data_eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import geopandas as gpd\n",
    "import ast\n",
    "from wordcloud import WordCloud, ImageColorGenerator, STOPWORDS\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import word_tokenize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw = pd.read_csv('glassdoor_jobs_cleaned.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Job Title</th>\n",
       "      <th>Job Description</th>\n",
       "      <th>Location</th>\n",
       "      <th>Headquarters</th>\n",
       "      <th>seniority</th>\n",
       "      <th>company_name</th>\n",
       "      <th>location_city</th>\n",
       "      <th>hq_city</th>\n",
       "      <th>ratings</th>\n",
       "      <th>avg_salary</th>\n",
       "      <th>...</th>\n",
       "      <th>avg_revenue</th>\n",
       "      <th>min_size</th>\n",
       "      <th>max_size</th>\n",
       "      <th>avg_size</th>\n",
       "      <th>languages</th>\n",
       "      <th>ownership</th>\n",
       "      <th>industry</th>\n",
       "      <th>sector</th>\n",
       "      <th>competitors</th>\n",
       "      <th>founded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Data Scientist - ZISHI Adaptive</td>\n",
       "      <td>Company Description\\n\\nIn just over 15 years, ...</td>\n",
       "      <td>Bromley, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>OSTC UK</td>\n",
       "      <td>Bromley</td>\n",
       "      <td>London</td>\n",
       "      <td>3.8</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.750000e+07</td>\n",
       "      <td>201</td>\n",
       "      <td>500</td>\n",
       "      <td>350.5</td>\n",
       "      <td>{'python': 1, 'excel': 1, 'sql': 1, 'aws': 1, ...</td>\n",
       "      <td>private</td>\n",
       "      <td>['Brokerage Services']</td>\n",
       "      <td>['Finance']</td>\n",
       "      <td>['J.P. Morgan', 'XTB', 'Mandara']</td>\n",
       "      <td>1999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Data Scientist, Digital</td>\n",
       "      <td>The details\\n\\n\\nNewton is a high growth and s...</td>\n",
       "      <td>Wideopen, England</td>\n",
       "      <td>Oxford, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>Newton Europe</td>\n",
       "      <td>Wideopen</td>\n",
       "      <td>Oxford</td>\n",
       "      <td>3.9</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.500000e+07</td>\n",
       "      <td>201</td>\n",
       "      <td>500</td>\n",
       "      <td>350.5</td>\n",
       "      <td>{'python': 1, 'excel': 0, 'sql': 1, 'aws': 0, ...</td>\n",
       "      <td>private</td>\n",
       "      <td>['Consulting']</td>\n",
       "      <td>['Business Services']</td>\n",
       "      <td>['-1']</td>\n",
       "      <td>2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>Imagine introducing the next generation of tec...</td>\n",
       "      <td>London, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>G-Research</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>4.8</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>501</td>\n",
       "      <td>1000</td>\n",
       "      <td>750.5</td>\n",
       "      <td>{'python': 1, 'excel': 0, 'sql': 1, 'aws': 0, ...</td>\n",
       "      <td>private</td>\n",
       "      <td>['Computer Hardware', 'Software']</td>\n",
       "      <td>['Information Technology']</td>\n",
       "      <td>['-1']</td>\n",
       "      <td>2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>Data Scientist\\nCambridge UK, Gaithersburg, Go...</td>\n",
       "      <td>Cambridge, England</td>\n",
       "      <td>Cambridge, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>AstraZeneca</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>4.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.500000e+09</td>\n",
       "      <td>10000</td>\n",
       "      <td>10000</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>{'python': 0, 'excel': 0, 'sql': 0, 'aws': 0, ...</td>\n",
       "      <td>public</td>\n",
       "      <td>['Biotech', 'Pharmaceuticals']</td>\n",
       "      <td>['Biotech', 'Pharmaceuticals']</td>\n",
       "      <td>['Roche', 'GlaxoSmithKline', 'Novartis']</td>\n",
       "      <td>1913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Senior Data Scientist</td>\n",
       "      <td>About Us\\n\\nWe want to help small businesses w...</td>\n",
       "      <td>London, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>senior</td>\n",
       "      <td>Funding Circle UK</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>3.4</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.500000e+07</td>\n",
       "      <td>501</td>\n",
       "      <td>1000</td>\n",
       "      <td>750.5</td>\n",
       "      <td>{'python': 1, 'excel': 1, 'sql': 1, 'aws': 0, ...</td>\n",
       "      <td>private</td>\n",
       "      <td>['Lending']</td>\n",
       "      <td>['Finance']</td>\n",
       "      <td>['LendingClub', 'OnDeck', 'Bond Street']</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Job Title  \\\n",
       "0  Data Scientist - ZISHI Adaptive   \n",
       "1          Data Scientist, Digital   \n",
       "2                   Data Scientist   \n",
       "3                   Data Scientist   \n",
       "4            Senior Data Scientist   \n",
       "\n",
       "                                     Job Description            Location  \\\n",
       "0  Company Description\\n\\nIn just over 15 years, ...    Bromley, England   \n",
       "1  The details\\n\\n\\nNewton is a high growth and s...   Wideopen, England   \n",
       "2  Imagine introducing the next generation of tec...     London, England   \n",
       "3  Data Scientist\\nCambridge UK, Gaithersburg, Go...  Cambridge, England   \n",
       "4  About Us\\n\\nWe want to help small businesses w...     London, England   \n",
       "\n",
       "                Headquarters seniority       company_name location_city  \\\n",
       "0     London, United Kingdom    junior            OSTC UK       Bromley   \n",
       "1     Oxford, United Kingdom    junior      Newton Europe      Wideopen   \n",
       "2     London, United Kingdom    junior         G-Research        London   \n",
       "3  Cambridge, United Kingdom    junior        AstraZeneca     Cambridge   \n",
       "4     London, United Kingdom    senior  Funding Circle UK        London   \n",
       "\n",
       "     hq_city  ratings  avg_salary  ...   avg_revenue  min_size  max_size  \\\n",
       "0     London      3.8     45000.0  ...  3.750000e+07       201       500   \n",
       "1     Oxford      3.9     45000.0  ...  7.500000e+07       201       500   \n",
       "2     London      4.8     45000.0  ... -1.000000e+00       501      1000   \n",
       "3  Cambridge      4.0     45000.0  ...  7.500000e+09     10000     10000   \n",
       "4     London      3.4     45000.0  ...  7.500000e+07       501      1000   \n",
       "\n",
       "   avg_size                                          languages  ownership  \\\n",
       "0     350.5  {'python': 1, 'excel': 1, 'sql': 1, 'aws': 1, ...    private   \n",
       "1     350.5  {'python': 1, 'excel': 0, 'sql': 1, 'aws': 0, ...    private   \n",
       "2     750.5  {'python': 1, 'excel': 0, 'sql': 1, 'aws': 0, ...    private   \n",
       "3   10000.0  {'python': 0, 'excel': 0, 'sql': 0, 'aws': 0, ...     public   \n",
       "4     750.5  {'python': 1, 'excel': 1, 'sql': 1, 'aws': 0, ...    private   \n",
       "\n",
       "                            industry                          sector  \\\n",
       "0             ['Brokerage Services']                     ['Finance']   \n",
       "1                     ['Consulting']           ['Business Services']   \n",
       "2  ['Computer Hardware', 'Software']      ['Information Technology']   \n",
       "3     ['Biotech', 'Pharmaceuticals']  ['Biotech', 'Pharmaceuticals']   \n",
       "4                        ['Lending']                     ['Finance']   \n",
       "\n",
       "                                competitors founded  \n",
       "0         ['J.P. Morgan', 'XTB', 'Mandara']    1999  \n",
       "1                                    ['-1']    2001  \n",
       "2                                    ['-1']    2001  \n",
       "3  ['Roche', 'GlaxoSmithKline', 'Novartis']    1913  \n",
       "4  ['LendingClub', 'OnDeck', 'Bond Street']    2010  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_rows', None)\n",
    "df_raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 Job Title\n",
      "2 Job Description\n",
      "3 Location\n",
      "4 Headquarters\n",
      "5 seniority\n",
      "6 company_name\n",
      "7 location_city\n",
      "8 hq_city\n",
      "9 ratings\n",
      "10 avg_salary\n",
      "11 min_salary\n",
      "12 max_salary\n",
      "13 min_revenue\n",
      "14 max_revenue\n",
      "15 avg_revenue\n",
      "16 min_size\n",
      "17 max_size\n",
      "18 avg_size\n",
      "19 languages\n",
      "20 ownership\n",
      "21 industry\n",
      "22 sector\n",
      "23 competitors\n",
      "24 founded\n"
     ]
    }
   ],
   "source": [
    "i = 0\n",
    "for col in list(df_raw.columns):\n",
    "    print(i+1, col)\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    ds\n",
       "1    ds\n",
       "2    ds\n",
       "3    ds\n",
       "4    ds\n",
       "Name: role, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create job role column\n",
    "df = df_raw.copy()\n",
    "def get_role(title):\n",
    "    if \"intern\" in title.lower():\n",
    "        return \"intern\"\n",
    "    elif \"research\" in title.lower():\n",
    "        return 'research'\n",
    "    elif \"analyst\" in title.lower():\n",
    "        return 'analyst'\n",
    "    elif \"machine learning\" in title.lower() or \"deep learning\" in title.lower():\n",
    "        return 'mle'\n",
    "    elif \"data engineer\" in title.lower():\n",
    "        return 'de'\n",
    "    else:\n",
    "        return 'ds'\n",
    "\n",
    "df[\"role\"] = df[\"Job Title\"].apply(lambda x: get_role(x))\n",
    "df.role.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def language_present(x):\n",
    "    Languages = [\"python\",\"excel\",\"sql\",\n",
    "                 \"aws\",\"spark\",\"hadoop\",\n",
    "                 \"java \",\" r \",\"tensorflow\",\n",
    "                 \"matlab\"]\n",
    "    y = []\n",
    "    x = ast.literal_eval(x)\n",
    "    for l in Languages:\n",
    "        if x[l]!=0:\n",
    "            y.append(l)\n",
    "    return y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"competitors\"] = df[\"competitors\"].apply(lambda x: ast.literal_eval(x))\n",
    "df[\"languages\"] = df[\"languages\"].apply(lambda x: language_present(x))\n",
    "df[\"industry\"] = df[\"industry\"].apply(lambda x: ast.literal_eval(x))\n",
    "df[\"sector\"] = df[\"sector\"].apply(lambda x: ast.literal_eval(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove England, United kingdom, briton from location\n",
    "def rm_contries(location):\n",
    "    unwanted = [\"uk\", \"england\", \"united kingdom\"]\n",
    "    if location.lower() in unwanted:\n",
    "        return \"-1\"\n",
    "    else:\n",
    "        return location\n",
    "    \n",
    "df.location_city = df.location_city.apply(lambda x: rm_contries(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Competitors count column\n",
    "df[\"num_comp\"] = df[\"competitors\"].apply(lambda x: 0 if x[0] == '-1' else len(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# number of languages in each job\n",
    "df[\"num_languages\"] = df[\"languages\"].apply(lambda x: len(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create company age column\n",
    "df[\"age\"] = df[\"founded\"].apply(lambda x: -1 if x == -1 else 2020 - int(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove newline character form job description field\n",
    "df[\"Job Description\"] = df[\"Job Description\"].apply(lambda x: x.replace(\"\\n\", \"\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Job discription length\n",
    "df[\"description_len\"] = df[\"Job Description\"].apply(lambda x: len(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Job location same as HQ\n",
    "df[\"same_state\"] = (df.location_city == df.hq_city).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        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>ratings</th>\n",
       "      <th>avg_salary</th>\n",
       "      <th>min_salary</th>\n",
       "      <th>max_salary</th>\n",
       "      <th>min_revenue</th>\n",
       "      <th>max_revenue</th>\n",
       "      <th>avg_revenue</th>\n",
       "      <th>min_size</th>\n",
       "      <th>max_size</th>\n",
       "      <th>avg_size</th>\n",
       "      <th>founded</th>\n",
       "      <th>num_comp</th>\n",
       "      <th>num_languages</th>\n",
       "      <th>age</th>\n",
       "      <th>description_len</th>\n",
       "      <th>same_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1.300000e+03</td>\n",
       "      <td>1.300000e+03</td>\n",
       "      <td>1.300000e+03</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.860231</td>\n",
       "      <td>49523.076923</td>\n",
       "      <td>37933.076923</td>\n",
       "      <td>61113.076923</td>\n",
       "      <td>1.284324e+09</td>\n",
       "      <td>5.647386e+09</td>\n",
       "      <td>3.465855e+09</td>\n",
       "      <td>3189.743846</td>\n",
       "      <td>4273.475385</td>\n",
       "      <td>3731.609615</td>\n",
       "      <td>1444.019231</td>\n",
       "      <td>0.744615</td>\n",
       "      <td>2.202308</td>\n",
       "      <td>37.817692</td>\n",
       "      <td>4372.536923</td>\n",
       "      <td>0.344615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.902329</td>\n",
       "      <td>11647.051839</td>\n",
       "      <td>10539.313027</td>\n",
       "      <td>14773.850192</td>\n",
       "      <td>2.078186e+09</td>\n",
       "      <td>5.541198e+10</td>\n",
       "      <td>2.803893e+10</td>\n",
       "      <td>4172.283823</td>\n",
       "      <td>4547.350806</td>\n",
       "      <td>4263.118680</td>\n",
       "      <td>872.030092</td>\n",
       "      <td>1.261502</td>\n",
       "      <td>1.484276</td>\n",
       "      <td>55.571201</td>\n",
       "      <td>2166.136540</td>\n",
       "      <td>0.475426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.000000</td>\n",
       "      <td>25000.000000</td>\n",
       "      <td>19000.000000</td>\n",
       "      <td>28000.000000</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>251.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>44000.000000</td>\n",
       "      <td>32000.000000</td>\n",
       "      <td>52000.000000</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>25.500000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>3025.750000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.600000</td>\n",
       "      <td>49000.000000</td>\n",
       "      <td>32000.000000</td>\n",
       "      <td>66000.000000</td>\n",
       "      <td>2.500000e+07</td>\n",
       "      <td>5.000000e+07</td>\n",
       "      <td>3.750000e+07</td>\n",
       "      <td>501.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>750.500000</td>\n",
       "      <td>1974.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>3983.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>54000.000000</td>\n",
       "      <td>43000.000000</td>\n",
       "      <td>66000.000000</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>5.000000e+09</td>\n",
       "      <td>3.500000e+09</td>\n",
       "      <td>5001.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>7500.500000</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>5149.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>87000.000000</td>\n",
       "      <td>69000.000000</td>\n",
       "      <td>105000.000000</td>\n",
       "      <td>1.000000e+10</td>\n",
       "      <td>1.000000e+12</td>\n",
       "      <td>5.050000e+11</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>352.000000</td>\n",
       "      <td>13940.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ratings    avg_salary    min_salary     max_salary   min_revenue  \\\n",
       "count  1300.000000   1300.000000   1300.000000    1300.000000  1.300000e+03   \n",
       "mean      2.860231  49523.076923  37933.076923   61113.076923  1.284324e+09   \n",
       "std       1.902329  11647.051839  10539.313027   14773.850192  2.078186e+09   \n",
       "min      -1.000000  25000.000000  19000.000000   28000.000000 -1.000000e+00   \n",
       "25%       3.000000  44000.000000  32000.000000   52000.000000 -1.000000e+00   \n",
       "50%       3.600000  49000.000000  32000.000000   66000.000000  2.500000e+07   \n",
       "75%       4.000000  54000.000000  43000.000000   66000.000000  2.000000e+09   \n",
       "max       5.000000  87000.000000  69000.000000  105000.000000  1.000000e+10   \n",
       "\n",
       "        max_revenue   avg_revenue      min_size      max_size      avg_size  \\\n",
       "count  1.300000e+03  1.300000e+03   1300.000000   1300.000000   1300.000000   \n",
       "mean   5.647386e+09  3.465855e+09   3189.743846   4273.475385   3731.609615   \n",
       "std    5.541198e+10  2.803893e+10   4172.283823   4547.350806   4263.118680   \n",
       "min   -1.000000e+00 -1.000000e+00     -1.000000     -1.000000     -1.000000   \n",
       "25%   -1.000000e+00 -1.000000e+00      1.000000     50.000000     25.500000   \n",
       "50%    5.000000e+07  3.750000e+07    501.000000   1000.000000    750.500000   \n",
       "75%    5.000000e+09  3.500000e+09   5001.000000  10000.000000   7500.500000   \n",
       "max    1.000000e+12  5.050000e+11  10000.000000  10000.000000  10000.000000   \n",
       "\n",
       "           founded     num_comp  num_languages          age  description_len  \\\n",
       "count  1300.000000  1300.000000    1300.000000  1300.000000      1300.000000   \n",
       "mean   1444.019231     0.744615       2.202308    37.817692      4372.536923   \n",
       "std     872.030092     1.261502       1.484276    55.571201      2166.136540   \n",
       "min      -1.000000     0.000000       0.000000    -1.000000       251.000000   \n",
       "25%      -1.000000     0.000000       1.000000    -1.000000      3025.750000   \n",
       "50%    1974.000000     0.000000       2.000000    15.000000      3983.000000   \n",
       "75%    2004.000000     1.000000       3.000000    42.000000      5149.000000   \n",
       "max    2019.000000     3.000000       7.000000   352.000000     13940.000000   \n",
       "\n",
       "        same_state  \n",
       "count  1300.000000  \n",
       "mean      0.344615  \n",
       "std       0.475426  \n",
       "min       0.000000  \n",
       "25%       0.000000  \n",
       "50%       0.000000  \n",
       "75%       1.000000  \n",
       "max       1.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A lot of the numerical columns have contain entries = -1. This will likely skew their statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of numeric columns\n",
    "numeric_cols = list(df.describe().columns)\n",
    "\n",
    "# Drop max and min columns\n",
    "numeric_cols_dropped = []\n",
    "\n",
    "for col in numeric_cols:\n",
    "    if 'min' in col or 'max' in col:\n",
    "        numeric_cols_dropped.append(col)\n",
    "    \n",
    "# List of acceptable numerical columns\n",
    "numeric_cols_ok = {x for x in numeric_cols if x not in numeric_cols_dropped}\n",
    "\n",
    "# create a numeric dataframe\n",
    "nm_df = df[list(numeric_cols_ok)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num_comp\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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V/fcKr/tfzP0m8E/AG7qfxyuNha/+S6skyaXA56vqyrXuRW1yhi5JjXCGrqNakguB5y44/OGq+ru16Ec6Ega6JDXCJRdJaoSBLkmNMNAlqREGuiQ14v8Amc+7m2chMdIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "age\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "same_state\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num_languages\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "description_len\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ratings\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg_salary\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "no_plot = ['founded', 'avg_revenue', 'avg_size']\n",
    "for col in nm_df.columns:\n",
    "    if col not in no_plot:\n",
    "        print(col)\n",
    "        plt.figure()\n",
    "        nm_df[col].hist()\n",
    "        plt.show()\n",
    "        plt.figure()\n",
    "        nm_df.boxplot(column=col)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#nm_df = nm_df.drop(\"founded\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>num_comp</th>\n",
       "      <th>age</th>\n",
       "      <th>same_state</th>\n",
       "      <th>num_languages</th>\n",
       "      <th>avg_size</th>\n",
       "      <th>description_len</th>\n",
       "      <th>ratings</th>\n",
       "      <th>avg_salary</th>\n",
       "      <th>avg_revenue</th>\n",
       "      <th>founded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>num_comp</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.432185</td>\n",
       "      <td>0.092946</td>\n",
       "      <td>-0.089149</td>\n",
       "      <td>0.626233</td>\n",
       "      <td>0.114318</td>\n",
       "      <td>0.296246</td>\n",
       "      <td>-0.034362</td>\n",
       "      <td>0.039579</td>\n",
       "      <td>0.303052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>0.432185</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.029391</td>\n",
       "      <td>-0.047702</td>\n",
       "      <td>0.616499</td>\n",
       "      <td>0.189465</td>\n",
       "      <td>0.302363</td>\n",
       "      <td>-0.027589</td>\n",
       "      <td>0.100215</td>\n",
       "      <td>0.367690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>same_state</th>\n",
       "      <td>0.092946</td>\n",
       "      <td>0.029391</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.080329</td>\n",
       "      <td>-0.094719</td>\n",
       "      <td>0.079660</td>\n",
       "      <td>0.207703</td>\n",
       "      <td>0.009824</td>\n",
       "      <td>-0.021019</td>\n",
       "      <td>0.239308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>num_languages</th>\n",
       "      <td>-0.089149</td>\n",
       "      <td>-0.047702</td>\n",
       "      <td>-0.080329</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.072233</td>\n",
       "      <td>0.057334</td>\n",
       "      <td>-0.064382</td>\n",
       "      <td>-0.002764</td>\n",
       "      <td>0.030906</td>\n",
       "      <td>-0.064308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_size</th>\n",
       "      <td>0.626233</td>\n",
       "      <td>0.616499</td>\n",
       "      <td>-0.094719</td>\n",
       "      <td>-0.072233</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.177982</td>\n",
       "      <td>0.388365</td>\n",
       "      <td>-0.038787</td>\n",
       "      <td>0.142649</td>\n",
       "      <td>0.369630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>description_len</th>\n",
       "      <td>0.114318</td>\n",
       "      <td>0.189465</td>\n",
       "      <td>0.079660</td>\n",
       "      <td>0.057334</td>\n",
       "      <td>0.177982</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.144064</td>\n",
       "      <td>-0.025651</td>\n",
       "      <td>0.026156</td>\n",
       "      <td>0.238329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratings</th>\n",
       "      <td>0.296246</td>\n",
       "      <td>0.302363</td>\n",
       "      <td>0.207703</td>\n",
       "      <td>-0.064382</td>\n",
       "      <td>0.388365</td>\n",
       "      <td>0.144064</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.015298</td>\n",
       "      <td>0.050492</td>\n",
       "      <td>0.596688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_salary</th>\n",
       "      <td>-0.034362</td>\n",
       "      <td>-0.027589</td>\n",
       "      <td>0.009824</td>\n",
       "      <td>-0.002764</td>\n",
       "      <td>-0.038787</td>\n",
       "      <td>-0.025651</td>\n",
       "      <td>-0.015298</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.016082</td>\n",
       "      <td>-0.040160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_revenue</th>\n",
       "      <td>0.039579</td>\n",
       "      <td>0.100215</td>\n",
       "      <td>-0.021019</td>\n",
       "      <td>0.030906</td>\n",
       "      <td>0.142649</td>\n",
       "      <td>0.026156</td>\n",
       "      <td>0.050492</td>\n",
       "      <td>-0.016082</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.032782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>founded</th>\n",
       "      <td>0.303052</td>\n",
       "      <td>0.367690</td>\n",
       "      <td>0.239308</td>\n",
       "      <td>-0.064308</td>\n",
       "      <td>0.369630</td>\n",
       "      <td>0.238329</td>\n",
       "      <td>0.596688</td>\n",
       "      <td>-0.040160</td>\n",
       "      <td>0.032782</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 num_comp       age  same_state  num_languages  avg_size  \\\n",
       "num_comp         1.000000  0.432185    0.092946      -0.089149  0.626233   \n",
       "age              0.432185  1.000000    0.029391      -0.047702  0.616499   \n",
       "same_state       0.092946  0.029391    1.000000      -0.080329 -0.094719   \n",
       "num_languages   -0.089149 -0.047702   -0.080329       1.000000 -0.072233   \n",
       "avg_size         0.626233  0.616499   -0.094719      -0.072233  1.000000   \n",
       "description_len  0.114318  0.189465    0.079660       0.057334  0.177982   \n",
       "ratings          0.296246  0.302363    0.207703      -0.064382  0.388365   \n",
       "avg_salary      -0.034362 -0.027589    0.009824      -0.002764 -0.038787   \n",
       "avg_revenue      0.039579  0.100215   -0.021019       0.030906  0.142649   \n",
       "founded          0.303052  0.367690    0.239308      -0.064308  0.369630   \n",
       "\n",
       "                 description_len   ratings  avg_salary  avg_revenue   founded  \n",
       "num_comp                0.114318  0.296246   -0.034362     0.039579  0.303052  \n",
       "age                     0.189465  0.302363   -0.027589     0.100215  0.367690  \n",
       "same_state              0.079660  0.207703    0.009824    -0.021019  0.239308  \n",
       "num_languages           0.057334 -0.064382   -0.002764     0.030906 -0.064308  \n",
       "avg_size                0.177982  0.388365   -0.038787     0.142649  0.369630  \n",
       "description_len         1.000000  0.144064   -0.025651     0.026156  0.238329  \n",
       "ratings                 0.144064  1.000000   -0.015298     0.050492  0.596688  \n",
       "avg_salary             -0.025651 -0.015298    1.000000    -0.016082 -0.040160  \n",
       "avg_revenue             0.026156  0.050492   -0.016082     1.000000  0.032782  \n",
       "founded                 0.238329  0.596688   -0.040160     0.032782  1.000000  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Correlattion table\n",
    "corr = nm_df.corr()\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x131ba1940>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "sns.heatmap(corr, cmap=cmap, square=True, linewidth=.5, center=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Catagorical columns\n",
    "catagoric_cols = list(col for col in list(df.columns) if col not in numeric_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Job Title</th>\n",
       "      <th>Job Description</th>\n",
       "      <th>Location</th>\n",
       "      <th>Headquarters</th>\n",
       "      <th>seniority</th>\n",
       "      <th>company_name</th>\n",
       "      <th>location_city</th>\n",
       "      <th>hq_city</th>\n",
       "      <th>languages</th>\n",
       "      <th>ownership</th>\n",
       "      <th>industry</th>\n",
       "      <th>sector</th>\n",
       "      <th>competitors</th>\n",
       "      <th>role</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Data Scientist - ZISHI Adaptive</td>\n",
       "      <td>Company DescriptionIn just over 15 years, OSTC...</td>\n",
       "      <td>Bromley, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>OSTC UK</td>\n",
       "      <td>Bromley</td>\n",
       "      <td>London</td>\n",
       "      <td>[python, excel, sql, aws, hadoop]</td>\n",
       "      <td>private</td>\n",
       "      <td>[Brokerage Services]</td>\n",
       "      <td>[Finance]</td>\n",
       "      <td>[J.P. Morgan, XTB, Mandara]</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Data Scientist, Digital</td>\n",
       "      <td>The detailsNewton is a high growth and success...</td>\n",
       "      <td>Wideopen, England</td>\n",
       "      <td>Oxford, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>Newton Europe</td>\n",
       "      <td>Wideopen</td>\n",
       "      <td>Oxford</td>\n",
       "      <td>[python, sql]</td>\n",
       "      <td>private</td>\n",
       "      <td>[Consulting]</td>\n",
       "      <td>[Business Services]</td>\n",
       "      <td>[-1]</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>Imagine introducing the next generation of tec...</td>\n",
       "      <td>London, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>G-Research</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>[python, sql, spark]</td>\n",
       "      <td>private</td>\n",
       "      <td>[Computer Hardware, Software]</td>\n",
       "      <td>[Information Technology]</td>\n",
       "      <td>[-1]</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>Data ScientistCambridge UK, Gaithersburg, Goth...</td>\n",
       "      <td>Cambridge, England</td>\n",
       "      <td>Cambridge, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>AstraZeneca</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>[]</td>\n",
       "      <td>public</td>\n",
       "      <td>[Biotech, Pharmaceuticals]</td>\n",
       "      <td>[Biotech, Pharmaceuticals]</td>\n",
       "      <td>[Roche, GlaxoSmithKline, Novartis]</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Senior Data Scientist</td>\n",
       "      <td>About UsWe want to help small businesses win. ...</td>\n",
       "      <td>London, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>senior</td>\n",
       "      <td>Funding Circle UK</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>[python, excel, sql,  r ]</td>\n",
       "      <td>private</td>\n",
       "      <td>[Lending]</td>\n",
       "      <td>[Finance]</td>\n",
       "      <td>[LendingClub, OnDeck, Bond Street]</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Job Title  \\\n",
       "0  Data Scientist - ZISHI Adaptive   \n",
       "1          Data Scientist, Digital   \n",
       "2                   Data Scientist   \n",
       "3                   Data Scientist   \n",
       "4            Senior Data Scientist   \n",
       "\n",
       "                                     Job Description            Location  \\\n",
       "0  Company DescriptionIn just over 15 years, OSTC...    Bromley, England   \n",
       "1  The detailsNewton is a high growth and success...   Wideopen, England   \n",
       "2  Imagine introducing the next generation of tec...     London, England   \n",
       "3  Data ScientistCambridge UK, Gaithersburg, Goth...  Cambridge, England   \n",
       "4  About UsWe want to help small businesses win. ...     London, England   \n",
       "\n",
       "                Headquarters seniority       company_name location_city  \\\n",
       "0     London, United Kingdom    junior            OSTC UK       Bromley   \n",
       "1     Oxford, United Kingdom    junior      Newton Europe      Wideopen   \n",
       "2     London, United Kingdom    junior         G-Research        London   \n",
       "3  Cambridge, United Kingdom    junior        AstraZeneca     Cambridge   \n",
       "4     London, United Kingdom    senior  Funding Circle UK        London   \n",
       "\n",
       "     hq_city                          languages ownership  \\\n",
       "0     London  [python, excel, sql, aws, hadoop]   private   \n",
       "1     Oxford                      [python, sql]   private   \n",
       "2     London               [python, sql, spark]   private   \n",
       "3  Cambridge                                 []    public   \n",
       "4     London          [python, excel, sql,  r ]   private   \n",
       "\n",
       "                        industry                      sector  \\\n",
       "0           [Brokerage Services]                   [Finance]   \n",
       "1                   [Consulting]         [Business Services]   \n",
       "2  [Computer Hardware, Software]    [Information Technology]   \n",
       "3     [Biotech, Pharmaceuticals]  [Biotech, Pharmaceuticals]   \n",
       "4                      [Lending]                   [Finance]   \n",
       "\n",
       "                          competitors role  \n",
       "0         [J.P. Morgan, XTB, Mandara]   ds  \n",
       "1                                [-1]   ds  \n",
       "2                                [-1]   ds  \n",
       "3  [Roche, GlaxoSmithKline, Novartis]   ds  \n",
       "4  [LendingClub, OnDeck, Bond Street]   ds  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dataframe of all catagorical data\n",
    "cat_df = df[catagoric_cols]\n",
    "cat_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove dictionaries and list\n",
    "# Remove large text fields and pre-derived fields\n",
    "cat_df = cat_df.drop([\"Job Description\",\"Job Title\",\"Location\",\n",
    "                     \"Headquarters\",\"languages\",\"industry\",\"sector\",\n",
    "                     \"competitors\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>seniority</th>\n",
       "      <th>company_name</th>\n",
       "      <th>location_city</th>\n",
       "      <th>hq_city</th>\n",
       "      <th>ownership</th>\n",
       "      <th>role</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>junior</td>\n",
       "      <td>OSTC UK</td>\n",
       "      <td>Bromley</td>\n",
       "      <td>London</td>\n",
       "      <td>private</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>junior</td>\n",
       "      <td>Newton Europe</td>\n",
       "      <td>Wideopen</td>\n",
       "      <td>Oxford</td>\n",
       "      <td>private</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>junior</td>\n",
       "      <td>G-Research</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>private</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>junior</td>\n",
       "      <td>AstraZeneca</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>public</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>senior</td>\n",
       "      <td>Funding Circle UK</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>private</td>\n",
       "      <td>ds</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  seniority       company_name location_city    hq_city ownership role\n",
       "0    junior            OSTC UK       Bromley     London   private   ds\n",
       "1    junior      Newton Europe      Wideopen     Oxford   private   ds\n",
       "2    junior         G-Research        London     London   private   ds\n",
       "3    junior        AstraZeneca     Cambridge  Cambridge    public   ds\n",
       "4    senior  Funding Circle UK        London     London   private   ds"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BEHQZYeqZRbjmzE82ldlsn6sGoSdBELzb6diIX9JSkiZKul/SfZIOTtsXknSdpIfT64Kd6kMQBEHQl06aet4CvmJmqwLrAgdIWhU4ArjBzFYEbkjrQRAEwSDRMVOPmT0DPJPeT5f0ALAEsC2wYRIbD9wIHN6pfrwbmXDW5k1ldtr7agDOGv+JprJ7j70WgFPO3ayp7EF7XNNUJgiCWZtBmdyVtAxef/d2YLF0UwB4FlhsMPoQBEEQOB1X/JLmBS4GDjGzV/L7zMwAqzhuP0mTJE2aNm1ap7sZBEHQNXRU8UuaHVf655rZJWnzc5IWT/sXB54vO9bMxpnZGDMbM2rUqE52MwiCoKvopFePgDOBB8zsR7ldlwNj0/uxQBSpDYIgGEQ66cf/EWAv4B5Jd6VtXweOBy6UtA/wBLBLB/sQdIijL2w+EXz0Lj0TwXtf2nhC+qztr57xfovLDmja9h+2PRWAT156bFPZq7b/ZlOZIOgmOunV82dAFbs36dTnBkEQBI2JyN2ga9jyklOayvx+h4Nc9uIzmsvu+DkAtppwblPZK3faY8b7rSdc0kASrthph6btBUF/iFw9QRAEXUYo/iAIgi4jTD1BMAuz7YSrm8pctpNPnG9/8Z+byl664/oA7Hzx1KayF+24OgAHXfpkU9lTtl8KgFMvfa6p7AHbR8zmzCZG/EEQBF1GjPiDIJgpXDLhhaYyO+y0yCD0pPuIEX8QBEGXEYo/CIKgywjFHwRB0GWE4g+CIOgyQvEHQRB0GaH4gyAIuoxQ/EEQBF1GKP4gCIIuIxR/EARBlxGRu0EQDAkmntu89vZGe0SZ1jp0svTiryQ9L+ne3LaFJF0n6eH0umCnPj8IgiAop5Omnl8DxXp7RwA3mNmKwA1pPQiCIBhEOqb4zexm4F+FzdsC49P78cB2nfr8IAiCoJzBntxdzMyeSe+fBSIxdxAEwSAz0yZ3zcwkWdV+SfsB+wGMHj160PoVBMHQ584znm8qs+bnFh2EnsyaDPaI/zlJiwOk18pfx8zGmdkYMxszalTM1AdBEAwUg634LwfGpvdjgcsG+fODIAi6nk66c54P3AqsLOkpSfsAxwObSnoY+HhaD4IgCAaRjtn4zWz3il2bdOozgyAIguZEyoYgCIIuIxR/EARBlxGKPwiCoMuIJG1BEHQ1j//k2aYyyxzyHgCePemRprLv+eoKADz3k8lNZRc75IMue8qNzWUP2rCpTF1ixB8EQdBlxIg/CIJgiPH8qVc0lVn0gK0r98WIPwiCoMsIxR8EQdBlhOIPgiDoMkLxB0EQdBmh+IMgCLqMUPxBEARdRij+IAiCLiMUfxAEQZcRij8IgqDLCMUfBEHQZYTiD4Ig6DJmiuKXtLmkhyQ9IumImdGHIAiCbmXQFb+k4cCpwBbAqsDuklYd7H4EQRB0KzNjxL828IiZPWpmbwIXANvOhH4EQRB0JTND8S8BPJlbfyptC4IgCAYBmdngfqC0E7C5mX0ure8FrGNmXyrI7Qfsl1ZXBh4qNLUI8EILH92K/LtZdlbpx1CTnVX6MSvIzir9mBVkZ5V+VMkubWaj+mw1s0FdgPWAa3LrRwJHttHOpE7Jv5tlZ5V+DDXZWaUfs4LsrNKPWUF2VulHq32eGaaeO4AVJS0raQ5gN+DymdCPIAiCrmTQSy+a2VuSvgRcAwwHfmVm9w12P4IgCLqVmVJz18yuAq7qZzPjOij/bpadVfox1GRnlX7MCrKzSj9mBdlZpR8t9XnQJ3eDIAiCmUukbAiCIOgyQvEHQxpJB9fZNkh9mUPS6pLenxwX2paVNH+DY8cMRH+DzpMyFcxyvGtNPZLmAV43s3ckrQSsAvzBzP6Xk7kCqDwBZrZNk8+Y28xeG8A+L2xmL9aU3QFYH+//n83s0gHqwyklm/+Nu4tdVuP4o83s6Ip978Ejtw24w8ye7U9fU5tTzGytwrY7zWzN/rbdYj+2BE4D/g4IWBbY38z+0I6spDuAT5jZS4VjPwGcaWZLDUCfFwRWBEZk28zs5grZHwDHAq8DVwOrA182s9/kZHZo9Hlmdkk/+row8Cn8fwzwAHB+3f9Lk7ZbuuYlXQfsbGYvp/UFgQvMbLMS2UeBi4GzzOz+is8/tFH/zOxHOdkPAU9m/x1JnwZ2BJ4AjjazfzVqK2OmTO62S/rDvI/eF+p3K8RvBj6afpRrcTfSXYE9cjInpdcdgPcA2UW8O/Bcg358GDgDmBcYLWkN/I/7xRLZJYClyZ3rqj8XcJuku4Cz8JtU6U1J0s+BFYDz06b9JX3czA6o6nMLjMD/XBel9R2Bx4A1JG1kZoc0OX5yRZ8/B3wb+COu7H4q6btm9qtGjUlalN6/9z/S9t1xRbCspLw78HzAvwptTKf8Bi9v0kZWfPbywFNm9oakDXFld3b2hy/wQ2AjM3skd+zvgT6Kv6bsOGCipE3NbFqS+xTwPWDLsv4mmZWAw+h7zW1ckPsccDCwJHAXsC5wK9BLLscnzOxrkrYHHsf/MzfT858B2Dq9Lgp8GP+tATYCbgF6KX5JvW7YRcxsSpL7v9TWNcCd+O/2IeDrkjY2swfLjq9zs0q0es0vkr8GzOyldJ2WsQbusn6GpGHAr/CbxCs5mfnS68rpe2XX89bAXwvtnQ58PH2/jwHHAwcCH8CvmZ0q+tGbVpz+Z+aCj5DOxtM9HAXcg498quSnpNcDga+l93fVDX4o25bbdzuwFHBnbtu9JXIn4H+Sq4Ar0nJ5g3YFbIor9EeA7wMrlcg9SHpaS+vDgAdK5PYBDsutPw28AkwHPl/Rh9uA4bn12XCFMBy4v8lvNAIfCZXtewhYOLe+MPBQg7a2AR4GXsX/hO8A9+X2Lw1smPq2QW5ZC5htgK65u9L3XwH4G3AicFWF7B0lv+Ud/ZEF9krX+eLAIel3X6ZJn+8GvoA/WX0wW0rk7km/111pfRXgkgbt3ptez8Aj7wHurpC9Flg8t744uaDN3PaJueUVXLln63/MyU0Adik5fkfg4ka/X3rdHjgTmL+sz61e8/jgZnThWpxS43raIP0HXwXGAysU9t8MzJdbnw+4ufj75t6fio/ye33fWtf2QPxBBmMBphZe5wX+1ED+TjxK+DbgfdnFXiH7ALBcbn1ZShRpbv/t2WeU/SC5bQ8Bc7b5fTdKF8nLwE3Aerl9V+Kh2PkL74qSNu6gt7K9M72OAG6q+NyHgPlz6/OTFHT+++b2Dwc+CZyDPyVNqGj3FmCO3PocwC0Nvv/d+M0h6/NGNLjRt3huFwVGZ0sDuWzwcBhwYNU5SNt/gd/gPwOMTb/Rz/GR8Q79kN0ZeBYf+S1S47tNrnkO7kivd2XXKLkba4n88fiN505gdmBU9j8okX2gsF46MCnIlJ7X7Jpsc1+tm1Ub1/zmwD/SNf8b3MyyWUUfhuODmEvTuTsUWAwfmf+tpB9z5tbnLH4/4F7SwCb9Hh8rft86y1Ay9byeXl+T9F7gRXwkUcUheDqIS83sPknL4SOJMr4M3JjsccIV6f4N2n4ymXtM0uz4I/MDJXKP4n+SNxq0NYNkx9wTH+k9hz+tXI4/xl2E35DARwIPSMoeAz8ETMpMHtYzNyHrbQO9KO3/r6S5KrrxA+AuSTfi5+JjwPfTnMn1ub5ugJtaPokrpY8Ay1r1nMcjwO2SLsPNLtsCUzP7puXsmIn/mdmLkoZJGmZmEyX9pNiopHWBnwL/h99MhgOvWon5RtI2uJnlvcDz+O/8AG4+LON/yaQ0lh4zxuwVsiPw32yDtD4NmCsdZ/Q2czSVlXRPei9gbvwm+EdJmXlq9Yp+XCHpi7iimXHdWV/b71OSFgB+B1wn6SVcgZViZkck08m/zextSa9SnVX3BknX0GOK3JXctVP1EQ32vdrmvislPYjrji9IGgX8t0Su1jU/o6NmVycz1bpp0yFmVpVT52Fc75xoZrfktk9Ippo8ZwN/lZTN122HPxnkOR+4SdIL6Xv9CUDSCvi8RC2GzOSupG/hf/BN8EccA84ws281Oa7WBKykOemZOHrQzCqVtaRFgJNxW5vwR9uDC0oWSRfjNr4b6P0nPKii3b/ho4izzOypwr7DzeyE9H6DsuNz7d+U5B4xsxVKPmcYnhp7uYp+LI6bCsBHhv8s7H8KH/H8AvidmU2X9JiZLUsFko5q0ufvFOSvxy/84/AEVM8DHzKzDxfkJuE21IuAMcCncfPYkSV9uBu3YV9vZmtK2gjY08z2qejzqsDngVvN7HxJy+ImhxMafZeBQNLSjfabWamSlvRYuXj5b52O2QAf5V5tnio9v6+tCds0F5AptputifNB2SR9bt9TQHFgAP7fO8QaTHRLWoiem9XcwEgrcSpods0nmVXM7MGquQlLcxKFY+Y1s/9U9a9Efi3go2n1ZjO7s0RmXXzQe62ZvZq2rQTMW9aH0s8ZKoo/T1LSI8ys8g4naT3crjevmTWbgJ0bfwRb2sz2lbQisLKZXdnPfo4t225mxbt4Ji+r+YNIWgwf6QP81cyeL5H5OfAvM/tmYfuxuNng8xVtN5yQTiPv7fDHzvOAy3AzWqVyaZU02nodNxPsgSumc0turpPMbIykqdkoWBVePTnZu4E1zT2+7jazNQagv2dRMmo1s8/2R7aTyB0flqL37zylIHNWgyas4vudYGaH19j2U3rOw254bY584wcluZYGDYXP+DCwDL2/49klck2dMCSNM7P9JJVZDswKE+jpmJXwAdJiZraapNWBbczs2BLZc8xsr0bbkq76nyXvREkr40/dT1TdhMsYMqYeSQfgf/yXzb0s5pb0RTP7ecUhPwE2I82Qm9ndJY9WGWfhEzbrpfWn8RFkqeKXNB4f4efduX5Y/BOY2Xi5j/ZKadNDlnMnzbU3w63Un+R7YwW3Ukm74BONN9LjIXOYmU0oHHoY7k3wCG4zB38CmQTsW/HdTsAfze/DJ1RJfZvxJzCzQyR9GZ9c3R1/VJ4/9euqshFO+rOUKbsqL5JDgV+b2ZOkx115qu5iaPpr6RzflUwRz1Adn/KypHnTdzlX0vM0MBWk0XNZn8tucPlrZQQ+odhn1FhXVn09kQxPuzsROLx4A8wdlw1iRiclVTqIkXQMPsfwKL1/516/h5ntXfEdGrEpcHhh2xYl2ybl3pd6gyVeNLOftdoJSecAy+PzGG+nzYabVPJyTa/5xHXpdR8ze7RmN36J/w9PBzCzqZLOw72NivQyOcpjAD5YkLkad9p4OJl3bgXOBbaS9KGyJ91Sqoz/s9pCyYw1jSeEak3Apu2T6spWfW7Ftg1xu+lN+EX0GLnJmJzcBo2WEvm7gUVz66Oa9Hc53H68NbB8k/Pc8oQ0bvfeKl2AL1TIfDC3fAR/dP9Bgzafx/+IG+W29fGcwEdpI4CRuLfXjyh4S+Rk58FvCrPhdvuDgIUa9GHh3LIEPm/03ZrnZBgNJq/bkQUWxOejLmog81vga/RMbM5d8d95iNxke81+bpna/na2FPZ/AfcWehWYmlsewwdttT+r0G5Tj5mK4x4g5/3W32uensn+2v2hZxI9r1vuKsgciXvavYV7N2Wedy8CxxVk78m9PwY4Nb2fgwrnldJ+tftjDPaSLqi8C+NwGnshTMB9iackxfRV3H+2TPYWfHIt+2GXx80nVW3fDSyYW1+o7KTjo5iVc+sr0cTrIv2AqwPvr/pjFj8rKY76P7r345cV+/6Am8fa/Z3makG20Tm+E/e6uZ3kklr484xscGyppw5wQp1tTfpc12tmZXweZUBlk3yl4qHmIAYPKlq0hc9s6k6Nm+OWwScgl84tpTdXkntzbrkMN8/uWff7NunzReTcShvI1brm8RH/tcBLhX5fToWbdmp7+Zxu2QmP0SmTPa5k23sL61Nz7/8CbNfod65ahoypB3/E+a2k09P6/mlbFZ/HJ2CXwE031wJVAU5Hp7aWknQuPiJt9Ij7Q+BWSRfhppad8MCaIrOb2YzKYWb2N7kXUCkqieiUVBb9eXWJ10SfbKfJnngS7sXyO3xS/GfAOuk7lPEabjapNSFdwuH4+Sz2ZaHc6jB85F+ZliB95j/SxOMv0rnOeyLdiPvsI+kGM9skt+932b4CdU0QWZ/zbQzDJ49L/zM504zS6/z5kuwAACAASURBVLMN2q0tW3Ls7FV9SLwp99jKTIfLU+5Vdhxwp6R76f07V0Wrf9jMVk9zKd+R9EMKwWnmc27/xs1/xX7/w8xGFzafVJTDB1F7SlrNzI5I21aX9EqJbMMAPNwp4H6591uj71j3mt8Sv67Oofr/U+QA3Dy5iqSn8aefPcoErdxMcxs+AMqYKukk3DS4Aq7XkHto1WYoKf7DcWX/hbR+He6fW4q5e1XpCS6RvVbSZNw9S7j9vrLkmZmdnbxJMnvoDlYejj1J0hn0RDfuQW+7ZpFa0Z9mdph6UjYAjLNyr4lf4hNLt+IK7i7cXr6HmZW5tUHPCKZdqmy1k+lRdm/hf4BSb5rEJHDXU2DvNMeTt3fmJ0PyN5XiPiR9AfgisJykqbld8+Gjpiryf+638GC8XcoEzWy+su3tylZ40yyI3+SLczl5jqLvIOYzJXLj8QDDe+ixazeiVXfqIn0mryx5n/URdLfkyUCm+O+x9lJwHF1TrtY1b+7xdJukD1uKpq7BE2b28eSsMMzMptc8LqN43vbF3cdH49HUmcfiqpTfSMsbTY8IQ4I0khmdH0U3kK01AZv2FUeMVdtGmtkrhdHrDKzgK528jw6gR0H/CbfJvVk8NsnfYWYfyq0LN4d8qET2PfjI/R0q8t5IusvMPpBbf9QG0PNmZqKc+58KroAl6/PjSvM4epQJwPTib9bPPm1DjwvjjdbAK6yZbIk3jeHK9kYz+32TfixMzyDmtrJBTPFaa4badKfOHV824m8kP+PaVYPcS5L+YmYfadDO0sCKZnZ9mvge3obyzdr6ibljQ2mOr7KnJUn/IFkr8GjklhRu2XmT9AF8tH+fmZXFDzVlyIz40x/lRNwGvmz68t9t8Gi6uvXNp9Hr4pE0Ap/8WiTdGLK760jcRFTkPHwSMxu9zmgqrReV6i64LT2fZGkrKryF8CeEq4ALU3s7A3dkoz9L7lqqn/dmRPrO2fd6I79uOdc9SRea2S7qCRzqheUChiTtiyugh9PN6Vd4+PzjwFgr9z2eHX9am6HsgNOtxMspyX8EH7EtTW8Xu+wcLyoP/lLuPWm9WFzazOzx9NRQ/JyFSm7Ye5rZb1SRPMv6Bpsh6XjcvfbctOngNDL8ejuy1p43Td489Ux6HZ1ufE+Y2Vs50T9JOg4f6ebNG6V+4GZ2THp7saQrKXGnrjpf+G8yb0lfywZQC+KxGPmqfBeVyGVU3kzSdbof/kS4PP6fPg2/ebV0zSfOSa+1R9Z4bNBW+ADwzHTuLjCzP+f6mXdr7fUVgF4mHEnfxi0HU4AfSDrOzH7ZQn+8naEy4k+mmI1xhbNm2naPmb2/Qv5uYENL2Q3TRXZTXl6evvcQ3Aaed6d7BVfYLbuQFfrwMq4Md8/uzMXRaEG+OMrLY9nTiqSHcJvri2l9YdwrZOVCexPpMa/MaCfX4MY52cXN7BlVBA5ZLmAo2YXXNLP/yROHfQX4BLAmcJSZfbR4fDJ5zU5PJOJewNtm9rmyz5NHXH4Zv8lmrnjkvvNRZcfl5Gb4dku60sy2Uo97pnqL9n4Kks+rnF71GVbiN55MSB8ws3fS+nB8grVPhG0rsq0i6TbcDj0V/56r4Up0fuALZpbZhCeWf7Vy91rl3KnT+oL4df3znEzt3yTJF3+P7KlmInCs9U5kVkqjJwl5wsO1cQ+/PjqjlWu+0O7BZnZys20lxy2IzzvuYWbDc9vHNjrOcnE/ku7DAxlfS//7q1t5css3OiQW/JEVensrTG0g/2k8l8UxuM/sg8BeFbIH1uzDWo2WEvk70777SMnLaOCC2sK5qJX3Br/o88myxuIjvFOo9rRo6vlCzh0Nfwo6OLde6oFBuWdJIxfU0jwwg3i9DcczOdaVn5o/p/gos/T6bEW2jX5fQspNldZXxecElqMnaVlL3634m+e29ftarvnZO1QsOwLTml1D9OR7mq3sPNe55gv7ytyKG7mWb4DnYnoUf5rfsR/nYkphvZaXWXEZMqYe4L40uhwuD0o5CFeApViNCVh5Stc/Ak+rZDLN+kbC/ZAGI2j6prQ1M5si90w5X9I6+J+uFNWP8qub9+Y0eqdwPY7mKVzreL68Iw9xfwl/bM57NFXlAHpb0vJm9vfUn+XIjeRLmCjpRFyRNTVF1EHlofb/pq8ZBPMQ/92BH9ds/vu4l8xEmJHv5YgBkG2VlcxshpnEzO6Xpxp4VCk4sI3vBv6/mxFZnp5SGhabqUMabb9qZi/IUxGsD/zdejsrbF1+NFBtNgXPafN1YC5Jm+IT/FeUyNXy9lILqcBzxzyODwAvxN2SG+UWqsNyuc8WsHy+L9akhkjGUFL8BwLfwJXA+Xhu7mOKQuo9AfssPiLN9hXtuRvgdvKyC8so5A/HL4QnzeyZ1N5YemzbR5e08Qy4h5GkzXAvitUafMe6UX5/T0tGViyi6C0yPPd9d8W9fy7G7bR35QXVmufLt3Gvm+G4//J9qY0N8FFNGV/FlXk+EV4jO/Y66TVfbcqozhdfh5/T2wzyfjztxPySZphBcvxF0s/wibkZf9jizUee++gdfEI1e+w+3Mon3GvL5o5ppQ7FfZJ+QU/6g11xl8Y5gfx8Sq3vlqNVd+qmJHv1WMAkXYAPUm4EtpS0gaU8+NbmfAd+M90H91zaH48qn2EPb/GaBx9oPoO7ieY9vqbj11Tx+w0HftXgt2qHYmK8VuYbeuj0Y9pgL8CV6fUxXAlly2PAo/1sewrpER0fpf0TV/zHUJGOuMX2m0b5FeTnbtJe7RSutB58Mxu5ILa0bR5KAmFIpgU8zezqaWkrXXVJ28vW2Za2NzWDFOQnlix/rGi7sn5DP2VbrUMxFz7ncmlavoo7MAzL/zatfLckPwyfnJ+Qlv3J5bAv/t41v9v9+FPDAvi82ty5a6t2iuEWr5e/tHvNt/l5lUGKM3MZSpO7K+EX8TI0qCzUZtsL4HMCxbYPKsjNSOgl6VTcvnh0Wu/lOpm2jcKfElal92itagLtD8CX8JD8tSTthOcF2aIgVysBnaRv4AmcXsC9H9YyM5Pn+BhvOTe4Cg+LGVg/3R4l/dXM1m4uOUN+flzRZV5AN+FeXEVPkrLSi5PNrJjjBEn3mtlqZdvKfr9WkHvqvEDfEXSf89ai7FTrCZxaXZ5r6A9WMoGeO2YOPBrYqMgP1UlUo9xgksu75PZy2Sz7XQeob09ayubZ7jWfzMIn4HUdlBaz8lTgP8adGpo+WSXz58l4zrB38PibL1v9vEC1GUqmnovw0c8ZNLYNA5DsXucDl1nztMxX4RFyzYJZhkuazdwevAnuKpZRdi7PxX/wLfFI4rF47vUq6kb51UpAZ2bfk0cjZilcs7v8MNx0lifvoloMGjH6uqq2SqumhV/hTyxZwNReeDK9HQAkrYKbP+YvzM+MJHeTLVDXDEL6jFo3n1xb0Ds6vOq8tSLbUuCUvETkeNz8KDyQa6yVlPusY0JS6y6PUK/cIMAC6bcTMDL3O4omUd39IP8d2r3mfwBsbfV86LPBRP68Vpksz8NjJLZP67vhOmydEtl+MZRG/KWjuAbyG+B/sC3xSlQX4GagPhGrdUcXrYyg831W75TBTQNnlKL88FDy3czs3ML+281snfwoSQOUXrhTqHX3wbInqHxQz7Z4auht6B11OR1XMn0m/uUBgF+kJ6DuL7jd/7+4meE/BfmL8ZtP3gV1DTNrmKN+IFGLgVNyt+dPWQpyTE/K5xf/O5JOw01AG+GDqZ1ws8Q+Bbm2XB5zx2+AK7QFcBPRMdYTmX5Wo2OtYNuXtDPuvjhd0jfx+Zpji4MHVdcQEHCamRXjPFpCTYLG+tHuDD2R29brfy1pDTO7u+/RPmdhZr+o9VlDSPEfjWdsbFZZqHjccPzuui9efq3scezLwH9wD4GGbauFIgiSbjOzdeV5dU7B5wQmmNnyBbmR+OhvCXyi9vq0/hXc/WzbgvwEPAtllnfnYGCMme3W6FzUoezJAaA4YpQ0G+6Hb5KWSv34u5UEb7XZj1txL4g/p/WPACeZ2XoFufXM7NaB+MySPjS8+aT1kbgX1sNpfWd6PJuuMbPn2pHNHTOnpaJA6clkBPBfqygUVKE8KrfVNSGpZo79tH04PuDaGzefnoM//X4U+L6ZrVQ8pqSNHc0dEcr6vD7u8HAiniF0nYJcqzeUWtd8Tv5k4D14Tqi8vuiTD18+gV3Wdp8JX3l66JfwQarhA9cF8e+Jmf0rmdF2NrPJhWO/gz+F1DKPDSXF/1jJZrPGlYWycna74qODK82saOJAHpzyPby+bXZCGrZds89b4WkalsJHbSOB75jZ5QW5y/Af/FZ8ZJfZDg82s17eN0m+VgWwNvucd3cbgccCTLbewV774jbO/+AT24fhE99r4l4MJ+Rkl8QLhGcK/FB6ojjPy0Z/Jf1YA5/UzB75X8KjgqcW5H6AK4HXcS+T1XG76G9yMu2YK2rdfCSNw2Mofp3WH8FzK80FvGW5YjetyOaOKZvDaBQE+CvcXJnPDzXcCqlKck+Nt+HmsxfxFAB9KrY16EefG0ra/ig+WXxm8clL0ilWI+GfylMV3GleOe04PH/PeWqQzqEuda75gnzZjcWK5zjJfqXQ9lZ4/eEy2TIdl29/OUkfxM3ee5jZrZKEu4CvDGxbYk6rbO1dueB+s4/j8wIb4QmSqmQfpUYh6w72NZ9jezj+ZDNiZp/D1J+lgIsL2+7DRyKjcXv9Imn73BRSZeM2yq1y6w/hTzLfokaOdvxmOTK9P6RkfxaUtD0+4T0/hcAwUhAbvT03ZiwNPnsNPAX342m5E08Fkpe5E3qlC897ZP25H7LvwZPSPYDfULNAwQ3x0qBVfZ4TL8RySVq+TIkHVTr/C+Beac/iborHlMhlOfZfo2+O/d8UZM9Jr98cgOvuyZJtV+Kuzo+mvs9Z/K1LjmlYQ6DuNT+A/6c58ewD/Wljddyde3N8Ev3ist+4YRud+HIdOmFzA9/EfdEBVswrlILsMODr1Hcru5YmrpFt9nlZ3CRzCQ3ydtM3Gq9RvvWNUnv3pWUCnpqiU+ddwP2FbZW53ilEMJZ8t/yxf2qxL/8o2XZfej0DN+X16VNOdgHcd/5DwPx1fr/0mr/5LFuQKdZGWC33vugy24rsWHzUPJ3eLpeX48GIA/kbz1l1PmjB5RF3z3wvqV4FHpE8YxmA33pu/OlkxbS+OJ6hsqqNllxhG13zhf0r4XW0s2I3q1PzZpfOS2ntBdyzsM9SkMnO5/r4XOMFeFxBS+d4KHn1nIXPwmfFtivLI5rXUt3ZzL5fs+1X8XzcE2kvB30Vv8NHoVfQ2FtoDfXkGxceafgKBTex5IXxM9xD4Dtp/1rAryR9ycz65ORvFfVOGDUM90ooet7MJU/2NgyYQz2J30Rfj5riej7j6SKtdq9k2xXyvD6vA1+Qu9D2msBPtvHT8cngx1I7S0u6FPi8VWRLxUdSa1nvx+cJ9E4P/Y6k91gKwDKze9NnLkHf37y2rHl+lvFltu4y2jFnqVCPVhJWqEdrKce+pKItf155IfF/5LadhivE5fD/ajHCvZgTqbSv6bjFSr7Da8ksupikzAz0YMnxGU1rCKR+1Lnm89Qup1j4jsPxBIJVAV15p48R+H9lCr1LRebTm0/H59b+mtYbeSL1Yigp/uXNbFd52HR2EZQpgowbJO0IXGLpVtmA36VloPmvmZ3STMhyCZuacBhecSc/q3+XPDXFTykpxtIG+XoBb+EeIcUoxmfxJ5ni+2w9z3RJK5nZ36BnwlzujtlqetwyhXZEsvP/2zwVwav0jW78Ju5LvZSllLyS5sO9ZL6VlhmoNVfRE/Gbz1dwUw74zfiktK9d2ez7Xax6kbsHp9etytopopr1aHP8nh6FMwJ/mn2IXJ3YdK2fIukXZvaF0lZ6U6uvuT4fiI/cn6N3bdyq5HZ1XWHrXPN55jazvxbUz1sVslsVZJ6zQnqQDCvMP8rji4oF6Jdt0K/aDCXFX7eyUMb+uK3zbUmvQ3WQheWy3w0wJ8szFl7LwOSbeY+VuHKlEUefEVI7WO9MgAvi9s6izIYtNHkUcKWk79Ezivogboo7uCisvkXGZ+yiJA+QpE/n3ud35RXY9sDalovnMHcJ/CIev1F0jVwZ/8MuQO90HtMpFKk3T9/8Aj7ae1/q+324LblYQKe2bO47lbpdFuUspRGx3llUF8ELlZedzzHAqjUGRVn7vbLgyvMeFQMGR6ano2+oJDjKCl5yVp39chhexau4/2C8lGldJ4Yrk/I8Eb/2jJLiTXWu+QIvJP2T6aKd6EmDnbUzN/C/7DtKWhl3BX8c90ysw6v4DTbfbnFS3/A610/WbDMdNYC2wk4ueCKlm/AAqHPTCdywn21emF7voffE1VQGIFsinhTtqdTvzEZbGRZfo73KTHyN9rX4GTfiI9uFcLPI7cCPCzJ7UpLpFPdz/1TJ9tVwRTw5LePJ2bf72d+f5pZf4hN/EwoyjbK4ltYqxh/Lvz4Qfezn95taeJ2XkrkRPPfPjfj8z5p4/MGzuKPA5iXyterRNulbcc6imC7lsdzSJ11Kus6OxM2Xn8Bv7gem//ZlJfITSSlI2uhro3mMptd8QX453OX6Ndzk/Gfccy0vczM9cxEr4Encfoqbwo6vaDdfg/j36RweX5CZWLLcjTsBfKDu+Rgy7pwAqlFZKCcr3JVtWTM7Ru5rvriZ/TUn06/glBr9fQQfVVXZkFtt72X8guqzC1jfzBYcgM/IXOY+h5tGjiq67Um6HdjE+gY8zQPcbC0E2g002eOxmW2e23Y37g1TZhqcaBWBb2oxzUQnqOt2mcx9X8cnY8cBW5jZbclsdb71BPpl1aPmw23ZzerRZu3ni6wMw01UC5vZZgU54ddN3vZf9d1adWM+E38a+32hz30K4yT5soCvY6wQa1Lnmq9ov7Kconrn/T8Gn3g9QJ5OY7KV1BGRB7tlvIVnjX2qUR9yx44BfmRmpTEJRWZ5U0/y2f2RmU0zf8T7fW5faQBJ4ue4HXBj3Nf8P7hNd8YEipU8Hufa/gter7Q/3IubC57vZzsZRdt1nvay9PVlNnnK5V3wbKhlzF5U+gBm9qoaFJMfJPo8HuPKsDjZmNFo5NNqmolOUGauKKu4NJv1FFn5rpndBmBmDxZMYO1eJ/nMr2/h/8M+k85mZpJ+j2c+bcZyOeV4Bm4uGW3V9aD/kZY5qJcS+ltmdpE84Ovj+Dk8jb4pEOpc86iiMpt60l3nb0D562pjeoKw3pRU6uhhZjclk22mox5u8v3yx06SB+HVYpZX/Lgd8VOSvmh9a42W5dHOWMc80dmdAOalF1vJH167PmgDFgAelHQHPSMUs0Ikbl2sojj1APNdPOX1n83sDnniqOIFOJekeayQWzxNmPY7R3srqHf90+F4QrwL8zJmtkybzdfOsyJpWTN7rNm2VrEaJQ8TeWXyemHfDCWUlMt2uPnhHjO7pmY/vgNuu7bmua+mSPqQmd3RRG5GfiTzifmnGij9fB/mTet9Bh8FsknrLXE38N9L6uN5Q71rHjz7LPRNf17GVEkn4aagFfB5vuyJtBRJu+A3iBthRknVw8xsQrMPSzeM2uabWd7UkxT3Xni+j5uBr1hPCHujIsy3466fd6QbwCg8zUKtKD+1WBy6oo38o5vwkPXdzOx9FYcMCSR9FX80/7z1TF4tgz9R3WhmpR4qJe1kCe/605cN6Lngs8fjp/vTZpv9aCVL6GJ4MZb3mtkWklYF1jOzMwtyC+OFP1ZJmx7Ao53LUom8jT+VZJPgmXIWfrOYPcn9HJ9YvgX/Da/I3Vwafb9aGWGT7IO4snsi1ycrmk5yfc76mfW71BFD0mp4+ods4vgF3M89X583L38lrng3xc08r+P5iDqe00ruiHIw7kX0K0tOGXIX2uXN7JySY+4GNjWz59P6KOB6652rp6w+70K4rjvYzMoKzfRhKIz4zczulbQ2nhVvsqRPWSF0v4RT8NnzReUeJTvhbn0zUONkTlWVpGqTRldr4n/enfGJo9P6224nSRfbvvRNUf3Z3PuTJP0HuDmNvjKf4uOtkCQqjci/VDSnSfo4nmW0UWGaRv3MvH/6ZFWU9AYe2fgNM7uhnfZzn9PQlVLtZQn9NR6XkpkV/oabk2Yofkn/hxcJuoYU8YubAL4urxzXy3/d6rsEfwxPNPe23PPkT5QUNCqhVkbYxGYV23vRQp8zxgGHmtlEAHkm0l/SE9tTZBc8uvUkM3s5mXMOKwrVueYL8uNxJZuvP/zDwn/kdeD44rHmKSyqKgcOy5R+4kV8PiXPpMK6JblDC8c2ZCgofgDSI+BBkrbAfaEb+seb2bnyTIVZwNB21jeNarsl3RoiT9q2e1qyvOsys43abbPQ/s5mdlGzbW1yGa4MrqdB+mszOw04LZl3KJvgSlyAV946E79xj8KVyNJ4dGpbmFnl47Y8SdhquPdXWzeW1E4dV8rarp85FjGzCyUdCWBmb6XRb55jcOXSy2wlj035Hp5qoR3eNLO30+c2i4XphZk9WRCvuj7KroVWYzbKmCdT+qk/N6YJ1ioWISlKNQ74qnXN51g9U/qpHy+lAV5/uVqe0PH8tL4rhdgcGyjXc5vJ7mrNFkqKGOOz/1fi2SGL++bGJx+z9ZXxfCUDGubepM/v4C6cK+S29av6V6H9smLPlWkeWmy7suJXTubQwvJl3BxXVflqfjzK8RH88X8/6MlZ08HfYf+K7UvgczijaeAeSE1XyrRvvRb6dSOwcPab4Z5qNxVkHmpwfOW+Gp+dz7mTz8FzD43dXifgI+speDDcV3HvqTLZx3EF+gI+Gn0bN7lMAT7Yj75fisdcLJOWbwKXNpC/J/fdHsZNgfeVyDW95gvyd5OrPoebWkrdgltoU3j8wA54QOSPgO3702ajZSiM+PuMys0fabaSp0gucjVeZ/NheZ78W/GR31ZpwunIjvbW2QEvojBR0tX4qLf2yKqK9LTzSWCJwhPPSKojB1vlSkmftMbpH8pG28vggTtHm9kFhX2r4hkP/4oHDi2GP212tDKUmZ0OkEbWs1uPieZWPBPrHHhMwXEVTRQjP/9FdRGU/eRZS4t9KDMXHIqbTJZP3mOj6Fv4vlFR7v4U7P6/No/7PJ4RdglciV9L70Iyea7DYymuAZD0CfwJ5Szc267dwiKfxVOVZOmP/5S2lWI1gs4Sda75PD8EbpV0Ef6/3gl/Cquk2aS4mZmkq1Kf+6R3Hmhm+cndPGlyp1jG8OyCTMv+sx3s7zy4C+buuCfI2fgIpVjUu257a+CeJt/FMw1mTMf90V/qX49n2M7nAd6kRzGblUQ8lxy7ED4ZtVZu25l4QNEB5mlk58H/vJ/Es222dS5aQdIU4KPWUz8h89sejo+01684LiuCsjE+cQ0VRVCSCSZjBB4t/E+ryPckr2ewMq44+pRHlPQUvVNhzNiFn7dm0aUzjfx/MLcty6XfrxKXHepby9d8mpDfGLexT7SKEpNpMvcM6k2Kjwd+Zs29oYrHZfWU66VkZgjZ+OWpDzbEFf9VwBZ4xFwxt0jL/rOdIima84Dz0gTQzrj7aVvKztwz4G5J5xUVxUBhDWznNY79V4nN+F5gP+uxK78KfDVd5KfS5rloo2/5UfLJadvbyfuiF5I+hKcFPiatz4ubCx4EflzRfrFoyPn49dkHef2Hcy15o0haUNLuZvbznNgvqXYb7JN2oNPUmdDM8Yw8qVu+xOVz6Ubb8n9Q0k/M7BD1dt2dgbUWdPbPkuNrXfPqScPwPzO7P83LfBL3uqqqLfxj6k+KrwPsIamhN1Tqy3n4U9jbeIXBkZJOtpoedUNG8eOPU2vgNv+95S5xvymRa8d/tlZJt/6QRuPj0tJflpEHthWffvpbFxcASdvQU2f2RjOrNdEtaSM8EnMGZlalKO+RxzcMBvNKmj27WVpPIZQ5cTNZkdPxgB/Sn/R4PJXAB/Dfr2iWKWNFfC6qjH3NLHuCwHxycF/cDJJt+06NzxhMWpnQ/BSeoylLfPiXtG04PTWUWyFzfWw1+KxW0BnUvuYbmZHXNrMjytq2+pPitbyhEqua2SuS9sAzjh6BBynWUvwdmTjoxIL735K+3Ej8btinIAXuhnkEPqpbI7f9w5Tkl0n7ssm79fGJty2B22f2d25wLv6MeytNxb1jjsaLgA9E28fj+UQ+m5brgOMKMmW5jZ7CbfirtPBZfXKud+h8fR8v+D13bts8uM35uBL5u3PvTwWOzq2XTgTi5rZXcq9/A3askL0HehVkGU7JpGOHz8miJdtWbiDf8oQmrnjnHcA+H1xnWxvtNr3ms98t9/4Y4NT0fo6qc0ELk+K5Y5o6H+DJ/WbHcy5tULxum37nwbzY+vnj/Bx3mfs8PkN/J3DWALV9Z3o9jpRkjBJvolllISVkK1yIA5WkbSq5amVJKU0tyCxdWEbjrnatflafKksdOl/D05/7BXzgMAVP9nd82R8LN0/Nlt4/CHwsv28A+nMiHl28SVouxM0mg3kNPQTsklv/Co2Lj3w6nYtj8OyiD1I9kHp/+n8+kZbJDEBSPsq92Sr/p/ik+Ym4afiP2VIi1/Saz+Ry7/+Cu4hn61XFfxbBnwqew1O3/AbPcZSXOZJcZTA8LcXUdI6PrGj3INyqcRU+CF6aFgobDQlTT7IbH2f+qHla8pQZac2DuOrytKTT8Qi/E5IJoBg4MSvxRprQeVjSl/ALoHaejhosgHuwQE/N2xlYC8nrVJKeN9vFAHg61cF8fuEIeUHqLLnZI+ZBNmWcD9wkT6H8Ou49Qnq875UuQX3T5BY/u8xceDieNjzLWX8dBbu9pB2spHj3ALIhMC6ZORfDo4IrE9KZ2dkpLiaLRdnBKiY0cVNZMdBqHNWBVg2R1+D4FLCspHy96vnouU7LOBePodkKHzCOxW/4ZTS85hMtm5HNE0nu0aCP4HN/+SL3L1rOyiD7agAAIABJREFU+YASrzNLtQ9ym55IptZaDBmvnrLZ+AFse248wu8eM3tYHuH3fhsEj5N2SJOPD+AX6zG46etES4m5+tn27vhIeCKumD8GHGFmv22zvccoj7AFBq6wRJM+ZJO1z6b1T+PuhU/gZpyyFAjr4q6b11qPN9BKuOliSk5uYu6wD+Kj2wyzioLdNfpcWVB9oEiTzEfiE667WaEwesUxi9J7XqlPFk5Jd1shLULZthb6uTSwLK4A83b06fgovNSVWSllhnKZNiXdYWYfKsjVuubVXhqGppPixd9a0mesZx6qKu3HnPg1vAy9o42rqnv1Pn4IKf62XJ3SsU3dneQZ/FY0s7PkIdzzWj8TbA1V0o0v+3P8NVOYQ5Xkzvlxc6+jj+HeJtlk7f+ZWZ3J2jqfU5k7qiD3EXxeZmn8T5t5byyXk+mo4pd0Pe7hchAeOHQmnlL7qxXy2+D+6+/FTRZLAw9YSd4peUnLKfRMyu6JB25tP9DfoxGSbjOzdeXRsKfg33eCmS1fItuRa77smihuk/Q34H3W16V3Tty0uGJJu1fjT5+TyU0Wm9kPa3WsVTvbzFpwe9dbeA6WOpGG5+Ej4XlwV6ungMMqZI/CiyD8La2/F/jLzP7Og3x+NwN2Ktm+E544qt1298y9/0hh35cG6bu1PFnb5ufUip5O1/IWuNfPwtlSkMlH2OaXhtd9C33drrA+G57GuPIcpn5m82EbUVG4HC8ofgqu/KfgjhYLDkCfs4nzV/C6ym8DrzSQ3wo326yGj+YnA1vn9nfkmi85bw0nxWnR+SDt79dc04Bc8IOx0HdCcWlg6Qbyd6XXPfCRyuxVfxi87qjITRQNxJ9rKC34ZNWoku2LALf2o90pZe/L1jv43To6Wdvq96GGxxjutVF6zTe67jt4Diel17tJE6G04EXSgf4I2I6KalZJZjywQG59IdxEk6135JovtNV0Upy+zgeTaeB8kI4Zh5uj2+rXkJjcTRxrZnvlN8gLRu9VIT+7vCjIdriJ6H+Squxab5qZZfvVOPHTu5U5zazPxJeZvdDP86GK92XrnaL2ZG2rqHea3CVVSB5o5ZG7EyWdiIfmV9VifsP6WQGuor9VNY2zPlRFq76cAtluBs6V9DyF1BGFideytksDrdrBXPv9Th7YWeo/T9/Yg38VYg/6fc03MyNbjUlxa935ANz1/DNpDu0NGgR7lTGUFH8vW2Ka8W5U4u90PFnU3Xj64KXxR8QyLkxePQukQJrPUl7laJZA0g/w0cPreFDJ6sCXzawsoK0uI1WSHz/dPPuTotoq3petdwQz+56kG+iZrM0+dxhu6+8P+TS5kyulepPlqhmT22b0LvDSkZzxlqJU5elMnsHt8FmZ0qo8ROCpR/6LJ+TbAzehFCcS1wOexG+0tzPAN3b1Tns9DD9/lYVbgGGSFrSUyiR5mOV1XlvXvFqPmn0QD2ycLR0/2komxZOiv6fB98mzRU25Umb5yV15gq2v07e4xJt4VZ3aSdfKfuTcvk3pKfh8jZld16+OdxClfCeStsftmIfiE3NtKwtJx+NufV+yHi+WeXH77AtWXeKyWbuv4Vk5BSyf3pPWlzOzbny6akrdieJ+tN+W542kkfT2IvlXbt9w3CV6d3ww8nu83m9poZQ2+nxWbvUtfGD3S6vIQ5+8t76OBzmBu01+z5L3TbvXfO7/twce5X8EHkdTllrhQHwO8Tn8RtHSyLykvZHmEbulbtJW4qFWykDYsQZjoWKSo4H8wfRE+J6JTzJ9YmZ/jwE6F/el1zOAzdP7ftlb8T9zlZ1x9n60W2mnZibYqmeVBY8O/xqebO/b5AJ40v6Ozn/gxUD2wO3Lw9L7WxrI7w88iyvbR/GiQpWpxoE5gc+ka2hQJvEr+rEq8KW0rFrY19Y1TwtRs/hAZ+H+fo9ce1em18dyv0O21E79PsuP+DOSC9xd5gW998TvtCdbhR00G71I2gy/aL8FnGO9/WX/bGbrl9g9S0u/zSrI8/Rsj5t61sb9+a80s3bT3ebbnov6dsb+fM4wYHczO7cT7c/KqKLAi5ntk5N5i54n3F6HMwDXprxU5snAR/Br/y941s/HK+QfxmsOvNCk3Tnxm9ruuI/55fiEatvlMFVebnAGVpEBtYX2W7rmJR2EB+HdjX/X0cBvzOyjJbITcQ+hltKmS/q+mX29ZPv6ZvZnSSOsQX3ipu0PIcU/Fbd7ro6XrjsDDznfoErePA3syXjSpUs7/fg8GCSFuS5uN/y3eYbJeYD5bBb0t0+mgQPw/COX41GqX8JTBNxtbRaeH8rkrs3sdV7gD3nFMatdq8lvfAdrkFNe0tm46+RVeD6aewfos8c22m8DVZWqH1SZkeVpyVfGzV75ifwf5WSK1QSFO62cnWQPyslmQWn9ivMYSpO7b5mZSdoW99I5U9I+DeQnS7oWj/g7Ul4isDQlbIW9bLp1KPVxfzCzdySdmlcK5vbJ/hTn6CTn4BNbtwKfw22uwv3I75qZHRtI5FG9vwAWM7PVJK0ObGNmx5aIZyO1rMDLizSeWB1wWuwveITvLZJup7cCy4+298Svw4PxMqkzPo5+PKUUFXu6UWJm/2mnvf6iiqhZ+k52g+fd+QeeyG2Oiia3x1MzXEvPhPhulDsL/E/SOEo8yKD+089QUvzT00TvXsBH08i3Uf/3wSMzHzWvLbowsHeF7BQ8evEl/MQvADwr6Tk8hW5db43B4gZ54Y9LbNZ/ZFvOegrjnIF7kozuz2PqLMov8ULepwOY2dTk/VGmSK+Q53c5Eb/2jL5eZANRP7kRrfSXJPdH3OukdABlZh3NbyUvxHQO7o8vSdOAT9sATR63wGX0RM2+0UjQ6qXXXhX3898c+KqZ/VPSURVPMlvhKcM3o74XWR+GkuLfFU/UtLeZPSsPvW/kEWL4Cd0KvxPPQy7HSIFOlYrrFPvjnjxvS3qdAZyTkLSPmZ2ZWx8OfLPmBVzGjKemZJZ66l2o9MGjLv+q3nnXyx79hwE3mPuXXyzpSmCEmRXjCWaX9O3i8QmzVCSm0/3N98fMDm2wfzAYR9/kb7+k/eRv7STYA1jSzDav+Rmj8En899E7x9HGuffTgUMkfRCPkfg9FUki0xzLBZIesJQrqB1m5QyUvUj264nAtpIex8v3/aTBIT/H/Yp3T+vT6SmfV2TdTOmnz7oWn8i6DfdOmKUws/nMbJiZzW5mI9P6QE1EbyLpKkmLS3ofcBvVlaDqsIakV9IyHVg9ey+pdqm4IcALkpYnTUJK2gl/uumFmb1D7jo0szdKlD7Af3CzSX4x/Em2Ldfadvqb4w+S9kvXxULZMgD9aIV5MqUPYGY30njw14wfpuVUPO5gHH4juZ1qXQFu8qqbMPJcfD5uWVxnPY77/vchWRY2xp02Squ35XhR0qWSnk/LxZKWrNmnWd+dE1gJ94N9MJ2MA4Enahw3Jb3m0zBUuVxdi/+ZMjfDr+FPAcMZpLQCLZ4T4fbUb6X1pYC1B7D9XXEXtyco5NeJpfKcLQdcj3viPJ2u1WUqZE/CnyhVs+35gG/iLnsnUFJEZYD6u3QD+cdKltrugwN0ji/FvfOWScs38RrW/W33EnLpD/AJ6gkN5O/H44geokn+JHpqZ+Rz+d9RkBnd4LM+WrH9Otx0PVtaPgNcV/s7D+YP1+aP8g4+8bFCblvTCw6/a89Q3HhRhtKiDXhujp/ixSPuBH6W5OfIf+6ssuCTcqfi2RHBk2LdMUBtr4j7eJ+Oh+efRi55VCxNz1/mYdVIZnq6rt8kV7WrRG4h3Ob+GJ7Ns9+Jzqr6m/4re1TIDAN2nQXObaeSv/Wpfla2LbevdkwKcFt6vQZ3/VwT+HtB5lF8sDk8ty0rLTupot0+g1haSDg4FGz8O+Az3BOTS9kF1AsFPwUfISwq6Xu4r/Q3ywTN7WYHJs8fs97eAo+UHTOTWcfM1pJ0J8yof1rlMdAqV+ABN9fLDcCH4o+mfdLvBj0UPT0y27mV5Ee3GsW95bl8dqAnGdeAeLAU3Gsvw0f9B+DutVNx00Sxv+9IOgwvajLTME+9cBCQ5bV/2ZLG6ydTk+NBlvJkD/xc9CKLmsVv1HU5VtL8+Pn9KR5U+uWCzAfxoLG7JB2MVzA7FPgBnuStjBdSPNP5aX133DusFkPJj38ePF/I7rgd7Gz8Ma+yWIqkVfDSdsIn1B6okHt/ai+zWb4AjLUB8kMeaJJL3YfxUf5aaQLpWhsAv+/cxZ3ftpKZ/a2/bb+bUQv50ZNjQh/M7OaczDu4x8hbDGBwoaTL6HGv3QRPDS28WEile608vcELuPKf4TpsdVME9IM0yX2hmT2YbrB/wGN63sZLpV7fz/ZH4NXQst/lZuAXVnBCkHSlmW2l8uJCZrl6Cm3242Dgx3jdgHXN7KkGskvjN5L1Ul9uAQ6ykhxApccPFcWfJ93td8YfPzdpIDccf2TK5xYpqxh0C/AN6+0t8H0za8tboNPIc4Tsio8Ufk16mjGzfrsASloMzw++hJltLmlVfKL7zCaHdjWS7jWz1WrKXpFbHYFHX0+2Nqt1tYJylezS/6OWe21SdkX6rezqIOk+vGavSdoP9+7bBJ//G29mlSUjB7gfLUfNpkHZvvStlJWvwLUAPnezDm7y+ST+/Q42sz+WtDkcONvMmpV0rGQomHr6kB75xqWlFFUkR8Ijf4v08RbQLJya2czOlad6zZ5mtqt6mmmDX+NurN9I63/DR3mh+Btzi6T3m1nT7IpmtnV+XdJSNPZQG0jacq+1QSiR2YA3cyadzfDEb28DD0jqtw5T34poAJTc1E7GB1u34Clj6nAZngb8+v9v78yjJKmqNP77ugUbRECOijuD7I6yKByQw4iCjI4LiIqICwpuMyKgM6Mexxn30XFDB3dFGRTBhWk3FMWWRXahG7ABaYFWxh1xBXHr5ps/3suuqKzIqlwiMzKi7u+cPCcjMuLF7a6sW+/dd+93KawEu1hFykI8xqn692xJuwMflHSz7SOKF+ef2zaSNrb9lz7tmEUjHX+fHA/sZLufuNdaSf/B7FZxa8dmWTXcE7jDuVWkpG1dTavIe9r+XC6Ww/Y6Sb2+sIseSdeQNmrvAhwlaS2D66P/GNhlfFbOYrdCGq2ATfLxgiGkXED1EGbno39ynMZm/pyf/QuSvlGxPeSmFYz/cVLcfVaYroRhqmY39cLKto/qDuvksNu+SjLxZawFLlLqgVAMvZ3Q4/pZtNnx/4j+m2wcTcqxXZ6PL8jnphKl5hN7kjRATiYpBZ5KEtwalT8oVTl38rv3YcRmJS3n/qQK8b7RbNGxJfn+XsVClWJ76TD35e/co0mO/2skPfgLyXoyY+Z44AxSpt17OhMcSU8gZeGNyu9sn9XHdcNUzZ4p6Qm2v9brgvli+bZ79QW5Kb+WMESdTSNj/P2gPsSRmoqkq0hpYas6G7rKgl8VjP1w0qbRQ0ktC+8FHOYRqgTbjIYQy9Js0bF1wA9tX1StZdUiaTVpQ/VKJ9XbrUmKlAfVbNrI5I3rpczfEa14/W79/j7kosW75XH/ypQo/7Z5xr+gOFLeZJtP7rWyVnEVM85WkdcC+5P+aIpUpNKYCu8auLeknlIGZRMNFzRYcqLCA8dkW5X8Mad1rsspobfQDLv7oZ+OaEV+JekLzKywLyBtxM6ZufeTujsMSnLPc3xXvwkCrXX87k9b5l1jN2Q8jLNV5CV5BrtB+ErSKvrfzFpsLAU2o7/aEgAknQccTPr9WwncIuli29353dPEFTn75GMkm28npYQ2HtuPWfiqWZwMnEbKLIS0J3gyqfsYMJIOUL8U9zmWkWpI+tb8b12oR9J7bb+812y+1yw+F0DtmA/XeAolmSFJEgIPAHamwlaRku5DilefSkqX6ziyzYEP2955lPHbypChnitt7yHphcADbb++qlDdJFBq4rK57TlFTmN+7l1t/3mhc0OO/UTmCqmVySxvaPLUde4q27sXjjtZgstIK4mrSb9Tu5KqcR85qs0ldn2n39TWNs74O5k5fc/mc97+KSQBJQEPlPS8YkHNtJBDPF/LudhV9gV+HEnv4wFAMTxxG0lDPyhnmIbid5F0X+AZzKTNTj2S7k8h5VHSoyb8O3IJc1eeZecGQj06os1zy4JVs51VhKTlwMM7ab45O+kNo9ibxykK5C0hpZlu0e/9rXP8ztr5ts/vnOvEUeeZobyb1I93Tb5+R9IP9RFjNndYVknay3apyt8w5LjzKZKeZvt/qxp3EdCzgHAe3kTSbrnQ9uWSHgzcUK1Z1SLp7aSiweuYSXk0qcp13M/urEY3kbQHs1ejVaRz7uuZjmhvlPRuUnVwL44mJUC8h5mq2V69PnYq1nbYvkZSFam7K5mpHl5H0nOarzHVLFoX6ulQFkcFLnKJpnjZMnual96Srif1CL2ZlMM7SM74QmOXdhfqtewNFgeS1gC7VhFWGeLZzyOtRvcErih8dBvwP7aXl903wPiX2d5b0qUkfaRfkUTati+5dqCqWUmfIe2HFHWANusuypo0rZvxF9jC9u9zHPWTnThqj2uv0FyRpit6XDsNPG6MY/fdXSgYjn7K+KeQtaR6kYl/JyawGj1TczuindTDlkGrZp9P0gE6Ph9/m6SuOxSSXmX7Hfn9YS7ItKhHg/bScVo8419N2vw8haTDc3mvWXye5R4D7JdPXQB8sI7ZzSBIujezN6P6EmhaYMy+NWeC4VDShrqAuYJuUxdiKxSb3Z+Ux/8tevfcHbctY1+N5meUdUQrXvNJUqX1vFWzeXWwYoisofns25BM0J1YMEiiQZtn/H3HUbODP4HZm5pTi6SDSfsS9yOFsLYBvkc10sl9a84EQ9NPGf+00Fn5riQ5ujoZy2pU0mHA151aIL4SeLikN9vuVRXcV9VsXh3cKWmL+f6QDGpuj/dlx70HaeuMfxDUv0jTVCDpalJxyYqcFvgY4Dm2+97cmWfs60j7Bz9gcM2ZoA8kvQW4eL4y/mlCSTBse1LcuyoxwGHsGMtqtBMJkLQfqfHNO4HX2R6517aSDPYepAy84upgqJVSVTP+1jp+SSdTnsc/J46aN0vniDS5P4G3iSPpCtt75j8Ae+SKyjm5xUOOvU3Zeds3jzp2kJjWMv4ylMQLn0v63dgbeJt768eM25aPAu+rejVaqKt4G7Da9mmdcz2u77tqVrPlOYrXnlJ2vg9b1zOT0LEJqXUm+XiZ7Y36GafNoZ4zC++XAYeSGhyU0a9I07TwW0mbkTaKPi3pFgqziWHQcN2FgiEYVxn/mHgmsLvtO5TE+75OdVXig7If8Hyl3gBVrkZ/kivhDwLenuP888mUDFI1+1nSagngRvep498LDymy101rZ/zdSFpCivfPaa6iAUWa6kZJm+ePpC/ns0mFG58eZYWiMXcXCiZSxl85JeGElbZrqW8Z12pU0qbA40mz/Rtycd3DPE93v5IxZlXNKvUJeCsp5/9mcmEoudeFa1YGWEyOfyfgqz1yc88tucVlS7c6kbQ9sLW7lBxzbPJntm+qx7KgH3p8zzpM3fcNQNJvmSnSEvB3heOJCxnm7/oOzn0oSDnxQ/ehyJk313oASZIeVbMn2t6pcM17SBu/r8ibxiiJ272LJHh3PDXSWsef46jFf9zPgddMY8pcv0g6k/RvWN11/mGkVpFPLr9zoGcs2A82WDxI2n++z12okJ+ALRv6UNjeUdL9gM/bHqkPRd6APbbfdOiuVXGnavZNti8sXHMDsKO7HGz+Q3O97R1GsXlUWhvjHySO2qBq1a3LNrZsr1YSzqqCVxbeb+gHS2+J2qDFTNKx98Gh5D4UALZ/KqmK/ZJ7ANdK+g6zM29KVzPurw2lu51+PrleWU69Tlrp+HN8bb1tK/Uz3Zu0sXJVj1uaUq265TyfbVLFA7pXDZpsP9ggmI9x9aH4j34uGrBq9jpJR7qrNaWSuNv1VRg9Cq0L9Sjp07+dpI/xZtIMdhVppvAJ228vuacR1aqSTgfO6U6ny7IUB9k+fAzPFCkG+pCqxw6CQZD0r8AOpOybt5E2Tk+z/b4Kxt6GtHewIm/2Lu3E5gvX9J1Dr6RkupyUhNFp07gnaYJ2qO2fjGrzKLTR8V9LSvu6O6madRvbt+Yf5uW251S3jis/uGqU2t19AfgLs79MG5O+TD+v4Bll/WB/aPs5o44dzKAuiWOYzn2UXLx1dVnYog4kHUSFfSjymC8CXgxsZXs7STuQelAc2HXdhtz+7jz/Xnn/kg5gpqL+OtvfGtXeKmhjqOcvtn8D/EbSjbZvBch5yLNElZT0fEz6fzhK0lqmuFrV9i+AfXOlbmeF8lXb51T4mKI43Trg9O4somA0VKPE8RCcBDxY0kqS/PBFpC5ttdR72P6mpMuY6Qmwle1fjzjsMaS9rMvyM25Q0sGa8/ge78uOO/aeA1T5+1kJbXT8Hc3uJcDGmtHvFgVBs8yTJm1cFdg+F5gvNXAUPs9MwckaT7lQXUN5CikzZer/b50qxDclOcZ9geOAT0n6OUnm/KWTskXSS4A3An8C7iRP0IBRa0z+bPsvKaq5YY+wzJHvJun3+bmb5PdQ7lummjaGeuZ1iC5RypO0DymOXcy33cX2ZeOxcvqQtBFJo+S5zHQi25oUAvsvSbvPszkeDICks4DDbN9ety2DkDdT9yE1GT8SWDLJwr6cIvnIziq+wnHfAfyW9G86FngpKSzTmO5og9I6xz8Mkq4ktUfrZAssIfXFXDQNxiWdSOpmVFZwsh54fJ9pbEEPNEUSx/0i6Vmkmf7uJFsvJ4VELqliT2lAW74OPNX2HQtePNi4S0jdqzbsHQAnTcu+xjgIxw+oq1FyPje1HbjGgaQbSVkNZQUntwL/YPvSWoxrCb0Euzp4SOGucZILIdcAHwa+bfv7NdqyB0ny4DIq/oMpaWNgZ9If5jXur8lKY2ljjH8Y1ko6jpnOOC8ldRxaTNw5T8HJL8Ppj07HseeQyZ9sr8/HS4G71mnbPGxJWp3sC7whS5/8jNTk/JKKEwsW4iOkjdLVpBh/JUh6IukP202kGf+2kl7iZgk3DkTM+IG8g38iqTrVpCX4y23fUqthE0TSF4HlPQpODrN9SD2WtQ+l3q6P7cT4lZRWz3aJgOC0kVOKDwNeDmzritQi+3x2T6nkEce9HniS7Rvz8XakbLm+9XuaRutm/BpCATE7+GeOzahmcAywXNLRlBSc1GZVO1lW3Ni1fXvOnJk6JO1Kmu13XhuT0jrfR0rtnCRnSXox8BVmh3pGTee8reP0M2tpuTx562b8hayeZSTHdTVp+bYracP2kSX37EgK82xt+6H5y36w7bdMyOypYVoLTtqEpItIomCr8vEjgPeXfTfrRtIqkoO/mJS+OXJf5xFsKVPh9KiZRZI+RCqm+xxpxX8Y8H/AivyA5aOMP420zvF3kLQceH2nGlfSQ4E32H56ybXnk6QdPlKozGuEjEPQPCTtBXyG1BhIwH2Aw22vnPfGRY6kZe5qZFJ2bohxT57nY7uka1/TaV2op8BORQkG29dI2qXHtZva/k6ngCPTq6NOEIyE7csl7Qx09NvXuObGHL2QdAjwANsfyMeXAffKH7/aBaGyCXAx0B3KLTs3ELaPGuX+JtJmx/9dSScBp+bjZwPfLV4g6UF56Xpr3tDp5PE/nZS5EASVIekA2+dIemrXRztKmtaQwquYvf91V2AvUs/gk0mV3mNF0n1ItQ+dqvzODG1zUu3JqONvSyrc+htmaydNtMnMJGmz4z8K+Ceg0+nm28yka3b4Imm28DJSqtjOkn5CaqwQomRB1exPSkcsa5hjkprjtLGx7R8Vji90avH5K1Uni7wQjwOeDzwAOKFw/jbg38puGJAvAh8nbRpXliY6zbQ2xg8gaRPgQbbX9Pi8W2HvbqQy9Fbv6Af1katEn277c3Xb0g9Z6HBOu9L82U22t5ugLU/zGDroSbrM9t5VjzvNtNbxSzqYpD2zse1ts7zsm4rLN0m3kDbZSpnGEvqg+Ui6wvaeddvRD5I+DZznuT0gXgI82vYRE7DhObZPlfQvlIin2T6h5LZBxn8WSef/bGanic5J/W4LbQ71vJ6kKHgegO2rciyvSLFJQhBMihVKTUU+y+xWf6Pmo4+DVwBfzM6x4wgfQYr1P2VCNnRCSpuNafyHkcQJD2Am1GNa3G60zTP+S23v09U8YZb+jrq65gTBJBhXPvo46arvuHbCUg1jJetUPaTt+jxF2jzjvzbPUpYqddQ5jpT6VWTR/KCD6aGJKqeegoYiOd++LNQzap79NSRNokUj0dJmx38s8FpSzO40ktTqrEpc2/vUYFewyJF0ZNn5bp2kYA5nFt4vI0mJ/LSCcbcErpd0ObNj/K1N52xlqCerHa4oa7oSBHWTdfk7LAMOBFaVVZUHvckZUheOKm4naf+y87bPH2XcaaaVM/4sJXynpC1s/65ue4KgiO1ji8eStmSe7LKgJzsAZb1xB6LbwUvaDzgCCMffQG4HVkv6JrMzJzakaEra3PbvJW1VNsCUZlkE7eMPQOPi/pMmN4Uphih+Dry6orH3AJ5FEmj7AVB5vcA00WbHv5yFKyFPIzVcX0n6QhXFeqpo4hwEc5D0FWYc2BLgIUxA+qDJKAlp/W2V6qBZlfeI/LqVlF6rxRAibmWMPwimma6Y8jrgZts/rsuepiBpte2HVTjencAFwAsKTVjWTnNabVUsqduAcSFpB0lnSLpO0trOq8e1X5Z0xLQ2wwjagaTHQYopF14X2f6xpMPqtq8BrMqS1lXxVJIY47mSPibpQGav+ltLa2f8ki4kVe++hySKdRRJh+d1JdfuDxwOPBG4nLTRduaoOt9BUETSepJY4HNs/6TrsygmXIDcInF74GbSvohIhW+7znvjwuPeDTiEFPI5APgk8AXbZ49m8fTSZse/0vYjisvDzrl57llK+sG/CHi87c0nZG6cJBsFAAAGL0lEQVSwCJB0JfBB4HXAK2yfUfxsHP1k24SkbcrO2765wmfcg7TBe7jtA6sad9pobagH+HPO871B0sskHco8Wh9ZyfNpwD+S9MZPmYyZwSLCWezsQODVkk4uhBfbOQOrlvsCv7Z9c3b2vyF1L6sM27+x/dE2O31ot+M/ntSk4TiSqNRzgeeVXSjpc8D3SLP99wPbdedaB0FV2P4+8EjgF8CVkhaVJPAIfIiUpt3hdub22Aj6oLWhnkHIm24rbK+v25agvZSFcyQ9GvgEcC/bd6/FsIYg6Srbu3ed++6oMf7FSGtn/JJ2zDv1Z0s6p/PquuZVALa/QdrhL3721gmaGywO3th9wvZ5pBXpf07cmuaxVtJxkjbKr+OB0ky9YH5aO+OXdDXwYVJx1oaZvO2VhWs2ZFJ0Z1VElkUQTBeS7g2cSArJGvgW8HLbi0ZVsyraXLm7zvZC8T/1eF92HARBjWQH/8wFLwwWpHWhHklbZe2dr0h6qaT7ds6VaPK4x/uy4yAIaiSHb78l6Zp8vKukf6/bribSulBP7m7UrbvTYVaXo1xQ0ykE2QS4o/MRsMz2RmM2NwiCPpF0PvBK4COFrnrX2H5ovZY1j9aFegbpbmR76ThtCYKgUja1/Z2k17aBdXUZ02TaGOrZS9J9CsdHSvqSpBN7yS8HQdAIbpW0HTkMK+npJK2dYEDaGOpZBTzW9q8lPYqku3MssDuwS3Q5CoJmIunBwEeBfUlVuz8Anl2lZMNioY2O/2rbu+X3HwB+afsN+XhOAUgQBM0ii6otIe3JPdP2p2s2qXG0LtQDLJXU2bs4ECgWbbVuTyMI2o6kzSW9RtL7JR1EcvjPA24EnlGvdc2kjY7wdOB8SbcCfyQ1WkDS9kD03w2C5vEpUmjnEpJy7mtJmXeH2r6qTsOaSutCPQCS9iEp+Z1t+w/53I7AZrZX1WpcEAQD0SWtvpS0ofug6JcxPG2c8WP70pJz36/DliAIRuavnTe210v6cTj90WjljD8IgvZQKLSE2cWWnQ5c0TBpQMLxB0EQLDJal9UjqVezlY0knT5pe4IgCKaN1jl+4HhJLy6eyHm/X2VGiycIgmDR0kbH/1jghZKOA5B0L+A8YJXtF9RpWBAEwTTQyhi/pM2Bs0g5/IcAH7b93/VaFQTBsOQ0zhW2H1O3LW2gdemckjotFD8KnEDq0vOjznnby+uyLQiC4chpnHdK2sJ2FGKOSOtm/JJOnudj2z56YsYEQVAZkr4E7AF8k5n0TmwfV5tRDaV1jj8IgnbSK2PP9imTtqXptM7xS/rnrlMGbgUutP2DGkwKgqAiJG1CkmtYU7ctTaaNWT1373ptDuwJnCUpGjUHQUOR9GTgKuDr+Xh3SV+u16pm0roZfy9y960Vth9ety1BEAyOpJXAAcB50XN3NNo44y/F9q8pb8AeBEEz+GtJRs+dtVjScFqXztkLSY8haXoHQdBMrpX0LFKzpR2A44CLa7apkbQu1CNpNbkZc4GtgJ8CR9q+fvJWBUEwKpI2JTVh+XvS6v0bwJtDonlw2uj4t+k6ZeBXnYYsQRA0m1yZb9u31W1LU2md4w+CoJ1I2gv4BClbD1Ir1aNtr6zPqmYSjj8IgkYg6bvAMbY7fbT3Az5oe9d6LWseiyarJwiCxrO+4/QBbF8IrKvRnsYSM/4gCBqBpPeS2i6eTtq7Oxz4E3AqgO1V9VnXLMLxB0HQCCSdO8/Htn3AxIxpOOH4gyBoBJKW2l5ftx1tIGL8QRA0hRskvVPSLnUb0nTC8QdB0BR2A74PfFzSpZJenHP6gwGJUE8QBI1D0v7AacCWwBmkCt4b67WqOcSMPwiCRiBpqaSDJX0BeC/wbuDBwFeAr9VqXMNYNCJtQRA0nhuAc4F32i6Ks50h6VE12dRIItQTBEEjkLSZ7dvrtqMNhOMPgmCqkfQ+5irubiCarQ9OhHqCIJh2rii8fyPw+roMaQsx4w+CoDFIurLTdjEYnsjqCYKgScRMtQLC8QdBECwyItQTBMFUI+k2Zmb6mwJ3dD4iibNF9e6AhOMPgiBYZESoJwiCYJERjj8IgmCREY4/CIJgkRGOPwiCYJERjj8IgmCREY4/CIJgkfH/4m/L0UXSgZAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for col in cat_df.columns:\n",
    "    plt.figure()\n",
    "    cat_count = cat_df[col].value_counts()[0:30]\n",
    "    chart = sns.barplot(x=cat_count.index, y=cat_count)\n",
    "    chart.set_xticklabels(chart.get_xticklabels(),\n",
    "                         rotation=90)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rnwJw8K1v5ZY5e8sF694mp33wnr/jOE4T4j1/x3HaxBm3vpe77/At5wXg2lum5pbZZasBANx104e5ZYZtN1crW+fk4T1/x3GcJsSFv+M4ThPiah/HcboEY67NVx2ts4upjsZf/kFumZX2nJuXz3s/d/+SB8wDwLt/eze3zMAjBwLw3t//m7l/3iOWAOD9Myfk1jHPYStambMfyS9z8Bq5++qF9/wdx3GaEO/5O47jdEI+OOf+3H1zH/RLK3PebfllDtiiYv3e83ccx2lCXPg7juM0IS78HcdxmhAX/o7jOE2IC3/HcZwmpEOEv4hsKCIvi8irInJUR7TBcRynmWl34S8iPYHzgI2ApYAdRWSp9m6H4zhOM9MRPf9VgFdVdbKqfgvcAGzeAe1wHMdpWkRV2/eEItsAG6rq3mF9V+Dnqnpgqty+wL5hdUng5Wj3XEB+CsBiZTpLHe11nmZra7Ndb3udp7PU0V7n6eptHaSqAzJLq2q7LsA2wKXR+q7AuTXWMa6tZTpLHd7WzluHt7Xz1uFtbV0d8dIRap93gHj6nwXCNsdxHKed6Ajh/xSwuIgsLCK9gR2AOzqgHY7jOE1Luyd2U9XvReRA4D6gJ3C5qj5fYzUX16FMZ6mjvc7TbG1ttuttr/N0ljra6zzdra3TaXeDr+M4jtPxeISv4zhOE+LC33Ecpwlx4e84XZQQLe90MkRkzjrVs3qRba2laYW/iPQQkX6tOK6hP0iobxERuVNEPhSRD0TkdhFZpJ7naEZEZB4RuUxE7gnrS4nIXm2sc0YR2bY+LayZV0TktGrpUURkgIhkB/pUQUT+JiL9RGQGERklIlNFZJfWNbfqueYXkaEislayZJSZSUSWbMM52uN6xorICBHZWESkDfWcU3Bb66glKKAjF2Ae4DLgnrC+FLBXtF+AXYC/hPWFgFVSdfwT6AfMDLwAvA38vsY6JmS0bUL0/zUZ+69JrS8BjAKeC+vLAn+O9o/Fgt96hWUX4ImMenPrwTypRle5pwsAtwJTgQ+AkcACrSkHDAJ+Ef6fCZg1o565wz1dCFgotW8NYI/w/wBg4WjfHZWWVD2bAaeHZdPUvnuA7YBnwnovYFL4/8jw9xzg7PSSqqcnsDFwDfA+cHPRZxVYGdgo495sDKyU2jY/MBRYK1lS+2cF9gEeC8/MvkC/6Fk+Fov4/Bj4JPx+f8k499+w92KG8DxNBXYJ+54Of7cM1zRbcv8y6jky/pu6X9WexVOB14F/AXeGJf3bbopF+k8J68snZYD1onILp47bKvq/6vXk/D6/Kfq8h3u/AXA98CpwMrBERp2bAEcCf0mWsH014AjgLeDwaDk2o60zhn23YO/lYcCMle719GOLFOoMCxVe3LB+AZYw7sWwPjvwVKqO5IffGfh7eNifLVJH0R+E1MchPPgvpLY9iOU4mhhtey76/9mM62/xwhWoZxQwW4V7+gCwB6WPzO7AA7WWwwTQU8BrYX1xYFS0fzPgFeBLYArwI/B8tH849rL/N6zPBzwa7Z8KTAB+jwnBteMlKndKuOY9w/IAcHK0P/kt4/uVPBObhr+7ZS1h39rAReEZGAm8B/St5VkF/oOF3KePGQT8J1qvKgxTx6+NBUt+CVwFnBSuP/6ILoK5WB+W8160EIiUOhaXYmlZIF/4T8h6Bwo+iy8DfarIgPGhbfHvNyl9zvT5U/uer3Y92Mc0/pgcSfiQF3neU3WtG36XT7H3dbWw/ULg6vAsDQcmAZdFv+Vw4N3wN1kOBxZP1X9T+M3WDcslwIhK93H6sUUKdYaFCi9u6sGL96d/1OcxgT+CIDTIENxZdWBCJ/cHAY4GpgHfA5+HZRrwEXBKjddyKnAUMBgTCkdigm0OYI4a6rkdeDM8HC16sXHZtmwDngZ6k/FSJvcQmDPZHx7Sy1LHS+r4+KPcE9gQE2oTgROBpTPa9CzQI3VcXM+Y0I7kd14VeLDg8/c2JhR2JfTyCD3QWp5VUh2SdPuj/4sIw57Yh/XWcF8Ox0Yd2wD/A+bKOGZA3K6wLVfAA38FXgr1zxCObzEKzXt/angW7wFmqXK9YzPu67MZ29LXF+87pdr1YDlyxgJrYh/RkUDvGp73OYFDgHHA3cBWWAdgCKVRy7Opv7MAD6faMajAc/lCkW1ZS7sHebWBL4MhRQFEZFXgs2j/d8EAluwfgPUwYy7CelPPAA+JyCBMSBepY7iqri8iS6vqcRntO0VETsXyFu1Z5Vo+FJFFo/Nsg31UErYLf/dLHbdDOCbR/1er55aw5PFR0HdeH9Z3xD5WtZb7RlW/TdSbItIraVPgO1X9KNhZeqjqaBH5R7T/W1VVEUmuY+b45Kr6A3AvcK+I9AnnHyMix6nquam29sfUHGC9xJjDMVXRoiLyKPbibxMXEJElgN9hH974/bgZ2ALYHvhBRG5PXWNMpWd19pxjAPpG/0/GhNM3Fcq/AowGTlPVx+K2ishFqtoiCZiqThWRGVKb7xKRl4Cvgf3Dc/+/UP4oEfkb8Jmq/iAiX9G6LLyZz6KInIPdp6+Ap0VkFNE1q+rBUfHnRWQnoKeILA4cjH2Qofy3SP8uye/QAxtBnVbpelT1QxHZDPg3NtrYRoNUDVR73h/HVIJbqOrb0fZxInJh+P/r8PcrEZkPe58Gptp9qYhsq6qfhvPMDtygqr+KykwQkVVVdWwo83Pso1OdIl+IzrAAKwKPYi/Ro8B/gWWj/TtjL/bb2Nf6ZWDbAvX2KlIHZiMYCrwIrBDaM33J6gFUOOci2IP1FTYkfIQCX/nW1IPpI5fMOX5QuN5El38bKV18Rrmp6XKYzviPWI9qA6wnelK0/99Yz+Yc7ANyFvBYtP932Id5Mjakfhw4KNWGPlgPagQ25D4GmD9VZkfgDeBKbJQwBdg+/XsDSwPLADNkXOszwP6YOm2lZAn7BBu1XByekWnYh3qWVB25zyo23D+JEGAZ1Xs8cHG0bSSmL76IfNtDbk+ZDNVLpX3YqLJn+L8vMG/0/5+TtmGj3GGV6iWj55/3LJKjZiNSt0Vl+4Z79xQm4E4i6LcxtcodmHBP/k/WP4nqyGxb2DeN0oj9c+wD+EWyXuR5x0Zjfy/w7h6DdVS2xtSH7wInpMpkjaCS0fMkbKT7ItZBfZ2SSrVQz79LRfiGL+yS2Mvysqp+l9r/E2D9sH+Uqr4Ytu+iqteKyOFZ9arqGQXq2AbYCzNMpr+sqqrrhXJXYVlKn8q5hp7Aqar6u9DD7aGq01Jlfp3TzqtT5RZW1SlxPcm2sH9TzPDZW1UXFpHlgeNVdbOwf4CqTs06Vy2EHtVewC+x+3YfNgKKe/JfY95lO2M98utU9aOojg3i41X1gWjf1Ziw/hfW83muQlsGYkZVgCdV9b1o3wHhvHFPakdVPT8qM15VVypwzTMAv8I+OL9S1blS+zOf1XAvLsU+Lk+H4sthz9TeqvpFKLdb1nlV9aroHAOwj+VgolGKqu4pIj9g+v/E2yR50QUTmGW9fxEZmlHP1SJyI9b7/bWqLiMifbEP9/IZ92SCqq4oIhNVdYXUvmrP4szA/9RGecl70kdVv8q6DxnnXjtj8/RrVtUHQ7nTsc7FLcnzWSsFnvfHVXW1Gurrg/0mn6W2jwe2VNU3w/og4NZwjwdVqlNV36h63i4m/DMf0Gh/T0znGe9/U0T2U9WLRGR4RrUKpFUH5QVUEzUCInKMqp5QoY0vAYthPdDk5VNVXTYqM1ZVV61QR+zONSP2MZqgqmkVxQRVXTG1bbrwCg/PesCY5GUUkedUdZnw/3+xHsONwMhEKGa0ZwGs1564tD4MHKJhSFvtxQ0f3RtVtVXZW0XkR+xeQvnwOrm3/UK5FdPHYr3vN9RySj2dFlppQSUix2KjoFspVz98HPb3x3q/YAbqz0RkJlX9WkS2qnQdqjpd7SHmurt0WH1eVSdnXHdvzKMLsjs7j2G/xXjgh+g8Iyu1I+M81wCLYh+jpB5V1YNFZJyqDonvk4g8o6rLZdRzhqoenvxN7av2LI7FvGeSj98swP2qOjSqI1Mlp6rricjmmAfaeaHsk5haT4E/qOqIsH0a5u33A9YhKXuGQpktMeP7Z2G9P7COqt5W8H5egHlqjaD03KZ//yIdkQ2xUeaDoZ1rAvuq6n1RmYWy2pB8MCrRZXT+eQ8oZjFHRA7CDLDvh/0S9i+rqheF8v9W1UdT9a6OvTxKqZdEtB7r2FHVE4I+MPFBHqOqd0XHxfq4PCaKyB3kPByqelCqjf2xGc+S9Z9ggmO2lMDph30sEr4LwimubrodRFWXEJFVMFvCn0TkBaxnfW2qvVdgbrKJP/suYdsGYX0U8AtsiAw2vL8fU5OBuSTeLyIfYx+aEar6vog8oqprhBcyV6iratF4lPMxlcuzoY5lMCP/bCKyP6YrlqiH1hMz3MUkPe7fR9tURH6KqWC2wIbXAgwSkVuB34Rym1Zom1Ku8z4OeAgz8mUJ/nUw1dXr4VwLishuqvpQVKyvqv4h62QiMmNo12LY/bhcVb/PadsQYKmcnvC3IjITJb35okQfRRGZIfkoJQI/LfgDFZ9FrOebPD+o6hdhlBEzAlObXUr0sQsciT3HCb3Ddc2MPasjQr2zZrQtzXBVvTVqy6eh43gbgIhMoqVd4TNs9HYi9g5+hH3spldD+e+/T/KhCuf4RET2wZ7hZNu9oUOTdBQP1ZZ2nLspyaoZgYUxdfXSVKHLCH8qP6Bg1vUlY1VCBudgwqFsm6ouXLQRInIKNmS/LjmviAxV1T9CabglInNTLohjijwcMV9iP2rCksAwTGcYC5xpmBogoZKBjNDeJ4EnReRk4AxM4KSF/wBVvSJav1JEDo2vp9KLq2YgP05ElsUMpg+KyNuY/rzqCxnq+i5SnSyJ+cW/Hr+kwP9h/vTPh3JLYbr0I7F7ey9wo4gknYH9wrb4fmQ+CyJyPGaAXVCDmk5EZsVcg48BjlHVPSpdR4rLsZ7cOUGgTgQeUtWzwv6/A79U1ZfDuZbA7CWxSuouEdlYVf+VUf9VwHfYyGBjTBgcktOW54B5KXcWSBiO3aMFReQ6bPS3e7T/ndCRuR7rLee9n9WexS9FZEVVnRCudyVKRtGE71X1gpz6e6vqW9H6I0EWfCSRA4HY12dnzAX2BBFZEBgY3oOErM5GLCvvwT4+/wzrO2D2iPeAK1W1UicgoWpHJLR1Q2ARVT1eRBYSkVXitqrqz1LHrAj8tsD5u5TBdwT2I+XtH01kvE3tK+qjv2LGsijlRuFq7oQVfdoLXuudlAxWd2OG0L9mlFsrY9vq0f+5BrKwvx/W070HM0qeSirQKJQbhfX2e4ZlF8r9+B+l3Oi9EvB4Rj3zAgeF8s9i6pVLsY+gVLgfDxH8m7Ge7MfYh3xUfF+IYhzS27ARYw/MmHtzWPajZORcL/zdKmd5jmyf/lnS58Vc/c7GYhPGYwbuOTOO7Yn16o7G1IQvxc9ZRvlnU+vTwvP1NZGhMuyLXQ97UdkAPBoLAruPjOC5cD2bYB2OuTKudb9Qx9vhWlfNOEf8LD5F6CFH+4cAr2Efq0cwY3c66O1YTLANJLg9E1yfsXnB867vtej/IvFAl2MdoUXDcgYm1JP9uYGemCH2ilBH2ZIqfxrmo79+WG4iZSgu0tac663qdKLaBVw9ReROrFc8K/BC0OXFutjNwr+TMfe/u1P7z8C+qLNgL0Hcy/yccle/tNrgZ9hLP5uI7K+q94dyldwJT8Be6H+r6goisi4mLONruoIMN0EtuYieHm3+HtNZv50uD/yDjJFMsk1N5/4nMRdU1ZRhGfNsuQ0zvD2eUX/CnqHeM0O7H8OCvhIOBUaIyP9h921erIcPgIj8FvOKGYB9xPdR1RfE3CG3wXrOV4vISOB6DW5rEbOr6ivh/91CmYOCTnw8FhMB1ru8gJKKbHvsmemDjRx+xF6orN7j2lgAVlavTYEfNcP4qDbKSf+WN2AfrK3D+s6YuusX0T0ZhakkHscE3sqq+kFUxzgRuZTSKGxnUo4GWnnE9F1U7nupnGXg2Lwdkf777rDeX0S20KD/VutdXwRcJOayuC1wZhj53qCqfwpVrYRFsP4pqntFzFWxJzYK+gk2qoUMGwc5KjlMLfuEiOyjqrZaJVoAACAASURBVJek2r8fEPfqf67BKB3a/0l4jmIOwp7JG0P9DwAHRPt7xj1wEVkZ+5CDva+xGnhGLHju/1Ln+AP20dw/rD+AdYRiqrZVyp1YemDvfvpcmXR6g69kW/GnoyUrfpYxFw0++eEBu0lVt84qF8rcgg3fM9UGqrq8iOyIBb6MxgTdWsBRqnpjOCYxkD0DrKCqP0rKQCYicRumPxwa+TSLyDyUe618EO1bDdOnH4oJ5IR+mHfAcqHcylivIxESnwF7qur4sF9UVcWMa2ikuonO1RO4WlV3zrtvodwM5Ly4QVV2o6o+nXmwlUkExw5YGojpgkNEntVgMBfzzz8tET7xvQ266d9iHllgI4zzMZe9vphXzbGY62ovSraFqnmTwu+5DuV2oYTRqd93uiEz2jZJoyG6iJyJCcRvQjsfwkZLX4f9fTCBk1zLw8B5qvptqt7ZMQP0dBWjqj4kLb19ZsJcglsYOEM9mc+bFDCSp/bNgo2UDsdG6vOE7V9hPf5to7qnOyyIyJOqukpWnUUIH5vbsPs5IWxeCXMR3kJV3w/lnsDenaeCYB2AGZYTI3RPrOO2boVzJe/VLNj9/BzYG7MvbaKqN6XK98DUUENT22fCXKZfzjlPxbaGMrHc+x6zEY1U1f/ltX86RYYHnWHBdN7xMHEmYHCNdbRQRaT2V1QbRNsGYuqdzQj+0NG+ij7tOeftQbnf+3aYGuAqzKA9BQs0SfavTYHwb2wEs2a0vgblKqplMF3zG1j05XhgmYz2PUIU4ZhzDUOBnYBfR0uSZ2aOrCWjjlnCcU8D70fbr8VGQ4dhBv2+YXt/clIN5LTxJWAj7OMyZ7KkyvTH9NFnUJ7f53VsdDklY5mcquMM7CPWIyzbAafntGlWrKf5BhY8lGyfHkkcbRuWWt8bUzN8gnVGviZKEVHDfcl93shWP01Krc+IfbhvIei9MV11z6jMRExt9CIwNNkW7T8T87pbk4z4mVBmhvDbJGq7A0nFamAqxIPCsl5G27NiebZLlamYiiIqN1vBckuSUkthsiMzT1GVtlaNXSq6dPqef4KIjMMemm/Dem+sx/Soqh4aqYfK0JJaqKoLlphP88eUqw3mwl7ER1R1ZTHvoKdV9UuxqNcVgbO0ZOidGetpJoalFj7tGde2JHC3qi4W1p8BNtBSD2kA1htZLnXcIK3gz5vVQ0v1th4D/qSqo8P6OlgunHQP5Wrgp9iDGN+3M8L+PE+sRVR1mIhMIcObSlUXEfNK2RTzlx+KGRdvwHIHJa6jM2HGyoGY7vSZsH1oOO+mqrqdZHthoKVRwxOq+vO8+xXdk7GYUI09o67KPahlHYk7YXJ8DyJXVVXtJ+adtgbWO30d69k/rKr/CXV8GrbvqKVYkzLX3nC9K2NpD5YX8wI7WVW3khq8fSo9byJyORY0lXimHIB9uHcPZf+JqbMexH63uzX0OkXkUFX9R9x2MWPvjVjPec/oWRyd0TTVED8TylyKfQCS32JX4AdV3TvruvKQnFieaP/tWCDnA5Q/7weH/X0wld5gyl1Ojw/7E++1xFvwPeBojVxwJdv1dfroMIwWVsXkUVbcUaa8i9qyWd6+hE6v84/opdGQVy28ujcWRg3levI8qnnZ7I6pDRJPlkcxv+LvCJ4pmL54ORFZDutpX4b1ltYO7foSQCxd9J1ZjZCWro3vYTrAhB5arv/9iMgDQUT+oaqHAudm6JuhpMN9UMyz5fpwvu2x/DYJMyeCP7R9jKRSKwReC0sPym0mCRU9sTTfgyYWHNcBO2nGcFVNFfLXcMwACcFpaikNHhORf4eiw7LOEzFaRE7Dfu/YLjQhKjOjZrgqigXVfKol3+91MbfP10mpY7SYO2EfbIQwPkcoT8ECiW4WkWPV/NTTKqf/qer/RAQR6aOqL0kp3XEt3j6VnrdY/w0t9d/3AvtpS3sS2PuRpPEQAFV9RSxV8+VYFlrC9lw1S8TKqQ7Qf8KHqzAico2q7oqNAtPbEqqlRbkdU6GOJyP9RsHfP8v1dfr7o6YuPi98GF5qcXQxeVeRriT8p4rIZqp6B4BYUMeHGvTXGnT/ldAqrnhqgTrnYD7qSrnuOtGHf6+qGs5/nqpeJlFOeDED03FY7/9HyIwVqPZw3Csi91HKpbM9Ft2aUO2D93fKe9p/SZpH+UdnsogcE9W3C6baKENLdpO+mh1xWclVECm5At6eOr6S4IiPl3ANB2KGNRGR7zE33eNV9d2gq72yihBJev1D4sujvDNwjZi/9V2Uv9g3YbaZz8SiU0dgScKWx+wKZb1PsfiLNUL9D2vJRpH0yAdj3jnjc9qqqjpBzOZ1vVjOlvTkLW+LxYDcBjwgIp9g6huwj3HSi7yMcqNnmtznLXRmjso7UFNR5ykkKrdC9P8XwHaSClASkU2wj1Rsvzg+KvKDiCyqqq+F8ovQ0t+/GmX+7+G5KYvoVtWrqujjF1DVDSudJO/3j6jqhg2MErMPZkUjv4C5YL+QOu9SWAqWqnQltc+iWO9w/rDpLWzYdxuVhz9xZO2MWG8q/YDtGfavQyqwBssv8lBUx4OY0NoT009+gOmdkxftFSxta4ukWlEdo1R1/axtQdAtgA3npxv7tNyfPT6uRRSoiByRvg3YA/GIhtQP4djZsQ9VbFQ8VlU/SZ1jNWyEM4uqLhRGPfup6m/D/tGYEMz0xAoCbHvMXfApTD1wV6QemBMbrayBfTAfwTyQPgr7D8d09ftqKXXFItgo7F5VPTO5h1ju9rIw+VoQi7w8CVN1JM+VAl9E6qPTMe+fI8Pw/OnUc3Y+pm6JhelrqnqAmGox6ZFvhHlyteiRi8jdqrpJ+L8H5oZ7hOYEvIV7PFu4H99mqIhaRIOnjk+EFUTPm1SIqs2rK6rzTSzVyd+klMCtjEiVciFmlF8X83rZBjM8xx2r9TE3ysnY+zkImwMiS2WUbsvRWD6e2PAN8C2Wt+joqGy1VBQXYx2PSTnnyv39ozJ9gT9RniLihHjkKyX14feUVMmqpja8AThfy4P+EJE1gf1Vdaeq96SrCP8ESXmmSOUcFz1Swm4ENoTaCfPi2RnzoT0k7B+PqR7KAms0yvUiIvOG459S1YdD72WdpAckIvdiAqhFDzl8fPpixrl1KD2A/bCX9iehXJlnSIV7sQ4ZHytKKqqYObDo42NV9YaM/ZXO8wT2Mt6h2aH5mR5Z6dFY6GWthwWibailtAwPYN4usVvjOqr6i7B/IqaT/jBVX9pTo6KuNpSp2LsUkcnYBD7pc8X62AmYDve+9L6w/hLw06S3FoT386r601Q9vTABlyuUqyHmLpn0MB/VUpBU4u0D9mzkevtIlJ4jqI2WxPLXfxfUKhfSMoVE4jGWVmFOrzaccwtVvUuq5CqS4NEV/Z0ltGFNscyWI0RkYcyNMfYqq5T1NOt+nRIL+pwy1VJRvIAJ9ylYZ6cshUul37+WtlZp4zhVHZKzr4W3WRZdRu0jIrNhHi1rhfUHMQG+jmYY48KLdQ1mSExYTFW3FZHNw9Dun1gPLGGGeJinqv+VVPpbVX1PLNJxZREZhr288dD3aEwP/QQtU9Puh9kT5sNepkT4f055fqEJIrKy5iSHi8iMAtWcxGQiMgfwbxHZmRqNRar6lpTrJ2NBUFXlFobRm2K9oBUxj5CEgVqeL+lEEdk+Wp8haySlLdMTV9TV5vUuU8VexYRkmv+IyE2Yamt2LCYAsURyaTvFq9hsZYkKZsGwDQr634cP2x+wWcDiD1VsAP0LJS8bgCtEZISqnqiqtczv+xCwZhgJ3ovFE2yPfYQrRdVWVWGKOQPcBfTXUvRyFpVSHB+NqdlGhg/ls9UvqUU7kg/sCMnIAaXldp9qqSg2qnK6Sr9/0p5KeYp+oma/yewUhLZWuu/plN2ZdBnhjxmInqOU635XbAg4WMzYdXFSMPRkbsVUQzHJi/epiCyDGVrnjvZXDawRke2w6LwxmPA+R0R+r6o3hyIXYYKhzFsEIDz8Z4nIQapaaS7OnwM7i0hucrhA1Y9V6vwfiz3RWbaC5GOQJY3eEvOs0VD/IZjLnh1g+erPwTyCemO66S+jnv1NWEqMe7GP3A9EQWBY3p8dML06mFC+L9pf5tueIvH+6gnsrpV1/kOj3uVxIvJ3LLo55kssr/xoynX+h4Q2DwTW0JItaDFsVBUzK/CiWEAimArvKTHbxwoikswhIcBMYT3dI78OM7JugtkIdqOlLndnYDktqc/+inlcnVjhHmQhqvqVmO3qgqCmSWIy7hQL0stMdFeAlYIw31PMa6zcwlmq5y4x+8VpmJ++Ugp6+khE7gcWDveQVB1VPVuwjlIeabtPRX285qRwkfKA1OT3V+x9TncyKuUpOgIbHWe1OWnrq5KR2kNENiLDbpeJ1slntNELObNJYS/ek8DBYdsATK+clQ5hb6zXtna4QR9guutkfx9K82HegvmV90nV8Qwwd7Q+gPIUEbn5wlP1tPCLj/YNyloy6rgce3jWCcslpMLIU+XXxT5MmwMHRNufJPirk+FHjLm7Xof52H+AfRznjPaPw4TgREzw70E0exmmbloFe7Ffx9ReB1KeP/1HTLf5ffg/zp/+A6XZ0eJlGtZLS8pVmyrwyfB3LDb66kNL/+vdspZUmRVS15Kee2DtaFkH85Z5ntS0k1Wej/HhbxyXkU5DMBrrUSfr/Wmdn/9ELAXKWMIMaZSmR5ySsUyuoe6DsY7CN0XrCb/LbNF6b8zt8ZXUvS18P2u8H9XSomSmcMlqW147k9+3DW1cHEvJciWluIarwrYW8wVnLV1G5y8ij2OTrT8S1lfHAmdWE3OrvAdT4WwOXKgZQ0wR6anBd7zCeXpjOsW0t0+yP63f7UG5wfdkTCjcSU5PSSqk0E2da35KHh7/pymXQMmOAj0fe2DTP+wcmL7015jxdgcNibBCL299QgZEbWmMrpj3X0pRzXEk7kSsp7xjWD7EerK/U9VKdppWU03nL+bZdA52redh9+gSVf1Lqp4Wnh5hmF74WkRkBezjvi0mIG7RyqO99PFjVXVVMS+cs7Hf7mZVXTQqcxs2qnggXMsG2If87fi6C5xrbay3+aiqnipmTD+06PEFz3GBqu5fYX/f0IaFVHWf0ONeUqOMudWewxrasgwt1WmVvJbSxz+D9b7LUrhoME4HzcPXau6aS2BpK+7R8qj3Y8lJHS4FU4OH938nLFgT7AP0Ty0S3UsXMviKWdyvwjwaBAt+2A3rcYINtc7Aen/TDZpankP7TUJmRzIyEEoxb5/TMP/k2JL/rIbUumIBTWlUoxQCIvIiGX7xYh4JM2gpWORNzOukN3CVqp5S6R5F9aQFkgIfaSkG4SlVXTkqf66qHhj+bzHXgFTJ+y8iD2H++pdSmpVodyw30sNYps1XQ9nJmpFOQaq7xhW57lyjYvhIr6phukPJn0Aj09MDiyGoeC21fiCqXEtyvgWxD1Y/4DgNrs6Vrje+7lrPm9GOvthoeCFV3TdLKFc5vlCwmRSYNKaIHaRAe4Zjo7GlMHfWjTAvuG2yVEoxWvL2qZjCRcxgvCamZXgUG0F8q1GKlEpyQiz3F5hKeijBvoSN3B9T1WrxLIXoMsI/IfTywXp2OxAly8pANZpPNzxQw8JxK2G98xui0URFb5+gLy/shlnhGkZgaqp3U9snYOkYEiE9MfQsemITja8RtmdGskYXnbYNpM//qoZo4ox9r8W9y2h7kvd/C8zHeHre//CxeR/7SB2GfaDPx3okO2BpgJPI3Us1FfQlBVzjipLVa4/25eakicpkenpgUxlWvBaxSWcKfew6AxKCBaVCdHwRoVzlHEVdW6tOGhP0/jdihtLpdhDNmdMgpz2TsBxPE9UimOcBrlXVDURkKmYnvB54gpb2iSSP2L+x9+AUTCX6ARaANjTsT6KZDwJmUrOhZE6AU6Wt92Odz3fD+kAsluVXUZksb6tkboEjNGOuiPiCOvWC9XiOxgyFG4Qf5EBsKH17G+qdHYvM/SHaViSNbma6VPJTAW+FuX7GZUeTkUKXVKpYzIDZQkdIjk2AHNtARluvwzJrprfvh33sKh07V8Z924qUbSR1zMzY8PRO7KN9AeallOx/CcrmtO1BSGNb42+6KRXypWA9+q3jc2XUMTb8jfPOPFvkWjCBcAMmQC7B1EtTWvl8LoyNZG8hI81yKDMM09d/TCqlc8FzJHMT5+qogXEZ96OWfEqFUktjBtWZKKVGXpRgo0m/A1SwgxRoT2L3GY/JFiGk0sZUrBtio/+JmOF86ZznuUe4nt0wu0ZsA8u1oURlqs6NnH4Hst4LLIvwfpjmox+wLxYTsj3Wgcm/F615MNtzwUKprwwXeBPmZfMgsHyqXKL/+iMWDfoXLIVsur61sV7p5FDf1tG+tAH1Ulrm4b4K+8qn672iwpKuI88o9F+yJxXvA7ySc38GYdPfEV6eWbPKpY6ZO7xsozGPgr+H+/o4ME9G+Yp5/8M1voG51g4jZ16FUHb28IDG8wHcRfTRCtd0ZyuelfHYqCMWVM9F/yeG5W/JEZaYPWQnTEWxOKZyubDotYTtFT92Ba/lGUyorEu+0fBVTAWZ+zErcJ6eWO6pvP1VhXKV+tMdmjzhvwH2Xk/FOievY27ccZnkw3wf5gW1AlGu/oLtOR8zjP8GM9pOxOxcWe/c7qE9B6bu1+gq51gL+1j/IawvApydKnMjli04SRzZl5RTC9bhvS+0Y/fw/p2Tfk4yzv903r6ycq19aNprobzn0BMbYs2YUe7e6IYekSypMq9jBpYdsbw2WT/44cDIsBxKKpsl1kv9Hst18yzm0tlixFDgumKh3Rf7cp+MfYD6RuWSaehOyahjH0yf+FpYX5yUIKrShooZEKNyU7Csi6tVKDMD5gVxHfYhuLTA+ZNJax7EfOvHhOVLqvRacuqr2GsvWEdFT49WtCnzA1HguCcKlBlNNLFQG9qYm7WVAkK5St2xp9a08O7kfXhzJ40J+4dhH/dlwrWPBzYr2I4tiLz0wrbB2DSv8bY+2Eh2RHgGjgHmT5UplPWzSnsKjaiwlCJnhmXLjP2PY+7vcQbZ5D1o4SEZL51e5y8Fw9SlQFSbiPRT1c8ztlea/PlILfnwZxlTgZLvbyhTLYp0H0wgzKGqiwYj2oVYqPdJmEtqUt9CWG/0z9rS2+dpzIXyCc3IDFgvRErTzVUpNwM2bN4Dm2Vsrirl187ajBnLdlDVqvOQpuq7DHsxj8LUOwdjI6nfhP1rZR2nqRD5zoCYn/niWJ6pzCR0YnnlT8CEc3oCo1rOVS1r65yYq6VggiU3dUlrkSrZcutQ/82YKuYrbDTzKGa7eC4qczX2YfkXZtN6Lqeual5lVVNiiGWPXR/zsFpRLH3N9VrjnAbBM+uscG2KqZoOA97BRueP5B7bBYR/oTB1qZJvI5RZABvGrx42PYwF79xIS9fH9bD88ldo5PooFtD0vJbmce2HhXI/EdaL5CipKLSD0TIxyL6qYYKPjOt5QlV/HhmGE51qRYNvUYoYBEO5jTAd4zpYz/0mLO1C3oThWedqk2tkqCPOlwI2ZD5RS0FQcZbVGbHfYHzqpcy61sSAdpEWdKNrK2IT4OyKjTCTYEFNtfV+LOFgOv30cTWea3jG5rnUZkurFGVaN0TkWcwQuyw20r0My7O/tuTkBYraUtglVSxFRDIZ0mpY5+opVd04GOynp96OD6Nc1uyPCXXFRjJfh3YkqSoqpsQIZTbAdP5LYR/41TEb35ii19JWOn2Er1YJU488X3oBe4jlZmmRbyNwBTbp8rZhfZewLWvy54+Bj6VliuMLKJ868YvUtiJRpN+oJd9KriF5kJJr/hp7oavxoIj8EYsS3QBLR52ZRrqVFE2X/WvsA7qf1pBrRbJdI0WLpfeN64ndCSdh6qkWHx5NTawtNnn3P1LFJmOjvtjzaBqWPO8STCC3B9ti8yFUim6er9potxrBk2wJTc3UFjpTUDnKtJ5UypabRNmvjgnLJL30tpjnWWFUdYqYm+9MYZkx/EVzkuYlhPf0ZCyp4xuYjFkIkyF/TF1LbkqMcK4HgndfMqI6pDUjKjH3131oOcrYM++YuBFdeqEGzxfyo4QLTf5coY7Y+6BIFOnfsIflJUyneitwUiuuvUf44UdgMxvtQxuMf238HebBdLLDSOlWKxzzI6ayWCzaVjh6NDrmRizqeD8sy+s/Ch4nwAupbS28R5Jt2Iivve7nbdXuY3iOajIk59RTdaa2drjeBzGvvlew9OA9aOkhM5bImQCzM40tWP8fsY7RWMxpY39MddOzhjaeiY3mZ4229QMujp85Kk80fwqWijmr/lNT64dklDkktf4Y5oCxHabq3JrIiaXi9XTkD17nh+eaatswffAumOG4Z/h/FDW4PmKudweHBy/Jc3MbZhxeBRvK9ceMRknA0wmpOuomtLFeaubDVId7OgkzaqeXMiM31gN7g5xpJyvUXxfXSIq7E55DaVrGczGhd22qzItYnECyvhDBvY6CqTvqdO/HYC6csTvw7akyiffS/8L/Nbl6RvVcTcm4eXiyhH0HUJ5CYnbgtw243nnDedeM7vuvU2VeJpr+M7Tl5YL1v4SpYY7F1II1G2yxD1OL9zTIklei9SkZy+Sw77PwrmySUU9Vz6j0M0gVo26lpdPr/IuSYRjuiQmFpaJtgzABkBhHHsME+f8oMPlzqGNuTHisF+oYhQn+IzE94k8xAfkoZol/TFNTOEqUQjdqax/NTgO9KKYLn24AFdMXDcfiHZKh6g+EyU2K37XK5Bm3E7SU4KrQtJMVzjMzlpZjR+y+Xg3cqqr3Fzy+qFPAbtHq98DrqvpoqszGmL72NWxksDDWixuDdRDSaqKGkDKGt9oIXvBcWTp/1NSWNU3g3sZ2DMLmoP53sN/01GiiHxHZAxPeo7F7shaWorxQJLNYVtuhYVkVs+k9g72jVxQ4/r+qukSt+1LlJmKqw39i2VSP0KAqjWx3O2Lv/BqUZx3uh8XXxDbIE0P7yxK8FaLeX/D2XrChYuxClriRfUSGe2SVugq5Plapozf2cP0Ocxf9P1qqFsZiE6Mk67NQPoH7fJjF/inswzQc+Fm0/3DM02DhaNsiWC/xsAbd50HkxBPQcnjeYshew3lqdo2kBnfC1HmWzdnXBzM+Lkcb3DzrcM8rJpALZTbDbDKnkwoSasX5Zomfy+S3pTwArycNUH9R0G0ZGyFsHq573laeqxeWafP3WKzEDwWPu43UaCRs3wUbma0X1nMDPSnFS8yIdSKfS55DQq8+vGvrYJ3HtaNlRVIxNJRGf19Xe+bTS3fq+edO0iCW9zwP1fJc8nn1H6nFZiSaDRtZrB7+9scE4R5RXVm9qaexAJQdsdnKbgrL7doyHUKhyU3qRZ5rqoYeiFTJd9RZEJExmNDohakAPsA+uodFZWbEevrT8wxh19peXj6F8wOJpXBeGVNbEo4Zl/ceVDjnMphxP0lN/SEm5J4Pv+0gLFU5mCr0LVVNzxbXJoq6LYvIZoQ5PbCUJ4UcHMJxQ7H3cmksCVo8Oq+aME4s0eItmKBNPHeGYJ2hLbGZ5oZLKTdPjKrqnhmj1I2wkebZWHK4FaJ9VRPEtYUuL/ylwMQH0nJaQ7Dgqb2wsOxZCpxnU1W9U/KTaSUP1TQsL8hYzBj1SbqgiDyK9eKSWZdWwnTQK2EP4xGqOi7sa5EbRirENFTa11ryXkzsgZ9HVR+V8mkAP8WiRl+rZzvaSjSs3htYMLyo0zORhjI3Yb9hMqfDTpjOe9uMKhvRxsL5gYJ75PKq+mNY74n1Hmty9RXzOf+ThukQxRIcnqyqQ8US4u1LKYfWA1gAX61z51ZrQ1W35ZyP3VOq+seMKtP130Lw7cfceyt5UVWraz1KcwG/oKqjaji2hcosqJIvBzbSyLtRKiSIKyL3qjamNcOmzrRQyo0xOmNpkdsci6T9M2aEOZWCnikF2pHMgHQl9rL8jBwjLvYAv4a95I9gQ8+VsAjH32CeDy9jATxvZRyfadCstq8N1/aElg9Le2F2jbuI1FFR+Z/RivQM7fCsTMI8MO4npOigZe6mFzKOa7GtgW0sbAQPv0FsAJ0jfT0Fz5kVWfpMar03poaqy/uScb6qHnDhentE6z1bc73t9DtugtkBy1LNYMGkecesmlpPVEQHYcGmUErdcEn4W0juZS2d3s+/Gqq6b/hb0Tc8GHsOx2Y/ugpYUTN65RWOr5budcNgiF0aG14eASwjIh8Dj6vq8KjsUyLyE8rnIk2GchcCF4oFpG0PvC+WAvpWLfVwlpPSbFBlzSSKKq4jefEEv9SMoDpVnSQigxvQjrZyPGYXeST8BotgHhwxE0RkVVUdCyAiPyc1m1sjUUtlfVtkBD8UmFtELqClEfwUYKLYrGOJAfSoVpx2sthcB0lcxy5APxFZWk31Mxs2Iv0BmENEfqeq1+dV1kqOwkbikzDV0r9U9ZKMcv0xLyiwVA+dDqkwXaiqvh2VazGvAKYxiIrIapjMSmIeeoZ69gl/a4qJKWtn+Hp0ecKQdxNaBjucEfSWW2H+uOdpmPy9xvoLpXsNZRfA1EBDMb/3OVW1f7T/AEwt8mlYnx3YUVXPzzn34mF/3Tx5aiEM/ffCXOQEE6CXAv9V1cVzjslNG92ZCR/aJYE3w6aFsFHY92RPpdkebZodc6fdXltOtDMQG0mCxZi818r6j6N8UqBfaphwXEQOxfL5bCEi82J657p7+6Ta9Ets8qYNROQ87L1bAPgrpSlU1wKOUtUbcyvqAKTCZPRRmeHkzCsQlVkLcxxpMcmOFJzwpWI7u5Hw/xfmGdMi1D3oUb8hvMDxYZTPm1qp/p7YcHRHzLh5NxYD8HzYfzAlN7LvMN1iskzSoJcNZTPd57Ah/6caJhgRmyFoC8wv+Fxtg56yrQRjMhoZxkTkemyIeUmq7N6YQXp7OhFSIBpSCrq3LRoI0QAAE1tJREFUdiQi8ivM2+rm1PZtgM9U9YE6nCPOq383MEJVr0zvq8N51sNGu/Nh3jSnYhGzgql9bhGRQ7C5FAZirtWvY8GZT9X6sRORQzQ1y1/WtrYQ2S/GYp3OjzAPqcWiMrnzCoT9PbGgr9/lnCMxKrd+wpeO0onVe6EddX9kpHvFcq9vDQwscHym+xw2opgvbFse87o4AlNTXdIB91Qwv+oPsaH2x+GaE/3lPNjHbQyl1NAPYiqCVrnhNfh6CkdDhpdqoWTp6Lan2vYoGYF92FwLj9dQzx0Vlg+xUesKmAF/3nBML0L++zpdy0SsB9wH6+h8QZRCOVV2EDaT10TMNvAXLC6glvNVDZyqwzUdg6mntqYU6Hl8qkzuvAJRmarRy5j9amC0PhC4r0g7u1PP/1TML7hQYFArz9EHUy3tiPUe78By9b9TYz1Z7nNvYkPtZA7c04EfVfXIoHZ5WttZ5SAih2PD0X1VdUrYtgiWy+heVT0zbFuXaB5RVf1PVn0dTdaIK6PMZthHbD7MFXQQFuFb9+Cq1iJh1qucfc8WfU6qqDIXwIKR5sVSF1wZjvkV9pzWxdVTWro+vqyqS1Y6JpRbAfOQWVar5P8K5ZPAqTWx4KqEWbH3bP3MA9uI5E8Xej5m4N4B6+B9gb3jsUv4BZjb9wjKs4fGU9O+qEE9F9Z7YO/g9G25betGwn9LzD2vB6Z2KazSKVh/oXSvBetK3OeSB+5Z7CVbS0uZPScAR6vqfWG98EtdL6Sd4wkajRSIhpQqk3N3BsTmVF5KW6b4ngHzTMq0w2TUU1GV2R6IJWKMVRunYcFXQAtB1wvrjOyAvTtjsPbeXuA8g4CFMSN5bBSfhmkNCmegrXCOlTHvvPfC+q+x3v8bWCTyx2G7YF4/SRbhwUA/VX02VV9uvEBU5lwsIC6OsXlVVQ+q2t5uJPynYN4Rk7QBFyUF073WUF+Swng7LJPkSOxHHIgNEzfDsi1+F4x6d+b19hqFtHM8QaMRm+90Zsz+k9lBkCqTc3cGxPzd58HUI8l8z7Nged0/1FYE14Ue6o6Y8D1OVc+tY5MrnTdLwCWoWmBU8oHaGPOauQELfvyywrFZ5+qJfdRb7SFTpf4JWBT8x8FYewPmprk8lvY9NubWbd6NYPxNjMkPacE5xbu8q2fEW9iUaA35mmmVdK9FkOzoTZKHMfQItsc+AGtoyf1zXixPfXtTycDcYcbn1qKqsxYo9mkQpA8B14nIB0RD7k7Cn7H5Zd8QkfSkP8fUUlGGKvNszMe+XYjVHBU4GsuFc4TW4J6dca4fRORHEZktrYapEz2T3j32Hl+sqiOBkWKBkjETRGRlVX0qXYkUzCYQrd+CRR7XRHfq+V+J5be5hzbMatRIpIbozdRxPTBXz+sqlas3Uj6RTtkuTI85Q3u2p7VIThRkgloU+GJYb/ppLHy/B+ZfPQi4W6OJODoLUnDSnwrH102V2VWQKrNwtbHu57CI6+9F5CXMVvZQsi8eKYf9i2EqoS8pjUKXFZFhqnqX5GQT0CiRXej1n4o5KAgZo9k8ulPPf0pYeoelM7IVpq8cLSL3YsPC6UY2sVnBDsCMPHdgD+iBmEHoGUph7e1CEUNaFyFrQpIExXT8/8BsLIlA+BG4SkR+hk3gsWnO8R2GFp/0J49dMMFzCHCwSOlRJAiQMDLYmpbusR0Sc1IHWtVLLsj1WEDkh1gH4mGA0LFIjzR+VaGe7bHo+f5a3QX1b8CmqvpirY3tNj3/GLGglU8bpQJqK5KTwhgT/J9grpLrU/qaH6Kq6WGjU0dE5ClVXTlnX93nRe4qhE7KZ7SckrDSB7VTE0ZMC6nqyw2oe1VCCpHIHrMEli01nn/5GlXdNXXsNaq6q4i8gOVSugdzg00HlH4cHfOoqq5OK+jywl8sY+dNakmO+mA3bHksoGsnVf13hzawChJFb2J5UxJvn56Y4XchbaeMks2MiLyS5yUjXTRauR402rAvNlm7qOo1qe27YqmW/1nn822Kpb/uraoLi8jymA/+ZvU8T4F25M4/IhYwuj+mxn6HcuGvsZpYRM7CbILJfCRJoaqjmzYbMTsB22Ph9wC7Ydc0AMt/fXJHNaooqvqJql6s5mf8XbT9B+BtF/ztxjix1NVliEUrdzp9f4yIbBx6s4kOuJ48FlRfjeIgsg3Mt2DqznpzLJah9lOAMKKuaHOrJyJydPA6W1ZEPg/LNCym5PbQprPV/PQvV9VFVHXhaEm3tR/wFZZ6ZdOwVI/upXv0/OMw9JHYcOuisJ45o1NnJWVgFSxP+FfUOWbBaYlYeP2tmBdTnKu9N7CltiJnTnsRfL2HYLPQrVqPZ14s/YBiev7FMXfkb4gMk209RzhP7jvaiNgWERmrqqum5EZHxNDkzj/SXnQHg+83Ytnx3sfyWsQBI307pkmtoxsZWDslIjIK+LtGQV4icrGq7qs2VedQKY9Wvls7YbSyWKbRyRryLKnqgUH9eQhmN6oHhXqPdWAmEZk57bMvIrPSGMeN50VkJ6CnWMLEg7G0H20m9ODzetPfYGnc/6SW//+u5LqD6mtF4CytMXdUsCdcgM2rsYyILAtspqonVj1Y65x3pL0XbDq2l7DkScdE2zcmNfm6L829YL3XB4Hh0ba6z3/QDtfxDDbnc7J+BqYmGYBlhqznua4psq0N9f8Os9MNirYNxqKNf9+Ae9cXOAmbGGVc+L/hU3Vi+buWw2KRwKL6JWybiH20H2xFvQ9iaqyJ0bbnihzb5Xv+qvoENr1Zevu/MP9lx0n4FPOiOltE7sRcHbsivVT1G7F0B1diboXbqEUj13u0W5bTKBgmV6pX5ap6uoh8ATwUgusES7nwV1W9oF7nic73FfAnsVxgqtEE8Y1EzYb3TAjcAvheVVVENscy9l4mIq1JIdJXVZ+M3HTBnF2q0uWFf4LYhBPDieb3xKz4jYjkc7omopbD5bcisjs2i9rsHdukVvFIUGHNi026vlYQ/GtjH4I2IyJHY4nHZpLSxEGC2UQursc5ElQ1mcBo1rDeMIEsln/nciyhGyLyGbCntlMQnwZ7JDAt3ONdgTVDIGdr5PGHIrIoQd0kltb73SIHdnmDb0Iw9j6HpT8Gu6nLqWq9vR+cLoqI7Be9fIjNnXyARomyugoisgYmiN8HbsbSOYOlqK4+f2vx8zTUMCmW/CwXVb26zud7FvvNkwCsNYDztf0NvvNiub2eVNVHxHIBXaGqi9ZYzyLYx3goFiM0BdhZC9gOupPwz5ogpWoKX6e5CGqLeSiPVn0z/4iugYgM0GiinTrUVzUlRp3Oc07Ors2A+VW1rtoJyZ5AvUO8AqWU3HFbTGjfoqp596NaXTNj8xtPE5FDVfUf1Y7pNmof4GsRWUNVHwEQkdWp0xDY6R6IyIGYn/f7lGZ7UyydcZemnoI/UCQlRpvRKPWwmOJ6Z2zClrGYMbYuRB+zB0XkIiwVg2JxQmPqdZ4C7chK7ijaxkyjWu4tdTiWrqRyW7pRz395TOWTTOr8CbC7qj7Tca1yOhMi8irwc1X9qKPb4pQIhuvdMc+fscApWufUC2KT3OehqlqXj1mBdrQquWON53hLVResVq479fxfUpsLsx+Aqn4uInNVO8hpKt6iZYItpwohjmYpYMZkW7108SJyABafMArYUFVfr0e9adras64jFZM71olCPfru1POfBOyjqmPD+tZYD2KJjm2Z01kQkcuAJTEf8k6Z9rsWROQWLIf/Par6Y7XyrTzHcCy52FKY6/RGWCzBNpWOq6H+H7HUBlPJniSp3hG+ncIrUHKSO2rBaWgrBJQJMFMRW0l3Ev4/w1y4xmDzr84J7K2qb3dku5zOQxBkLVDV49q7LfVARH4B7AGsis3zekUD1CWTCIFIYWQ9D3Ctqm5Qp/oHVdpfxGulxvN1Oq9AiZI7aoPmEs48b3cR/gAisgVwDRYkslaiU3Oc7kzoze6Izfb2FnAJJqC/q3hgsbqfVNVVRGQ8lj5lGjahfYvAyq6AewWW6DY6/zCkXxTz3FgCy51xjqqe17EtczoLYhPPH4lFrcb663Yx9jUCEZkTi1TeFUsTcB2wBpbhdp06nGKciPTHPijjgS+w+SbqQhX1hWr9kxm6V2Cg2/T8ReRQLDFSEuk2G3CGqrYmZNrphojI/Zhr3e+A32ACcqq2YsLzzoCI3IrZMK4BrlTVd6N941R1SJ3PNxjop6rP1rPe9iTlFSjAx8BuXfmaWku3Ef6OUw0RGa+qK8UpfKXCDF6dHRFZV1UruTDW4xyJ7/0iqnq8iCwEzKuqTzbyvI0m8QrEUqjvoO08P3ZnoDtM5gKAiCwuIjeLyAsiMjlZOrpdTqci0YG/KyKbhAjLOTqyQW3kCRH5s4hcDNPfgXqnYj4fWA2zKYDp/LucKlVE+olNpHKuiGyAXcevgVeB7Tq2dR1Dt9H5A1dgLlxnYoapPehGHzenLpwY1IFHAOdgsyAd1rFNahNXYHr4oWH9Hczr5646nuPnqrqiiEwEm3lORBqRZ7/RXENpfux9MOO4YBP1NOX82N1J+M+kqqNERIJ72LHBQ+EvHd0wp3OgqolQ/AzrIHR1FlXV7UVkR7B0xZLK7VsHvgv5kBJb2gBKqTG6EotoaX7sS/H5sbuV8P8mpEV9JeRweQdLd+s0OSJypKr+LSQRa2HkUtWDO6BZ9eBbsbl7E8G8KFHwWp04G5vecm4ROQnYBvhznc/RHpTNjy0iTT8/dncS/odgs/QcDJyARc3t1qEtcjoLL4a/4zq0FfVnOHAvsKCIXAesjuXIqRuqel0YQa+PqUm2UNUXqxzWGVlOyuclSOYpaNr5sd3bx3G6MMHPf1VMiI1V1Q/rVG9FQ7iqflyP8zgdR5cX/mLT8eVehKpu1o7NcToh3fUZCQFKT2sbJwHPqXsKds8EGAj8X7IL6ynXLQul0zF0B+G/dsbm5KJEVR9sz/Y4nY+cZ2Q6XfUZEZuVajksqv0KLMnbdqpa8XpbcZ4WE6A4XZ/uoPPvDyyQpHEQkSeBAdgHoEtGbjr1pasK9wLEk4Cfp62fBLwaXbuH6GTSHYT/kVh+7ITewBBgZqw3NKIjGuV0HkJmykr5Y7rqTF7JJOC7AGsFb7cZOrhNThehOwj/3qr6VrT+SJip6aOQM9tx6h312lnYHpsDdi9VfS+kXjitHhWLyOHR6typ9S47B4JTojvo/F9V1cVy9r2mqou2d5ucroGIrAHsqKoHdHRbOht5cx8kdNU5EJwS3aHn/4SI7KOql8QbRWQ//r+9+wmVsorDOP59MLAWhm0sWkRhREmFZYssCrE/SFFaIf3ZBK0KhBZtatEiaNMioWjRIgolUijSgkJMLlFEFN2QTIS4GJQQgZsCI8jr0+K8w0wXuw7ed+47Z+b5wIU779w552zmd8973t/5Hai6+FS0r6nn8wTl8IyfgQ+7HdH5k/Qw8AqwhrKE1VrOeoL75JuEmf8aYD9lZ+P3zeUNwErKhpTfuxpbjAdJ11AKkz0OnKQp62x70VOkxl1zIP0DlW66io5VH/x7JG2mHNIBcNT2TJfjifHRnBP7JWVtfK65drz2XHVJX9m+vetxRJ0mJvhH/J/meM/HKOUPDgB7gbdsX9XpwJZI0mvAZfTvfAGwPdKlLEmX5o66fgn+MTWa7K+tlOWfzcBuYJ/tg50O7DxJeucsl237qRH0tRp4hPK85Drbl7fdRyyvBP+YSpIuoTz0fdT2XV2PZxw1FUO3UgL+TcAqYBvwhe0ayzrHgAT/iMosR4lqSe8BdwAHKctkM8Bc7Utl0TcJqZ4R02Y5SlSvo5x8dQw41tTAz0xxgiT4R9TnFwDbuxa+IemZNjqwvV7StZTnI4cknQRW5WHv5MiyT0RlJB0HttueXXD9JUre/80j6HMD/c1xJ2zfdo6PxJjLAecR9dkOvC9pI4CKN4E7gU2j6ND2rO3ngLWUdNmoXIJ/RGWaGf824F1JW4APKGXMt9j+c9EPD0nSxZJekPSGpHubfzA7gJ8oO+ijcln2iajMwBGL6ygbvA4BO4Az0M4Ri5I+ojzw/Zpyfm+vftCztg8vtf3oXoJ/RGUWHLHY03vdyhGLko7YvqH5fQXwG3CF7b+X2naMh2T7RFRmmXLt/xnob17SiQT+yZKZf0SlJD0EzNj+o3m9Gthke38Lbc8Dp+jfXVwE/EWLZaOjWwn+EZWSdNj2+gXXcth6DCXLPhH1Olu2XivfaUkXAk8DVwM/AG/bPt1G2zEekuoZUa/vJO2UtLb52QnMnvNTw9kF3AIcAe4DXm2p3RgTWfaJqFRTovpF4O7m0mfAy7ZPtdD2YLbPBcC3o9g5HN3Jsk9EpZog//yImh/M9jktabG/jQpl5h9RGUkfL/a+7Qdb6KOX7QMlwyfZPhMmM/+I+mwEfgX2AN/w381erbC9ou02Y7xk5h9RmWbH7T2Ucss3Ap8Ae2wf7XRgUZVk+0RUxva87QO2nwRuBeaAz5vCaxFDybJPRIUkrQTup8z+rwReB/Z1OaaoS5Z9IiojaTdwPfApsNf2jx0PKSqU4B9RGUln6GfiDH6Bk4kTQ0vwj4iYQnngGxExhRL8IyKmUIJ/RMQUSvCPiJhCCf4REVMowT8iYgr9C6fRLR4c+2XwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for col in [\"languages\",\"industry\",\"sector\",\"competitors\"]:\n",
    "    plt.figure()\n",
    "    cat_count = df.explode(col)[col].value_counts()[0:40]\n",
    "    if '-1' in cat_count.index:\n",
    "        cat_count = cat_count.drop('-1', axis=0)\n",
    "    chart = sns.barplot(x=cat_count.index, y=cat_count)\n",
    "    chart.set_xticklabels(chart.get_xticklabels(),rotation=90)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>avg_salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seniority</th>\n",
       "      <th>role</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>senior</th>\n",
       "      <th>de</th>\n",
       "      <td>53326.923077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">junior</th>\n",
       "      <th>mle</th>\n",
       "      <td>50750.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ds</th>\n",
       "      <td>50329.371817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">senior</th>\n",
       "      <th>ds</th>\n",
       "      <td>49588.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>analyst</th>\n",
       "      <td>49518.518519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">junior</th>\n",
       "      <th>research</th>\n",
       "      <td>47500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de</th>\n",
       "      <td>47321.782178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>senior</th>\n",
       "      <th>research</th>\n",
       "      <td>47000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>junior</th>\n",
       "      <th>analyst</th>\n",
       "      <td>46725.806452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>senior</th>\n",
       "      <th>mle</th>\n",
       "      <td>45793.103448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>junior</th>\n",
       "      <th>intern</th>\n",
       "      <td>43500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>senior</th>\n",
       "      <th>intern</th>\n",
       "      <td>33500.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      avg_salary\n",
       "seniority role                  \n",
       "senior    de        53326.923077\n",
       "junior    mle       50750.000000\n",
       "          ds        50329.371817\n",
       "senior    ds        49588.750000\n",
       "          analyst   49518.518519\n",
       "junior    research  47500.000000\n",
       "          de        47321.782178\n",
       "senior    research  47000.000000\n",
       "junior    analyst   46725.806452\n",
       "senior    mle       45793.103448\n",
       "junior    intern    43500.000000\n",
       "senior    intern    33500.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index=['seniority','role'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by revenue\n",
    "#pd.pivot_table(df[df.role=='ds'], index=['avg_revenue'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by rating\n",
    "#pd.pivot_table(df[df.role=='ds'], index=['ratings'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by industry\n",
    "#pd.pivot_table(df[df.role=='ds'].explode('industry'), index=['industry'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by Sector\n",
    "#pd.pivot_table(df[df.role=='ds'].explode('sector'), index=['sector'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by num_comp\n",
    "#pd.pivot_table(df[df.role=='ds'], index=['num_comp'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by each Language\n",
    "#pd.pivot_table(df[df.role=='ds'].explode('languages'), index=['languages'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Salary by ownership\n",
    "#pd.pivot_table(df[df.role=='ds'], index=['ownership'], values='avg_salary').sort_values(by='avg_salary', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Title\n",
      "                                                      avg_salary\n",
      "Job Title                                                       \n",
      "BIG DATA ARCHITECT                                  87000.000000\n",
      "Applied Scientist - Information Retrieval and N...  87000.000000\n",
      "Clinical Development Scientist - Oncology Haema...  87000.000000\n",
      "Chief Data Scientist (AI, Data Science)             87000.000000\n",
      "Chemical Development Scientist                      87000.000000\n",
      "Lead Scientist - Next Generation Sequencing         87000.000000\n",
      "Data Platform Software Engineer                     87000.000000\n",
      "Bioinformatics Data Manager                         87000.000000\n",
      "Digital Scientist, Associate Director, Oncology...  87000.000000\n",
      "Computational Genetics Scientist                    87000.000000\n",
      "Senior Development Scientist                        87000.000000\n",
      "Senior Organizational Development Scientist         87000.000000\n",
      "Head of Data Strategy (remote working)              87000.000000\n",
      "Software Developer/Scientist – Crystallography      87000.000000\n",
      "Data Platform Engineer (Cloud, DevOps)              87000.000000\n",
      "PBPK Modelling and Simulation Scientist             87000.000000\n",
      "AI Scientist - Computer Vision                      87000.000000\n",
      "Analytical Chemistry Scientist - HPLC Analysis      82000.000000\n",
      "Senior Data Scientist - Remote & Cambridge - 80...  82000.000000\n",
      "Data Scientist/Lead                                 82000.000000\n",
      "Data Innovation Project Manager                     82000.000000\n",
      "Head of Data and Analytics                          82000.000000\n",
      "BioInformatics Data Scientist                       82000.000000\n",
      "Senior Decision Scientist                           82000.000000\n",
      "Principal Data Scientist - Marketing                82000.000000\n",
      "Senior Data Scientist - Forecasting                 82000.000000\n",
      "Scientist, Data, Methods and Analytics Immuno-i...  82000.000000\n",
      "Associate Scientist, Cell & Gene Therapy Techno...  82000.000000\n",
      "Senior Applied Data Scientist                       82000.000000\n",
      "Data Scientist - Engineering and Product            82000.000000\n",
      "Assay Development Scientist                         82000.000000\n",
      "Team Lead, Analytics Data Preparation               82000.000000\n",
      "Chemical Assay Scientist                            68000.000000\n",
      "Molecular Virology Scientist                        68000.000000\n",
      "Principal Electro-optic Materials Scientist         68000.000000\n",
      "Senior Scientist, Downstream                        68000.000000\n",
      "Data Entry Administrator (Night Shift)              68000.000000\n",
      "Scientist I- Toxicology                             68000.000000\n",
      "Senior Devops - Applied Data Science for Global...  68000.000000\n",
      "Data Catalogue Lead                                 68000.000000\n",
      "Senior Purification Scientist                       68000.000000\n",
      "Technical Transfer Scientist                        68000.000000\n",
      "Business Data Steward                               66500.000000\n",
      "Senior Consultant, Cloud Data Solution Architec...  66500.000000\n",
      "Senior Environmental Scientist                      66500.000000\n",
      "Principal Consultant - Data Scientist               66500.000000\n",
      "Data Architect                                      66000.000000\n",
      "Data Scientist - Reinforcement Learning             64500.000000\n",
      "Principal Data Scientist (Fintech)                  64500.000000\n",
      "Data Modeller                                       64500.000000\n",
      "senior data scientist - remote & cambridge - 80...  64500.000000\n",
      "Mid-Senior Data Scientist                           64500.000000\n",
      "Geo Spatial Data Scientist/Engineer                 64500.000000\n",
      "Data Scientist (KTP Associate)                      64500.000000\n",
      "Sports Data Scientist                               64500.000000\n",
      "Senior Scientist - Data Science - Structural Bi...  64500.000000\n",
      "Senior Data Scientist, Operations                   64500.000000\n",
      "Scientist Flu BPD                                   64500.000000\n",
      "Computational Genomics Scientist                    62000.000000\n",
      "rotein Scientist                                    62000.000000\n",
      "Data Specification Specialist - IRC                 62000.000000\n",
      "Senior Data Scientist / ML Engineer                 62000.000000\n",
      "Investigator Scientist - Structural Studies - D...  62000.000000\n",
      "Senior Analytical Scientist - Pharmaceuticals       62000.000000\n",
      "Data Scientist - (Business Consultancy / Analysis)  61500.000000\n",
      "Marketing Mix Model Data Scientist                  61500.000000\n",
      "Data Scientist - Absence Intelligence               61500.000000\n",
      "Data Scientist (Python)                             61500.000000\n",
      "Data Scientist - Genomics                           61500.000000\n",
      "Data Scientist, Managed Rules                       61500.000000\n",
      "Healthcare Data Scientist                           61500.000000\n",
      "Data Scientist / Senior Data Scientist              61500.000000\n",
      "Graduate Data Scientist                             61500.000000\n",
      "Regulatory Reporting - Data Scientist               61500.000000\n",
      "Senior Data Scientist - Curve Credit.               61500.000000\n",
      "Applied Scientist - Personalization                 61000.000000\n",
      "In Vivo Scientist                                   60000.000000\n",
      "Drug Discovery Scientist                            60000.000000\n",
      "HCPC Registered Biomedical Scientist                60000.000000\n",
      "Senior Data Consultant                              60000.000000\n",
      "Reporting Scientist (Toxicology)                    60000.000000\n",
      "Senior Data Warehouse/ETL Engineer                  60000.000000\n",
      "QC Analytical Scientist                             60000.000000\n",
      "Sr. SAS Programmer / Data Manager (Associcate S...  60000.000000\n",
      "Product Manager - Data                              60000.000000\n",
      "Pharmacovigilance Safety Scientist, Manager         60000.000000\n",
      "Data scientist VP                                   59250.000000\n",
      "Principal Data Scientist                            58750.000000\n",
      "Bioassay Scientist                                  58625.000000\n",
      "Head of Data Science                                58285.714286\n",
      "EMEA Senior Data Scientist I                        57833.333333\n",
      "Data Scientist Lead                                 57000.000000\n",
      "Data Science Manager                                56083.333333\n",
      "GPS Scientist                                       56000.000000\n",
      "Senior Specialist Biomedical Scientist              56000.000000\n",
      "Data Scientist - suit PhD - Sept/Oct start          56000.000000\n",
      "Head Data Strategy & Management                     56000.000000\n",
      "Senior Assay Development Scientist - Diagnostics    55500.000000\n",
      "Pan-Prostate Cancer Group Data Manager              55250.000000\n",
      "Biomedical Scientist Virology                       55000.000000\n",
      "Epidemiological Support Scientist (SD20/82)         55000.000000\n",
      "Biomedical Scientist/Specialist Biomedical Scie...  55000.000000\n",
      "Associate Scientist Bioscience                      55000.000000\n",
      "Senior Scientist (Bioscience)                       55000.000000\n",
      "Residue Scientist                                   55000.000000\n",
      "R Developer / Data Developer - Fully Remote - 1...  55000.000000\n",
      "Senior Support Scientist / Beamline Scientist       55000.000000\n",
      "Crop Protection Modelling Scientist                 55000.000000\n",
      "Data Insight Consultant                             55000.000000\n",
      "Lead Data Scientist - Consumer Behaviour            54500.000000\n",
      "Head of Data Science (findajob)                     54500.000000\n",
      "BXB Digital: Data Scientist                         54500.000000\n",
      "Data Scientist - AWS Sagemaker                      54000.000000\n",
      "Data Scientist (Fixed Term Contract)                54000.000000\n",
      "Data Scientist, Legal                               54000.000000\n",
      "Data Scientist - Cyber                              54000.000000\n",
      "Data Scientist - Marketing                          54000.000000\n",
      "Data Analytics Statistician/Data Scientist          54000.000000\n",
      "Data Scientist (Carra)                              54000.000000\n",
      "Data Scientist, Product                             54000.000000\n",
      "DATA SCIENTIST                                      54000.000000\n",
      "AI Scientist                                        54000.000000\n",
      "Data Scientist - Menu Tribe                         54000.000000\n",
      "Data Scientist / ML Engineer                        54000.000000\n",
      "Consultant, Data Scientist, Defence and Securit...  54000.000000\n",
      "Data Scientist - Talent Pool (m/f/d)                54000.000000\n",
      "Applied Scientist - IR and NLP                      53166.666667\n",
      "Lead Data Scientist - Product                       53000.000000\n",
      "Lead Data Scientist                                 52708.333333\n",
      "CDO Data Scientist                                  52500.000000\n",
      "Earth Observation Scientists                        52000.000000\n",
      "NLP Data Scientist                                  52000.000000\n",
      "Principal Advisory Consultant – Data Science        52000.000000\n",
      "Scientists – Secure Navigation and Sensing          51750.000000\n",
      "Statistical Scientist                               51750.000000\n",
      "Senior Data Scientist - Oncology                    51750.000000\n",
      "Analytic Consulting, Data Scientist                 51750.000000\n",
      "Senior Data Scientist - Digital                     51750.000000\n",
      "Consultant, Data Scientist, Defence and Securit...  51750.000000\n",
      "Data Product Technical Lead – Data Scientist        51750.000000\n",
      "Clinical Data Scientist                             51750.000000\n",
      "Data Scientist - Fintech                            51750.000000\n",
      "Formulation Design and Development Scientist        51187.500000\n",
      "Data Scientist                                      51125.000000\n",
      "Coastal Process Scientist                           50750.000000\n",
      "Senior Manager Data Scientist                       50750.000000\n",
      "Data Scientist - AI & ML - UK Projects              50500.000000\n",
      "Development Scientist                               50500.000000\n",
      "Senior Data Scientist (Growth Tribe)                50500.000000\n",
      "SENIOR DATA SCIENTIST                               50500.000000\n",
      "Bioinformatics Scientist – Algorithm Developer      50500.000000\n",
      "R&D Principal Scientist                             50500.000000\n",
      "Computational and Data Scientist                    50500.000000\n",
      "Senior Data Scientist (Business Intelligence an...  50500.000000\n",
      "Scientist, Cell & Gene Therapy Technologies         50500.000000\n",
      "Particle and Powder Characterisation Scientist      49500.000000\n",
      "Bioinformatics Scientist                            49500.000000\n",
      "Data Scientist – Office based in Sofia, Bulgaria    49500.000000\n",
      "Analytical Scientist API                            49500.000000\n",
      "Data Scientist - Computer Vision                    49500.000000\n",
      "Senior Scientist - Secure Navigation                49500.000000\n",
      "Level 6 (Degree) Apprentice - Data Science          49333.333333\n",
      "Senior Pharmacovigilance Scientist                  49333.333333\n",
      "Data Architect - Data Steward                       49250.000000\n",
      "Data Discovery Manager                              49250.000000\n",
      "Medical Scientist (Late Stage Oncology)             49000.000000\n",
      "Lead Scientist - Enzymology & Protein Engineering   49000.000000\n",
      "Senior Scientist Cell Therapy                       49000.000000\n",
      "Delivery Director (Data) / Senior Engagement Pr...  49000.000000\n",
      "Senior Biomedical Scientist (Multidisciplinary ...  49000.000000\n",
      "Senior Medical Safety Scientist, Oncology           49000.000000\n",
      "Senior Associate QC Scientist (12 month Fixed T...  49000.000000\n",
      "Senior Principal Scientist - Process Developmen...  49000.000000\n",
      "SENIOR SCIENTIST: CELL TECHNOLOGIES                 49000.000000\n",
      "Associate Scientist - Chemistry                     49000.000000\n",
      "Virology Scientist (Physio-chemistry)               49000.000000\n",
      "Biotransformation Scientist and DMPK Design Lead    49000.000000\n",
      "Senior Data Scientist                               48914.634146\n",
      "Senior Applied Scientist                            48500.000000\n",
      "Software Developer/Scientist - Crystallography      48277.777778\n",
      "Senior Data Scientist (Geospatial Data Exploita...  48000.000000\n",
      "Insights Data Scientist                             48000.000000\n",
      "Data Scientist 1                                    48000.000000\n",
      "Data Scientist - App Store, Apple Music, Apple ...  48000.000000\n",
      "Data Scientist – Causality Expert                   48000.000000\n",
      "Data Scientist (SaaS)                               48000.000000\n",
      "Marketing Data Analytics Lead                       48000.000000\n",
      "Senior Data Scientist - Marketing Science           47975.000000\n",
      "Principal Applied Scientist                         47694.444444\n",
      "Client Facing Data Scientist                        47617.647059\n",
      "Level 6 (Degree) Apprentice - Data Science, AI&...  47394.736842\n",
      "Data Science Lead                                   47052.631579\n",
      "Customer Analytics Data Scientist                   47000.000000\n",
      "Applied Scientist - Automatic Speech Recognition    46815.789474\n",
      "Senior Data Scientist (Belfast, UK)                 45785.714286\n",
      "Radio Frequency Physics Effects (RF PE) Scienti...  45500.000000\n",
      "Senior Scientist: Pooled CRISPR Screening           45500.000000\n",
      "Senior Epidemiology Scientist (Real-time Syndro...  45500.000000\n",
      "CRUK ECRIN-M3 Data Manager in B-cell Malignancies   45500.000000\n",
      "Scientist I - Validation Project Manager            45500.000000\n",
      "Senior Project Scientist Late RIA                   45500.000000\n",
      "Data Visualization/BI professional (Entry-Level...  45000.000000\n",
      "Data Scientists                                     45000.000000\n",
      "HR Data Scientist                                   45000.000000\n",
      "Data Scientist I                                    45000.000000\n",
      "Data Scientist - ZISHI Adaptive                     45000.000000\n",
      "Data Scientist Associate                            45000.000000\n",
      "Junior Data Scientist                               45000.000000\n",
      "Artificial Intelligence – Data Scientist            45000.000000\n",
      "Data Scientist - Applied Science                    45000.000000\n",
      "Data Scientist, Digital                             45000.000000\n",
      "Lead Data Scientist - Head of People Analytics      45000.000000\n",
      "Data Scientist/Bioinformatician with expertise ...  45000.000000\n",
      "Senior Scientist & Project Manager - Chromatogr...  45000.000000\n",
      "RWE Data Scientist                                  45000.000000\n",
      "Senior Data Scientist - London-Remote - £70k-£80k   44500.000000\n",
      "Data Scientist - Return to Engineering              44500.000000\n",
      "Healthcare Scientist (Health Protection)            44000.000000\n",
      "Senior Data Lab Architect                           44000.000000\n",
      "Specialist Biomedical Scientist (Virology)          44000.000000\n",
      "Senior Scientist – Translational Genomics, Tran...  44000.000000\n",
      "Protein Scientist                                   44000.000000\n",
      "Scientist / Engineer, Process Validation            44000.000000\n",
      "Scientist - New Modalities and Parenteral Devel...  44000.000000\n",
      "CPRD Data Scientist - £39,853 p.a. + benefits       44000.000000\n",
      "Mass Spectrometry Proteomics Scientist              44000.000000\n",
      "Clinical Scientist - Early Phase Oncology           44000.000000\n",
      "Principal Scientist - Biomarker Specialist          44000.000000\n",
      "Senior Analytical Development Scientist - Clean...  42500.000000\n",
      "Senior Data Developer & Data Tools specialist -...  42500.000000\n",
      "Informatics Scientist, Data Management              42500.000000\n",
      "Investigator Scientist                              42500.000000\n",
      "Head of Data Science and Engineering                42500.000000\n",
      "20N/SPTR Temporary Scientists – PCR (20N/SPTR)      42500.000000\n",
      "Audience Measurement - Senior Data Scientist        42500.000000\n",
      "Associate Scientists                                42500.000000\n",
      "Director of Applied Data Science - Financial Se...  42500.000000\n",
      "Associate Principal Scientist - Characterisation    42500.000000\n",
      "Data Curation Director                              42500.000000\n",
      "QC Scientist III - Molecular Biology & Virology     42500.000000\n",
      "Product Manager - Data Platforms                    42500.000000\n",
      "Scientist - Chemical Epigenetics 10                 42500.000000\n",
      "QC Scientist                                        42500.000000\n",
      "Scientist                                           42500.000000\n",
      "(Associate Principal/Sr) Clinical Genomics Scie...  42500.000000\n",
      "Data Asset Management Director                      42500.000000\n",
      "Data Scientist Engineer (Python AI/ML)              41500.000000\n",
      "CPRD Data Scientist                                 41500.000000\n",
      "Software Engineer (Data)                            41500.000000\n",
      "Data Solutions Lead, Associate Director             41500.000000\n",
      "Data Scientist - SC/DV Clearance                    41500.000000\n",
      "Data Scientist (Cyber Security / AI startup)        41500.000000\n",
      "Data Scientist - Defence Consultancy                41500.000000\n",
      "Data Scientist, Sample Management                   41500.000000\n",
      "Data Scientist - AI                                 41500.000000\n",
      "Data Scientist - Causality Inference and Discovery  41500.000000\n",
      "Creative Data Scientist                             41500.000000\n",
      "Senior Data Scientist, Product Analytics (Belfa...  41400.000000\n",
      "Sr Data Scientist                                   41166.666667\n",
      "Computer Scientist                                  41000.000000\n",
      "Lead Data Scientist - Digital                       41000.000000\n",
      "Senior Data Scientist - Premium Analytics (Paym...  40500.000000\n",
      "Bioinformatics Data Scientist                       40500.000000\n",
      "Data-Scientist/Artificial Intelligence Scientist    40500.000000\n",
      "Data Scientist Specialist                           40500.000000\n",
      "Data Science Fellow - OrgAnalytics (part time)      40500.000000\n",
      "Lead Data Scientist (Maternity Cover)               40500.000000\n",
      "Audience Measurement - Data Scientist               40500.000000\n",
      "Senior Data Scientist – Premium Analytics (Paym...  40500.000000\n",
      "Data Science                                        40500.000000\n",
      "Level 7 (Master's) Graduate Apprentice - Data S...  40500.000000\n",
      "Data Scientist / Software Developer                 40500.000000\n",
      "Data Scientist / Senior Data Scientist - Reading    40500.000000\n",
      "Applied Scientist                                   40500.000000\n",
      "Analytical Development Documentation Scientist      40000.000000\n",
      "Senior Data Scientist - Fully Remote Until Sept...  40000.000000\n",
      "Data Scientist (SC / DV / NPPV3 Cleared)            39750.000000\n",
      "Register for our Data Science Talent Pool           39750.000000\n",
      "Data Scientist - Innovative Applications of Cau...  39750.000000\n",
      "Data Scientist - NLP                                39750.000000\n",
      "Senior Data Scientist - Cambridge-Remote - 3 Mo...  39750.000000\n",
      "Senior Data Scientist (UK Remote)                   39750.000000\n",
      "MIS - Data Scientist                                39750.000000\n",
      "Data Scientist (NLP, Python, R, Linguistics)        39375.000000\n",
      "Senior Scientist                                    35500.000000\n",
      "Biomarker Scientist                                 35500.000000\n",
      "919-SA-33705099-EXT Data Scientist                  35500.000000\n",
      "Senior Data Scientist - Electrical Power Systems    35500.000000\n",
      "Senior Data Scientist - Procurement Team            34500.000000\n",
      "Senior Data Scientist (PSGA Technical Support)      33750.000000\n",
      "RNA Scientist                                       33750.000000\n",
      "Development Scientist ( Assay Development )         33750.000000\n",
      "Data Lead                                           33750.000000\n",
      "919-BA-31427835-EXT - Senior Epidemiology Scien...  33500.000000\n",
      "Senior Scientist Product Characterization           33500.000000\n",
      "Senior Scientist IHC NPD                            33500.000000\n",
      "PKPD Modelling & Simulation Scientists              33500.000000\n",
      "Assistant Scientist 1                               33500.000000\n",
      "Senior Drug Discovery Scientist                     33500.000000\n",
      "Manager, Clinical Scientist                         33500.000000\n",
      "Scientist (Purification Development)                33500.000000\n",
      "Principal Enterprise Architect Data and Decision    33500.000000\n",
      "SCIENTIST: CELL TECHNOLOGIES                        33500.000000\n",
      "Principal Scientist in data driven drug discovery   33500.000000\n",
      "Biomedical Scientist specialising in Histology      33500.000000\n",
      "Scientist – Viral Cell Line Development             33500.000000\n",
      "Visiting Scientist, Core Data Science               32000.000000\n",
      "NLP Scientist                                       32000.000000\n",
      "G4 Lead Data Scientist –                            32000.000000\n",
      "Data Modeler                                        32000.000000\n",
      "Data Consultant                                     32000.000000\n",
      "Scientist - Bioassay / Cell-based Assays            32000.000000\n",
      "Senior Statistician/Data Scientist                  32000.000000\n",
      "Data Strategy & Design Expert                       29500.000000\n",
      "Senior Applied Scientist, Computer Vision           29500.000000\n",
      "Virology Scientist                                  29500.000000\n",
      "Power BI Consultant | Data Analytics & Modelling    29500.000000\n",
      "Head of Data Science - Revolut for Business (fi...  29500.000000\n",
      "Senior Strategic Consultant - Data Science & An...  29500.000000\n",
      "Data Discovery Director                             29500.000000\n",
      "Development Lead Scientist                          25500.000000\n",
      "Real World Evidence Scientist (RWE)                 25500.000000\n",
      "Data Verification and Documentation Group Scien...  25500.000000\n",
      "Senior Applied Scientist - NLP                      25500.000000\n",
      "Solution Architect (Data Science & AI)              25000.000000\n",
      "Job Description\n",
      "                                                      avg_salary\n",
      "Job Description                                                 \n",
      "Due to business growth, there is now an excitin...  87000.000000\n",
      "You want to be the next Herzberg? The next Ryan...  87000.000000\n",
      "Chief Data Scientist (AI, Python, NLP)A leading...  87000.000000\n",
      "Post-graduate degree in Computer Science, Mathe...  87000.000000\n",
      "Company DescriptionEurofins Scientific is an in...  87000.000000\n",
      "Consider joining Eurofins, where people are the...  87000.000000\n",
      "What we’re looking for:Want to join the Chief D...  87000.000000\n",
      "Genestack's mission is to accelerate health dis...  87000.000000\n",
      "At AstraZeneca, we work together across global ...  87000.000000\n",
      "Reading Scientific Services Ltd (RSSL)is a cutt...  87000.000000\n",
      "Data Platform Software EngineerEdinburgh£50000 ...  87000.000000\n",
      "Our Client are building the next generation mar...  87000.000000\n",
      "You'll work in a top tier team of AI experts, s...  87000.000000\n",
      "A Technology DisrupterA consultancy with the be...  87000.000000\n",
      "Job ref: IRC254133Software Developer/Scientist ...  87000.000000\n",
      "Advances in digitalization, data and advance an...  87000.000000\n",
      "CK Group are recruiting for a Senior Developmen...  87000.000000\n",
      "We are currently looking for a Computational Ge...  87000.000000\n",
      "Head of Data Strategy (remote working) - London...  87000.000000\n",
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      "Closing date: Tuesday, 21 Jul 2020Band 6Full Ti...  44000.000000\n",
      "Salary InformationRD005 Senior Scientist: Salar...  44000.000000\n",
      "We are looking for a Process Validation scienti...  44000.000000\n",
      "Senior Scientist - Translational Genomics - Fix...  44000.000000\n",
      "Company DescriptionConsider joining Eurofins, w...  44000.000000\n",
      "We are currently looking for a Mass Spectrometr...  44000.000000\n",
      "Are you a data and analytics specialist? Do you...  44000.000000\n",
      "An opportunity has opened for an experienced Cl...  44000.000000\n",
      "Company DescriptionEurofins Scientific is an in...  44000.000000\n",
      "General Purpose and Scope:Avacta Life Sciences ...  44000.000000\n",
      "Scientist - New Modalities and Parenteral Devel...  44000.000000\n",
      "SummarySalary:£CompetitiveTeam:Data ScienceLoca...  44000.000000\n",
      "Job DescriptionMay include but will not be excl...  42500.000000\n",
      "Would you like to be a part of a Data Science &...  42500.000000\n",
      "Temporary Scientists – PCR (20N/SPTR)Randox req...  42500.000000\n",
      "Are you looking to develop your career in one o...  42500.000000\n",
      "To work within the Group of Dr Sjors Scheres in...  42500.000000\n",
      "Are you an experienced Senior Analyst with equi...  42500.000000\n",
      "Job Overview:Who we are and what we do:Covance ...  42500.000000\n",
      "About the roleYou will be responsible for;Defin...  42500.000000\n",
      "Today Lonza is a global leader in life sciences...  42500.000000\n",
      "This role offers you the unique opportunity to ...  42500.000000\n",
      "Director of Applied Data Science - Financial Se...  42500.000000\n",
      "(Associate Principal / Senior) Clinical Genomic...  42500.000000\n",
      "Cyprotex, part of the Evotec Group, are recruit...  42500.000000\n",
      "LocationSouth WestAbout the jobSummaryAre you a...  42500.000000\n",
      "Brief DescriptionSalary: £31,305 - £34,028 (Ban...  42500.000000\n",
      "Senior Data Developer & Data Tools specialist -...  42500.000000\n",
      "Main Scope of Role:In the Scientific Data Manag...  42500.000000\n",
      "Data Asset Management Director R&D Data OfficeL...  42500.000000\n",
      "LocationEndeavour Way, Wimbledon, London, SW19 ...  42500.000000\n",
      "Scientist - Chemical EpigeneticsOxfordCompetiti...  42500.000000\n",
      "Our missionWant to make a difference in this wo...  41500.000000\n",
      "Data Solutions Lead Associate DirectorAt AstraZ...  41500.000000\n",
      "Alexa find me a job on the Alexa Knowledge team...  41500.000000\n",
      "About UsAt Sensyne Health we combine technology...  41500.000000\n",
      "Position Type :Full timeEducation Desired :Bach...  41500.000000\n",
      "Data Scientist - Defence ConsultancyBristol | u...  41500.000000\n",
      "Our client is an artificial intelligence-driven...  41500.000000\n",
      "Job Title: Data Scientist - AISalary: Circa £45...  41500.000000\n",
      "People Source Consulting are working with a lea...  41500.000000\n",
      "We strongly encourage people of color, lesbian,...  41500.000000\n",
      "We would like to reassure all applicants that w...  41500.000000\n",
      "Data Scientist (NLP, Python, R, Linguistics)Dat...  41500.000000\n",
      "An exciting opportunity has arisen to play a ke...  41500.000000\n",
      "Data Scientist (Cyber Security / AI startup)An ...  41500.000000\n",
      "Base Location: Reading or HavantSalary: up to £...  41500.000000\n",
      "Data Scientist, Sample ManagementLocation: Camb...  41500.000000\n",
      "About DueDilDuedil exists to tell the story beh...  41500.000000\n",
      "What is Slice?Slice is the leading technology a...  41500.000000\n",
      "Bachelor or Master's degree in highly quantitat...  41500.000000\n",
      "MagicLab is looking for a Senior Data Scientist...  41250.000000\n",
      "What is Slice?Slice is the leading technology a...  41000.000000\n",
      "ABOUT CAPCOCapco is a global technology and bus...  41000.000000\n",
      "Deep tech startupLocation: CambridgeFlexible wo...  41000.000000\n",
      "About usLaunched in 2012, Checkout.com is a lea...  40500.000000\n",
      "Genestack's mission is to accelerate health dis...  40500.000000\n",
      "You will be leading the work on re-inventing ho...  40500.000000\n",
      "Yieldify is a customer journey optimization com...  40500.000000\n",
      "Our mission is to break down the barriers of to...  40500.000000\n",
      "Data Scientist - 11 month contract - £320 per d...  40500.000000\n",
      "Love using technology to solve complex problems...  40500.000000\n",
      "Company descriptionAda Mode is an industrial te...  40500.000000\n",
      "We are scientists and engineers who enjoy solvi...  40500.000000\n",
      "Our client is looking for several Data Scientis...  40500.000000\n",
      "Our client is looking for a Data Scientist / Ma...  40500.000000\n",
      "We collect on average 600,000 data points annua...  40500.000000\n",
      "Who are QC?Founded in 2008, we’re an independen...  40500.000000\n",
      "Now, more than ever we are ensuring the continu...  40500.000000\n",
      "About Usmyenergi Ltd is young, progressive, inn...  40500.000000\n",
      "JOB DETAILSDepartment: AIJob Title: Data-Scient...  40500.000000\n",
      "Alexa Shopping Spoken Language Understanding te...  40500.000000\n",
      "Brief DescriptionSalary: £27,390 (year 1) risin...  40500.000000\n",
      "The Premium Analytics team is part of the busin...  40500.000000\n",
      "Racing Post are seeking an experienced Data Sci...  40500.000000\n",
      "Data Scientist - PermanentData Idols are workin...  40500.000000\n",
      "Are you looking to develop your career in one o...  40500.000000\n",
      "Bottomline is at the forefront of digital trans...  40500.000000\n",
      "QUALIFICATIONSCurrently enrolled in or recently...  40500.000000\n",
      "The JobThe Renal Association’s Systems Team has...  40500.000000\n",
      "At Natter.ai we specialise in natural language ...  40500.000000\n",
      "The Premium Analytics team is part of the busin...  40500.000000\n",
      "The online travel market never stands still. At...  40500.000000\n",
      "Interested in Amazon Alexa? Were building the s...  40000.000000\n",
      "We are notonthehighstreet.We’re home to 5,000 p...  40000.000000\n",
      "We are currently looking for a Analytical Devel...  40000.000000\n",
      "PhD Degree in Computer Science, Machine Learnin...  40000.000000\n",
      "A London based Consultancy are looking to add D...  40000.000000\n",
      "Register Your Interest with the FT for our 2020...  39750.000000\n",
      "Senior Data ScientistThis is a UK remote positi...  39750.000000\n",
      "Looking fir excel experts with contact centre e...  39750.000000\n",
      "Data Scientist - NLPData Idols are working with...  39750.000000\n",
      "Our Central Government client based in London a...  39750.000000\n",
      "Customer Analytics Data Scientist18 months FTCS...  39750.000000\n",
      "Streetbees is building the world's first real-t...  39750.000000\n",
      "My client a leading Fintech organisation are cu...  39750.000000\n",
      "It’s a really exciting time for us, as we conti...  39750.000000\n",
      "About the roleAt Tesco, our Data Science team f...  39750.000000\n",
      "SummaryWe are looking for a motivated and high-...  39750.000000\n",
      "Job Title: Senior Data ScientistDo you want to ...  39750.000000\n",
      "Data Scientist (NLP, Python, R, Linguistics)My ...  39375.000000\n",
      "Reporting into the Laboratory Manager, the Scie...  35500.000000\n",
      "At AstraZeneca every one of our employees makes...  35500.000000\n",
      "Ordnance Survey (OS) is the national mapping ag...  35500.000000\n",
      "MBNs client, one of the UK’s most iconic brands...  35500.000000\n",
      "TouMetis Job DescriptionSenior Data Scientist -...  35500.000000\n",
      "LocationLondon, SE1 8UGAbout the jobSummaryPubl...  35500.000000\n",
      "An established consultancy are looking for an e...  35500.000000\n",
      "Back to search resultsPrevious jobNext jobJOB D...  34500.000000\n",
      "Brief DescriptionSalary: £15,769 (year 1) risin...  33750.000000\n",
      "Zuhlke Engineering is an international consulta...  33750.000000\n",
      "For 70 years, Charles River employees have work...  33750.000000\n",
      "What is Slice?Slice is the leading technology a...  33750.000000\n",
      "Ordnance Survey (OS) is the national mapping ag...  33750.000000\n",
      "OverviewhVIVO is a dynamic and pioneering globa...  33750.000000\n",
      "Who we areWe are reinventing personal communica...  33750.000000\n",
      "Senior Scientist Immunohistochemistry – New Pro...  33500.000000\n",
      "...a.dialogApplyBtn {display: none;}Senior Scie...  33500.000000\n",
      "For 70 years, Charles River employees have work...  33500.000000\n",
      "On behalf of our client, we are looking to recr...  33500.000000\n",
      "Biomedical Scientist State HCPC registered only...  33500.000000\n",
      "As a Scientist - Viral Cell Line Development yo...  33500.000000\n",
      "We lead our industry in our development of a st...  33500.000000\n",
      "The Manager, Clinical Scientist (CS) will provi...  33500.000000\n",
      "LocationBirminghamAbout the jobSummaryJob title...  33500.000000\n",
      "Principal Scientist in data driven drug discove...  33500.000000\n",
      "Our mission is to break down the barriers of to...  33500.000000\n",
      "Today Lonza is a global leader in life sciences...  33500.000000\n",
      "If you decline, your information won’t be track...  33500.000000\n",
      "The National Crime Agency (NCA) leads the UK’s ...  32000.000000\n",
      "The Bank of England is the UK's central bank. O...  32000.000000\n",
      "Functional Area:FA - FinanceEstimated Travel Pe...  32000.000000\n",
      "Facebook's mission is to give people the power ...  32000.000000\n",
      "Scientist - Bioassay / Cell-based AssaysBased i...  32000.000000\n",
      "5 billion people, two-thirds of the world’s pop...  32000.000000\n",
      "Company DescriptionThe Rank Group is growing ra...  32000.000000\n",
      "Senior Strategic Consultant - Data Science & An...  29500.000000\n",
      "Outstanding opportunity for a Virology Scientis...  29500.000000\n",
      "Company DescriptionEurofins Scientific is an in...  29500.000000\n",
      "EVEN THOUGH ADVERTISED IN UK ROLE IS BASED IN B...  29500.000000\n",
      "Would you like to be a part of a Data Science &...  29500.000000\n",
      "Site Name: UK - Hertfordshire - Stevenage, USA ...  29500.000000\n",
      "Remote Contract Role - Power BI Consultant - Ju...  29500.000000\n",
      "Job Title: Head of Data Science - Revolut for B...  29500.000000\n",
      "Eurofins Scientific is an international life sc...  25500.000000\n",
      "We are currently looking for a Real World Evide...  25500.000000\n",
      "Weve solved many complex problems to get to whe...  25500.000000\n",
      "About Evaluate LtdEvaluate provides trusted com...  25500.000000\n",
      "Due to an increased number of projects within o...  25500.000000\n",
      "Do you have a combination of deep technical exp...  25000.000000\n",
      "Location\n",
      "                                                      avg_salary\n",
      "Location                                                        \n",
      "Wirral, England                                     87000.000000\n",
      "Weybridge, England                                  87000.000000\n",
      "Shoreditch, England                                 87000.000000\n",
      "Collegeville, PA                                    82000.000000\n",
      "Nottingham, England                                 74250.000000\n",
      "Brentford, England                                  71000.000000\n",
      "York, England                                       68000.000000\n",
      "Crayford, England                                   68000.000000\n",
      "Bromley, England                                    66000.000000\n",
      "Sutton, Bedfordshire, East of England, England      64500.000000\n",
      "Havant, England                                     64500.000000\n",
      "Harpenden, England                                  64500.000000\n",
      "Brighton, England                                   64500.000000\n",
      "Chester, England                                    63250.000000\n",
      "Bracknell, England                                  62250.000000\n",
      "Little Chesterford, England                         62000.000000\n",
      "Abingdon, England                                   61700.000000\n",
      "Newcastle upon Tyne, England                        61500.000000\n",
      "Dartford, England                                   61500.000000\n",
      "Chichester, England                                 60000.000000\n",
      "Aylesbury, England                                  57833.333333\n",
      "Milton Keynes, England                              57500.000000\n",
      "Farnborough, Hampshire, South East England, Eng...  56750.000000\n",
      "Worthing, South East England, England               56000.000000\n",
      "Milton, Oxfordshire, South East England, England    56000.000000\n",
      "Bedford, England                                    55500.000000\n",
      "Hinxton, England                                    55250.000000\n",
      "Reading, England                                    55235.294118\n",
      "Sutton in Ashfield, England                         55000.000000\n",
      "Welwyn Garden City, England                         55000.000000\n",
      "Milton, East Dunbartonshire, Scotland               55000.000000\n",
      "United Kingdom                                      54722.222222\n",
      "Edinburgh, Scotland                                 54409.090909\n",
      "London                                              54000.000000\n",
      "Livingston, Scotland                                54000.000000\n",
      "Hazelwood, England                                  54000.000000\n",
      "Poole, England                                      54000.000000\n",
      "Leominster, England                                 54000.000000\n",
      "Grimsby, England                                    54000.000000\n",
      "Fareham, England                                    54000.000000\n",
      "Greater London                                      54000.000000\n",
      "Peterborough, England                               54000.000000\n",
      "Stevenage, England                                  54000.000000\n",
      "Croydon, England                                    54000.000000\n",
      "Coventry, England                                   54000.000000\n",
      "West Yorkshire                                      54000.000000\n",
      "Lewes, England                                      54000.000000\n",
      "Exeter, England                                     53250.000000\n",
      "Royston, East of England, England                   52875.000000\n",
      "Wilmslow, England                                   52000.000000\n",
      "Kent                                                51500.000000\n",
      "Paddington, England                                 51375.000000\n",
      "Sandwich, England                                   51346.153846\n",
      "Leeds, England                                      51333.333333\n",
      "Malvern, England                                    51000.000000\n",
      "Bolton, England                                     51000.000000\n",
      "Morden, London, England                             50500.000000\n",
      "London, England                                     50097.133758\n",
      "Saffron Walden, England                             49833.333333\n",
      "Slough, Berkshire, South East England, England      49766.666667\n",
      "Oxfordshire                                         49694.444444\n",
      "City of London, England                             49590.909091\n",
      "Kingston upon Hull, England                         49500.000000\n",
      "Portsmouth, South East England, England             49500.000000\n",
      "Cambridge, England                                  49411.585366\n",
      "Birmingham, England                                 49214.285714\n",
      "Sittingbourne, England                              49000.000000\n",
      "Macclesfield, England                               48826.086957\n",
      "Didcot, England                                     48631.578947\n",
      "Liverpool, England                                  48555.555556\n",
      "Warrington, North West England, England             48131.578947\n",
      "Glasgow, Scotland                                   48090.909091\n",
      "Maidenhead, England                                 48055.555556\n",
      "Bristol, England                                    48000.000000\n",
      "Twickenham, England                                 48000.000000\n",
      "Sunbury, England                                    48000.000000\n",
      "Sheffield, England                                  48000.000000\n",
      "Cardiff, Wales                                      48000.000000\n",
      "Okehampton, England                                 48000.000000\n",
      "England                                             47000.000000\n",
      "Oxford, England                                     46785.714286\n",
      "Southampton, England                                46035.714286\n",
      "Greater Manchester                                  45875.000000\n",
      "Belfast, Northern Ireland                           45277.777778\n",
      "Wideopen, England                                   45000.000000\n",
      "Basingstoke, England                                45000.000000\n",
      "Warwick, West Midlands, England                     45000.000000\n",
      "Bourne End, East of England, England                45000.000000\n",
      "Manchester, England                                 45000.000000\n",
      "Whittlesford, England                               44000.000000\n",
      "Malmesbury, England                                 44000.000000\n",
      "Hertfordshire                                       43500.000000\n",
      "South West England                                  42500.000000\n",
      "Crumlin, Wales                                      42500.000000\n",
      "Cheshire                                            42500.000000\n",
      "Cambridge, Cambridgeshire                           42500.000000\n",
      "Harrogate, England                                  42500.000000\n",
      "Loughborough, England                               42500.000000\n",
      "Theale, South West England, England                 40500.000000\n",
      "Ashby de la Zouch, England                          40500.000000\n",
      "Gloucester, England                                 40500.000000\n",
      "Charlbury, England                                  40500.000000\n",
      "Market Rasen, England                               40500.000000\n",
      "Berkshire                                           40000.000000\n",
      "Covent Garden, England                              40000.000000\n",
      "Richmond, London, England                           40000.000000\n",
      "Salford, North West England, England                39750.000000\n",
      "Remote                                              39666.666667\n",
      "Shrewsbury, England                                 35500.000000\n",
      "Tranent, Scotland                                   33500.000000\n",
      "Billingham, England                                 33500.000000\n",
      "Hurley, South East England, England                 33500.000000\n",
      "Stirling, Scotland                                  33500.000000\n",
      "Stevenage, United Kingdom                           29500.000000\n",
      "Headquarters\n",
      "                                       avg_salary\n",
      "Headquarters                                     \n",
      "Copenhagen, Denmark                  87000.000000\n",
      "Bromley, United Kingdom              87000.000000\n",
      "Brentwood, United Kingdom            87000.000000\n",
      "New Milton, United Kingdom           82000.000000\n",
      "Brussels, Belgium                    82000.000000\n",
      "Hammersmith, United Kingdom          82000.000000\n",
      "Abingdon, United Kingdom             71000.000000\n",
      "York, United Kingdom                 68000.000000\n",
      "Douglas, Isle of Man                 66500.000000\n",
      "Overland Park, KS                    66500.000000\n",
      "Trenton, NJ                          64500.000000\n",
      "Sofia, Bulgaria                      64500.000000\n",
      "Diemen, Netherlands                  64500.000000\n",
      "Burton-on-Trent, United Kingdom      64500.000000\n",
      "Hunt Valley, MD                      64500.000000\n",
      "Heidelberg, Germany                  63000.000000\n",
      "Saffron Walden, United Kingdom       62000.000000\n",
      "Boston, MA                           62000.000000\n",
      "Dartford, United Kingdom             61500.000000\n",
      "Marlow, United Kingdom               60500.000000\n",
      "Barcelona, Spain                     60166.666667\n",
      "Rio de Janeiro, Brazil               60000.000000\n",
      "Princeton, NJ                        60000.000000\n",
      "Wirral, United Kingdom               60000.000000\n",
      "Reading, United Kingdom              59083.333333\n",
      "Nottingham, United Kingdom           58000.000000\n",
      "Chichester, United Kingdom           57333.333333\n",
      "Milton Keynes, United Kingdom        57000.000000\n",
      "Brentford, United Kingdom            56600.000000\n",
      "Irving, TX                           56000.000000\n",
      "Boulogne-Billancourt, France         56000.000000\n",
      "Luxembourg, Luxembourg               55500.000000\n",
      "Denver, CO                           55250.000000\n",
      "Edinburgh, United Kingdom            55125.000000\n",
      "Didcot, United Kingdom               55000.000000\n",
      "SUTTON-IN-ASHFIELD, United Kingdom   55000.000000\n",
      "Waltham Abbey, United Kingdom        55000.000000\n",
      "Addlestone, United Kingdom           55000.000000\n",
      "Wilmington, DE                       55000.000000\n",
      "Berkhamsted, United Kingdom          55000.000000\n",
      "San Francisco, CA                    54750.000000\n",
      "Sydney, Australia                    54500.000000\n",
      "Wimbledon, United Kingdom            54500.000000\n",
      "Durham, NC                           54375.000000\n",
      "Burr Ridge, IL                       54333.333333\n",
      "Singapore, Singapore                 54250.000000\n",
      "Milan, Italy                         54000.000000\n",
      "Bolton, United Kingdom               54000.000000\n",
      "Lewes, United Kingdom                54000.000000\n",
      "Mount Laurel, NJ                     54000.000000\n",
      "Nerima, Japan                        54000.000000\n",
      "Birmingham, United Kingdom           54000.000000\n",
      "Wickliffe, OH                        54000.000000\n",
      "Newcastle upon Tyne, United Kingdom  54000.000000\n",
      "Redhill, United Kingdom              54000.000000\n",
      "Newport, United Kingdom              54000.000000\n",
      "Bradford, United Kingdom             54000.000000\n",
      "Cincinnati, OH                       54000.000000\n",
      "Peterborough, United Kingdom         54000.000000\n",
      "Poole, United Kingdom                54000.000000\n",
      "FAREHAM, United Kingdom              54000.000000\n",
      "Düsseldorf, Germany                  54000.000000\n",
      "Raleigh, NC                          54000.000000\n",
      "COLCHESTER, United Kingdom           54000.000000\n",
      "Saint Helier, Jersey                 54000.000000\n",
      "Zurich, Switzerland                  54000.000000\n",
      "Turin, Italy                         53750.000000\n",
      "Exeter, United Kingdom               52750.000000\n",
      "Manchester, United Kingdom           52129.629630\n",
      "San Jose, CA                         51750.000000\n",
      "Oxford, United Kingdom               51666.666667\n",
      "Bristol, United Kingdom              51500.000000\n",
      "Basel, Switzerland                   51477.272727\n",
      "-1                                   51440.677966\n",
      "Hull, United Kingdom                 51166.666667\n",
      "Lyndhurst, United Kingdom            50750.000000\n",
      "TUNBRIDGE WELLS, United Kingdom      50500.000000\n",
      "San Diego, CA                        50166.666667\n",
      "Gottingen, Germany                   50055.555556\n",
      "Mississauga, Canada                  50000.000000\n",
      "Menlo Park, CA                       50000.000000\n",
      "London, United Kingdom               49548.022599\n",
      "Algonquin, IL                        49500.000000\n",
      "Slough, United Kingdom               49500.000000\n",
      "Plantation, FL                       49500.000000\n",
      "Waltham, MA                          49500.000000\n",
      "Glasgow, United Kingdom              49300.000000\n",
      "Tokyo, Japan                         49277.777778\n",
      "Atlanta, GA                          49250.000000\n",
      "Cambridge, United Kingdom            49006.944444\n",
      "Liverpool, United Kingdom            49000.000000\n",
      "Cambridge, MA                        49000.000000\n",
      "Salisbury, United Kingdom            49000.000000\n",
      "Port Washington, NY                  48833.333333\n",
      "Brussel, Belgium                     48722.222222\n",
      "Swindon, United Kingdom              48655.172414\n",
      "Macclesfield, United Kingdom         48638.888889\n",
      "Cupertino, CA                        48000.000000\n",
      "Sheffield, United Kingdom            48000.000000\n",
      "Harpenden, United Kingdom            48000.000000\n",
      "Burbank, CA                          48000.000000\n",
      "Salford, United Kingdom              48000.000000\n",
      "Paris, France                        47700.000000\n",
      "New York, NY                         47412.500000\n",
      "Milwaukee, WI                        47000.000000\n",
      "Wilmington, MA                       45750.000000\n",
      "Waterbeach, United Kingdom           45500.000000\n",
      "Seattle, WA                          45055.555556\n",
      "Frankfurt am Main, Germany           45000.000000\n",
      "Dudley, United Kingdom               45000.000000\n",
      "Didsbury, United Kingdom             45000.000000\n",
      "Lincolnshire, IL                     45000.000000\n",
      "Nuneaton, United Kingdom             44500.000000\n",
      "Southampton, United Kingdom          43277.777778\n",
      "Schlieren, Switzerland               42750.000000\n",
      "Montreal, Canada                     42750.000000\n",
      "Redmond, WA                          42500.000000\n",
      "Burlington, NC                       42500.000000\n",
      "Horsham, United Kingdom              42500.000000\n",
      "Crumlin, United Kingdom              42500.000000\n",
      "Hamburg, Germany                     42500.000000\n",
      "Elk Grove Village, IL                42500.000000\n",
      "Taunton, United Kingdom              42500.000000\n",
      "Headington, United Kingdom           41500.000000\n",
      "Norwich, United Kingdom              41500.000000\n",
      "Jacksonville, FL                     41500.000000\n",
      "Perth, United Kingdom                41500.000000\n",
      "Mc Lean, VA                          41000.000000\n",
      "Welwyn Garden City, United Kingdom   40666.666667\n",
      "Newton, NJ                           40500.000000\n",
      "Chicago, IL                          40500.000000\n",
      "Chipping Norton, United Kingdom      40500.000000\n",
      "Stockholm, Sweden                    40500.000000\n",
      "Portsmouth, NH                       40500.000000\n",
      "STEVENAGE, United Kingdom            40500.000000\n",
      "Maidstone, United Kingdom            40500.000000\n",
      "Pune, India                          39750.000000\n",
      "Bexhill-on-Sea, United Kingdom       39750.000000\n",
      "LONDON, United Kingdom               38500.000000\n",
      "Boise, ID                            35500.000000\n",
      "San Mateo, CA                        35500.000000\n",
      "Streamwood, IL                       34500.000000\n",
      "Stockton-on-Tees, United Kingdom     33500.000000\n",
      "Darmstadt, Germany                   33500.000000\n",
      "Clayton, NC                          33500.000000\n",
      "Maidenhead, United Kingdom           32000.000000\n",
      "Göttingen, Germany                   29500.000000\n",
      "Newtown, PA                          25000.000000\n",
      "seniority\n",
      "             avg_salary\n",
      "seniority              \n",
      "junior     50329.371817\n",
      "senior     49588.750000\n",
      "company_name\n",
      "                                                      avg_salary\n",
      "company_name                                                    \n",
      "CK Group- Science, Clinical and Technical           87000.000000\n",
      "Additional Resources                                87000.000000\n",
      "Eden Scott                                          87000.000000\n",
      "Science & Technology Facilities Council (STFC)      87000.000000\n",
      "Peakon                                              87000.000000\n",
      "William James Consultants                           87000.000000\n",
      "Amazon Dev Centre(Scotland)Ltd                      87000.000000\n",
      "Altius Data                                         87000.000000\n",
      "Direct Line Group                                   87000.000000\n",
      "Valtech                                             82000.000000\n",
      "Capital on Tap                                      82000.000000\n",
      "Springer Nature                                     82000.000000\n",
      "Ntrinsic                                            82000.000000\n",
      "FirstPort                                           82000.000000\n",
      "Newton Colmore Consulting Ltd                       82000.000000\n",
      "Adaptimmune                                         82000.000000\n",
      "dunnhumby                                           82000.000000\n",
      "Anson McCade                                        71750.000000\n",
      "British American Tobacco Holdings Plc               68000.000000\n",
      "Abingdon Health                                     68000.000000\n",
      "SUEZ                                                68000.000000\n",
      "Black & Veatch                                      66500.000000\n",
      "Invenio Business Solutions                          66500.000000\n",
      "PokerStars                                          66500.000000\n",
      "European Bioinformatics Institute (EMBL-EBI)        66500.000000\n",
      "Oxford Biomedica                                    66250.000000\n",
      "Reading Scientific Services                         66000.000000\n",
      "Equal Approach                                      64500.000000\n",
      "Maestro Technologies                                64500.000000\n",
      "SBTech                                              64500.000000\n",
      "Randstad                                            64500.000000\n",
      "Manchester Metropolitan University                  64500.000000\n",
      "Expedia                                             64500.000000\n",
      "Reed Business Information                           64500.000000\n",
      "Monzo Bank                                          64500.000000\n",
      "Agrimetrics                                         64500.000000\n",
      "MADE.COM                                            64500.000000\n",
      "McCormick & Company                                 64500.000000\n",
      "Genestack Ltd                                       63750.000000\n",
      "PGSM Consulting                                     63500.000000\n",
      "Arabesque                                           63500.000000\n",
      "Domainex                                            62000.000000\n",
      "Guardian News & Media                               62000.000000\n",
      "Network Rail                                        62000.000000\n",
      "Vertex Pharmaceuticals                              62000.000000\n",
      "Medical Research Council                            62000.000000\n",
      "Doji Ltd                                            62000.000000\n",
      "e-days                                              61500.000000\n",
      "Avumi                                               61500.000000\n",
      "EDF Trading                                         61500.000000\n",
      "Huxley Associates                                   61500.000000\n",
      "EdPlace                                             61500.000000\n",
      "Curve                                               61500.000000\n",
      "Vyn SmartVideoNotes                                 61500.000000\n",
      "Badoo                                               61500.000000\n",
      "BAE Systems UK                                      61500.000000\n",
      "Laing O'Rourke                                      61500.000000\n",
      "Cloudflare                                          61500.000000\n",
      "Origami Energy                                      61500.000000\n",
      "London Stock Exchange Group                         61500.000000\n",
      "Bowerford Associates                                61500.000000\n",
      "CashFlows                                           61500.000000\n",
      "Real Time Consultants                               61500.000000\n",
      "Sainsburys                                          61500.000000\n",
      "Geollect Limited                                    61500.000000\n",
      "McGinley Support Services (Infrastructure) Ltd      61500.000000\n",
      "DataSpartan Consulting                              60500.000000\n",
      "Eurofins Biopharma Product Testing Ireland Limited  60166.666667\n",
      "Cazana                                              60000.000000\n",
      "Russell Taylor Group Ltd                            60000.000000\n",
      "Cellmark Forensic Services                          60000.000000\n",
      "Outra Limited                                       60000.000000\n",
      "Certara                                             60000.000000\n",
      "Novafutur                                           59333.333333\n",
      "Western Sussex Hospitals NHS Foundation Trust       57333.333333\n",
      "Orchard Therapeutics                                56750.000000\n",
      "Deloitte                                            56666.666667\n",
      "Quotient Sciences                                   56250.000000\n",
      "GSK                                                 56166.666667\n",
      "UK Government - Met Office                          56000.000000\n",
      "IPSEN                                               56000.000000\n",
      "Syngenta                                            55666.666667\n",
      "Medical Research Network                            55625.000000\n",
      "Eurofins Scientific                                 55500.000000\n",
      "Talenting                                           55250.000000\n",
      "Sherwood Forest Hospitals NHS Foundation Trust      55000.000000\n",
      "Animal and Plant Health Agency                      55000.000000\n",
      "CitizenMe                                           55000.000000\n",
      "Corteva Agriscience                                 55000.000000\n",
      "The Placement Group                                 55000.000000\n",
      "Quanta                                              55000.000000\n",
      "Diamond Light Source                                55000.000000\n",
      "Oscar Associates                                    54750.000000\n",
      "Domestic & General Group                            54500.000000\n",
      "Search Consultancy                                  54500.000000\n",
      "Brambles                                            54500.000000\n",
      "McCormick                                           54500.000000\n",
      "IQVIA                                               54375.000000\n",
      "Measurelab                                          54000.000000\n",
      "dotdigital                                          54000.000000\n",
      "GR8 CONNECT                                         54000.000000\n",
      "University Hospitals Birmingham NHS Foundation ...  54000.000000\n",
      "Medpace                                             54000.000000\n",
      "Signal AI                                           54000.000000\n",
      "Tec Partners                                        54000.000000\n",
      "HITACHI EUROPE LTD.                                 54000.000000\n",
      "Acorn Recruitment                                   54000.000000\n",
      "Keoghs LLP                                          54000.000000\n",
      "Lubrizol Corporation                                54000.000000\n",
      "Moonshot CVE                                        54000.000000\n",
      "Landmark Information Group                          54000.000000\n",
      "Admiral Insurance                                   54000.000000\n",
      "Specsavers                                          54000.000000\n",
      "Mint Selection                                      54000.000000\n",
      "NRG                                                 54000.000000\n",
      "Medicines Discovery Catapult                        54000.000000\n",
      "Jagex                                               54000.000000\n",
      "Holland & Barrett Retail                            54000.000000\n",
      "Vitality UK                                         54000.000000\n",
      "Calligo                                             54000.000000\n",
      "Founders Factory                                    54000.000000\n",
      "PRA Health Sciences                                 54000.000000\n",
      "Pitchup.com                                         54000.000000\n",
      "Playdemic                                           54000.000000\n",
      "Bet.Me / Easysoft                                   54000.000000\n",
      "Forsyth Barnes                                      54000.000000\n",
      "Deloitte UK                                         54000.000000\n",
      "Deep Labs                                           54000.000000\n",
      "Coople                                              54000.000000\n",
      "RNLI                                                54000.000000\n",
      "Cleo AI                                             54000.000000\n",
      "Citi                                                54000.000000\n",
      "Bwin                                                54000.000000\n",
      "Caresoft Global                                     54000.000000\n",
      "Recruitment Services                                54000.000000\n",
      "The Access Group (UK)                               54000.000000\n",
      "Capital One                                         54000.000000\n",
      "BenevolentAI                                        54000.000000\n",
      "Openreach                                           54000.000000\n",
      "YOOX NET-A-PORTER GROUP                             54000.000000\n",
      "FitXR                                               54000.000000\n",
      "Echobox                                             54000.000000\n",
      "Wm Morrison Supermarkets                            54000.000000\n",
      "Balfour Beatty                                      54000.000000\n",
      "Turner Broadcasting                                 54000.000000\n",
      "BGL Group                                           54000.000000\n",
      "Rentify Ltd.                                        54000.000000\n",
      "Reply                                               53750.000000\n",
      "QinetiQ                                             53300.000000\n",
      "J.P. Morgan                                         52750.000000\n",
      "Hyper Recruitment Solutions LTD                     52700.000000\n",
      "Citibank                                            52625.000000\n",
      "FICO                                                51750.000000\n",
      "Medopad                                             51750.000000\n",
      "Hummingbird Technologies Ltd                        51750.000000\n",
      "EXPLORE AI Limited                                  51750.000000\n",
      "Gousto                                              51666.666667\n",
      "Marks & Spencer                                     51375.000000\n",
      "causaLens                                           51187.500000\n",
      "Agenda Life Sciences                                51166.666667\n",
      "Templeton & Partners                                51000.000000\n",
      "Plum Fintech                                        51000.000000\n",
      "SRG                                                 50952.380952\n",
      "Data Idols                                          50916.666667\n",
      "Lonza                                               50815.789474\n",
      "New Forest District Council                         50750.000000\n",
      "Quintex Consulting                                  50700.000000\n",
      "Gerrard White                                       50500.000000\n",
      "Provectus Recruitment                               50500.000000\n",
      "Sourcific Talent Ltd                                50500.000000\n",
      "Isotropic Systems                                   50500.000000\n",
      "Illumina                                            50166.666667\n",
      "Randstad Technologies                               50100.000000\n",
      "Sartorius                                           50055.555556\n",
      "Facebook                                            50000.000000\n",
      "Ignite Digital                                      50000.000000\n",
      "Abcam                                               50000.000000\n",
      "Pro Clinical                                        49500.000000\n",
      "RB                                                  49500.000000\n",
      "Thermo Fisher Scientific                            49500.000000\n",
      "Oodle Finance                                       49500.000000\n",
      "Marshall Wolfe                                      49500.000000\n",
      "AVEVA                                               49500.000000\n",
      "Shift F5 Limited                                    49300.000000\n",
      "Revolut                                             49166.666667\n",
      "MBR Partners                                        49166.666667\n",
      "AstraZeneca                                         49136.363636\n",
      "NTT Data UK                                         49000.000000\n",
      "Biogen                                              49000.000000\n",
      "GW Pharmaceuticals                                  49000.000000\n",
      "UK Shared Business Services                         49000.000000\n",
      "Redx Pharma                                         49000.000000\n",
      "RLBUH                                               49000.000000\n",
      "Careers at Depop                                    48850.000000\n",
      "Pall                                                48833.333333\n",
      "UCB S.A.                                            48722.222222\n",
      "People Source Consulting                            48166.666667\n",
      "Capco                                               48166.666667\n",
      "Mogrify Ltd                                         48088.235294\n",
      "Colt Technology Services                            48000.000000\n",
      "Davies Group                                        48000.000000\n",
      "Evi Technologies Limited                            48000.000000\n",
      "The Floow Campus                                    48000.000000\n",
      "ProFinda                                            48000.000000\n",
      "Envelop Risk Analytics                              48000.000000\n",
      "Pertemps Thames Water Commercial                    48000.000000\n",
      "MIAC Analytics                                      48000.000000\n",
      "CKM Advisors                                        48000.000000\n",
      "Warner Bros. Entertainment Group                    48000.000000\n",
      "Roc Search Limited                                  48000.000000\n",
      "Selina Finance                                      48000.000000\n",
      "Apple                                               48000.000000\n",
      "SoulTek                                             48000.000000\n",
      "ctrlio Ltd                                          48000.000000\n",
      "Vital Human Resources                               48000.000000\n",
      "Kinect Recruitment Ltd                              48000.000000\n",
      "Lloyd's                                             48000.000000\n",
      "Lynx Recruitment Ltd                                48000.000000\n",
      "Southern Lights Ltd                                 48000.000000\n",
      "iwoca                                               48000.000000\n",
      "Synaptiv                                            48000.000000\n",
      "Rothamsted Research                                 48000.000000\n",
      "SG Digital                                          47694.444444\n",
      "Depop                                               47625.000000\n",
      "Experis                                             47000.000000\n",
      "Ampersand Consulting                                46785.714286\n",
      "British American Tobacco                            46500.000000\n",
      "Peak                                                46500.000000\n",
      "Slice                                               46086.956522\n",
      "Eurofins UK PSS                                     46083.333333\n",
      "Bank of England                                     46000.000000\n",
      "Amazon                                              45937.500000\n",
      "MBN Solutions                                       45833.333333\n",
      "Charles River Laboratories, Inc.                    45750.000000\n",
      "University of Southampton                           45500.000000\n",
      "Tessian                                             45500.000000\n",
      "Horizon Discovery                                   45500.000000\n",
      "G-Research                                          45000.000000\n",
      "Funding Circle UK                                   45000.000000\n",
      "Zebra Technologies                                  45000.000000\n",
      "Newton Europe                                       45000.000000\n",
      "OSTC UK                                             45000.000000\n",
      "Randstad Sourceright                                45000.000000\n",
      "ITECCO Limited                                      45000.000000\n",
      "Concept Resourcing                                  45000.000000\n",
      "Current Health                                      45000.000000\n",
      "Henry Nicholas                                      45000.000000\n",
      "Deutsche Bank                                       45000.000000\n",
      "Lyst                                                45000.000000\n",
      "Capgemini                                           45000.000000\n",
      "STEM Returners                                      44500.000000\n",
      "X4 Group Ltd                                        44250.000000\n",
      "BT                                                  44100.000000\n",
      "NHS National Services Scotland                      44000.000000\n",
      "EMBL                                                44000.000000\n",
      "Avacta Life Sciences Ltd                            44000.000000\n",
      "Met Office                                          44000.000000\n",
      "Medicines and Healthcare Products Regulatory Ag...  44000.000000\n",
      "University Hospital Southampton NHS Foundation ...  44000.000000\n",
      "Dyson                                               44000.000000\n",
      "Ordnance Survey                                     42857.142857\n",
      "Zühlke                                              42750.000000\n",
      "MRC Laboratory of Molecular Biology                 42500.000000\n",
      "Microsoft                                           42500.000000\n",
      "Group Quality and Regulatory Operations             42500.000000\n",
      "Covance                                             42500.000000\n",
      "UK Hydrographic Office                              42500.000000\n",
      "Next Phase Recruitment                              42500.000000\n",
      "Evotec                                              42500.000000\n",
      "Randox Laboratories                                 42500.000000\n",
      "Cyprotex                                            42500.000000\n",
      "Public Health England                               42125.000000\n",
      "Ipsos                                               41833.333333\n",
      "Your.MD                                             41500.000000\n",
      "Streetbees                                          41500.000000\n",
      "DueDil                                              41500.000000\n",
      "Amazon Dev Centre (London) Ltd                      41500.000000\n",
      "Medicines and Healthcare products Regulatory Ag...  41500.000000\n",
      "SSE plc                                             41500.000000\n",
      "Coburg Banks IT                                     41500.000000\n",
      "Sensyne Health                                      41500.000000\n",
      "Chronomics                                          41500.000000\n",
      "AstraZeneca UK                                      41500.000000\n",
      "FIS                                                 41500.000000\n",
      "MagicLab                                            41500.000000\n",
      "Science and Technology Facilities Council           41333.333333\n",
      "INTELLEGENS                                         41000.000000\n",
      "Tesco                                               40666.666667\n",
      "Yieldify                                            40500.000000\n",
      "Tessella                                            40500.000000\n",
      "The Renal Association                               40500.000000\n",
      "myenergi Ltd                                        40500.000000\n",
      "Spotlight Sports Group                              40500.000000\n",
      "QueryClick                                          40500.000000\n",
      "McKinsey & Company                                  40500.000000\n",
      "Intec Select Ltd                                    40500.000000\n",
      "Natter ai                                           40500.000000\n",
      "HealthyHealth                                       40500.000000\n",
      "Expedia Group                                       40500.000000\n",
      "Checkout.com                                        40500.000000\n",
      "Exposed Solutions                                   40500.000000\n",
      "CGI                                                 40500.000000\n",
      "Retail-FCL                                          40500.000000\n",
      "STATS PERFORM                                       40500.000000\n",
      "Bottomline Technologies                             40500.000000\n",
      "Ada Mode                                            40500.000000\n",
      "Spotify                                             40500.000000\n",
      "MThree Consulting                                   40500.000000\n",
      "Notonthehighstreet                                  40000.000000\n",
      "Techmahindra                                        39750.000000\n",
      "Financial Times                                     39750.000000\n",
      "Hastings Direct                                     39750.000000\n",
      "Holland & Barrett International                     39750.000000\n",
      "J Sainsbury                                         39750.000000\n",
      "Koyo                                                39750.000000\n",
      "GB01 Lonza Biologics plc.                           38000.000000\n",
      "Slice (NY)                                          36166.666667\n",
      "Jenrick Commercial                                  35500.000000\n",
      "Toumetis                                            35500.000000\n",
      "Altius Consulting                                   34500.000000\n",
      "Mars                                                34500.000000\n",
      "TouchNote                                           33750.000000\n",
      "hVIVO                                               33750.000000\n",
      "Merck KGaA                                          33500.000000\n",
      "Acculabs Diagnostics UK Ltd                         33500.000000\n",
      "Novo Nordisk Pharmaceutical Industries              33500.000000\n",
      "OXGENE                                              33500.000000\n",
      "Pfizer                                              33500.000000\n",
      "Allen Lane                                          32000.000000\n",
      "AIG                                                 32000.000000\n",
      "Rank Group                                          32000.000000\n",
      "Touch Surgery                                       32000.000000\n",
      "Amey                                                29500.000000\n",
      "Sartorius Corporation                               29500.000000\n",
      "Nodes ApS                                           29500.000000\n",
      "Evaluate Group                                      25500.000000\n",
      "EPAM Systems                                        25000.000000\n",
      "location_city\n",
      "                       avg_salary\n",
      "location_city                    \n",
      "Wirral               87000.000000\n",
      "Shoreditch           87000.000000\n",
      "Weybridge            87000.000000\n",
      "Collegeville         82000.000000\n",
      "Nottingham           74250.000000\n",
      "Brentford            71000.000000\n",
      "York                 68000.000000\n",
      "Crayford             68000.000000\n",
      "Bromley              66000.000000\n",
      "Sutton               64500.000000\n",
      "Harpenden            64500.000000\n",
      "Brighton             64500.000000\n",
      "Havant               64500.000000\n",
      "Chester              63250.000000\n",
      "Bracknell            62250.000000\n",
      "Little Chesterford   62000.000000\n",
      "Abingdon             61700.000000\n",
      "Dartford             61500.000000\n",
      "Newcastle upon Tyne  61500.000000\n",
      "Chichester           60000.000000\n",
      "Aylesbury            57833.333333\n",
      "Milton Keynes        57500.000000\n",
      "Farnborough          56750.000000\n",
      "Worthing             56000.000000\n",
      "Milton               55666.666667\n",
      "Bedford              55500.000000\n",
      "Hinxton              55250.000000\n",
      "Reading              55235.294118\n",
      "Sutton in Ashfield   55000.000000\n",
      "Welwyn Garden City   55000.000000\n",
      "Edinburgh            54409.090909\n",
      "West Yorkshire       54000.000000\n",
      "Leominster           54000.000000\n",
      "Grimsby              54000.000000\n",
      "Lewes                54000.000000\n",
      "Greater London       54000.000000\n",
      "Peterborough         54000.000000\n",
      "Fareham              54000.000000\n",
      "Poole                54000.000000\n",
      "Livingston           54000.000000\n",
      "Croydon              54000.000000\n",
      "Coventry             54000.000000\n",
      "Hazelwood            54000.000000\n",
      "Exeter               53250.000000\n",
      "Royston              52875.000000\n",
      "-1                   52791.666667\n",
      "Wilmslow             52000.000000\n",
      "Kent                 51500.000000\n",
      "Paddington           51375.000000\n",
      "Sandwich             51346.153846\n",
      "Leeds                51333.333333\n",
      "Bolton               51000.000000\n",
      "Malvern              51000.000000\n",
      "Morden               50500.000000\n",
      "London               50109.523810\n",
      "Saffron Walden       49833.333333\n",
      "Slough               49766.666667\n",
      "Oxfordshire          49694.444444\n",
      "City of London       49590.909091\n",
      "Portsmouth           49500.000000\n",
      "Kingston upon Hull   49500.000000\n",
      "Cambridge            49369.696970\n",
      "Birmingham           49214.285714\n",
      "Sittingbourne        49000.000000\n",
      "Macclesfield         48826.086957\n",
      "Didcot               48631.578947\n",
      "Liverpool            48555.555556\n",
      "Warrington           48131.578947\n",
      "Glasgow              48090.909091\n",
      "Maidenhead           48055.555556\n",
      "Okehampton           48000.000000\n",
      "Twickenham           48000.000000\n",
      "Cardiff              48000.000000\n",
      "Sheffield            48000.000000\n",
      "Bristol              48000.000000\n",
      "Sunbury              48000.000000\n",
      "Oxford               46785.714286\n",
      "Southampton          46035.714286\n",
      "Greater Manchester   45875.000000\n",
      "Belfast              45277.777778\n",
      "Basingstoke          45000.000000\n",
      "Bourne End           45000.000000\n",
      "Manchester           45000.000000\n",
      "Wideopen             45000.000000\n",
      "Warwick              45000.000000\n",
      "Malmesbury           44000.000000\n",
      "Whittlesford         44000.000000\n",
      "Hertfordshire        43500.000000\n",
      "South West England   42500.000000\n",
      "Crumlin              42500.000000\n",
      "Harrogate            42500.000000\n",
      "Loughborough         42500.000000\n",
      "Cheshire             42500.000000\n",
      "Theale               40500.000000\n",
      "Charlbury            40500.000000\n",
      "Market Rasen         40500.000000\n",
      "Gloucester           40500.000000\n",
      "Ashby de la Zouch    40500.000000\n",
      "Richmond             40000.000000\n",
      "Covent Garden        40000.000000\n",
      "Berkshire            40000.000000\n",
      "Salford              39750.000000\n",
      "Remote               39666.666667\n",
      "Stevenage            37666.666667\n",
      "Shrewsbury           35500.000000\n",
      "Hurley               33500.000000\n",
      "Tranent              33500.000000\n",
      "Billingham           33500.000000\n",
      "Stirling             33500.000000\n",
      "hq_city\n",
      "                        avg_salary\n",
      "hq_city                           \n",
      "Copenhagen            87000.000000\n",
      "Bromley               87000.000000\n",
      "Brentwood             87000.000000\n",
      "New Milton            82000.000000\n",
      "Brussels              82000.000000\n",
      "Hammersmith           82000.000000\n",
      "Abingdon              71000.000000\n",
      "York                  68000.000000\n",
      "Douglas               66500.000000\n",
      "Overland Park         66500.000000\n",
      "Sofia                 64500.000000\n",
      "Trenton               64500.000000\n",
      "Diemen                64500.000000\n",
      "Burton-on-Trent       64500.000000\n",
      "Hunt Valley           64500.000000\n",
      "Heidelberg            63000.000000\n",
      "Saffron Walden        62000.000000\n",
      "Boston                62000.000000\n",
      "Dartford              61500.000000\n",
      "Marlow                60500.000000\n",
      "Barcelona             60166.666667\n",
      "Wirral                60000.000000\n",
      "Rio de Janeiro        60000.000000\n",
      "Princeton             60000.000000\n",
      "Reading               59083.333333\n",
      "Nottingham            58000.000000\n",
      "Chichester            57333.333333\n",
      "Milton Keynes         57000.000000\n",
      "Brentford             56600.000000\n",
      "Boulogne-Billancourt  56000.000000\n",
      "Irving                56000.000000\n",
      "Luxembourg            55500.000000\n",
      "Denver                55250.000000\n",
      "Edinburgh             55125.000000\n",
      "Didcot                55000.000000\n",
      "SUTTON-IN-ASHFIELD    55000.000000\n",
      "Addlestone            55000.000000\n",
      "Waltham Abbey         55000.000000\n",
      "Berkhamsted           55000.000000\n",
      "San Francisco         54750.000000\n",
      "Wimbledon             54500.000000\n",
      "Sydney                54500.000000\n",
      "Durham                54375.000000\n",
      "Burr Ridge            54333.333333\n",
      "Singapore             54250.000000\n",
      "Mount Laurel          54000.000000\n",
      "Birmingham            54000.000000\n",
      "Nerima                54000.000000\n",
      "Redhill               54000.000000\n",
      "Wickliffe             54000.000000\n",
      "Bolton                54000.000000\n",
      "Milan                 54000.000000\n",
      "Lewes                 54000.000000\n",
      "Newcastle upon Tyne   54000.000000\n",
      "Zurich                54000.000000\n",
      "Newport               54000.000000\n",
      "Bradford              54000.000000\n",
      "Cincinnati            54000.000000\n",
      "Peterborough          54000.000000\n",
      "Poole                 54000.000000\n",
      "FAREHAM               54000.000000\n",
      "Düsseldorf            54000.000000\n",
      "Raleigh               54000.000000\n",
      "COLCHESTER            54000.000000\n",
      "Saint Helier          54000.000000\n",
      "Turin                 53750.000000\n",
      "Exeter                52750.000000\n",
      "Manchester            52129.629630\n",
      "San Jose              51750.000000\n",
      "Oxford                51666.666667\n",
      "Bristol               51500.000000\n",
      "Basel                 51477.272727\n",
      "-1                    51440.677966\n",
      "Hull                  51166.666667\n",
      "Lyndhurst             50750.000000\n",
      "TUNBRIDGE WELLS       50500.000000\n",
      "San Diego             50166.666667\n",
      "Gottingen             50055.555556\n",
      "Mississauga           50000.000000\n",
      "Menlo Park            50000.000000\n",
      "London                49548.022599\n",
      "Waltham               49500.000000\n",
      "Algonquin             49500.000000\n",
      "Slough                49500.000000\n",
      "Plantation            49500.000000\n",
      "Glasgow               49300.000000\n",
      "Tokyo                 49277.777778\n",
      "Atlanta               49250.000000\n",
      "Cambridge             49006.211180\n",
      "Liverpool             49000.000000\n",
      "Salisbury             49000.000000\n",
      "Port Washington       48833.333333\n",
      "Brussel               48722.222222\n",
      "Swindon               48655.172414\n",
      "Macclesfield          48638.888889\n",
      "Salford               48000.000000\n",
      "Harpenden             48000.000000\n",
      "Cupertino             48000.000000\n",
      "Sheffield             48000.000000\n",
      "Burbank               48000.000000\n",
      "Paris                 47700.000000\n",
      "Wilmington            47600.000000\n",
      "New York              47412.500000\n",
      "Milwaukee             47000.000000\n",
      "Waterbeach            45500.000000\n",
      "Seattle               45055.555556\n",
      "Frankfurt am Main     45000.000000\n",
      "Didsbury              45000.000000\n",
      "Lincolnshire          45000.000000\n",
      "Dudley                45000.000000\n",
      "Nuneaton              44500.000000\n",
      "Southampton           43277.777778\n",
      "Schlieren             42750.000000\n",
      "Montreal              42750.000000\n",
      "Redmond               42500.000000\n",
      "Horsham               42500.000000\n",
      "Crumlin               42500.000000\n",
      "Hamburg               42500.000000\n",
      "Elk Grove Village     42500.000000\n",
      "Burlington            42500.000000\n",
      "Taunton               42500.000000\n",
      "Perth                 41500.000000\n",
      "Headington            41500.000000\n",
      "Norwich               41500.000000\n",
      "Jacksonville          41500.000000\n",
      "Mc Lean               41000.000000\n",
      "Welwyn Garden City    40666.666667\n",
      "Newton                40500.000000\n",
      "Maidstone             40500.000000\n",
      "Chipping Norton       40500.000000\n",
      "Stockholm             40500.000000\n",
      "Portsmouth            40500.000000\n",
      "STEVENAGE             40500.000000\n",
      "Chicago               40500.000000\n",
      "Pune                  39750.000000\n",
      "Bexhill-on-Sea        39750.000000\n",
      "LONDON                38500.000000\n",
      "Boise                 35500.000000\n",
      "San Mateo             35500.000000\n",
      "Streamwood            34500.000000\n",
      "Clayton               33500.000000\n",
      "Stockton-on-Tees      33500.000000\n",
      "Darmstadt             33500.000000\n",
      "Maidenhead            32000.000000\n",
      "Göttingen             29500.000000\n",
      "Newtown               25000.000000\n",
      "languages\n",
      "              avg_salary\n",
      "languages               \n",
      "matlab      51728.070175\n",
      "hadoop      50833.333333\n",
      "java        50637.096774\n",
      " r          50623.456790\n",
      "aws         50435.897436\n",
      "spark       50112.149533\n",
      "excel       50091.078067\n",
      "sql         49785.714286\n",
      "tensorflow  49708.333333\n",
      "python      49425.818882\n",
      "ownership\n",
      "             avg_salary\n",
      "ownership              \n",
      "third      58454.545455\n",
      "-1         51850.427350\n",
      "private    50422.794118\n",
      "public     49001.103753\n",
      "industry\n",
      "                                      avg_salary\n",
      "industry                                        \n",
      "Real Estate                         68000.000000\n",
      "Utilities                           68000.000000\n",
      "Architectural                       66500.000000\n",
      "Engineering Services                66500.000000\n",
      "Home Furniture and Houseware Shops  64500.000000\n",
      "General Repair                      62000.000000\n",
      "Maintenance                         62000.000000\n",
      "Superstores                         61500.000000\n",
      "General Merchandise                 61500.000000\n",
      "Stock Exchanges                     61500.000000\n",
      "Publishing                          57100.000000\n",
      "Insurance Operators                 55714.285714\n",
      "Accounting                          55500.000000\n",
      "Modelling Agencies                  55250.000000\n",
      "Chemical Manufacturing              55250.000000\n",
      "Talent                              55250.000000\n",
      "Marketing                           55083.333333\n",
      "Advertising                         55083.333333\n",
      "Farm Support Services               55000.000000\n",
      "Colleges                            55000.000000\n",
      "Universities                        55000.000000\n",
      "Aerospace                           54666.666667\n",
      "Defence                             54666.666667\n",
      "Logistics                           54500.000000\n",
      "Supply Chain                        54500.000000\n",
      "Legal                               54000.000000\n",
      "Caravan Parks                       54000.000000\n",
      "Camping                             54000.000000\n",
      "Financial Analytics                 54000.000000\n",
      "Video Games                         54000.000000\n",
      "Network Solutions                   53500.000000\n",
      "Enterprise Software                 53500.000000\n",
      "Consumer Products Manufacturing     52625.000000\n",
      "Building Societies                  52083.333333\n",
      "Banks                               52083.333333\n",
      "Outsourcing                         52007.692308\n",
      "Staffing                            52007.692308\n",
      "Beverage Shops                      51666.666667\n",
      "Telecommunications Manufacturing    51666.666667\n",
      "Energy                              51500.000000\n",
      "Shoe Shops                          51375.000000\n",
      "Department                          51375.000000\n",
      "Clothing                            51375.000000\n",
      "-1                                  51161.764706\n",
      "Gambling                            50833.333333\n",
      "Lending                             50571.428571\n",
      "Biotech                             49914.448669\n",
      "Pharmaceuticals                     49914.448669\n",
      "Asset Management                    49816.666667\n",
      "Investment Banking                  49816.666667\n",
      "Wholesale                           49500.000000\n",
      "Hospitals                           49481.481481\n",
      "Healthcare Services                 49481.481481\n",
      "Financial Transaction Processing    49227.272727\n",
      "Computer Hardware                   48444.444444\n",
      "Software                            48444.444444\n",
      "IT Services                         48331.395349\n",
      "Food                                48083.333333\n",
      "Film Production                     48000.000000\n",
      "Food Production                     48000.000000\n",
      "Distribution                        48000.000000\n",
      "TV Broadcasting                     47250.000000\n",
      "Cable Networks                      47250.000000\n",
      "Consulting                          46781.250000\n",
      "Other Retail Shops                  46357.142857\n",
      "Internet                            45957.142857\n",
      "Brokerage Services                  45000.000000\n",
      "Telecommunications Services         44750.000000\n",
      "Health Shops                        44500.000000\n",
      "Drink Manufacturing                 44500.000000\n",
      "Pharmacies                          44500.000000\n",
      "Electrical                          44000.000000\n",
      "Electronic Manufacturing            44000.000000\n",
      "Construction                        43625.000000\n",
      "Building                            43625.000000\n",
      "Government Agencies                 43466.666667\n",
      "Research                            43321.428571\n",
      "Supermarkets                        42583.333333\n",
      "Grocery Shops                       42583.333333\n",
      "Brokerages                          42500.000000\n",
      "Insurance Agencies                  42500.000000\n",
      "Development                         41541.666667\n",
      "sector\n",
      "                          avg_salary\n",
      "sector                              \n",
      "Real Estate             68000.000000\n",
      "Utilities               57000.000000\n",
      "Gas                     57000.000000\n",
      "Oil                     57000.000000\n",
      "Energy                  57000.000000\n",
      "Accounting              55125.000000\n",
      "Legal                   55125.000000\n",
      "Education               55000.000000\n",
      "Defence                 54666.666667\n",
      "Aerospace               54666.666667\n",
      "Transportation          54500.000000\n",
      "Logistics               54500.000000\n",
      "Travel                  54000.000000\n",
      "Tourism                 54000.000000\n",
      "Media                   53600.000000\n",
      "Entertainment           53357.142857\n",
      "Recreation              53357.142857\n",
      "Arts                    53357.142857\n",
      "Insurance               51750.000000\n",
      "Forestry                51500.000000\n",
      "Agriculture             51500.000000\n",
      "-1                      51161.764706\n",
      "Manufacturing           50750.000000\n",
      "Business Services       50237.623762\n",
      "Finance                 50109.375000\n",
      "Pharmaceuticals         49914.448669\n",
      "Biotech                 49914.448669\n",
      "Maintenance             49750.000000\n",
      "Repair                  49750.000000\n",
      "Building                49750.000000\n",
      "Healthcare              49481.481481\n",
      "Information Technology  48497.191011\n",
      "Retail                  48000.000000\n",
      "Telecommunications      47055.555556\n",
      "Government              43466.666667\n",
      "competitors\n",
      "                                    avg_salary\n",
      "competitors                                   \n",
      "first direct                      87000.000000\n",
      "RSA Group                         87000.000000\n",
      "Veolia                            68000.000000\n",
      "CH2M                              68000.000000\n",
      "American Water                    68000.000000\n",
      "Kiewit Corporation                66500.000000\n",
      "Burns & McDonnell                 66500.000000\n",
      "Thomson Reuters                   64500.000000\n",
      "Bloomberg L.P.                    64500.000000\n",
      "DNAnexus                          63750.000000\n",
      "Biogen                            62000.000000\n",
      "Sanger Institute                  62000.000000\n",
      "News International                62000.000000\n",
      "Daily Mail and General Trust      62000.000000\n",
      "Amey                              62000.000000\n",
      "The Telegraph                     62000.000000\n",
      "Wellcome Trust                    62000.000000\n",
      "Transport for London              62000.000000\n",
      "Bechtel National                  62000.000000\n",
      "Thales                            61500.000000\n",
      "Nasdaq                            61500.000000\n",
      "Rolls-Royce                       61500.000000\n",
      "Babcock International Group       61500.000000\n",
      "Intercontinental Exchange         61500.000000\n",
      "Euronext                          61500.000000\n",
      "AstraZeneca                       56600.000000\n",
      "Merck                             56600.000000\n",
      "Pfizer                            56600.000000\n",
      "PwC                               56000.000000\n",
      "McKinsey & Company                55600.000000\n",
      "LV=                               55500.000000\n",
      "Hays                              54500.000000\n",
      "PageGroup                         54500.000000\n",
      "INC Research                      54375.000000\n",
      "Parexel                           54000.000000\n",
      "Boots Opticians                   54000.000000\n",
      "Wells Fargo                       54000.000000\n",
      "Walt Disney Company               54000.000000\n",
      "Vrbo                              54000.000000\n",
      "Vision Express                    54000.000000\n",
      "Laing O'Rourke                    54000.000000\n",
      "Markel Insurance                  54000.000000\n",
      "Airbnb                            54000.000000\n",
      "ArenaNet                          54000.000000\n",
      "Skanska                           54000.000000\n",
      "Precise                           54000.000000\n",
      "Bet365                            54000.000000\n",
      "Costain                           54000.000000\n",
      "Chubb                             54000.000000\n",
      "Optical Express                   54000.000000\n",
      "Philadelphia Insurance Companies  54000.000000\n",
      "Paddy Power Betfair               54000.000000\n",
      "Blizzard Entertainment            54000.000000\n",
      "Philip Morris International       53666.666667\n",
      "Imperial Brands                   53666.666667\n",
      "Japan Tobacco International       53666.666667\n",
      "Amazon                            53300.000000\n",
      "PPD                               52333.333333\n",
      "PRA Health Sciences               52000.000000\n",
      "Verily Life Sciences              51750.000000\n",
      "DeepMind                          51750.000000\n",
      "Babylon Health                    51750.000000\n",
      "NBCUniversal                      51000.000000\n",
      "Covance                           50815.789474\n",
      "DSM                               50815.789474\n",
      "Perrigo                           50815.789474\n",
      "-1                                50251.020408\n",
      "Thermo Fisher Scientific          50166.666667\n",
      "Robert Walters                    50000.000000\n",
      "Agilent Technologies              49500.000000\n",
      "J.P. Morgan                       49500.000000\n",
      "Illumina                          49500.000000\n",
      "Novartis                          49038.461538\n",
      "GlaxoSmithKline                   49038.461538\n",
      "Roche                             49006.024096\n",
      "Capgemini                         49000.000000\n",
      "Deloitte                          48875.000000\n",
      "Donaldson Company                 48833.333333\n",
      "Parker Hannifin                   48833.333333\n",
      "GE                                48833.333333\n",
      "AbbVie                            48722.222222\n",
      "Apple                             48500.000000\n",
      "Accenture                         48318.181818\n",
      "IQVIA                             48250.000000\n",
      "EY                                48166.666667\n",
      "Premier Group Recruitment         48000.000000\n",
      "Austin Fraser                     48000.000000\n",
      "BT                                48000.000000\n",
      "Samsung Electronics               48000.000000\n",
      "GCS Recruitment                   48000.000000\n",
      "NES Global Talent                 48000.000000\n",
      "Gattaca                           48000.000000\n",
      "Deutsche Telekom                  48000.000000\n",
      "Fircroft                          48000.000000\n",
      "Booking.com                       47250.000000\n",
      "Robert Half                       47000.000000\n",
      "Adecco                            46500.000000\n",
      "Microsoft                         46295.454545\n",
      "Google                            46130.434783\n",
      "NortonLifeLock                    45500.000000\n",
      "Mimecast                          45500.000000\n",
      "Proofpoint                        45500.000000\n",
      "Walmart                           45323.529412\n",
      "ASDA                              45285.714286\n",
      "Sopra Steria                      45000.000000\n",
      "Allegis Global Solutions          45000.000000\n",
      "Cielo                             45000.000000\n",
      "Farfetch                          45000.000000\n",
      "OnDeck                            45000.000000\n",
      "Bond Street                       45000.000000\n",
      "LendingClub                       45000.000000\n",
      "Mandara                           45000.000000\n",
      "CGI                               45000.000000\n",
      "XTB                               45000.000000\n",
      "Tesco                             44500.000000\n",
      "Orange                            44100.000000\n",
      "Vodafone                          44100.000000\n",
      "J Sainsbury                       44000.000000\n",
      "William Hill                      43000.000000\n",
      "Siemens                           42500.000000\n",
      "Fiserv                            41500.000000\n",
      "Jack Henry & Associates           41500.000000\n",
      "First Data                        41500.000000\n",
      "Adyen                             40500.000000\n",
      "IBM                               40500.000000\n",
      "Boston Consulting Group           40500.000000\n",
      "Priceline.com                     40500.000000\n",
      "Stripe                            40500.000000\n",
      "Strategy&                         40500.000000\n",
      "Braintree                         40500.000000\n",
      "Kayak.com                         40500.000000\n",
      "Bain & Company                    40500.000000\n",
      "Booz Allen Hamilton               40500.000000\n",
      "Morrisons                         40300.000000\n",
      "Wipro                             39750.000000\n",
      "Admiral Insurance                 39750.000000\n",
      "Swinton Insurance                 39750.000000\n",
      "HCL Technologies                  39750.000000\n",
      "Infosys                           39750.000000\n",
      "Minted                            33750.000000\n",
      "Moonpig                           33750.000000\n",
      "Shutterfly                        33750.000000\n",
      "Sanofi                            33500.000000\n",
      "Adobe                             32000.000000\n",
      "Balfour Beatty                    29500.000000\n",
      "Atkins                            29500.000000\n",
      "role\n",
      "        avg_salary\n",
      "role              \n",
      "ds    50029.828109\n"
     ]
    }
   ],
   "source": [
    "for col in catagoric_cols:\n",
    "    print(col)\n",
    "    try: \n",
    "        print(pd.pivot_table(df[df.role=='ds'], index=col, values='avg_salary').sort_values(by='avg_salary', ascending=False))\n",
    "    except:\n",
    "        print(pd.pivot_table(df[df.role=='ds'].explode(col), index=col, values='avg_salary').sort_values(by='avg_salary', ascending=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "words = \" \".join(df['Job Description'])\n",
    "\n",
    "def punctuation_stop(text):\n",
    "    \"\"\"remove punctuation and stop words\"\"\"\n",
    "    filtered = []\n",
    "    stop_words = set(stopwords.words('english'))\n",
    "    word_tokens = word_tokenize(text)\n",
    "    for w in word_tokens:\n",
    "        if w not in stop_words and w.isalpha():\n",
    "            filtered.append(w.lower())\n",
    "    return filtered\n",
    "\n",
    "\n",
    "words_filtered = punctuation_stop(words)\n",
    "\n",
    "text = \" \".join([ele for ele in words_filtered])\n",
    "\n",
    "wc= WordCloud(background_color=\"white\",\n",
    "              random_state=1, stopwords=STOPWORDS,\n",
    "              max_words=2000, width=800, height=1500)\n",
    "wc.generate(text)\n",
    "\n",
    "plt.figure(figsize=[10,10])\n",
    "plt.imshow(wc, interpolation=\"bilinear\")\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>Job Title</th>\n",
       "      <th>Job Description</th>\n",
       "      <th>Location</th>\n",
       "      <th>Headquarters</th>\n",
       "      <th>seniority</th>\n",
       "      <th>company_name</th>\n",
       "      <th>location_city</th>\n",
       "      <th>hq_city</th>\n",
       "      <th>ratings</th>\n",
       "      <th>avg_salary</th>\n",
       "      <th>...</th>\n",
       "      <th>industry</th>\n",
       "      <th>sector</th>\n",
       "      <th>competitors</th>\n",
       "      <th>founded</th>\n",
       "      <th>role</th>\n",
       "      <th>num_comp</th>\n",
       "      <th>num_languages</th>\n",
       "      <th>age</th>\n",
       "      <th>description_len</th>\n",
       "      <th>same_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Data Scientist - ZISHI Adaptive</td>\n",
       "      <td>Company DescriptionIn just over 15 years, OSTC...</td>\n",
       "      <td>Bromley, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>OSTC UK</td>\n",
       "      <td>Bromley</td>\n",
       "      <td>London</td>\n",
       "      <td>3.8</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>[Brokerage Services]</td>\n",
       "      <td>[Finance]</td>\n",
       "      <td>[J.P. Morgan, XTB, Mandara]</td>\n",
       "      <td>1999</td>\n",
       "      <td>ds</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>21</td>\n",
       "      <td>4349</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Data Scientist, Digital</td>\n",
       "      <td>The detailsNewton is a high growth and success...</td>\n",
       "      <td>Wideopen, England</td>\n",
       "      <td>Oxford, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>Newton Europe</td>\n",
       "      <td>Wideopen</td>\n",
       "      <td>Oxford</td>\n",
       "      <td>3.9</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>[Consulting]</td>\n",
       "      <td>[Business Services]</td>\n",
       "      <td>[-1]</td>\n",
       "      <td>2001</td>\n",
       "      <td>ds</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>5561</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>Imagine introducing the next generation of tec...</td>\n",
       "      <td>London, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>G-Research</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>4.8</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>[Computer Hardware, Software]</td>\n",
       "      <td>[Information Technology]</td>\n",
       "      <td>[-1]</td>\n",
       "      <td>2001</td>\n",
       "      <td>ds</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "      <td>3349</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Data Scientist</td>\n",
       "      <td>Data ScientistCambridge UK, Gaithersburg, Goth...</td>\n",
       "      <td>Cambridge, England</td>\n",
       "      <td>Cambridge, United Kingdom</td>\n",
       "      <td>junior</td>\n",
       "      <td>AstraZeneca</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>4.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>[Biotech, Pharmaceuticals]</td>\n",
       "      <td>[Biotech, Pharmaceuticals]</td>\n",
       "      <td>[Roche, GlaxoSmithKline, Novartis]</td>\n",
       "      <td>1913</td>\n",
       "      <td>ds</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>107</td>\n",
       "      <td>4825</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Senior Data Scientist</td>\n",
       "      <td>About UsWe want to help small businesses win. ...</td>\n",
       "      <td>London, England</td>\n",
       "      <td>London, United Kingdom</td>\n",
       "      <td>senior</td>\n",
       "      <td>Funding Circle UK</td>\n",
       "      <td>London</td>\n",
       "      <td>London</td>\n",
       "      <td>3.4</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>[Lending]</td>\n",
       "      <td>[Finance]</td>\n",
       "      <td>[LendingClub, OnDeck, Bond Street]</td>\n",
       "      <td>2010</td>\n",
       "      <td>ds</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>3786</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Job Title  \\\n",
       "0  Data Scientist - ZISHI Adaptive   \n",
       "1          Data Scientist, Digital   \n",
       "2                   Data Scientist   \n",
       "3                   Data Scientist   \n",
       "4            Senior Data Scientist   \n",
       "\n",
       "                                     Job Description            Location  \\\n",
       "0  Company DescriptionIn just over 15 years, OSTC...    Bromley, England   \n",
       "1  The detailsNewton is a high growth and success...   Wideopen, England   \n",
       "2  Imagine introducing the next generation of tec...     London, England   \n",
       "3  Data ScientistCambridge UK, Gaithersburg, Goth...  Cambridge, England   \n",
       "4  About UsWe want to help small businesses win. ...     London, England   \n",
       "\n",
       "                Headquarters seniority       company_name location_city  \\\n",
       "0     London, United Kingdom    junior            OSTC UK       Bromley   \n",
       "1     Oxford, United Kingdom    junior      Newton Europe      Wideopen   \n",
       "2     London, United Kingdom    junior         G-Research        London   \n",
       "3  Cambridge, United Kingdom    junior        AstraZeneca     Cambridge   \n",
       "4     London, United Kingdom    senior  Funding Circle UK        London   \n",
       "\n",
       "     hq_city  ratings  avg_salary  ...                       industry  \\\n",
       "0     London      3.8     45000.0  ...           [Brokerage Services]   \n",
       "1     Oxford      3.9     45000.0  ...                   [Consulting]   \n",
       "2     London      4.8     45000.0  ...  [Computer Hardware, Software]   \n",
       "3  Cambridge      4.0     45000.0  ...     [Biotech, Pharmaceuticals]   \n",
       "4     London      3.4     45000.0  ...                      [Lending]   \n",
       "\n",
       "                       sector                         competitors  founded  \\\n",
       "0                   [Finance]         [J.P. Morgan, XTB, Mandara]     1999   \n",
       "1         [Business Services]                                [-1]     2001   \n",
       "2    [Information Technology]                                [-1]     2001   \n",
       "3  [Biotech, Pharmaceuticals]  [Roche, GlaxoSmithKline, Novartis]     1913   \n",
       "4                   [Finance]  [LendingClub, OnDeck, Bond Street]     2010   \n",
       "\n",
       "   role  num_comp  num_languages  age description_len same_state  \n",
       "0    ds         3              5   21            4349          0  \n",
       "1    ds         0              2   19            5561          0  \n",
       "2    ds         0              3   19            3349          1  \n",
       "3    ds         3              0  107            4825          1  \n",
       "4    ds         3              4   10            3786          1  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"glassdoor_jobs_eda.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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