{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='top'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TransferMarkt Player Bio and Status Data Engineering\n",
    "##### Notebook to engineer data scraped from [TransferMarkt](https://www.transfermarkt.co.uk/) using the [Tyrone Mings web scraper](https://github.com/FCrSTATS/tyrone_mings) by [FCrSTATS](https://twitter.com/FC_rstats).\n",
    "\n",
    "### By [Edd Webster](https://www.twitter.com/eddwebster)\n",
    "Notebook first written: 13/09/2020<br>\n",
    "Notebook last updated: 30/08/2021\n",
    "\n",
    "![title](../../img/transfermarkt-logo-banner.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "\n",
    "<a id='sectionintro'></a>\n",
    "\n",
    "## <a id='import_libraries'>Introduction</a>\n",
    "This notebook engineers previously scraped data from [TransferMarkt](https://www.transfermarkt.co.uk/) using the [FCrSTATS](https://twitter.com/FC_rstats) [Tyrone Mings webscraper](https://github.com/FCrSTATS/tyrone_mings)  and manipulates this landed data as DataFrames using [pandas](http://pandas.pydata.org/) and [matplotlib](https://matplotlib.org/) for visualisation.\n",
    "\n",
    "For more information about this notebook and the author, I'm available through all the following channels:\n",
    "*    [eddwebster.com](https://www.eddwebster.com/);\n",
    "*    edd.j.webster@gmail.com;\n",
    "*    [@eddwebster](https://www.twitter.com/eddwebster);\n",
    "*    [linkedin.com/in/eddwebster](https://www.linkedin.com/in/eddwebster/);\n",
    "*    [github/eddwebster](https://github.com/eddwebster/);\n",
    "*    [public.tableau.com/profile/edd.webster](https://public.tableau.com/profile/edd.webster);\n",
    "*    [kaggle.com/eddwebster](https://www.kaggle.com/eddwebster); and\n",
    "*    [hackerrank.com/eddwebster](https://www.hackerrank.com/eddwebster).\n",
    "\n",
    "![title](../../img/fifa21eddwebsterbanner.png)\n",
    "\n",
    "The accompanying GitHub repository for this notebook can be found [here](https://github.com/eddwebster/football_analytics) and a static version of this notebook can be found [here](https://nbviewer.jupyter.org/github/eddwebster/football_analytics/blob/master/notebooks/A%29%20Web%20Scraping/TransferMarkt%20Web%20Scraping%20and%20Parsing.ipynb)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "\n",
    "<a id='sectioncontents'></a>\n",
    "\n",
    "## <a id='notebook_contents'>Notebook Contents</a>\n",
    "1.    [Notebook Dependencies](#section1)<br>\n",
    "2.    [Project Brief](#section2)<br>\n",
    "3.    [Data Sources](#section3)<br>\n",
    "      1.    [Introduction](#section3.1)<br>\n",
    "      2.    [Data Dictionary](#section3.2)<br>\n",
    "      3.    [Creating the DataFrame](#section3.3)<br>\n",
    "      4.    [Initial Data Handling](#section3.4)<br>\n",
    "      5.    [Export the Raw DataFrame](#section3.5)<br>         \n",
    "4.    [Data Engineering](#section4)<br>\n",
    "      1.    [Introduction](#section4.1)<br>\n",
    "      2.    [Columns of Interest](#section4.2)<br>\n",
    "      3.    [String Cleaning](#section4.3)<br>\n",
    "      4.    [Converting Data Types](#section4.4)<br>\n",
    "      5.    [Export the Engineered DataFrame](#section4.5)<br>\n",
    "5.    [Exploratory Data Analysis (EDA)](#section5)<br>\n",
    "      1.    [...](#section5.1)<br>\n",
    "      2.    [...](#section5.2)<br>\n",
    "      3.    [...](#section5.3)<br>\n",
    "6.    [Summary](#section6)<br>\n",
    "7.    [Next Steps](#section7)<br>\n",
    "8.    [Bibliography](#section8)<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "\n",
    "<a id='section1'></a>\n",
    "\n",
    "## <a id='#section1'>1. Notebook Dependencies</a>\n",
    "This notebook was written using [Python 3](https://docs.python.org/3.7/) and requires the following libraries:\n",
    "*    [`Jupyter notebooks`](https://jupyter.org/) for this notebook environment with which this project is presented;\n",
    "*    [`NumPy`](http://www.numpy.org/) for multidimensional array computing;\n",
    "*    [`pandas`](http://pandas.pydata.org/) for data analysis and manipulation;\n",
    "*    [`Beautifulsoup`](https://pypi.org/project/beautifulsoup4/) for web scraping; and\n",
    "*    [`matplotlib`](https://matplotlib.org/contents.html?v=20200411155018) for data visualisations;\n",
    "\n",
    "All packages used for this notebook except for BeautifulSoup can be obtained by downloading and installing the [Conda](https://anaconda.org/anaconda/conda) distribution, available on all platforms (Windows, Linux and Mac OSX). Step-by-step guides on how to install Anaconda can be found for Windows [here](https://medium.com/@GalarnykMichael/install-python-on-windows-anaconda-c63c7c3d1444) and Mac [here](https://medium.com/@GalarnykMichael/install-python-on-mac-anaconda-ccd9f2014072), as well as in the Anaconda documentation itself [here](https://docs.anaconda.com/anaconda/install/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Libraries and Modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setup Complete\n"
     ]
    }
   ],
   "source": [
    "# Python ≥3.5 (ideally)\n",
    "import platform\n",
    "import sys, getopt\n",
    "assert sys.version_info >= (3, 5)\n",
    "import csv\n",
    "\n",
    "# Import Dependencies\n",
    "%matplotlib inline\n",
    "\n",
    "# Math Operations\n",
    "import numpy as np\n",
    "import math\n",
    "from math import pi\n",
    "\n",
    "# Datetime\n",
    "import datetime\n",
    "from datetime import date\n",
    "import time\n",
    "\n",
    "# Data Preprocessing\n",
    "import pandas as pd\n",
    "import os\n",
    "import re\n",
    "import random\n",
    "from io import BytesIO\n",
    "from pathlib import Path\n",
    "\n",
    "# Reading directories\n",
    "import glob\n",
    "import os\n",
    "from os.path import basename\n",
    "\n",
    "# Flatten lists\n",
    "from functools import reduce\n",
    "\n",
    "# Working with JSON\n",
    "import json\n",
    "from pandas.io.json import json_normalize\n",
    "\n",
    "# Web Scraping\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import re\n",
    "\n",
    "# Currency Converter\n",
    "from currency_converter import CurrencyConverter\n",
    "\n",
    "# APIs\n",
    "from tyrone_mings import * \n",
    "\n",
    "# Fuzzy Matching - Record Linkage\n",
    "import recordlinkage\n",
    "import jellyfish\n",
    "import numexpr as ne\n",
    "\n",
    "# Data Visualisation\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "import missingno as msno\n",
    "\n",
    "# Progress Bar\n",
    "from tqdm import tqdm\n",
    "\n",
    "# Display in Jupyter\n",
    "from IPython.display import Image, YouTubeVideo\n",
    "from IPython.core.display import HTML\n",
    "\n",
    "# Ignore Warnings\n",
    "import warnings\n",
    "warnings.filterwarnings(action=\"ignore\", message=\"^internal gelsd\")\n",
    "\n",
    "print('Setup Complete')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python: 3.7.6\n",
      "NumPy: 1.20.3\n",
      "pandas: 1.3.2\n",
      "matplotlib: 3.4.2\n",
      "Seaborn: 0.11.2\n"
     ]
    }
   ],
   "source": [
    "# Python / module versions used here for reference\n",
    "print('Python: {}'.format(platform.python_version()))\n",
    "print('NumPy: {}'.format(np.__version__))\n",
    "print('pandas: {}'.format(pd.__version__))\n",
    "print('matplotlib: {}'.format(mpl.__version__))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Defined Filepaths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up initial paths to subfolders\n",
    "base_dir = os.path.join('..', '..')\n",
    "data_dir = os.path.join(base_dir, 'data')\n",
    "data_dir_tm = os.path.join(base_dir, 'data', 'tm')\n",
    "img_dir = os.path.join(base_dir, 'img')\n",
    "fig_dir = os.path.join(base_dir, 'img', 'fig')\n",
    "video_dir = os.path.join(base_dir, 'video')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Defined Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define today's date\n",
    "today = datetime.datetime.now().strftime('%d/%m/%Y').replace('/', '')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Defined Lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defined Lists\n",
    "\n",
    "## Define list of league codes\n",
    "df_leagues = pd.read_csv(data_dir_tm + '/reference/tm_leagues_comps.csv')\n",
    "lst_league_codes = df_leagues['league_code'].to_numpy().tolist()\n",
    "\n",
    "## Define list of 'Big 5' European Leagues and MLS codes\n",
    "lst_big5_mls_league_codes = ['GB1', 'FR1', 'L1', 'IT1', 'ES1', 'MLS1']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Notebook Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "<a id='section2'></a>\n",
    "\n",
    "## <a id='#section2'>2. Project Brief</a>\n",
    "This Jupyter notebook is part of a series of notebooks to scrape, parse, engineer, unify, and the model, culminating in a an Expected Transfer (xTransfer) player performance vs. valuation model. This model aims to determine the under- and over-performing players based on their on-the-pitch output against transfer fee and wages.\n",
    "\n",
    "This particular notebook is one of several data eningeering notebooks, that cleans player bio and status (valuation) data from [TransferMarkt](https://www.transfermarkt.co.uk/) using [pandas](http://pandas.pydata.org/).\n",
    "\n",
    "[TransferMarkt](https://www.transfermarkt.co.uk/) is a German-based website owned by [Axel Springer](https://www.axelspringer.com/en/) and is the leading website for the football transfer market. The website posts football related data, including: scores and results, football news, transfer rumours, and most usefully for us - calculated estimates ofthe market values for teams and individual players.\n",
    "\n",
    "To read more about how these estimations are made, [Beyond crowd judgments: Data-driven estimation of market value in association football](https://www.sciencedirect.com/science/article/pii/S0377221717304332) by Oliver Müllera, Alexander Simons, and Markus Weinmann does an excellent job of explaining how the estimations are made and their level of accuracy.\n",
    "\n",
    "This notebook, along with the other notebooks in this project workflow are shown in the following diagram:\n",
    "\n",
    "![roadmap](../../img/football_analytics_data_roadmap.png)\n",
    "\n",
    "Links to these notebooks in the [`football_analytics`](https://github.com/eddwebster/football_analytics) GitHub repository can be found at the following:\n",
    "*    [Webscraping](https://github.com/eddwebster/football_analytics/tree/master/notebooks/1_data_scraping)\n",
    "     +    [FBref Player Stats Webscraping](https://github.com/eddwebster/football_analytics/blob/master/notebooks/1_data_scraping/FBref%20Player%20Stats%20Web%20Scraping.ipynb)\n",
    "     +    [TransferMarket Player Bio and Status Webscraping](https://github.com/eddwebster/football_analytics/blob/master/notebooks/1_data_scraping/TransferMarkt%20Player%20Bio%20and%20Status%20Web%20Scraping.ipynb)\n",
    "     +    [TransferMarket Player Valuation Webscraping](https://github.com/eddwebster/football_analytics/blob/master/notebooks/1_data_scraping/TransferMarkt%20Player%20Valuation%20Web%20Scraping.ipynb)\n",
    "     +    [TransferMarkt Player Recorded Transfer Fees Webscraping](https://github.com/eddwebster/football_analytics/blob/master/notebooks/1_data_scraping/TransferMarkt%20Player%20Recorded%20Transfer%20Fees%20Webscraping.ipynb)\n",
    "     +    [Capology Player Salary Webscraping](https://github.com/eddwebster/football_analytics/blob/master/notebooks/1_data_scraping/Capology%20Player%20Salary%20Web%20Scraping.ipynb)\n",
    "     +    [FBref Team Stats Webscraping](https://github.com/eddwebster/football_analytics/blob/master/notebooks/1_data_scraping/FBref%20Team%20Stats%20Web%20Scraping.ipynb)\n",
    "*    [Data Parsing](https://github.com/eddwebster/football_analytics/tree/master/notebooks/2_data_parsing)\n",
    "     +    [ELO Team Ratings Data Parsing](https://github.com/eddwebster/football_analytics/blob/master/notebooks/2_data_parsing/ELO%20Team%20Ratings%20Data%20Parsing.ipynb)\n",
    "*    [Data Engineering](https://github.com/eddwebster/football_analytics/tree/master/notebooks/3_data_engineering)\n",
    "     +    [FBref Player Stats Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/FBref%20Player%20Stats%20Data%20Engineering.ipynb)\n",
    "     +    [TransferMarket Player Bio and Status Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/TransferMarkt%20Player%20Bio%20and%20Status%20Data%20Engineering.ipynb)\n",
    "     +    [TransferMarket Player Valuation Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/TransferMarkt%20Player%20Valuation%20Data%20Engineering.ipynb)\n",
    "     +    [TransferMarkt Player Recorded Transfer Fees Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/TransferMarkt%20Player%20Recorded%20Transfer%20Fees%20Data%20Engineering.ipynb)\n",
    "     +    [Capology Player Salary Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/Capology%20Player%20Salary%20Data%20Engineering.ipynb)\n",
    "     +    [FBref Team Stats Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/FBref%20Team%20Stats%20Data%20Engineering.ipynb)\n",
    "     +    [ELO Team Ratings Data Parsing](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/ELO%20Team%20Ratings%20Data%20Parsing.ipynb)\n",
    "     +    [TransferMarkt Team Recorded Transfer Fee Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/TransferMarkt%20Team%20Recorded%20Transfer%20Fee%20Data%20Engineering.ipynb) (aggregated from [TransferMarkt Player Recorded Transfer Fees notebook](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/TransferMarkt%20Player%20Recorded%20Transfer%20Fees%20Data%20Engineering.ipynb))\n",
    "     +    [Capology Team Salary Data Engineering](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/Capology%20Team%20Salary%20Data%20Engineering.ipynb) (aggregated from [Capology Player Salary notebook](https://github.com/eddwebster/football_analytics/blob/master/notebooks/3_data_engineering/Capology%20Player%20Salary%20Data%20Engineering.ipynb))\n",
    "*    [Data Unification](https://github.com/eddwebster/football_analytics/tree/master/notebooks/4_data_unification)\n",
    "     +    [Golden ID for Player Level Datasets](https://github.com/eddwebster/football_analytics/blob/master/notebooks/4_data_unification/Golden%20ID%20for%20Player%20Level%20Datasets.ipynb)\n",
    "     +    [Golden ID for Team Level Datasets](https://github.com/eddwebster/football_analytics/blob/master/notebooks/4_data_unification/Golden%20ID%20for%20Team%20Level%20Datasets.ipynb)\n",
    "*    [Production Datasets](https://github.com/eddwebster/football_analytics/tree/master/notebooks/5_production_datasets)\n",
    "     +    [Player Performance/Market Value Dataset](https://github.com/eddwebster/football_analytics/tree/master/notebooks/5_production_datasets/Player%20Performance/Market%20Value%20Dataset.ipynb)\n",
    "     +    [Team Performance/Market Value Dataset](https://github.com/eddwebster/football_analytics/tree/master/notebooks/5_production_datasets/Team%20Performance/Market%20Value%20Dataset.ipynb)\n",
    "*    [Expected Transfer (xTransfer) Modeling](https://github.com/eddwebster/football_analytics/tree/master/notebooks/6_data_analysis_and_projects/expected_transfer_modeling)\n",
    "     +    [Expected Transfer (xTransfer) Modeling](https://github.com/eddwebster/football_analytics/tree/master/notebooks/6_data_analysis_and_projects/expected_transfer_modeling/Expected%20Transfer%20%20Modeling.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "<a id='section3'></a>\n",
    "\n",
    "## <a id='#section3'>3. Data Sources</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='section3.3.1'></a>\n",
    "\n",
    "### <a id='#section3.1'>3.1. Introduction</a>\n",
    "Before conducting our EDA, the data needs to be imported as a DataFrame in the Data Sources section [Section 3](#section3) and cleaned in the Data Engineering section [Section 4](#section4).\n",
    "\n",
    "We'll be using the [pandas](http://pandas.pydata.org/) library to import our data to this workbook as a DataFrame."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a id='#section3.2'>3.2. Bio and Status Dataset</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section3.2.1'>3.2.1. Data Dictionaries</a>\n",
    "The [TransferMarkt](https://www.transfermarkt.co.uk/) dataset has six features (columns) with the following definitions and data types:\n",
    "\n",
    "| Feature     | Data type    |\n",
    "|------|-----|\n",
    "| `position_number`    | object     |\n",
    "| `position_description`    | object     |\n",
    "| `name`    | object     |\n",
    "| `dob`    | object     |\n",
    "| `nationality`    | object     |\n",
    "| `value`    | object     |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section3.2.2'>3.2.2. Import CSV files as pandas DataFrames</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Import Bio data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import DataFrame as a CSV file\n",
    "df_tm_bio_raw = pd.read_csv(data_dir_tm + f'/raw/bio/tm_player_bio_combined_latest.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Import Status data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import DataFrame as a CSV file\n",
    "df_tm_status_raw = pd.read_csv(data_dir_tm + f'/raw/status/tm_player_status_combined_latest.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section3.2.3'>3.2.3. Preliminary Data Handling</a>\n",
    "Let's quality of the dataset by looking first and last rows in pandas using the [head()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.head.html) and [tail()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tail.html) methods."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Bio data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>player_id</th>\n",
       "      <th>player_name</th>\n",
       "      <th>day_of_birth</th>\n",
       "      <th>month_of_birth</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>pob</th>\n",
       "      <th>cob</th>\n",
       "      <th>dob</th>\n",
       "      <th>position</th>\n",
       "      <th>height</th>\n",
       "      <th>foot</th>\n",
       "      <th>citizenship</th>\n",
       "      <th>second_citizenship</th>\n",
       "      <th>league_code</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2963</td>\n",
       "      <td>martín demichelis</td>\n",
       "      <td>20.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>Justiniano Posse</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>1980-12-20</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>184.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Italy</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5404</td>\n",
       "      <td>jérémy mathieu</td>\n",
       "      <td>29.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Luxeuil-les-Bains</td>\n",
       "      <td>France</td>\n",
       "      <td>1983-10-29</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>189.0</td>\n",
       "      <td>left</td>\n",
       "      <td>France</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5856</td>\n",
       "      <td>daniele bonera</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>Brescia</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1981-05-31</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>183.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7593</td>\n",
       "      <td>fernando navarro</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1982-06-25</td>\n",
       "      <td>Defender - Left-Back</td>\n",
       "      <td>176.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7600</td>\n",
       "      <td>andrés iniesta</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Fuentealbilla</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1984-05-11</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>171.0</td>\n",
       "      <td>both</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   player_id        player_name  day_of_birth  month_of_birth  year_of_birth  \\\n",
       "0       2963  martín demichelis          20.0            12.0         1980.0   \n",
       "1       5404     jérémy mathieu          29.0            10.0         1983.0   \n",
       "2       5856     daniele bonera          31.0             5.0         1981.0   \n",
       "3       7593   fernando navarro          25.0             6.0         1982.0   \n",
       "4       7600     andrés iniesta          11.0             5.0         1984.0   \n",
       "\n",
       "                 pob        cob         dob                     position  \\\n",
       "0   Justiniano Posse  Argentina  1980-12-20       Defender - Centre-Back   \n",
       "1  Luxeuil-les-Bains     France  1983-10-29       Defender - Centre-Back   \n",
       "2            Brescia      Italy  1981-05-31       Defender - Centre-Back   \n",
       "3          Barcelona      Spain  1982-06-25         Defender - Left-Back   \n",
       "4      Fuentealbilla      Spain  1984-05-11  midfield - Central Midfield   \n",
       "\n",
       "   height   foot citizenship second_citizenship league_code  season  \n",
       "0   184.0  right         NaN              Italy         ES1    2016  \n",
       "1   189.0   left      France                NaN         ES1    2016  \n",
       "2   183.0  right       Italy                NaN         ES1    2016  \n",
       "3   176.0   left       Spain                NaN         ES1    2016  \n",
       "4   171.0   both       Spain                NaN         ES1    2016  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the first five rows of the raw DataFrame, df_tm_bio_raw\n",
    "df_tm_bio_raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>player_id</th>\n",
       "      <th>player_name</th>\n",
       "      <th>day_of_birth</th>\n",
       "      <th>month_of_birth</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>pob</th>\n",
       "      <th>cob</th>\n",
       "      <th>dob</th>\n",
       "      <th>position</th>\n",
       "      <th>height</th>\n",
       "      <th>foot</th>\n",
       "      <th>citizenship</th>\n",
       "      <th>second_citizenship</th>\n",
       "      <th>league_code</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24206</th>\n",
       "      <td>898751</td>\n",
       "      <td>mamadou fall</td>\n",
       "      <td>21.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Rufisque</td>\n",
       "      <td>Senegal</td>\n",
       "      <td>2002-11-21</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>189.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Senegal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24207</th>\n",
       "      <td>900440</td>\n",
       "      <td>bryce washington</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Atlanta, Georgia</td>\n",
       "      <td>United States</td>\n",
       "      <td>1998-09-12</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>188.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24208</th>\n",
       "      <td>900569</td>\n",
       "      <td>george asomani</td>\n",
       "      <td>26.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1999.0</td>\n",
       "      <td>Accra</td>\n",
       "      <td>Ghana</td>\n",
       "      <td>1999-03-26</td>\n",
       "      <td>midfield - Defensive Midfield</td>\n",
       "      <td>168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ghana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24209</th>\n",
       "      <td>905609</td>\n",
       "      <td>arquimides ordonez</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>Cincinnati, Ohio</td>\n",
       "      <td>United States</td>\n",
       "      <td>2003-08-05</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>188.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24210</th>\n",
       "      <td>921655</td>\n",
       "      <td>ismaël koné</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Abidjan</td>\n",
       "      <td>Cote d'Ivoire</td>\n",
       "      <td>2002-06-06</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>188.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cote d'Ivoire</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       player_id         player_name  day_of_birth  month_of_birth  \\\n",
       "24206     898751        mamadou fall          21.0            11.0   \n",
       "24207     900440    bryce washington          12.0             9.0   \n",
       "24208     900569      george asomani          26.0             3.0   \n",
       "24209     905609  arquimides ordonez           5.0             8.0   \n",
       "24210     921655         ismaël koné           6.0             6.0   \n",
       "\n",
       "       year_of_birth               pob            cob         dob  \\\n",
       "24206         2002.0          Rufisque        Senegal  2002-11-21   \n",
       "24207         1998.0  Atlanta, Georgia  United States  1998-09-12   \n",
       "24208         1999.0             Accra          Ghana  1999-03-26   \n",
       "24209         2003.0  Cincinnati, Ohio  United States  2003-08-05   \n",
       "24210         2002.0           Abidjan  Cote d'Ivoire  2002-06-06   \n",
       "\n",
       "                            position  height foot    citizenship  \\\n",
       "24206         Defender - Centre-Back   189.0  NaN        Senegal   \n",
       "24207         Defender - Centre-Back   188.0  NaN  United States   \n",
       "24208  midfield - Defensive Midfield   168.0  NaN          Ghana   \n",
       "24209        attack - Centre-Forward   188.0  NaN            NaN   \n",
       "24210    midfield - Central Midfield   188.0  NaN            NaN   \n",
       "\n",
       "      second_citizenship league_code  season  \n",
       "24206                NaN        MLS1    2020  \n",
       "24207                NaN        MLS1    2020  \n",
       "24208                NaN        MLS1    2020  \n",
       "24209          Guatemala        MLS1    2020  \n",
       "24210      Cote d'Ivoire        MLS1    2020  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the last five rows of the raw DataFrame, df_tm_bio_raw\n",
    "df_tm_bio_raw.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(24211, 15)\n"
     ]
    }
   ],
   "source": [
    "# Print the shape of the raw DataFrame, df_tm_bio_raw\n",
    "print(df_tm_bio_raw.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['player_id', 'player_name', 'day_of_birth', 'month_of_birth',\n",
      "       'year_of_birth', 'pob', 'cob', 'dob', 'position', 'height', 'foot',\n",
      "       'citizenship', 'second_citizenship', 'league_code', 'season'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Print the column names of the raw DataFrame, df_tm_bio_raw\n",
    "print(df_tm_bio_raw.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset has thirteen features (columns). Full details of these attributes can be found in the [Data Dictionary](section3.3.1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "player_id               int64\n",
       "player_name            object\n",
       "day_of_birth          float64\n",
       "month_of_birth        float64\n",
       "year_of_birth         float64\n",
       "pob                    object\n",
       "cob                    object\n",
       "dob                    object\n",
       "position               object\n",
       "height                float64\n",
       "foot                   object\n",
       "citizenship            object\n",
       "second_citizenship     object\n",
       "league_code            object\n",
       "season                  int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data types of the features of the raw DataFrame, df_tm_bio_raw\n",
    "df_tm_bio_raw.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All thirteen of the columns have the object data type. Full details of these attributes and their data types can be found in the [Data Dictionary](section3.3.1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 24211 entries, 0 to 24210\n",
      "Data columns (total 15 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   player_id           24211 non-null  int64  \n",
      " 1   player_name         24211 non-null  object \n",
      " 2   day_of_birth        24171 non-null  float64\n",
      " 3   month_of_birth      24171 non-null  float64\n",
      " 4   year_of_birth       24171 non-null  float64\n",
      " 5   pob                 23930 non-null  object \n",
      " 6   cob                 24172 non-null  object \n",
      " 7   dob                 24171 non-null  object \n",
      " 8   position            24172 non-null  object \n",
      " 9   height              23802 non-null  float64\n",
      " 10  foot                22565 non-null  object \n",
      " 11  citizenship         15651 non-null  object \n",
      " 12  second_citizenship  8521 non-null   object \n",
      " 13  league_code         24211 non-null  object \n",
      " 14  season              24211 non-null  int64  \n",
      "dtypes: float64(4), int64(2), object(9)\n",
      "memory usage: 2.8+ MB\n"
     ]
    }
   ],
   "source": [
    "# Info for the raw DataFrame, df_tm_bio_raw\n",
    "df_tm_bio_raw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>player_id</th>\n",
       "      <th>day_of_birth</th>\n",
       "      <th>month_of_birth</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>height</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24211.000000</td>\n",
       "      <td>24171.000000</td>\n",
       "      <td>24171.000000</td>\n",
       "      <td>24171.000000</td>\n",
       "      <td>23802.000000</td>\n",
       "      <td>24211.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>249165.466606</td>\n",
       "      <td>15.400811</td>\n",
       "      <td>5.840429</td>\n",
       "      <td>1993.637086</td>\n",
       "      <td>182.295395</td>\n",
       "      <td>2018.368551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>179097.376690</td>\n",
       "      <td>8.762392</td>\n",
       "      <td>3.438228</td>\n",
       "      <td>4.951668</td>\n",
       "      <td>6.759016</td>\n",
       "      <td>1.637394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>26.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1975.000000</td>\n",
       "      <td>158.000000</td>\n",
       "      <td>2016.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>93604.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1990.000000</td>\n",
       "      <td>178.000000</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>221150.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1994.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>2018.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>361104.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1997.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>2020.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>921655.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2006.000000</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>2021.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           player_id  day_of_birth  month_of_birth  year_of_birth  \\\n",
       "count   24211.000000  24171.000000    24171.000000   24171.000000   \n",
       "mean   249165.466606     15.400811        5.840429    1993.637086   \n",
       "std    179097.376690      8.762392        3.438228       4.951668   \n",
       "min        26.000000      1.000000        1.000000    1975.000000   \n",
       "25%     93604.000000      8.000000        3.000000    1990.000000   \n",
       "50%    221150.000000     15.000000        5.000000    1994.000000   \n",
       "75%    361104.000000     23.000000        9.000000    1997.000000   \n",
       "max    921655.000000     31.000000       12.000000    2006.000000   \n",
       "\n",
       "             height        season  \n",
       "count  23802.000000  24211.000000  \n",
       "mean     182.295395   2018.368551  \n",
       "std        6.759016      1.637394  \n",
       "min      158.000000   2016.000000  \n",
       "25%      178.000000   2017.000000  \n",
       "50%      183.000000   2018.000000  \n",
       "75%      187.000000   2020.000000  \n",
       "max      202.000000   2021.000000  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Description of the raw DataFrame, df_tm_bio_raw, showing some summary statistics for each numberical column in the DataFrame\n",
    "df_tm_bio_raw.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1sGUTMplM3Lp1C4BMmTIB4ODgwK5duwgKCsLf359u3bpx79499u/fz7Vr1wDw9fXFzs4Os9mcbueQ0VitVm2Cedu2bRk/fjzDhg0jMDCQdu3acenSJRlfEUL8bRKEE0KkGVsD5PPPP0cpRXh4OD179mTw4MH4+PgAL1fK2VK/SYPl9bFYLJjNZvR6PcnJyTx48IAnT57ISsR05u3tTbt27TCZTLRr1449e/ZQuHBhpk2bRqlSpdiyZQvbt29PdYynpydLly5l9erVrF+/Hjs7O1kB94ps9yCAwYMHM2TIEBYvXsySJUuwt7fXZpuWLVuW8ePHk5iYKIE4IYQQQgghRJozm83Y2dkRFxdH586d2b17NwCffPIJN27coGfPnowYMYLAwED69+8PQGJiIu7u7mTLli3VZ9nZ2b3x8mc0tonMtrGUwYMH4+rqytSpU/nyyy+ZP38+58+fZ/To0TK2JYT42yQIJ4RIM7YAz6NHjzAajbi7uwMv0yZMnz6dUaNGkTNnTsaPH09MTIwEhF6D8+fPc+PGDQwGgzZrq2fPnrRv356GDRuyfft2bX8+kX7u379PpkyZGDVqFAcOHMDT05PZs2fj5OTE8uXLUwXibLMiy5Yti16vx2KxyAq4V2A2m5k4cSLh4eEAJCcn06pVK8aNG8fVq1e5f/8+d+/e1d7/3nvvMWHCBJKSkli1ahU7duxIr6ILIYQQQgghMhBbAM5oNNKmTRtOnTrFkSNHMJlMlCpViqCgIH755Rfee+89unXrhslk4sqVK+zYsYPixYvj4eGR3qeQYVy9epWYmBitzw1w79497t69S9u2bSlfvjz58uXjxo0bmM1m2rZty8WLF0lISJCxLSHEX5IgnBDilaRMd2j7ty0lpbu7O19++SVBQUEEBgbSrVs3Hj58yLfffsujR4/Sq8gZ1osXLxg/fjwtWrTQUlh06tQJq9VKkyZN+OCDDxgzZgzR0dEkJiamc2nfLb9duebp6UloaChVq1ZlyJAhHDhwAC8vL+bMmYPBYGDFihVasOe3sxklAPdq7OzsqFy5MtHR0YwfP5527drx9ddf0759e0aOHMm5c+dYu3ZtqtVytkDcrVu3OH78eDqWXgghhBBCCPFvZzabUwXgmjVrhpeXF506deLJkydaH7BZs2b079+fY8eO0a1bNzp06EBgYCBms5kZM2ag0+l+twWF+N89efKETz/9lP79+xMTE6P1uZOSknj06JH2865duxg+fDj+/v7UqVOHBQsWaFtKCCHE/0WCcEKIfyxlusPHjx9rg9atW7dGp9PRuHFj/P39GTlyJH379gVeBupy5MiBs7NzehY9Q3J1daVnz554e3vTuXNnDh06RKFChZg4cSJBQUFMnz6dXr16MW3aNNatWyeBuNfM1hmyrVxLSkrixIkTHDx4kEePHlGoUCEmTJhAjRo1tEBcgQIFmDNnDnZ2dkyZMoX//Oc/6XwWGVPz5s0ZNGgQGzdu5P79+zRq1Ai9Xk/37t0JCgpi+fLlrFq1KlUgrkKFCqxcuZLx48enY8mFEEIIIYQQ/1YXLlwAXk4MtAXgGjdujKenJxEREbz//vvEx8fz9OlTAHLlykXfvn3ZvHkzFSpU4L333qNNmzZs2rQJe3t7bUxGvBp3d3eaNWuG1Wpl6NCh3LlzBwAXFxcyZ87M6dOn2blzJ0OHDiUwMJC+ffui1+u5ffu2ZBoSQvwtkixYCPGPKKW0RqOfnx83b94kd+7ctGvXDl9fX4KCgli0aBGenp506NCBuLg47t27x6pVqyhUqBCFChVK71PIMO7evcuNGzeoWrUqH3/8Mfb29kRGRuLv74+bm5uWJ97BwYHBgwcDMG3aNAA6duxI5syZ063sGdWZM2fYsmULgYGBZMmShbi4ODp27MiTJ094+PAhefPm5cMPP2TMmDFMnDiR0aNHM2TIEObOnUudOnWYNm0aS5cupXr16ul9KhmKbbZp5syZiYuLI3fu3Ny/f5+5c+cyZswYAG3CwMyZM9HpdHTr1k1LrVu0aFEASQkqhBBCCCGE+J88fPiQ3r1706dPH7p27YpSiunTp5MvXz6mTp2Km5sbOXPmJCYmhkePHpE9e3bg5dhL2bJlKVu2bKrPs1gssgdcGrBarej1enr06IGDgwM7duxgxIgRTJs2jTx58uDn50dERARms5kRI0bQo0cP4OU2LI6OjuTLlw94WU+SllII8Wfkbi2E+Ed0Oh0WiwV/f38sFgsNGzbk4sWLzJgxA4vFQtu2bbFarcyePZuGDRvi6OgIgKOjI5GRkVraBJm19WqUUvz0009s2LCBLFmyULp0aUqXLo2/vz/Lli3j1KlTxMTEkDVrViwWC/b29gwePBidTsfMmTOJj4+nb9++ODg4pPepZCgXL15k/fr1WCwWhg4dyrhx48iSJQsjR44kd+7crF27lkOHDtGrVy+WL19OaGgoEyZMICgoiMmTJ9OoUSMiIiIACfiklZQTB7p27Ur79u3ZsGEDn3/+ObNmzUIpRXBwMPDfQNycOXOIjY3Vgqk2Uh9CCCGEEEKI/4WTkxOzZs3Cx8cHk8mEg4MDQ4YMAdAm/bm4uGAwGIiLi9OOi4mJYfHixXzyySdUqVJFC/ZInyRtKKWA/2ay0ev1HDt2jJEjRzJlyhQ6derE/fv3WblyJQ8ePODIkSM8f/6clStX4uTkRKtWrQAkACeE+D9JEE4I8T+xrSSBl/mxHR0dGTJkCOXLl+fKlSssWrSI6dOnA9C+fXvq1KnDxo0bsbOzw8PDA19fXwwGQ6rPEf+cTqfDw8ODZ8+eERoayqlTp+jZsydDhw7FbDYze/ZsevXqxdq1aylYsKAWiBs0aBAvXrzgyJEjDBw4ML1PI8Np3LgxSinGjRuHxWIhMTGRVq1aUbVqVQCCgoIoWrQoCxcuZOLEiYSEhDB06FDGjx/PunXraNSokXSu0pDtfmOxWIiOjsZgMFCiRAly585NmzZtUEoxe/ZsgFSBOKvVyqFDh3B1dU3H0gshhBBCCCH+rWJiYjCZTBQoUAAfHx/MZjO9e/cmNjaW7du3A/+deOnl5YWDgwPXr1+nYsWK3L59m4CAABITExk3bhwgwZ60ZjAYiI+Pp2nTpuTNm5eCBQvi5ubGL7/8wqeffsrMmTMJCAjAw8ODRYsW8dlnn+Hu7o6XlxeRkZEYDAaZOCuE+EsyAi6E+Nts6Q7i4uJYtGgRFouFX375BRcXFwC8vb3p06cPADNmzCApKYnOnTtrKRB/+zni1VmtVqpXr46fnx+jR4/G1dWVYsWKodPpqFu3Ljqdjnnz5tGtWzdWr16dKhA3evRoDAYDOp1OUiekMQcHB5o0aYLFYiEiIoK4uDg+/vhj4GVAyMnJiaZNm3LmzBm+++47Xrx4gbe3NxEREeTNmxeQztWrOnHiBMuXL9c6RsnJyXTo0AGj0UitWrUoV64cAG5ubrRt2xZ4ufLNarXStm1bDh06RIsWLejXr59cI0IIIYQQQoj/mdlsZt++ffzwww9MmzYNFxcXjEYjderUYcWKFVo/3TZROVOmTDg4OPDgwQOePn3K0KFDSUxMZNu2bRLseQ1sfbx169bh6OjIpEmT8PT0BGD79u1s2LCBoKAgZsyYQbdu3ahXrx5xcXFkypQJLy8vdDqdTDAXQvwtkgdOCPG3KKW0GUK+vr5s27aNnTt38ujRI/bt26e9r1ixYvTp04eaNWuyaNEiFi9e/LvPkkZj2rCl80xMTOTAgQNUqVKF7Nmzs2HDBr777jsA6tSpw+DBg3F3d6d79+5cv34dg8GA1WrFzs5OgguvkYODA82aNWPcuHE4Ozvzn//8B3i5CbctENehQwdu376tbdCdP39+9Hq9lgpD/DNWq5VTp07h5eUFvAxo2tvbU6VKFa5fv853333HlStXtPfbAnFBQUFs2bKFVq1acejQIXLmzCnXiBBCCCGEEOIfse1Hff78eYYNG0b58uX58ssvad26NX5+fly+fJmuXbtq77VYLOTLl4+bN28yaNAgnj9/zrZt27C3t8dsNstYShqz9fGePXtGcnIy2bJl037XokULOnTowPXr1xk5ciQxMTHky5ePYsWKUaBAAW2LFQnACSH+DgnCCSH+km0A2mKxcPr0aby8vNi6dSsLFy6kc+fOzJ07l1WrVmnvtwXiypQpw88//6zl2BZpQymFxWJBr9eTlJREy5YtSUhIIDIyksDAQOLi4oiMjOTbb78F/huIy549O40bNyYmJibVXnwSXHh9MmXKRKNGjRg1ahRfffWVlqrV1lC/c+cOefLkwcPDI9Vxslfiq9Hr9bRv357hw4eTkJBAeHg4AMOGDSMoKIjLly+zatUqYmJitGPc3Nxo164da9asYfTo0URHR2sBUblGhBBCCCHE2+7PJvJJf/zNO3bsGJGRkcDLbTp8fX359ttvcXJyolChQri4uNCsWTMGDRrElStXtECcg4MDuXPn5rPPPsNoNLJz504tACfBnrSR8nowm80A2NvbExcXx5MnT4CX2ZsAmjdvTsWKFTl69Ci9evXiwYMHqT5L+u1CiL9L7uBCiL+k0+kwmUz06tWLFy9eULRoUXLlykWuXLm0mUIREREAdO/eHYCiRYsyZswY8uXLJytJ0sizZ89wc3PT9glLTEzk4MGDFCxYkFGjRuHo6EiDBg1QSjF//nwtDV/VqlWpXbs2SUlJfPPNN+TMmTO9T+Wd4uDgQPPmzVFKERISwoMHD6hduzb29vYsXbqUPHnyaCu2RNrJlCkTAF999RXR0dHcuXOHhQsX0rdvX0wmE5GRkTg7O9OtWzfy5MkDvNwIvUKFClSoUAFAOrtCCCGEEOJfwdZuTU5O5vHjxxiNRooUKQKgrdiRgMGbYTKZ+PLLL1MFRR89ekSePHkwm81ERUWRM2dOChQoQLNmzQCIjIyka9eurFmzhmrVqhEfH8/SpUu1LCrSJ0kbtnSetvGppKQk7Ozs6NKlC5s3b2bKlCnaOIpNtmzZqFixIhUqVCB79uzpWHohxL+ZTsmUGCHE33D//n2WLFnCzp07qVy5MpGRkVpQ7c6dO6xcuZLo6GhGjRpFt27dUh0rDf5Xd+rUKSZNmkRISAjFixfHarUSHBzMZ599RtGiRYmKisLNzU17/5dffsmCBQvIlCkTDRs25M6dO7Rq1YqSJUsCSC75NGAymXBwcPjb709OTmbHjh1MnjyZuLg4bQXjtGnTsLe3l+skjfw24P/s2TN27NhBZGQkFStW1FLkzp07lwULFtC9e/dUgTghhBBCCCH+TWztX6PRSP/+/bl9+zb37t2jUqVKfPzxx3Tu3DnV+8TrZ5tAGx8fz6FDh/jkk08wmUwsW7aMbdu2UaJECT799FMKFiyI0Wjk888/Z/78+eTNm5dNmzZpdSUBuLRjGwOJi4tjxowZXLlyhbi4OGrVqkWLFi04efIkISEhVKpUicDAQDw8PHj8+DHBwcHUqVOHPn36aBmiZCxFCPG/ktE+IcQfsi2/t8mVKxe9e/emdevWfP311yxbtkz7Xb58+ejRowddunRh8uTJfPHFF6mOlcDCq9PpdNSoUUMLwOn1epo2bUq1atW4e/culy5dAv6bTqFBgwYMHDiQ5ORkIiMjOXDgAMWKFdM+TxqNr+bHH3+kf//+vHjx4m8fY29vT7NmzRg/fjwAZcqUYfbs2Vp6EblOXo1SCrPZrHVWY2NjefLkCW5ubnTo0IHBgwdz7Ngx+vXrB8CQIUMYOHAgq1atYt68eTx+/Didz0AIIYQQQoi/L2X712q10r9/f3Q6HUOGDCEyMhKz2cyKFSu0rDW2DDXi9bNNkF27di1BQUFERkbi4ODAgAEDaNGiBefPn2fGjBncunULFxcXmjZtSs+ePcmWLZuWDl8pJQG4NGQwGIiPj6dt27b8+uuvuLu74+3tzfz58wkODsbJyYmQkBB+/fVXunTpQtOmTRk4cCBxcXH07NlTqxMZSxFC/BOyEk4I8Tu22VYJCQls376dFy9eULduXQoVKsTz589ZsGABUVFRjBgxgh49emjH3bx5kwMHDtC5c2dpLKahlCukEhMTGTt2LPXr16dBgwacOHGCkJAQnjx5wtq1a/H09Ew1W+7GjRvExsZSqlQpDAaDzNpKA7du3aJDhw68//77zJkzR3v9784sTUxM5Pvvv+fDDz+U6yQNnDt3DqUUpUqVAsBoNBIQEMCdO3eIiYmhcePGtGzZEh8fH6Kiopg9ezY+Pj7airjJkyfzyy+/sH79egmECiGEEEKIt15MTAxZsmTB2dkZgPj4eI4ePcqePXvw9fWlatWq2vsWLlzIkSNH6Nu3L23btk3PYr8Tftvfvn//PkuXLmXDhg307t2bgIAAAObPn8/OnTspUqQILVq04M6dO9SqVYuCBQtK+tDXaO7cuRw+fJgZM2ZQsGBBAH799Vd69+5N6dKlmTx5Mk5OTmzbtg2TyUS2bNlo0aKFjKUIIV6ZBOFEujlz5gw7duxg9OjR6V0UkYKtYWE0Gmnfvj0PHz7k+fPnZMuWjU8//ZTmzZsTFxfH/PnziYqKYuTIkdo+cClJ2oTX49KlS7Rr145ixYrh5+dHrVq1+OWXXxg7dixxcXGsWrUKLy+vP/z+pdGYNo4fP07v3r2ZPn06devWZcuWLbRu3foffZZSCqWUdLD+oYSEBAYOHMiRI0fYtm0bJUuWpEWLFjg5OVG7dm0tBaiDgwP9+/enSZMmrFmzRktNuWjRIuC/AVTp7AohhBBCiLfZ5cuX6du3L6GhodSoUQN4GdCZN28eANHR0fj4+JCcnIy9vT0xMTEMGTKEbNmysWTJkvQseoZn64MnJiZy6NAhEhISKFasGPny5SMyMvJ3gbiFCxeydetWbt++Td68efnqq69S7Vcm0t7AgQPR6XRERkYCaNfJyZMnadeuHUOGDGHAgAG/O07GUoQQr0pGyEW6MJvNHDx4kDVr1qCUYsyYMeldJPH/GQwGkpKS6NatG7ly5SI8PJzChQvToUMHFi5cCEDz5s21xsvUqVMxGo0MGjQo1edIAC5t/DYoULRoUVasWMGIESO0jlatWrUICwtj7NixdO/endWrV+Pp6fm7xrs0GtNGgQIF8PHxYfTo0Tg4OFCjRg0aNmyIi4vLXx6bsj5Pnz5NmTJlpIP1ChwdHfH398disdC9e3cmTpxIrly58Pf311bGValShaVLlzJv3jxy585N+/btUUoxefJkpkyZwogRIwAkGCqEEEIIId56hQsXpn///tSoUQOz2YzVaqV169YYjUZWr17Nr7/+io+PDwaDgeTkZPLkyUO3bt0YMWIEd+/eJU+ePNL/eA2sVit2dnYYjUa6dOmC0WgkNjYWe3t7tm3bRrdu3QC0bT0CAgLw8/OjUqVKvHjxgpo1a2IwGGRSYBr67XdpNptJTk7GYrFo+7vb29uTnJxM+fLl+eSTT/j666/p3r07Dg4Oqca0ZCxFCPGq5M4u0oWdnR2tW7dmwIABbNq0SdsjSbwdjh49SnJyMsOGDaNcuXIYjUZKlChBYmIi06ZNY+fOnTg7OzNgwACaNWvGt99+K7nl05Dtu0xKSkKv12MymThz5gwnTpzgwYMHVKhQgRkzZhAbG6ulU6hQoQLh4eG4urryySefcP/+felcvSYeHh707duXuLg4nj59SqNGjXBxcfnLayBlkGfNmjW0b9+e8+fPv4kiZ2jly5dn6NChFCtWjEGDBnHkyBGcnJyAl9+5j48Pffr0wWQysXv3bhwcHGjevDkzZ87k008/BV7ujyHXixBCCCGEeJtZLBb0ej1t27bFZDLRr18/5s+fT7Zs2ejduzctW7Zk2rRp7N+/H71ej729PQDPnj2jcOHCuLm5SZv3NdHr9ZjNZgIDA3F1dWXRokVs3ryZqKgocuTIgaenJ926daN9+/YsX76cuXPnAuDj48NHH32kpTuUAFzasO25npyczK1bt7hz5w46nY4aNWrwww8/cPToUe29tuvEbDbj7u6Ok5OTTCoXQqQ5uauIdJGcnEzu3Llp06YNer2eyMhIsmTJog2IivR17do1YmJiKF68ODqdjqioKB4+fMi6desYNWoUc+fOxWKxUL9+fUJDQ7Gzs9M2qZVG/au5cOEC27dvZ+DAgbi4uPD8+XP69OnD3bt3iYuLw8nJicDAQFq3bs28efMYPHhwqhVxwcHBbN68GQ8Pj3Q+k4zJloZi//79VKhQAZPJxLBhw1ixYgWlS5f+02sg5etRUVFEREQQEhJCiRIl3vQpZEhly5Zl6NChLF++nK+//pqYmBgKFiyopYTx8fGhcePGbNu2jaCgINzc3Pjkk08ASZ0rhBBCCCH+HVKuxrGlPbRNkO3WrZs2njJ48GCCg4MpW7as9p78+fPj6OiYXkV/J8TGxnLr1i26deuGt7d3qt9dv36dO3fu0KdPHwAWLFhA3rx5U21rIKut0obFYtFWJQ4ZMoQ7d+4QGxtLnTp1GD16NF999RVjxowhPDycDz74gEyZMnH58mVu377NBx98kN7FF0JkUDLqJN44q9WKvb09RqORWbNmce/ePQCWLl1KYmKipKZ8w/4o3UHVqlXZu3cvCQkJ7N27l5UrV7JkyRIKFChA06ZNCQkJYebMmdy6dUtr6EvahFenlGLjxo3s3r0bq9XKoEGDmDx5Mg4ODoSFhaHT6di3bx/BwcFcvHiR0aNHa6t5Fi5cSFJSEg0aNKBSpUqA5C1PS7bv0vZ9Dhw4EIDbt28THh5Oz549Wb58OWXKlPldIO63AbhJkyYRGhpKmzZt3vyJZEC277d8+fL07t2bp0+f8umnn7J582by5cunvQcgX758v0sbKgE4IYQQQgjxtvtt306v17NmzRoGDx5MdHQ0QKpAXHh4OEopGjRoQObMmZkzZ47sgfyaPX/+nOvXr5M1a1Yg9RjJgwcP6NWrF9u3b6d3797kz5+fFi1apGNpMy7bFitdu3bF1dWVgIAA7t+/T/HixXF2dmbixImEhITQv39/KleujJOTEzdu3MDBwYGgoCAAmWAuhEhzOiU55EQ6MJlMdOzYkcyZM9OhQwfc3d3ZuXMn+/bt04I84vWzrQAxmUxcu3YNd3d3cuTIAcCtW7fInz8/rVu3pkaNGgQGBmKxWJg/fz5nzpyhXr16+Pr6SpAnjSUmJhIREcF3331H1apVOX/+PN27d9dW7cDLDZznzJlDWFgYbdq04ZdffqFnz5588sknhIeHp2PpM6aUG2wfPnyYhw8f4u7uzgcffIC7uzsXLlxgwoQJXL169XeBOAnAvRkpv+fTp08zZcoUrly5QmRkJDlz5iQhIYERI0ZQoEABZs2alc6lFUIIIYQQ4q8lJiaSOXNmkpOTsbe3JyEhgS1btqDX6ylQoAA1atTAYrEwaNAgzpw5Q+fOnenWrRtGo5HFixcTFRXFiBEj6N69O4D2OeL1SE5OpmfPnlitViIiIvD09NQCcbdu3aJNmzZERERQu3Zt7RjJyvF6fPvtt4SFhREREcF7772X6nf379/H3t6effv2cejQIXQ6HUWLFsXf3x87OzuZzCyEeC3kTi9eu5MnT5KcnIyPj4/22vnz53ny5AmhoaHUqFEDgOLFi1O2bFlmzJiBvb09wcHB6VXkd4JSSlui37t3b27fvk1cXBzdu3enbdu2eHp6kpycTFxcHPHx8cDLVT9Hjhzhgw8+0III0kBJOxaLhcyZMzNq1CjCwsL47rvvuHfvHgULFgTQNg/28/Pj6tWrREZGUrduXSpUqMDmzZu194m0k3KD7c6dOxMbG0tcXBxGo5GSJUvSvXt3mjRpQkhICBMmTKBXr14sW7aMsmXLppr5GB0dLQG41yhlwLNMmTKMGDGCKVOm0K1bN5ycnKhevToAU6dOBWRmoxBCCCGEeLtdvHiRmTNn0rdvXypWrIjRaKRVq1Y8f/6cxMREdDodQ4cOpVOnTsyfP59BgwYRFRUFvFwR179/fxISEoiIiMDV1ZVWrVpJAO41s7e3p0GDBixbtowVK1bQo0cPvLy8ADAajbi5uf2uDiQA93rcu3ePmzdv4unpCfx33CoxMZFt27Zx8OBB1q9fT5s2bVLVgQRFhRCvi6xBF69VUlISM2fO5D//+c/vfvfo0SNMJhPwckDU3d2dhg0b0qRJE6Kjo5k5c+abLu47w2KxoNPpMJvN9OzZE3t7ewYOHEizZs1YunQpK1as4MaNGxgMBkqWLMnXX39Njx49GDx4MCaTiUGDBgEv600CcGnHthlzpkyZGDt2LLVr18ZisbBixQri4+NxcHAgOTkZgNq1axMXF8fTp08B8Pb21o4Xace2mbO/vz9Zs2Zl3rx57Nq1i/Xr15OUlMSiRYvYu3cvxYoVIzg4mOLFi9OmTRuuXLmiBeCioqIIDw+XANw/dOzYMdatW/eX77MF4gDKlCnD8OHDqVu3Ls+fP6d79+5s3boVe3t7zGazBOCEEEIIIcRb7fTp05w+fZoFCxZw8uRJoqOjyZ8/P2vXrmXx4sU0atSIsLAwoqKi0Ov1REZGUq5cOdatW8eCBQtwdXWlf//+tG/fnjFjxrB9+/b0PqUMzdYP6dKlC5988gn79+9nxIgRfP7556xdu5YJEyaQLVs22XPsDcmdOzdZs2bl8OHDJCcnYzAYUEqROXNmHB0diYmJITY29ncBNwnACSFeF7m7iNcqU6ZMzJo1C3d3dxISErh27RqlSpXCzc0NZ2dnbVWVk5MTAO7u7jRq1IitW7eyZMkSXFxc6Nu3bzqfRcZjmwH04MEDPD096dOnDyVKlAAgV65cLF68GKvVypAhQwgICGD16tXcvHmTChUqMG7cOFmi/xqlDMSNGDECi8XC8ePHiYqKonPnzjg7O2vvzZo16+9m0kmdpL0nT55w//59BgwYQOnSpQHIkSMHCxYsoF+/fqxatYoPPviAUqVKERAQwK5du7RViQ8fPuTnn3/WUoeK/82FCxfo2bMnvr6+f+uek3JFXNmyZencuTMeHh6ULl1a+510rIQQQgghxNvO19cXpRTLli1j4cKFPH/+nEaNGuHt7Y23tzd58uTBzs6OiRMnAi+DP/PmzaNz585cvHgRe3t78uXLR69evXBwcKBMmTLpfEYZm06n0/orI0aMIG/evHz11VcMGzaMIkWKkD9/fubNm6f196Xf/npVqlSJPHnysHLlSgoXLkyZMmW0sZNs2bKRPXt2mcAshHijZE848cYEBwezZcsWoqOj8fHxYdWqVUydOpXRo0fTsmVLLbiwb98+1q5dS6dOnahXr540Tl6TkSNHsn37djw8PFi/fr22TB9e7jm2cOFC2rRpw8CBA3F3d091rCzRf/1sDfOkpCTCwsI4deoUpUuXpkePHty6dYtFixbh4uLC8uXLZWPt1+zMmTO0atWKxYsXU6tWLZRSWK1WDAYDv/zyCx07dmT69Omp9u2D/27E/fjxY7Jnz55Opf93W7hwIWvWrOH7778H4MqVK3h7e//t41OmnZQ9MIQQ4t0lA55CiH+TlPesDRs2sHr1aq5du8bkyZNp2bKl9r5bt26xdOlSNm3aRHBwMJ07d0YphVIqVR9R+u//XGxsLJkzZ8bBweFvvT9l3ZnNZu7evUuWLFnImjWrlo1I6uL1stVBTEwMHTt2xNnZme7du/Phhx9y69Ytpk+fjoeHB/PmzZMMKUKIN0bu/OKN6dGjB7dv38bf3585c+bQsWNH7t69y8SJE7lw4QKVKlXC3t6e5cuXkzdvXho0aCCNlNeoT58+JCYmsn//fs6fP0/+/PmBlzO4/Pz80Ol0LF68mBcvXhAUFETu3LkBZCVJGkhISMDR0fH/fM9vU1NOnjyZTZs2sXfvXkqVKoWXlxcRERHo9fpUe4+JtJc1a1by5s3LwYMHKV++PG5ubtr3nStXLpycnHjx4sXvjrM16CUA988VLVoUo9HIyJEjtWCop6fn3+oEp+wAP3v2DDc3t9dcWiGEEG8j2/MgISGB7du34+joSP78+VPtVy2EEG8L2z3LNpmsffv2ODg4MHPmTJYvX07hwoUpX748gJbVRq/XEx4ejoeHBw0bNkSn06XqI0r//Z+5fv06Xbt2Zfjw4TRo0OBv9UFS1p2dnZ22Jxz8d79x8XoZDAasVit58uQhOjqagQMHMm3aNMaOHUv+/PnJli0bs2bN+t11IoQQr5Pc/cUb4+3tTUhICMHBwQQEBDB79myGDx+Op6cnK1euZOfOneTOnZvcuXMzY8YM7YEojZTXw9vbm4CAAJ4+farlJ/fx8dEajP379ycuLo5Tp06RM2dO7TiZKfRqTpw4wYYNGwgICCBPnjz/53tTBuJGjx6NnZ0dX3zxBS1atKB169YSpH5D8ufPT/369Vm7di2lS5emfv36WkDn4cOHuLm5pbpGbORaeXV16tShZ8+eLFu2DFdXV9q1a4eDg8NfrmhIuV/l2rVr2b9/P3PnzsXV1fVNFV0IIcRbwPY8iIuLo1WrVsTGxvLixQs8PDzo27cvHTp0SO8iCiGExta3S0pK4pdffuH27du0atUKX19fAJYsWcKcOXMIDAykbNmywMtAXPfu3cmfPz/16tXTPksCC68uR44c5M2bl4iICBwcHKhdu/bfCsTZ+oEps3KA1MmbZJusnC9fPjZt2sTx48e5f/8+uXLlonLlyhgMBhlLeU1++3cvhHhJ0lGKN+7GjRuMGTOG69evM3v2bHx8fHjw4AFGoxG9Xk+BAgUkuPAG3bhxg+DgYK5du6bVR8qHpu3fMkPo1d28eZOmTZvSqVMnhg8f/rePswUcEhMTWbVqFX379pUVcG9Iyu84KCiIL7/8El9fX2rWrInRaGTt2rUYDAbt/yLt2L77Nm3a8PTpUx49ekTTpk0JCwsD/jy1WMr7V1RUFBMnTiQ8PJzWrVu/0fILIYRIX7bnhMViISIigitXrjBq1CgePHjA5s2b+emnnxgwYACdOnVK76IKIYTW9jUajXTt2pVnz54RExPD4MGD6dOnD/b29mzcuJEVK1aQL1++VIG4lGQcJW0lJiYyaNAgfv31V0JDQ6lZs+ZfZrWB1H2SQ4cO4eHhIfvypYM/6zNKmuq09+jRI7JkyfK3U7cK8a6RIJxIF7bAz9WrV5kzZ87v0sFIcOHNstXH9evXmTVr1u/qQ2aypI0jR44QGBjIxIkTqVu3LhcvXqR48eJ/61hpJKaflH//U6ZM4csvv+TOnTsUKFCA/Pnzs2jRIuzt7aWO0shv7//ffPMNOXLkYP/+/SxdupSmTZsSHh4O/P66+G0AbvLkyYSEhNCmTZs3exJCCCHeCgkJCezdu5c9e/ZQt25d2rVrB8D58+dZtmwZ3333HYMGDZJAnBDirZCUlES3bt1wdnbGz88PDw8PcuTIgb29vTawvXv3bubOnYunpycDBgygYsWK6VzqjMkWzDSbzZw/f55evXrh4eGBv7//X66IS9knWbVqFXPmzGH+/PlUq1btTRVf/IaMMb5eYWFhnDhxArPZTLdu3fjoo49wd3dP72IJ8VaRO5BIFwUKFCA8PJwiRYrQuXNnzp8/n+r38nB8s2z1Ubhw4T+sDwnApQ03NzcyZ87MmjVrqFChAkuWLNE2zv4rKa+JmzdvkpiY+DqLKlLQ6XRaHY0YMYI1a9awdetWlixZwrJly7C3t8dsNksALg2YzWb0ej3Jyclcu3aN8+fPU6ZMGUqUKEG3bt3o06cPn3/+OcHBwcB/U7ZC6s7umjVrmDRpkgTghBDiHffVV18xatQovv3221QrF0qUKEGfPn2oXr06CxYsYN26delYyoxL5vsK8b85e/YsT548wd/fHx8fH3LmzMmBAwfo0aMHnTp1YtGiRTRu3Bg/Pz9OnTrF3r1707vIGZJSCjs7O4xGI02bNmX69OlkzZqV58+fM2HCBA4dOoTJZPrTY1NOCpw2bRojR46UANwrsvX5/shfPWuUUtp4ioylpL1hw4axb98+ypUrh7OzM6GhoWzYsIHHjx+nd9GEeKvIGnWRJv7JrJICBQowbtw41q1bR9GiRV9Tyd5NUh9vp1KlSjFy5EiGDx+Oq6srderU+dN88Sml/N3y5cvZtWsX8+bNI3/+/G+s7O+6lClZ8+XLR758+bTfWSwWSfmSBmzfo9FoZPDgwdy4cYPHjx/j6upK7969ad68OT169ABg6dKl6HQ6wsLCfpfP37YCLjQ0VAJwQgjxjvlte6pZs2aYTCbCwsLYsGED3t7elC5dGoDixYvTp08fDAYDoaGh5MiRg/r166dX0TOUZ8+e4ebmpk1kkgl9Qvw9JpOJ+Ph4bt++zYULF9i7dy/fffcd77//PiaTiejoaKpUqUKLFi1wdXWldu3a6V3kDMl27woLC8PJyYkJEyaQLVs2jEYj4eHhjBkzhokTJ/5uRdxvA3CTJk2SPkkasPX1EhIS2LVrF0+ePMHR0ZGPP/4YDw8PDAbDn46ByVjK6/XixQuSkpKYNm0aVatWBWDcuHEsX74cq9VKhw4dyJ49ezqXUoi3g4waileWcr+qO3fu4O3t/bePLVy4MGPHjgUgOTkZe3v711XMd4bUx9vJarWi0+n49ttv8fDwIDk5mS1btpA9e3Y++OCDPx2k+G1DfsaMGYwZM0Yaja/ot9/13wlc237/22NlBVzaMBgMJCUl0bVrV5ydnfH398fZ2ZkDBw4QERHBrVu38Pf3p0uXLgCsXLmS58+fM3fuXC0At2rVKiIiIggLC5POrhBCvGNSpg6Lj4/n6dOnFChQgNatW6PT6Zg6dSrLli2jX79+lChRAngZiOvatSuenp7UqVMnnc8gY0hMTGTixImUK1eOLl26oNPppF8hxB/4o1T27733Hrly5dL2D8+bNy+zZ8/WJghUrlyZkydP8t5771G3bt0//Rzx6iwWC3fv3qVChQoULFgQgKxZs7Jw4UIGDBjA+PHjCQkJoWbNmmTOnDlVf1ICcGkn5arENm3aoJTCYrHw/Plz1q9fT6tWrejUqdMf7tMnYymv17Rp01i3bh3u7u6pAm2hoaHAy/46IIE4If4/CcKJV2K1WjEYDCQkJNC2bVsqVapEYGAgrq6uf+tYWyMlLi4OZ2fn113cDE/q4+1j6xTZvtuRI0fi6urKgQMHmDBhAosWLUIpRdWqVX8XiJOZdGnPYrFoDXmLxUJCQgKOjo5/u+Oask6+//573N3d//a+fuKv/fDDD5hMJkJDQ7WNy+vVq0eBAgWYNWsWhQsXplOnTrRt25a4uDjOnj2r3btOnjzJ6tWrJQWlEEK8g1Kuph45ciSXL1/m2bNneHl5MXDgQFq1aoVOp2PKlCkAqQJxpUuX1lbHyWD2q9Pr9Tg7O7N8+XIsFgtff/01w4YNo0yZMrLlgBD/n+1eEx8fT3R0NCaTiRIlSlCvXj3Wr1/Prl27yJMnD4UKFSJ37twAXLhwgZw5c5InT55UnyX3rNfDzs6OpKQkbty4ob1mMplwcHDQ+hvz5s0jMTGRhg0baivi1qxZQ0REhPTb04hOp8NisTB69GiyZs3K5MmTyZEjBy4uLtSqVYtNmzbx4YcfUqxYsVQTZWUs5fWrX78+v/zyCydPnuThw4cUK1ZM65vbAnFRUVEkJCTQq1cv2SNOvPOkFSz+MVteZZPJxOrVq3Fzc6Nnz564uLj87WPh5cqFHj16kJCQ8LqLnKFJfbx9bPuEJSUlcfz4cXbv3s2FCxdITEykTp06TJgwgatXr7J48WK+//574L+pL6TRmLauXr2qBaltg3QDBgygY8eOtG7dmpMnT/6tXPIpN9geMGAAL168eBPFf2fcuHGDO3fu4OXlBbxckQsvB0tbtGjBokWLePr0KTlz5sTPz49Vq1Zp966iRYsSGRlJu3bt0q38Qggh0odtElrHjh159uwZvr6+DB48GIvFQkBAAFFRUfj6+vLpp59y9OhRli5dyq+//vqHnyNejYODA126dKFEiRJMnz6dmzdvUqpUKfR6PVarNb2LJ0S6U0phMBiIi4ujZcuWrFmzhqioKAYNGsSCBQtwcHDA19eXqlWrcvXqVQ4cOMDevXsJDQ3FycmJevXqpfcpZDhmsxlAW2Vl8/HHH3P+/Hk2b94MoAXaHBwccHV15fr16+zcuVN7fePGjbIv9WuQnJzM7du3qVmzJgULFsTFxYXDhw9z//59+vXrx7179zhz5oz2fhlLeTMqVKhAcHAwBQoUYOLEiVy+fDnVsz40NJQPP/yQ3bt3p3NJhXg7yEo48Y/pdDrMZjNTp05l//79lCpVSlvW/Xf3t4qKimLq1KmMHz/+D5ePi79P6uPtYrVatWBP165defbsGXfv3sXV1ZU8efIwf/58Le3RhAkTWLJkCTqdTktNaSONxlf35MkT+vTpg6urK9u3bwegdevWuLi4ULJkSS5evEjfvn2JiIigVq1af5lLPioqiunTpxMcHIyPj8+bPJUMz8XFBTs7O86ePUvlypWxt7fXUljVqlWLPXv2EBMTQ7Zs2ciSJQuAFrR2cnLSVjIIIYTI2J4+fUq2bNlSvbZv3z4Axo8fr+1v3KlTJ4YMGcLMmTMpUqQIbdu2xWQyER4eToECBShbtuwbL/u7wNvbm7i4OFxcXLBarWzdupV27dppg3OyIk68q2x//1arlc2bN5M/f34mTJhAQkICu3fvZt68eej1evr374/RaGTq1KlcvXoVDw8PChcuzKpVqzAYDLJqNw3ZVlLHxcUxf/587t27R/Xq1alduzYtW7bkq6++IioqCqvVqk32e/LkCe7u7lqmDps7d+4QERFBixYt0ulsMobf/n3btlqxWCzodDq++OILgoKC8Pf3p1WrVvTo0YM8efIwadIkCcC9Zvv27eP27dvY29vj7e1N9erVmT59OkFBQQQEBDB79myKFCmi3eumT5/Ow4cPZRWcEEgQTrwiOzs7cubMSaZMmTh69Ci3bt3C09PzT4M+8kB8vaQ+3h62VYmDBw8ma9asDB8+nMKFC3Po0CGioqLo3LkzGzdu1AJx4eHhREREEB4erqXhW7JkCfPmzZM6eUWZM2emW7durFixgs6dOzNs2DCKFClCcHAwHh4exMbGEhwczIgRI4iIiKB27dqpBofkOnlz6tWrx4wZM1ixYgWFCxfGw8ND20MmPj6e3Llz4+bmluoYnU73p5MMhBBCZDxXrlyhXbt2REdHayklAS5dukRcXJwWgLOlDZs7dy6+vr7MmTOHqlWr0rlzZ3LlyiV7wKWx3w6a+vn5YTab2bhxIwsXLkQpRfv27SUQJ95per2epKQk5s+fz/Hjx6latSqenp4A5MiRA4PBwOzZs1FK4efnx4YNGzh37hyOjo4UK1YMvV6v7X8p0oYtLWjr1q1JSkoiU6ZMfPHFF3zyySeMGTOGGTNmMGzYMObOncvOnTvJnTs3Fy9eBKBQoUKp6iQoKCidzyZjsK1uv3TpEqVLlyZr1qxUqVKFH374ATs7O+bMmUNQUBC9evUCXj5/TCYTgNYvlLGUtOfv78+xY8fIlCkTcXFxGI1GOnfuzKhRo5g5cyYBAQEEBgYye/ZsvL29tWd9jhw50rvoQrwdlBD/A7PZ/Ievf/bZZ6p69eqqadOm6tatW0oppSwWS6r3WK1W7d9r1qxRJUqUUJs2bXp9hX0HSH283c6fP6/q16+vDh06pL1mMpnUL7/8oho3bqxatmypEhISlFJKffnll2rAgAFaPb148UJVr15dRUVFpUvZM4I7d+6oq1evKqWUio+PVxs2bFAffvih8vHxUc2bN1fx8fHae588eaL69++vKlWqpL7++mutHuQ6eXNs97PDhw+r999/X/Xu3Vt999136vHjx+rEiROqTZs2ys/PL1WdCCGEeHfY7v/37t3TnsUWi0V7PTIyUtWuXVtduXJFOyYpKUkppdTKlStV5cqV1c2bN1N95p+1pcX/JjExUSn18vs+fvy4OnPmjFYvv/zyixowYICqVauWWrdunXbMb/smQrwrDh8+rFq2bKkqVKig9fVs18PTp0/VnDlzVIkSJdT8+fN/d6xcN2kn5Xe5d+9e1aVLF+0ZsW3bNlWuXDkVEBCgHj58qJ48eaLWr1+vevTooQYMGKDCwsJUcnLy7z5HpJ2xY8eq4sWLq++//14ppdT+/ftVqVKlVPHixdXkyZO19928eVM1atRIRUZGKqVe1oeMpaS9xYsXq/r166sjR46opKQkdfPmTbVgwQJVunRpFRYWppRS6uzZs6pJkyaqRo0aqdpiQoiXJAgn/jZbI8M2mD1v3jy1cuVKraGyc+dO9fHHH6sOHTpor8lA9usj9fH2O3jwoCpVqpQ6d+6cUuplAM72/3Xr1qlKlSqpn3766XfH2d5nNBrfXGEzGIvFolatWqX69eunnj17ppRS6vHjx2rDhg2qUaNG6qOPPtICoLYBuCdPnqgBAwaoKlWqqC+++CLVwNyaNWtUyZIl5Tp5AywWi/rmm29UjRo1VMWKFVWFChVU3bp1VatWrbRrQzq7Qgjx7omNjVVK/bcdm5SUpNq1a6d27NihlFLq1KlTqkSJEioiIiLVRBullFqwYIFq2rSpevHixZstdAZ24cIFtWzZMu3nZ8+eKV9fX+3Z3bNnT+15feLECTVgwAD10UcfqbVr16qnT5+qQ4cOSX2Id8IftVu//PJL1aRJE1W5cmX1448/pvrd06dP1bx581Tx4sXVtm3b3lAp301JSUmqc+fOatCgQVogwWbr1q2qXLlyKjAwUN24ceMPj7eNyYi0d+/ePdWjRw9VrVo1deTIEaXUyzGukiVLqp49e6qVK1eqFStWqJYtW6oWLVr8LigqYylpa8CAAWrEiBGp/uZjY2PVypUrU92rfvnlF9WmTZvfTXoSQiglOSDE36KU0va38vX1ZcWKFXzxxRfMmTOHAQMGsGjRIpo2bUqvXr149uwZI0aM4Pbt21q6EduS8JUrVzJ58mRZEv6KpD7+HQoXLoy9vT0HDx4ESLW/Vc2aNYmNjeXRo0e/O86Wfs/Z2fmNljcj0ev1ODs7c+HCBUaMGEHZsmXZt28fjRs3pmvXrsTFxdG9e3esVqu2r0K2bNmYOHEihQsXZsuWLVpKpTVr1sgG22+QXq+nRo0a7N69mzFjxhAYGMjw4cPZuHEj9vb2mM1mSWElhBDvmPj4eIYOHcrmzZvR6XQkJyfz4MEDXFxcCA0NZe/evZQtW5bhw4ezatUq5syZw5UrV7BarZw7d44DBw5QvHhxaVulkeTkZCIjI1m+fDnLly9HKcW4ceNwcXEhJCSEHj16cOHCBVq1aoXFYqFChQr06dOH0qVLM2PGDKpVq8bq1aulPkSGZ2u3Jicn8/jxY86fPw9A/fr1GT16NPny5WPChAkcO3ZMO8bNzY2OHTsSFhZGkyZN0qvo7wSj0YiTkxNfffUV8fHxmM1mrFYrAL6+vowfP56DBw8SGRnJr7/++rvjJS1o2jCbzal+tlgs5MqVi4iICIoUKUJQUBDff/89TZs2Zc6cOWTOnJmFCxeyZ88eChYsyObNm7Gzs8NisWj9RHm+pA2z2YzRaOTixYs4OztjZ2enpf50dXWlUaNGFC1alOPHjwNQrlw5oqOjtTS7Qoj/0imlVHoXQvw7WCwWPv30Ux48eMDEiRPx8vLCYDDQsGFDnj9/TnR0NN7e3mzZsoXVq1eTnJzMmjVryJkzJwBnz57F39+fnj170qFDh3Q+m38/qY+3m1IKk8nE5MmT+fzzzxk7dmyqDZq//fZbQkNDmTZtGuXLl0+/gmZw8+fPZ9GiRbi4uDB79myqVKlCfHw8n3/+OfPmzaNgwYKsWbMGvV6v7WVi64zZGvCTJk2iaNGiEoB7Bf/r5vF/9n7ZhF4IId5dYWFhbNiwgeDgYA4cOEDPnj0pWLAgU6ZM4fDhw0ybNo0aNWqwYcMGpkyZQo4cObCzs8POzg4XFxc2bdqEnZ3dn+6VLP43t2/fZsqUKVy6dIk6depw/vx5+vXrR5UqVbBarezdu5dJkyaRI0cObXLTmTNnOHPmDLdu3WLIkCHY29tLfYgMK2XfYtCgQdy+fZt79+5RqFAh2rdvT5s2bTh+/DizZs0iLi6OkJAQfHx8fvc5sgdc2vmj/SgfPHjAlClT+Oqrr5gyZQqNGjVK9ftt27YxatQoBg0axKBBg95kcd8pCQkJzJgxg+DgYOC/18+DBw8YNmwYly5dYsaMGVStWhWz2UxsbCyZM2fGyckJkOvkdRs9ejQHDhzg888/J0eOHNq+uwA9e/ZEp9OxdOlSmSwrxP9B7lDib1NKcfPmTWrVqqUFfA4fPsz169eZPHkyN27cIC4ujtatWxMbG8vZs2fJnj27dny+fPmIjIykePHi6XgWGYfUx9tNp9ORKVMmWrVqRUxMDKGhody5c4cPP/yQhw8fsnTpUnLlykXZsmXTu6gZkq1ReP/+ffLnz09SUhJRUVHkzJmTQoUK0bRpUwDmzZtHt27dWL16NQaDAavViouLC/Dfhvzo0aPT81T+9WwdqISEBE6fPk2lSpX+8hhboO23HWUJwAkhxLvl7NmzODs7U6BAAbp27crDhw8JDQ0lT548VK1aFYCRI0ditVoZNmwY06ZNo3v37vj4+HD48GGMRiMFCxakdevWGAwGGaRLI2azmfz58zNq1ChCQ0PZs2cPL168oFixYsDLVe316tVDp9MxceJE2rRpw5YtWyhdujSlS5dO9TlSHyKjMhgMJCUl0aVLF7JmzcqAAQMoXLgw0dHRTJ8+nYsXLxISEkJCQgKLFi0iJCSE0aNHa/c2G7lG0obtfmMymbh69SoPHjwgd+7cFCtWjJCQEJKTkxk9ejR2dnbUr19fO65ly5a4u7tTvXr1dCx9xpSyr3fgwAGio6O5c+cOCxcu1LLV5MyZk8mTJzN48GDGjRtHWFgYPj4+uLu7a59jyxQl0s727dt58OABmTNnpmvXrvj6+vLTTz8REBDA3LlztbHFBw8ekJiYyPvvvy8TaoT4C7ISTvwp2wPR1lh58uQJDRo0oFevXvj5+bFr1y6GDh3KkCFDGDBgAN26dSNfvnxMmjQJQJvVaFsSLjfkVyP18e915swZPvvsMz777DOSkpLImTMnXl5eLF++HHt7+z+ckSf+md+ulHrx4gWZMmVi5cqVbN26lWLFihEUFEThwoWJi4tj165dzJ8/HxcXF3bv3i3XRRqz1UdiYiKNGzemdOnSzJw58291klLOjL916xa5cuXSZtsJIYTI+IxGI61ataJVq1b07dsXgD59+nDy5Eni4+MJCwujZcuWANy7d49JkybxzTffMHnyZBo2bPi7z5PV1GnD1m61TXi6c+cOkydPZv/+/fTq1Ythw4Zp7zWZTHz99ddERESg0+k4ePCgtLXSkKwifPt9//33jBo1ihkzZlChQgUMBgOff/45w4YNY+bMmZQqVYqCBQtq10n58uWZPn16ehc7w7Hdt4xGIz179uTx48fcuXOHrFmzUqFCBWbOnInZbGbMmDF89913TJ06NVUgzkYmDqQd2/3LZDJhMpmwt7dny5YtzJ07lwoVKrB48WLgv9/5ihUrmDp1Kvb29qxfv54yZcqk8xlkXEOGDOHUqVPodDoqVqxIQEAAnp6erF27lhUrVmCxWPD398doNHLy5Em++eYb1q9fT+HChdO76EK81eTpIf6ULXd527ZtGThwIPXq1aN27dp89dVXWCwW5s+fT2BgIL169QJervxJSkrSjtfpdCilpLObRqQ+/n1sDcvSpUtTtGhRunfvzrVr1/Dw8KBEiRKpgqri1aVccbV582YyZcqEp6cn1apVo1+/fiil+Oyzz5gxYwbDhw+nQIECNGnShISEBH788UdtfziRdmwzgH/44QeKFi2Kn5/f3zou5aDS8uXL2bt3L3PmzCFv3ryvs7hCCCHeIi4uLixfvpz8+fOTkJDAo0eP6NWrF3Z2dqxdu5axY8eilMLX15fcuXMzevRoIiIiGDNmDCaTiaZNm6YKUMgz/tXZ2lrJycl06NCBnj170rhxY4KDg1FK8eWXX5I1a1YtaOrg4EDdunVJSkpi37590tZKI7b+g61/J4G4t8dvg/23bt3i8ePHlCxZEoPBwPbt2xk1ahQBAQHky5ePkJAQwsLCqFu3Lq6urrz//vvpWPqMyzZxoH///jg6OjJu3Djy5MnDwYMHiYqKonv37qxdu5apU6cyYsQIRo0aRWJiopY9xUb67WnDdp1YLBbat29P2bJl8ff3p3Xr1litVubNm0e/fv1YvHix9p3b29vTp08fMmXKRIkSJdL5DDKu6dOnc+rUKebNm4eHhwc5cuQA/jsxKn/+/Kxfv56xY8fi7u5Ovnz5WL16tQTghPgb5Aki/pK7uzvbt2+ndu3aNGjQgNDQUCIjI+ncubM2sH3r1i3u3bv3uzRj0iFIe1If6e+3nas/6/ymfM3Ozg5PT89UG9RarVZpyKcRW4A5Li4OX19f4uLiiI2NJVu2bHTu3Jk+ffrQv39/4GVe/4iICFq0aMGdO3f46KOP6Natm7ZSVAaH0tbIkSPZs2cPefPm1fbn+b9Wf6a8nqKiopg+fTpjx46VAJwQQryD8ufPj1KKgIAArly5wooVK/Dy8iJLliwopRg3bhxKKVq1akXu3LkZOXIk8fHxbN26lWbNmqV38TMUW+AnKSmJEydOaOnWHR0dqVOnDqNHjyY8PJytW7cCpArENWnSRNsbWdpar0YpRUREBLly5aJPnz7odDri4uJwdnZO76K982zXSHx8PJcuXaJ8+fKUKFECnU7HTz/9RHJyMiNHjiQwMJB+/foRExPD999/z6lTp8ifPz+VK1cG5Bp5XU6fPs3Dhw8JDw/Hx8cHnU6Hl5cXpUqVYuTIkQQEBLBgwQImTJjAp59+ytatW38XhBOvznadJCQkcO7cOeLj49m1axcuLi707duXtm3bAmiBuLCwMO7du8eePXuoVq2ati+fXCdpz2QycePGDXx9fSlbtizPnz/n8OHDzJ49m0ePHpE3b14mTpzIokWLuHjxota3d3V1Te+iC/GvIKO/4v9kb29P7dq1Wb58OXfu3KFBgwY8fPiQhQsXcubMGaKjo4mPj2ffvn04OjrSr1+/9C5yhib18Xawpdc7ePAgjRo1+lvBTb1erwUXUv5fvLqUM+kiIyPJly8fY8aM4enTp2zatImVK1eilKJv3770798fvV7P5s2bCQgIIE+ePFoATlaKpo3fBqVHjhxJbGws3333HYcPH6ZJkyZkypTpL4+Niopi0qRJhIaG0qZNmzdS9oxKUt4K8ef+7PqQ1SXpK+X3r5SiT58+jB49Gn9/f+bMmUOxYsXw8/NDp9MREhKCUooGDRrw888/ExwcTP78+dP5DDIW2347RqORzp07o9fryZYtGzdv3iQwMJCpU6fy8ccfExwcrAXidDodffr0AVKvHpG21qvR6XTkyZOHGTNm4OTkxOXLl6lYsSINGzbE3t4+vYv3zrIFFuLi4ujQoQNJSUls3rwZd3d3ypUrR2hoKHfv3mX48OH07NkTq9XKhQsXyJMnD15eXqk+S66R1+Pu3bvcvXuXnDlzotPpMJvNZM6cmUqVKtGpUyeioqK4dOkSRYsWZebMmbi5uaV3kTMk23Xi6+uLm5sbOXPmxM3NjeXLl5OcnMygQYNo164dOp2OyMhIatasSdasWcmTJ482qRbkOnkdHBwcePz4MQ8fPqRIkSJ89tlnfPvtt7z33nvUqVOHAwcOMGnSJNasWUPRokWlnSzE/0j2hBMa20C21WrFYrGkasQ3btwYb29v5s6dC8Du3bs5ePAghw4dwtvbG09PTyIiIrCzs5MZKWlE6uPtNmHCBI4fP87nn38O/PVgXcrfHzt2DB8fnzdSzndFQkICu3btYv/+/dSsWZNOnToBcOXKFZYvX87Bgwfp0aOHNiv7+PHjGI1GatSooV1nEqR4dbYBCIvFgsViAV425h89ekS/fv14+PAhERERVK5c+XerQCUAl7ZS7gNqMBgwmUycO3eO2NhYSpQogYeHh3Sc0sH/lYJYgj5vXso20s2bNzEajRQqVIjMmTOj0+nk2ZBOUj5LlFIkJibi4uLCyZMnGTp0KM7OzsydOxcvLy8uXrzI4sWL2b17Nw4ODlSuXJmlS5dK/aWB335/FouFYcOGcfv2bUJDQ/H29ubUqVOsW7eOffv2MWPGDD7++GNtj7ijR48yduxYmjdvno5nkTHdunWLlStXsmHDBvR6PQcPHiRHjhzyN59ObPcso9FIs2bNePToEVmzZmXPnj24uLjwzTffMHr0aJycnPj000+pX78+P//8s7ZP8sqVK6Xe0tgfjYGcPHmSjh07MnHiRFq0aIFSCovFgp2dHWfPnsXX15dly5ZRo0YN7Ri5pl6PyZMnc+TIESIjI/H09MRsNrNu3ToiIiLo2rUrAwcOxNXVlTt37nDw4EGcnZ1p0aIFBoNBtvN4DWxhAZ1Ox5EjRxg5ciQPHjygaNGitGrViu7duwMwc+ZMfvzxR9auXStjjEL8A3LnEhrbXkqDBw+mWLFidO7cWUv/1bt3b1asWKEFDxo3bkzjxo158uQJLi4uODg4ALJRbVqS+ni7tW/fnh07drBx40ZtptafSTmwumbNGiZNmsSGDRuoUKHCGyptxvfNN98wduxYAOrVq6e97u3tre2TuGrVKm1Wdsr9FiRQnTZSzgAOCQnhxo0bFClShCZNmlC1alUWL15Mnz59GDt2LGFhYakCcb+9RiZPniwBuFdw+vRpduzYgb+/Py4uLsTFxdGpUydtZqOXlxfVqlVjzJgxMmv+DTCbzSQnJ+Po6Kj9zW/fvp1bt26RO3duChcuzPvvvy8BuDckPj6eqKgoOnbsqKXPGTZsGD///DN37tyhaNGiVK9enaFDh/5l+lyR9mwDorZnyaVLl/Dy8sLf35/y5cszbdo0hg4dypAhQ5g7dy7FihVj0KBBVKtWjatXrxIYGKitbpd6++eOHTvGnj17GDFihNaviI+P59q1a9SsWVPbj6dixYraKp7hw4djb29PnTp1GD58OBs3bqRJkybpdg4ZmaenJ3q9HoPBgFKKzz//nJ49e6LX6+We9YYlJydjb2+P0WikefPmeHl5MXr0aEaPHs2DBw9wdnbmww8/JDw8nEWLFjF27FiCg4NxdXUlR44crFq1SuotjaVMd7hjxw7u3r1LiRIlKF68OA0aNGDKlCnkzJmTatWqYWdnh1KKu3fvUqBAAXLmzJnqs6RO0p7VauXmzZsUKFCAAgUKAC9Xx9kCPREREdjb29O5c2c8PT3p2rWrdqytjSDSji2rlqenJw0aNKBatWrs2LGDW7duUbhwYVxcXAC0NLs5c+aU8RMh/iF5oohUKfFMJhNJSUkcOnSI5s2bs2DBAn799VcaNmxIYmIiR44cSXWcu7u71jGzpSkRr0bq4+1jW9FjYzabKVSoEI0bN+bAgQM8e/bsT4/97eqeqVOnEhYWJgG4V2S1WlP93KBBA2bMmIGzszMbN27kxIkT2u+8vb3p3bs3devWZcaMGezcuTPVsdKAfHW2/Q2NRiO+vr6cOXMGd3d3jhw5wowZMzh8+DAeHh4sW7aMrFmzMnbsWH788UeSk5OB/+6fuGTJEqZNmyYBuFd07tw5oqKimDlzJi9evGDUqFG4uroSERHB7t27qV69Ot9++y09e/bU6kC8HiaTifbt2xMdHU1SUhIAQ4YMYfLkyWzfvp3p06czcOBAlixZoh0jSSper2+++YZZs2Yxa9YskpKSmDVrFseOHaN///4sX76ckiVL8vXXX9OzZ09MJpOWTlq8Gbb9XVu1asXdu3cpX748RYsW1fa7qlChgnZvGzJkCDdu3KBQoUK0atWKYcOGYWdnh9lslqD2K7p69So6nU7rV8DLutHpdDx//lx7TafTkSNHDjp37oxOp2PYsGEcPnwYLy8vgoKCtHTh4tXZ2r62/3/00UfMnz8fX19fZsyYwbJlywC0gI54fU6dOsVXX32F1WrVAnDNmjXD09OTmTNnUrZsWeLj47l37542KaBWrVpMmzaNRYsWMWzYMMLDw1m7di329vaYzWYJ9qQR2xhIXFwcbdu2ZeXKlezZs4dJkyZhtVrp0KEDhQsXJjAwkK1bt3L58mWOHj3KsmXLyJMnD0WKFEnvU8hwftuG0uv1uLm5cePGDUwmk/Yeq9VKp06deO+994iOjmbTpk3ExsamOlb67Wlr8ODBrFq1ivv377Njxw4mTpzI4cOHyZYtG+XKlePGjRuEhISwdu1aRo8ezfHjxxk8eHCqtoEQ4n+gxDstOTlZKaWU1WpVcXFx2uuXLl1S06dPV7Vr11bVq1dXixcvVjNmzFCVKlVS58+fT6/iZnhSH2+vhIQE9dNPP6V6bc+ePaps2bLqxx9/VEq9rLeUUv68Zs0aVaJECbVp06bXX9gMznadJCcnq8ePH6vLly8ri8WilFLqiy++UFWqVFF+fn7q5MmTqY67ePGiWrx4sTKbzW+8zO+C5ORkNXDgQNWrVy918+ZNpZRS8+fPV5UrV1Zt2rRRBw4cUEop9ejRI+Xr66vKli2r1ZHFYlHPnj1TlStXVlFRUel2DhlFUlKS2rRpkypdurQaO3as6tevn9q+fbv2e6PRqNauXatq166txo0b97t7l0hbAQEBqnz58io6Olrt2bNHffzxx+rIkSPKbDar8+fPq0mTJqnixYur2bNnp3dR3wlJSUlq48aNqnTp0io0NFQFBwerJUuWaL+3XR+1atVSw4cP154v4s2ZOXOmatOmjYqJidFeu3Dhgtq9e7f68ssvlVJKnTx5UtWvX199+OGH6u7du+lV1AzL1laKj49XixYtUi9evFBKKTVs2DBVq1at3/U/EhMTVePGjVXNmjVV2bJl1blz5954mTOylG3XZ8+eqUePHmk/37t3TwUHB6tSpUqlupfJsz3tWa1WZbVaVZMmTdSsWbO011evXq06d+6s7t+/rywWi3r06JGqWLGidr+ySdm/t5F+Sdozm81q2LBhqlOnTuratWtKqZfXic2hQ4fUiBEjVKlSpVTp0qVVrVq1VIcOHZTJZFJKKXnup6GU41sJCQna65s2bVJVq1ZV0dHRqV5PTk5W3bp1U02aNFHFixdXW7du1Y4XaWvatGmqQYMG2hhXdHS0qly5smrbtq06ePCgUkqpnTt3qurVq6sGDRqozp07qwsXLqRjiYX495NlMu+wlKnDZs6cyfXr1ylTpgydO3emSJEifPrppzRq1IhTp04xf/58nJyciIuL47vvvqN48eKyBDmNSX28vSwWC6NHj+aLL76gVatW1K9fn9q1a9OwYUP27NnD7NmzWbRokZbWCmR/q9fFloLCaDQydOhQrl27xtOnT8mdOzcDBw6kUaNG6HQ6QkJCWLRoEf3796dcuXIAFC1alKJFi2qfI9dL2oqLi+P27dt06tQJT09PHj9+zIMHDyhVqhQPHjxg7ty52NvbU6NGDRYtWsTMmTMpXbo08HImfdasWdm/f3+q60j8Mw4ODjRv3hyr1UpERAQJCQk0bNgQePmscXZ2pnnz5pw5c4ajR4/y4sULsmTJks6lzrhmzZrFuHHjmDp1KjVr1iRPnjz4+PhgMBgoXrw4vXv3JlOmTCxbtowyZcpQt27d9C5yhubg4ECLFi206yMxMZGAgADg5bPBtu/ItWvX2L9/P3fv3iV//vzpW+h3zO3bt8mZMye5c+fm+PHj7Nmzh+joaDJlykRSUhJ9+/YlKCiISZMmER0d/bv0YeLV2dpI//nPf5g1axZ3794lJCSEkSNH0rZtW8aNG0dISIiWlvLKlSs4OjrSt29f1q5dy+rVqwkNDcXOzk5WJb4iq9Wq1Ud4eDjHjh3j5s2b5MmTh44dO9KkSRPtHjZnzhz0ej09evTgm2++oVSpUuTIkSMdS5+xqP+f5nbr1q04ODiQkJDA2bNn6dq1Kx06dNBSfLu5ueHh4cH58+epX78+Sinu3LmDv78/vXr14pNPPtE+U/ojaU8pxeXLl6lSpQoFCxYEIHv27FitVh4+fMj9+/dp3749HTt25M6dO3h4ePD++++j1+tlO4809EfjW+XKlaNr1660adOGffv2MW/ePJRStG3bFgcHB27evElcXBwjR45k3759LF68mI8//hgnJ6f0Pp0MJTk5mdOnT9O0aVN8fHxITEwkNjaWQoUKERsby9y5c3F2dqZp06Y0aNCAZ8+e4eLiomUlEEL8M7Lm/R3129RhBw8eJD4+nuXLlxMeHs6lS5cAKFWqFO3bt2f37t107dqV999/n9WrV5OYmCgNxjQk9fH2SZnGxWAw0L17dyZOnMj3339PSEgIXbp04ZdffuGDDz4gc+bMXLhwIdVxtgGH6OhoCcClIYPBQGJiIp06dcJoNNKhQweGDRtG1qxZ+fTTT1myZAkNGzZkzJgxnDx5kmXLlnH8+PE//ByRdpRSPHr0iBs3buDm5gbA+vXrOXjwIGFhYYwYMYJz584xffp0li1bRo4cOZg8ebKWpsp2vUgA7tWoFOleHBwcaNasGWPHjsXR0ZFvv/0WQEvV5uzsTIcOHbhx4wZXr15NryK/M0JCQmjVqhVfffUVd+/e5cWLF9rvcuTIQcuWLcmdOzenT59Ox1JmbL+9Ppo3b864ceNwcnLi9OnTmM1mDAYDZrMZJycnevXqRUxMDOfPn0/HUmd86g9SfZYtW5bDhw/Tvn17Bg8ezMaNGwkICGDZsmUMGjSIrVu38uDBAypWrMjs2bMl5WEa+m191KpVi5CQELZu3apdL9OmTePp06f4+fkRHBzMtGnTGDFiBPb29jRr1gx3d3diY2Oxt7eXAFwasKUpHDFiBAcOHODjjz9m5MiReHl5MX36dGbOnInBYGDQoEG0bt2aadOmUatWLcLDw+X7T0P37t3j1KlTJCUlaanYgoOD6dSpE/v379e+a1vQ1MXFhevXrwMQExPDiBEjePr0KfXr10+vU3gnWCwWnj17xpMnT8icOTPwMuBgZ2eHXq/n6dOnhIeH8+DBA8qVK0ejRo2oVKkSer1e9htLQ382vrV06VLGjh3Lo0ePWLZsGe+99x6LFy+mRYsW+Pn50bdvX5KTk6latSo5c+bUAj9yL0s7VquV58+fc/nyZS2o9s0337Bu3Tr8/PwYPXo0Z8+eZfLkyaxdu5ZMmTKRK1cuCcAJkQbkCfOO0uv1JCcn4+/vT968eZk4cSJ58+bVVvTYGvKFCxcGIEuWLLRv356PP/6Ynj17smHDBrp3755qtY/456Q+3i62WVsmk4lffvmF7NmzU7hwYcqVK0fNmjX57rvv2LBhA0OHDqVo0aJ899135M+fHx8fn1T5/KOjowkPDyc8PJzWrVun4xllLF9//TVWq5WxY8dSvHhxANq0acPIkSOJjIykaNGiNGnSBJPJxOjRoylQoADvv/9+Opc6Y/nt5vE6nQ5vb2+6detGnjx5OHbsGJGRkURGRpI/f36cnZ1xcXFBr9fzzTff0KtXL+1eJQHRtGG7b1mtVhISErBarWTKlAlfX18SExMJDw8nf/78BAQEaAMMd+/eJU+ePLi7u6dz6TOeP7pGxo0bh8FgICoqikOHDtGyZUvtOihUqBC5cuXSJt2ItJVy9bPFYsFisZA5c2Z8fX1JSkoiPDycefPmERgYqF0fDx48IGfOnGTPnj09i56hpbxvJSYmpqqX58+fc/ToUZo2bconn3xC+fLlAThz5gw5cuTAyckp1TUmz5JXl7I+kpKStD3h2rVrh9lsZtKkSRgMBkaNGsWWLVuYOnUqly9fJikpidKlSxMWFoZSCrPZTJEiRbBareh0OumbpIFz585x4sQJRo0aRb169dDpdLRt25aZM2eyceNG8uXLR9++fenZsyelS5fm559/pnv37nh4eKR30TOM//znPyxZsoT58+fj5eXFL7/8wqRJk7h06RKTJk3CYrFQt25d7OzsUErh5eXF48ePefbsGUOGDCEhIYF9+/Zpe8BJsCdt/La9ZTAY8PDwoGrVqkRHR9O2bVvy5MlDcnIy9vb2lChRgly5cnH79u3ffZY8R9LOX41v6fV6xo8fz8KFC9m5cyc//vgjsbGxNGzYkKFDhwJw8eJF8uXLpwW+5VmSNvR6PR4eHrRo0YKcOXPy+PFjRowYQZcuXahVqxYAefPm5dmzZyxZsoRGjRqRLVs2+f6FSAPy5H9HXLx4kdjYWN577z2tcXHv3j2ePHlCQEAAefPm5f79+zx+/JiPPvqI/fv3k5SURFBQEN7e3sDLRombmxuZMmXi2rVrAHIj/oekPt5eKdMd9u3blytXrgBQp04d/Pz88PLyokWLFrRo0YL169drv9+5cycff/wx1apVA8BoNHL37l0JwL0Gly9f5vnz51pqSZPJhIODAxEREdy8eZO5c+dSu3ZtfH198fDwoHr16ulc4ozFNnCQlJTE6dOnefr0Ke7u7lSsWFFLhzRv3jzef/996tWrh8lk4vTp03h7exMQEMAHH3ygbVIv96y0kfK+FRwczO3bt3ny5Ane3t4MGjSIjh07Ai/TWN2/f59atWphZ2fHsmXLyJs3r6TaS2MpAz5Xrlzh2bNnZM6cmdKlSzNmzBiSkpIIDQ3FycmJWrVq4ejoyKNHj0hKStLSJom0k7I+5s6dy6VLl7h9+zbFixenS5cudOjQAaUU4eHhPHv2jKZNm2JnZ8emTZuAlwMRIu390X3r8ePHFC1alMGDB+Pv74+fnx8ODg6YTCbg5fN/3759eHl5yYzsNJayPkaPHk1MTAyxsbGULl2aPn360KlTJ/R6PRMnTsRsNhMWFkZ4eDgAjx49QqfTcfv2bZYvX86pU6cYNWpUqoFx8WpiYmK4e/cuZcuWRafTaW3foKAgYmJiWLNmDW3btsXLywsvLy9at24tbaw0EhcXh7OzM7Vr1+aLL76gR48e6HQ6atasSdWqVdm4cSOtWrUiIiICeNlntLe3x8vLi5MnT9KvXz9evHjBrl27JACXxv6vPkn//v359ddf6dKlC1FRUeTJkwd4OQ6j1+vJlStXOpc+4/u/xrcOHTqEyWQiODiYZs2a0axZM4xGI/fu3ePHH39k27ZtHD16VFuJJV7d1atXMRqNODs74+3trQU7t23bRs6cORk0aBBWq5WzZ8/i5uZGt27dqFmzJtmyZUvnkguRccjT/x2QnJzMqFGjuHv3LnPnzqVixYoYDAZevHjBuXPntPR569ev58iRIyxdupRmzZoRGBhIlixZqFatGk2bNgXg7NmzPH36lEePHmnL+qWB/7+R+nh72Rry8fHxtG3bFldXV8aOHcupU6f4/PPPSUxMJCgoCE9PTwA6dOgAwMcff0xISAhHjhzRgnAuLi4MGDAAFxeXdDufjOC3sxutVitOTk5YrVYuXbpEsWLFtAE6BwcHGjduzOzZs7l+/TqFChWiZs2agOwBl1ZSphbp3LkzCQkJ3Lx5E3d3d4oVK0ZISAheXl5YLBZ+/fVXbt26xdOnT1myZAnu7u5aAO639SpejcFgICEhgQ4dOpA5c2Zq1aqF0Wjk6NGjdOrUiTlz5tCxY0eUUkyfPp1t27Zp6Q9nzJiBXq+XOkkjKffuGTFiBCdPnuT69eu4urpSsmRJwsLCCA0NRSnF0KFDadSoEblz5+bOnTtcv35dG8QTaSPlYGdgYCA//fQTH374IV5eXpw4cYJdu3aluj6mTJnCxo0bqV27No8ePWLx4sUyUPea/Nl96/vvv6dDhw7MmjWL+vXrc/jwYcaMGUOOHDlITEzE0dGRGTNmyLMkjdnqo127dri4uFC3bl1iY2M5d+4cLVu2ZNmyZdqksokTJ6LX6xk2bBguLi5cunSJmTNn8vjxYzJnzszq1au17B3i1dj+xp2dnbG3t+fkyZPkzp07Vdu3V69e7Nq1i+PHj2t7ikp/MG0cO3aMZcuWERISQq5cuRg1ahTNmzfH3t6e2rVrY7VacXR0ZOvWrakCcfXq1SNbtmzcvXuXHDlySADuNfi/+iQlSpQgODiYwYMHM2/ePJo1a0b79u1JTk7m+PHjuLq6ansli9fHaDT+5fiWm5sbVatWpXnz5ty+fZvZs2dz6tQpPD09WbNmjTbpVryaYcOGcfr0aa5du0aePHm0fnvu3LmJj4/nxo0bPHnyBIAtW7ZgsVioUaOGBOCESGtKvBNu376tWrRooRo0aKCOHj2qkpOTVWJiopo2bZq6fPmy+uabb1Tx4sXVgQMHlFJKHT9+XBUvXlyVKlVKDR06VFmtVqWUUgcPHlT9+/dXFy9eTM/T+deT+nh7XLhwQc2fP1/7OTk5Wc2cOVN16NBB3bt3Tyml1NmzZ9Unn3yiatasqfz9/dWdO3eUUkpZLBaVnJyslFLqs88+UxUrVtSOEa/O9t2aTCZ18+ZN9fjxY6WUUhcvXlSlS5dW48aNUy9evEh1zLJly1STJk3Us2fP3nh53xVJSUmqS5cuqlOnTur48ePq6tWr6ujRo6pEiRKqc+fO6vHjx+rkyZOqQYMGqnjx4qp69erK19dXmUwmpdTL60akHdvzYOXKlcrX11fduHFD+92lS5dUQECAKl26tDp9+rRS6uW9qnjx4mr9+vXa+2zXmkg7EyZMUB999JHatm2bOnr0qIqOjlb169dXjRo1UleuXFFKKTV+/HhVvHhx1aBBA7VgwQJ16dKldC51xhAfH6/WrVun/Wy1WtW+fftUgwYN1E8//aRdM+fOndOuj5MnTyql/nt9TJ8+XSUkJKRL+d8Ff3XfCgwMVKVLl1bnzp1TMTExaunSpWrs2LFq6dKl2v1K7ltpx1Yf69atU40bN1aXL1/Wfrdo0SJVvHhxtXfvXhUbG6uUUmr9+vWqePHiatmyZdr7tm/frn788UdpB78is9n8hz8/fPhQ1apVS/Xo0UNdvXo11XsOHTqkqlevrs6fP//Gyvmu+O6771RoaGiqnwcMGKDatm2rqlatqn788UftXhQfH68aNWqkateurQ4cOKCuXLmipkyZIves18hkMv1hn6R48eKqZ8+e6uHDh+r8+fNqzJgx6qOPPlKtW7dWI0aM0Orit9eb+Of+qH/34sWLvz2+ZXPu3Dl1/fp19fTp0zdV9AxvwoQJqmbNmmr37t3q+++/V1999ZWqXLmyatq0qYqJiVHnz59XDRo0UCVLllQNGjRQlStXVufOnUvvYguRIUkQ7h0SExOjmjRpoho0aKB++OEHpZTSBrBHjRql+vbtq5R62RjZt2+fGjBggDp37tzvHqhxcXFvtuAZlNRH+jObzWro0KGqSpUqKjIyUnvd399fDR48WCUnJ6uEhAQ1ceJENXjwYBUWFqbee+89FRgYqAXibKKjo1X16tXVzZs33/RpZEi2AaEXL16oNm3aqA8//FBVrlxZ7dq1Syml1MaNG1XJkiXV2LFj1dmzZ1VSUpI6ffq0at26tQoMDNSOF2kjZSf17t27qk6dOuqLL77QXtuxY4cqWbKk2rRpkzp+/LhKTExUN2/eVFu2bFHbt2/XjpcBiNdn7NixqmXLlioxMTHV3/+FCxdUkyZNVP/+/ZXJZFLx8fHqq6++krp4je7cuaN8fX3V5s2btbowm83qwoULqlGjRqpdu3bae0ePHq1q1qyp4uPj06u4Gc7UqVNVxYoV1bx587TXlixZoj766CN1//79VO+9fPmyat26tWrfvr2Ki4tT8fHxauvWramCEOL1+av7lp+f3x/eq2Tg9PWYNWuW+uijj7SJTLt371bFixdXq1evVt9//70KDAxUjx8/VsnJyfIceQ2SkpK0fy9ZskQNHz5ctW3bVi1evFjduXNHnTp1SpUtW1b1799fHTlyRCml1M2bN9Xo0aNV06ZNtclqIm2k7HPHxcWpsLAw9dNPPymz2azu3LmjOnfurKpWrap++OGHVIG4Jk2aqFKlSml1pJS0f1+XK1euqPr16/9hn2Tjxo3q+PHj2nf/+PHjVM8OqZO0Y/suk5KS1OXLl9WRI0dUbGysMpvN2nf+v4xvibTz8OFD5evrq1auXKlNiL18+bKqUKGCmjhxorp06ZJKSEhQFy5cUAsXLlSLFi1S169fT+dSC5FxSf6ODE4ppf07d+7cLF26FHt7e4KDg/nxxx+1/Mo6nY779+9z7tw5bt68yZo1a7BarZQoUQK9Xo/FYtE+y8nJKV3OJSOQ+ni7GAwGhg4dSvXq1dmxYwezZs0CwNHREZPJhJ2dHRs2bGDjxo307duX4OBgSpUqxd69e/H19eX8+fPAy30aDh48SHx8PI6Ojul5ShmGTqfDYrEQFBSEvb097dq144MPPmDEiBFs2LCBTz75hJCQED777DN69+5N3bp1CQwMxGKxMHXqVC1NlUgbtjRVmzdv5tmzZzx58kRLp7Nr1y6GDx9OQEAAtWrVYurUqaxfvx5PT09atWpF8+bNMRgM2n4zIm1ZLBYAkpKSSExMJFOmTOh0OpKTkwEoVqwYlSpV4sKFC1oqt3r16mFnZ4fZbE7PomcYv73XxMXFceXKFRwdHbV7kcFgoEiRIvj7+3PmzBl2794NvNynb9OmTfLsSENdu3alVq1a7Ny5U3uu266P7NmzA2jXh7e3N3Xq1OHq1au8ePECR0dHfH19tf13xevxd+9b58+fJyEh4XfHS3rpV5eyT2KrD71ej8lkImvWrOzdu5egoCACAwPp2rUr9+7d49ChQzx48AA7Ozt5jqQRo9HItm3bAHBwcABeps5du3Ytjx49wt3dnYULFzJ48GCePXvGqlWrOHbsGAEBAXz44Yf4+fnx9ddfM3XqVNzd3dPzVDKclNfItWvXiI6OZsWKFZw/f568efMyefJkbb/jkydPYjabtdSUzZo1o3Llytrx0v5NG79tb5lMJu7du4e9vT2Quk9Su3Ztpk+fzsqVKwHIkiWL9uxQSkmdpJGUaUG7dOlCnz596NGjB02aNCE0NJSYmBjg741vibRntVq5efMmAPb29ly/fp0OHTrw0Ucf0atXL+bOncuKFSsoVqwY/fv3p2/fvhQoUCCdSy1ExiVBuAzMbDaj0+m0BqTVaiV37twsW7YMBwcHxo4dy88//wyAj48PDx48oGfPnnTv3p2EhATmzZsHvGykGAwGyS3/iqQ+3j5JSUnkypWLESNGULJkSfbs2cOqVasICAggMDCQ+/fvM2/ePEaOHEmZMmUwmUzodDo++OAD2rZtS5EiRQDImTMn/fr1Y8uWLXh4eKTzWf27pRzMMRgM5M6dm4CAAAYOHMi0adNo164d4eHh7Nq1izZt2rBjxw569OiBr68v/fr1Y/PmzdqgkOwTk7aWL1/O0qVLsVqtODg4cO7cOT7//HOGDh1KYGAgffv2RafTcfv2bYxG4++Ol0HTtGG7RlIODgH4+vpy69YtwsPDAbQBCQBXV1dy5cr1uzqQAYhXZ7FYtHvNlStXOHnyJM+fP8dgMGid3pTv8/HxwWAw8OjRI+DloITsOZZ2TCYTuXLlYty4cZQpU4Yvv/ySFStWULt2bXQ6HRMmTABeXh+2AR8PDw9cXFykXfUavcp9S+5TaS85OVmb7GT7D6B169bEx8fj6+tLUFAQw4cPp2/fvtpxOXLk+N3kP6mffy4hIYE2bdqwd+9erd20fft2Tpw4wcyZM5k/fz4LFy5k1qxZ2NvbM3v2bNzc3Ni+fTtDhgzh448/pkOHDmzatIkSJUqk89lkLGazGYPBQFJSEj/88AMGg4GxY8dy6NAh5s2bx/nz58mfPz8REREUKVKEgQMHsnr1anr27Mm3337L5MmTtQloIm3Y+nZms5lnz55x8+ZNChQogKOjI+fPn//DPsnNmzcxmUxA6nuVPO/Tjm3yRu/evXF0dNSuk44dO2pBUavVSqVKlbh///7/Ob4l0o7JZOLx48dkz56drFmzcu/ePa5cuULbtm2pVq0a4eHhZM2alRs3bnDjxg3tOLk2hHi9pNWcQdlWHMTFxbFgwQJu3LhB9uzZqVKlCp988gnLli2jT58+BAcHExERQcuWLXF1deXGjRvodDq6du2qDWRL5+rVSX28fSwWC5kyZeL58+esXLmSx48fc/PmTWbNmoXRaGTQoEGcO3cOOzs7ateuDcDt27cxm820atWKFi1aaJ9jMBioVKlS+p1MBpHyOpk3bx53797lhx9+oEmTJsDLGcLDhg0DICwsDIvFQqdOnX63YkFWXL0ezZo1Y+nSpZw/f54RI0YwduxYLBYLI0eOpHv37gA8efIEV1dX8uXLl76FzaD+7FlSvXp16tatS7t27dizZw9KKcaOHUt8fDz37t3jm2++oUSJErJyOo3ZVrgBDB8+nFOnTnH9+nUaN25MrVq1mDt3LqVKlaJWrVraMU+fPiVv3rzkyZMnvYqdYdkmCADs3bsXpRQ3b95k3rx5tG/fniZNmvD1118THh5OcHAwBoOBJ0+e8O2335IvXz6cnZ3T+Qwyple9b8kq0bRx//599Ho9OXLkwN7eHqPRSEhICDExMXh7e9OkSRMqVaqEv78/y5cvp3DhwtpAaUxMDGvXrqVw4cJ4enqm96lkGLt27eLOnTssX74cFxcXnj59SkxMDO7u7pQrV057vtSuXRs7OztGjhzJmjVrmDBhAh07dpTB0tck5cqerl27YjQauXnzJi1btmTs2LFaHyQoKIiSJUsybdo0xo0bx8KFC/H29qZmzZraZ0lgIW3YniNGo5GgoCBu3LhBcnIyCxcupF+/fsyYMQOLxcKIESPo0aMH8N8+Sd68edO59BlLymeJzdWrV7l37x4TJkygRo0a2NnZkT9/fhISEmjbti3nzp2jRYsWuLi4aBPUZHzr9ZkyZQonTpzgyZMnTJ8+nT59+hASEsKqVato1qwZoaGhZM6cmYcPH5IpUya8vLyAl8FQea4I8XrJ3S4Dss0ksc2uMxgMuLm5cefOHTZu3MjPP//MmDFjWLp0Kb1792bkyJFERERQr169VJ8jA9lpQ+rj7WSb3dijRw+cnZ1p2rQp/fr1Y+nSpezZsweARo0aYTAYCA8Pp2bNmmzatAm9Xk/Tpk0BmbWVln57ncTGxpItWzaeP3/Ol19+SaFChciRIweZM2dm2LBh6HQ6pkyZQlJSEp07d9YGXkE6vGnhtx0ii8WCl5cX3bp1Y8OGDQwfPpxu3bqxatUqjEYjP/30E8+fP2fJkiW4uLjQrFmzdCx9xvRXzxI/Pz86dOiAXq9nw4YNfPvttzg6OpKUlESmTJkIDQ3VPkc6WGnDtgIuPDycY8eOMXz4cLJnz879+/cpX748cXFxDBgwgHHjxuHj40NCQgJr164lPj6ecuXKpXPpMx5bfQwfPpwffviB1q1bExwczNatW/npp58oWLAgH374Ibt27eLYsWPkypWL+Ph4zp8/T3R0tAThXgO5b70djEYj9evXp0OHDgwcOJAsWbLQvn17dDodOXPm5Ouvv+bXX39l2LBhdOnSBaUU8+bNo1GjRmTKlEkLcM+dO1dLsSvZBl5dzpw5cXBwYMWKFTx8+JBy5crx+PFjHj58qGU9sa3IqlGjBq1atWL9+vUEBgbi6uoq18RrotfrSU5OZvDgwbi6ujJhwgRcXV158uQJ77//Pl5eXvTu3RsHBwf8/PwoU6YMixcv5syZM5QsWVJLrSf9kbRjMBiIj4+nQ4cOeHh40KZNG7JmzYqbmxvNmjXj+fPnLFu2jPj4eH788UdiY2OlT/IapHyW9O7dWwvE3bt3jwcPHuDt7Y2dnR3bt29n5MiR+Pv7U6ZMGcaNG8eQIUNkfOsNCAwM5NSpU9SrV4/MmTMD0KBBA+7evcuyZcsoUKAAMTExvHjxgvXr13P79m1tbEueKUK8fnLHy2BsnVSr1cq+fftwcnJiypQpeHt7c//+ffbs2cP06dPR6/WMHj2aZcuW0a9fP/r06UN0dDSlSpXSPksajq9O6uPtdurUKR4+fMjo0aPx8fEBoHTp0ixYsIB9+/YRHx9P79692bhxI2fOnMHb25tFixZp6UWkTtJGyutk//795MmTh4ULF5ItWzZWrFjBokWLyJ49O+3atcPd3Z3MmTMzdOhQYmNjOXDggDbjUaQdOzs7EhISOH78ODVq1ND+1t9//30+++wznj9/zuDBg3FxcWHlypWsWbMGd3d38ufPz8KFC+UaSWN/51kydepU7VlSv359tm7dSubMmcmXLx89evSQ2aavycOHD/n555/p0qULDRs2TPU7Pz8/zGYz48ePx9XVFScnJwwGA4sWLSJ37tzpVOKM7fLly1pAtHHjxgDUr1+fBQsWcOHCBVxdXZk4cSK7d+/m0aNHeHt7M2HCBNkD7jWQ+9bbw8XFhblz5zJgwAAcHR3JmTMnuXLlYvz48Xh5efHNN9+wcOFCIiIitNXtderUYePGjdjb25MrVy7atm2LwWCQ+khDVapUoW3btmzatEmbtHHnzh22bt3K2rVr/197dx5edXXnD/xzbyAgiqiAG264gdY62o4WtxqrHSt1Oq2tOtVORevug2tnbOPoqHVqa1VC1YoLSt2XOlXb2lpbQcVfLF1EcaOgiAsqCIIaAiH33t8fmtRASHKTe+/3S3i9nuc+hnu/5+SN3ycLeeecE0cccURUV1e3fj/Vt2/f2HDDDWPddddVgpbZa6+9Fq+//nqcffbZrb80s80220Q+n4999tknjjjiiLj33nsjn8/HiSeeGLvvvnt86lOfiojw/W+ZtJydeOmll7Z+D/X000/HU089FQ0NDfHNb34zJk2aFJMmTYrBgwf7N0kZtHwtOe2006J///7xrW99K4YOHRo77bRT9O/fPx555JEYPnx4fO9734uzzjorTjrppPjwww9jxowZMXv27Bg1alSb+dyT0vrDH/7Qup3xZz7zmYj4aEXoE088EX369InDDz88rr322rj99tujf//+0a9fv7jppptaV8IB5ec76F6mZX//o48+Ovr16xeDBw9u/cHCJptsEv/+7/8e+Xw+fvKTn8See+4ZBx10UFxzzTXx05/+NEaMGJFw+t7H/Ui3pUuXxgcffBD9+vWLiI/2zt5oo43ilFNOiZdffjnuv//+OPLII+OOO+6IZcuWxWabbda6F70fQJROy8fJt771rejbt29sttlmrQcCn3nmmZHL5WL8+PEREW2KuEsuuST69OnTetai394qnUKhEJdeemncc889cdBBB8X+++8fhx9+eOy///5x4IEHxuWXXx6jRo2KU089NQ499ND48MMPo1+/fjF8+HAfI2XQ1a8ll112WXz605+OmpqaVbbI9dum5ZHP5+PNN99s8/mn5fy3Dz/8MHK5XFx44YWRzWZj8ODBscsuuzgDroxyuVy89957rV/XV6xYEUOGDInTTjstzjvvvHjooYdi6623jiuvvDIiwoqeMvJ5K11qamri+uuvjxNPPDFGjhwZW2yxResP3vbbb78oFArxs5/9LH784x/HGWecEQcccEDrFuAt3I/S6t+/f7z88suRy+Vio402ivvvvz/OPffc2GOPPeKaa66J/v37x1e/+tXo06dPLF68OGbNmhXDhw9vXR3n+97yWbZsWSxcuHCVc8RWrFgRv/rVr2LOnDlx4YUXxgUXXBDbbLNN7L777q3XKRbKY/78+dGnT5/YYIMNYurUqfHrX/867r///thoo41i0aJFcfTRR8eDDz7Y+j2Af5OUR01NTVx33XVx/PHHR0TEUUcdFUOGDInRo0fHddddF0uWLGn9ZY58Ph8zZ86MoUOHtv7bnvJZvHhx9OvXL3bccceYNWtWTJ48OSZMmBC5XC6WL18ehx9+eNx3333x1ltvxbrrrhvDhw+PIUOGJB0b1ir+1dkLVVVVxcknnxx/+tOfYtasWfHOO++0vta/f/8YPXp0bL/99vHCCy9ERMQWW2wRl112mcODy8T9SK+WbwYfe+yxiPjozLGmpqYYPHhwnHDCCfH+++/HvffeG48++mgMGzYsstls6zkBlFZVVVWcdNJJMW3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      "text/plain": [
       "<Figure size 2160x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot visualisation of the missing values for each feature of the raw DataFrame, df_tm_bio_raw\n",
    "msno.matrix(df_tm_bio_raw, figsize = (30, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day_of_birth             40\n",
       "month_of_birth           40\n",
       "year_of_birth            40\n",
       "pob                     281\n",
       "cob                      39\n",
       "dob                      40\n",
       "position                 39\n",
       "height                  409\n",
       "foot                   1646\n",
       "citizenship            8560\n",
       "second_citizenship    15690\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Counts of missing values\n",
    "tm_bio_null_value_stats = df_tm_bio_raw.isnull().sum(axis=0)\n",
    "tm_bio_null_value_stats[tm_bio_null_value_stats != 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The visualisation shows us very quickly that there a few missing values in most of the columns, but the dataset is ready for us."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Status data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>player_id</th>\n",
       "      <th>current_club</th>\n",
       "      <th>current_club_country</th>\n",
       "      <th>market_value</th>\n",
       "      <th>joined</th>\n",
       "      <th>contract_expires</th>\n",
       "      <th>contract_option</th>\n",
       "      <th>on_loan_from</th>\n",
       "      <th>on_loan_from_country</th>\n",
       "      <th>loan_contract_expiry</th>\n",
       "      <th>player_agent</th>\n",
       "      <th>league_code</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2963</td>\n",
       "      <td>retired</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2017-07-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jorge Cyterszpiler</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5404</td>\n",
       "      <td>retired</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Team Spirit Football Consult.</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5856</td>\n",
       "      <td>retired</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TMP SOCCER srl</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7593</td>\n",
       "      <td>retired</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-07-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AC Talent</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7600</td>\n",
       "      <td>vissel kobe</td>\n",
       "      <td>japan</td>\n",
       "      <td>2300000</td>\n",
       "      <td>2018-07-01</td>\n",
       "      <td>2024-01-31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sports&amp;Life</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   player_id current_club current_club_country  market_value      joined  \\\n",
       "0       2963      retired                  NaN             0  2017-07-01   \n",
       "1       5404      retired                  NaN             0  2020-07-01   \n",
       "2       5856      retired                  NaN             0  2019-07-01   \n",
       "3       7593      retired                  NaN             0  2018-07-01   \n",
       "4       7600  vissel kobe                japan       2300000  2018-07-01   \n",
       "\n",
       "  contract_expires contract_option on_loan_from on_loan_from_country  \\\n",
       "0              NaN             NaN          NaN                  NaN   \n",
       "1              NaN             NaN          NaN                  NaN   \n",
       "2              NaN             NaN          NaN                  NaN   \n",
       "3              NaN             NaN          NaN                  NaN   \n",
       "4       2024-01-31             NaN          NaN                  NaN   \n",
       "\n",
       "  loan_contract_expiry                   player_agent league_code  season  \n",
       "0                  NaN             Jorge Cyterszpiler         ES1    2016  \n",
       "1                  NaN  Team Spirit Football Consult.         ES1    2016  \n",
       "2                  NaN                 TMP SOCCER srl         ES1    2016  \n",
       "3                  NaN                      AC Talent         ES1    2016  \n",
       "4                  NaN                    Sports&Life         ES1    2016  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the first five rows of the raw DataFrame, df_tm_status_raw\n",
    "df_tm_status_raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>player_id</th>\n",
       "      <th>current_club</th>\n",
       "      <th>current_club_country</th>\n",
       "      <th>market_value</th>\n",
       "      <th>joined</th>\n",
       "      <th>contract_expires</th>\n",
       "      <th>contract_option</th>\n",
       "      <th>on_loan_from</th>\n",
       "      <th>on_loan_from_country</th>\n",
       "      <th>loan_contract_expiry</th>\n",
       "      <th>player_agent</th>\n",
       "      <th>league_code</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24327</th>\n",
       "      <td>898751</td>\n",
       "      <td>los angeles fc</td>\n",
       "      <td>united states</td>\n",
       "      <td>50000</td>\n",
       "      <td>2021-06-04</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>club option 2 years</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24328</th>\n",
       "      <td>900440</td>\n",
       "      <td>atlanta united fc</td>\n",
       "      <td>united states</td>\n",
       "      <td>25000</td>\n",
       "      <td>2021-06-04</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>club option 3 years</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24329</th>\n",
       "      <td>900569</td>\n",
       "      <td>san jose earthquakes</td>\n",
       "      <td>united states</td>\n",
       "      <td>25000</td>\n",
       "      <td>2021-01-21</td>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>club option 3 years</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24330</th>\n",
       "      <td>905609</td>\n",
       "      <td>fc cincinnati</td>\n",
       "      <td>united states</td>\n",
       "      <td>25000</td>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>club option 2 years</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Remington Ellis Management</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24331</th>\n",
       "      <td>921655</td>\n",
       "      <td>club de foot montréal</td>\n",
       "      <td>canada</td>\n",
       "      <td>0</td>\n",
       "      <td>2021-08-13</td>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>club option 2 years</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Axia Sports Management</td>\n",
       "      <td>MLS1</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       player_id           current_club current_club_country  market_value  \\\n",
       "24327     898751         los angeles fc        united states         50000   \n",
       "24328     900440      atlanta united fc        united states         25000   \n",
       "24329     900569   san jose earthquakes        united states         25000   \n",
       "24330     905609          fc cincinnati        united states         25000   \n",
       "24331     921655  club de foot montréal               canada             0   \n",
       "\n",
       "           joined contract_expires      contract_option on_loan_from  \\\n",
       "24327  2021-06-04       2022-12-31  club option 2 years          NaN   \n",
       "24328  2021-06-04       2022-12-31  club option 3 years          NaN   \n",
       "24329  2021-01-21       2021-12-31  club option 3 years          NaN   \n",
       "24330  2021-07-02       2023-12-31  club option 2 years          NaN   \n",
       "24331  2021-08-13       2022-12-31  club option 2 years          NaN   \n",
       "\n",
       "      on_loan_from_country loan_contract_expiry                player_agent  \\\n",
       "24327                  NaN                  NaN                         NaN   \n",
       "24328                  NaN                  NaN                         NaN   \n",
       "24329                  NaN                  NaN                         NaN   \n",
       "24330                  NaN                  NaN  Remington Ellis Management   \n",
       "24331                  NaN                  NaN      Axia Sports Management   \n",
       "\n",
       "      league_code  season  \n",
       "24327        MLS1    2020  \n",
       "24328        MLS1    2020  \n",
       "24329        MLS1    2020  \n",
       "24330        MLS1    2020  \n",
       "24331        MLS1    2020  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the last five rows of the raw DataFrame, df_tm_status_raw\n",
    "df_tm_status_raw.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(24332, 13)\n"
     ]
    }
   ],
   "source": [
    "# Print the shape of the raw DataFrame, df_tm_status_raw\n",
    "print(df_tm_status_raw.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['player_id', 'current_club', 'current_club_country', 'market_value',\n",
      "       'joined', 'contract_expires', 'contract_option', 'on_loan_from',\n",
      "       'on_loan_from_country', 'loan_contract_expiry', 'player_agent',\n",
      "       'league_code', 'season'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Print the column names of the raw DataFrame, df_tm_status_raw\n",
    "print(df_tm_status_raw.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset has thirteen features (columns). Full details of these attributes can be found in the [Data Dictionary](section3.3.1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "player_id                int64\n",
       "current_club            object\n",
       "current_club_country    object\n",
       "market_value             int64\n",
       "joined                  object\n",
       "contract_expires        object\n",
       "contract_option         object\n",
       "on_loan_from            object\n",
       "on_loan_from_country    object\n",
       "loan_contract_expiry    object\n",
       "player_agent            object\n",
       "league_code             object\n",
       "season                   int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data types of the features of the raw DataFrame, df_tm_status_raw\n",
    "df_tm_status_raw.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All thirteen of the columns have the object data type. Full details of these attributes and their data types can be found in the [Data Dictionary](section3.3.1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 24332 entries, 0 to 24331\n",
      "Data columns (total 13 columns):\n",
      " #   Column                Non-Null Count  Dtype \n",
      "---  ------                --------------  ----- \n",
      " 0   player_id             24332 non-null  int64 \n",
      " 1   current_club          24332 non-null  object\n",
      " 2   current_club_country  21817 non-null  object\n",
      " 3   market_value          24332 non-null  int64 \n",
      " 4   joined                24324 non-null  object\n",
      " 5   contract_expires      19675 non-null  object\n",
      " 6   contract_option       2085 non-null   object\n",
      " 7   on_loan_from          1851 non-null   object\n",
      " 8   on_loan_from_country  1851 non-null   object\n",
      " 9   loan_contract_expiry  1570 non-null   object\n",
      " 10  player_agent          20805 non-null  object\n",
      " 11  league_code           24332 non-null  object\n",
      " 12  season                24332 non-null  int64 \n",
      "dtypes: int64(3), object(10)\n",
      "memory usage: 2.4+ MB\n"
     ]
    }
   ],
   "source": [
    "# Info for the raw DataFrame, df_tm_status_raw\n",
    "df_tm_status_raw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>player_id</th>\n",
       "      <th>market_value</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24332.000000</td>\n",
       "      <td>2.433200e+04</td>\n",
       "      <td>24332.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>248287.445792</td>\n",
       "      <td>6.062581e+06</td>\n",
       "      <td>2018.352992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>178109.795844</td>\n",
       "      <td>1.235660e+07</td>\n",
       "      <td>1.630859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2016.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>93704.000000</td>\n",
       "      <td>3.250000e+05</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>218129.000000</td>\n",
       "      <td>1.500000e+06</td>\n",
       "      <td>2018.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>358148.500000</td>\n",
       "      <td>5.000000e+06</td>\n",
       "      <td>2020.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>921655.000000</td>\n",
       "      <td>1.600000e+08</td>\n",
       "      <td>2021.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           player_id  market_value        season\n",
       "count   24332.000000  2.433200e+04  24332.000000\n",
       "mean   248287.445792  6.062581e+06   2018.352992\n",
       "std    178109.795844  1.235660e+07      1.630859\n",
       "min        26.000000  0.000000e+00   2016.000000\n",
       "25%     93704.000000  3.250000e+05   2017.000000\n",
       "50%    218129.000000  1.500000e+06   2018.000000\n",
       "75%    358148.500000  5.000000e+06   2020.000000\n",
       "max    921655.000000  1.600000e+08   2021.000000"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Description of the raw DataFrame, df_tm_status_raw, showing some summary statistics for each numberical column in the DataFrame\n",
    "df_tm_status_raw.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot visualisation of the missing values for each feature of the raw DataFrame, df_tm_status_raw\n",
    "msno.matrix(df_tm_status_raw, figsize = (30, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "current_club_country     2515\n",
       "joined                      8\n",
       "contract_expires         4657\n",
       "contract_option         22247\n",
       "on_loan_from            22481\n",
       "on_loan_from_country    22481\n",
       "loan_contract_expiry    22762\n",
       "player_agent             3527\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Counts of missing values\n",
    "tm_status_null_value_stats = df_tm_status_raw.isnull().sum(axis=0)\n",
    "tm_status_null_value_stats[tm_status_null_value_stats != 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The visualisation shows us very quickly that there a few missing values in most of the columns, but the dataset is ready for us."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='#section4'>4. Data Engineering</a>\n",
    "Before we answer the questions in the brief through [Exploratory Data Analysis (EDA)](#section5), we'll first need to clean and wrangle the datasets to a form that meet our needs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a id='#section4.1'>4.1. Bio and Status Datasets</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.1'>4.1.1. Assign Raw DataFrames to New Engineered DataFrames</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assign Raw DataFrames to new Engineered DataFrames\n",
    "df_tm_bio = df_tm_bio_raw.copy()\n",
    "df_tm_status = df_tm_status_raw.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.2'>4.1.2. Dedupe DataFrames</a>\n",
    "A copy of each player is saved per season, causing duplication if not treated."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Bio data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tm_bio = (df_tm_bio\n",
    "                 .sort_values(['season', 'player_id'], ascending=[False, True])\n",
    "                #.drop(columns=['league_code', 'season'])\n",
    "                 .drop_duplicates(subset=['player_id'], keep='first')\n",
    "            )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No. rows in Bio DataFrame BEFORE deduplication: 24211\n",
      "No. rows in DataFrame AFTER deduplication: 9429\n",
      "\n",
      "Variance in rows before and after deduplication: 14782\n",
      "\n",
      "----------\n"
     ]
    }
   ],
   "source": [
    "print('No. rows in Bio DataFrame BEFORE deduplication: {}'.format(len(df_tm_bio_raw)))\n",
    "print('No. rows in DataFrame AFTER deduplication: {}\\n'.format(len(df_tm_bio)))\n",
    "print('Variance in rows before and after deduplication: {}\\n'.format(len(df_tm_bio_raw) - len(df_tm_bio)))\n",
    "print('-'*10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9429"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tm_bio['player_id'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Status data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tm_status = (df_tm_status\n",
    "                    .sort_values(['season', 'player_id'], ascending=[False, True])\n",
    "                    .drop(columns=['league_code', 'season'])\n",
    "                    .drop_duplicates(subset=['player_id'], keep='first')\n",
    "               )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No. rows in Status DataFrame BEFORE deduplication: 24332\n",
      "No. rows in DataFrame AFTER deduplication: 9323\n",
      "\n",
      "Variance in rows before and after deduplication: 15009\n",
      "\n",
      "----------\n"
     ]
    }
   ],
   "source": [
    "print('No. rows in Status DataFrame BEFORE deduplication: {}'.format(len(df_tm_status_raw)))\n",
    "print('No. rows in DataFrame AFTER deduplication: {}\\n'.format(len(df_tm_status)))\n",
    "print('Variance in rows before and after deduplication: {}\\n'.format(len(df_tm_status_raw) - len(df_tm_status)))\n",
    "print('-'*10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9323"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tm_status['player_id'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.2'>4.1.2. Join Bio and Status Datasets</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Join the Bio and Status DataFrames to form one, unified DataFrame\n",
    "df_tm_bio_status = pd.merge(df_tm_bio, df_tm_status, left_on='player_id', right_on='player_id', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No. rows in Bio DataFrame BEFORE join to Status data: 9429\n",
      "No. rows in DataFrame AFTER join: 9429\n",
      "\n",
      "Variance in rows before and after join: 0\n",
      "\n",
      "----------\n"
     ]
    }
   ],
   "source": [
    "print('No. rows in Bio DataFrame BEFORE join to Status data: {}'.format(len(df_tm_bio)))\n",
    "print('No. rows in DataFrame AFTER join: {}\\n'.format(len(df_tm_bio_status)))\n",
    "print('Variance in rows before and after join: {}\\n'.format(len(df_tm_bio_status) - len(df_tm_bio)))\n",
    "print('-'*10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9429, 25)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tm_bio_status.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.3'>4.1.3. String Cleaning</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# \n",
    "df_tm_bio_status['name_lower'] = (df_tm_bio_status['player_name']\n",
    "                                      .str.normalize('NFKD')\n",
    "                                      .str.encode('ascii', errors='ignore')\n",
    "                                      .str.decode('utf-8')\n",
    "                                      .str.lower()\n",
    "                                 )\n",
    "\n",
    "# First Name Lower\n",
    "df_tm_bio_status['firstname_lower'] = df_tm_bio_status['name_lower'].str.rsplit(' ', 0).str[0]\n",
    "\n",
    "# Last Name Lower\n",
    "df_tm_bio_status['lastname_lower'] = df_tm_bio_status['name_lower'].str.rsplit(' ', 1).str[-1]\n",
    "\n",
    "# First Initial Lower\n",
    "df_tm_bio_status['firstinitial_lower'] = df_tm_bio_status['name_lower'].astype(str).str[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### League Country lower"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove accents and create lowercase name\n",
    "df_tm_bio_status['league_country_lower'] = (df_tm_bio_status['current_club_country']\n",
    "                                                .str.normalize('NFKD')\n",
    "                                                .str.encode('ascii', errors='ignore')\n",
    "                                                .str.decode('utf-8')\n",
    "                                                .str.lower()\n",
    "                                           )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.4'>4.1.4. Converting Data Types</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Date Time\n",
    "First we need to convert the `dob` column from the `object` data type to `datetime64[ns]`, again using the [.to_datetime()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_datetime.html) method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Convert birth_date from string to datetime64[ns]\n",
    "df_tm_bio_status['dob'] = pd.to_datetime(df_tm_bio_status['dob'])\n",
    "df_tm_bio_status['joined'] = pd.to_datetime(df_tm_bio_status['joined'])\n",
    "df_tm_bio_status['contract_expires'] = pd.to_datetime(df_tm_bio_status['contract_expires'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Numeric\n",
    "The `value` column needs to be converted from a string to an integer using to [to_numeric()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_numeric.html) method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert string to integer\n",
    "df_tm_bio_status['market_value'] = pd.to_numeric(df_tm_bio_status['market_value'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.5'>4.1.5. Create New Attributes</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Position Codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Goalkeeper', 'midfield - Central Midfield',\n",
       "       'attack - Centre-Forward', 'midfield - Defensive Midfield',\n",
       "       'attack - Right Winger', 'attack - Second Striker',\n",
       "       'Defender - Left-Back', 'Defender - Centre-Back',\n",
       "       'Defender - Right-Back', 'midfield - Attacking Midfield',\n",
       "       'midfield - Right Midfield', 'attack - Left Winger',\n",
       "       'midfield - Left Midfield', nan, 'midfield', 'attack', 'Defender'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tm_bio_status['position'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_positions_codes = {'Goalkeeper': 'GK',\n",
    "                        'Defender': 'DEF',\n",
    "                        'Defender - Centre-Back': 'CB',\n",
    "                        'Defender - Left-Back': 'LB',\n",
    "                        'Defender - Right-Back': 'RB',\n",
    "                        'midfield': 'MF',\n",
    "                        'midfield - Central Midfield': 'CM',\n",
    "                        'midfield - Defensive Midfield': 'CDM',\n",
    "                        'midfield - Left Midfield': 'LM',\n",
    "                        'midfield - Right Midfield': 'RM',\n",
    "                        'midfield - Attacking Midfield': 'CAM',\n",
    "                        'attack': 'FW',\n",
    "                        'attack - Left Winger': 'LW',\n",
    "                        'attack - Right Winger': 'RW',\n",
    "                        'attack - Second Striker': 'SS',\n",
    "                        'attack - Centre-Forward': 'ST'\n",
    "                       }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map grouped positions to DataFrame\n",
    "df_tm_bio_status['position_code'] = df_tm_bio_status['position'].map(dict_positions_codes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Position Grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_positions_grouped = {'Goalkeeper': 'Goalkeeper',\n",
    "                          'Defender': 'Defender',\n",
    "                          'Defender - Centre-Back': 'Defender',\n",
    "                          'Defender - Left-Back': 'Defender',\n",
    "                          'Defender - Right-Back': 'Defender',\n",
    "                          'midfield': 'Midfielder',\n",
    "                          'midfield - Central Midfield': 'Midfielder',\n",
    "                          'midfield - Defensive Midfield': 'Midfielder',\n",
    "                          'midfield - Left Midfield': 'Midfielder',\n",
    "                          'midfield - Right Midfield': 'Midfielder',\n",
    "                          'midfield - Attacking Midfield': 'Midfielder',\n",
    "                          'attack': 'Forward',\n",
    "                          'attack - Left Winger': 'Forward',\n",
    "                          'attack - Right Winger': 'Forward',\n",
    "                          'attack - Second Striker': 'Forward',\n",
    "                          'attack - Centre-Forward': 'Forward'\n",
    "                         }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map grouped positions to DataFrame\n",
    "df_tm_bio_status['position_grouped'] = df_tm_bio_status['position'].map(dict_positions_grouped)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Goalkeeper / Outfielder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separate Goalkeeper and Outfielders\n",
    "df_tm_bio_status['outfielder_goalkeeper'] = np.where(df_tm_bio_status['position'].isnull(), np.nan, (np.where(df_tm_bio_status['position'] == 'Goalkeeper', 'Goalkeeper', 'Outfielder')))                                                 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Current Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "now = pd.Timestamp('now')\n",
    "df_tm_bio_status['dob'] = pd.to_datetime(df_tm_bio_status['dob'], format='%m%d%y')\n",
    "df_tm_bio_status['dob'] = df_tm_bio_status['dob'].where(df_tm_bio_status['dob'] < now, df_tm_bio_status['dob'] -  np.timedelta64(100, 'Y'))\n",
    "df_tm_bio_status['age'] = (now - df_tm_bio_status['dob']).astype('<m8[Y]')\n",
    "df_tm_bio_status['age'] = df_tm_bio_status['age'].astype(np.int64, errors='ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Age When Joining Club"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tm_bio_status['age_when_joining'] = (df_tm_bio_status['joined'] - df_tm_bio_status['dob']) / timedelta(days=365)\n",
    "df_tm_bio_status['age_when_joining'] = np.floor(df_tm_bio_status['age_when_joining'])      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Time Since Joining Club"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "now = pd.Timestamp('now')\n",
    "df_tm_bio_status['joined'] = pd.to_datetime(df_tm_bio_status['joined'], format='%m%d%y')\n",
    "df_tm_bio_status['joined'] = df_tm_bio_status['joined'].where(df_tm_bio_status['joined'] < now, df_tm_bio_status['joined'] -  np.timedelta64(100, 'Y'))\n",
    "df_tm_bio_status['years_since_joining'] = (now - df_tm_bio_status['joined']).astype('<m8[Y]')\n",
    "df_tm_bio_status['years_since_joining'] = df_tm_bio_status['years_since_joining'].astype(np.int64, errors='ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Time Until Contract Expiry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "now = pd.Timestamp('now')\n",
    "df_tm_bio_status['contract_expires'] = pd.to_datetime(df_tm_bio_status['contract_expires'], format='%m%d%y')\n",
    "#df_tm_bio_status['contract_expires'] = df_tm_bio_status['contract_expires'].where(df_tm_bio_status['contract_expires'] < now, df_tm_bio_status['contract_expires'] - np.timedelta64(100, 'Y'))\n",
    "df_tm_bio_status['years_until_contract_expiry'] = (df_tm_bio_status['contract_expires'] - now).astype('<m8[Y]')\n",
    "df_tm_bio_status['years_until_contract_expiry'] = df_tm_bio_status['years_until_contract_expiry'].astype(np.int64, errors='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>player_id</th>\n",
       "      <th>player_name</th>\n",
       "      <th>day_of_birth</th>\n",
       "      <th>month_of_birth</th>\n",
       "      <th>year_of_birth</th>\n",
       "      <th>pob</th>\n",
       "      <th>cob</th>\n",
       "      <th>dob</th>\n",
       "      <th>position</th>\n",
       "      <th>height</th>\n",
       "      <th>foot</th>\n",
       "      <th>citizenship</th>\n",
       "      <th>second_citizenship</th>\n",
       "      <th>league_code</th>\n",
       "      <th>season</th>\n",
       "      <th>current_club</th>\n",
       "      <th>current_club_country</th>\n",
       "      <th>market_value</th>\n",
       "      <th>joined</th>\n",
       "      <th>contract_expires</th>\n",
       "      <th>contract_option</th>\n",
       "      <th>on_loan_from</th>\n",
       "      <th>on_loan_from_country</th>\n",
       "      <th>loan_contract_expiry</th>\n",
       "      <th>player_agent</th>\n",
       "      <th>name_lower</th>\n",
       "      <th>firstname_lower</th>\n",
       "      <th>lastname_lower</th>\n",
       "      <th>firstinitial_lower</th>\n",
       "      <th>league_country_lower</th>\n",
       "      <th>position_code</th>\n",
       "      <th>position_grouped</th>\n",
       "      <th>outfielder_goalkeeper</th>\n",
       "      <th>age</th>\n",
       "      <th>age_when_joining</th>\n",
       "      <th>years_since_joining</th>\n",
       "      <th>years_until_contract_expiry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2857</td>\n",
       "      <td>eldin jakupovic</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Kozarac</td>\n",
       "      <td>Jugoslawien (SFR)</td>\n",
       "      <td>1984-10-02</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>191.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bosnia-Herzegovina</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>leicester city</td>\n",
       "      <td>england</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2017-07-19</td>\n",
       "      <td>2021-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HSD</td>\n",
       "      <td>eldin jakupovic</td>\n",
       "      <td>eldin</td>\n",
       "      <td>jakupovic</td>\n",
       "      <td>e</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>36.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3333</td>\n",
       "      <td>james milner</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Leeds</td>\n",
       "      <td>England</td>\n",
       "      <td>1986-01-04</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>175.0</td>\n",
       "      <td>right</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>liverpool fc</td>\n",
       "      <td>england</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>2015-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Samii Sport-Marketing Agentur</td>\n",
       "      <td>james milner</td>\n",
       "      <td>james</td>\n",
       "      <td>milner</td>\n",
       "      <td>j</td>\n",
       "      <td>england</td>\n",
       "      <td>CM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>35.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3455</td>\n",
       "      <td>zlatan ibrahimovic</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>Malmö</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>1981-10-03</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>195.0</td>\n",
       "      <td>both</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bosnia-Herzegovina</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>ac milan</td>\n",
       "      <td>italy</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mino Raiola</td>\n",
       "      <td>zlatan ibrahimovic</td>\n",
       "      <td>zlatan</td>\n",
       "      <td>ibrahimovic</td>\n",
       "      <td>z</td>\n",
       "      <td>italy</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>39.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5578</td>\n",
       "      <td>nicolas penneteau</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>Marseille</td>\n",
       "      <td>France</td>\n",
       "      <td>1981-02-28</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>185.0</td>\n",
       "      <td>left</td>\n",
       "      <td>France</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>stade reims</td>\n",
       "      <td>france</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USM GROUP</td>\n",
       "      <td>nicolas penneteau</td>\n",
       "      <td>nicolas</td>\n",
       "      <td>penneteau</td>\n",
       "      <td>n</td>\n",
       "      <td>france</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6442</td>\n",
       "      <td>antonio rosati</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Tivoli</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1983-06-26</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>195.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>acf fiorentina</td>\n",
       "      <td>italy</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>2021-02-01</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alessandro Lucci - WSA</td>\n",
       "      <td>antonio rosati</td>\n",
       "      <td>antonio</td>\n",
       "      <td>rosati</td>\n",
       "      <td>a</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>38.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7093</td>\n",
       "      <td>francesco magnanelli</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Umbertide</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1984-11-12</td>\n",
       "      <td>midfield - Defensive Midfield</td>\n",
       "      <td>181.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>us sassuolo</td>\n",
       "      <td>italy</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>2005-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TMP SOCCER srl</td>\n",
       "      <td>francesco magnanelli</td>\n",
       "      <td>francesco</td>\n",
       "      <td>magnanelli</td>\n",
       "      <td>f</td>\n",
       "      <td>italy</td>\n",
       "      <td>CDM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7161</td>\n",
       "      <td>jonas hofmann</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Heidelberg</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1992-07-14</td>\n",
       "      <td>attack - Right Winger</td>\n",
       "      <td>176.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Germany</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L1</td>\n",
       "      <td>2021</td>\n",
       "      <td>borussia mönchengladbach</td>\n",
       "      <td>germany</td>\n",
       "      <td>16000000.0</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dr. Gutfleisch</td>\n",
       "      <td>jonas hofmann</td>\n",
       "      <td>jonas</td>\n",
       "      <td>hofmann</td>\n",
       "      <td>j</td>\n",
       "      <td>germany</td>\n",
       "      <td>RW</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>29.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7663</td>\n",
       "      <td>joaquín</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>El Puerto de Santa María</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1981-07-21</td>\n",
       "      <td>attack - Right Winger</td>\n",
       "      <td>181.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>real betis balompié</td>\n",
       "      <td>spain</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>2015-08-31</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Juzzt Football</td>\n",
       "      <td>joaquin</td>\n",
       "      <td>joaquin</td>\n",
       "      <td>joaquin</td>\n",
       "      <td>j</td>\n",
       "      <td>spain</td>\n",
       "      <td>RW</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>40.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7825</td>\n",
       "      <td>pepe reina</td>\n",
       "      <td>31.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1982-08-31</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>ss lazio</td>\n",
       "      <td>italy</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>2020-09-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Manuel García Quilón</td>\n",
       "      <td>pepe reina</td>\n",
       "      <td>pepe</td>\n",
       "      <td>reina</td>\n",
       "      <td>p</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>39.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8176</td>\n",
       "      <td>oier olazábal</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Irún</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1989-09-14</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>189.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>rcd espanyol barcelona</td>\n",
       "      <td>spain</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sport Agency 4U</td>\n",
       "      <td>oier olazabal</td>\n",
       "      <td>oier</td>\n",
       "      <td>olazabal</td>\n",
       "      <td>o</td>\n",
       "      <td>spain</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>31.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8198</td>\n",
       "      <td>cristiano ronaldo</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Funchal</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>1985-02-05</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>187.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>juventus fc</td>\n",
       "      <td>italy</td>\n",
       "      <td>45000000.0</td>\n",
       "      <td>2018-07-10</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gestifute</td>\n",
       "      <td>cristiano ronaldo</td>\n",
       "      <td>cristiano</td>\n",
       "      <td>ronaldo</td>\n",
       "      <td>c</td>\n",
       "      <td>italy</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>8246</td>\n",
       "      <td>philipp pentke</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Freiberg</td>\n",
       "      <td>DDR</td>\n",
       "      <td>1985-05-01</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>191.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Germany</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L1</td>\n",
       "      <td>2021</td>\n",
       "      <td>tsg 1899 hoffenheim</td>\n",
       "      <td>germany</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bigpoint</td>\n",
       "      <td>philipp pentke</td>\n",
       "      <td>philipp</td>\n",
       "      <td>pentke</td>\n",
       "      <td>p</td>\n",
       "      <td>germany</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>36.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>8806</td>\n",
       "      <td>cesc fàbregas</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Arenys de Mar</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1987-05-04</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>178.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>as monaco</td>\n",
       "      <td>monaco</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>2019-01-11</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Darren Dein</td>\n",
       "      <td>cesc fabregas</td>\n",
       "      <td>cesc</td>\n",
       "      <td>fabregas</td>\n",
       "      <td>c</td>\n",
       "      <td>monaco</td>\n",
       "      <td>CM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>34.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12359</td>\n",
       "      <td>niki mäenpää</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Espoo</td>\n",
       "      <td>Finland</td>\n",
       "      <td>1985-01-23</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>191.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Finland</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>venezia fc</td>\n",
       "      <td>italy</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>2021-02-15</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICM Stellar Sports</td>\n",
       "      <td>niki maenpaa</td>\n",
       "      <td>niki</td>\n",
       "      <td>maenpaa</td>\n",
       "      <td>n</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>36.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>12563</td>\n",
       "      <td>goran pandev</td>\n",
       "      <td>27.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Strumica</td>\n",
       "      <td>Jugoslawien (SFR)</td>\n",
       "      <td>1983-07-27</td>\n",
       "      <td>attack - Second Striker</td>\n",
       "      <td>184.0</td>\n",
       "      <td>left</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Italy</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>genoa cfc</td>\n",
       "      <td>italy</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>2015-07-07</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Carlo Pallavicino</td>\n",
       "      <td>goran pandev</td>\n",
       "      <td>goran</td>\n",
       "      <td>pandev</td>\n",
       "      <td>g</td>\n",
       "      <td>italy</td>\n",
       "      <td>SS</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>38.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>12907</td>\n",
       "      <td>alessio cragno</td>\n",
       "      <td>28.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Fiesole</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1994-06-28</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>184.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>cagliari calcio</td>\n",
       "      <td>italy</td>\n",
       "      <td>20000000.0</td>\n",
       "      <td>2014-07-12</td>\n",
       "      <td>2024-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Promoesport</td>\n",
       "      <td>alessio cragno</td>\n",
       "      <td>alessio</td>\n",
       "      <td>cragno</td>\n",
       "      <td>a</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>27.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>13460</td>\n",
       "      <td>lee grant</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Hemel Hempstead</td>\n",
       "      <td>England</td>\n",
       "      <td>1983-01-27</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>193.0</td>\n",
       "      <td>right</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>manchester united</td>\n",
       "      <td>england</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>2018-07-03</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>lee grant</td>\n",
       "      <td>lee</td>\n",
       "      <td>grant</td>\n",
       "      <td>l</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>38.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>13572</td>\n",
       "      <td>ben foster</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Leamington Spa</td>\n",
       "      <td>England</td>\n",
       "      <td>1983-04-03</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>193.0</td>\n",
       "      <td>left</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>watford fc</td>\n",
       "      <td>england</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2018-07-05</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ben foster</td>\n",
       "      <td>ben</td>\n",
       "      <td>foster</td>\n",
       "      <td>b</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>38.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>14044</td>\n",
       "      <td>andy lonergan</td>\n",
       "      <td>19.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Preston</td>\n",
       "      <td>England</td>\n",
       "      <td>1983-10-19</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>193.0</td>\n",
       "      <td>left</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>everton fc</td>\n",
       "      <td>england</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>2021-08-20</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UK Sport Management BV</td>\n",
       "      <td>andy lonergan</td>\n",
       "      <td>andy</td>\n",
       "      <td>lonergan</td>\n",
       "      <td>a</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>14086</td>\n",
       "      <td>ashley young</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Stevenage</td>\n",
       "      <td>England</td>\n",
       "      <td>1985-07-09</td>\n",
       "      <td>Defender - Left-Back</td>\n",
       "      <td>175.0</td>\n",
       "      <td>both</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jamaica</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>aston villa</td>\n",
       "      <td>england</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CAA Base Ltd</td>\n",
       "      <td>ashley young</td>\n",
       "      <td>ashley</td>\n",
       "      <td>young</td>\n",
       "      <td>a</td>\n",
       "      <td>england</td>\n",
       "      <td>LB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>14555</td>\n",
       "      <td>scott carson</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Whitehaven</td>\n",
       "      <td>England</td>\n",
       "      <td>1985-09-03</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>right</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>manchester city</td>\n",
       "      <td>england</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2021-07-20</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Wasserman</td>\n",
       "      <td>scott carson</td>\n",
       "      <td>scott</td>\n",
       "      <td>carson</td>\n",
       "      <td>s</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>35.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>15452</td>\n",
       "      <td>raúl albiol</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Vilamarxant</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1985-09-04</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>190.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>villarreal cf</td>\n",
       "      <td>spain</td>\n",
       "      <td>2500000.0</td>\n",
       "      <td>2019-07-04</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Football Capital</td>\n",
       "      <td>raul albiol</td>\n",
       "      <td>raul</td>\n",
       "      <td>albiol</td>\n",
       "      <td>r</td>\n",
       "      <td>spain</td>\n",
       "      <td>CB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>35.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>15773</td>\n",
       "      <td>phil bardsley</td>\n",
       "      <td>28.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Salford</td>\n",
       "      <td>England</td>\n",
       "      <td>1985-06-28</td>\n",
       "      <td>Defender - Right-Back</td>\n",
       "      <td>180.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>England</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>burnley fc</td>\n",
       "      <td>england</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2017-07-25</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>phil bardsley</td>\n",
       "      <td>phil</td>\n",
       "      <td>bardsley</td>\n",
       "      <td>p</td>\n",
       "      <td>england</td>\n",
       "      <td>RB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>15930</td>\n",
       "      <td>david martin</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>London</td>\n",
       "      <td>England</td>\n",
       "      <td>1986-01-22</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>right</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>west ham united</td>\n",
       "      <td>england</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Momentum Sports Management</td>\n",
       "      <td>david martin</td>\n",
       "      <td>david</td>\n",
       "      <td>martin</td>\n",
       "      <td>d</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>35.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>15956</td>\n",
       "      <td>jesús navas</td>\n",
       "      <td>21.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Los Palacios y Villafranca</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1985-11-21</td>\n",
       "      <td>Defender - Right-Back</td>\n",
       "      <td>172.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>sevilla fc</td>\n",
       "      <td>spain</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>2017-08-01</td>\n",
       "      <td>2024-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bahía Internacional</td>\n",
       "      <td>jesus navas</td>\n",
       "      <td>jesus</td>\n",
       "      <td>navas</td>\n",
       "      <td>j</td>\n",
       "      <td>spain</td>\n",
       "      <td>RB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>35.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>16136</td>\n",
       "      <td>dante</td>\n",
       "      <td>18.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Salvador da Bahia</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>1983-10-18</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>189.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>ogc nice</td>\n",
       "      <td>france</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2016-08-23</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marcus Marin</td>\n",
       "      <td>dante</td>\n",
       "      <td>dante</td>\n",
       "      <td>dante</td>\n",
       "      <td>d</td>\n",
       "      <td>france</td>\n",
       "      <td>CB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>37.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>16306</td>\n",
       "      <td>casemiro</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>São José dos Campos</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>1992-02-23</td>\n",
       "      <td>midfield - Defensive Midfield</td>\n",
       "      <td>185.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Spain</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>real madrid</td>\n",
       "      <td>spain</td>\n",
       "      <td>70000000.0</td>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>2025-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Best of You</td>\n",
       "      <td>casemiro</td>\n",
       "      <td>casemiro</td>\n",
       "      <td>casemiro</td>\n",
       "      <td>c</td>\n",
       "      <td>spain</td>\n",
       "      <td>CDM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>29.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>16408</td>\n",
       "      <td>orestis karnezis</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Athen</td>\n",
       "      <td>Greece</td>\n",
       "      <td>1985-07-11</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>190.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Greece</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>losc lille</td>\n",
       "      <td>france</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>2020-09-04</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>orestis karnezis</td>\n",
       "      <td>orestis</td>\n",
       "      <td>karnezis</td>\n",
       "      <td>o</td>\n",
       "      <td>france</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>36.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>16633</td>\n",
       "      <td>alex cordaz</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Vittorio Veneto</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1983-01-01</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>inter milan</td>\n",
       "      <td>italy</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>QUAN SPORTS MANAGEMENT ITALIA</td>\n",
       "      <td>alex cordaz</td>\n",
       "      <td>alex</td>\n",
       "      <td>cordaz</td>\n",
       "      <td>a</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>38.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>16911</td>\n",
       "      <td>kasper schmeichel</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Kopenhagen</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>1986-11-05</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>189.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>leicester city</td>\n",
       "      <td>england</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>2011-07-01</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P&amp;P Sport Management S.A.M.</td>\n",
       "      <td>kasper schmeichel</td>\n",
       "      <td>kasper</td>\n",
       "      <td>schmeichel</td>\n",
       "      <td>k</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>34.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>16922</td>\n",
       "      <td>kevin-prince boateng</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Berlin</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1987-03-06</td>\n",
       "      <td>midfield - Attacking Midfield</td>\n",
       "      <td>186.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Germany</td>\n",
       "      <td>L1</td>\n",
       "      <td>2021</td>\n",
       "      <td>hertha bsc</td>\n",
       "      <td>germany</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Excellence Sport</td>\n",
       "      <td>kevin-prince boateng</td>\n",
       "      <td>kevin-prince</td>\n",
       "      <td>boateng</td>\n",
       "      <td>k</td>\n",
       "      <td>germany</td>\n",
       "      <td>CAM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>34.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>17259</td>\n",
       "      <td>manuel neuer</td>\n",
       "      <td>27.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Gelsenkirchen</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1986-03-27</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>193.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Germany</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L1</td>\n",
       "      <td>2021</td>\n",
       "      <td>bayern munich</td>\n",
       "      <td>germany</td>\n",
       "      <td>18000000.0</td>\n",
       "      <td>2011-07-01</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PRO Profil GmbH</td>\n",
       "      <td>manuel neuer</td>\n",
       "      <td>manuel</td>\n",
       "      <td>neuer</td>\n",
       "      <td>m</td>\n",
       "      <td>germany</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>35.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>17965</td>\n",
       "      <td>hugo lloris</td>\n",
       "      <td>26.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Nizza</td>\n",
       "      <td>France</td>\n",
       "      <td>1986-12-26</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>left</td>\n",
       "      <td>France</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>tottenham hotspur</td>\n",
       "      <td>england</td>\n",
       "      <td>9000000.0</td>\n",
       "      <td>2012-08-31</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hugo lloris</td>\n",
       "      <td>hugo</td>\n",
       "      <td>lloris</td>\n",
       "      <td>h</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>34.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>18644</td>\n",
       "      <td>álvaro negredo</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1985-08-20</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>186.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>cádiz cf</td>\n",
       "      <td>spain</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>2020-08-04</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Niagara Sports Company</td>\n",
       "      <td>alvaro negredo</td>\n",
       "      <td>alvaro</td>\n",
       "      <td>negredo</td>\n",
       "      <td>a</td>\n",
       "      <td>spain</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>18909</td>\n",
       "      <td>jimmy briand</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Vitry-sur-Seine</td>\n",
       "      <td>France</td>\n",
       "      <td>1985-08-02</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>183.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Martinique</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>fc girondins bordeaux</td>\n",
       "      <td>france</td>\n",
       "      <td>1100000.0</td>\n",
       "      <td>2018-08-10</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TTMA</td>\n",
       "      <td>jimmy briand</td>\n",
       "      <td>jimmy</td>\n",
       "      <td>briand</td>\n",
       "      <td>j</td>\n",
       "      <td>france</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>18922</td>\n",
       "      <td>karim benzema</td>\n",
       "      <td>19.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Lyon</td>\n",
       "      <td>France</td>\n",
       "      <td>1987-12-19</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>184.0</td>\n",
       "      <td>both</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>real madrid</td>\n",
       "      <td>spain</td>\n",
       "      <td>25000000.0</td>\n",
       "      <td>2009-07-09</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>karim benzema</td>\n",
       "      <td>karim</td>\n",
       "      <td>benzema</td>\n",
       "      <td>k</td>\n",
       "      <td>spain</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>33.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>18934</td>\n",
       "      <td>thomas mangani</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Carpentras</td>\n",
       "      <td>France</td>\n",
       "      <td>1987-04-29</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>183.0</td>\n",
       "      <td>left</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Italy</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>sco angers</td>\n",
       "      <td>france</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2015-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kemari</td>\n",
       "      <td>thomas mangani</td>\n",
       "      <td>thomas</td>\n",
       "      <td>mangani</td>\n",
       "      <td>t</td>\n",
       "      <td>france</td>\n",
       "      <td>CM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>34.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>18944</td>\n",
       "      <td>gerard piqué</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Barcelona</td>\n",
       "      <td>Spain</td>\n",
       "      <td>1987-02-02</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>194.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Spain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>fc barcelona</td>\n",
       "      <td>spain</td>\n",
       "      <td>10000000.0</td>\n",
       "      <td>2008-07-01</td>\n",
       "      <td>2024-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AC Talent</td>\n",
       "      <td>gerard pique</td>\n",
       "      <td>gerard</td>\n",
       "      <td>pique</td>\n",
       "      <td>g</td>\n",
       "      <td>spain</td>\n",
       "      <td>CB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>34.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>20005</td>\n",
       "      <td>papu gómez</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>1988-02-15</td>\n",
       "      <td>attack - Second Striker</td>\n",
       "      <td>167.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Italy</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>sevilla fc</td>\n",
       "      <td>spain</td>\n",
       "      <td>9000000.0</td>\n",
       "      <td>2021-01-26</td>\n",
       "      <td>2024-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gr Sports</td>\n",
       "      <td>papu gomez</td>\n",
       "      <td>papu</td>\n",
       "      <td>gomez</td>\n",
       "      <td>p</td>\n",
       "      <td>spain</td>\n",
       "      <td>SS</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>33.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>20463</td>\n",
       "      <td>corentin jean</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Blois</td>\n",
       "      <td>France</td>\n",
       "      <td>1995-07-15</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>170.0</td>\n",
       "      <td>right</td>\n",
       "      <td>France</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>rc lens</td>\n",
       "      <td>france</td>\n",
       "      <td>1600000.0</td>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>firsteleven ISM</td>\n",
       "      <td>corentin jean</td>\n",
       "      <td>corentin</td>\n",
       "      <td>jean</td>\n",
       "      <td>c</td>\n",
       "      <td>france</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>26.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>20506</td>\n",
       "      <td>andrés guardado</td>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Guadalajara</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1986-09-28</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>169.0</td>\n",
       "      <td>left</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Spain</td>\n",
       "      <td>ES1</td>\n",
       "      <td>2021</td>\n",
       "      <td>real betis balompié</td>\n",
       "      <td>spain</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>2017-07-07</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>andres guardado</td>\n",
       "      <td>andres</td>\n",
       "      <td>guardado</td>\n",
       "      <td>a</td>\n",
       "      <td>spain</td>\n",
       "      <td>CM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>34.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>21726</td>\n",
       "      <td>philipp tschauner</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Schwabach</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1985-11-03</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>196.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Germany</td>\n",
       "      <td>NaN</td>\n",
       "      <td>L1</td>\n",
       "      <td>2021</td>\n",
       "      <td>rb leipzig</td>\n",
       "      <td>germany</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2019-07-30</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>philipp tschauner</td>\n",
       "      <td>philipp</td>\n",
       "      <td>tschauner</td>\n",
       "      <td>p</td>\n",
       "      <td>germany</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>35.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>21763</td>\n",
       "      <td>federico peluso</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Roma</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1984-01-20</td>\n",
       "      <td>Defender - Centre-Back</td>\n",
       "      <td>188.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>us sassuolo</td>\n",
       "      <td>italy</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>2014-07-03</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PLAYER MANAGEMENT SRL</td>\n",
       "      <td>federico peluso</td>\n",
       "      <td>federico</td>\n",
       "      <td>peluso</td>\n",
       "      <td>f</td>\n",
       "      <td>italy</td>\n",
       "      <td>CB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>37.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>21872</td>\n",
       "      <td>gianluca pegolo</td>\n",
       "      <td>25.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>Bassano del Grappa</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1981-03-25</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>183.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>us sassuolo</td>\n",
       "      <td>italy</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>2013-09-02</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P&amp;P Sport Management S.A.M.</td>\n",
       "      <td>gianluca pegolo</td>\n",
       "      <td>gianluca</td>\n",
       "      <td>pegolo</td>\n",
       "      <td>g</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>40.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>21905</td>\n",
       "      <td>valon behrami</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Mitrovicë</td>\n",
       "      <td>Jugoslawien (SFR)</td>\n",
       "      <td>1985-04-19</td>\n",
       "      <td>midfield - Defensive Midfield</td>\n",
       "      <td>184.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kosovo</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>genoa cfc</td>\n",
       "      <td>italy</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>QUAN SPORTS MANAGEMENT ITALIA</td>\n",
       "      <td>valon behrami</td>\n",
       "      <td>valon</td>\n",
       "      <td>behrami</td>\n",
       "      <td>v</td>\n",
       "      <td>italy</td>\n",
       "      <td>CDM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>36.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>21972</td>\n",
       "      <td>cristian molinaro</td>\n",
       "      <td>30.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Vallo della Lucania</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1983-07-30</td>\n",
       "      <td>Defender - Left-Back</td>\n",
       "      <td>182.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>venezia fc</td>\n",
       "      <td>italy</td>\n",
       "      <td>75000.0</td>\n",
       "      <td>2020-01-15</td>\n",
       "      <td>2024-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no agent</td>\n",
       "      <td>cristian molinaro</td>\n",
       "      <td>cristian</td>\n",
       "      <td>molinaro</td>\n",
       "      <td>c</td>\n",
       "      <td>italy</td>\n",
       "      <td>LB</td>\n",
       "      <td>Defender</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>38.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>22318</td>\n",
       "      <td>federico marchetti</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Bassano del Grappa</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1983-02-07</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>left</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>genoa cfc</td>\n",
       "      <td>italy</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>2018-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AGB Sport Management</td>\n",
       "      <td>federico marchetti</td>\n",
       "      <td>federico</td>\n",
       "      <td>marchetti</td>\n",
       "      <td>f</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>38.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>22328</td>\n",
       "      <td>fabio quagliarella</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Castellammare di Stabia</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1983-01-31</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>180.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>uc sampdoria</td>\n",
       "      <td>italy</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2016-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AGB Sport Management</td>\n",
       "      <td>fabio quagliarella</td>\n",
       "      <td>fabio</td>\n",
       "      <td>quagliarella</td>\n",
       "      <td>f</td>\n",
       "      <td>italy</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>38.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>22628</td>\n",
       "      <td>benoît costil</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Caen</td>\n",
       "      <td>France</td>\n",
       "      <td>1987-07-03</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>188.0</td>\n",
       "      <td>right</td>\n",
       "      <td>France</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>fc girondins bordeaux</td>\n",
       "      <td>france</td>\n",
       "      <td>2800000.0</td>\n",
       "      <td>2017-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SVF FOOT</td>\n",
       "      <td>benoit costil</td>\n",
       "      <td>benoit</td>\n",
       "      <td>costil</td>\n",
       "      <td>b</td>\n",
       "      <td>france</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>34.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>23951</td>\n",
       "      <td>steve mandanda</td>\n",
       "      <td>28.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Kinshasa</td>\n",
       "      <td>Zaire</td>\n",
       "      <td>1985-03-28</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>185.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DR Congo</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>olympique marseille</td>\n",
       "      <td>france</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>2017-07-11</td>\n",
       "      <td>2024-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S.C. Sports Management</td>\n",
       "      <td>steve mandanda</td>\n",
       "      <td>steve</td>\n",
       "      <td>mandanda</td>\n",
       "      <td>s</td>\n",
       "      <td>france</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>36.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    player_id           player_name  day_of_birth  month_of_birth  \\\n",
       "0        2857       eldin jakupovic           2.0            10.0   \n",
       "1        3333          james milner           4.0             1.0   \n",
       "2        3455    zlatan ibrahimovic           3.0            10.0   \n",
       "3        5578     nicolas penneteau          28.0             2.0   \n",
       "4        6442        antonio rosati          26.0             6.0   \n",
       "5        7093  francesco magnanelli          12.0            11.0   \n",
       "6        7161         jonas hofmann          14.0             7.0   \n",
       "7        7663               joaquín          21.0             7.0   \n",
       "8        7825            pepe reina          31.0             8.0   \n",
       "9        8176         oier olazábal          14.0             9.0   \n",
       "10       8198     cristiano ronaldo           5.0             2.0   \n",
       "11       8246        philipp pentke           1.0             5.0   \n",
       "12       8806         cesc fàbregas           4.0             5.0   \n",
       "13      12359          niki mäenpää          23.0             1.0   \n",
       "14      12563          goran pandev          27.0             7.0   \n",
       "15      12907        alessio cragno          28.0             6.0   \n",
       "16      13460             lee grant          27.0             1.0   \n",
       "17      13572            ben foster           3.0             4.0   \n",
       "18      14044         andy lonergan          19.0            10.0   \n",
       "19      14086          ashley young           9.0             7.0   \n",
       "20      14555          scott carson           3.0             9.0   \n",
       "21      15452           raúl albiol           4.0             9.0   \n",
       "22      15773         phil bardsley          28.0             6.0   \n",
       "23      15930          david martin          22.0             1.0   \n",
       "24      15956           jesús navas          21.0            11.0   \n",
       "25      16136                 dante          18.0            10.0   \n",
       "26      16306              casemiro          23.0             2.0   \n",
       "27      16408      orestis karnezis          11.0             7.0   \n",
       "28      16633           alex cordaz           1.0             1.0   \n",
       "29      16911     kasper schmeichel           5.0            11.0   \n",
       "30      16922  kevin-prince boateng           6.0             3.0   \n",
       "31      17259          manuel neuer          27.0             3.0   \n",
       "32      17965           hugo lloris          26.0            12.0   \n",
       "33      18644        álvaro negredo          20.0             8.0   \n",
       "34      18909          jimmy briand           2.0             8.0   \n",
       "35      18922         karim benzema          19.0            12.0   \n",
       "36      18934        thomas mangani          29.0             4.0   \n",
       "37      18944          gerard piqué           2.0             2.0   \n",
       "38      20005            papu gómez          15.0             2.0   \n",
       "39      20463         corentin jean          15.0             7.0   \n",
       "40      20506       andrés guardado          28.0             9.0   \n",
       "41      21726     philipp tschauner           3.0            11.0   \n",
       "42      21763       federico peluso          20.0             1.0   \n",
       "43      21872       gianluca pegolo          25.0             3.0   \n",
       "44      21905         valon behrami          19.0             4.0   \n",
       "45      21972     cristian molinaro          30.0             7.0   \n",
       "46      22318    federico marchetti           7.0             2.0   \n",
       "47      22328    fabio quagliarella          31.0             1.0   \n",
       "48      22628         benoît costil           3.0             7.0   \n",
       "49      23951        steve mandanda          28.0             3.0   \n",
       "\n",
       "    year_of_birth                         pob                cob        dob  \\\n",
       "0          1984.0                     Kozarac  Jugoslawien (SFR) 1984-10-02   \n",
       "1          1986.0                       Leeds            England 1986-01-04   \n",
       "2          1981.0                       Malmö             Sweden 1981-10-03   \n",
       "3          1981.0                   Marseille             France 1981-02-28   \n",
       "4          1983.0                      Tivoli              Italy 1983-06-26   \n",
       "5          1984.0                   Umbertide              Italy 1984-11-12   \n",
       "6          1992.0                  Heidelberg            Germany 1992-07-14   \n",
       "7          1981.0    El Puerto de Santa María              Spain 1981-07-21   \n",
       "8          1982.0                      Madrid              Spain 1982-08-31   \n",
       "9          1989.0                        Irún              Spain 1989-09-14   \n",
       "10         1985.0                     Funchal           Portugal 1985-02-05   \n",
       "11         1985.0                    Freiberg                DDR 1985-05-01   \n",
       "12         1987.0               Arenys de Mar              Spain 1987-05-04   \n",
       "13         1985.0                       Espoo            Finland 1985-01-23   \n",
       "14         1983.0                    Strumica  Jugoslawien (SFR) 1983-07-27   \n",
       "15         1994.0                     Fiesole              Italy 1994-06-28   \n",
       "16         1983.0             Hemel Hempstead            England 1983-01-27   \n",
       "17         1983.0              Leamington Spa            England 1983-04-03   \n",
       "18         1983.0                     Preston            England 1983-10-19   \n",
       "19         1985.0                   Stevenage            England 1985-07-09   \n",
       "20         1985.0                  Whitehaven            England 1985-09-03   \n",
       "21         1985.0                 Vilamarxant              Spain 1985-09-04   \n",
       "22         1985.0                     Salford            England 1985-06-28   \n",
       "23         1986.0                      London            England 1986-01-22   \n",
       "24         1985.0  Los Palacios y Villafranca              Spain 1985-11-21   \n",
       "25         1983.0           Salvador da Bahia             Brazil 1983-10-18   \n",
       "26         1992.0         São José dos Campos             Brazil 1992-02-23   \n",
       "27         1985.0                       Athen             Greece 1985-07-11   \n",
       "28         1983.0             Vittorio Veneto              Italy 1983-01-01   \n",
       "29         1986.0                  Kopenhagen            Denmark 1986-11-05   \n",
       "30         1987.0                      Berlin            Germany 1987-03-06   \n",
       "31         1986.0               Gelsenkirchen            Germany 1986-03-27   \n",
       "32         1986.0                       Nizza             France 1986-12-26   \n",
       "33         1985.0                      Madrid              Spain 1985-08-20   \n",
       "34         1985.0             Vitry-sur-Seine             France 1985-08-02   \n",
       "35         1987.0                        Lyon             France 1987-12-19   \n",
       "36         1987.0                  Carpentras             France 1987-04-29   \n",
       "37         1987.0                   Barcelona              Spain 1987-02-02   \n",
       "38         1988.0                Buenos Aires          Argentina 1988-02-15   \n",
       "39         1995.0                       Blois             France 1995-07-15   \n",
       "40         1986.0                 Guadalajara             Mexico 1986-09-28   \n",
       "41         1985.0                   Schwabach            Germany 1985-11-03   \n",
       "42         1984.0                        Roma              Italy 1984-01-20   \n",
       "43         1981.0          Bassano del Grappa              Italy 1981-03-25   \n",
       "44         1985.0                   Mitrovicë  Jugoslawien (SFR) 1985-04-19   \n",
       "45         1983.0         Vallo della Lucania              Italy 1983-07-30   \n",
       "46         1983.0          Bassano del Grappa              Italy 1983-02-07   \n",
       "47         1983.0     Castellammare di Stabia              Italy 1983-01-31   \n",
       "48         1987.0                        Caen             France 1987-07-03   \n",
       "49         1985.0                    Kinshasa              Zaire 1985-03-28   \n",
       "\n",
       "                         position  height   foot citizenship  \\\n",
       "0                      Goalkeeper   191.0  right         NaN   \n",
       "1     midfield - Central Midfield   175.0  right     England   \n",
       "2         attack - Centre-Forward   195.0   both         NaN   \n",
       "3                      Goalkeeper   185.0   left      France   \n",
       "4                      Goalkeeper   195.0  right       Italy   \n",
       "5   midfield - Defensive Midfield   181.0  right       Italy   \n",
       "6           attack - Right Winger   176.0  right     Germany   \n",
       "7           attack - Right Winger   181.0  right       Spain   \n",
       "8                      Goalkeeper   188.0  right       Spain   \n",
       "9                      Goalkeeper   189.0   left       Spain   \n",
       "10        attack - Centre-Forward   187.0  right    Portugal   \n",
       "11                     Goalkeeper   191.0  right     Germany   \n",
       "12    midfield - Central Midfield   178.0  right       Spain   \n",
       "13                     Goalkeeper   191.0  right     Finland   \n",
       "14        attack - Second Striker   184.0   left         NaN   \n",
       "15                     Goalkeeper   184.0  right       Italy   \n",
       "16                     Goalkeeper   193.0  right     England   \n",
       "17                     Goalkeeper   193.0   left     England   \n",
       "18                     Goalkeeper   193.0   left     England   \n",
       "19           Defender - Left-Back   175.0   both         NaN   \n",
       "20                     Goalkeeper   188.0  right     England   \n",
       "21         Defender - Centre-Back   190.0  right       Spain   \n",
       "22          Defender - Right-Back   180.0  right         NaN   \n",
       "23                     Goalkeeper   188.0  right     England   \n",
       "24          Defender - Right-Back   172.0  right       Spain   \n",
       "25         Defender - Centre-Back   189.0   left      Brazil   \n",
       "26  midfield - Defensive Midfield   185.0  right         NaN   \n",
       "27                     Goalkeeper   190.0  right      Greece   \n",
       "28                     Goalkeeper   188.0  right       Italy   \n",
       "29                     Goalkeeper   189.0  right     Denmark   \n",
       "30  midfield - Attacking Midfield   186.0  right         NaN   \n",
       "31                     Goalkeeper   193.0  right     Germany   \n",
       "32                     Goalkeeper   188.0   left      France   \n",
       "33        attack - Centre-Forward   186.0   left       Spain   \n",
       "34        attack - Centre-Forward   183.0  right         NaN   \n",
       "35        attack - Centre-Forward   184.0   both         NaN   \n",
       "36    midfield - Central Midfield   183.0   left         NaN   \n",
       "37         Defender - Centre-Back   194.0  right       Spain   \n",
       "38        attack - Second Striker   167.0  right         NaN   \n",
       "39        attack - Centre-Forward   170.0  right      France   \n",
       "40    midfield - Central Midfield   169.0   left         NaN   \n",
       "41                     Goalkeeper   196.0  right     Germany   \n",
       "42         Defender - Centre-Back   188.0   left       Italy   \n",
       "43                     Goalkeeper   183.0   left       Italy   \n",
       "44  midfield - Defensive Midfield   184.0  right         NaN   \n",
       "45           Defender - Left-Back   182.0   left       Italy   \n",
       "46                     Goalkeeper   188.0   left       Italy   \n",
       "47        attack - Centre-Forward   180.0  right       Italy   \n",
       "48                     Goalkeeper   188.0  right      France   \n",
       "49                     Goalkeeper   185.0  right         NaN   \n",
       "\n",
       "    second_citizenship league_code  season              current_club  \\\n",
       "0   Bosnia-Herzegovina         GB1    2021            leicester city   \n",
       "1                  NaN         GB1    2021              liverpool fc   \n",
       "2   Bosnia-Herzegovina         IT1    2021                  ac milan   \n",
       "3                  NaN         FR1    2021               stade reims   \n",
       "4                  NaN         IT1    2021            acf fiorentina   \n",
       "5                  NaN         IT1    2021               us sassuolo   \n",
       "6                  NaN          L1    2021  borussia mönchengladbach   \n",
       "7                  NaN         ES1    2021       real betis balompié   \n",
       "8                  NaN         IT1    2021                  ss lazio   \n",
       "9                  NaN         ES1    2021    rcd espanyol barcelona   \n",
       "10                 NaN         IT1    2021               juventus fc   \n",
       "11                 NaN          L1    2021       tsg 1899 hoffenheim   \n",
       "12                 NaN         FR1    2021                 as monaco   \n",
       "13                 NaN         IT1    2021                venezia fc   \n",
       "14               Italy         IT1    2021                 genoa cfc   \n",
       "15                 NaN         IT1    2021           cagliari calcio   \n",
       "16                 NaN         GB1    2021         manchester united   \n",
       "17                 NaN         GB1    2021                watford fc   \n",
       "18                 NaN         GB1    2021                everton fc   \n",
       "19             Jamaica         GB1    2021               aston villa   \n",
       "20                 NaN         GB1    2021           manchester city   \n",
       "21                 NaN         ES1    2021             villarreal cf   \n",
       "22             England         GB1    2021                burnley fc   \n",
       "23                 NaN         GB1    2021           west ham united   \n",
       "24                 NaN         ES1    2021                sevilla fc   \n",
       "25                 NaN         FR1    2021                  ogc nice   \n",
       "26               Spain         ES1    2021               real madrid   \n",
       "27                 NaN         FR1    2021                losc lille   \n",
       "28                 NaN         IT1    2021               inter milan   \n",
       "29                 NaN         GB1    2021            leicester city   \n",
       "30             Germany          L1    2021                hertha bsc   \n",
       "31                 NaN          L1    2021             bayern munich   \n",
       "32                 NaN         GB1    2021         tottenham hotspur   \n",
       "33                 NaN         ES1    2021                  cádiz cf   \n",
       "34          Martinique         FR1    2021     fc girondins bordeaux   \n",
       "35             Algeria         ES1    2021               real madrid   \n",
       "36               Italy         FR1    2021                sco angers   \n",
       "37                 NaN         ES1    2021              fc barcelona   \n",
       "38               Italy         ES1    2021                sevilla fc   \n",
       "39                 NaN         FR1    2021                   rc lens   \n",
       "40               Spain         ES1    2021       real betis balompié   \n",
       "41                 NaN          L1    2021                rb leipzig   \n",
       "42                 NaN         IT1    2021               us sassuolo   \n",
       "43                 NaN         IT1    2021               us sassuolo   \n",
       "44              Kosovo         IT1    2021                 genoa cfc   \n",
       "45                 NaN         IT1    2021                venezia fc   \n",
       "46                 NaN         IT1    2021                 genoa cfc   \n",
       "47                 NaN         IT1    2021              uc sampdoria   \n",
       "48                 NaN         FR1    2021     fc girondins bordeaux   \n",
       "49            DR Congo         FR1    2021       olympique marseille   \n",
       "\n",
       "   current_club_country  market_value     joined contract_expires  \\\n",
       "0               england      300000.0 2017-07-19       2021-06-30   \n",
       "1               england     3000000.0 2015-07-01       2022-06-30   \n",
       "2                 italy     4000000.0 2020-01-02       2022-06-30   \n",
       "3                france      200000.0 2021-07-01       2023-06-30   \n",
       "4                 italy      100000.0 2021-02-01              NaT   \n",
       "5                 italy      400000.0 2005-07-01       2022-06-30   \n",
       "6               germany    16000000.0 2016-01-01       2023-06-30   \n",
       "7                 spain     1500000.0 2015-08-31       2022-06-30   \n",
       "8                 italy      800000.0 2020-09-01       2022-06-30   \n",
       "9                 spain      300000.0 2020-01-31       2022-06-30   \n",
       "10                italy    45000000.0 2018-07-10       2022-06-30   \n",
       "11              germany      300000.0 2019-07-01       2022-06-30   \n",
       "12               monaco     5000000.0 2019-01-11       2022-06-30   \n",
       "13                italy      200000.0 2021-02-15       2023-06-30   \n",
       "14                italy      500000.0 2015-07-07       2022-06-30   \n",
       "15                italy    20000000.0 2014-07-12       2024-06-30   \n",
       "16              england      250000.0 2018-07-03       2022-06-30   \n",
       "17              england      300000.0 2018-07-05       2022-06-30   \n",
       "18              england      250000.0 2021-08-20       2022-06-30   \n",
       "19              england     1000000.0 2021-07-01       2022-06-30   \n",
       "20              england      300000.0 2021-07-20       2022-06-30   \n",
       "21                spain     2500000.0 2019-07-04       2022-06-30   \n",
       "22              england      300000.0 2017-07-25       2022-06-30   \n",
       "23              england      250000.0 2019-07-01       2022-06-30   \n",
       "24                spain     3000000.0 2017-08-01       2024-06-30   \n",
       "25               france     1000000.0 2016-08-23       2022-06-30   \n",
       "26                spain    70000000.0 2013-07-01       2025-06-30   \n",
       "27               france      500000.0 2020-09-04       2023-06-30   \n",
       "28                italy      500000.0 2021-07-01       2022-06-30   \n",
       "29              england     6000000.0 2011-07-01       2023-06-30   \n",
       "30              germany     2000000.0 2021-07-01       2022-06-30   \n",
       "31              germany    18000000.0 2011-07-01       2023-06-30   \n",
       "32              england     9000000.0 2012-08-31       2022-06-30   \n",
       "33                spain     1200000.0 2020-08-04       2022-06-30   \n",
       "34               france     1100000.0 2018-08-10       2022-06-30   \n",
       "35                spain    25000000.0 2009-07-09       2023-06-30   \n",
       "36               france     1000000.0 2015-07-01       2022-06-30   \n",
       "37                spain    10000000.0 2008-07-01       2024-06-30   \n",
       "38                spain     9000000.0 2021-01-26       2024-06-30   \n",
       "39               france     1600000.0 2020-07-01       2023-06-30   \n",
       "40                spain     1500000.0 2017-07-07       2022-06-30   \n",
       "41              germany      300000.0 2019-07-30       2022-06-30   \n",
       "42                italy      400000.0 2014-07-03       2022-06-30   \n",
       "43                italy      100000.0 2013-09-02       2022-06-30   \n",
       "44                italy      400000.0 2020-01-02       2022-06-30   \n",
       "45                italy       75000.0 2020-01-15       2024-06-30   \n",
       "46                italy      200000.0 2018-07-01       2022-06-30   \n",
       "47                italy     1000000.0 2016-07-01       2022-06-30   \n",
       "48               france     2800000.0 2017-07-01       2022-06-30   \n",
       "49               france     2000000.0 2017-07-11       2024-06-30   \n",
       "\n",
       "   contract_option on_loan_from on_loan_from_country loan_contract_expiry  \\\n",
       "0              NaN          NaN                  NaN                  NaN   \n",
       "1              NaN          NaN                  NaN                  NaN   \n",
       "2              NaN          NaN                  NaN                  NaN   \n",
       "3              NaN          NaN                  NaN                  NaN   \n",
       "4              NaN          NaN                  NaN                  NaN   \n",
       "5              NaN          NaN                  NaN                  NaN   \n",
       "6              NaN          NaN                  NaN                  NaN   \n",
       "7              NaN          NaN                  NaN                  NaN   \n",
       "8              NaN          NaN                  NaN                  NaN   \n",
       "9              NaN          NaN                  NaN                  NaN   \n",
       "10             NaN          NaN                  NaN                  NaN   \n",
       "11             NaN          NaN                  NaN                  NaN   \n",
       "12             NaN          NaN                  NaN                  NaN   \n",
       "13             NaN          NaN                  NaN                  NaN   \n",
       "14             NaN          NaN                  NaN                  NaN   \n",
       "15             NaN          NaN                  NaN                  NaN   \n",
       "16             NaN          NaN                  NaN                  NaN   \n",
       "17             NaN          NaN                  NaN                  NaN   \n",
       "18             NaN          NaN                  NaN                  NaN   \n",
       "19             NaN          NaN                  NaN                  NaN   \n",
       "20             NaN          NaN                  NaN                  NaN   \n",
       "21             NaN          NaN                  NaN                  NaN   \n",
       "22             NaN          NaN                  NaN                  NaN   \n",
       "23             NaN          NaN                  NaN                  NaN   \n",
       "24             NaN          NaN                  NaN                  NaN   \n",
       "25             NaN          NaN                  NaN                  NaN   \n",
       "26             NaN          NaN                  NaN                  NaN   \n",
       "27             NaN          NaN                  NaN                  NaN   \n",
       "28             NaN          NaN                  NaN                  NaN   \n",
       "29             NaN          NaN                  NaN                  NaN   \n",
       "30             NaN          NaN                  NaN                  NaN   \n",
       "31             NaN          NaN                  NaN                  NaN   \n",
       "32             NaN          NaN                  NaN                  NaN   \n",
       "33             NaN          NaN                  NaN                  NaN   \n",
       "34             NaN          NaN                  NaN                  NaN   \n",
       "35             NaN          NaN                  NaN                  NaN   \n",
       "36             NaN          NaN                  NaN                  NaN   \n",
       "37             NaN          NaN                  NaN                  NaN   \n",
       "38             NaN          NaN                  NaN                  NaN   \n",
       "39             NaN          NaN                  NaN                  NaN   \n",
       "40             NaN          NaN                  NaN                  NaN   \n",
       "41             NaN          NaN                  NaN                  NaN   \n",
       "42             NaN          NaN                  NaN                  NaN   \n",
       "43             NaN          NaN                  NaN                  NaN   \n",
       "44             NaN          NaN                  NaN                  NaN   \n",
       "45             NaN          NaN                  NaN                  NaN   \n",
       "46             NaN          NaN                  NaN                  NaN   \n",
       "47             NaN          NaN                  NaN                  NaN   \n",
       "48             NaN          NaN                  NaN                  NaN   \n",
       "49             NaN          NaN                  NaN                  NaN   \n",
       "\n",
       "                     player_agent            name_lower firstname_lower  \\\n",
       "0                             HSD       eldin jakupovic           eldin   \n",
       "1   Samii Sport-Marketing Agentur          james milner           james   \n",
       "2                     Mino Raiola    zlatan ibrahimovic          zlatan   \n",
       "3                       USM GROUP     nicolas penneteau         nicolas   \n",
       "4          Alessandro Lucci - WSA        antonio rosati         antonio   \n",
       "5                  TMP SOCCER srl  francesco magnanelli       francesco   \n",
       "6                  Dr. Gutfleisch         jonas hofmann           jonas   \n",
       "7                  Juzzt Football               joaquin         joaquin   \n",
       "8            Manuel García Quilón            pepe reina            pepe   \n",
       "9                 Sport Agency 4U         oier olazabal            oier   \n",
       "10                      Gestifute     cristiano ronaldo       cristiano   \n",
       "11                       Bigpoint        philipp pentke         philipp   \n",
       "12                    Darren Dein         cesc fabregas            cesc   \n",
       "13             ICM Stellar Sports          niki maenpaa            niki   \n",
       "14              Carlo Pallavicino          goran pandev           goran   \n",
       "15                    Promoesport        alessio cragno         alessio   \n",
       "16                            NaN             lee grant             lee   \n",
       "17                            NaN            ben foster             ben   \n",
       "18         UK Sport Management BV         andy lonergan            andy   \n",
       "19                   CAA Base Ltd          ashley young          ashley   \n",
       "20                      Wasserman          scott carson           scott   \n",
       "21               Football Capital           raul albiol            raul   \n",
       "22                            NaN         phil bardsley            phil   \n",
       "23     Momentum Sports Management          david martin           david   \n",
       "24            Bahía Internacional           jesus navas           jesus   \n",
       "25                   Marcus Marin                 dante           dante   \n",
       "26                    Best of You              casemiro        casemiro   \n",
       "27                            NaN      orestis karnezis         orestis   \n",
       "28  QUAN SPORTS MANAGEMENT ITALIA           alex cordaz            alex   \n",
       "29    P&P Sport Management S.A.M.     kasper schmeichel          kasper   \n",
       "30               Excellence Sport  kevin-prince boateng    kevin-prince   \n",
       "31                PRO Profil GmbH          manuel neuer          manuel   \n",
       "32                            NaN           hugo lloris            hugo   \n",
       "33         Niagara Sports Company        alvaro negredo          alvaro   \n",
       "34                           TTMA          jimmy briand           jimmy   \n",
       "35                            NaN         karim benzema           karim   \n",
       "36                         Kemari        thomas mangani          thomas   \n",
       "37                      AC Talent          gerard pique          gerard   \n",
       "38                      Gr Sports            papu gomez            papu   \n",
       "39                firsteleven ISM         corentin jean        corentin   \n",
       "40                            NaN       andres guardado          andres   \n",
       "41                            NaN     philipp tschauner         philipp   \n",
       "42          PLAYER MANAGEMENT SRL       federico peluso        federico   \n",
       "43    P&P Sport Management S.A.M.       gianluca pegolo        gianluca   \n",
       "44  QUAN SPORTS MANAGEMENT ITALIA         valon behrami           valon   \n",
       "45                       no agent     cristian molinaro        cristian   \n",
       "46           AGB Sport Management    federico marchetti        federico   \n",
       "47           AGB Sport Management    fabio quagliarella           fabio   \n",
       "48                       SVF FOOT         benoit costil          benoit   \n",
       "49         S.C. Sports Management        steve mandanda           steve   \n",
       "\n",
       "   lastname_lower firstinitial_lower league_country_lower position_code  \\\n",
       "0       jakupovic                  e              england            GK   \n",
       "1          milner                  j              england            CM   \n",
       "2     ibrahimovic                  z                italy            ST   \n",
       "3       penneteau                  n               france            GK   \n",
       "4          rosati                  a                italy            GK   \n",
       "5      magnanelli                  f                italy           CDM   \n",
       "6         hofmann                  j              germany            RW   \n",
       "7         joaquin                  j                spain            RW   \n",
       "8           reina                  p                italy            GK   \n",
       "9        olazabal                  o                spain            GK   \n",
       "10        ronaldo                  c                italy            ST   \n",
       "11         pentke                  p              germany            GK   \n",
       "12       fabregas                  c               monaco            CM   \n",
       "13        maenpaa                  n                italy            GK   \n",
       "14         pandev                  g                italy            SS   \n",
       "15         cragno                  a                italy            GK   \n",
       "16          grant                  l              england            GK   \n",
       "17         foster                  b              england            GK   \n",
       "18       lonergan                  a              england            GK   \n",
       "19          young                  a              england            LB   \n",
       "20         carson                  s              england            GK   \n",
       "21         albiol                  r                spain            CB   \n",
       "22       bardsley                  p              england            RB   \n",
       "23         martin                  d              england            GK   \n",
       "24          navas                  j                spain            RB   \n",
       "25          dante                  d               france            CB   \n",
       "26       casemiro                  c                spain           CDM   \n",
       "27       karnezis                  o               france            GK   \n",
       "28         cordaz                  a                italy            GK   \n",
       "29     schmeichel                  k              england            GK   \n",
       "30        boateng                  k              germany           CAM   \n",
       "31          neuer                  m              germany            GK   \n",
       "32         lloris                  h              england            GK   \n",
       "33        negredo                  a                spain            ST   \n",
       "34         briand                  j               france            ST   \n",
       "35        benzema                  k                spain            ST   \n",
       "36        mangani                  t               france            CM   \n",
       "37          pique                  g                spain            CB   \n",
       "38          gomez                  p                spain            SS   \n",
       "39           jean                  c               france            ST   \n",
       "40       guardado                  a                spain            CM   \n",
       "41      tschauner                  p              germany            GK   \n",
       "42         peluso                  f                italy            CB   \n",
       "43         pegolo                  g                italy            GK   \n",
       "44        behrami                  v                italy           CDM   \n",
       "45       molinaro                  c                italy            LB   \n",
       "46      marchetti                  f                italy            GK   \n",
       "47   quagliarella                  f                italy            ST   \n",
       "48         costil                  b               france            GK   \n",
       "49       mandanda                  s               france            GK   \n",
       "\n",
       "   position_grouped outfielder_goalkeeper   age  age_when_joining  \\\n",
       "0        Goalkeeper            Goalkeeper  36.0              32.0   \n",
       "1        Midfielder            Outfielder  35.0              29.0   \n",
       "2           Forward            Outfielder  39.0              38.0   \n",
       "3        Goalkeeper            Goalkeeper  40.0              40.0   \n",
       "4        Goalkeeper            Goalkeeper  38.0              37.0   \n",
       "5        Midfielder            Outfielder  36.0              20.0   \n",
       "6           Forward            Outfielder  29.0              23.0   \n",
       "7           Forward            Outfielder  40.0              34.0   \n",
       "8        Goalkeeper            Goalkeeper  39.0              38.0   \n",
       "9        Goalkeeper            Goalkeeper  31.0              30.0   \n",
       "10          Forward            Outfielder  36.0              33.0   \n",
       "11       Goalkeeper            Goalkeeper  36.0              34.0   \n",
       "12       Midfielder            Outfielder  34.0              31.0   \n",
       "13       Goalkeeper            Goalkeeper  36.0              36.0   \n",
       "14          Forward            Outfielder  38.0              31.0   \n",
       "15       Goalkeeper            Goalkeeper  27.0              20.0   \n",
       "16       Goalkeeper            Goalkeeper  38.0              35.0   \n",
       "17       Goalkeeper            Goalkeeper  38.0              35.0   \n",
       "18       Goalkeeper            Goalkeeper  37.0              37.0   \n",
       "19         Defender            Outfielder  36.0              36.0   \n",
       "20       Goalkeeper            Goalkeeper  35.0              35.0   \n",
       "21         Defender            Outfielder  35.0              33.0   \n",
       "22         Defender            Outfielder  36.0              32.0   \n",
       "23       Goalkeeper            Goalkeeper  35.0              33.0   \n",
       "24         Defender            Outfielder  35.0              31.0   \n",
       "25         Defender            Outfielder  37.0              32.0   \n",
       "26       Midfielder            Outfielder  29.0              21.0   \n",
       "27       Goalkeeper            Goalkeeper  36.0              35.0   \n",
       "28       Goalkeeper            Goalkeeper  38.0              38.0   \n",
       "29       Goalkeeper            Goalkeeper  34.0              24.0   \n",
       "30       Midfielder            Outfielder  34.0              34.0   \n",
       "31       Goalkeeper            Goalkeeper  35.0              25.0   \n",
       "32       Goalkeeper            Goalkeeper  34.0              25.0   \n",
       "33          Forward            Outfielder  36.0              34.0   \n",
       "34          Forward            Outfielder  36.0              33.0   \n",
       "35          Forward            Outfielder  33.0              21.0   \n",
       "36       Midfielder            Outfielder  34.0              28.0   \n",
       "37         Defender            Outfielder  34.0              21.0   \n",
       "38          Forward            Outfielder  33.0              32.0   \n",
       "39          Forward            Outfielder  26.0              24.0   \n",
       "40       Midfielder            Outfielder  34.0              30.0   \n",
       "41       Goalkeeper            Goalkeeper  35.0              33.0   \n",
       "42         Defender            Outfielder  37.0              30.0   \n",
       "43       Goalkeeper            Goalkeeper  40.0              32.0   \n",
       "44       Midfielder            Outfielder  36.0              34.0   \n",
       "45         Defender            Outfielder  38.0              36.0   \n",
       "46       Goalkeeper            Goalkeeper  38.0              35.0   \n",
       "47          Forward            Outfielder  38.0              33.0   \n",
       "48       Goalkeeper            Goalkeeper  34.0              30.0   \n",
       "49       Goalkeeper            Goalkeeper  36.0              32.0   \n",
       "\n",
       "    years_since_joining  years_until_contract_expiry  \n",
       "0                   4.0                         -1.0  \n",
       "1                   6.0                          0.0  \n",
       "2                   1.0                          0.0  \n",
       "3                   0.0                          1.0  \n",
       "4                   0.0                          NaN  \n",
       "5                  16.0                          0.0  \n",
       "6                   5.0                          1.0  \n",
       "7                   6.0                          0.0  \n",
       "8                   0.0                          0.0  \n",
       "9                   1.0                          0.0  \n",
       "10                  3.0                          0.0  \n",
       "11                  2.0                          0.0  \n",
       "12                  2.0                          0.0  \n",
       "13                  0.0                          1.0  \n",
       "14                  6.0                          0.0  \n",
       "15                  7.0                          2.0  \n",
       "16                  3.0                          0.0  \n",
       "17                  3.0                          0.0  \n",
       "18                  0.0                          0.0  \n",
       "19                  0.0                          0.0  \n",
       "20                  0.0                          0.0  \n",
       "21                  2.0                          0.0  \n",
       "22                  4.0                          0.0  \n",
       "23                  2.0                          0.0  \n",
       "24                  4.0                          2.0  \n",
       "25                  5.0                          0.0  \n",
       "26                  8.0                          3.0  \n",
       "27                  0.0                          1.0  \n",
       "28                  0.0                          0.0  \n",
       "29                 10.0                          1.0  \n",
       "30                  0.0                          0.0  \n",
       "31                 10.0                          1.0  \n",
       "32                  8.0                          0.0  \n",
       "33                  1.0                          0.0  \n",
       "34                  3.0                          0.0  \n",
       "35                 12.0                          1.0  \n",
       "36                  6.0                          0.0  \n",
       "37                 13.0                          2.0  \n",
       "38                  0.0                          2.0  \n",
       "39                  1.0                          1.0  \n",
       "40                  4.0                          0.0  \n",
       "41                  2.0                          0.0  \n",
       "42                  7.0                          0.0  \n",
       "43                  7.0                          0.0  \n",
       "44                  1.0                          0.0  \n",
       "45                  1.0                          2.0  \n",
       "46                  3.0                          0.0  \n",
       "47                  5.0                          0.0  \n",
       "48                  4.0                          0.0  \n",
       "49                  4.0                          2.0  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tm_bio_status.head(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.6'>4.1.6. Convert Euros to Pounds</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.90053"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get EUR to GBP exchange rate\n",
    "\n",
    "## Get latest currency rates\n",
    "c = CurrencyConverter()\n",
    "\n",
    "##  Get conversion rate from EUR to GBP\n",
    "rate_eur_gbp = (c.convert(1, 'EUR', 'GBP'))\n",
    "rate_eur_gbp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Overwrite\n",
    "rate_eur_gbp = 0.90\n",
    "rate_eur_gbp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert TM.com Euro value to Pounds\n",
    "df_tm_bio_status['market_value_gbp'] = df_tm_bio_status['market_value'] * rate_eur_gbp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.7'>4.1.7. Rename Columns</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tm_bio_status = df_tm_bio_status.rename(columns={'player_id': 'tm_id',\n",
    "                                                    'season_x': 'season',\n",
    "                                                    'market_value': 'market_value_eur',\n",
    "                                                    'day_of_birth': 'birth_day',\n",
    "                                                    'month_of_birth': 'birth_month',\n",
    "                                                    'year_of_birth': 'birth_year'\n",
    "                                                   }\n",
    "                                          )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.8'>4.1.8. Filter Players in 'Big 5' European Leagues</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter players in the 'Big 5' European Leagues and MLS\n",
    "df_tm_bio_status_big5_mls = df_tm_bio_status[df_tm_bio_status['league_code'].isin(lst_big5_mls_league_codes)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No. rows in DataFrame BEFORE filtration: 9429\n",
      "No. rows in DataFrame AFTER filtration: 9429\n",
      "\n",
      "Variance in rows before and after filtration: 0\n",
      "\n",
      "----------\n"
     ]
    }
   ],
   "source": [
    "print('No. rows in DataFrame BEFORE filtration: {}'.format(len(df_tm_bio_status)))\n",
    "print('No. rows in DataFrame AFTER filtration: {}\\n'.format(len(df_tm_bio_status_big5_mls)))\n",
    "print('Variance in rows before and after filtration: {}\\n'.format(len(df_tm_bio_status_big5_mls) - len(df_tm_bio_status)))\n",
    "print('-'*10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <a id='#section4.1.9'>4.1.9. Exporting the Engineered DataFrames</a>\n",
    "Export the two engineered [TransferMarkt](https://www.transfermarkt.co.uk/) DataFrames as CSV files."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### All players"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Filename\n",
    "file_name = 'tm_player_bio_status_all'\n",
    "\n",
    "## Full season string\n",
    "full_season_string = '2016/2017 - 2021/2022'\n",
    "\n",
    "## Short season string\n",
    "short_season_string = '1617-2122'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export DataFrame as a CSV file\n",
    "\n",
    "## Export a copy to the 'archive' subfolder of the TM folder, including the date\n",
    "df_tm_bio_status.to_csv(data_dir_tm + f'/engineered/bio-status/archive/{file_name}_{short_season_string}_last_updated_{today}.csv', index=None, header=True)\n",
    "\n",
    "## Export another copy to the TM folder called 'latest' (can be overwritten)\n",
    "df_tm_bio_status.to_csv(data_dir_tm + f'/engineered/bio-status/{file_name}_{short_season_string}_latest.csv', index=None, header=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 'Big 5' European and MLS Players"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Filename\n",
    "file_name = 'tm_player_bio_status_big5_mls'\n",
    "\n",
    "## Full season string\n",
    "full_season_string = '2016/2017-2021/2022'\n",
    "\n",
    "## Short season string\n",
    "short_season_string = '1617-2122'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 'Big 5' European Leagues and MLS\n",
    "\n",
    "### Export a copy to the 'archive' subfolder of the TM folder, including the date\n",
    "df_tm_bio_status_big5_mls.to_csv(data_dir_tm + f'/engineered/bio-status/archive/tm_bio_status_big5_mls_{short_season_string}_last_updated_{today}.csv', index=None, header=True)\n",
    "\n",
    "### Export another copy to the TM folder called 'latest' (can be overwritten)\n",
    "df_tm_bio_status_big5_mls.to_csv(data_dir_tm + f'/engineered/bio-status/tm_bio_status_big5_mls_{short_season_string}_latest.csv', index=None, header=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have created three pandas DataFrames and wrangled the data to meet our needs, we'll next conduct and [Exploratory Data Analysis ](#section5)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='#section5'>5. Exploratory Data Analysis</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>tm_id</th>\n",
       "      <th>player_name</th>\n",
       "      <th>birth_day</th>\n",
       "      <th>birth_month</th>\n",
       "      <th>birth_year</th>\n",
       "      <th>pob</th>\n",
       "      <th>cob</th>\n",
       "      <th>dob</th>\n",
       "      <th>position</th>\n",
       "      <th>height</th>\n",
       "      <th>foot</th>\n",
       "      <th>citizenship</th>\n",
       "      <th>second_citizenship</th>\n",
       "      <th>league_code</th>\n",
       "      <th>season</th>\n",
       "      <th>current_club</th>\n",
       "      <th>current_club_country</th>\n",
       "      <th>market_value_euros</th>\n",
       "      <th>joined</th>\n",
       "      <th>contract_expires</th>\n",
       "      <th>contract_option</th>\n",
       "      <th>on_loan_from</th>\n",
       "      <th>on_loan_from_country</th>\n",
       "      <th>loan_contract_expiry</th>\n",
       "      <th>player_agent</th>\n",
       "      <th>name_lower</th>\n",
       "      <th>firstname_lower</th>\n",
       "      <th>lastname_lower</th>\n",
       "      <th>firstinitial_lower</th>\n",
       "      <th>league_country_lower</th>\n",
       "      <th>position_code</th>\n",
       "      <th>position_grouped</th>\n",
       "      <th>outfielder_goalkeeper</th>\n",
       "      <th>age</th>\n",
       "      <th>age_when_joining</th>\n",
       "      <th>years_since_joining</th>\n",
       "      <th>years_until_contract_expiry</th>\n",
       "      <th>market_value_pounds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2857</td>\n",
       "      <td>eldin jakupovic</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Kozarac</td>\n",
       "      <td>Jugoslawien (SFR)</td>\n",
       "      <td>1984-10-02</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>191.0</td>\n",
       "      <td>right</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bosnia-Herzegovina</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>leicester city</td>\n",
       "      <td>england</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2017-07-19</td>\n",
       "      <td>2021-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HSD</td>\n",
       "      <td>eldin jakupovic</td>\n",
       "      <td>eldin</td>\n",
       "      <td>jakupovic</td>\n",
       "      <td>e</td>\n",
       "      <td>england</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>36.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>270000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3333</td>\n",
       "      <td>james milner</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Leeds</td>\n",
       "      <td>England</td>\n",
       "      <td>1986-01-04</td>\n",
       "      <td>midfield - Central Midfield</td>\n",
       "      <td>175.0</td>\n",
       "      <td>right</td>\n",
       "      <td>England</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GB1</td>\n",
       "      <td>2021</td>\n",
       "      <td>liverpool fc</td>\n",
       "      <td>england</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>2015-07-01</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Samii Sport-Marketing Agentur</td>\n",
       "      <td>james milner</td>\n",
       "      <td>james</td>\n",
       "      <td>milner</td>\n",
       "      <td>j</td>\n",
       "      <td>england</td>\n",
       "      <td>CM</td>\n",
       "      <td>Midfielder</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>35.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2700000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3455</td>\n",
       "      <td>zlatan ibrahimovic</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>Malmö</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>1981-10-03</td>\n",
       "      <td>attack - Centre-Forward</td>\n",
       "      <td>195.0</td>\n",
       "      <td>both</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bosnia-Herzegovina</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>ac milan</td>\n",
       "      <td>italy</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>2022-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mino Raiola</td>\n",
       "      <td>zlatan ibrahimovic</td>\n",
       "      <td>zlatan</td>\n",
       "      <td>ibrahimovic</td>\n",
       "      <td>z</td>\n",
       "      <td>italy</td>\n",
       "      <td>ST</td>\n",
       "      <td>Forward</td>\n",
       "      <td>Outfielder</td>\n",
       "      <td>39.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3600000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5578</td>\n",
       "      <td>nicolas penneteau</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>Marseille</td>\n",
       "      <td>France</td>\n",
       "      <td>1981-02-28</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>185.0</td>\n",
       "      <td>left</td>\n",
       "      <td>France</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FR1</td>\n",
       "      <td>2021</td>\n",
       "      <td>stade reims</td>\n",
       "      <td>france</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USM GROUP</td>\n",
       "      <td>nicolas penneteau</td>\n",
       "      <td>nicolas</td>\n",
       "      <td>penneteau</td>\n",
       "      <td>n</td>\n",
       "      <td>france</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>180000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6442</td>\n",
       "      <td>antonio rosati</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Tivoli</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1983-06-26</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>195.0</td>\n",
       "      <td>right</td>\n",
       "      <td>Italy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IT1</td>\n",
       "      <td>2021</td>\n",
       "      <td>acf fiorentina</td>\n",
       "      <td>italy</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>2021-02-01</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alessandro Lucci - WSA</td>\n",
       "      <td>antonio rosati</td>\n",
       "      <td>antonio</td>\n",
       "      <td>rosati</td>\n",
       "      <td>a</td>\n",
       "      <td>italy</td>\n",
       "      <td>GK</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>Goalkeeper</td>\n",
       "      <td>38.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tm_id         player_name  birth_day  birth_month  birth_year        pob  \\\n",
       "0   2857     eldin jakupovic        2.0         10.0      1984.0    Kozarac   \n",
       "1   3333        james milner        4.0          1.0      1986.0      Leeds   \n",
       "2   3455  zlatan ibrahimovic        3.0         10.0      1981.0      Malmö   \n",
       "3   5578   nicolas penneteau       28.0          2.0      1981.0  Marseille   \n",
       "4   6442      antonio rosati       26.0          6.0      1983.0     Tivoli   \n",
       "\n",
       "                 cob        dob                     position  height   foot  \\\n",
       "0  Jugoslawien (SFR) 1984-10-02                   Goalkeeper   191.0  right   \n",
       "1            England 1986-01-04  midfield - Central Midfield   175.0  right   \n",
       "2             Sweden 1981-10-03      attack - Centre-Forward   195.0   both   \n",
       "3             France 1981-02-28                   Goalkeeper   185.0   left   \n",
       "4              Italy 1983-06-26                   Goalkeeper   195.0  right   \n",
       "\n",
       "  citizenship  second_citizenship league_code  season    current_club  \\\n",
       "0         NaN  Bosnia-Herzegovina         GB1    2021  leicester city   \n",
       "1     England                 NaN         GB1    2021    liverpool fc   \n",
       "2         NaN  Bosnia-Herzegovina         IT1    2021        ac milan   \n",
       "3      France                 NaN         FR1    2021     stade reims   \n",
       "4       Italy                 NaN         IT1    2021  acf fiorentina   \n",
       "\n",
       "  current_club_country  market_value_euros     joined contract_expires  \\\n",
       "0              england            300000.0 2017-07-19       2021-06-30   \n",
       "1              england           3000000.0 2015-07-01       2022-06-30   \n",
       "2                italy           4000000.0 2020-01-02       2022-06-30   \n",
       "3               france            200000.0 2021-07-01       2023-06-30   \n",
       "4                italy            100000.0 2021-02-01              NaT   \n",
       "\n",
       "  contract_option on_loan_from on_loan_from_country loan_contract_expiry  \\\n",
       "0             NaN          NaN                  NaN                  NaN   \n",
       "1             NaN          NaN                  NaN                  NaN   \n",
       "2             NaN          NaN                  NaN                  NaN   \n",
       "3             NaN          NaN                  NaN                  NaN   \n",
       "4             NaN          NaN                  NaN                  NaN   \n",
       "\n",
       "                    player_agent          name_lower firstname_lower  \\\n",
       "0                            HSD     eldin jakupovic           eldin   \n",
       "1  Samii Sport-Marketing Agentur        james milner           james   \n",
       "2                    Mino Raiola  zlatan ibrahimovic          zlatan   \n",
       "3                      USM GROUP   nicolas penneteau         nicolas   \n",
       "4         Alessandro Lucci - WSA      antonio rosati         antonio   \n",
       "\n",
       "  lastname_lower firstinitial_lower league_country_lower position_code  \\\n",
       "0      jakupovic                  e              england            GK   \n",
       "1         milner                  j              england            CM   \n",
       "2    ibrahimovic                  z                italy            ST   \n",
       "3      penneteau                  n               france            GK   \n",
       "4         rosati                  a                italy            GK   \n",
       "\n",
       "  position_grouped outfielder_goalkeeper   age  age_when_joining  \\\n",
       "0       Goalkeeper            Goalkeeper  36.0              32.0   \n",
       "1       Midfielder            Outfielder  35.0              29.0   \n",
       "2          Forward            Outfielder  39.0              38.0   \n",
       "3       Goalkeeper            Goalkeeper  40.0              40.0   \n",
       "4       Goalkeeper            Goalkeeper  38.0              37.0   \n",
       "\n",
       "   years_since_joining  years_until_contract_expiry  market_value_pounds  \n",
       "0                  4.0                         -1.0             270000.0  \n",
       "1                  6.0                          0.0            2700000.0  \n",
       "2                  1.0                          0.0            3600000.0  \n",
       "3                  0.0                          1.0             180000.0  \n",
       "4                  0.0                          NaN              90000.0  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tm_bio_status_big5_mls.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='#section6'>6. Summary</a>\n",
    "This Jupyter notebook engineered scraped football data from [TransferMarkt](https://www.transfermarkt.co.uk/) using [pandas](http://pandas.pydata.org/) for data manipulation through DataFrames."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='#section7'>7. Next Steps</a>\n",
    "The step is to use this data and match it to FBref, 21st Club, Opta, FIFA, and other TransferMarkt datasets, such as the Transfer History dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='#section8'>8. References</a>\n",
    "\n",
    "#### Data and Web Scraping\n",
    "*    [tyrone_mings GitHub repository](https://github.com/FCrSTATS/tyrone_mings) by [FCrSTATS](https://github.com/FCrSTATS)\n",
    "*    [Python Package Index (PyPI) tyrone-mings library](https://pypi.org/project/tyrone-mings/)\n",
    "*    [Beyond crowd judgments: Data-driven estimation of market value in association football](https://www.sciencedirect.com/science/article/pii/S0377221717304332) by Oliver Müllera, Alexander Simons, and Markus Weinmann.\n",
    "*    [06/04/2020: BBC - Premier League squads 'drop £1.6bn in value'](https://www.bbc.co.uk/sport/football/52221463)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "***Visit my website [eddwebster.com](https://www.eddwebster.com) or my [GitHub Repository](https://github.com/eddwebster) for more projects. If you'd like to get in contact, my Twitter handle is [@eddwebster](http://www.twitter.com/eddwebster) and my email is: edd.j.webster@gmail.com.***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Back to the top](#top)"
   ]
  }
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