salary/salary-eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "sns.set_palette('husl')\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Login huggingface hub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n",
      "Token is valid (permission: read).\n",
      "Your token has been saved to /Users/daniele/.cache/huggingface/token\n",
      "Login successful\n"
     ]
    }
   ],
   "source": [
    "from huggingface_hub import login\n",
    "from dotenv import load_dotenv\n",
    "import os\n",
    "\n",
    "load_dotenv()\n",
    "login(os.getenv('HUGGINGFACE_TOKEN'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Downlaod dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from datasets import load_dataset\n",
    "\n",
    "DATASET_RAW = \"hugginglearners/data-science-job-salaries\"\n",
    "\n",
    "#dataset = load_dataset(DATASET_RAW, split=\"train\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year experience_level employment_type             job_title  salary  \\\n0       2023               SE              FT          Data Modeler  258700   \n1       2023               SE              FT          Data Modeler  146600   \n2       2023               MI              FT  Data Science Manager  190000   \n3       2023               MI              FT  Data Science Manager  160000   \n4       2023               EN              FT      Research Analyst   90000   \n\n  salary_currency  salary_in_usd employee_residence  remote_ratio  \\\n0             USD         258700                 US             0   \n1             USD         146600                 US             0   \n2             USD         190000                 US           100   \n3             USD         160000                 US           100   \n4             USD          90000                 US           100   \n\n  company_location company_size  \n0               US            M  \n1               US            M  \n2               US            M  \n3               US            M  \n4               US            M  ",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>employment_type</th>\n      <th>job_title</th>\n      <th>salary</th>\n      <th>salary_currency</th>\n      <th>salary_in_usd</th>\n      <th>employee_residence</th>\n      <th>remote_ratio</th>\n      <th>company_location</th>\n      <th>company_size</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>258700</td>\n      <td>USD</td>\n      <td>258700</td>\n      <td>US</td>\n      <td>0</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>146600</td>\n      <td>USD</td>\n      <td>146600</td>\n      <td>US</td>\n      <td>0</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>190000</td>\n      <td>USD</td>\n      <td>190000</td>\n      <td>US</td>\n      <td>100</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>160000</td>\n      <td>USD</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>100</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>EN</td>\n      <td>FT</td>\n      <td>Research Analyst</td>\n      <td>90000</td>\n      <td>USD</td>\n      <td>90000</td>\n      <td>US</td>\n      <td>100</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "#dataset = pd.DataFrame(dataset).drop(columns=['Unnamed: 0'])\n",
    "dataset = pd.read_csv(\"https://ai-jobs.net/salaries/download/salaries.csv\")\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          work_year        salary  salary_in_usd  remote_ratio\ncount  10456.000000  1.045600e+04   10456.000000   10456.00000\nmean    2022.778883  1.704655e+05  149263.499904      36.49101\nstd        0.506937  4.195989e+05   65269.393738      47.58074\nmin     2020.000000  1.400000e+04   15000.000000       0.00000\n25%     2023.000000  1.050000e+05  104640.250000       0.00000\n50%     2023.000000  1.430000e+05  142200.000000       0.00000\n75%     2023.000000  1.882750e+05  185900.000000     100.00000\nmax     2023.000000  3.040000e+07  750000.000000     100.00000",
      "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>work_year</th>\n      <th>salary</th>\n      <th>salary_in_usd</th>\n      <th>remote_ratio</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>10456.000000</td>\n      <td>1.045600e+04</td>\n      <td>10456.000000</td>\n      <td>10456.00000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2022.778883</td>\n      <td>1.704655e+05</td>\n      <td>149263.499904</td>\n      <td>36.49101</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>0.506937</td>\n      <td>4.195989e+05</td>\n      <td>65269.393738</td>\n      <td>47.58074</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>2020.000000</td>\n      <td>1.400000e+04</td>\n      <td>15000.000000</td>\n      <td>0.00000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>2023.000000</td>\n      <td>1.050000e+05</td>\n      <td>104640.250000</td>\n      <td>0.00000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>2023.000000</td>\n      <td>1.430000e+05</td>\n      <td>142200.000000</td>\n      <td>0.00000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>2023.000000</td>\n      <td>1.882750e+05</td>\n      <td>185900.000000</td>\n      <td>100.00000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>2023.000000</td>\n      <td>3.040000e+07</td>\n      <td>750000.000000</td>\n      <td>100.00000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "count     10456.000000\nmean     149263.499904\nstd       65269.393738\nmin       15000.000000\n25%      104640.250000\n50%      142200.000000\n75%      185900.000000\nmax      750000.000000\nName: salary_in_usd, dtype: float64"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['salary_in_usd'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: ylabel='Frequency'>"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset['salary_in_usd'].plot.hist(bins=100, figsize=(14, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "329835.00000000023"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quantile = dataset['salary_in_usd'].quantile(0.99)\n",
    "quantile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dataset = dataset[dataset['salary_in_usd'] < quantile]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: ylabel='Frequency'>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset['salary_in_usd'].plot.hist(bins=100, figsize=(14, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Feature engineering\n",
    "\n",
    "We will use only the salary in USD dollars, so we will drop the other column. Also, we will drop **employee_residence** and **remote_ratio** to reduce the number of useless features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dataset['salary'] = dataset['salary_in_usd']\n",
    "dataset.drop(columns=['salary_in_usd','employee_residence', 'remote_ratio'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year experience_level employment_type             job_title  salary  \\\n0       2023               SE              FT          Data Modeler  258700   \n1       2023               SE              FT          Data Modeler  146600   \n2       2023               MI              FT  Data Science Manager  190000   \n3       2023               MI              FT  Data Science Manager  160000   \n4       2023               EN              FT      Research Analyst   90000   \n\n  salary_currency company_location company_size  \n0             USD               US            M  \n1             USD               US            M  \n2             USD               US            M  \n3             USD               US            M  \n4             USD               US            M  ",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>employment_type</th>\n      <th>job_title</th>\n      <th>salary</th>\n      <th>salary_currency</th>\n      <th>company_location</th>\n      <th>company_size</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>258700</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>146600</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>190000</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>160000</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>EN</td>\n      <td>FT</td>\n      <td>Research Analyst</td>\n      <td>90000</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year experience_level employment_type             job_title  salary  \\\n0       2023               SE              FT          Data Modeler  258700   \n1       2023               SE              FT          Data Modeler  146600   \n2       2023               MI              FT  Data Science Manager  190000   \n3       2023               MI              FT  Data Science Manager  160000   \n4       2023               EN              FT      Research Analyst   90000   \n\n  salary_currency company_location company_size  \n0             USD               US            M  \n1             USD               US            M  \n2             USD               US            M  \n3             USD               US            M  \n4             USD               US            M  ",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>employment_type</th>\n      <th>job_title</th>\n      <th>salary</th>\n      <th>salary_currency</th>\n      <th>company_location</th>\n      <th>company_size</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>258700</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>146600</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>190000</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>160000</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>EN</td>\n      <td>FT</td>\n      <td>Research Analyst</td>\n      <td>90000</td>\n      <td>USD</td>\n      <td>US</td>\n      <td>M</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_currency_list = [\n",
    "    'USD',\n",
    "    'EUR',\n",
    "    'GBP'\n",
    "]\n",
    "\n",
    "dataset['salary_currency'] = dataset['salary_currency'].map(lambda x: x if x in salary_currency_list else 'other_currency')\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year experience_level employment_type             job_title  salary  \\\n0       2023               SE              FT          Data Modeler  258700   \n1       2023               SE              FT          Data Modeler  146600   \n2       2023               MI              FT  Data Science Manager  190000   \n3       2023               MI              FT  Data Science Manager  160000   \n4       2023               EN              FT      Research Analyst   90000   \n\n  company_location company_size    EUR    GBP   USD  \n0               US            M  False  False  True  \n1               US            M  False  False  True  \n2               US            M  False  False  True  \n3               US            M  False  False  True  \n4               US            M  False  False  True  ",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>employment_type</th>\n      <th>job_title</th>\n      <th>salary</th>\n      <th>company_location</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>258700</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>SE</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>146600</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>190000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>MI</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>EN</td>\n      <td>FT</td>\n      <td>Research Analyst</td>\n      <td>90000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = pd.get_dummies(dataset, columns=['salary_currency'],prefix='', prefix_sep='', sparse=False).drop(columns=['other_currency'])\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Experience level\n",
    "\n",
    "We will map the experience level to a number, so we can use it in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "experience_level\nSE    7245\nMI    2177\nEN     643\nEX     286\nName: count, dtype: int64"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['experience_level'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year  experience_level employment_type             job_title  salary  \\\n0       2023                 2              FT          Data Modeler  258700   \n1       2023                 2              FT          Data Modeler  146600   \n2       2023                 1              FT  Data Science Manager  190000   \n3       2023                 1              FT  Data Science Manager  160000   \n4       2023                 0              FT      Research Analyst   90000   \n\n  company_location company_size    EUR    GBP   USD  \n0               US            M  False  False  True  \n1               US            M  False  False  True  \n2               US            M  False  False  True  \n3               US            M  False  False  True  \n4               US            M  False  False  True  ",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>employment_type</th>\n      <th>job_title</th>\n      <th>salary</th>\n      <th>company_location</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>2</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>258700</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>2</td>\n      <td>FT</td>\n      <td>Data Modeler</td>\n      <td>146600</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>190000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>FT</td>\n      <td>Data Science Manager</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>FT</td>\n      <td>Research Analyst</td>\n      <td>90000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experience_level_map = {\n",
    "    'EN': 0,\n",
    "    'MI': 1,\n",
    "    'SE': 2,\n",
    "    'EX': 3\n",
    "}\n",
    "\n",
    "dataset['experience_level'] = dataset['experience_level'].map(experience_level_map)\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Job title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='job_title'>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset['job_title'].value_counts().plot.bar(figsize=(14, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Since there are too meny different job titles, with few samples for each one, we will group them by the most common ones. We will keep only the job titles that summed up makes the 90% of the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "(['Data Engineer',\n  'Data Scientist',\n  'Data Analyst',\n  'Machine Learning Engineer',\n  'Research Scientist',\n  'Applied Scientist',\n  'Analytics Engineer',\n  'Data Architect',\n  'Research Engineer',\n  'Business Intelligence Engineer',\n  'Data Manager',\n  'ML Engineer',\n  'Data Science Manager',\n  'Machine Learning Scientist',\n  'Business Intelligence Analyst',\n  'BI Developer',\n  'Research Analyst',\n  'Data Science Consultant'],\n 18)"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jobs = dataset['job_title'].value_counts()\n",
    "jobs = jobs[jobs.cumsum() < len(dataset) * 0.9]\n",
    "jobs = jobs.index.tolist()\n",
    "jobs, len(jobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='job_title'>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = dataset[dataset['job_title'].isin(jobs)]\n",
    "dataset['job_title'].value_counts().plot.bar(figsize=(14, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots = []\n",
    "for job in jobs:\n",
    "    plots.append(dataset[dataset['job_title'] == job]['salary'].plot.hist(bins=100, figsize=(14, 7), title=job))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#### Employment type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "employment_type\nFT    9286\nPT      12\nCT       6\nFL       4\nName: count, dtype: int64"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['employment_type'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We will use only the full time jobs, so we will drop the other rows. And so drop the column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year  experience_level             job_title  salary company_location  \\\n2       2023                 1  Data Science Manager  190000               US   \n3       2023                 1  Data Science Manager  160000               US   \n4       2023                 0      Research Analyst   90000               US   \n5       2023                 0      Research Analyst   65000               US   \n6       2023                 1         Data Engineer  160000               US   \n\n  company_size    EUR    GBP   USD  Engineer  Scientist  Research  Analyst  \n2            M  False  False  True         0          0         0        0  \n3            M  False  False  True         0          0         0        0  \n4            M  False  False  True         0          0         1        1  \n5            M  False  False  True         0          0         1        1  \n6            M  False  False  True         1          0         0        0  ",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>job_title</th>\n      <th>salary</th>\n      <th>company_location</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n      <th>Engineer</th>\n      <th>Scientist</th>\n      <th>Research</th>\n      <th>Analyst</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>Data Science Manager</td>\n      <td>190000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>Data Science Manager</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>Research Analyst</td>\n      <td>90000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>Research Analyst</td>\n      <td>65000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>Data Engineer</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = dataset[dataset['employment_type'] == 'FT'].drop(columns=['employment_type'])\n",
    "\n",
    "dataset['Engineer'] = dataset['job_title'].apply(lambda x: 1 if 'engineer' in x.lower() else 0)\n",
    "dataset['Scientist'] = dataset['job_title'].apply(lambda x: 1 if 'data scientist' in x.lower() else 0)\n",
    "dataset['Research'] = dataset['job_title'].apply(lambda x: 1 if 'research' in x.lower() else 0)\n",
    "dataset['Analyst'] = dataset['job_title'].apply(lambda x: 1 if 'analyst' in x.lower() else 0)\n",
    "\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year  experience_level  salary company_location company_size    EUR  \\\n2       2023                 1  190000               US            M  False   \n3       2023                 1  160000               US            M  False   \n4       2023                 0   90000               US            M  False   \n5       2023                 0   65000               US            M  False   \n6       2023                 1  160000               US            M  False   \n\n     GBP   USD  Engineer  Scientist  ...  Data Manager  \\\n2  False  True         0          0  ...         False   \n3  False  True         0          0  ...         False   \n4  False  True         0          0  ...         False   \n5  False  True         0          0  ...         False   \n6  False  True         1          0  ...         False   \n\n   Data Science Consultant  Data Science Manager  Data Scientist  ML Engineer  \\\n2                    False                  True           False        False   \n3                    False                  True           False        False   \n4                    False                 False           False        False   \n5                    False                 False           False        False   \n6                    False                 False           False        False   \n\n   Machine Learning Engineer  Machine Learning Scientist  Research Analyst  \\\n2                      False                       False             False   \n3                      False                       False             False   \n4                      False                       False              True   \n5                      False                       False              True   \n6                      False                       False             False   \n\n   Research Engineer  Research Scientist  \n2              False               False  \n3              False               False  \n4              False               False  \n5              False               False  \n6              False               False  \n\n[5 rows x 30 columns]",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>salary</th>\n      <th>company_location</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n      <th>Engineer</th>\n      <th>Scientist</th>\n      <th>...</th>\n      <th>Data Manager</th>\n      <th>Data Science Consultant</th>\n      <th>Data Science Manager</th>\n      <th>Data Scientist</th>\n      <th>ML Engineer</th>\n      <th>Machine Learning Engineer</th>\n      <th>Machine Learning Scientist</th>\n      <th>Research Analyst</th>\n      <th>Research Engineer</th>\n      <th>Research Scientist</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>190000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>90000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>65000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>M</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>1</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 30 columns</p>\n</div>"
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = pd.get_dummies(dataset, columns=['job_title'],prefix='', prefix_sep='', sparse=False)\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#### Company size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "company_size\nM    8530\nL     656\nS     100\nName: count, dtype: int64"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['company_size'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "company_size_map = {\n",
    "    'S': 0,\n",
    "    'M': 1,\n",
    "    'L': 2,\n",
    "}\n",
    "\n",
    "dataset['company_size'] = dataset['company_size'].map(company_size_map)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Company location\n",
    "\n",
    "We will use the country code to get the continent of the company."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pycountry_convert as pc\n",
    "\n",
    "dataset['company_continent'] = dataset['company_location'].apply(lambda x: pc.country_alpha2_to_continent_code(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='company_continent'>"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 700x400 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset['company_continent'].value_counts().sort_index().plot.bar( figsize=(7,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We can see that the majority of the companies are in EU and NA. So we will exclude the other continents, since we don't have enough data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dataset = dataset[dataset['company_continent'].isin(['EU', 'NA'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x169457160>"
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 2 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "salary_avg = dataset.groupby('company_location', as_index=False)['salary'].mean().rename(columns={'salary': 'salary_avg'})\n",
    "\n",
    "ax = dataset['company_location'].value_counts().sort_index().plot.bar( figsize=(14, 7))\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(salary_avg['company_location'],salary_avg['salary_avg'], color='r', marker='o', markersize=3)\n",
    "ax2.legend(['Salary avg'], loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#### CPI (Consumer Price Index)\n",
    "The consumer price index (CPI) measures the average price change of all goods and services purchased by households for consumption purposes, e.g. food, clothing, motor vehicles, rents, cleaning services, repairs, etc.\n",
    "\n",
    "We will take the data of the specific year of the job offer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "\n",
    "def get_gdp_by_country_code(country_code, year=2023, index='FP.CPI.TOTL'):\n",
    "    # World Bank API endpoint for GDP data\n",
    "    api_url = f'http://api.worldbank.org/v2/country/{country_code}/indicator/{index}?data={year}&format=json'\n",
    "\n",
    "\n",
    "    # Make a GET request to the API\n",
    "    response = requests.get(api_url)\n",
    "\n",
    "    # Check if the request was successful (status code 200)\n",
    "    if response.status_code == 200:\n",
    "        # Parse the JSON response\n",
    "        data = response.json()\n",
    "\n",
    "        # Extract the GDP value from the response\n",
    "        gdp_value = data[1][0]['value'] if data[1] else None\n",
    "\n",
    "        return gdp_value\n",
    "    else:\n",
    "        # If the request was not successful, print an error message\n",
    "        print(f\"Error: Unable to fetch data. Status code: {response.status_code}\")\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "     work_year company_location         CPI\n2         2023               US  134.211206\n22        2023               DE  124.489744\n23        2023               GB  133.660070\n87        2023               CA  129.858329\n253       2023               HU  151.411886",
      "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>work_year</th>\n      <th>company_location</th>\n      <th>CPI</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>US</td>\n      <td>134.211206</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2023</td>\n      <td>DE</td>\n      <td>124.489744</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>2023</td>\n      <td>GB</td>\n      <td>133.660070</td>\n    </tr>\n    <tr>\n      <th>87</th>\n      <td>2023</td>\n      <td>CA</td>\n      <td>129.858329</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>2023</td>\n      <td>HU</td>\n      <td>151.411886</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_CPI = dataset[['work_year','company_location']].drop_duplicates()\n",
    "\n",
    "country_CPI['CPI'] = country_CPI.apply(lambda x: get_gdp_by_country_code(x['company_location'], x['work_year']), axis=1)\n",
    "country_CPI.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x169570af0>"
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1800x700 with 2 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.figure(figsize=(18, 7)).gca()\n",
    "country_CPI = country_CPI.sort_values(by=['company_location'])\n",
    "\n",
    "cpi_avg = country_CPI.groupby('company_location', as_index=False)['CPI'].mean().rename(columns={'CPI': 'CPI_avg'})\n",
    "\n",
    "ax.plot(salary_avg['company_location'],salary_avg['salary_avg'], color='r', marker='o', markersize=3)\n",
    "\n",
    "ax.legend(['Salary avg'], loc='upper left')\n",
    "\n",
    "ax3 = ax.twinx()\n",
    "ax3.plot(cpi_avg['company_location'],cpi_avg['CPI_avg'], color='orange')\n",
    "ax3.legend(['CPI'], loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Salary avg inside europe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          salary_avg\ncount      29.000000\nmean    73517.989918\nstd     36363.466877\nmin     28369.000000\n25%     53308.818182\n50%     63040.000000\n75%     88462.000000\nmax    230000.000000",
      "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>salary_avg</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>29.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>73517.989918</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>36363.466877</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>28369.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>53308.818182</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>63040.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>88462.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>230000.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_avg_europe = dataset.where(dataset['company_continent'] == 'EU').groupby('company_location', as_index=False)['salary'].mean().rename(columns={'salary': 'salary_avg'})\n",
    "salary_avg_europe.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x169435220>"
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1400x700 with 2 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = dataset.where(dataset['company_continent'] == 'EU')['company_location'].value_counts().sort_index().plot.bar( figsize=(14, 7))\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(salary_avg_europe['salary_avg'], color='r', marker='o')\n",
    "ax2.legend(['Salary avg'], loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Correlation between salary and CPI in europe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "60"
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_avg_europe_se = dataset.where(dataset['company_continent'] == 'EU')\\\n",
    "                              .where(dataset['company_location'].isin(country_CPI.dropna().company_location))\\\n",
    "                              .groupby(['company_location', 'experience_level'], as_index=False)['salary'].mean().rename(columns={'salary': 'salary_avg'})\n",
    "len(salary_avg_europe_se)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "company_location    60\nexperience_level    60\nsalary_avg          60\nCPI                 60\ndtype: int64"
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_avg_europe_se['CPI']= salary_avg_europe_se['company_location'].apply(lambda x: country_CPI[country_CPI.company_location == x].CPI.values[0])\n",
    "salary_avg_europe_se.dropna(inplace=True)\n",
    "salary_avg_europe_se.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   experience_level      corr      variance  n_samples   p_value\n0               1.0 -0.294793  4.615603e+08         23  0.172093\n1               2.0  0.720948  1.899170e+09         21  0.000227\n2               0.0 -0.241196  4.375489e+08         12  0.450129\n3               3.0  0.581454  1.606456e+09          4  0.418546",
      "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>experience_level</th>\n      <th>corr</th>\n      <th>variance</th>\n      <th>n_samples</th>\n      <th>p_value</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.0</td>\n      <td>-0.294793</td>\n      <td>4.615603e+08</td>\n      <td>23</td>\n      <td>0.172093</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2.0</td>\n      <td>0.720948</td>\n      <td>1.899170e+09</td>\n      <td>21</td>\n      <td>0.000227</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.0</td>\n      <td>-0.241196</td>\n      <td>4.375489e+08</td>\n      <td>12</td>\n      <td>0.450129</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3.0</td>\n      <td>0.581454</td>\n      <td>1.606456e+09</td>\n      <td>4</td>\n      <td>0.418546</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calculate the correlation coefficient with CPI\n",
    "from scipy.stats import pearsonr\n",
    "results =[]\n",
    "for exp in salary_avg_europe_se.experience_level.unique():\n",
    "    corr, p_value = pearsonr(salary_avg_europe_se[salary_avg_europe_se.experience_level == exp]['CPI'], salary_avg_europe_se[salary_avg_europe_se.experience_level == exp]['salary_avg'])\n",
    "    variance = salary_avg_europe_se[salary_avg_europe_se.experience_level == exp]['salary_avg'].var()\n",
    "    n_samples = salary_avg_europe_se[salary_avg_europe_se.experience_level == exp]['salary_avg'].count()\n",
    "    results.append({'experience_level': exp, 'corr': corr, 'variance': variance, 'n_samples': n_samples, 'p_value': p_value})\n",
    "\n",
    "results = pd.DataFrame(results)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#### Correlation between salary and CPI worldwide"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "71"
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_avg_se = dataset.where(dataset['company_location'].isin(country_CPI.dropna().company_location))\\\n",
    "                              .groupby(['company_location', 'experience_level'], as_index=False)['salary'].mean().rename(columns={'salary': 'salary_avg'})\n",
    "len(salary_avg_se)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "company_location    71\nexperience_level    71\nsalary_avg          71\nCPI                 71\ndtype: int64"
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_avg_se['CPI']= salary_avg_se['company_location'].apply(lambda x: country_CPI[country_CPI.company_location == x].CPI.values[0])\n",
    "salary_avg_se.dropna(inplace=True)\n",
    "salary_avg_se.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   experience_level      corr      variance  n_samples   p_value\n0               1.0 -0.250339  7.080258e+08         26  0.217403\n1               2.0  0.625006  2.145775e+09         24  0.001093\n2               0.0 -0.064610  6.294023e+08         14  0.826310\n3               3.0 -0.268470  1.899853e+09          7  0.560477",
      "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>experience_level</th>\n      <th>corr</th>\n      <th>variance</th>\n      <th>n_samples</th>\n      <th>p_value</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.0</td>\n      <td>-0.250339</td>\n      <td>7.080258e+08</td>\n      <td>26</td>\n      <td>0.217403</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2.0</td>\n      <td>0.625006</td>\n      <td>2.145775e+09</td>\n      <td>24</td>\n      <td>0.001093</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.0</td>\n      <td>-0.064610</td>\n      <td>6.294023e+08</td>\n      <td>14</td>\n      <td>0.826310</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3.0</td>\n      <td>-0.268470</td>\n      <td>1.899853e+09</td>\n      <td>7</td>\n      <td>0.560477</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calculate the correlation coefficient with CPI\n",
    "\n",
    "results =[]\n",
    "for exp in salary_avg_se.experience_level.unique():\n",
    "    corr, p_value = pearsonr(salary_avg_se[salary_avg_se.experience_level == exp]['CPI'], salary_avg_se[salary_avg_se.experience_level == exp]['salary_avg'])\n",
    "    variance = salary_avg_se[salary_avg_se.experience_level == exp]['salary_avg'].var()\n",
    "    n_samples = salary_avg_se[salary_avg_se.experience_level == exp]['salary_avg'].count()\n",
    "\n",
    "    results.append({'experience_level': exp, 'corr': corr, 'variance': variance, 'n_samples': n_samples, 'p_value': p_value})\n",
    "\n",
    "results = pd.DataFrame(results)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "From the result above, we can see that the correlation between salary and CPI is medium, and the variance is high. Also, the correlation is negative, which means that the higher the CPI, the lower the salary. This is not what we expected!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Correlation between salary and GDP worldwide"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "     work_year company_location           GDP\n2         2023               US  2.543970e+13\n22        2023               DE  4.082469e+12\n23        2023               GB  3.089073e+12\n87        2023               CA  2.137939e+12\n253       2023               HU  1.773374e+11",
      "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>work_year</th>\n      <th>company_location</th>\n      <th>GDP</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>US</td>\n      <td>2.543970e+13</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2023</td>\n      <td>DE</td>\n      <td>4.082469e+12</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>2023</td>\n      <td>GB</td>\n      <td>3.089073e+12</td>\n    </tr>\n    <tr>\n      <th>87</th>\n      <td>2023</td>\n      <td>CA</td>\n      <td>2.137939e+12</td>\n    </tr>\n    <tr>\n      <th>253</th>\n      <td>2023</td>\n      <td>HU</td>\n      <td>1.773374e+11</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_GDP = dataset[['work_year','company_location']].drop_duplicates()\n",
    "country_GDP['GDP'] = country_CPI.apply(lambda x: get_gdp_by_country_code(x['company_location'], x['work_year'], index='NY.GDP.MKTP.CD'), axis=1)\n",
    "country_GDP.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "company_location    71\nexperience_level    71\nsalary_avg          71\nCPI                 71\nGDP                 71\ndtype: int64"
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_avg_se['GDP']= salary_avg_se['company_location'].apply(lambda x: country_GDP[country_GDP.company_location == x].GDP.values[0])\n",
    "\n",
    "salary_avg_se.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   experience_level      corr      variance  n_samples   p_value\n0               1.0  0.489591  7.080258e+08         26  0.011129\n1               2.0  0.379060  2.145775e+09         24  0.067740\n2               0.0  0.636151  6.294023e+08         14  0.014457\n3               3.0  0.716943  1.899853e+09          7  0.069806",
      "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>experience_level</th>\n      <th>corr</th>\n      <th>variance</th>\n      <th>n_samples</th>\n      <th>p_value</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.0</td>\n      <td>0.489591</td>\n      <td>7.080258e+08</td>\n      <td>26</td>\n      <td>0.011129</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2.0</td>\n      <td>0.379060</td>\n      <td>2.145775e+09</td>\n      <td>24</td>\n      <td>0.067740</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.0</td>\n      <td>0.636151</td>\n      <td>6.294023e+08</td>\n      <td>14</td>\n      <td>0.014457</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3.0</td>\n      <td>0.716943</td>\n      <td>1.899853e+09</td>\n      <td>7</td>\n      <td>0.069806</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calculate the correlation coefficient with GDP\n",
    "\n",
    "results =[]\n",
    "for exp in salary_avg_se.experience_level.unique():\n",
    "    corr, p_value = pearsonr(salary_avg_se[salary_avg_se.experience_level == exp]['GDP'], salary_avg_se[salary_avg_se.experience_level == exp]['salary_avg'])\n",
    "    variance = salary_avg_se[salary_avg_se.experience_level == exp]['salary_avg'].var()\n",
    "    n_samples = salary_avg_se[salary_avg_se.experience_level == exp]['salary_avg'].count()\n",
    "\n",
    "    results.append({'experience_level': exp, 'corr': corr, 'variance': variance, 'n_samples': n_samples, 'p_value': p_value})\n",
    "\n",
    "results = pd.DataFrame(results)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Build final dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year  experience_level  salary company_location  company_size    EUR  \\\n2       2023                 1  190000               US             1  False   \n3       2023                 1  160000               US             1  False   \n4       2023                 0   90000               US             1  False   \n5       2023                 0   65000               US             1  False   \n6       2023                 1  160000               US             1  False   \n\n     GBP   USD  Engineer  Scientist  ...  Data Science Consultant  \\\n2  False  True         0          0  ...                    False   \n3  False  True         0          0  ...                    False   \n4  False  True         0          0  ...                    False   \n5  False  True         0          0  ...                    False   \n6  False  True         1          0  ...                    False   \n\n   Data Science Manager  Data Scientist  ML Engineer  \\\n2                  True           False        False   \n3                  True           False        False   \n4                 False           False        False   \n5                 False           False        False   \n6                 False           False        False   \n\n   Machine Learning Engineer  Machine Learning Scientist  Research Analyst  \\\n2                      False                       False             False   \n3                      False                       False             False   \n4                      False                       False              True   \n5                      False                       False              True   \n6                      False                       False             False   \n\n   Research Engineer  Research Scientist  company_continent  \n2              False               False                 NA  \n3              False               False                 NA  \n4              False               False                 NA  \n5              False               False                 NA  \n6              False               False                 NA  \n\n[5 rows x 31 columns]",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>salary</th>\n      <th>company_location</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n      <th>Engineer</th>\n      <th>Scientist</th>\n      <th>...</th>\n      <th>Data Science Consultant</th>\n      <th>Data Science Manager</th>\n      <th>Data Scientist</th>\n      <th>ML Engineer</th>\n      <th>Machine Learning Engineer</th>\n      <th>Machine Learning Scientist</th>\n      <th>Research Analyst</th>\n      <th>Research Engineer</th>\n      <th>Research Scientist</th>\n      <th>company_continent</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>190000</td>\n      <td>US</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NA</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NA</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>90000</td>\n      <td>US</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NA</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>65000</td>\n      <td>US</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NA</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>US</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>1</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NA</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 31 columns</p>\n</div>"
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year  experience_level  salary  company_size    EUR    GBP   USD  \\\n0       2023                 1  190000             1  False  False  True   \n1       2023                 1  160000             1  False  False  True   \n2       2023                 0   90000             1  False  False  True   \n3       2023                 0   65000             1  False  False  True   \n4       2023                 1  160000             1  False  False  True   \n\n   Engineer  Scientist  Research  ...  Data Science Manager  Data Scientist  \\\n0         0          0         0  ...                  True           False   \n1         0          0         0  ...                  True           False   \n2         0          0         1  ...                 False           False   \n3         0          0         1  ...                 False           False   \n4         1          0         0  ...                 False           False   \n\n   ML Engineer  Machine Learning Engineer  Machine Learning Scientist  \\\n0        False                      False                       False   \n1        False                      False                       False   \n2        False                      False                       False   \n3        False                      False                       False   \n4        False                      False                       False   \n\n   Research Analyst  Research Engineer  Research Scientist           GDP  \\\n0             False              False               False  2.543970e+13   \n1             False              False               False  2.543970e+13   \n2              True              False               False  2.543970e+13   \n3              True              False               False  2.543970e+13   \n4             False              False               False  2.543970e+13   \n\n          CPI  \n0  134.211206  \n1  134.211206  \n2  134.211206  \n3  134.211206  \n4  134.211206  \n\n[5 rows x 31 columns]",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>salary</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n      <th>Engineer</th>\n      <th>Scientist</th>\n      <th>Research</th>\n      <th>...</th>\n      <th>Data Science Manager</th>\n      <th>Data Scientist</th>\n      <th>ML Engineer</th>\n      <th>Machine Learning Engineer</th>\n      <th>Machine Learning Scientist</th>\n      <th>Research Analyst</th>\n      <th>Research Engineer</th>\n      <th>Research Scientist</th>\n      <th>GDP</th>\n      <th>CPI</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>190000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>90000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>65000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 31 columns</p>\n</div>"
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_final = dataset.merge(country_GDP, on=['company_location','work_year'], how='left')\n",
    "dataset_final = dataset_final.merge(country_CPI, on=['company_location','work_year'], how='left')\n",
    "dataset_final = dataset_final.drop(columns=['company_location', 'company_continent'])\n",
    "dataset_final.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We want to separate the salary into 5 classes, so we will use the quantile function to split the salary into 5 bins. Use as lables te salary boundary of each bin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "salary\n0    3070\n1    3047\n2    3044\nName: count, dtype: int64"
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_bins = pd.qcut(dataset_final['salary'], q=3, labels=False)\n",
    "salary_bins.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "[(170000.0, 329700.0], (122000.0, 170000.0], (16454.999, 122000.0]]\nCategories (3, interval[float64, right]): [(16454.999, 122000.0] < (122000.0, 170000.0] < (170000.0, 329700.0]]"
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from_to = pd.qcut(dataset_final['salary'], q=3).unique()\n",
    "from_to"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   work_year  experience_level  salary  company_size    EUR    GBP   USD  \\\n0       2023                 1  190000             1  False  False  True   \n1       2023                 1  160000             1  False  False  True   \n2       2023                 0   90000             1  False  False  True   \n3       2023                 0   65000             1  False  False  True   \n4       2023                 1  160000             1  False  False  True   \n\n   Engineer  Scientist  Research  ...  Data Scientist  ML Engineer  \\\n0         0          0         0  ...           False        False   \n1         0          0         0  ...           False        False   \n2         0          0         1  ...           False        False   \n3         0          0         1  ...           False        False   \n4         1          0         0  ...           False        False   \n\n   Machine Learning Engineer  Machine Learning Scientist  Research Analyst  \\\n0                      False                       False             False   \n1                      False                       False             False   \n2                      False                       False              True   \n3                      False                       False              True   \n4                      False                       False             False   \n\n   Research Engineer  Research Scientist           GDP         CPI  \\\n0              False               False  2.543970e+13  134.211206   \n1              False               False  2.543970e+13  134.211206   \n2              False               False  2.543970e+13  134.211206   \n3              False               False  2.543970e+13  134.211206   \n4              False               False  2.543970e+13  134.211206   \n\n   salary_bins  \n0            2  \n1            1  \n2            0  \n3            0  \n4            1  \n\n[5 rows x 32 columns]",
      "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>work_year</th>\n      <th>experience_level</th>\n      <th>salary</th>\n      <th>company_size</th>\n      <th>EUR</th>\n      <th>GBP</th>\n      <th>USD</th>\n      <th>Engineer</th>\n      <th>Scientist</th>\n      <th>Research</th>\n      <th>...</th>\n      <th>Data Scientist</th>\n      <th>ML Engineer</th>\n      <th>Machine Learning Engineer</th>\n      <th>Machine Learning Scientist</th>\n      <th>Research Analyst</th>\n      <th>Research Engineer</th>\n      <th>Research Scientist</th>\n      <th>GDP</th>\n      <th>CPI</th>\n      <th>salary_bins</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>190000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>90000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2023</td>\n      <td>0</td>\n      <td>65000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2023</td>\n      <td>1</td>\n      <td>160000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>2.543970e+13</td>\n      <td>134.211206</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 32 columns</p>\n</div>"
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_final['salary_bins'] = salary_bins\n",
    "dataset_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected. Call `.close()` to terminate connection gracefully.\n",
      "\n",
      "Multiple projects found. \n",
      "\n",
      "\t (1) goodonions_id2223_lab1\n",
      "\t (2) dancip00\n",
      "Invalid input, should be an integer from the list of projects.\n",
      "\n",
      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/217237\n",
      "Connected. Call `.close()` to terminate connection gracefully.\n"
     ]
    }
   ],
   "source": [
    "import hopsworks\n",
    "project = hopsworks.login()\n",
    "fs = project.get_feature_store()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dataset_final.columns = dataset_final.columns.str.lower()\n",
    "dataset_final.columns = dataset_final.columns.str.replace(' ', '_')\n",
    "\n",
    "primary_key = dataset_final.columns[dataset_final.columns != 'salary_bins'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "Index(['work_year', 'experience_level', 'salary', 'company_size', 'eur', 'gbp',\n       'usd', 'engineer', 'scientist', 'research', 'analyst',\n       'analytics_engineer', 'applied_scientist', 'bi_developer',\n       'business_intelligence_analyst', 'business_intelligence_engineer',\n       'data_analyst', 'data_architect', 'data_engineer', 'data_manager',\n       'data_science_consultant', 'data_science_manager', 'data_scientist',\n       'ml_engineer', 'machine_learning_engineer',\n       'machine_learning_scientist', 'research_analyst', 'research_engineer',\n       'research_scientist', 'gdp', 'cpi', 'salary_bins'],\n      dtype='object')"
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "outputs": [],
   "source": [
    "dataset_final = dataset_final[dataset_final.cpi.isna() == False]"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "Uploading Dataframe: 0.00% |          | Rows 0/9154 | Elapsed Time: 00:00 | Remaining Time: ?",
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "3a8bdd7165904519b7bfa7b63c9c49dc"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Launching job: salary_2_offline_fg_materialization\n",
      "Job started successfully, you can follow the progress at \n",
      "https://c.app.hopsworks.ai/p/217237/jobs/named/salary_2_offline_fg_materialization/executions\n"
     ]
    },
    {
     "data": {
      "text/plain": "(<hsfs.core.job.Job at 0x28af582b0>, None)"
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary_fg = fs.get_or_create_feature_group(\n",
    "    name=\"salary\",\n",
    "    version=2,\n",
    "    primary_key=primary_key,\n",
    "    description=\"salary dataset\")\n",
    "salary_fg.insert(dataset_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "outputs": [
    {
     "data": {
      "text/plain": "['work_year',\n 'experience_level',\n 'salary',\n 'company_size',\n 'eur',\n 'gbp',\n 'usd',\n 'engineer',\n 'scientist',\n 'research',\n 'analyst',\n 'analytics_engineer',\n 'applied_scientist',\n 'bi_developer',\n 'business_intelligence_analyst',\n 'business_intelligence_engineer',\n 'data_analyst',\n 'data_architect',\n 'data_engineer',\n 'data_manager',\n 'data_science_consultant',\n 'data_science_manager',\n 'data_scientist',\n 'ml_engineer',\n 'machine_learning_engineer',\n 'machine_learning_scientist',\n 'research_analyst',\n 'research_engineer',\n 'research_scientist',\n 'gdp',\n 'cpi',\n 'salary_bins']"
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "columns = dataset_final.columns.tolist()\n",
    "columns"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}