\n",
       "313    https://www.allegisglobalsolutions.com/en-gb/c...      03550830   \n",
       "314             https://www.allegisgroup.com/en-gb/legal      02876353   \n",
       "472                         https://www.ans.co.uk/about/      03176761   \n",
       "1722   https://www.ccsmedia.com/media/CCS-Media-Our-G...      01693516   \n",
       "2950   https://www.ensono.com/uk/about-us/careers/gen...      03276974   \n",
       "4333   https://cic-uk.eu-gb.mybluemix.net/pages/repor...      09360752   \n",
       "4344                                                 NaN      02758710   \n",
       "4572   https://www.itcinfotech.com/wp-content/uploads...      02777705   \n",
       "4901   https://www.cloud9umbrella.com/modern-slavery-...      08156779   \n",
       "6496              https://www.oracle.com/goto/gpg-report      01782505   \n",
       "7179   http://www.redcentricplc.com/about-us/gender-p...      08322856   \n",
       "8151   http://www.ssp-worldwide.com/wp-content/upload...      04234499   \n",
       "8467                  http://www.synectics-solutions.com      02685135   \n",
       "10590  https://www.allegisgroup.com/-/media/files/all...      02876353   \n",
       "13302  https://www.ensono.com/sites/default/files/Ens...      03276974   \n",
       "13419  https://www.everis.co.uk/newsroom/2019-gender-...      07235059   \n",
       "13444                     https://www.excelredstone.com/      02027207   \n",
       "14724        http://uk.ciceurope.com/pages/reporting2018      09360752   \n",
       "14976  https://www.itcinfotech.com/docs/resources/Gen...      02777705   \n",
       "16504  https://www.netapp.com/us/media/netapp-gender-...      02998329   \n",
       "16915  https://www.oracle.com/a/ocom/docs/oracle-gend...      01782505   \n",
       "17616  https://www.redcentricplc.com/about-us/gender-...      08322856   \n",
       "18093  https://www.scisys.co.uk/who-we-are/csr/gender...      04373530   \n",
       "18616  http://www.ssp-worldwide.com/wp-content/upload...      04234499   \n",
       "18936  https://www.synectics-solutions.com/our-thinki...      02685135   \n",
       "22820  https://www.everis.co.uk/newsroom/2020-gender-...      07235059   \n",
       "23640  https://www.ibm.com/employment/ciceurope/uk-en...      09360752   \n",
       "24820  https://www.netapp.com/pdf.html?item=/media/11...      02998329   \n",
       "25565  https://www.redcentricplc.com/wp-content/uploa...      08322856   \n",
       "25898  https://www.cgi-group.co.uk/sites/default/file...      04373530   \n",
       "26265  https://www.ssp-worldwide.com/about-us/gender-...      04234499   \n",
       "26488  https://www.synectics-solutions.com/our-thinki...      02685135   \n",
       "28017  https://www.allegisglobalsolutions.com/en-gb/a...      03550830   \n",
       "28196  https://www.ans.co.uk/wp-content/uploads/2021/...      03176761   \n",
       "30718  https://www.ensono.com/ensono-gender-pay-gap-r...      03276974   \n",
       "30841  https://www.everis.co.uk/newsroom/2021-gender-...      07235059   \n",
       "32137  https://www.ibm.com/employment/ciceurope/uk-en...      09360752   \n",
       "32150                          https://www.idegroup.com/      02758710   \n",
       "33939  https://www.netapp.com/pdf.html?item=/media/60...      02998329   \n",
       "34380  https://www.oracle.com/uk/a/ocom/docs/oracle-g...      01782505   \n",
       "35107  https://careers.redcentricplc.com/wp-content/u...      08322856   \n",
       "35570  https://www.cgi-group.co.uk/sites/default/file...      04373530   \n",
       "36110  https://www.ssp-worldwide.com/wp-content/uploa...      04234499   \n",
       "36445  https://www.synectics-solutions.com/our-thinki...      02685135   \n",
       "38570  https://www.allegisglobalsolutions.com/en-gb/l...      03550830   \n",
       "38747                    https://www.ans.co.uk/policies/      03176761   \n",
       "41283  https://www.ensono.com/wp-content/uploads/2022...      03276974   \n",
       "41407  https://uk.nttdata.com/insights/reports/gender...      07235059   \n",
       "41435                      https://www.excelredstone.com      02027207   \n",
       "42677  https://www.ibm.com/employment/ciceurope/uk-en...      09360752   \n",
       "44448                                                NaN      02998329   \n",
       "44883  https://www-sites.oracle.com/uk/corporate/cont...      01782505   \n",
       "45611      https://careers.redcentricplc.com/our-values/      08322856   \n",
       "46586  https://www.ssp-worldwide.com/ssp-gender-pay-g...      04234499   \n",
       "46919  https://www.synectics-solutions.com/our-thinki...      02685135   \n",
       "\n",
       "                                     CurrentName  \\\n",
       "313             ALLEGIS GLOBAL SOLUTIONS LIMITED   \n",
       "314                        ALLEGIS GROUP LIMITED   \n",
       "472                            ANS GROUP LIMITED   \n",
       "1722                        CCS BOTTOMCO LIMITED   \n",
       "2950                              ENSONO LIMITED   \n",
       "4333              IBM SERVICES CENTRE UK LIMITED   \n",
       "4344                    IDE GROUP MANAGE LIMITED   \n",
       "4572                        ITC INFOTECH LIMITED   \n",
       "4901                   HAMRAN MANAGEMENT LIMITED   \n",
       "6496               ORACLE CORPORATION UK LIMITED   \n",
       "7179                REDCENTRIC SOLUTIONS LIMITED   \n",
       "8151                                 SSP LIMITED   \n",
       "8467                 SYNECTICS SOLUTIONS LIMITED   \n",
       "10590                      ALLEGIS GROUP LIMITED   \n",
       "13302                             ENSONO LIMITED   \n",
       "13419                  EVERISCONSULTANCY LIMITED   \n",
       "13444  EXCELREDSTONE CONVERGED SOLUTIONS LIMITED   \n",
       "14724             IBM SERVICES CENTRE UK LIMITED   \n",
       "14976                       ITC INFOTECH LIMITED   \n",
       "16504                              NETAPP UK LTD   \n",
       "16915              ORACLE CORPORATION UK LIMITED   \n",
       "17616               REDCENTRIC SOLUTIONS LIMITED   \n",
       "18093                          SCISYS UK LIMITED   \n",
       "18616                                SSP LIMITED   \n",
       "18936                SYNECTICS SOLUTIONS LIMITED   \n",
       "22820                  EVERISCONSULTANCY LIMITED   \n",
       "23640             IBM SERVICES CENTRE UK LIMITED   \n",
       "24820                              NETAPP UK LTD   \n",
       "25565               REDCENTRIC SOLUTIONS LIMITED   \n",
       "25898                          SCISYS UK LIMITED   \n",
       "26265                                SSP LIMITED   \n",
       "26488                SYNECTICS SOLUTIONS LIMITED   \n",
       "28017           ALLEGIS GLOBAL SOLUTIONS LIMITED   \n",
       "28196                          ANS GROUP LIMITED   \n",
       "30718                             ENSONO LIMITED   \n",
       "30841                  EVERISCONSULTANCY LIMITED   \n",
       "32137             IBM SERVICES CENTRE UK LIMITED   \n",
       "32150                   IDE GROUP MANAGE LIMITED   \n",
       "33939                              NETAPP UK LTD   \n",
       "34380              ORACLE CORPORATION UK LIMITED   \n",
       "35107               REDCENTRIC SOLUTIONS LIMITED   \n",
       "35570                          SCISYS UK LIMITED   \n",
       "36110                                SSP LIMITED   \n",
       "36445                SYNECTICS SOLUTIONS LIMITED   \n",
       "38570           ALLEGIS GLOBAL SOLUTIONS LIMITED   \n",
       "38747                          ANS GROUP LIMITED   \n",
       "41283                             ENSONO LIMITED   \n",
       "41407                  EVERISCONSULTANCY LIMITED   \n",
       "41435  EXCELREDSTONE CONVERGED SOLUTIONS LIMITED   \n",
       "42677             IBM SERVICES CENTRE UK LIMITED   \n",
       "44448                              NETAPP UK LTD   \n",
       "44883              ORACLE CORPORATION UK LIMITED   \n",
       "45611               REDCENTRIC SOLUTIONS LIMITED   \n",
       "46586                                SSP LIMITED   \n",
       "46919                SYNECTICS SOLUTIONS LIMITED   \n",
       "\n",
       "                            SicCodes Sector  \n",
       "313    62030,\\n78109,\\n78200,\\n78300   None  \n",
       "314    62030,\\n78109,\\n78200,\\n78300   None  \n",
       "472    61900,\\n62020,\\n62030,\\n62090   Tech  \n",
       "1722                           62030   Tech  \n",
       "2950   62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "4333   62012,\\n62020,\\n62030,\\n63120   Tech  \n",
       "4344                           62030   Tech  \n",
       "4572   62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "4901                           62030   Tech  \n",
       "6496   62012,\\n62020,\\n62030,\\n63110   Tech  \n",
       "7179   62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "8151   62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "8467                   62030,\\n63110   Tech  \n",
       "10590  62030,\\n78109,\\n78200,\\n78300   None  \n",
       "13302  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "13419  62012,\\n62020,\\n62030,\\n70229   Tech  \n",
       "13444          62020,\\n62030,\\n62090   Tech  \n",
       "14724  62012,\\n62020,\\n62030,\\n63120   Tech  \n",
       "14976  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "16504          46510,\\n62030,\\n62090   Tech  \n",
       "16915  62012,\\n62020,\\n62030,\\n63110   Tech  \n",
       "17616  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "18093  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "18616  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "18936                  62030,\\n63110   Tech  \n",
       "22820  62012,\\n62020,\\n62030,\\n70229   Tech  \n",
       "23640  62012,\\n62020,\\n62030,\\n63120   Tech  \n",
       "24820          46510,\\n62030,\\n62090   Tech  \n",
       "25565  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "25898  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "26265  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "26488          62030,\\n63110,\\n82302   Tech  \n",
       "28017  62030,\\n78109,\\n78200,\\n78300   None  \n",
       "28196  61900,\\n62020,\\n62030,\\n62090   Tech  \n",
       "30718  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "30841  62012,\\n62020,\\n62030,\\n70229   Tech  \n",
       "32137  62012,\\n62020,\\n62030,\\n63120   Tech  \n",
       "32150                          62030   Tech  \n",
       "33939          46510,\\n62030,\\n62090   Tech  \n",
       "34380  62012,\\n62020,\\n62030,\\n63110   Tech  \n",
       "35107  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "35570  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "36110  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "36445          62030,\\n63110,\\n82302   Tech  \n",
       "38570  62030,\\n78109,\\n78200,\\n78300   None  \n",
       "38747  61900,\\n62020,\\n62030,\\n62090   Tech  \n",
       "41283  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "41407  62012,\\n62020,\\n62030,\\n70229   Tech  \n",
       "41435          62020,\\n62030,\\n62090   Tech  \n",
       "42677  62012,\\n62020,\\n62030,\\n63120   Tech  \n",
       "44448          46510,\\n62030,\\n62090   Tech  \n",
       "44883  62012,\\n62020,\\n62030,\\n63110   Tech  \n",
       "45611  62020,\\n62030,\\n62090,\\n63110   Tech  \n",
       "46586  62012,\\n62020,\\n62030,\\n62090   Tech  \n",
       "46919          62030,\\n63110,\\n82302   Tech  "
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tech_support = pay_df.loc[pay_df[\"SicCodes\"].str.contains(\"62030\", na=False)][[\"CompanyLinkToGPGInfo\",\n",
    "                                                                               \"CompanyNumber\", \n",
    "                                                                \"CurrentName\",\"SicCodes\", \"Sector\"]].drop_duplicates()\n",
    "\n",
    "#tech_support.to_csv(\"tech_support.csv\")\n",
    "tech_support"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aabe9801",
   "metadata": {},
   "source": [
    "### Clean employername"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1a51cab3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DiffMeanHourlyPercent</th>\n",
       "      <th>DiffMedianHourlyPercent</th>\n",
       "      <th>DiffMeanBonusPercent</th>\n",
       "      <th>DiffMedianBonusPercent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file</th>\n",
       "      <th>SIC_section_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"13\" valign=\"top\">2021 to 2022</th>\n",
       "      <th>Accommodation and food services (I)</th>\n",
       "      <td>8.065885</td>\n",
       "      <td>4.581237</td>\n",
       "      <td>16.730532</td>\n",
       "      <td>2.542297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Administrative activities (N)</th>\n",
       "      <td>9.804222</td>\n",
       "      <td>8.432806</td>\n",
       "      <td>13.688840</td>\n",
       "      <td>-17.991050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arts, entertainment and recreation (R)</th>\n",
       "      <td>22.324107</td>\n",
       "      <td>4.953571</td>\n",
       "      <td>24.597122</td>\n",
       "      <td>12.642446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Construction (F)</th>\n",
       "      <td>20.053169</td>\n",
       "      <td>22.062324</td>\n",
       "      <td>16.675391</td>\n",
       "      <td>-36.842188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education (P)</th>\n",
       "      <td>16.049583</td>\n",
       "      <td>23.590917</td>\n",
       "      <td>17.185397</td>\n",
       "      <td>12.909524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finance and insurance (K)</th>\n",
       "      <td>24.949884</td>\n",
       "      <td>22.209049</td>\n",
       "      <td>36.818029</td>\n",
       "      <td>27.033173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health and social work (Q)</th>\n",
       "      <td>9.910315</td>\n",
       "      <td>5.023561</td>\n",
       "      <td>10.276732</td>\n",
       "      <td>13.022558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Information and communication (J)</th>\n",
       "      <td>17.821158</td>\n",
       "      <td>16.436128</td>\n",
       "      <td>27.239095</td>\n",
       "      <td>7.201852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manufacturing (C)</th>\n",
       "      <td>10.689612</td>\n",
       "      <td>8.451008</td>\n",
       "      <td>21.622801</td>\n",
       "      <td>-7.994535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public administration (O)</th>\n",
       "      <td>6.425502</td>\n",
       "      <td>6.015462</td>\n",
       "      <td>2.542986</td>\n",
       "      <td>-0.479638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Retail (G)</th>\n",
       "      <td>14.039179</td>\n",
       "      <td>8.644728</td>\n",
       "      <td>25.227536</td>\n",
       "      <td>4.384783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scientific and technical activities (M)</th>\n",
       "      <td>18.184746</td>\n",
       "      <td>15.465113</td>\n",
       "      <td>27.293185</td>\n",
       "      <td>10.137084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transportation (H)</th>\n",
       "      <td>9.155467</td>\n",
       "      <td>8.912000</td>\n",
       "      <td>16.738393</td>\n",
       "      <td>-4.234226</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      DiffMeanHourlyPercent  \\\n",
       "file         SIC_section_name                                                 \n",
       "2021 to 2022 Accommodation and food services (I)                   8.065885   \n",
       "             Administrative activities (N)                         9.804222   \n",
       "             Arts, entertainment and recreation (R)               22.324107   \n",
       "             Construction (F)                                     20.053169   \n",
       "             Education (P)                                        16.049583   \n",
       "             Finance and insurance (K)                            24.949884   \n",
       "             Health and social work (Q)                            9.910315   \n",
       "             Information and communication (J)                    17.821158   \n",
       "             Manufacturing (C)                                    10.689612   \n",
       "             Public administration (O)                             6.425502   \n",
       "             Retail (G)                                           14.039179   \n",
       "             Scientific and technical activities (M)              18.184746   \n",
       "             Transportation (H)                                    9.155467   \n",
       "\n",
       "                                                      DiffMedianHourlyPercent  \\\n",
       "file         SIC_section_name                                                   \n",
       "2021 to 2022 Accommodation and food services (I)                     4.581237   \n",
       "             Administrative activities (N)                           8.432806   \n",
       "             Arts, entertainment and recreation (R)                  4.953571   \n",
       "             Construction (F)                                       22.062324   \n",
       "             Education (P)                                          23.590917   \n",
       "             Finance and insurance (K)                              22.209049   \n",
       "             Health and social work (Q)                              5.023561   \n",
       "             Information and communication (J)                      16.436128   \n",
       "             Manufacturing (C)                                       8.451008   \n",
       "             Public administration (O)                               6.015462   \n",
       "             Retail (G)                                              8.644728   \n",
       "             Scientific and technical activities (M)                15.465113   \n",
       "             Transportation (H)                                      8.912000   \n",
       "\n",
       "                                                      DiffMeanBonusPercent  \\\n",
       "file         SIC_section_name                                                \n",
       "2021 to 2022 Accommodation and food services (I)                 16.730532   \n",
       "             Administrative activities (N)                       13.688840   \n",
       "             Arts, entertainment and recreation (R)              24.597122   \n",
       "             Construction (F)                                    16.675391   \n",
       "             Education (P)                                       17.185397   \n",
       "             Finance and insurance (K)                           36.818029   \n",
       "             Health and social work (Q)                          10.276732   \n",
       "             Information and communication (J)                   27.239095   \n",
       "             Manufacturing (C)                                   21.622801   \n",
       "             Public administration (O)                            2.542986   \n",
       "             Retail (G)                                          25.227536   \n",
       "             Scientific and technical activities (M)             27.293185   \n",
       "             Transportation (H)                                  16.738393   \n",
       "\n",
       "                                                      DiffMedianBonusPercent  \n",
       "file         SIC_section_name                                                 \n",
       "2021 to 2022 Accommodation and food services (I)                    2.542297  \n",
       "             Administrative activities (N)                        -17.991050  \n",
       "             Arts, entertainment and recreation (R)                12.642446  \n",
       "             Construction (F)                                     -36.842188  \n",
       "             Education (P)                                         12.909524  \n",
       "             Finance and insurance (K)                             27.033173  \n",
       "             Health and social work (Q)                            13.022558  \n",
       "             Information and communication (J)                      7.201852  \n",
       "             Manufacturing (C)                                     -7.994535  \n",
       "             Public administration (O)                             -0.479638  \n",
       "             Retail (G)                                             4.384783  \n",
       "             Scientific and technical activities (M)               10.137084  \n",
       "             Transportation (H)                                    -4.234226  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_filter = (pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))\n",
    "pivot = pay_df[_filter].groupby([\"file\", \"SIC_section_name\"])[['DiffMeanHourlyPercent','DiffMedianHourlyPercent' ,\n",
    "                                                           'DiffMeanBonusPercent', 'DiffMedianBonusPercent' ]].mean()\n",
    "pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "219755cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>DiffMeanHourlyPercent</th>\n",
       "      <th>DiffMedianHourlyPercent</th>\n",
       "      <th>DiffMeanBonusPercent</th>\n",
       "      <th>DiffMedianBonusPercent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file</th>\n",
       "      <th>SIC_section_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"13\" valign=\"top\">2021 to 2022</th>\n",
       "      <th>Accommodation and food services (I)</th>\n",
       "      <td>469</td>\n",
       "      <td>469</td>\n",
       "      <td>357</td>\n",
       "      <td>357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Administrative activities (N)</th>\n",
       "      <td>1137</td>\n",
       "      <td>1137</td>\n",
       "      <td>905</td>\n",
       "      <td>905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arts, entertainment and recreation (R)</th>\n",
       "      <td>224</td>\n",
       "      <td>224</td>\n",
       "      <td>139</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Construction (F)</th>\n",
       "      <td>284</td>\n",
       "      <td>284</td>\n",
       "      <td>256</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education (P)</th>\n",
       "      <td>1200</td>\n",
       "      <td>1200</td>\n",
       "      <td>315</td>\n",
       "      <td>315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finance and insurance (K)</th>\n",
       "      <td>431</td>\n",
       "      <td>431</td>\n",
       "      <td>416</td>\n",
       "      <td>416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health and social work (Q)</th>\n",
       "      <td>921</td>\n",
       "      <td>921</td>\n",
       "      <td>563</td>\n",
       "      <td>563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Information and communication (J)</th>\n",
       "      <td>501</td>\n",
       "      <td>501</td>\n",
       "      <td>486</td>\n",
       "      <td>486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manufacturing (C)</th>\n",
       "      <td>1290</td>\n",
       "      <td>1290</td>\n",
       "      <td>1171</td>\n",
       "      <td>1171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public administration (O)</th>\n",
       "      <td>498</td>\n",
       "      <td>498</td>\n",
       "      <td>221</td>\n",
       "      <td>221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Retail (G)</th>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>828</td>\n",
       "      <td>828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scientific and technical activities (M)</th>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>631</td>\n",
       "      <td>631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transportation (H)</th>\n",
       "      <td>375</td>\n",
       "      <td>375</td>\n",
       "      <td>336</td>\n",
       "      <td>336</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      DiffMeanHourlyPercent  \\\n",
       "file         SIC_section_name                                                 \n",
       "2021 to 2022 Accommodation and food services (I)                        469   \n",
       "             Administrative activities (N)                             1137   \n",
       "             Arts, entertainment and recreation (R)                     224   \n",
       "             Construction (F)                                           284   \n",
       "             Education (P)                                             1200   \n",
       "             Finance and insurance (K)                                  431   \n",
       "             Health and social work (Q)                                 921   \n",
       "             Information and communication (J)                          501   \n",
       "             Manufacturing (C)                                         1290   \n",
       "             Public administration (O)                                  498   \n",
       "             Retail (G)                                                 901   \n",
       "             Scientific and technical activities (M)                    708   \n",
       "             Transportation (H)                                         375   \n",
       "\n",
       "                                                      DiffMedianHourlyPercent  \\\n",
       "file         SIC_section_name                                                   \n",
       "2021 to 2022 Accommodation and food services (I)                          469   \n",
       "             Administrative activities (N)                               1137   \n",
       "             Arts, entertainment and recreation (R)                       224   \n",
       "             Construction (F)                                             284   \n",
       "             Education (P)                                               1200   \n",
       "             Finance and insurance (K)                                    431   \n",
       "             Health and social work (Q)                                   921   \n",
       "             Information and communication (J)                            501   \n",
       "             Manufacturing (C)                                           1290   \n",
       "             Public administration (O)                                    498   \n",
       "             Retail (G)                                                   901   \n",
       "             Scientific and technical activities (M)                      708   \n",
       "             Transportation (H)                                           375   \n",
       "\n",
       "                                                      DiffMeanBonusPercent  \\\n",
       "file         SIC_section_name                                                \n",
       "2021 to 2022 Accommodation and food services (I)                       357   \n",
       "             Administrative activities (N)                             905   \n",
       "             Arts, entertainment and recreation (R)                    139   \n",
       "             Construction (F)                                          256   \n",
       "             Education (P)                                             315   \n",
       "             Finance and insurance (K)                                 416   \n",
       "             Health and social work (Q)                                563   \n",
       "             Information and communication (J)                         486   \n",
       "             Manufacturing (C)                                        1171   \n",
       "             Public administration (O)                                 221   \n",
       "             Retail (G)                                                828   \n",
       "             Scientific and technical activities (M)                   631   \n",
       "             Transportation (H)                                        336   \n",
       "\n",
       "                                                      DiffMedianBonusPercent  \n",
       "file         SIC_section_name                                                 \n",
       "2021 to 2022 Accommodation and food services (I)                         357  \n",
       "             Administrative activities (N)                               905  \n",
       "             Arts, entertainment and recreation (R)                      139  \n",
       "             Construction (F)                                            256  \n",
       "             Education (P)                                               315  \n",
       "             Finance and insurance (K)                                   416  \n",
       "             Health and social work (Q)                                  563  \n",
       "             Information and communication (J)                           486  \n",
       "             Manufacturing (C)                                          1171  \n",
       "             Public administration (O)                                   221  \n",
       "             Retail (G)                                                  828  \n",
       "             Scientific and technical activities (M)                     631  \n",
       "             Transportation (H)                                          336  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_filter = (pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))\n",
    "pivot = pay_df[_filter].groupby([\"file\", \"SIC_section_name\"])[['DiffMeanHourlyPercent','DiffMedianHourlyPercent' ,\n",
    "                                                           'DiffMeanBonusPercent', 'DiffMedianBonusPercent' ]].count()\n",
    "pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c0fee85b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FemaleLowerQuartile</th>\n",
       "      <th>FemaleLowerMiddleQuartile</th>\n",
       "      <th>FemaleUpperMiddleQuartile</th>\n",
       "      <th>FemaleTopQuartile</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SIC_section_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Health and social work (Q)</th>\n",
       "      <td>77.768681</td>\n",
       "      <td>78.037253</td>\n",
       "      <td>77.337692</td>\n",
       "      <td>72.278571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education (P)</th>\n",
       "      <td>79.766413</td>\n",
       "      <td>75.312098</td>\n",
       "      <td>69.788663</td>\n",
       "      <td>63.589509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public administration (O)</th>\n",
       "      <td>57.384553</td>\n",
       "      <td>56.384959</td>\n",
       "      <td>54.008537</td>\n",
       "      <td>48.978659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accommodation and food services (I)</th>\n",
       "      <td>54.476667</td>\n",
       "      <td>51.524444</td>\n",
       "      <td>49.656222</td>\n",
       "      <td>45.302000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Administrative activities (N)</th>\n",
       "      <td>50.779216</td>\n",
       "      <td>46.686326</td>\n",
       "      <td>42.660073</td>\n",
       "      <td>37.892069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arts, entertainment and recreation (R)</th>\n",
       "      <td>45.900000</td>\n",
       "      <td>44.983886</td>\n",
       "      <td>42.202370</td>\n",
       "      <td>35.267299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Retail (G)</th>\n",
       "      <td>47.181561</td>\n",
       "      <td>45.842986</td>\n",
       "      <td>41.152376</td>\n",
       "      <td>35.249434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scientific and technical activities (M)</th>\n",
       "      <td>53.150860</td>\n",
       "      <td>48.021347</td>\n",
       "      <td>42.424785</td>\n",
       "      <td>34.577364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finance and insurance (K)</th>\n",
       "      <td>57.276102</td>\n",
       "      <td>50.431090</td>\n",
       "      <td>41.544084</td>\n",
       "      <td>30.673782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Information and communication (J)</th>\n",
       "      <td>44.248081</td>\n",
       "      <td>37.031515</td>\n",
       "      <td>30.612323</td>\n",
       "      <td>25.292121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manufacturing (C)</th>\n",
       "      <td>34.277804</td>\n",
       "      <td>26.035387</td>\n",
       "      <td>23.221880</td>\n",
       "      <td>20.807109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transportation (H)</th>\n",
       "      <td>29.332698</td>\n",
       "      <td>23.329973</td>\n",
       "      <td>18.918529</td>\n",
       "      <td>17.335150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Construction (F)</th>\n",
       "      <td>35.153546</td>\n",
       "      <td>21.999291</td>\n",
       "      <td>15.310993</td>\n",
       "      <td>14.095745</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         FemaleLowerQuartile  \\\n",
       "SIC_section_name                                               \n",
       "Health and social work (Q)                         77.768681   \n",
       "Education (P)                                      79.766413   \n",
       "Public administration (O)                          57.384553   \n",
       "Accommodation and food services (I)                54.476667   \n",
       "Administrative activities (N)                      50.779216   \n",
       "Arts, entertainment and recreation (R)             45.900000   \n",
       "Retail (G)                                         47.181561   \n",
       "Scientific and technical activities (M)            53.150860   \n",
       "Finance and insurance (K)                          57.276102   \n",
       "Information and communication (J)                  44.248081   \n",
       "Manufacturing (C)                                  34.277804   \n",
       "Transportation (H)                                 29.332698   \n",
       "Construction (F)                                   35.153546   \n",
       "\n",
       "                                         FemaleLowerMiddleQuartile  \\\n",
       "SIC_section_name                                                     \n",
       "Health and social work (Q)                               78.037253   \n",
       "Education (P)                                            75.312098   \n",
       "Public administration (O)                                56.384959   \n",
       "Accommodation and food services (I)                      51.524444   \n",
       "Administrative activities (N)                            46.686326   \n",
       "Arts, entertainment and recreation (R)                   44.983886   \n",
       "Retail (G)                                               45.842986   \n",
       "Scientific and technical activities (M)                  48.021347   \n",
       "Finance and insurance (K)                                50.431090   \n",
       "Information and communication (J)                        37.031515   \n",
       "Manufacturing (C)                                        26.035387   \n",
       "Transportation (H)                                       23.329973   \n",
       "Construction (F)                                         21.999291   \n",
       "\n",
       "                                         FemaleUpperMiddleQuartile  \\\n",
       "SIC_section_name                                                     \n",
       "Health and social work (Q)                               77.337692   \n",
       "Education (P)                                            69.788663   \n",
       "Public administration (O)                                54.008537   \n",
       "Accommodation and food services (I)                      49.656222   \n",
       "Administrative activities (N)                            42.660073   \n",
       "Arts, entertainment and recreation (R)                   42.202370   \n",
       "Retail (G)                                               41.152376   \n",
       "Scientific and technical activities (M)                  42.424785   \n",
       "Finance and insurance (K)                                41.544084   \n",
       "Information and communication (J)                        30.612323   \n",
       "Manufacturing (C)                                        23.221880   \n",
       "Transportation (H)                                       18.918529   \n",
       "Construction (F)                                         15.310993   \n",
       "\n",
       "                                         FemaleTopQuartile  \n",
       "SIC_section_name                                            \n",
       "Health and social work (Q)                       72.278571  \n",
       "Education (P)                                    63.589509  \n",
       "Public administration (O)                        48.978659  \n",
       "Accommodation and food services (I)              45.302000  \n",
       "Administrative activities (N)                    37.892069  \n",
       "Arts, entertainment and recreation (R)           35.267299  \n",
       "Retail (G)                                       35.249434  \n",
       "Scientific and technical activities (M)          34.577364  \n",
       "Finance and insurance (K)                        30.673782  \n",
       "Information and communication (J)                25.292121  \n",
       "Manufacturing (C)                                20.807109  \n",
       "Transportation (H)                               17.335150  \n",
       "Construction (F)                                 14.095745  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_filter = (pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))\n",
    "pivot = pay_df[_filter].groupby([ \"SIC_section_name\"])[[ 'FemaleLowerQuartile', \n",
    "                                                               'FemaleLowerMiddleQuartile',\n",
    "                                                               'FemaleUpperMiddleQuartile',\n",
    "                                                               'FemaleTopQuartile' ]].mean()\n",
    "pivot = pivot.sort_values(by=\"FemaleTopQuartile\", ascending=False)\n",
    "pivot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c9e60a1",
   "metadata": {},
   "source": [
    "## Proportion of women per pay band by industry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "d532b7c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_filter = (pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))\n",
    "pivot = pay_df[_filter].groupby([ \"SIC_section_name\"])[[ 'FemaleLowerQuartile', \n",
    "                                                               'FemaleLowerMiddleQuartile',\n",
    "                                                               'FemaleUpperMiddleQuartile',\n",
    "                                                               'FemaleTopQuartile' ]].mean()\n",
    "data = pivot.sort_values(by=\"FemaleTopQuartile\", ascending=False)\n",
    "\n",
    "## Charts\n",
    "title_font = font_manager.FontProperties(fname='C:\\\\WINDOWS\\\\Fonts\\\\Lato-Black.ttf')\n",
    "label_font = font_manager.FontProperties(fname='C:\\\\WINDOWS\\\\Fonts\\\\Lato-Regular.ttf')\n",
    "colours = [\"#ef767a\",\"#456990\", \"#56cfe1\"]\n",
    "\n",
    "# =========\n",
    "# Initialise Figure and define layout\n",
    "fig, ax = plt.subplots(figsize=(8,7))\n",
    "fig.set_facecolor(\"#efe9e5\")\n",
    " \n",
    "#make plot area transparent\n",
    "plt.subplots_adjust(left=0.01, bottom=0.08, right=0.9, top=0.90, wspace=None, hspace=None)\n",
    "plt.gca().patch.set_alpha(0) \n",
    "\n",
    "#remove grid\n",
    "for pos in ['right', 'top',  'left']:\n",
    "    ax.spines[pos].set_visible(False)\n",
    "\n",
    "# ===========\n",
    "# plot data                  \n",
    "my_range=range(1,len(data.index)+1)\n",
    "\n",
    "# The horizontal plot is made using the hline function\n",
    "plt.hlines(y=my_range, xmin=data['FemaleLowerQuartile'], xmax=data['FemaleTopQuartile'],linewidth=2, \n",
    "           color='#666666', alpha=1, zorder=2)\n",
    "plt.scatter(data['FemaleTopQuartile'], my_range, s=175, linewidth=1, edgecolors='black', \n",
    "            alpha=1, label='Top Quartile', zorder=3, color=colours[0])\n",
    "plt.scatter(data['FemaleLowerQuartile'], my_range, s=175, linewidth=1, edgecolors='black', \n",
    "            alpha=1 , label='Lower Quartile', zorder=3, color=colours[1])\n",
    "\n",
    "#==========\n",
    "#annotation\n",
    "plt.plot([50, 50], [0,len(data)+0.5],linestyle= (0,(1,1)), linewidth=1.5, color='#777777')\n",
    "\n",
    "for i, values in enumerate(data['FemaleTopQuartile']):\n",
    "    #if data.index[i].isin(['Information and communication (J)',])\n",
    "    plt.text(values -4, my_range[i],'{:,.0f}'.format(values), fontsize = 11, weight = 'regular',  \n",
    "             color='black', va='center', ha='right')\n",
    "for i, values in enumerate(data['FemaleLowerQuartile']):   \n",
    "    plt.text(values +4, my_range[i],'{:,.0f}'.format(values), fontsize = 11, weight = 'regular',  \n",
    "             color='black', va='center', ha='left')\n",
    "\n",
    "# ==========\n",
    "#y-axis\n",
    "plt.tick_params(axis='both', length = 0, color = \"#444444\")\n",
    "plt.gca().set_ylim(ymin=0)\n",
    "plt.yticks(my_range, data.index, fontsize=13, fontproperties=label_font)\n",
    "\n",
    "#x-axis\n",
    "plt.xticks(np.arange(0,110,10), fontfamily='Arial')\n",
    "plt.tick_params(axis='x', labelsize=11)\n",
    "plt.gca().set_xlim(xmin=0, xmax=100)\n",
    "plt.gca().xaxis.set_major_formatter(mpl.ticker.FuncFormatter(lambda x, pos: '{:,.0f}%'.format(x)))\n",
    "\n",
    "# ==========\n",
    "#legend\n",
    "L = ax.legend(ncol=2, frameon=False, loc='upper right',bbox_to_anchor=(1.05,1.08))\n",
    "plt.setp(L.texts, fontfamily=\"Lato\", fontsize=13)\n",
    "\n",
    "# ==========\n",
    "# Title and footer\n",
    "plt.figtext(-0.4,1.05,'Technical and financial sectors have the lowest share of women in the top pay bands',\n",
    "         fontsize = 16, weight = 'bold', fontproperties=title_font, color='black')\n",
    "plt.figtext(-0.4,1, \"Average proportion of women in lower and top pay quarter by industry*, 2021/22 (%)\", \n",
    "            fontproperties=label_font,\n",
    "            fontsize=14, ha='left',  color=\"#111111\", fontfamily=\"Lato\")\n",
    "\n",
    "#footer\n",
    "plt.figtext(-0.4,-0.0, \"*Excludes industries with sample size less than 100\",\n",
    "            fontsize=10, ha='left', color=\"#111111\", fontfamily=\"Lato\")\n",
    "plt.figtext(-0.4,-0.05, \"#TidyTuesday 2022 W26 | Source: UK Government\", fontsize=11,\n",
    "            ha='left', color=\"#111111\", fontfamily=\"Lato\")\n",
    "plt.figtext(0.98,-0.05, \"Design by: Lisa Hornung            \",\n",
    "            fontsize=11, ha='right', color=\"#111111\", fontfamily=\"Lato\")\n",
    "\n",
    "# ==========\n",
    "#save\n",
    "plt.savefig(\"Women_share_top_low_pay_band_by_industry.png\", bbox_inches=\"tight\",pad_inches=0.2)\n",
    "\n",
    "# Show the graph\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72985632",
   "metadata": {},
   "source": [
    "## Median pay difference by industry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "24ee3e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 13 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# =========\n",
    "# Initialise Figure and define layout\n",
    "fig, ax = plt.subplots(figsize=(10,8))\n",
    "fig.set_facecolor(\"#efe9e5\")\n",
    "\n",
    "#data\n",
    "data = pay_df[(pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))]\n",
    "\n",
    "_filter = (pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))\n",
    "mean_data = pay_df[_filter].groupby([\"SIC_section_name\"])[['DiffMedianHourlyPercent' ,\n",
    "                                                    'DiffMedianBonusPercent' ]].mean().sort_values(by=\"DiffMedianHourlyPercent\",\n",
    "                                                                                                    ascending=False)\n",
    "\n",
    "#set colours and font\n",
    "colours = [\"#ef767a\",\"#456990\", \"#56cfe1\"]\n",
    "title_font = font_manager.FontProperties(fname='C:\\\\WINDOWS\\\\Fonts\\\\Lato-Black.ttf')\n",
    "label_font = font_manager.FontProperties(fname='C:\\\\WINDOWS\\\\Fonts\\\\Lato-Regular.ttf')\n",
    "\n",
    "#define arrow style\n",
    "style = \"Simple, tail_width=0.5, head_width=5, head_length=5\"\n",
    "kw = dict(arrowstyle=style, color=\"#333333\")\n",
    "\n",
    "# =======\n",
    "#plot data for each age bracket\n",
    "num=0\n",
    "for i in mean_data.index:\n",
    "    num+=1\n",
    "    plt.subplot(13,1,num)\n",
    "    plt.gca().patch.set_alpha(0)\n",
    "    \n",
    "    g = sns.kdeplot(data[data[\"SIC_section_name\"]==i]['DiffMedianHourlyPercent' ], fill=True, alpha=0.7, color=colours[0])\n",
    "    g = sns.kdeplot(data[data[\"SIC_section_name\"]==i]['DiffMedianHourlyPercent' ], color=\"#555555\", lw=1.5)\n",
    "    \n",
    "    ### Axis\n",
    "    plt.gca().set_xlim(xmin=-80, xmax=80)\n",
    "    plt.gca().set_ylim(ymin=0, ymax=0.07)\n",
    "    \n",
    "    if num < len(pivot):\n",
    "        plt.axis('off')\n",
    "    \n",
    "    else: \n",
    "        \n",
    "        ## Format bottom axis\n",
    "        for pos in [\"top\", \"bottom\", \"right\", \"left\"]:\n",
    "            plt.gca().spines[pos].set_visible(False)\n",
    "        plt.grid(visible=False, axis='both')\n",
    "        plt.gca().get_yaxis().set_visible(False)\n",
    "        plt.gca().set_xlabel(\"\")\n",
    "        plt.xticks([-75, -50, -25, 0, 25, 50, 75], [\"75%\", \"50%\", \"25%\", \"Equal\", \"25%\", \"50%\", \"75%\"])\n",
    "        \n",
    "        ### add arrows    \n",
    "        a1 = mpl.patches.FancyArrowPatch((-40, -0.035), (-50, -0.035),clip_on=False, linewidth=0.5,\n",
    "                                connectionstyle=\"arc3,rad=0\", **kw)\n",
    "        a2 = mpl.patches.FancyArrowPatch((40, -0.035), (50, -0.035),clip_on=False, linewidth=0.5,\n",
    "                                    connectionstyle=\"arc3,rad=0\", **kw)  \n",
    "        #add \n",
    "        for a in [a1,a2]:\n",
    "            plt.gca().add_patch(a)\n",
    "            \n",
    "        ## add annotation\n",
    "        plt.text(-38, -0.035, \"women paid more\", va='center', fontsize=10)\n",
    "        plt.text(38, -0.035, \"men paid more\", va='center', fontsize=10, ha='right')\n",
    "   \n",
    "    ### Mean value line\n",
    "    #get kde values to add line to show average\n",
    "    kde_values = pd.DataFrame(g.get_children()[1].get_path().vertices).rename(columns={0:\"x\", 1: \"y\"})\n",
    "    mean = mean_data[\"DiffMedianHourlyPercent\"][i]\n",
    "    x_pos, y_pos = kde_values[kde_values[\"x\"]>=mean].iloc[0]\n",
    "    plt.plot([mean,mean], [0, y_pos], linewidth=1.5, linestyle='dotted', color = \"#333333\")\n",
    "    \n",
    "    ## annotation for top mean value\n",
    "    if num ==1:\n",
    "        plt.gca().add_patch(mpl.patches.FancyArrowPatch((mean+15, y_pos+0.01), (mean, y_pos+0.002),clip_on=False, linewidth=0.5,\n",
    "                                    connectionstyle=\"arc3,rad=0.3\", **kw))\n",
    "        plt.text(mean+15, y_pos+0.01, \"average pay gap\", va='center')\n",
    "      \n",
    "    ### Title\n",
    "    ymin, ymax = plt.gca().get_ylim()\n",
    "    plt.text(-80,ymax/11, i, fontsize = 13, ha='right', fontproperties=label_font,)\n",
    "\n",
    "fig.subplots_adjust(hspace=-0.6)\n",
    "    \n",
    "# ==========\n",
    "# Title and footer\n",
    "plt.figtext(-0.2,0.94,'Men working in construction, finance and education earn over 22% more than women per hour',\n",
    "         fontsize = 16, weight = 'bold', fontproperties=title_font, color='black')\n",
    "plt.figtext(-0.2,0.89, \"Distribution of companies per median hourly gender pay gap by industry, 2021/22 (% difference)\", \n",
    "            fontproperties=label_font,  fontsize=14, ha='left',  color=\"#111111\", fontfamily=\"Lato\")\n",
    "\n",
    "#footer\n",
    "plt.figtext(-0.2,-0.0, \"*Excludes industries with sample size less than 100\",\n",
    "            fontsize=10, ha='left', color=\"#111111\", fontfamily=\"Lato\")\n",
    "plt.figtext(-0.2,-0.05, \"#TidyTuesday 2022 W26 | Source: UK Government\", fontsize=11,\n",
    "            ha='left', color=\"#111111\", fontfamily=\"Lato\")\n",
    "plt.figtext(0.95,-0.05, \"Design by: Lisa Hornung            \",\n",
    "            fontsize=11, ha='right', color=\"#111111\", fontfamily=\"Lato\")\n",
    "\n",
    "# ==========\n",
    "#save\n",
    "plt.savefig(\"Distribution_median_hourly_pay_gap_by_industry.png\", bbox_inches=\"tight\",pad_inches=0.2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "480d2a3c",
   "metadata": {},
   "source": [
    "## Pay gap versus representation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "9d696746",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_filter = (pay_df[\"file\"] == \"2021 to 2022\") & (~pay_df[\"SIC_section\"].isin([\"S\", \"T\", \"U\", \"D\", \"L\", \"E\"]))\n",
    "data = pay_df[_filter].groupby([ \"SIC_section\"])[['DiffMedianHourlyPercent','FemaleTopQuartile']].mean()\n",
    "\n",
    "# =========\n",
    "# Initialise Figure and define layout\n",
    "fig, ax = plt.subplots(figsize=(12,7))\n",
    "fig.set_facecolor(\"#efe9e5\")\n",
    "ax.set_facecolor(\"#efe9e5\")\n",
    "\n",
    "#data\n",
    "x = data['DiffMedianHourlyPercent']\n",
    "y = data['FemaleTopQuartile']\n",
    "labels = data.index.map(sic_section_names_chart)\n",
    "\n",
    "#plot data\n",
    "plt.scatter(x, y, s=150, linewidth=1, alpha=1, color=colours[1], zorder=2, edgecolors=\"#333333\")\n",
    "plt.scatter(x[10], y[10], s=150, linewidth=1, alpha=1, color=colours[0], zorder=2, edgecolors=\"#333333\")\n",
    "\n",
    "#add labels\n",
    "for i in range(len(data)):\n",
    "    plt.text(x[i]+0.35 ,y[i], labels[i], zorder=2, \n",
    "             fontproperties=label_font, size=12, va='center', color=\"#222222\")\n",
    "\n",
    "    \n",
    "# =======\n",
    "#style graph\n",
    "for pos in [\"top\", \"right\"]:\n",
    "    ax.spines[pos].set_visible(False)\n",
    "ax.tick_params(axis='both', length = 0, color = \"#111111\", labelsize=11)\n",
    "ax.grid(visible=True, axis='both', zorder=1, color = \"#333333\", linestyle=(0,(1,5)))\n",
    "\n",
    "\n",
    "#axis\n",
    "ax.set_ylim(ymin=0, ymax=80)\n",
    "ax.set_xlim(xmin=0, xmax=30)\n",
    "ax.yaxis.set_major_formatter(mpl.ticker.FuncFormatter(lambda x, pos: '{:,.0f}%'.format(x)))\n",
    "ax.xaxis.set_major_formatter(mpl.ticker.FuncFormatter(lambda x, pos: '{:,.0f}%'.format(x)))\n",
    "\n",
    "# Adding and styling axis labels\n",
    "plt.xlabel('Difference in hourly pay (men versus women)', loc='right', size=12, labelpad=12)\n",
    "plt.ylabel('Women\\nin top\\n pay\\nband', loc='top', va='top', size=12,\n",
    "           labelpad=12, rotation=0)\n",
    "\n",
    "\n",
    "### Annotation\n",
    "### add arrows\n",
    "style = \"Simple, tail_width=0.5, head_width=5, head_length=5\"\n",
    "kw = dict(arrowstyle=style, color=\"#333333\")\n",
    "a1 = mpl.patches.FancyArrowPatch((21, 73), (23.6, 65),clip_on=False, linewidth=0.5,\n",
    "                        connectionstyle=\"arc3,rad=-0.3\", **kw)\n",
    "plt.gca().add_patch(a1)\n",
    "plt.text(21, 73, \"65% of women in top pay\\nband, yet men earn 24%\\nmore on average\", va='center', ha='right', fontsize=14, fontproperties=label_font)\n",
    "\n",
    "# ==========\n",
    "# Title and footer\n",
    "plt.figtext(0.02,1,'Education has the worst gender pay gap despite more women in top pay bands',\n",
    "         fontsize = 16, weight = 'bold', fontproperties=title_font, color='black')\n",
    "plt.figtext(0.02,0.95, \"Average hourly pay gap versus proportion of women in top pay bands by industry, 2021/22\", \n",
    "            fontproperties=label_font,  fontsize=14, ha='left',  color=\"#111111\", fontfamily=\"Lato\")\n",
    "\n",
    "#footer\n",
    "plt.figtext(0.02,0, \"#TidyTuesday 2022 W26 | Source: UK Government\", fontsize=11,\n",
    "            ha='left', color=\"#111111\", fontfamily=\"Lato\")\n",
    "plt.figtext(0.95,0, \"Design by: Lisa Hornung            \",\n",
    "            fontsize=11, ha='right', color=\"#111111\", fontfamily=\"Lato\")\n",
    "\n",
    "# ==========\n",
    "#save\n",
    "plt.savefig(\"Median_hourly_pay_gap_versus_women_top_pay_band_by_industry.png\", bbox_inches=\"tight\",pad_inches=0.2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25886adc",
   "metadata": {},
   "source": [
    "# Tech vs charities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "a58dd91e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_coords_for_beeswarm(df, values):\n",
    "    df = df.sort_values(by=values).reset_index(drop=True)\n",
    "    #df[\"x\"] = round(df[values] * 2) / 2\n",
    "    df[\"x\"] = [math.floor(x) for x in df[values]]\n",
    "    df['y_start'] = (df[\"x\"].groupby(df[\"x\"]).transform('count') - 1)/2 *-1\n",
    "    y_value = []\n",
    "    for i in range(len(df[\"x\"])):\n",
    "        if i == 0:\n",
    "            num = df[\"y_start\"][i]\n",
    "        elif df[\"x\"][i] == df[\"x\"][i-1]:\n",
    "            num+=1\n",
    "        else:\n",
    "            num = df[\"y_start\"][i]\n",
    "        y_value.append(num)\n",
    "    df[\"y\"] = y_value\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "975e424a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CompanyNumber</th>\n",
       "      <th>NiceName</th>\n",
       "      <th>DiffMedianHourlyPercent</th>\n",
       "      <th>EmployerSize</th>\n",
       "      <th>x</th>\n",
       "      <th>y_start</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>07795137</td>\n",
       "      <td>Cooper Parry Group Limited</td>\n",
       "      <td>-19.4</td>\n",
       "      <td>250 to 499</td>\n",
       "      <td>-20</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01459419</td>\n",
       "      <td>Flooid Limited</td>\n",
       "      <td>-16.0</td>\n",
       "      <td>Less than 250</td>\n",
       "      <td>-16</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02542980</td>\n",
       "      <td>Fdm Group Limited</td>\n",
       "      <td>-9.6</td>\n",
       "      <td>5000 to 19,999</td>\n",
       "      <td>-10</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SC077144</td>\n",
       "      <td>Intelligent Office Uk Limited</td>\n",
       "      <td>-8.2</td>\n",
       "      <td>500 to 999</td>\n",
       "      <td>-9</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>08933499</td>\n",
       "      <td>Oh Goodlord Ltd</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>Less than 250</td>\n",
       "      <td>-7</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>-0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>01870679</td>\n",
       "      <td>Broadridge Financial Solutions Limited</td>\n",
       "      <td>40.1</td>\n",
       "      <td>500 to 999</td>\n",
       "      <td>40</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>00968498</td>\n",
       "      <td>Nec Software Solutions Uk Limited</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1000 to 4999</td>\n",
       "      <td>42</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>-0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>02348923</td>\n",
       "      <td>Acora Limited</td>\n",
       "      <td>42.4</td>\n",
       "      <td>250 to 499</td>\n",
       "      <td>42</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>04570027</td>\n",
       "      <td>Fortinet Uk Limited</td>\n",
       "      <td>47.7</td>\n",
       "      <td>250 to 499</td>\n",
       "      <td>47</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>02998329</td>\n",
       "      <td>Netapp Uk Ltd</td>\n",
       "      <td>48.0</td>\n",
       "      <td>250 to 499</td>\n",
       "      <td>48</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    CompanyNumber                                NiceName  \\\n",
       "0        07795137              Cooper Parry Group Limited   \n",
       "1        01459419                          Flooid Limited   \n",
       "2        02542980                       Fdm Group Limited   \n",
       "3        SC077144           Intelligent Office Uk Limited   \n",
       "4        08933499                         Oh Goodlord Ltd   \n",
       "..            ...                                     ...   \n",
       "220      01870679  Broadridge Financial Solutions Limited   \n",
       "221      00968498       Nec Software Solutions Uk Limited   \n",
       "222      02348923                           Acora Limited   \n",
       "223      04570027                     Fortinet Uk Limited   \n",
       "224      02998329                           Netapp Uk Ltd   \n",
       "\n",
       "     DiffMedianHourlyPercent    EmployerSize   x  y_start    y  \n",
       "0                      -19.4      250 to 499 -20     -0.0 -0.0  \n",
       "1                      -16.0   Less than 250 -16     -0.0 -0.0  \n",
       "2                       -9.6  5000 to 19,999 -10     -0.0 -0.0  \n",
       "3                       -8.2      500 to 999  -9     -0.0 -0.0  \n",
       "4                       -7.0   Less than 250  -7     -0.5 -0.5  \n",
       "..                       ...             ...  ..      ...  ...  \n",
       "220                     40.1      500 to 999  40     -0.0 -0.0  \n",
       "221                     42.0    1000 to 4999  42     -0.5 -0.5  \n",
       "222                     42.4      250 to 499  42     -0.5  0.5  \n",
       "223                     47.7      250 to 499  47     -0.0 -0.0  \n",
       "224                     48.0      250 to 499  48     -0.0 -0.0  \n",
       "\n",
       "[225 rows x 7 columns]"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_filter = (pay_df[\"Sector\"]==\"Tech\") & (pay_df[\"file\"] == \"2021 to 2022\")\n",
    "\n",
    "table = pay_df[_filter][['CompanyNumber', 'NiceName', 'DiffMedianHourlyPercent', \"EmployerSize\"]]\n",
    "\n",
    "#get x and y values for beeswarm plot\n",
    "table = get_coords_for_beeswarm(table, 'DiffMedianHourlyPercent' )\n",
    "\n",
    "table.to_csv(\"tech_companies_gender_pay_gap_2020-21.csv\")\n",
    "\n",
    "table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0bae1dd",
   "metadata": {},
   "source": [
    "### Gender pay gap in Tech companies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "f45674de",
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_axis():\n",
    "    plt.gca().set_facecolor(\"#efe9e5\")\n",
    "    for pos in [\"top\", \"right\", \"bottom\", \"left\"]:\n",
    "        plt.gca().spines[pos].set_visible(False)\n",
    "    plt.gca().tick_params(axis='both', length = 0, color = \"#111111\", labelsize=10)\n",
    "    #plt.gca().grid(visible=True, axis='x', zorder=1, color = \"#333333\", linestyle=(0,(1,5)))\n",
    "    plt.grid(visible=False, axis='both')\n",
    "    plt.gca().get_yaxis().set_visible(False)\n",
    "    plt.gca().set_xlabel(\"\")\n",
    "    plt.gca().set_xlim(xmin=-25, xmax=50)\n",
    "    plt.gca().set_ylim(ymin=-10, ymax=10)\n",
    "    plt.gca().set_xticks([ -25, 0, 25, 50], [ \"25%\", \"Equal\",\n",
    "                                                       \"25%\", \"50%\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "id": "b02280cc",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'str' object has no attribute 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32mC:\\Users\\LISA~1.HOR\\AppData\\Local\\Temp/ipykernel_7636/671963022.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     16\u001b[0m \u001b[1;31m#add highlights\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtech_gap\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 18\u001b[1;33m     \u001b[1;32mif\u001b[0m \u001b[0mtech_gap\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"NiceName\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m \u001b[1;34m\"Fortinet Uk Limited\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"Netapp Uk Ltd\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"Rightmove Group Limited\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     19\u001b[0m         \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtech_gap\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"x\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtech_gap\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"y\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0ms\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m20\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcolours\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0medgecolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'black'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     20\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'str' object has no attribute 'str'"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colours = [\"#ef767a\",\"#456990\", \"#56cfe1\"]\n",
    "\n",
    "# =========\n",
    "# Initialise Figure and define layout\n",
    "fig, ax = plt.subplots(figsize=(15,4))\n",
    "fig.set_facecolor(\"#efe9e5\")\n",
    "\n",
    "## PLOT 1\n",
    "#Tech companies\n",
    "tech_gap = pay_df[(pay_df[\"Sector\"]==\"Tech\") & (pay_df[\"file\"] == \"2021 to 2022\")][['CompanyNumber', 'NiceName', 'DiffMedianHourlyPercent']]\n",
    "tech_gap = get_coords_for_beeswarm(tech_gap, 'DiffMedianHourlyPercent' )\n",
    "\n",
    "plt.scatter(tech_gap[\"x\"], tech_gap[\"y\"], s=20, color=colours[0], alpha=1)\n",
    "format_axis()\n",
    "\n",
    "#add highlights\n",
    "for i in range(len(tech_gap)):\n",
    "    \n",
    "    if tech_gap[\"NiceName\"][i].str.isin([ \"Fortinet Uk Limited\", \"Netapp Uk Ltd\", \"Rightmove Group Limited\"]):\n",
    "        plt.scatter(tech_gap[\"x\"][i], tech_gap[\"y\"][i], s=20, color=colours[0], alpha=1, edgecolor='black')\n",
    "\n",
    "## add annotation\n",
    "plt.text(-20, -13, \"women paid more\", va='center', fontsize=12)\n",
    "plt.text(20, -13, \"men paid more\", va='center', fontsize=12, ha='right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "64417f78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzcAAABwCAYAAAAjZI6TAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAanklEQVR4nO3de3RV5Z3G8SfJSWJVBAQ1CV7DRUCqECyK3AwiGByn4gVEGNSqrba1jlatUhkXo1OtdWBZq7bVaR1HsYgXHB0D4RKsIBoRU4eLogRBCOEOC1ByOWT+SM2Qczbkzb69Oznfz1quZTb77P3b+33PTt6z9/uctF1bNtULAAAAAFq5dNsFAAAAAIAfGNwAAAAAaBMY3AAAAABoExjcAAAAAGgTGNwAAAAAaBNiNnbatVcfnXrKKTZ2DQAAAKAV2PDVV1q7ekWLXmNlcHPqKaeotKTYxq4BAAAAtAKFI4ta/BorgxsAAPywumKX1q7fo66ntVev/I62ywEAWMacGwBAq7S6YpdmFX+hDz7ZolnFX2h1xS7bJQEALGNwAwBoldau36PauoOSpNq6g1q7fo/ligAAtjG4AQC0Sl1Pa6/MWMOvscxYurqe1t5yRQAA25hzAwBolXrld9TVRd2YcwMAaMTgBgDQavXK78igBgDQiMENgJS2rrJGG6pqdGpOls7Iy7JdDtAiUU6LK1+1UavWbFbvHrnq2/tk2+VYF+W2AtoS5twASFnrKms09/29+t+11Zr7/l6tq6yxXRJgLMppceWrNurZGYu1aOkaPTtjscpXbbRdklVRbiugrWFwAyBlbaiqUV284f/r4g0/A61FlNPiVq3ZrJrahjdXTW1cq9ZstlyRXVFuK6CtYXADIGWdmpOlWEbD/8cyGn4GWosop8X17pGrrMyGN1dWZoZ698i1XJFdUW4roK1hzg2AlHVGXpZGnd+OOTdolaKcFte398m66drBzLn5uyi3FdDWeB7cbNy0Sbf+9HZt3bZN6enpum7iBN3yw5v8qA0AAndGHoMatF5RTovr2/vklB/UHCrKbQW0JZ4HN7FYTA9NfUDnnP1d7d23T4UXX6ILhw1VzzN7+FEfACBEttLjypavUfmKCvXtk68BBT0ck6US15GcE6hspFKZ7tNLbVFJ2/KSgkaCmn9M+kNU+gwQprRdWzbV+7nBayfdoJtvvEGFw4Yedp3CkUUqLSn2c7cAAI++TY+rizfMQRp1frtQBjhly9do2tOvq7qmVtlZmbp27KUqX/ONausOKjOWrquLumnv7m1N1rnz1jFq1+EEzSr+osl6kpKWBf1H3bdJWM3t03Q9L/sI2rcpaDW1cWVlZuimawcbD1K8vBZNmfSHqPQZwAs3YwZfAwU2bPhKn6xYof4F/ZL+7bnnX1DhyCIVjizS9h07/NwtAMAHttLjyldUqLqmVpJUXVOrVWt3JCVLJa5TvqLCMYHKRiqV6T691BaVtC0vKWgkqPnHpD9Epc8AYfNtcLNv/35NuvFmPfzgVB3Xrl3Sv18/aaJKS4pVWlKszp06+bVbAIBPbKXH9e2Tr+ysTElSdlamenftlJQslbhO3z75jglUNlKpTPfppbaopG15SUEjQc0/Jv0hKn0GCJsvj6XV1tbqmonXaXjhMP3klh81uz6PpQFANDHnxh3m3AT/WjTFnBukAjdjBs+Dm/r6et162+3q2KGDHn7oX41ew+AGAAAAwJG4GTN4Tkt7v+xDzZz1qnr36qUhwy+WJE2ZfK9GjrjI66YBIHB8sgnbvPRBp7tZbtZpyXqmgr6zYHonz0nlzkxt3Z2pEzvUKu/42hbt1y2uNU1xFw9B8T0tzQR3bgBEAWlCsM1LH0xMmbvz1jFJgxKTdVqynp/H5fexO6XnOW2vcmemyj5vp/jBNGWk12tA972BD3C41jRFch5MWU9LA4DWhDQh2OalDzolyLlZpyXrmQo6zcs0Pc/J1t2Zih9MkyTFD6Zp6+5M8wNziWtNUyTnIUgMbgCkLNKEYJuXPuiUIOdmnZasZyroNC/T9DwnJ3aoVUZ6w0MrGen1OrFD8I+lca1piuQ8BInH0gCkNJ6Dh23MuWHOTSpizg1MWElLc4PBDQAAAIAjYc4NAAAAgJTlOQoaANB2mH6Jp99fRpm4zGkdp8dYwvgSz8TtOZ0j0zpMazM9VpN6/eZl+zYeRQp6n2GcD7d9iUfhkIp4LA0AIKlhYDP3/b2qi0uxDGnU+e0cBzheYm2dXiupybKB/XK09OOqJutUH9ifFB2bfdQxzW7La+RuYr0XDuyqVV/WNzlHBw7sN6rDtDanmFynY3V6bdCRw162byP+N+h9hnE+TN4zfkdtA1HBY2kAANc2VNWoriGdVXXxhp+deIm1dXpt4rLPKnYlreMUHWuyLa+Ru4nbW7epOukcmdZhWpvpsZrU63fksJft24j/DXqfYZwPt32J+GmkKgY3AABJ0qk5WYo1pLMqltHwsxMvsbZOr01cdmZ+x6R1nKJjTbblNXI3cXtndMlOOkemdZjWZnqsJvX6HTnsZfs24n+D3mcY58NtXyJ+GqmKx9IAAI2Yc9N8vcy5Yc7NoZhzAwSHKGgAAAAAbYKbMQNpaQBcs/FFeH7z8qV/bj8VDfrOgtMyL3cCUonpnSs/Bf3Jfxh3ixYvLVfZ8pUaUHCWBg/sK8nsS0G93I3y+86YCS/1erlLEzQb+7T1JZ5c99o+7twAcKVyZ6bKPm+n+ME0ZaTXa0D3va1ugGOaJuR0rHt2b3WVROR3gpFJklJBr3aas7DcVfpWKjFNi/NT0Glbptv3ktC2eGm5Hnjkj6qurlF2dpam3vtDZWUfrWlPv67qmlplZ2XqzlvHJA1wTGszTQtzWmZ6rCZ/XHup1yntzzQZLej3pY192kjOk0iQa41ISwMQmq27MxU/mCZJih9M09bdmZYrajnTNCGnY3WbRBR0mpdTktInqze5Tt9KJaZpcX4KOm0rjIS2suUrVV3dcK6qq2tUtnylyldUqLqm4cOO6ppala+ocF1bGGl0JrzU6yUZLWg29mkjOU8iQS5VMLgB4MqJHWqVkd5w4zcjvV4ndmhdd20k8zQhp2N1m0QUdJqXU5LS2b26uE7fSiWmaXF+CjptK4yEtgEFZyk7u+FcZWdnaUDBWerbJ1/ZWQ0feGRnZapvn3zXtYWRRmfCS71ektGCZmOfNpLzJBLkUgWPpQFwjTk3zLlpa5hzw5ybI2HOjX+YcwMT1tLS5i8s1X33/4vi8YP6pwnjdcfPfnrE9RncAAAAADgSK2lp8Xhcd9/7S73+8kvKy8vV8FGjVTRqpHqe6fwpDaIpSp9k2PjkNCqcPv00ZfopWOL5Nfl0VfLWR5za1GlZ4jHY6pd+7te0P9v6DpdETtt36iOmn9Sbbi9xmdM6TufIaZlpHW7PidO2TPu46fvN9PhN6nW7jpft26rNy/bcvt+83IEI+k6Ql9+nft/xi/J3HHl5v5nw+5oUFTZ+R5nwfOem7MNl+vVj0/TqzBmSpGmPPyFJuvP22w77Gu7cREuU0kNspBVFhVPikOkAxzR5JvH8djmuSi/OfOuIiUaStz7i1KaSkpbt2b21yTGMHtFfy1buDr1f+vl+MO3PpklVklkalFtOx75397ak1Kua6q+N0rHadTjBaHuSmiy7bNQAvTm3rMk6WUcdnXSOJCUtqznwtVEdpuct8ZwM7JejpR9XNdnWUUcdY9THt1V92WyCmNTwh1Diek7H7zZty0sfD/q1YaQJeklkS3ytl9SvoNPXvPw+9TtlzzQtzk+mbePl/WbCafterklR4fY901JW0tI2V1WpS15e4895ebnaXFWVtN5zz7+gwpFFKhxZpO07dnjdLXwUpfQQG2lFUeGUOGTKNHkm8fx+9LfmE40kb33EqU2dliUew6drd1rpl36+H0z7s2lSVdDvVaftO6VemaZjmW4vcVnZ8jVJ6zidI6dlpnW4PSefVexK2pZpHzdJEJPkuJ6faVt+ng+/XxtGmqDpeiav9ZL6FXT6mpffp36n7NlIRzPdp5f3mwm/r0lRYeN3lCnPg5v6+uQbP2lKS1p2/aSJKi0pVmlJsTp36uR1t/BRlNJDbKQVRYVT4pAp0+SZxPPb/5zmE40kb33EqU2dliUeQ8+ux1vpl36+H0z7s2lSVdDvVaftO6VemaZjmW4vcdmAgh5J6zidI6dlpnW4PSdn5ndM2pZpHzdJEJPkuJ6faVt+ng+/XxtGmqDpeiav9ZL6FXT6mpffp36n7NlIRzPdp5f3mwm/r0lRYeN3lCkeS4OkaDwj+S3m3DDnhjk3zLlhzg1zbphzc+T1mHPTPObcBCuM31FW0tLq6up07sAheuOVmcrNzdHwUaP1zNNPqlfPM30tFAAAAEDqsJKWFovF9OjDD+nKa65VPH5QE8aPO+LABkDbYet7CvxkerfMz0/ewvhkOrHeqHySGnU2Pk01vZvjxM87IV76iNvvyPFy59jkDmBLtmfCdPumdxn9rM0LG9eCtnBnHtHEl3gCcMVLSlBUmCbU+Zl2E0YaVGIi2bVjL1X5mm+spxdFnY3kSKe+ZTrA8TN9zG0il2SemJW4X9NjN03xk+R6eybtbFqv0/mQkpP93Kbd+c3GtdxWSmuU0mFhxkpaGoDUZCP9xm+mCXV+pt2EkQaVWO+qtTsikV4UdTaSfkwT1Jz4mT7mJeHKNDHL7bG7Td3zO/3RdPumyX5+1uaFjWuBrVStqKR5IVgMbgC4YiP9xm+mCXV+pt2EkQaVWG/vrp0ikV4UdTaSfkwT1Jz4mT7mJeHKNDHL7bG7Td3zO/3RdPumyX5+1uaFjWuBrVStqKR5IVg8lgbAtbYwZ4M5N627/fzGnBvm3BwJc278w5wbmLCSluYGgxsAAAAAR2IlLQ0A0HaY3sny8p1MJncITO8iONXh96fQJt/B4+U7ftyeI9N6/WbrO3LcCnqfQd95k9zfCQq6LwBRxJ0bAIAk8/Q40/WcmKRyjR7RX8tW7m42uWvfnu1JdRzbvrOvyU+JCVmXjRqgN+eWNZvS5ZSm55TwZZrmZZpc5iV9zYSXtCkbSVVB7zPotDvJffpa0H0BCANpaQAA10zT40zXc2KSyvXp2p1GyV1Odfid/JSYkFW2fI1RSpdpwpfbc3S44/KSvmbCS9qUjaSqoPcZdNqd5D59Lei+AEQVgxsAgCTz9DjT9ZyYpHL17Hq8UXKXUx1+Jz8lJmQNKOhhlNJlmvDl9hwd7ri8pK+Z8JI2ZSOpKuh9Bp12J7lPXwu6LwBRxWNpAIBGzLlJxpyb5msL47VuMeeGOTdovUhLAwAAANAmMOcGAAAAQMoiChpASuML3WCbl8foTB4P9PJFnF6YbM/L+8/pkauoPLrnhGtNU5wPBIXH0gCkLBvRtMChnGJ+TQcWJpHcptv3Uofb4/Ly/nOKOc466uhIxGU74VrTFOcDpngsDQBawEY0LXAoL9HVJpHcptv3O0LbZHte3n9OMcdRict2wrWmKc4HgsTgBkDKshFNCxzKS3S1SSS36fb9jtA22Z6X959TzHFU4rKdcK1pivOBIPFYGoCUxnPfsI05N8y5SUWcD5gIPQp6ytQHNbdknjIzs3TG6afpycenqX375kffDG4AAAAAHEnoc24Khw3Ve+8s1JJF89W1a76m/fZ3XjYHALBsdcUuvVX6pVZX7Ap1v+WrNmrG7A9VvmrjYetwWpb4Oqnhbsa0J1/U4qXl1ur3up4TW23jZx1ejh9Nraus0TvL92ldZc1h14lKnwHC5NtjaW+9Xaw33vwfPfN08wMc7twAQPTYSjBKTNYaPaK/lq3c3aQOSUm1VR/Yn5SOtW/P9mYTxIKuP4hEsqikS3mpw+9EtlS2rrJGc9/fq7q4FMuQRp3fTmfkZTVZJyp9BvDCalraCzP+ohEXFR723597/gUVjixS4cgibd+xw6/dAgB8YivBKDHl6tO1O5PqcKrNKR3LJEEs6PqDSCSLSrqUlzr8TmRLZRuqalTXcCpVF2/4OVFU+gwQtmYHN5dfNU4Dhw5P+u/t4rmN6zw2/XHFYjGNvfKKw27n+kkTVVpSrNKSYnXu1Mmf6gEAvrGVYJSYctWz6/FJdTjV5pSOZZIgFnT9QSSSRSVdyksdfieypbJTc7IUaziVimU0/JwoKn0GCJvnx9Jemvmy/vyf/6XZr7yso4/+jtFreCwNAKLJVoJRYsqVUx1Oy5zSsUwSxIKu3+t6TqKSLuWlDr8T2VLZusoabaiq0ak5WUmPpH0rKn0GcCv0tLT5C0t1/wNT9dbrr6pzZ/O7MQxuAAAAAByJmzFDzMsO77nvflXXVGvM2GskSef2L9D03/zayyYBIFR8sonWLMp3QqJcmw1ca4BweBrcLP9giV91AEDoDk0TWr5qG2lCaFUOTR97b9naSKWPRbk2G7jWAOHxLS0NAFob0oTQmkU5fSzKtdnAtQYID4MbACmLNCG0ZlFOH4tybTZwrQHC4+mxNABozXrld9TVRd14Dh6tUt/eJ+umawdHcl5LlGuzgWsNEB4GNwBSWq/8jvyhgVarb++TIztwiHJtNnCtAcLB4AYA0GqVLV+j8hUV6tsnXwMKetguBwBgGXNuAACtUtnyNZr29OsqXrBM055+XWXL19guCQBgGYMbAECrVL6iQtU1tZKk6ppala+osFwRAMA2BjcAgFapb598ZWdlSpKyszLVt0++5YoAALYx5wYA0CoNKOihO28dw5wbAEAjBjcAgFZrQEEPBjUAgEZWBjeff/6FCkcW2dg1DrF9xw517tTJdhkpjTaIBtohGmgH+2iDaKAdooF2sO/zz79o8WusDG66d++m0pJiG7vGIQpHFtEOltEG0UA7RAPtYB9tEA20QzTQDva5uRlCoAAAAACANoHBDQAAAIA2wcrg5rqJE2zsFgloB/tog2igHaKBdrCPNogG2iEaaAf73LRB2q4tm+oDqAUAAAAAQsVjaQAAAADaBAY3AAAAANqE0AY3//bIoxp04QgNGX6xrhg7Xpurqhr/bdrjT6jgvEH63gVDtKB0UVglpaQpUx/UgEFDNejCEZp4/Y3as2dP47/RDuGZ/d9vauDQQh2fc7I+Lv9bk3+jHcIzf2GpvnfBEBWcN0jTf/s72+WkjJ/efqe69z5bA4cOb1y2a9cujbn6GvU/f5DGXH2Ndu/eba/AFLFx0yZdNuYqnTd4mAYOLdTv//isJNoiTAcOHNBFoy7V4MIRGji0UA8/+pgk2sCWeDyuoReN1LgJkyTRDjacfe55umDYRRoy/OLGGOiWtkNog5vbfnKrliyar3cXztOoi0fo0X+fLkn69LM1em32G1r614V65aUXddcvJisej4dVVsopHDZU772zUEsWzVfXrvma9vc/6GiHcPXq2VPP/+kZXTDw/CbLaYfwxONx3X3vLzVrxgt6/91Svfr6bH362RrbZaWE8deM1St/ebHJsulPPKmhQwbro/eXaOiQwZr+xJOWqksdsVhMD019QB8sfkclb7+pZ//8nD79bA1tEaLs7Gy98drLWlw6X39dUKIFCxfpw2Uf0QaW/P6ZZ9Wje/fGn2kHO958bZbeXTiv8TuGWtoOoQ1ujmvXrvH/93/9tdLS0iRJb8+Zqysu/76ys7N12mmnKv+M0/XR8o/DKivlDL9wmGKxhu9u/V7/AlVWbpZEO4TtzB7d1b1bt6TltEN4Plr+sfLPOF2nn36asrKydMXl39fbc+baLislDBp4vjp26NBkWfGcuRo/7mpJ0vhxV+vt4jkWKkstOSedpHPO/q4kqd2xx6pH9+7aXFVFW4QoLS1Nxx5zjCSptrZOtXW1SktLow0s2FRZqZJ5CzRpwvjGZbRDNLS0HUKdc/Pgrx7RWf3O1axXX9fke+6WJG2uqlKXLnmN6+Tl5jZ5ZA3BeWHGXzTiokJJtENU0A7h2VxVpS55h5zrPM61TVu3bVfOSSdJavije9v2HZYrSi0bNnylT1asUP+CfrRFyOLxuIYMv1g9zjpbFw4bqnP7F9AGFkye8oCm/sv9Sk///z+NaYfwpSlNV4wbrwsvvkTPPf+CpJa3Q8zPgi6/apy2bN2WtHzKfb/Q6KJRmjL5Xk2ZfK+mPf6EnvnTn3XfPXepvj45ifrbuzpwp7l2kKTHpj+uWCymsVdeIUm0QwBM2iER7RAex3MtzjVSz779+zXpxpv18INTmzxlgXBkZGTo3YXztGfPHk28/katWv2p7ZJSzpySeercubP6nnO2Fi95z3Y5KW3OW7OVm5Ojbdu2a8zYa9S9e/JTLs3xdXAz+5WZRutddcUYjZswSffdc5fycnO1aVNl479Vbt7cODqDO821w0szX1bJvPma/crLjX840w7+M30/HIp2CE9ebq42VR5yris3KyeHc23LiSd0VtWWLco56SRVbdmiEzp3sl1SSqitrdV1P7hZV185RpddOloSbWFL+/btNXjQBVpQuog2CNkHZcs0Z26J5i1YqOoD1dq7b69++OPbaAcLcnNyJEknnNBZ/zC6SMs/Lm9xO4T2WNraiorG/58zt0Q9uneVJBWNGqnXZr+h6upqrV+/QWsr1ql/Qb+wyko58xeW6vHfPaUZzz+no4/+TuNy2iEaaIfwFPTrq7UV67R+/QbV1NTotdlvqGjUSNtlpaxLRo3USzNnSZJemjlLRZc4392Ef+rr63XbHT9Xj+7d9JNbftS4nLYIz/btOxpTS7/55hst+uu76t6tK20Qsgfuv08ryz/SJ8s+0H/84SkNGTRIf3zqCdohZPv3f629+/Y1/v/CRe+oV88zW9wOabu2bEp+NiMAk35wsz7/Yq3S09N1ysldNO03jygvN1dSwyNSL740U7FYhn714FRdfNHwZrYGtwrOG6Tqmmod37GjJOnc/gWa/ptfS6IdwvTW28X6xeT7tX3HTrU/7jh9t89ZenXmDEm0Q5hK5i/Q5CkPKB4/qAnjx+muO263XVJKuPFHP9aS95Zqx86dOvGEzrr37rt0adEo3XDzLdq4aZNO7tJFzz37B3X8+3UKwVj6QZlG/+MY9e7VS+npDXfxp0y+V+cW9KMtQrJi5Sr9+Gf/rHj8oA4ePKgx379M9/z8Du3cuZM2sGTxkvf0xFO/18wXn6cdQvbll+s18YYbJTXMRbtyzOW6647bW9wOoQ1uAAAAACBIoaalAQAAAEBQGNwAAAAAaBMY3AAAAABoExjcAAAAAGgTGNwAAAAAaBMY3AAAAABoExjcAAAAAGgT/g9ELZoi5H0+3wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x108 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colours = {'Not Provided': \"#9CB0F8\", 'Less than 250': \"#8394D2\", '250 to 499' : \"#6C7AAE\" , '500 to 999': \"#55608A\",\n",
    "           '1000 to 4999': \"#404869\", '5000 to 19,999':  \"#2B3149\",\n",
    "         '20,000 or more': \"#181B2B\" }\n",
    " \n",
    "tech_gap = table[['NiceName', \"x\", \"y\", \"EmployerSize\"]]\n",
    "\n",
    "\n",
    "# =========\n",
    "# Initialise Figure and define layout\n",
    "fig, ax = plt.subplots(figsize=(14,1.5))\n",
    "fig.set_facecolor(\"#efe9e5\")\n",
    "ax.set_facecolor(\"#efe9e5\")\n",
    "\n",
    "#for i in range(len)\n",
    "for i in range(len(tech_gap)):\n",
    "    plt.scatter(tech_gap[\"x\"][i], tech_gap[\"y\"][i], s=10, color=colours[tech_gap[\"EmployerSize\"][i]])\n",
    "\n",
    "plt.gca().set_xlim(xmin=-30, xmax=50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "bfd86ac8",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "        \n",
    "        ## add annotation\n",
    "    #plt.text(-38, -0.035, \"women paid more\", va='center', fontsize=10)\n",
    "    #plt.text(38, -0.035, \"men paid more\", va='center', fontsize=10, ha='right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "c4dcd92f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "604\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colours = [\"#ef767a\",\"#456990\", \"#56cfe1\"]\n",
    "# =========\n",
    "# Initialise Figure and define layout\n",
    "fig, ax = plt.subplots(figsize=(16,12))\n",
    "fig.set_facecolor(\"#efe9e5\")\n",
    "\n",
    "## PLOT 1\n",
    "#Tech companies\n",
    "plt.subplot(3,1,1)\n",
    "tech_gap = pay_df[(pay_df[\"Sector\"]==\"Tech\") & (pay_df[\"file\"] == \"2021 to 2022\")][['CompanyNumber', 'NiceName', 'DiffMedianHourlyPercent']]\n",
    "tech_gap = get_coords_for_beeswarm(tech_gap, 'DiffMedianHourlyPercent' )\n",
    "\n",
    "plt.scatter(tech_gap[\"x\"], tech_gap[\"y\"], s=13, color=colours[0], alpha=0.7)\n",
    "format_axis()\n",
    "\n",
    "## PLOT 1\n",
    "#Charities\n",
    "plt.subplot(3,1,2)\n",
    "char_gap = pay_df[(~pay_df[\"charityNumber\"].isna()) & (pay_df[\"file\"] == \"2021 to 2022\")][['CompanyNumber', 'NiceName', 'DiffMedianHourlyPercent']]\n",
    "char_gap = get_coords_for_beeswarm(char_gap, 'DiffMedianHourlyPercent' )\n",
    "#char_gap = char_gap[~char_gap[\"x\"].isin([0])]\n",
    "\n",
    "plt.scatter(char_gap[\"x\"], char_gap[\"y\"], s=13, color=colours[0], alpha=0.7)\n",
    "format_axis()\n",
    "print(len(char_gap))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "ea2450ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38251    1145141\n",
       "38253    1084866\n",
       "38314    1117138\n",
       "38315     200719\n",
       "38344    1071298\n",
       "          ...   \n",
       "48638     306122\n",
       "48640    1079570\n",
       "48641    1090981\n",
       "48642    1041923\n",
       "48643    1069810\n",
       "Name: charityNumber, Length: 604, dtype: object"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pay_df[(~pay_df[\"charityNumber\"].isna()) & (pay_df[\"file\"] == \"2021 to 2022\")][\"charityNumber\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "185d6b5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Address', 'CompanyLinkToGPGInfo', 'CompanyNumber', 'CurrentName',\n",
       "       'DateSubmitted', 'DiffMeanBonusPercent', 'DiffMeanHourlyPercent',\n",
       "       'DiffMedianBonusPercent', 'DiffMedianHourlyPercent', 'DueDate',\n",
       "       'EmployerId', 'EmployerName', 'EmployerSize', 'FemaleBonusPercent',\n",
       "       'FemaleLowerMiddleQuartile', 'FemaleLowerQuartile', 'FemaleTopQuartile',\n",
       "       'FemaleUpperMiddleQuartile', 'MaleBonusPercent',\n",
       "       'MaleLowerMiddleQuartile', 'MaleLowerQuartile', 'MaleTopQuartile',\n",
       "       'MaleUpperMiddleQuartile', 'PostCode', 'ResponsiblePerson', 'SicCodes',\n",
       "       'SubmittedAfterTheDeadline', 'active', 'charityNumber', 'companyNumber',\n",
       "       'dateModified', 'dateRegistered', 'dateRemoved', 'file', 'id',\n",
       "       'latestIncome', 'latestIncomeDate', 'linked_orgs', 'name', 'orgIDs',\n",
       "       'organisationType', 'organisationTypePrimary', 'postalCode', 'source',\n",
       "       'url', 'SIC_clean', 'SIC_count', 'SIC_sections', 'SIC_names',\n",
       "       'SIC_section', 'SIC_name', 'SIC_section_name', 'Sector', 'NiceName'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pay_df.columns"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}