SoccerTeamsAnalysis/European_Soccer.ipynb

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   "source": [
    "# European Soccer Dataset\n",
    "\n",
    "## Table of Contents\n",
    "<ul>\n",
    "<li><a href=\"#intro\">Introduction</a></li>\n",
    "<li><a href=\"#wrangling\">Data Wrangling</a></li>\n",
    "    <ul>\n",
    "    <li><a href=\"#general\">General Properties</a></li>\n",
    "    <li><a href=\"#cleaning\">Data Cleaning</a></li>\n",
    "    </ul>\n",
    "    <ul></ul>\n",
    "<li><a href=\"#eda\">Exploratory Data Analysis</a></li>\n",
    "    <ul>\n",
    "    <li><a href=\"#teams\">Teams Distribution</a></li>\n",
    "    <li><a href=\"#effectivityVSgoals_scored\">Teams' Effectivity Correlation to Scored Goals</a></li>\n",
    "    <li><a href=\"#effectivityVSgoals_recv\">Teams' Effectivity Correlation to Received Goals</a></li>\n",
    "    <li><a href=\"#home_away_goals\">Home and Away Goals</a></li>\n",
    "    <li><a href=\"#scored_recv_goals\">Scored and Against Goals</a></li>\n",
    "    <li><a href=\"#home_win\">Home Games and the Winning Factor</a></li>\n",
    "    <li><a href=\"#leagues\">Leagues Performance</a></li> \n",
    "    </ul>\n",
    "    <ul></ul>\n",
    "<li><a href=\"#conclusions\">Conclusions</a></li>\n",
    "<li><a href=\"#limitations\">Limitations on Analysis</a></li>\n",
    "</ul>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='intro'></a>\n",
    "## Introduction\n",
    "\n",
    "The dataset analyzed in this notebook is related to european football soccer teams matches. The dataset is provided in the format of an **SQLite database on Kaggle** and can be found [here](https://www.kaggle.com/hugomathien/soccer/data). If you are insterested in following along the first section of data wrangling demo for sqlite3 usage, please download the database in the same folder of the notebook and name it **soccer_db.sqlite**.\n",
    "\n",
    "The analysis of this data involved SQL queries using [DB Browser](http://sqlitebrowser.org/). \n",
    "\n",
    "### **Data Analysis Motivation**\n",
    "\n",
    "The purpose of this analysis is to use data from:\n",
    "* England Premier League\n",
    "* Spain LIGA BBVA\n",
    "* Germany 1. Bundesliga\n",
    "* Italy Serie A\n",
    "* France Ligue 1\n",
    "* Netherlands Eredivisie\n",
    "\n",
    "with the purpose of understanding what the distribution of the teams performance over all seasons is.\n",
    "\n",
    "Once the performance of every team is computed and the distribution is plotted, it will be good to find out if scoring more goals correlates to the performance of a team. While doing the previous it is also an opportunity to analyze if receiving less or more goals is also correlated to performance. \n",
    "\n",
    "The next mistery to unveil is the intriguing belief that when a team plays at home usually wins, while playing away gives the team less chance to win. \n",
    "\n",
    "\n",
    "Finally, it will be great to compare the leagues and check which league has a better average performance which is computed by averaging the teams performance in a given league. \n"
   ]
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  {
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import sqlite3\n",
    "from mpl_toolkits.mplot3d import Axes3D #for 3D plots\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='wrangling'></a>\n",
    "## Data Wrangling\n",
    "\n",
    "The data at first was loaded using *Python sqlite3* package, which helps stablish a connection to the database, then pandas is used to query, store, clean up and analysis of data. An example using the **soccer_db.sqlite** database is given to illustrate how to use the described above and to verify the leagues we are interested exist in the database.\n",
    "However, the final query that merges joins, Common Table Expressions (CTE)and does math operations to the joined tables was very long and had to be processed in DB browser. The resulting table was saved as **teams_rank.csv** file to be able to load it on a pandas dataframe. \n",
    "\n",
    "\n",
    "<a id='general'></a>\n",
    "### General Properties\n",
    "\n",
    "The database used contains 8 tables:\n",
    "* Country - All countries from which their teams data was collected\n",
    "* League - All football leagues in the database\n",
    "* Match - All games played in the different leagues\n",
    "* Player - All players biometrics \n",
    "* Player_Attributes - All players and their statistics based on FIFA\n",
    "* Team -  All team names\n",
    "* Team_Attributes - Teams' statistics\n",
    "* sqlite_sequence - sequence of the previous tables\n",
    "\n",
    "Getting started with the analysis, I would like to show the use of sqlite3 and pandas, we need to connect to the SQLite database and find if the leagues we are interested exist in the current database.\n",
    "\n",
    ">**Note:** Due to the complexity of the final query we use DB Browser, but this serves as a good section to learn a new tool to your belt."
   ]
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   "cell_type": "code",
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>country_id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1729</td>\n",
       "      <td>1729</td>\n",
       "      <td>England Premier League</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4769</td>\n",
       "      <td>4769</td>\n",
       "      <td>France Ligue 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7809</td>\n",
       "      <td>7809</td>\n",
       "      <td>Germany 1. Bundesliga</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10257</td>\n",
       "      <td>10257</td>\n",
       "      <td>Italy Serie A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13274</td>\n",
       "      <td>13274</td>\n",
       "      <td>Netherlands Eredivisie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>21518</td>\n",
       "      <td>21518</td>\n",
       "      <td>Spain LIGA BBVA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  country_id                    name\n",
       "0   1729        1729  England Premier League\n",
       "1   4769        4769          France Ligue 1\n",
       "2   7809        7809   Germany 1. Bundesliga\n",
       "3  10257       10257           Italy Serie A\n",
       "4  13274       13274  Netherlands Eredivisie\n",
       "5  21518       21518         Spain LIGA BBVA"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "#Stablish SQL connection and pandas for SQL query execution\n",
    "conn = sqlite3.connect(\"soccer_db.sqlite\")\n",
    "\n",
    "#Query database to check and retrieve the leagues we are interested on\n",
    "df_test = pd.read_sql_query(\"SELECT * \\\n",
    "                              FROM League\\\n",
    "                              WHERE name LIKE 'England%Premier%'\\\n",
    "                                    OR name LIKE 'Spain%BBVA%'\\\n",
    "                                    OR name LIKE 'Italy%'\\\n",
    "                                    OR name LIKE 'Germany%'\\\n",
    "                                    OR name LIKE 'France%'\\\n",
    "                                    OR name LIKE 'Netherlands%';\"\\\n",
    "                            , conn)\n",
    "df_test\n",
    "\n"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once the database was used and we confirmed the leagues we are interested exist on the database, the connection can be closed. \n",
    "**NOTE:** We only close the connection because from here on we have already collected the data in a csv file to help the user follow better and able to skip this sqlite part if needed."
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "#Close connection to database opened\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since all leagues exist, we can extract the data in a combined table to have all teams listed by a performance in descending order.  \n",
    "\n",
    "**The Match table** has:\n",
    "* League id and teams id, so we needs to perform the join with Team to understand which teams played\n",
    "* Contains the season in which the match was played. The season are from 2008 to 2015. We are mainly interested in the overall performance of teams over these all season, therefore we are looking for a table that combines evything and not broken by seasons. \n",
    "\n",
    ">**Note:**The information above is important to mention in case someone else wants to use the same database for season analysis.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='cleaning'></a>\n",
    "### Data Cleaning\n",
    "\n",
    "The steps followed in the SQL data preparation and cleaning are:\n",
    "\n",
    "1. Join the tables League, Match and Team to understand the data\n",
    "    \n",
    "2. From the data on the join above create a new temporary table (CTE) that perfoms aggregations to create the league season results including season, team, total points, wins, losses, draws, home wins, home loses, home draws, away wins, away loses, away draws, home goals, away goals, total goals, home goals received, away goals received, total goals received, goals difference - *This table is league_results*\n",
    "\n",
    "3. The table *league_results* can help us create a new table that consolidates results for each team over all seasons. In this step is when we should remember our questions to make the table contain what we need:\n",
    "\n",
    "    * What is the distribution of the teams performance?\n",
    "    * Is scoring more goals related to better performance?\n",
    "    * Is receiving goals correlated to better performance?\n",
    "    * Is playing home related to more wins?\n",
    "    * Describe the performance of each league\n",
    "  \n",
    "4. Some data manipulation is needed to check each league over all seasons. However, this can be done in pandas with the table gotten from SQL\n",
    "\n",
    ">**Note:** Something to highlight here that caught my attention is that the data was ready to use for answering the questions proposed above. The only caveat was that the total number of matches in each league could vary and we needed to consider proporction and averages to do our analysis instead of using the raw values from **SUM( )** or **AVG( )** from aggregations as they won't be fair for leagues or teams which had less matches. Besides that the data was clean enough to use it"
   ]
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   "source": [
    "To create a table with all the historical data from the desired leagues, use the query below:\n",
    "\n",
    ">**Note:** The query below does step 1 and 2. The output of this query is what we describe in 3 as a table to help us answer our questions\n",
    "\n",
    "``` mysql\n",
    "WITH league_table AS ( \n",
    "                       SELECT \n",
    "                            l.id AS league_id,\n",
    "                            t.team_api_id AS team_id,\n",
    "                            l.name AS league,\n",
    "\t\t\t\t\t\t\tm.season AS season,\n",
    "\t\t\t\t\t\t\tt.team_long_name AS team,\n",
    "\t\t\t\t\t\t\tSUM(CASE  WHEN (m.home_team_api_id = t.team_api_id \n",
    "                                           AND m.home_team_goal - m.away_team_goal >= 1) \n",
    "                                           THEN 1 \n",
    "                                       ELSE 0 \n",
    "                                 END) AS HomeWins,\n",
    "\t\t\t\t\t\t\t\n",
    "                            SUM(CASE WHEN (m.home_team_api_id = t.team_api_id  \n",
    "                                          AND m.home_team_goal = m.away_team_goal) \n",
    "                                          THEN 1 \n",
    "                                      ELSE 0 \n",
    "                                 END) AS HomeDraws,\n",
    "                                 \n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN (m.home_team_api_id = t.team_api_id \n",
    "                                          AND m.home_team_goal - m.away_team_goal < 0) \n",
    "                                          THEN 1 \n",
    "                                      ELSE 0 \n",
    "                                 END) AS HomeLoses,\n",
    "                                 \n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN (m.away_team_api_id = t.team_api_id \n",
    "                                          AND m.away_team_goal - m.home_team_goal >=1 ) \n",
    "                                          THEN 1 \n",
    "                                      ELSE 0 \n",
    "                                 END) AS AwayWins,\n",
    "                                 \n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN (m.away_team_api_id = t.team_api_id \n",
    "                                          AND m.away_team_goal = m.home_team_goal) \n",
    "                                          THEN 1 \n",
    "                                      ELSE 0 \n",
    "                                 END) AS AwayDraws,\n",
    "                                 \n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN (m.away_team_api_id = t.team_api_id \n",
    "                                          AND m.away_team_goal - m.home_team_goal < 0) \n",
    "                                          THEN 1 \n",
    "                                      ELSE 0 \n",
    "                                 END) AS AwayLoses,\n",
    "                                 \n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN m.home_team_api_id = t.team_api_id \n",
    "                                            THEN m.home_team_goal END ) AS HomeGoals,\n",
    "                                            \n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN m.home_team_api_id = t.team_api_id \n",
    "                                            THEN m.away_team_goal END ) \n",
    "                            AS HomeGoalsConceded,\n",
    "\t\t\t\t\t\t\t\n",
    "                            SUM(CASE WHEN m.away_team_api_id = t.team_api_id \n",
    "                                            THEN m.away_team_goal END ) AS AwayGoals,\n",
    "\t\t\t\t\t\t\tSUM(CASE WHEN m.away_team_api_id = t.team_api_id \n",
    "                                            THEN m.home_team_goal END ) \n",
    "                            AS AwayGoalsConceded\t\n",
    "\t\t\t\t\t\t\t\n",
    "                            FROM League l\n",
    "\t\t\t\t\t\t\tJOIN Match m\n",
    "                                ON l.id = m.league_id\n",
    "\t\t\t\t\t\t\tJOIN Team t\n",
    "                                ON m.home_team_api_id = t.team_api_id  \n",
    "                                    OR m.away_team_api_id = t.team_api_id\n",
    "\t\t\t\t\t\t\tWHERE l.name LIKE 'England%' \n",
    "                                  OR l.name LIKE 'Spain%' \n",
    "                                  OR l.name LIKE 'Italy%' \n",
    "                                  OR l.name LIKE 'Germany%'\n",
    "                                  OR l.name LIKE 'France%'\n",
    "                                  OR l.name LIKE 'Netherlands%'\n",
    "\t\t\t\t\t\t\tGROUP BY l.name, m.season, t.team_long_name\n",
    "\t\t\t\t\t\t\tORDER BY m.season, HomeWins DESC, AwayWins DESC \n",
    "\t\t\t),\n",
    "\t\t\t\n",
    "\t\t\tleague_results AS (\t\t\t\n",
    "\t\t\t\t\t\t\t\tSELECT \n",
    "                                    league_id,\n",
    "                                    team_id,\n",
    "\t\t\t\t\t\t\t\t\tleague,\n",
    "\t\t\t\t\t\t\t\t\tseason,\n",
    "\t\t\t\t\t\t\t\t\tteam,\n",
    "\t\t\t\t\t\t\t\t\t(HomeWins + AwayWins)*3 \n",
    "                                        + (HomeDraws + AwayDraws) AS total_points,\n",
    "\t\t\t\t\t\t\t\t\t\n",
    "                                    (HomeWins + AwayWins + HomeDraws \n",
    "                                        + AwayDraws + HomeLoses + AwayLoses) \n",
    "                                    AS total_matches,\n",
    "\t\t\t\t\t\t\t\t\t\n",
    "                                    (HomeWins + AwayWins) AS win,\n",
    "\t\t\t\t\t\t\t\t\t(HomeDraws + AwayDraws)  AS draw,\n",
    "\t\t\t\t\t\t\t\t\t(HomeLoses + AwayLoses) AS lose,\n",
    "\t\t\t\t\t\t\t\t\t(HomeGoals + AwayGoals) AS total_goals,\n",
    "\t\t\t\t\t\t\t\t\t(HomeGoalsConceded \n",
    "                                        + AwayGoalsConceded) AS total_goals_conceded,\n",
    "\t\t\t\t\t\t\t\t\t\n",
    "                                    (HomeGoals + AwayGoals) \n",
    "                                        - (HomeGoalsConceded + AwayGoalsConceded)  \n",
    "                                    AS goals_difference,\n",
    "                                        \n",
    "\t\t\t\t\t\t\t\t\t(HomeWins + HomeDraws + HomeLoses) AS home_g,\n",
    "\t\t\t\t\t\t\t\t\t(AwayWins + AwayDraws + AwayLoses) AS away_g,\n",
    "\t\t\t\t\t\t\t\t\tHomeWins AS home_wins,\n",
    "\t\t\t\t\t\t\t\t\tHomeDraws AS home_draws,\n",
    "\t\t\t\t\t\t\t\t\tHomeLoses AS home_loses,\n",
    "\t\t\t\t\t\t\t\t\tAwayWins AS away_wins,\n",
    "\t\t\t\t\t\t\t\t\tAwayDraws AS away_draws,\n",
    "\t\t\t\t\t\t\t\t\tAwayLoses AS away_loses,\n",
    "\t\t\t\t\t\t\t\t\tHomeGoals AS home_goals,\n",
    "\t\t\t\t\t\t\t\t\tHomeGoalsConceded AS home_goals_conceded,\n",
    "\t\t\t\t\t\t\t\t\tAwayGoals AS away_goals,\n",
    "\t\t\t\t\t\t\t\t\tAwayGoalsConceded AS away_goals_conceded\n",
    "\t\t\t\t\t\t\t\t\n",
    "                                FROM league_table\n",
    "\t\t\t\t\t\t\t\tORDER BY season, total_points DESC \n",
    "\t\t\t)\n",
    "\t\t\t\n",
    "SELECT \n",
    "    league_id,\n",
    "    team_id,\n",
    "    league,\n",
    "\tteam,\n",
    "\tSUM(total_points) AS total_points,\n",
    "    \n",
    "\t100.0*SUM(win)/SUM(total_matches) + 100.0*SUM(draw)/SUM(total_matches) \n",
    "    AS overall_effectivity,\n",
    "    \n",
    "    100.0*SUM(lose)/SUM(total_matches) AS overall_ineffectuality,\n",
    "    \n",
    "    CAST(ROUND(1.0*SUM(total_points)/SUM(total_matches))AS INT) AS avg_points_per_match,\n",
    "\tSUM(total_matches) AS total_matches,\n",
    "\n",
    "\tSUM(win) AS total_wins,\n",
    "\tSUM(draw) AS total_draws,\n",
    "\tSUM(lose) AS total_loses,\n",
    "\t\n",
    "\tCAST( 100.0*SUM(win)/SUM(total_matches)  AS REAL) AS win_pct,\n",
    "\tCAST( 100.0*SUM(draw)/SUM(total_matches) AS REAL) AS draw_pct,\n",
    "\tCAST( 100.0*SUM(lose)/SUM(total_matches) AS REAL) AS lose_pct,\n",
    "       \n",
    "\tSUM(total_goals) AS total_goals,\n",
    "\tSUM(total_goals_conceded) AS total_goals_conceded,\n",
    "\tSUM(goals_difference) AS total_goals_difference,\n",
    "\t\n",
    "\tSUM(total_goals)/SUM(total_matches) AS avg_goal_per_match,\n",
    "\tSUM(total_goals_conceded) /SUM(total_matches) AS avg_goal_against_per_match,\n",
    "\t\n",
    "\tSUM(home_g) AS home,\n",
    "\tSUM(away_g) AS away,\n",
    "\tSUM(home_wins) AS total_home_wins,\n",
    "\tSUM(home_draws) AS total_home_draws,\n",
    "\tSUM(home_loses) AS total_home_loses,\n",
    "\tSUM(away_wins) AS total_away_wins,\n",
    "\tSUM(away_draws) AS total_away_draws,\n",
    "\tSUM(away_loses) AS total_away_loses,\n",
    "\t\n",
    "\tCAST( 100.0*SUM(home_wins)/SUM(win) AS REAL) AS avg_home_win,\n",
    "\tCAST( 100.0*SUM(home_draws)/SUM(draw) AS REAL) AS avg_home_draw,\n",
    "\tCAST( 100.0*SUM(home_loses)/SUM(lose) AS REAL) AS avg_home_lose,\n",
    "\t\n",
    "\tCAST( 100.0*SUM(away_wins)/SUM(win) AS REAL) AS avg_away_win,\n",
    "\tCAST( 100.0*SUM(away_draws)/SUM(draw) AS REAL) AS avg_away_draw,\n",
    "\tCAST( 100.0*SUM(away_loses)/SUM(lose) AS REAL) AS avg_away_lose,\n",
    "\t\n",
    "\tCAST( 100.0*SUM(home_wins)/SUM(home_g) AS REAL) AS prop_home_win,\n",
    "\tCAST( 100.0*SUM(away_wins)/SUM(away_g) AS REAL) AS prop_away_win,\n",
    "\t\n",
    "\tCAST( 100.0*SUM(home_draws)/SUM(home_g) AS REAL) AS prop_home_draw,\n",
    "\tCAST( 100.0*SUM(away_draws)/SUM(away_g) AS REAL) AS prop_away_draw,\n",
    "\t\n",
    "\tCAST( 100.0*SUM(home_loses)/SUM(home_g) AS REAL) AS prop_home_lose,\n",
    "\tCAST( 100.0*SUM(away_loses)/SUM(away_g) AS REAL) AS prop_away_lose,\n",
    "\t\n",
    "\tSUM(home_goals) AS total_home_goals,\n",
    "\tSUM(home_goals_conceded) AS total_home_goals_conceded,\n",
    "\tSUM(away_goals) AS total_away_goals,\n",
    "\tSUM(away_goals_conceded) AS total_away_goals_conceded,\n",
    "\t\n",
    "\t\n",
    "\t100.0*SUM(home_goals)/SUM(total_goals) AS prop_home_goals,\n",
    "\t100.0*SUM(away_goals)/SUM(total_goals) AS prop_away_goals,\n",
    "\t100.0*SUM(home_goals_conceded)/SUM(total_goals_conceded) AS prop_home_goals_recv,\n",
    "\t100.0*SUM(away_goals_conceded)/SUM(total_goals_conceded) AS prop_away_goals_recv,\n",
    "\t\n",
    "\tROUND(1.0*SUM(home_goals)/SUM(total_matches) )AS avg_home_goals_per_match,\n",
    "\tROUND(1.0*SUM(away_goals)/SUM(total_matches) )AS avg_away_goals_per_match\n",
    "\t\t\n",
    "FROM league_results\n",
    "GROUP BY team\n",
    "ORDER BY overall_effectivity DESC, total_points DESC, total_goals_difference DESC\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Teams Rank\n",
    "\n",
    "In order to make it easier for anyone to follow the notebook, the table has been saved as [**teams_rank.csv**](./teams_rank.csv) and one can load it using pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>league_id</th>\n",
       "      <th>team_id</th>\n",
       "      <th>league</th>\n",
       "      <th>team</th>\n",
       "      <th>total_points</th>\n",
       "      <th>overall_effectivity</th>\n",
       "      <th>overall_ineffectuality</th>\n",
       "      <th>avg_points_per_match</th>\n",
       "      <th>total_matches</th>\n",
       "      <th>total_wins</th>\n",
       "      <th>...</th>\n",
       "      <th>total_home_goals</th>\n",
       "      <th>total_home_goals_conceded</th>\n",
       "      <th>total_away_goals</th>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "      <th>prop_home_goals</th>\n",
       "      <th>prop_away_goals</th>\n",
       "      <th>prop_home_goals_recv</th>\n",
       "      <th>prop_away_goals_recv</th>\n",
       "      <th>avg_home_goals_per_match</th>\n",
       "      <th>avg_away_goals_per_match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21518</td>\n",
       "      <td>8634</td>\n",
       "      <td>Spain LIGA BBVA</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>745</td>\n",
       "      <td>91.118421</td>\n",
       "      <td>8.881579</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>234</td>\n",
       "      <td>...</td>\n",
       "      <td>495</td>\n",
       "      <td>101</td>\n",
       "      <td>354</td>\n",
       "      <td>131</td>\n",
       "      <td>58.303887</td>\n",
       "      <td>41.696113</td>\n",
       "      <td>43.534483</td>\n",
       "      <td>56.465517</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13274</td>\n",
       "      <td>8593</td>\n",
       "      <td>Netherlands Eredivisie</td>\n",
       "      <td>Ajax</td>\n",
       "      <td>602</td>\n",
       "      <td>88.235294</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>181</td>\n",
       "      <td>...</td>\n",
       "      <td>360</td>\n",
       "      <td>78</td>\n",
       "      <td>287</td>\n",
       "      <td>158</td>\n",
       "      <td>55.641422</td>\n",
       "      <td>44.358578</td>\n",
       "      <td>33.050847</td>\n",
       "      <td>66.949153</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7809</td>\n",
       "      <td>9823</td>\n",
       "      <td>Germany 1. Bundesliga</td>\n",
       "      <td>FC Bayern Munich</td>\n",
       "      <td>623</td>\n",
       "      <td>87.132353</td>\n",
       "      <td>12.867647</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>193</td>\n",
       "      <td>...</td>\n",
       "      <td>382</td>\n",
       "      <td>96</td>\n",
       "      <td>271</td>\n",
       "      <td>115</td>\n",
       "      <td>58.499234</td>\n",
       "      <td>41.500766</td>\n",
       "      <td>45.497630</td>\n",
       "      <td>54.502370</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21518</td>\n",
       "      <td>8633</td>\n",
       "      <td>Spain LIGA BBVA</td>\n",
       "      <td>Real Madrid CF</td>\n",
       "      <td>720</td>\n",
       "      <td>86.842105</td>\n",
       "      <td>13.157895</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>228</td>\n",
       "      <td>...</td>\n",
       "      <td>505</td>\n",
       "      <td>147</td>\n",
       "      <td>338</td>\n",
       "      <td>157</td>\n",
       "      <td>59.905101</td>\n",
       "      <td>40.094899</td>\n",
       "      <td>48.355263</td>\n",
       "      <td>51.644737</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10257</td>\n",
       "      <td>9885</td>\n",
       "      <td>Italy Serie A</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>633</td>\n",
       "      <td>84.717608</td>\n",
       "      <td>15.282392</td>\n",
       "      <td>2</td>\n",
       "      <td>301</td>\n",
       "      <td>189</td>\n",
       "      <td>...</td>\n",
       "      <td>307</td>\n",
       "      <td>124</td>\n",
       "      <td>236</td>\n",
       "      <td>126</td>\n",
       "      <td>56.537753</td>\n",
       "      <td>43.462247</td>\n",
       "      <td>49.600000</td>\n",
       "      <td>50.400000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13274</td>\n",
       "      <td>8640</td>\n",
       "      <td>Netherlands Eredivisie</td>\n",
       "      <td>PSV</td>\n",
       "      <td>581</td>\n",
       "      <td>82.720588</td>\n",
       "      <td>17.279412</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>178</td>\n",
       "      <td>...</td>\n",
       "      <td>370</td>\n",
       "      <td>126</td>\n",
       "      <td>282</td>\n",
       "      <td>168</td>\n",
       "      <td>56.748466</td>\n",
       "      <td>43.251534</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>57.142857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4769</td>\n",
       "      <td>9847</td>\n",
       "      <td>France Ligue 1</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>601</td>\n",
       "      <td>82.565789</td>\n",
       "      <td>17.434211</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>175</td>\n",
       "      <td>...</td>\n",
       "      <td>332</td>\n",
       "      <td>116</td>\n",
       "      <td>236</td>\n",
       "      <td>151</td>\n",
       "      <td>58.450704</td>\n",
       "      <td>41.549296</td>\n",
       "      <td>43.445693</td>\n",
       "      <td>56.554307</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1729</td>\n",
       "      <td>10260</td>\n",
       "      <td>England Premier League</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>633</td>\n",
       "      <td>81.907895</td>\n",
       "      <td>18.092105</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>192</td>\n",
       "      <td>...</td>\n",
       "      <td>338</td>\n",
       "      <td>120</td>\n",
       "      <td>244</td>\n",
       "      <td>160</td>\n",
       "      <td>58.075601</td>\n",
       "      <td>41.924399</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>57.142857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1729</td>\n",
       "      <td>8455</td>\n",
       "      <td>England Premier League</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>598</td>\n",
       "      <td>80.921053</td>\n",
       "      <td>19.078947</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>176</td>\n",
       "      <td>...</td>\n",
       "      <td>333</td>\n",
       "      <td>129</td>\n",
       "      <td>250</td>\n",
       "      <td>157</td>\n",
       "      <td>57.118353</td>\n",
       "      <td>42.881647</td>\n",
       "      <td>45.104895</td>\n",
       "      <td>54.895105</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7809</td>\n",
       "      <td>9789</td>\n",
       "      <td>Germany 1. Bundesliga</td>\n",
       "      <td>Borussia Dortmund</td>\n",
       "      <td>533</td>\n",
       "      <td>80.514706</td>\n",
       "      <td>19.485294</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>157</td>\n",
       "      <td>...</td>\n",
       "      <td>298</td>\n",
       "      <td>112</td>\n",
       "      <td>253</td>\n",
       "      <td>170</td>\n",
       "      <td>54.083485</td>\n",
       "      <td>45.916515</td>\n",
       "      <td>39.716312</td>\n",
       "      <td>60.283688</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   league_id  team_id                  league                 team  \\\n",
       "0      21518     8634         Spain LIGA BBVA         FC Barcelona   \n",
       "1      13274     8593  Netherlands Eredivisie                 Ajax   \n",
       "2       7809     9823   Germany 1. Bundesliga     FC Bayern Munich   \n",
       "3      21518     8633         Spain LIGA BBVA       Real Madrid CF   \n",
       "4      10257     9885           Italy Serie A             Juventus   \n",
       "5      13274     8640  Netherlands Eredivisie                  PSV   \n",
       "6       4769     9847          France Ligue 1  Paris Saint-Germain   \n",
       "7       1729    10260  England Premier League    Manchester United   \n",
       "8       1729     8455  England Premier League              Chelsea   \n",
       "9       7809     9789   Germany 1. Bundesliga    Borussia Dortmund   \n",
       "\n",
       "   total_points  overall_effectivity  overall_ineffectuality  \\\n",
       "0           745            91.118421                8.881579   \n",
       "1           602            88.235294               11.764706   \n",
       "2           623            87.132353               12.867647   \n",
       "3           720            86.842105               13.157895   \n",
       "4           633            84.717608               15.282392   \n",
       "5           581            82.720588               17.279412   \n",
       "6           601            82.565789               17.434211   \n",
       "7           633            81.907895               18.092105   \n",
       "8           598            80.921053               19.078947   \n",
       "9           533            80.514706               19.485294   \n",
       "\n",
       "   avg_points_per_match  total_matches  total_wins            ...             \\\n",
       "0                     2            304         234            ...              \n",
       "1                     2            272         181            ...              \n",
       "2                     2            272         193            ...              \n",
       "3                     2            304         228            ...              \n",
       "4                     2            301         189            ...              \n",
       "5                     2            272         178            ...              \n",
       "6                     2            304         175            ...              \n",
       "7                     2            304         192            ...              \n",
       "8                     2            304         176            ...              \n",
       "9                     2            272         157            ...              \n",
       "\n",
       "   total_home_goals  total_home_goals_conceded  total_away_goals  \\\n",
       "0               495                        101               354   \n",
       "1               360                         78               287   \n",
       "2               382                         96               271   \n",
       "3               505                        147               338   \n",
       "4               307                        124               236   \n",
       "5               370                        126               282   \n",
       "6               332                        116               236   \n",
       "7               338                        120               244   \n",
       "8               333                        129               250   \n",
       "9               298                        112               253   \n",
       "\n",
       "   total_away_goals_conceded  prop_home_goals  prop_away_goals  \\\n",
       "0                        131        58.303887        41.696113   \n",
       "1                        158        55.641422        44.358578   \n",
       "2                        115        58.499234        41.500766   \n",
       "3                        157        59.905101        40.094899   \n",
       "4                        126        56.537753        43.462247   \n",
       "5                        168        56.748466        43.251534   \n",
       "6                        151        58.450704        41.549296   \n",
       "7                        160        58.075601        41.924399   \n",
       "8                        157        57.118353        42.881647   \n",
       "9                        170        54.083485        45.916515   \n",
       "\n",
       "   prop_home_goals_recv  prop_away_goals_recv  avg_home_goals_per_match  \\\n",
       "0             43.534483             56.465517                       2.0   \n",
       "1             33.050847             66.949153                       1.0   \n",
       "2             45.497630             54.502370                       1.0   \n",
       "3             48.355263             51.644737                       2.0   \n",
       "4             49.600000             50.400000                       1.0   \n",
       "5             42.857143             57.142857                       1.0   \n",
       "6             43.445693             56.554307                       1.0   \n",
       "7             42.857143             57.142857                       1.0   \n",
       "8             45.104895             54.895105                       1.0   \n",
       "9             39.716312             60.283688                       1.0   \n",
       "\n",
       "   avg_away_goals_per_match  \n",
       "0                       1.0  \n",
       "1                       1.0  \n",
       "2                       1.0  \n",
       "3                       1.0  \n",
       "4                       1.0  \n",
       "5                       1.0  \n",
       "6                       1.0  \n",
       "7                       1.0  \n",
       "8                       1.0  \n",
       "9                       1.0  \n",
       "\n",
       "[10 rows x 50 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#path where our csv file exists\n",
    "path = './data/'\n",
    "\n",
    "#csv file\n",
    "file = 'teams_rank.csv'\n",
    "\n",
    "#Retrieving the data from our csv file\n",
    "df_teams = pd.read_csv(path+file)\n",
    "\n",
    "#Shows top 10 teams from all leagues\n",
    "df_teams.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As one can see the query was able to compute the results of all teams from 2008 until 2015 seasons.\n",
    "\n",
    "The top 10 teams displayed above are determined based on cummulative statistics and sorted by their overall effectivity, which is the percentage a team wins/draws a game out of all the games played until the last match provided in our dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The data we will analyze includes 189 teams\n"
     ]
    }
   ],
   "source": [
    "#Number of teams in our dataset\n",
    "print('The data we will analyze includes {} teams'.format(df_teams.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above line tell us that we have 189 teams."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Performance of leagues\n",
    "\n",
    "Once we extracted the teams' statistics over all season, we can compute the performance of each league doing an average on all the teams that belong to the league.\n",
    "\n",
    "This is a perfect task for pandas and the groupby and mean methods which will helps us gather all teams from a league and average their statistics to compute the league statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_points</th>\n",
       "      <th>overall_effectivity</th>\n",
       "      <th>overall_ineffectuality</th>\n",
       "      <th>avg_points_per_match</th>\n",
       "      <th>total_matches</th>\n",
       "      <th>total_wins</th>\n",
       "      <th>total_draws</th>\n",
       "      <th>total_loses</th>\n",
       "      <th>win_pct</th>\n",
       "      <th>draw_pct</th>\n",
       "      <th>...</th>\n",
       "      <th>total_home_goals</th>\n",
       "      <th>total_home_goals_conceded</th>\n",
       "      <th>total_away_goals</th>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "      <th>prop_home_goals</th>\n",
       "      <th>prop_away_goals</th>\n",
       "      <th>prop_home_goals_recv</th>\n",
       "      <th>prop_away_goals_recv</th>\n",
       "      <th>avg_home_goals_per_match</th>\n",
       "      <th>avg_away_goals_per_match</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>league</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>France Ligue 1</th>\n",
       "      <td>236.028571</td>\n",
       "      <td>58.512710</td>\n",
       "      <td>41.487290</td>\n",
       "      <td>1.171429</td>\n",
       "      <td>173.714286</td>\n",
       "      <td>62.314286</td>\n",
       "      <td>49.085714</td>\n",
       "      <td>62.314286</td>\n",
       "      <td>30.779270</td>\n",
       "      <td>27.733441</td>\n",
       "      <td>...</td>\n",
       "      <td>121.857143</td>\n",
       "      <td>90.342857</td>\n",
       "      <td>90.342857</td>\n",
       "      <td>121.857143</td>\n",
       "      <td>58.330381</td>\n",
       "      <td>41.669619</td>\n",
       "      <td>43.390985</td>\n",
       "      <td>56.609015</td>\n",
       "      <td>0.914286</td>\n",
       "      <td>0.371429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>England Premier League</th>\n",
       "      <td>245.205882</td>\n",
       "      <td>58.224421</td>\n",
       "      <td>41.775579</td>\n",
       "      <td>1.235294</td>\n",
       "      <td>178.823529</td>\n",
       "      <td>66.382353</td>\n",
       "      <td>46.058824</td>\n",
       "      <td>66.382353</td>\n",
       "      <td>32.601817</td>\n",
       "      <td>25.622604</td>\n",
       "      <td>...</td>\n",
       "      <td>138.676471</td>\n",
       "      <td>103.676471</td>\n",
       "      <td>103.676471</td>\n",
       "      <td>138.676471</td>\n",
       "      <td>56.787461</td>\n",
       "      <td>43.212539</td>\n",
       "      <td>42.891962</td>\n",
       "      <td>57.108038</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.529412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy Serie A</th>\n",
       "      <td>257.968750</td>\n",
       "      <td>57.921813</td>\n",
       "      <td>42.078187</td>\n",
       "      <td>1.218750</td>\n",
       "      <td>188.562500</td>\n",
       "      <td>69.406250</td>\n",
       "      <td>49.750000</td>\n",
       "      <td>69.406250</td>\n",
       "      <td>31.370972</td>\n",
       "      <td>26.550840</td>\n",
       "      <td>...</td>\n",
       "      <td>141.500000</td>\n",
       "      <td>105.218750</td>\n",
       "      <td>105.218750</td>\n",
       "      <td>141.500000</td>\n",
       "      <td>57.700007</td>\n",
       "      <td>42.299993</td>\n",
       "      <td>42.794959</td>\n",
       "      <td>57.205041</td>\n",
       "      <td>0.875000</td>\n",
       "      <td>0.406250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands Eredivisie</th>\n",
       "      <td>270.520000</td>\n",
       "      <td>57.289216</td>\n",
       "      <td>42.710784</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>195.840000</td>\n",
       "      <td>74.680000</td>\n",
       "      <td>46.480000</td>\n",
       "      <td>74.680000</td>\n",
       "      <td>33.686275</td>\n",
       "      <td>23.602941</td>\n",
       "      <td>...</td>\n",
       "      <td>174.280000</td>\n",
       "      <td>127.400000</td>\n",
       "      <td>127.400000</td>\n",
       "      <td>174.280000</td>\n",
       "      <td>58.942504</td>\n",
       "      <td>41.057496</td>\n",
       "      <td>42.048914</td>\n",
       "      <td>57.951086</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain LIGA BBVA</th>\n",
       "      <td>255.030303</td>\n",
       "      <td>56.912641</td>\n",
       "      <td>43.087359</td>\n",
       "      <td>1.181818</td>\n",
       "      <td>184.242424</td>\n",
       "      <td>70.787879</td>\n",
       "      <td>42.666667</td>\n",
       "      <td>70.787879</td>\n",
       "      <td>33.450957</td>\n",
       "      <td>23.461685</td>\n",
       "      <td>...</td>\n",
       "      <td>150.272727</td>\n",
       "      <td>104.636364</td>\n",
       "      <td>104.636364</td>\n",
       "      <td>150.272727</td>\n",
       "      <td>58.255259</td>\n",
       "      <td>41.744741</td>\n",
       "      <td>41.178577</td>\n",
       "      <td>58.821423</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.454545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany 1. Bundesliga</th>\n",
       "      <td>224.900000</td>\n",
       "      <td>56.813842</td>\n",
       "      <td>43.186158</td>\n",
       "      <td>1.166667</td>\n",
       "      <td>163.200000</td>\n",
       "      <td>61.700000</td>\n",
       "      <td>39.800000</td>\n",
       "      <td>61.700000</td>\n",
       "      <td>31.686158</td>\n",
       "      <td>25.127684</td>\n",
       "      <td>...</td>\n",
       "      <td>132.733333</td>\n",
       "      <td>104.033333</td>\n",
       "      <td>104.033333</td>\n",
       "      <td>132.733333</td>\n",
       "      <td>56.165352</td>\n",
       "      <td>43.834648</td>\n",
       "      <td>45.336792</td>\n",
       "      <td>54.663208</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        total_points  overall_effectivity  \\\n",
       "league                                                      \n",
       "France Ligue 1            236.028571            58.512710   \n",
       "England Premier League    245.205882            58.224421   \n",
       "Italy Serie A             257.968750            57.921813   \n",
       "Netherlands Eredivisie    270.520000            57.289216   \n",
       "Spain LIGA BBVA           255.030303            56.912641   \n",
       "Germany 1. Bundesliga     224.900000            56.813842   \n",
       "\n",
       "                        overall_ineffectuality  avg_points_per_match  \\\n",
       "league                                                                 \n",
       "France Ligue 1                       41.487290              1.171429   \n",
       "England Premier League               41.775579              1.235294   \n",
       "Italy Serie A                        42.078187              1.218750   \n",
       "Netherlands Eredivisie               42.710784              1.200000   \n",
       "Spain LIGA BBVA                      43.087359              1.181818   \n",
       "Germany 1. Bundesliga                43.186158              1.166667   \n",
       "\n",
       "                        total_matches  total_wins  total_draws  total_loses  \\\n",
       "league                                                                        \n",
       "France Ligue 1             173.714286   62.314286    49.085714    62.314286   \n",
       "England Premier League     178.823529   66.382353    46.058824    66.382353   \n",
       "Italy Serie A              188.562500   69.406250    49.750000    69.406250   \n",
       "Netherlands Eredivisie     195.840000   74.680000    46.480000    74.680000   \n",
       "Spain LIGA BBVA            184.242424   70.787879    42.666667    70.787879   \n",
       "Germany 1. Bundesliga      163.200000   61.700000    39.800000    61.700000   \n",
       "\n",
       "                          win_pct   draw_pct            ...             \\\n",
       "league                                                  ...              \n",
       "France Ligue 1          30.779270  27.733441            ...              \n",
       "England Premier League  32.601817  25.622604            ...              \n",
       "Italy Serie A           31.370972  26.550840            ...              \n",
       "Netherlands Eredivisie  33.686275  23.602941            ...              \n",
       "Spain LIGA BBVA         33.450957  23.461685            ...              \n",
       "Germany 1. Bundesliga   31.686158  25.127684            ...              \n",
       "\n",
       "                        total_home_goals  total_home_goals_conceded  \\\n",
       "league                                                                \n",
       "France Ligue 1                121.857143                  90.342857   \n",
       "England Premier League        138.676471                 103.676471   \n",
       "Italy Serie A                 141.500000                 105.218750   \n",
       "Netherlands Eredivisie        174.280000                 127.400000   \n",
       "Spain LIGA BBVA               150.272727                 104.636364   \n",
       "Germany 1. Bundesliga         132.733333                 104.033333   \n",
       "\n",
       "                        total_away_goals  total_away_goals_conceded  \\\n",
       "league                                                                \n",
       "France Ligue 1                 90.342857                 121.857143   \n",
       "England Premier League        103.676471                 138.676471   \n",
       "Italy Serie A                 105.218750                 141.500000   \n",
       "Netherlands Eredivisie        127.400000                 174.280000   \n",
       "Spain LIGA BBVA               104.636364                 150.272727   \n",
       "Germany 1. Bundesliga         104.033333                 132.733333   \n",
       "\n",
       "                        prop_home_goals  prop_away_goals  \\\n",
       "league                                                     \n",
       "France Ligue 1                58.330381        41.669619   \n",
       "England Premier League        56.787461        43.212539   \n",
       "Italy Serie A                 57.700007        42.299993   \n",
       "Netherlands Eredivisie        58.942504        41.057496   \n",
       "Spain LIGA BBVA               58.255259        41.744741   \n",
       "Germany 1. Bundesliga         56.165352        43.834648   \n",
       "\n",
       "                        prop_home_goals_recv  prop_away_goals_recv  \\\n",
       "league                                                               \n",
       "France Ligue 1                     43.390985             56.609015   \n",
       "England Premier League             42.891962             57.108038   \n",
       "Italy Serie A                      42.794959             57.205041   \n",
       "Netherlands Eredivisie             42.048914             57.951086   \n",
       "Spain LIGA BBVA                    41.178577             58.821423   \n",
       "Germany 1. Bundesliga              45.336792             54.663208   \n",
       "\n",
       "                        avg_home_goals_per_match  avg_away_goals_per_match  \n",
       "league                                                                      \n",
       "France Ligue 1                          0.914286                  0.371429  \n",
       "England Premier League                  0.970588                  0.529412  \n",
       "Italy Serie A                           0.875000                  0.406250  \n",
       "Netherlands Eredivisie                  0.960000                  0.640000  \n",
       "Spain LIGA BBVA                         0.969697                  0.454545  \n",
       "Germany 1. Bundesliga                   0.900000                  0.666667  \n",
       "\n",
       "[6 rows x 46 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Grouping our dataset by League in which each team plays and\n",
    "# perform and average with all teams that belong to such league\n",
    "df_leagues = df_teams.groupby('league').mean()\n",
    "df_leagues.sort_values(by='overall_effectivity', ascending=False, inplace=True)\n",
    "\n",
    "#No need an average ID of teams and league as this are unique for each, drop such columns\n",
    "df_leagues.drop(['league_id','team_id'], axis=1, inplace=True)\n",
    "df_leagues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point we have all the data needed and we have even gone beyond and done some descriptive statistics to our current values. However, before we proceed, it will be a good idea to have a single table in which we add the league performance/effectivity to all our results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>league</th>\n",
       "      <th>league_overall_effectivity</th>\n",
       "      <th>league_total_goals</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>France Ligue 1</td>\n",
       "      <td>58.512710</td>\n",
       "      <td>212.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>England Premier League</td>\n",
       "      <td>58.224421</td>\n",
       "      <td>242.352941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Italy Serie A</td>\n",
       "      <td>57.921813</td>\n",
       "      <td>246.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Netherlands Eredivisie</td>\n",
       "      <td>57.289216</td>\n",
       "      <td>301.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Spain LIGA BBVA</td>\n",
       "      <td>56.912641</td>\n",
       "      <td>254.909091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Germany 1. Bundesliga</td>\n",
       "      <td>56.813842</td>\n",
       "      <td>236.766667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   league  league_overall_effectivity  league_total_goals\n",
       "0          France Ligue 1                   58.512710          212.200000\n",
       "1  England Premier League                   58.224421          242.352941\n",
       "2           Italy Serie A                   57.921813          246.718750\n",
       "3  Netherlands Eredivisie                   57.289216          301.680000\n",
       "4         Spain LIGA BBVA                   56.912641          254.909091\n",
       "5   Germany 1. Bundesliga                   56.813842          236.766667"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Retrieving only the mean total goals and effectivity of each league\n",
    "df_league_eff = df_leagues[['overall_effectivity','total_goals']].copy()\n",
    "\n",
    "#Rename the columns to prefix them with 'league_' and move league to be a column and not an index\n",
    "df_league_eff.rename(columns={'overall_effectivity':'league_overall_effectivity',\n",
    "                              'total_goals':'league_total_goals'},\n",
    "                                 inplace=True)\n",
    "df_league_eff.reset_index(level=0,inplace=True)\n",
    "df_league_eff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>league_id</th>\n",
       "      <th>team_id</th>\n",
       "      <th>league</th>\n",
       "      <th>team</th>\n",
       "      <th>total_points</th>\n",
       "      <th>overall_effectivity</th>\n",
       "      <th>overall_ineffectuality</th>\n",
       "      <th>avg_points_per_match</th>\n",
       "      <th>total_matches</th>\n",
       "      <th>total_wins</th>\n",
       "      <th>...</th>\n",
       "      <th>total_away_goals</th>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "      <th>prop_home_goals</th>\n",
       "      <th>prop_away_goals</th>\n",
       "      <th>prop_home_goals_recv</th>\n",
       "      <th>prop_away_goals_recv</th>\n",
       "      <th>avg_home_goals_per_match</th>\n",
       "      <th>avg_away_goals_per_match</th>\n",
       "      <th>league_overall_effectivity</th>\n",
       "      <th>league_total_goals</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21518</td>\n",
       "      <td>8634</td>\n",
       "      <td>Spain LIGA BBVA</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>745</td>\n",
       "      <td>91.118421</td>\n",
       "      <td>8.881579</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>234</td>\n",
       "      <td>...</td>\n",
       "      <td>354</td>\n",
       "      <td>131</td>\n",
       "      <td>58.303887</td>\n",
       "      <td>41.696113</td>\n",
       "      <td>43.534483</td>\n",
       "      <td>56.465517</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.912641</td>\n",
       "      <td>254.909091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13274</td>\n",
       "      <td>8593</td>\n",
       "      <td>Netherlands Eredivisie</td>\n",
       "      <td>Ajax</td>\n",
       "      <td>602</td>\n",
       "      <td>88.235294</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>181</td>\n",
       "      <td>...</td>\n",
       "      <td>287</td>\n",
       "      <td>158</td>\n",
       "      <td>55.641422</td>\n",
       "      <td>44.358578</td>\n",
       "      <td>33.050847</td>\n",
       "      <td>66.949153</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>57.289216</td>\n",
       "      <td>301.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7809</td>\n",
       "      <td>9823</td>\n",
       "      <td>Germany 1. Bundesliga</td>\n",
       "      <td>FC Bayern Munich</td>\n",
       "      <td>623</td>\n",
       "      <td>87.132353</td>\n",
       "      <td>12.867647</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>193</td>\n",
       "      <td>...</td>\n",
       "      <td>271</td>\n",
       "      <td>115</td>\n",
       "      <td>58.499234</td>\n",
       "      <td>41.500766</td>\n",
       "      <td>45.497630</td>\n",
       "      <td>54.502370</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.813842</td>\n",
       "      <td>236.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21518</td>\n",
       "      <td>8633</td>\n",
       "      <td>Spain LIGA BBVA</td>\n",
       "      <td>Real Madrid CF</td>\n",
       "      <td>720</td>\n",
       "      <td>86.842105</td>\n",
       "      <td>13.157895</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>228</td>\n",
       "      <td>...</td>\n",
       "      <td>338</td>\n",
       "      <td>157</td>\n",
       "      <td>59.905101</td>\n",
       "      <td>40.094899</td>\n",
       "      <td>48.355263</td>\n",
       "      <td>51.644737</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.912641</td>\n",
       "      <td>254.909091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10257</td>\n",
       "      <td>9885</td>\n",
       "      <td>Italy Serie A</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>633</td>\n",
       "      <td>84.717608</td>\n",
       "      <td>15.282392</td>\n",
       "      <td>2</td>\n",
       "      <td>301</td>\n",
       "      <td>189</td>\n",
       "      <td>...</td>\n",
       "      <td>236</td>\n",
       "      <td>126</td>\n",
       "      <td>56.537753</td>\n",
       "      <td>43.462247</td>\n",
       "      <td>49.600000</td>\n",
       "      <td>50.400000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>57.921813</td>\n",
       "      <td>246.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13274</td>\n",
       "      <td>8640</td>\n",
       "      <td>Netherlands Eredivisie</td>\n",
       "      <td>PSV</td>\n",
       "      <td>581</td>\n",
       "      <td>82.720588</td>\n",
       "      <td>17.279412</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>178</td>\n",
       "      <td>...</td>\n",
       "      <td>282</td>\n",
       "      <td>168</td>\n",
       "      <td>56.748466</td>\n",
       "      <td>43.251534</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>57.142857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>57.289216</td>\n",
       "      <td>301.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4769</td>\n",
       "      <td>9847</td>\n",
       "      <td>France Ligue 1</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>601</td>\n",
       "      <td>82.565789</td>\n",
       "      <td>17.434211</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>175</td>\n",
       "      <td>...</td>\n",
       "      <td>236</td>\n",
       "      <td>151</td>\n",
       "      <td>58.450704</td>\n",
       "      <td>41.549296</td>\n",
       "      <td>43.445693</td>\n",
       "      <td>56.554307</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>58.512710</td>\n",
       "      <td>212.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1729</td>\n",
       "      <td>10260</td>\n",
       "      <td>England Premier League</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>633</td>\n",
       "      <td>81.907895</td>\n",
       "      <td>18.092105</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>192</td>\n",
       "      <td>...</td>\n",
       "      <td>244</td>\n",
       "      <td>160</td>\n",
       "      <td>58.075601</td>\n",
       "      <td>41.924399</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>57.142857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>58.224421</td>\n",
       "      <td>242.352941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1729</td>\n",
       "      <td>8455</td>\n",
       "      <td>England Premier League</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>598</td>\n",
       "      <td>80.921053</td>\n",
       "      <td>19.078947</td>\n",
       "      <td>2</td>\n",
       "      <td>304</td>\n",
       "      <td>176</td>\n",
       "      <td>...</td>\n",
       "      <td>250</td>\n",
       "      <td>157</td>\n",
       "      <td>57.118353</td>\n",
       "      <td>42.881647</td>\n",
       "      <td>45.104895</td>\n",
       "      <td>54.895105</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>58.224421</td>\n",
       "      <td>242.352941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7809</td>\n",
       "      <td>9789</td>\n",
       "      <td>Germany 1. Bundesliga</td>\n",
       "      <td>Borussia Dortmund</td>\n",
       "      <td>533</td>\n",
       "      <td>80.514706</td>\n",
       "      <td>19.485294</td>\n",
       "      <td>2</td>\n",
       "      <td>272</td>\n",
       "      <td>157</td>\n",
       "      <td>...</td>\n",
       "      <td>253</td>\n",
       "      <td>170</td>\n",
       "      <td>54.083485</td>\n",
       "      <td>45.916515</td>\n",
       "      <td>39.716312</td>\n",
       "      <td>60.283688</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.813842</td>\n",
       "      <td>236.766667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   league_id  team_id                  league                 team  \\\n",
       "0      21518     8634         Spain LIGA BBVA         FC Barcelona   \n",
       "1      13274     8593  Netherlands Eredivisie                 Ajax   \n",
       "2       7809     9823   Germany 1. Bundesliga     FC Bayern Munich   \n",
       "3      21518     8633         Spain LIGA BBVA       Real Madrid CF   \n",
       "4      10257     9885           Italy Serie A             Juventus   \n",
       "5      13274     8640  Netherlands Eredivisie                  PSV   \n",
       "6       4769     9847          France Ligue 1  Paris Saint-Germain   \n",
       "7       1729    10260  England Premier League    Manchester United   \n",
       "8       1729     8455  England Premier League              Chelsea   \n",
       "9       7809     9789   Germany 1. Bundesliga    Borussia Dortmund   \n",
       "\n",
       "   total_points  overall_effectivity  overall_ineffectuality  \\\n",
       "0           745            91.118421                8.881579   \n",
       "1           602            88.235294               11.764706   \n",
       "2           623            87.132353               12.867647   \n",
       "3           720            86.842105               13.157895   \n",
       "4           633            84.717608               15.282392   \n",
       "5           581            82.720588               17.279412   \n",
       "6           601            82.565789               17.434211   \n",
       "7           633            81.907895               18.092105   \n",
       "8           598            80.921053               19.078947   \n",
       "9           533            80.514706               19.485294   \n",
       "\n",
       "   avg_points_per_match  total_matches  total_wins         ...          \\\n",
       "0                     2            304         234         ...           \n",
       "1                     2            272         181         ...           \n",
       "2                     2            272         193         ...           \n",
       "3                     2            304         228         ...           \n",
       "4                     2            301         189         ...           \n",
       "5                     2            272         178         ...           \n",
       "6                     2            304         175         ...           \n",
       "7                     2            304         192         ...           \n",
       "8                     2            304         176         ...           \n",
       "9                     2            272         157         ...           \n",
       "\n",
       "   total_away_goals  total_away_goals_conceded  prop_home_goals  \\\n",
       "0               354                        131        58.303887   \n",
       "1               287                        158        55.641422   \n",
       "2               271                        115        58.499234   \n",
       "3               338                        157        59.905101   \n",
       "4               236                        126        56.537753   \n",
       "5               282                        168        56.748466   \n",
       "6               236                        151        58.450704   \n",
       "7               244                        160        58.075601   \n",
       "8               250                        157        57.118353   \n",
       "9               253                        170        54.083485   \n",
       "\n",
       "   prop_away_goals  prop_home_goals_recv  prop_away_goals_recv  \\\n",
       "0        41.696113             43.534483             56.465517   \n",
       "1        44.358578             33.050847             66.949153   \n",
       "2        41.500766             45.497630             54.502370   \n",
       "3        40.094899             48.355263             51.644737   \n",
       "4        43.462247             49.600000             50.400000   \n",
       "5        43.251534             42.857143             57.142857   \n",
       "6        41.549296             43.445693             56.554307   \n",
       "7        41.924399             42.857143             57.142857   \n",
       "8        42.881647             45.104895             54.895105   \n",
       "9        45.916515             39.716312             60.283688   \n",
       "\n",
       "   avg_home_goals_per_match  avg_away_goals_per_match  \\\n",
       "0                       2.0                       1.0   \n",
       "1                       1.0                       1.0   \n",
       "2                       1.0                       1.0   \n",
       "3                       2.0                       1.0   \n",
       "4                       1.0                       1.0   \n",
       "5                       1.0                       1.0   \n",
       "6                       1.0                       1.0   \n",
       "7                       1.0                       1.0   \n",
       "8                       1.0                       1.0   \n",
       "9                       1.0                       1.0   \n",
       "\n",
       "   league_overall_effectivity  league_total_goals  \n",
       "0                   56.912641          254.909091  \n",
       "1                   57.289216          301.680000  \n",
       "2                   56.813842          236.766667  \n",
       "3                   56.912641          254.909091  \n",
       "4                   57.921813          246.718750  \n",
       "5                   57.289216          301.680000  \n",
       "6                   58.512710          212.200000  \n",
       "7                   58.224421          242.352941  \n",
       "8                   58.224421          242.352941  \n",
       "9                   56.813842          236.766667  \n",
       "\n",
       "[10 rows x 52 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merge the previous dataframe with each league information into our original dataframe which includes all teams\n",
    "df_all = pd.merge( left=df_teams, right=df_league_eff, on='league')\n",
    "df_all.sort_values(by='overall_effectivity', ascending=False, inplace=True)\n",
    "df_all.reset_index(drop=True,inplace=True)\n",
    "df_all.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the merge above we could add the league average effetivity to each row, so that a team depending on the league the belong can get the overall effectivity of their league.\n",
    "\n",
    "This previous step makes us ready to explore our data and find insights from it to answer our questions later on and maybe dig in more into relations of league and teams."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='eda'></a>\n",
    "## Exploratory Data Analysis\n",
    "\n",
    "In this section we will take advantage of our collected and cleaned data to understand the motivation of the analysis and the questions during <a href='#cleaning'>data cleaning</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='teams'></a>\n",
    "### Teams' Effectivity Distribution\n",
    "\n",
    "The **overall_effectivity** column gives us the team effectivity. We can use this column to plot a histogram of all teams effectivity. It will also be a good idea to use a boxplot to find the quartiles, minimum, maximum and some outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean: 57.65\n",
      "Standard Dev: 12.13\n",
      "Median: 56.58\n"
     ]
    },
    {
     "data": {
      "image/png": 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Uk0W0JEmS1JNFtCRJktSTRbQkSZLUk0W0JEmS1JNFtCRJktSTRbQkSZLU08iK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\nJPX0/wB22+ZQTqGrbQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110130390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Calculate mean, standard deviation and mean of teams' overall effectivity\n",
    "mean_eff = df_all['overall_effectivity'].mean()\n",
    "std_eff = df_all['overall_effectivity'].std()\n",
    "median_eff = df_all['overall_effectivity'].median()\n",
    "print('Mean: {:.2f}\\nStandard Dev: {:.2f}\\nMedian: {:.2f}'\\\n",
    "      .format(mean_eff, std_eff, median_eff))\n",
    "\n",
    "#Plot teams effectivity histogram and boxplot to understand what kind of distribution it follows\n",
    "plt.figure(figsize=(12,4))\n",
    "plt.subplot(1,2,1)\n",
    "plt.axvline(mean_eff, color='r', linewidth=2)\n",
    "plt.hist(df_all['overall_effectivity'], bins=8)\n",
    "plt.xlabel('Team Effectivity [%]')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('All Teams Effectivity Distribution');\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.boxplot(df_all['overall_effectivity'], vert=0)\n",
    "plt.xlabel('Team Effectivity [%]')\n",
    "plt.title('Teams Effectivity Distribution');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the above we can see that the distribution of the teams effectivity is close to normal, but we are a little skewed to the right. This is caused by the outliers that we see on the boxplot. The interesting part is that most outliers are in the better effectivity side, meaning there are some star teams in our dataset and they must be part of the top 10 teams we showed above.\n",
    "\n",
    "In addition, the standard deviation is 12.13% effectivity and the mean is 57.63% effectivity which means that average teams win/draw more than they lose.\n",
    "\n",
    "If teams win/draw more to have a >50% effectivity, it will be interesting to check if scoring or receiving scores is related to the wins/draws."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='effectivityVSgoals_scored'></a>\n",
    "### Teams' Effectivity Correlation to Scored Goals\n",
    "\n",
    "Here we try to visualize if there might be a correlation of effectivity and scored goals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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T6TFQpq3PzF6KqMSIKtUXNL7HObfXzGYBG81srDTraKMFj4r8nXP3APcALF++POlvBksX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\n/Zwpvx4bs9fZdHQUQoixSIJrMX6NoCbu1qZOvvb4GxzuDhAMR7AdMPP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ULqXUTqXU+TLm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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11010f940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Scatter plot of a team effectivity against the total goals at home and away\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.scatter(x=df_all['overall_effectivity'],y=df_all['total_home_goals'], \\\n",
    "            alpha=0.6, label = 'Home')\n",
    "plt.scatter(x=df_all['overall_effectivity'],y=df_all['total_away_goals'], \\\n",
    "            alpha=0.6, color='r', label = 'Away')\n",
    "plt.xlabel('Effectivity [%]')\n",
    "plt.ylabel('Goals')\n",
    "plt.title('Correlation of Effectivty and Scoring')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the graph we noticed that there seem to be a positive correlation, so it will be nice to know the actual correlation coefficient to prove our idea true."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>overall_effectivity</th>\n",
       "      <th>total_home_goals</th>\n",
       "      <th>total_away_goals</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>overall_effectivity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.857166</td>\n",
       "      <td>0.868547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_home_goals</th>\n",
       "      <td>0.857166</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.981976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_away_goals</th>\n",
       "      <td>0.868547</td>\n",
       "      <td>0.981976</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     overall_effectivity  total_home_goals  total_away_goals\n",
       "overall_effectivity             1.000000          0.857166          0.868547\n",
       "total_home_goals                0.857166          1.000000          0.981976\n",
       "total_away_goals                0.868547          0.981976          1.000000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Calculate pearson coefficient to verify if there is correlation between the chosen columns\n",
    "df_all[['overall_effectivity','total_home_goals','total_away_goals']].corr('pearson')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pearson coefficient shows us that effectivity is strongly correlated to the goals scored. \n",
    "\n",
    ">**Insight:** We found an interesting correlation. It seems that goals scored at home and goals scored away are even stronger correlated, meaning that there is a relationship with a team ascoring home versus away. This might be something interesting to check later on"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='effectivityVSgoals_recv'></a>\n",
    "### Teams' Effectivity Correlation to Received Goals\n",
    "\n",
    "After proving that the scored goals are related to effectivity, we would like to know if the goals received is also related to the effectivity. We will first visualize this in a scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xrkjoCxke9oK6VasOL0vs4U7sTS3noK+UP2ulvG8iEWVma5xzrenWU1qISL4V\nuqyVFBe/6Q1+yt2Vm1L9rJVbKUCRIqO0EBGRKPOb3qDBsuVDVYdEIk3BtYhIlPnN71UFi/KhCymR\nSFNwLSISZX5zazVYtnzoQkok0hRci4hEVSazDKqCRfnQhZRIpGlAo4hIVGU6SDFPA/jWbeli+dpt\nbO3sZfbUOi5fOJMFc6aE/rqSoKEBHn/c+/nMM/N3IaUqJSJpKbgWEQlLroHI5s1ej3WixNzaAgQ6\n67Z0cfMDm2isrWJGUy2dBwa4+YFNXHfh3OAD7JD2r6gvDhIrhfzVXx0uuZjv11aVEpGkQksLMbPZ\nZvZ7M3vWzDaY2Wdiy6ea2QNm9nzs+5TYcjOzW8zsBTN7yswWhtU2EZHQZZLSMfZ58Ylgtmw5cpBa\nPLc22+3naPnabczb9hwfvPvrXP3VJXzw7q8zb9tzLF+7LbsNJpv4JqT9i18cdB4YGHVxsG5LV07b\nzZtCVgpRlRIRX8LMuR4CljrnTgbOBpaY2euBfwD+2zl3AvDfsccAFwMnxL4+DnwvxLaJiIQrm0Bk\n9Wr2/f0/8vRfXuT3B6p5oaKBwbVPwosvHplbW6BAp7L9CS79xe3U9XTTPW0GdT3dXPqL26lsfyLz\njaUKoEPav+Vrt9FYW8WkiVVUmDFpYhWNtVXZXxzkWyErhahKiYgvoQXXzrntzrm1sZ97gGeBmcC7\ngfhfx2XApbGf3w38P+d5HJhsZseE1T4RkVBlEYjs+s7tPNNr7K2up66mkh3NM9k44zh6t247cpBi\ngQKdi9b8lv219fTVN4IZffWN7K+t56I1v818Y6kC6JD2b2tnLw21ozMiG2or2drZm9N286aQlUJU\npUTEl7xUCzGzY4HTgT8DM5xz28ELwIGjYqvNBLYmPK0jtkxEpPhkEYh0btjEUMMkqiorAKOqsoK9\nR89ia0OzN9X5rbdCWxvrtnTxZzeJx/+ymSde6mT3/n5f2w/CSX172Ftdx+DQMOAYHBpmb3UdJ/Xt\nyXxjqQLokAK52VPr2N83NGrZ/r4hZk+ty2xDydJZwlbISiGlWKWkUO+jlLTQg2szawCWA591zu1L\nteo4y9w42/u4mbWbWfuuXbuCaqaISLCyCEQ6Js2gceDAqGWNAwfomDRj5HE8Z/gPb1jElIGDVOzd\ny1Nbu+l65dXD2w8xYGh6/VxObzJqqiroHThETVUFpzcZTa+fm/nGUgXQIQVyly+cSU/fIPsODjLs\nHPsODtJte9JDAAAgAElEQVTTN8jlCzPoy8k0HzzI96MQJRfj7b/xRhgYgCeegBUrYMMGeN/7incw\nY4HGLUjpCzW4NrMqvMD6x865X8QW74yne8S+vxpb3gHMTnj6LOCVsdt0zn3fOdfqnGudPn16eI0X\nEclFFkHQ8xdfTmVPD7UHesA5ag/0UNnTw/MXXz6yTjxnuPuU03nwyiUMTJ7KjH272DRU420fwg0Y\nFi9myuBBzpxcwVtOaObMyRVMGTyYXdCbKoAOKYhcMGcK1104l6n11ezc28fU+urMK51kkg8eRgDX\n1ubdxUi4mxGaxPZXV8Nf/gI7doAZ9PXB7bcXbzCqAZoSEnPuiM7hYDZsZng51Z3Ouc8mLP+/wB7n\n3NfM7B+Aqc65683sHcA1wCLgLOAW51zKvxitra2uvb09lPaLiGQq1xJv67Z0cf/t9/PWP/8XMzq3\ns3PqMTx01sVc9onLRrZz1Z2rmdFUS4Udvtk37Bw79/Zx19VtXg/j7t2Ha2KDF7Q2N8OttwZThi7I\nEnnFWDd50SIvUK5I6J8aHvYuAlatGr1umvcj8hLb/8ADXmBdUQFVVTBlCvT2wrnnws9/XuiWZi6T\n91EEMLM1zrnWdOuFWef6jcCHgKfNbF1s2T8BXwN+amZ/A2wB3hP73Sq8wPoFoBf4SIhtExEJVBD1\nnxfMmQKfuIzlZ7YlDX5nT62j88AAkyZWjSwblTOcojZ2YDWqg5ysJk8T3wSqpeXIgDlZPni6WuVR\nl9j+XbugstILRgcHoabGW/5EFpVioiCT91EkA6EF1865Rxg/jxrggnHWd8CSsNojIhKmxBJvwMj3\n5Wu3ZRS4LpgzJeX6ly+cyc0PbAK8Khf7+4bo6RvkY+fFAoIUAUNQbSx7ixd7qRLgBcrxiVyWLj1y\n3WIP4MZr//Cw13Nd7DJ5H0UykJdqISIipS5fJd7S5gynyGMu+jJ0YfM78DCTfPBir7CR2P7mZm9A\n49CQF4wODHhpIWeeWehWZqcQg0OlLISWc50PyrmWYlTUUy9LUjesWH9Eusa+g4NMra/mpktPSf3k\noPOOk2wvpzaWusSpvRN7MYMItooxrzxRvP1PPgn/+78wYYKXGlJTA9Onw7e/XVz7I5IlvznXCq5F\n8igx5zXxln7GOa8SOVm/tymCunVHnxDohZjOvxSKfeBhvhT7hYJIDhRci0SQeg5LW9q7EuMFJsuW\njRvU7appYOmbPx54IFxSd06CDPTyUTlCgalIUYtCtRARGWNrZy8zmmpHLVPOa+lIORgxsYd65ky6\ntrzC7k9ci9u3j73HnUhLZT/NDbHqC5Mm0bl2I41vD37wYboBk0VjzPEcqR+dbRpH2AMPg25vrm2J\nSpAfpbaIBEQDGkXyKLCpl8tRsU9TnDBhxe7eQZ7cB/tq6mkcPEjFvn081bF31DTmHZNmFHTw4bot\nXdywYj1X3bmaG1asZ92Wrry8rm9BTwAyduDhiy/CY495ecZBnG9RmbAkSrMSRqktIgFScC2SR4FM\nvVyOSuGf8ObNXk41sHn3AaonVDDUOImBiQ009h+gqf8Am3ftH6km8fzFlxfsQiyem915YGBUPexI\nBdgJx3NELvWj45UjDh2CX/4SHn3U+3n69GDOt6Dbm62oBPlRa4tIgBRci+RRIFMvl6NS+Cfc0uKl\nGQD7+4eoqjRqe/fzSstJPHDFEvonT6F6+ysj5cDOvuKigl2IJdbDrjBj0sQqGmurWL52W+iv7VvC\n8RwRRBrH/v3Q0ADHHONVw1i71is5l+v5FlZ7MxWVID9qbREJkHKuRfKsZHJe86nYZ7mDURNWNFRP\noGLfPib2H+CRd32YjhNO5ZlZJzG1vprTYgNbFwDXXTh31ODDj53XEv65s3o153/768zcu4Ouo2ax\n9i3vouOEU6M3NiCMCUDiF3EDA1Bff3j5pk1wzjm5nW9RmbAkSpPaJLbl1Ve949zZCdOmeXcJlHst\nRUo91yISfVHp9ctFwoQVcwf30jWxkfsv+wRbjj8laa/0gjlTuOnSU7jr6jZuuvSUvATWfPGLHDW4\nn91NR1HX082F993KrOefjt7YgDAmAIn3pDY2egE2QHU19PTkfr5FZcKSKE1qE2/Liy96U6jv2+fV\n0D766OJL+xJJoFJ8IhI9YysItLbCT34SzgQfBRLJknixWs+7KyfyVMdeqidU0Ni/n+6Jk7jjyr9L\nm8IUyX3KRLzW9cAAtLd7gbVzXirS8ccX9fk2SpQqdKxeDVdfDXv2wNSp3kXH7t2He7DvvLM0jrmU\nBNW5FpHilGxSlfe9zwt4ohAQZCnywWdCrefd+/vZvPsA+/sGec3+PRy8f2XawLroJ6hJPPf6+2H9\neu/ce/Ob4frri+58Kxrx82737sMXNVVV3rE/7bTSuaiRoqc61yJSnBIHL8Lh7+3tRT1TXmLwmViB\n47oL5wJEI+hOyIFtbqjx6m53d0PzfEjTnsRBkBBcXe68iqduxHt13/72pBdxkb9QKibx827TJi+w\nrq72Lm6mTj08kLStLVo97iIpKOdaRKKlRCsIJKvAcdvDL3Ljyg38cdMuNu7o4Y+bdnHjyg2FKXuX\nQz7u1s7egtblDkxbm3cRt2qV9z1JYB35UoXFJH7edXZ6Pdb9/TA4CHPnHv7sl0I5TikbCq5FJFpK\nYfDiOJIFn+0vd9HRfZBhB3XVExh20NF9kNsefjH/jcxh0F05TZBUFKUK8y2XSZ7i5920aV6QPXGi\nN87iqKMOf/azLcdZ7JNPSVFScC0i0RKlagYZSDejYbLgs3fgELVVE6iurMDMqK6soLZqAk917M1n\n8w/z0XM7nnKaIKlkeumDEkSvclubN3jxtNPglFO8C7vEz342d7TU2y0FouBaRKIlKiXLMuAnTSBZ\n8DmxqgIbs72xj4tBOU2QVE699L4ENclTqs9+Nne0SmHyKSlKSQc0mtnUVE90znUG3xwREbx/pkEG\n00EOhBpnW4//4UX+5ne/4OjOHXQeNZO1b3kXz8w6adRgvnjwOXZSmNsefpH2l7owMyonGEOHHAcH\nDtF67JS0rxvWBUe2g/XKZYKkyxfO5OYHNgGMqozysfOKO3Upa0FO8pTss5/NJDylMPmUFKWkpfjM\nbDPg8DpR5gBdsZ8nA1uccwX/K6JSfCKSVrLSftn0ho+3rS1beH5nD73HzKSvrpHa3v1M7O3ht+/7\nW9YcdQJ3XZ36NdZt6eLGX26g68Ag/UOHqKmcwJT6Km68ZN7hQDXofUgRpJdESb08ULWQBPH64Imz\nPnZ3ez3PQVb4yfQCM1/tkrKRcym+ePBsZrcBK51zq2KPLwbeFlRDRURClay0X7y8V67bWrOGKQcH\n2FlzIlVm9NU3AjD/wRW8es2X0m5ywZwp3HjJvKSB2rotXfR/6WZc5xAT3DAtlYM0Z7sPiUF6Yg5q\nQpAepZJ6UQ5gy6WXPqV4sPvkk9DR4VX3iKdvhDG1e6Z3tKIy5byUHT91rs90zn0y/sA5919mdlOI\nbRIRCU6Qt4bH21Z/P402zMChYQCqKo2e6jqadm7zPZgvWaAW70X+3Pat7J9+NP2DwzzVsZf5s5po\n9rsPib19W7Z4U0unuNDY2tnLjKbaUZsoxGC9VHXBEy88ohp8l7zEC7V586CuzqtT3dsLp5/uBbCF\nHicxtm55S0s02iUlz09wvdvMvgD8B16ayAeBPaG2SkQkKAkTo4zItrTfeNuqqaEGmD+ryZvRsH+I\n5qGDHH36yUzPMdCL9yLvO3o2dT3dEOsV37z7AM2TK47Yh7HB5gcrdnDid79xuKf6yScZ2NPJCz3D\n7JzYRENNJS1TJ9KcEKTPnlpH54GBkR5rKMxgvXQ96H6CbwnR2Ls4xx3nldKLWspF0OM3RHzwUy3k\nSmA6cH/sa3psmYhI9AVZ2m+8bU2fDs3NNA8d5Mw5k3nLjGpObYDp13zC92afW/kgf774Cv5y6jn8\n+eIreG7lg8Dhkm9r3/IuJvb2UHugh6oJcKir64h9GK9iydZvfo+uqokj1RIONjaxr+8Qkzteoq56\nAv2Dw7zwwivsaj5mZDtRKamXrtydak0XWIlO9iQShLTBtXOu0zn3GeA859xC59xnVSlERIpGkKX9\nxtvWt78Nt9yS9fafW/kgFZ/9DC1rH2XO9v+lZe2jVHz2Mzy38sGRkm8dJ5zKA1csobdxMg27dmDT\njnyN8YLNY7p28EL/hJF1Nk+ZSYU5Gnp7wEFj/wEa+3tZfsrhYTRRKamXrtydak0XWIlO9iQShLRp\nIWZ2DvBDoAGYY2anAZ9wzv1t2I0TEQlEkLeGk20ry+0P/su/MrtzJ4M1tQzUTGTC0CBHde5k67/8\nK5f/5KcjJd+2HH8Kz8w6aaRyB2OC3fFypQ/VTmT2usfpXw/dE2rYUT+D3ubZHN3bzeQ9O+k8aibt\nl3yINc3H8cmE50VhsF66cndRSV8pWxosKJKUn7SQbwJvJ5Zn7Zz7C/CmMBslIlIujt70NIM1tRyq\nqgYzDlVVM1hTy9Gbns6oF3lsT++s55+mYfer1A4cpHtgGOvv57RtG6k+2MsNl1zHNz5zMys//nk2\nzj45kgFpun2PSvpK2SrCyZ4yomnTJQd+BjTinNtqNmrOsEPhNEdEpLxMqDCGxsw34JyjssL7m+u3\nF3lsT+8pD9zPq1OOYm/TNGbseJm6/oP019Wxq2k6G+ecRN3uA1RXToj05Cep9j3ZpDyF7nEvK6U6\nWNBHyUqRVPwE11tjqSHOzKqBTwPPhtssEZEyceaZVD76KENmDFdVUTE4SGV/H7zxjRltZmyweXTX\nDqbNbeHp7T0MTJsGGDjHUa9up756Ap0HBphaXx3JgNRvib0opK9ICQqyNr6UJT/B9SeBbwMzgQ7g\nd8CSMBslIlIuptz4BfZ/cgmHXtlB5YEDuJoaqo57HQ03fiHjbY0KNtfMh927aaippH9wmKpKo7Z3\nP/uPmc2JR09ian01N116SsavEXZtaZXYk4ILY9r0TGeXlKLmJ7g259wHQm+JiEiJyCgAbWuj4bZb\naUgzJXnGAW1swNnx1RN58qDzSvn1HeA3b39/1qkg+Qh8ozRDpJSpIGvjg9JMypC5Mbl+R6xg9jyw\nGfgJsNw5152PhvnR2trq2tvbC90MEZERiQFoYpWLbAPQnLYX6y3b+8wmNtZO4zdnvJ2h1jOz7m2+\nYcX6Iyp07Ds4mHUv+HiuunM1M5pqqUgY5zPsHDv39nHX1YUJREptJshS25/AJQbDiZVQsg2Glyw5\nMljv7o7ehDuSlpmtcc61plsvbc+1c+4EM2sDrgA+b2bPAPc55/4jgHaKiJSUoHtec9pebMBZE3BW\n7CsX+ZgaPWol9kotTaXU9ucIQaRfBD1tehhpJhJpfkrx4Zxb7Zy7DmgDOoFlobZKRKRIBT25SZQm\nS0k3sUsQolZir9Rmgiy1/Rkl3uO8e/fo9Itsyui1tXm9yqtWed9zSd/QhDtlJ21wbWaTzGyxmf0X\n8D/AdrwgW0RExgg6AM1HQOtXPgLfqMwQGReli5sghLU/67Z0ccOK9Vx152puWLGedVu6ctpeVhKr\nfFRUeN+bmrzlhbR4sZdW0t0Nw8Pe9717veVSkvz0XP8FWAB82Tk31zn3OefcmpDbJSISHRlMKBF0\nABqlntx8Bb4L5kzhpktP4a6r27jp0lMKmq4QpYubIISxP/FUk84DA6NSTfIeYG/e7KVbJIpC+kWp\nT7gjR/AzoNFcupUKRAMaRSR0WQxuCnrAmAagFU7QA1QLLYz9ycdAV180cFBClvOARjP7lnPus8BK\nMzsiuHbOvSvHNoqIRF8WE0oEPbmJJkvxJ9eLkGTPj+JMkNnuaxj7k4+Brr7Eyk8Coy+Ely7Nbzuk\n7CXtuTazM5xza8zszeP93jn3cKgt80E91yISukWLvMFRFQlZdMPD3u3dVasA9SxHQa49ssXUQx21\ntkam5xoKO1mLJoopeTn3XMfzqp1zD5vZRGCOc+65ANsoIhJ9aSaUKPnSZmOEdSGR63ZzLYFYTJPX\nRK2tly+cyc0PbAIYFexnM1FRzmLlJ/NOE8VIAj/VQi4B1gG/iT1eYGYrw26YiEgkpBnpX9KlzcYI\na+BaENvNtQpGMVUFiVpbo1bhpSCiWqkkLBkM8i5HfqY/vxGv9N4fAJxz68zs2NBaJCISJWkmlIhM\nvmkehNVjGsR2c518JmqT16QSxbbmPC4g6ikV6dpXzBPFZHrs1Uuflp9SfEPOub2ht0REJKpSTChR\naqXaUgmrxzSI7eZasjBKJQ/TKaa2+hLk5C9h8NO+Yp0oJptjX2699FnwE1yvN7P3AxPM7AQz+3e8\nyWREREpHlrc5Sy7QSSGsC4kgtptrakIxpTYUU1t9iXqw5qd9xTpRTDbHPqr1xCPET53rOuDzwF/F\nFv0W+Ipzri/ktqWlaiEiEogsalknKpdqIcmqVHx+eg8n/vb+cW8r+zk267Z0cePKDXT1DtI/NExN\nZQVT6qq48V3zSvI4yhiLFrG7qZnNnQfZ3z9EQ00lLVMn0rx390hFnkK3L13FICD6qS3j8btvicq4\nnnjO1ULinHO9eMH154NomIhI5GRRyzpRudShHq9G8qcbOznxu98YN/9y3dEn+K+kYvEf3JjHUup2\nNR/Di8++zFBjE3XVE+gfHOaFF17Bnfxaphe6cZC2YtCIQlUqyYXffUukeuJppQ2uzewB4D3Oue7Y\n4ynAfc65t4fdOBGRvCjmwUh5dsSFxJLvJb0wWX7hp3wNVFy+dhszJ9dx8jGj6yRHsQxeLkrtDkdQ\n+7P8lLdx3rp/Z6i6kr4JDTT2H6Cyv5flp7yNT4bQ7oyVcjCZzb6lGeQt/nKum+OBNYBzrgs4Krwm\niYjkWbEORoqCFPmXfgcqRq20XBjCKmNYKEHuz+PNx/HQ+5fQ2ziZyXt20ts4mYfev4THm48LoeVZ\niAeTzc1eukRzc+lUxsh231IM8hZ/pfiGzWyOc24LgJm9lpH7dsmZ2Z3AO4FXnXOnxJbdCHwM2BVb\n7Z+cc6tiv/tH4G+AQ8CnnXO/zXBfRESyk0vPVMB5lr57A6OS35nitrLfknFhlZaLUk9x1CZ+yVWQ\n+zN7ah0ba07mlY/PH1m27+Ags+urg2twrnJJ+YjKZzWZYkxniTg/PdefBx4xs7vN7G7gj8A/+nje\nXcBF4yz/pnNuQewrHli/HrgCmBd7znfNbIKfHRARyVm2vTcBlxDz3RsYpdJl41RJ2LdjN7e99lw2\nvLKXtVu6eHn3gZSVVJJVXDl15iRuWLGeq+5czQ0r1mfUKxq1nuJS650Pcn9KuuJOlD6rkjdpg2vn\n3G+AhcBPgJ8CZ/jpVXbO/RHo9NmOd+Plcfc75zYDL+BNXCMikh/Z3OYMuISY79keo1S6bMyFya6a\nBv7t3A/w9MwTOWFGI69rrmfzngNs2rEvacm48UrLvXP+Mfzqqe1ZB8dRmzmz1OqhB7k/JVdaMFGU\nPquSN34GNBpeb/LrnHNfNrM5ZtbmnMv2susaM/sw0A4sjeVwzwQeT1inI7ZMpLRF/XahpBbwQEjf\nsz36fN1s0iKySqVIuK18y4r1o1I85kyrZ3JdNVPrq7np0lOSbmLsQMkbVqzPKe0gajNnXr5wJjc/\nsGmkHfEyhh87rzjz+oPen5KtuKPB0mXJT1rId4E3AFfGHvcA2RYy/B5wHLAA2A78W2z5eEWXxs3r\nNrOPm1m7mbXv2rVrvFVEioNuFxa/gAdC+u4NjL3u7v39PPFSJ79/7lWefnYru5qPGVklm7SIIFIp\ngkoXyHU7UespLrXe2VLbn9AUwWDpdVu6sk6/kvH5GdB4lnNuoZk9CV61EDPLapSBc25n/Gcz+wHw\nq9jDDmB2wqqzgFeSbOP7wPfBm0Qmm3aIREKOtZVLWZQGoqWU6UDINHcqfPcGLl7Mvr//R17oNYYa\nJjF1sJeKnh6+M/u9XLaliwVzpmQ14CyIQWpBDU7MdTtR7Ckutd7ZUtufUES8jF/ixFBpa9GLb356\nrgdjgwsdgJlNB4azeTEzOybh4WXA+tjPK4ErzKzGzFqAEwB130lp0xSy44raQLSUMhkI6eNOhe/e\nwLY27nnHR+lvmsL0vbvobZzCHz5wDbtfv2Akpzibnt+xz5n1/NN84O5/5a9v+LjvKeGDGpyW63ZK\nuWdVPY1FJOJl/KI2NqFU+Om5vgW4HzjKzL4K/DXwhXRPMrN7gfOBZjPrAL4EnG9mC/AC9ZeATwA4\n5zaY2U+BZ4AhYIlz7lDGeyNSTLKZGasMFF3JMr9lrHzeqfDbG/h483Fs/tQNVNjhrLoG50aC52x6\nfhOfM+v5p7nwvlvpqaln4JjXjJp5MdX+jjeL48fOa8n4vQtiO6XYs6qexiIU4VJ3URubUCr8TH/+\nYzNbA1yAlxt9qXPuWR/Pu3KcxXekWP+rwFfTbVekZET8dmGhlOwf+4AHNqULnrNJi0h8zum//096\naurZW1PP/OkN0FDjreQjbSmooLYUg+NcFd3Fp0RaWDXmy52ftBCccxudc7c6574DbDezz4fcLpHS\nl+/bhatXe7f2Fy3yfYu/EKI2EC0wAQ9sSpc2kU1aROJz6rdtZXjSJObPaqI5HljncDGgVIZglFq9\nbCmskq4xXkDm3PhjAs1sNnAD8BpgBXAPcBPwIeBe59xn8tXIZFpbW117e3uhmyESffF836am0b3k\nEcr9i0u87Z3Y4xqV295ZD7YM4T0IdeDnkiVHpi11d3sXgbdmVjAq6u9pMblhTKlD8GYzTFfqsNgV\nzSDnIqRj65+ZrXHOtaZdL0Vw/XvgYeAxvDrXFwAbgGudczsCbGvWFFyL+BRgoJQPUf1jn3OQWEx1\nzQO8GCjXgDAM5XihUo77LNHkN7hOlXM91Tl3Y+zn35rZTuBM51x/EA0UkTwqsokMopprm3O+aw4D\nm/J+wRFPW0q8GFi6NKv2l2wefQEENWA0Z3m8UFSeuRSblAMazWwKhyd42QHUmVk9gHPO79TmIlJo\npVyZJI//5MMKEtMFzgWrEBFQlQMNmgpWwS8+E+9qJJaVDCnNLJfPXVTvgklpSxVcNwFrGD174trY\ndwe8LqxGiUjA0lUmKYZ0hfHaCHn9Jx9GkOgncB6v527Oi+vp/8Q3wfZF9z2LieKELun4ueApl6Dt\np09s4YePbGZ3Tz/NjTXc+ugdnJDHCbCy/dypbKEUStJqIc65Y51zr3POtYzzpcBapJi0tcH73gcb\nNsCKFd73973PWx7BadjHVpZ4buWD47fx618/XDu6osL73tTk/ZMPQaYj6/1UyPAzicN4k7tc+ovb\ncXui856lUmwTuqSbyKioJjrK0U+f2MK//NdGevqGaKqroqdviJ1/2ciLA2PChxDTzLKtaKEJUqRQ\nfJXiE5Eit3o1/OQnMG8eXHqp9/0nPzncG5zHADWd8QKXrd/8Hl1VE49s4xNP5HWWy0yCRL8BmJ/S\namPLEy78/Ur219YzYcqUSLxnfiyYM4WbLj2Fu65u46ZLT4lsYA3pg7JyCtp++MhmaqsmUFddSYVV\nUFddyc5pR7N1887RK4aYZpbtxZnKFkqh+JmhUUSKXarZASM22HG8FIhjunbwQtUxnDm2jeD9U89j\nLrnffFe/g7D83PIem1YxacdWdk6azvzm+sMvOGkSPPmkVxkmyuk9RSBdjm85DdDc3dNPU13VqGUP\ntF3Eh1bd6VUcynECLL/pNdnkmSvXXwpFPdci5WDz5uQ9vAFPbpKr8Xqb9h49i0Pd3aNX3LcPzjzT\n+6fe3Q3Dw973vXsP52MXkN9eMz+3vMf23O0/ZjanN9nhyV3Aey87OiKV3lOs0k1kVLITHY2jubGG\nvsHhUcv+csyJ3PvOj+Y8AVbY6TWaIEUKJW1wbWbHmVlN7OfzzezTZjY53fNEJEJSBdCLF0cqQB0v\ncPnTOe9g2uDBI9t4/fX5neUyA34DML+3vBPTKs76P9cxZezx2LQJ5s6NTHpPMUsXlJVT0PbRc1vo\nGzxE78AQw26Y7t5+9uzvZ9Ock7jhwk+x7rYfe7Xys/jMhZ1eU2y5/lI6kk4iM7KC2TqgFTgW+C2w\nEjjRObco9NaloUlkRHxKNyFImNVCMtx2sgkjPj+9hxN/e3/RpDyEPvHF2OP65JNeLn1FQp/J8LB3\n0bFqVe6vV2ZULeSweLWQHXv7GBp2HNdcz+tnNuV8Tl9152pmNNVSYYeLkg07x869fdx1dXQ/21K+\ncp6hMWFDa51zC83s74E+59y/m9mTzrnTg2psthRci2SgEOX2spzlb9zAZcfz0S8XOEZeA7Aim4VT\nik/QM21q5k4pNkHM0Bg3aGZXAouBS2LLqlKsLyJRFNCEIBlJNZAyRVuOGLyU50krgjJ2P+Kl+UIJ\nttPVMo8rhprmEklBD+QsxvrnkmdF+vfKz4DGjwBvAL7qnNtsZi3Af4TbLBEpCakGUmYiYuUCs5Fq\n8JafethpxacrT5V/HsGa5lI8gh7ImZgT/fzOHp5/tYeevkGWr91WkjXDJUNF/Pcqbc+1c+4Z4NMJ\njzcDXwuzUSJSIoKadj1i5QKzkaw0320Pv0jvwKFgZpFLd3ciyzsJUVVOec9RcPnCmdy4cgPrtw3S\nPzRMTWUFU+qqcuppjr9fL+85wDFNE2morYzkTIo61wqgiP9eJe25NrOnzeypZF/5bKSIFKmgKpFE\nrFxgNpKV5nuqY2/+JiQJ6k5CBJTTLImRMjL20I15nL3EC8+uAwNs2tnDs9v3cf3ypyLxfupcK5Ai\n/nuVKi3knXg51sm+RERS85Oq4EfEygVmI9ktdSB/s8iVwEVKXDnNkhgVy9duY+bkOs45vpm3nDSD\nc45vZubkupyPefzCc8/+fp7q2Ev/0DANtZV0RSSI1blWIEX89yppWohz7uV8NkRECifUW55BDKSM\nB+mJA1uWLo38rcFEly+cyf23389b//xfzOjczs6px/DQWRcz/6T57O8bys8scn4HPRaBYpolsVRS\nCmYlj/MAACAASURBVMI65vGZFDfvPkB1ZQVVEyoYGBqmqa56JIgt5PEqpnOtpBTx3ys/k8icbWZP\nmNl+Mxsws0Nmti/d80SkOBTNLc+2Nq+k3KpVWU9aUUgLdjzP0kd+zNS+HrY3NjO1r4elj/yYa5u6\nk09Isnq1V2Jv0SLve64DeYK6kxABxTJLYtF8vnwI65jHJ+Xp7h1gQgUMDA0zeGiYlml1kQhig9jv\nQAYtxwX9dyGqivjvlZ861+3AFcDP8CaT+TBwvHPu8+E3LzXVuZZiF4UerXKoNRuF45yqDvW6z31l\n/LreWdQILxehT9ITkFL6fIV5zNdt6eL65U/RdWCAprpqWqbV0dxYO+pYFepznOt+B3rcspw7QIIR\n5CQy7c65VjN7yjk3P7bsf5xz5wTU1qwpuJZiFpXgoNRnSYvKcWbRIq/iid8ZFEOaFCYSFxoBKYZ9\nKbXPV3y2xt09/TQ31vDRc1t475lzAtl2qs8q4OtzHNY5kct2A73AWrKEri2v8MJAJfv7h2ioqeT4\n6iGmzHmNJovKgyAnkek1s2pgnZl9HdgO1OfaQJFyl6w0W77zC+P5jnnJ+S2AqBznjMsShlB+MDF4\nybnsXwQcMdlQBJXS52vdli5+9dR2TjiqkdPnTGF/3xC/emo7c2c0BvI+xOteJwaxHzuvhQVzpnDD\nivVpP8dhnt+5nGtB5mzvfWYTTx6qp7pymLrqCfQPDvPkQccZz2yiKavWSRj8BNcfwsvNvga4FpgN\nXB5mo0TKQfwP7qznn2bh71cy9dVt7DnqNTzQehHk8XZxqc+Slo/BSL56tTIdnBNUjfAEkbnQKCOl\n9PnKx/mTLIj18znOpn35uPsR5AXWxtppNHV1MlTrhdJVlcbE3h42TpnGWYG1WHKVdkBjrGrIMDAH\nWA58zjn3QtgNEyl1s6fWMXXDOi6871bqerrpnjaDmu4u3v/rH+Z1gEriLGk79/Yxtb66aHsyxxP2\nwDffA9YyHZwTQvnBZLW2Cz1grJSV0uerkOePn89xpu3L12DT+IDNcQctZ+g3Z7ydhr4D1B7oAeeo\nPdBDQ98BfnPG2wNts+Qmbc+1mZ0PLANewisXP9vMFjvn/hhu00RK2+ULZ7L721+ip6aeofoGBocc\nB2rqed30+rzPQFUMt9ezFXbPYUa9ZZmUJQyh/GAUUxSiljcdRntK5fNVyPPHz+c40/YF3ROf7NxJ\nle6SqaHWM1lRPYE3/c8qpr66jc6jZvKbt7+fofkLM96WhMfPgMY1wPudc8/FHs8F7nXOnZGH9qWk\nAY1S7Pa+5UI2VTWxf+AQDTWVtDTX01xXlXyQm2QlzACumAasRWZwp9pTlAp9fNJ9jjNtX5Cf3Xwd\nm0K/B+UuyAGNVfHAGsA5t8nMqlI9QUT8aXr9XM7cvRsmTzu8sLu7KGagKiZh9hxGsTc4mSB70IIQ\ntRzwqLUnagp9/qT7HGfaviA/u/k6dwr9Hog/foLrdjO7A7g79vgDwJrwmiRSRop4Bqqysnr16PSM\nxYtH0jNOnTmJbz74PEOHhpk0sYoZjbVUTrBoDVhLaP+ClhYWLF4Mlxa+Vz1qM99FrT1RFPUUl0za\nF2TKWD7Pnai/B+JjQCPwKWAD8GngM8AzwCfDbJRI2cjjDFSBzhBWTuKTNuze7ZXG273be7x69Uhp\nstc119M0sYp9BwfZvOcA75x/THT++aVof6FFbZbFqLVHwhXkYFOdO5Iobc51lCnnWsQf5enlIMVk\nLjdc+KmCzb7nO488pMloghC18zJq7ZHikW4CnCgN2pXs+c25TtpzbWbvNrMlCY//bGb/G/t6T1AN\nFZHwJeYDVpgxaWIVjbVVLF+7rdBN861gPe+bN3spO4lik7kUqjTZui1d3LhyA3/ctIuNO3r446Zd\n3Lhyw/jHJEX7Cy1qZeqi1h4pHsnOHSAv5f4CsXq1dzG+aJH3PQJ3t4pVqpzr64ErEh7XAGfizc74\nI+BnIbZLRAJU7LmkBZ1ZMMVkLoUazHjbwy/S0X2QiVWV1FVPYPCQo6P7ILc9/CK3fWhMp0oIk9EE\nWX0lavmjUWuPFI/xzh0/M0tGQjx9rKlpdPpYSGmKpS5VznW1c25rwuNHnHN7nHNb0PTnIkWl2PMB\nC9rznmIylyAnh8jEUx17qa2aQHVlBWZGdWUFtVUTeKpjb0btz0a+Jt4QKQVFM3HTsmVeYD15MlRU\neN+bmrzlkrFUwfWoSyrn3DUJD6eH0xwRCUOhgkDf0tyOLOg/qBSDTguZRmBpHo/IYdDseKk4pZBi\nJJJOUGloRdOxEeH0sWKUKi3kz2b2MefcDxIXmtknACXiiBSRSNdG9XE7suC1pFPMrFiINIL5s5po\nf6kLM6NygjF0yHFw4BCtxyZpRyYzQ8YkS8Xp6Rtk7tGj/wlHsidOJEtBpqGFPUNsYEJIHytnqYLr\na4EVZvZ+YG1s2Rl4udeXht0wEQlWZHNJE29HwuHvCVPAX75wJjeu3MD6bYP0Dw1TU1nBlLqq6P2D\nypNPvvk4bty3ga4Dg/T2D1FTOYFZUyfyyTcfB6TOifabL51sUowd+/rY3zdUFJPmiGQjyAlhIt2x\nkUhzLgQqaXDtnHsVOMfM3grMiy3+tXPuoby0TERKQtpgbvNmr8c60Xi3I0fyHtyYx+VnwZwp3HjJ\nPG57+EWe6tjL4KFhjp7kDVhN1esG+O6RGzsIdtbzT3P67/+Tmq1b6DrqNax5y7vpnLeA/X1DbOvu\n5dDwMFfduVqlxqToBT0APLIdG4ni6WOJk2UtXarBjFlKO0NjLJhWQC1SzlLMUJiKr9urPm5HLl+7\njZmT6zj5mNH1pCM34j7PegcOcfqcKSO3m29+YBN11ROS9roBvnvkElNxZj3/NBfedys9NfUMz5zJ\nGTWHeO39t3PPwEfZe+Kp4GBCRQUzmqrzW8lFJAQFT0MrlCzSx2R8fmZoFJFylsMMf74Gv/moZlE0\nI+5zlUGd2WTH9qmOvUmPVSbHMXEQ7Om//096aurZW1NPy/QGprzmKE6YO4svdbUzvbGWmVPqNMBR\nSkbkB4BL5Cm4FpHUcijR5CuY81HNomhG3OcyCUOGFzHJji2Q9FhlchwTK6HUb9vK8KRJzJ/VRHND\njbdCgSfSEQmLJhOSXKVNCxGRMuc3J3ocvm+vprkdWRQj7nOdhMHHwM5EyY7t/FlN9PQNAuMfq0yO\n40iu6AOne/sTD6yh4BPpiISpKPKkJbLUcy1SyoKYzralxQukEvks0RTU7dWi6EnKdRKGDOvMJju2\nn3zzcUmPVdbHMYIT6YiIRJU55wrdhqy1tra69vb2QjdDJJoSe1ITSytlOp1tjtsJcqrsSFu0yOux\nrkjosxge9lJdVq1K//wlS44c2Nnd7aXJ3HrruE/J67FNMai1bN5jESlrZrbGOdeadj0F1yIlKotg\nLaksq4WUCl/BY67HO6iLoWzaLiIiafkNrpUWIlKqgpzOtq3NCxBXrfK+l1lgffMDm+g8MDCqnOAR\n0yH7qHqSUg7TlOfcdhERCYwGNIqUKk1nGwjfs7UFMQlDwHVmg5xpTkRE/AktuDazO4F3Aq86506J\nLZsK/AQ4FngJeK9zrsvMDPg2sAjoBa5yzq0db7si4lOZTGebNO0hoFSWjGZri9gkDEHPNCcikk/F\nmtYWZlrIXcBFY5b9A/DfzrkTgP+OPQa4GDgh9vVx4HshtkukPISQZhA1ydIenlv5YNYT34xVNDW2\nxxFv+6znn+Zd3/8qV33lb1n0vZs4e/eLhW6aiEhKxZzWFlrPtXPuj2Z27JjF7wbOj/28DPgD8LnY\n8v/nvNGVj5vZZDM7xjm3Paz2iZSFiPWkBi1Z2kP3936YUc3oVIKssZ3vXpjLF87k/tvv5/xf/pCh\nxkZ2NU2nZm8X7//1D+H840r63BCR4lbMaW35zrmeEQ+YnXPbzeyo2PKZwNaE9TpiyxRciwSkWG+v\npZIs7aG2YwucPW/0ymkGcyY7PvHa0Im/+9h5LRkfu3gvTGNt1ahemDDrdS+YM4WZWx9lx6RJdFZO\npKF6Ai1zZzFp6GBWFxolo8yr34gUg2JOa4vKgEYbZ9m4NQLN7ON4qSPMmTMnzDaJlIxCBHb5kGx2\nwL5Zc7wcc5+DOdMdnyBmaytUL8z03duZfvLsMfW3q7KrGlMKcp1JU4DSvFiXaCnm2V/zXYpvp5kd\nAxD7/mpseQcwO2G9WcAr423AOfd951yrc651+vTpoTZWpFQkBnYVZkyaWEVjbRXL124rdNNykmx2\nwMmf+mhGZfGWr93GvG3P8cG7v87VX13CB+/+OvO2PRfo8dna2UtD7ej+jLz0wuQww2ZJynUmTSnq\nXFhJbt2WLm5YsZ6r7lzNDSvWF/z9LObZX/MdXK8E4v/dFgP/mbD8w+Y5G9irfGuR4OQa2EXtj25c\nsum8T3zX2zIazFnZ/gSX/uJ26nq66Z42g7qebi79xe1Utj8RWFsLNjAy1/rbpSbI+u9lqlQv1stZ\nFC+Ykv19L4Y7JGGW4rsXb/Bis5l1AF8Cvgb81Mz+BtgCvCe2+iq8Mnwv4JXi+0hY7RIpR7ncXot6\nSknSlI0MBnNetOa37K+tZ6i+EYC++kaGDg1z0ZrfEtSfoyAHRmYkiPrbpUT133NWzLmwMr6oDh4M\nIiWvEMKsFnJlkl9dMM66DlgSVltEyl0ugV1U/+gG6aS+Payprv//27vz+LjK+97jn0cz2jWSrMWy\nkTEWxibewDhGIRAIBNJgWogplEBLr6ElEJYkbQm00Li3N/SW3LhpWm64lMQJOG0C5OJATAokgZJQ\nygvEZuMNL2AjWzayZe37jObpH2dkj2TJmuXM/n2/Xn6N5jBz5pkzw8xvnvN7fj8KAkHyvQZ/wNJX\nUMLHB4+49hhuLYyMSZZXjYlKjtR/T6RMzoWViekHk7vSZUGjiCRQPIFdLnzoViycz1nNB9g9nEfv\nUICyQi+LSoNUzJ7v6uNk6ixMVtFMftxSdhZGEkY/mNyl4FokR8Qa2OXEh+6qVUz7m7/h7MoKKK8J\nzWYOuJ6XrAoLaUIz+XFJ6VkYSQj9YHKXcTIyMtPy5cvtm2++mephiGS18Jzr8A/ddMm5dk2Cax/H\nchzdCsbd2I9+GIhkN/0/PjVjzFvW2uVT3k7BtYhMJdc/dN14/quf3nLcGYDuAT9VpQXct3LxhI/p\nxo8aN/aTMz+woqVmNCI5JdLgWmkhIjKlXM4VdqtaSrS5624tJHVjP7mwqDVqakYjIpNQcC0icgJu\nBZaR5K6Hz5DvbO1h4UnlwLHbx7KQ1I0FqVHtI1dmc8Ob0cCxy1xuKy8iQPKbyIhIOmpqgttvh8su\ncy6bmlI9orThVmfFqbqNjW/ikO/JY+O+Ttp6Bo/uI5aFpG40r4l4H6OzuW1tY2dzs/H9pGY0IjIJ\nBdciuS6XAqIYuNVZcapuY+O73p0+wwcWdrb2xtX6140WwhHvI5dai6utvIhMQsG1SK7LpYAoBm4E\np6OWzp7GfSsX8+ifNHLfysVj0krGz5BXlxVy1uxK/CPBuFr/utFCOOJ95NJsrtrKi8gklHMtkuv2\n7HFmrMNla0AUg2TV9J0oJ7vA6+HiBXUTVhOJhhsLUiPaRy61FlczGhGZhIJrkUz0yCPw7W9DayvU\n1Tlf6jfeGNu+sjQgcrN84NHAsqkJ1j0E33N/sV5WNHHItdbiakYjIhNQWohIpnnkEbjrLidoqa52\nLu+6y9keiyw8vT1+ceBo+byNzR2x7zSS3PQ4Foa6kb6RcqOzuTU10NLiXKo0nYjkGDWREck0ixc7\nwW9Z2bFtvb1OnvSWLbHtM8vKp0XbsCUit99+/Ax/Z6cTQD744Ni6x+Gztgou006uN0USkdioiYxI\ntmptdWasw5WWOttjlQGnt6MJiNyo7XycqXLT07jucTKDyXQPXN1qCiQiMhmlhUjmy7UazXV10Nc3\ndltfn7M9S0Wb5uFW+bwxpiq9lqaVMhKSIpMGjxWr8SUPy4vz8RXls/7tllQPTUSyhIJryWy5WKP5\nzjthYMBJBbHWuRwYyN5FY0QfELlZPu+oqXLT07TucTKDyUwIXN1qCiQiMhkF15LZcrFG8403wpo1\nzvM8csS5XLMm9mohGSDagCghiwOnWqyXpgtDkxlMZkLgmpCzGiI5ZmNzB6uf3sINP2xi9dNb0urs\nVDpQzrVktlyt0XzjjVkdTI83UQ3oqQIiN2o7H+dEuelpWvc4lmOXCY8Vq6woeSiSQlq3MDXNXEtm\nS9NT8dHQDMDUEpLmEYsp8vs3zpjH6s/eyg1X/y2rP3srG2fMS+74JpDMY5c2r9MJZEXJQ5EUyoT0\nr1RTKT7JbBle/ix8BiB8Fk1f9sdLeRWKKd5r6fBaTnaMVC1ERNxyww+bqKsoIs+Yo9uC1tLaNcij\nf5L+37vxUCk+yQ1peio+UuEzAMDRy/VvtyggGSchaR7RmKLUXqpfy6lO1Sbr2KX8dRKRhMqE9K9U\nU3AtmS8DajRPJiH1mMNoFtFFU+T3J/q1nEqqg3sRyQ1atzA1BdciKZTIGYCoFp2kuENjRvwIaGig\no/kAu4e99A4FKCv0clpBgGmh/P5Uz+akOrgXkdwwum4h/DP7i+c3pN9ndgppQaNICiVyAVjEi05S\nXCs8ExqPAOz43JXs23OQvK4uSvLzyOvqYt+eg+z43JVA6hfzqcRc8mkxsuSqpbOncd/KxTz6J43c\nt3KxAutxFFyLpFAiKxdEXHM4xbXCM2Xl+b8FZ/DcNbcxXFlF5ZFDDFdW8dw1t/FvwRlA6qtQpDq4\nzzWZ8qNQRJJPaSEiKZaoBWARpymkuFZ4pqQz7Gvvp27RUjYsPuvotqC1tIaNM5WL+dL2VG2KU44S\nRTnuIjIZBdciWSriRScNDU4qyGj1C0hqrfBU5ypHKhPGmXaVOsLLF4anHGVIqcwTyZQfhSKSfEoL\nEclSEacppLhtd6akM1y1rJ6Wjn5e3d3GS+8d4tXdbRS/8yZf+dl3Jm0qk/NSnHKUSMpxF5HJKLgW\nyWIRLToZrRVeUwMtLc5lEmcWU52rHJWjPRMsH2vezh8++wO8He0pWQiaEfbscVKMwiUx5SiRMuVH\noYgkn9JCRCT+WuFx5tWmQzrDVOUA17/dQn1lCQtmOmkhV7y8Fltewe5hL2ePzsrC0aYyQspTjhIp\nbXPcRSTlNHMtIvFJcSk/N0RS+WF89ZWqQy0EfD56h8JSA7JkVtY1KU45SjSVIxORiSi4FpH4JCuv\ntqnJyWtOQH5zJOUAx+fYtk+vx9vTQ1lh2AnALJmVdU2KU45ERFJBwbWIxCcZebUJnh2PpCb4+Bzb\nl8+9jPzebk4rCGTlrKxrGhvhwQfh2WedSwXWIpLlFFyLSHwaGpwZ23Buz+CuW0dHfjFvdAZ5aVcb\nb3QG6cgvdm12PJLKD+MXXvaesYzCv/87ps0+SbOyIiJylBY0isjxolmguGqVM4sMzox1d7czg3vn\nna4Np2vbTnZ3DFF/eD/FQ/0MFJawu3YW83t7qXBh/5HWBD9+4eViuOISF0YgIiLZQjPXIjJWUxPd\nd93D5k3v81JfAZs3vU/3XfdMnoKRhLzafYMwf+82CgLDDBcWUxAYZv7ebewbdGf/GVUOUERE0ppm\nrkVkjMPffZj3+w0BXyklXkNXoJRtPV3M/e7D1P5okoA53lJ+U+gfHsEAxhgwBmMMJrTdLelQDlBE\nRDKfgmuRDDRVTeZ4tG/dSaC8lnyvc2Ir32vwl5XTvnUnta48QvQq8PPB3MXMPLSPwoF+hopL2Fc/\nlwr8KRrRxBL5uoiISGZQWohIhomkJnM89pfX4RvuG7PNN9zH/vI6V/Yfi6pF8xnM87Jr3lJ2LDuP\nXfOWMpjnpWrR/JSNabxEvy45I4ElF0VEkkHBtWS8jc0drH56Czf8sInVT2/J+mAmkprM8di14iq8\nPT0U9fWAtRT19eDt6WHXiqtc2X8sau+4hYUllorhPvqHAlQM97GwxFJ7xy1T3zlJwVqiX5eckAUN\niUREFFxLRsvF2cJIajLH45xrL+Wnl99EZ7GPiiMf0Vns46eX38Q5117qyv6PiibobWykfM39LDlz\nLheVDrPkzLmUr7l/6jzvJAZriX5dckKyGhKJiCSQcq4lo4XPFgJHL9e/3ZK1ua4nV5XQ3jd89LnC\n8TWZ47F09jS45UrWn92YuNzh0aC3omJs0Ot2nejwYA2OXa5b5/oCzES/Ljlhzx7n/RBOLeVFJMMo\nuJaMtq+9n7qKojHbsn22MNKazNGYaCHefSsXuzXk40Ub9MYajCcxWEvE65JzGhqc13b0/QBqKS8i\nGUdpIZLRIumsl23crsmcktSaaFumx5oukIzukSGqle2CVaucBkSdnWopLyIZSzPXktFydbbQzZrM\nKUmtiXaGMtYZ6CR0jwynWtlxGm1IFN4d9M471VJeRDKKZq4lo2m2MH4pWYgX7QxlrDPQSegeKS5r\nbIQHH4Rnn3Uu9VqJSIbRzLVkPM0WxiclC/GinaGMZwY6wd0jRUREwqUkuDbG7AV6gBEgYK1dboyp\nAp4A5gB7gWustdlbT00kDm52AkxZak00QW9jIztu+xqdD62laNtWBmfNpvK2r3G6gmbJVU1NY3+c\nrlqlH5EiacJYa5P/oE5wvdxa2xa27VtAu7X2m8aYvwKmWWv/8kT7Wb58uX3zzTcTO1iRNPsSG12A\n6CvKHxMMx7uoMZ3bdifiOYtkrPDqOeFncpTyJJJQxpi3rLXLp7pdOqWFfB64MPT3OuA3wAmDa5GE\nS1Y95igkYgFiuqfW5GI9c5FJJbF+u4hEL1ULGi3wK2PMW8aYm0Pb6qy1BwFCl9NTNDaRY9KwY1wu\ndgLMxecsMqloS1mKSFKlaub6PGvtAWPMdODXxpj3Ir1jKBi/GWD27NmJGp+IY88eyM+HV16Bnh7w\n+eC001L6JZaLnQDjec7pnvIiEjU12xFJaymZubbWHghdHgKeAhqBVmPMTIDQ5aFJ7vs9a+1ya+3y\n2traZA1ZclVJCbz+OgwMOH8PDDjXS1IXyF61rJ6eQT/dA36C1tI94Kdn0M9Vy+qnvnOCbGzuYPXT\nW7jhh02sfnqL6w1oYn3OKWmQI5JoarYjktaSPnNtjCkF8qy1PaG/fwf4BrABWAV8M3T582SPTWRS\nxhz7l2Kjtb3DZ2O/eH5DXLOx8czubmzu4KmHn+KS15+jrv0grVUzeeoTK+CWK12bIY71OStXW7KS\nmu2IpLVUpIXUAU8ZJ0jxAj+x1j5vjHkD+Kkx5k+BZuAPUjA2kbH6++Gcc2DXrmNpIUuWONtTyM0F\niOGVOMJndyOtxPHa489zzTNrCfjK6aqeQWV/D9c8s5b/rChm6d3XuTJGiO0572vvp66iaMw25WpL\nVlD9dpG0lfTg2lr7AXDmBNuPABcnezwiJzSa2/ipTx3b1tl5fCvuDBbv7O6859YT8PkYLPUBMFjq\nowjLvOfWg4vBdSxyMT9dRERSK51K8Ymkn3g6A2aIeGd3Z3W3cri8lvywbT0FpczqbnVxlLGlriS6\nQY4WS4qIyHipKsWXFXZseIHXV1zLpiXn8vqKa9mx4YVUDylzNTXB7bfDZZc5l01NqR6RYzS3saYG\nWlqcyyxr1HByVQm9g4Ex26KZ3a1aNB9vbzf+QBCw+ANBvL3dVC2a79oYY12YOJqrXVVaQGvXIFWl\nBa41ntFiycRI9OJYEZFES0mHRrekskPjjg0vMHTv1/GXlRPw+fD29JDf203h3/8dp19xSUrGlLHU\nbSyl4u5+2NRE91338OFIPm2eImpGBjnF46d8zf0nfP2imfVd/fQWyt59mwtefZaqQy20T6/n5XMv\no/eMZdy3cnGsTz0uq5/eclzKSfeAn6rSgpSNKdOpE6eIpLNIOzRq5jpGnQ+tdQLr8goweQTKK/CX\nldP50NpUDy3zpGGjlqRyc9Y+hn3FPbvb2Ej5mvtZcuZcLiodZsmZcyMKrKOZ9fW++QYrf/YwJT2d\ndFbXUdLTycqfPYz3zTciG2MCqLGN+8Lz//OMobw4H19RPuvfbkn10NKOZvhF0pdyrmNUtL+ZwRkz\nx2wL+HwU7W9O0Ygy2J49xy8QjKbbWFPT2JJUq1Zlzox3UxN85SvOosmhIdi5E956Cx54IPrnEEer\n9rirj0RZuSDaRZSXvvVLeotKCYQtmgyMBLn0rV8CN8Y+7jhosaT7VN0lMvFW+BGRxNLMdYwGZ83G\n29MzZpu3p4fBWeoaGbWGBicVJFyk3cZGA8q2trEBZbrkbE/lW9+CvXudRhClpc7l3r3O9mhl0BmA\naGd9PzZ4hK6CkjF53V0FJXxs8EgSRjuxdGzmk+nizf/PFZrhF0lvCq5jVHnrTeT3duPt7gIbxNvd\nRX5vN5W33pTqoWWeeLqNZVBAOaE33nC6PRYWOg1qCgud62/EkO6wZ48z4x8umjMAsWpqguXLnTbx\nHo9TC3z16hPeJdogqmLhfE4rHKFrwM/+9gG6BvycVjhCxUL3Fk1GK5GLJXOVfrBERilJIulNaSEx\nOv2KS9gBDDy01kkRmTWbsnvv1mLGWMTTbSyGlJIdG16gM+x1q7z1pux43UZrcldWHtsW6RmAWDU1\nwXXXOcfbGOcHTn8/3H+/89/vu2/Cu0VbIm/H565k6LdfZ0ZZOYFpzgLizoPdDHz5q5zu5nOJMr3I\nzWY+kpjuo9lIKUki6U3VQiSz3X778QFlZ6dTMu/BB4+7edpVebn6anjlFSclpKAAhoehr89pWvPk\nk9HtKxVVV26/Hb7/feeMg8fjbLPWuV5eDu3tk941raqFqGKNZBBVVRFJjUirhWjmWjLbqlXw1a86\niwCHhpy0itraSZu8dD60lmBRKUdMEYGuIbyeIqqLRhh4aC2kIri++256P/iQwQMfYdp7sIWFFJ10\nMmV33x39vuI5AxCrPXsgEADvBB8lvb0nvGs0s7772vv5eIFnzLaSAg/b3ToNHp5eBMcu161TI+R/\naAAAFptJREFUcB0nNdpxn2b4RdKbguscly5ffHGNY/zZlxOcjfE2f0hzcRWeoMXjMQSDlo8oYnbz\nh3GMPnYbZ8zjqRW38pnXn6Ou/SCtVTP5j0+s4MoZ81gayw6jrNoRt4YGJ7AOn7keVVbm2sOc0/Y+\nn/3+N6no68ITGKb6wIdM37WV/FvuBVx4vnv20FZRw5697fQOBSgr9NJQVUxNovPVs5yqWiSOUpJE\n0peC6xy2sbmDpx5+ikvCArunPrECbrkyqR/acX0Br1tHR+1MdlecfDQoOq0gwLRJZhxbKus4qbWZ\nup52iocHGCgoptVXRUvdbD6eoOd3IuvfbuGDOQt5tXru0fFP9xVOWpIuZokqV7hqFTz/vLNfa52c\n62DQyb++/fb49x/yhZd+gmk7wHBRMSOFxZiAn+q2A3zhpZ/A3dfFvf/DNTP56I3N1He3UTzUz0Bh\nCQfLa7BnL6HWhfHnqmhLLoqIZANVC8lhrz3+PNc8s5bKgR66qmdQOdDDNc+s5bXHn0/qOOIpK9W1\nbSfvdFmG/EFKCjwM+YO802Xp2rZzwtvvaVjAwv07qe1oxdfbRW1HKwv372RPwwK3n1ZEth7oYvvB\nbg52DdLZ7+dg1yDbD3az9UCXew+SyHKFjY3w2GOwbNmxwLqkBO65Z9LFjLGYtu1diip8UFBAwAIF\nBRRV+Ji27V1X9v9y+Rzm7N9J8VA/w4XFFA/1M2f/Tl4un+PK/kflWuMPVbUQkVykmescNu+59QR8\nPgbDGnMUYZn33HpXZgMjFU/jiPeKqik+fJgj+aUERoJ4PXlU+/t4r7aWT0xw+4vffxObl4fFYoJB\n5++8PC5+PzULYw/3DNE7FCDf48HrMQSD0DsU4HDPkHsPsm4d3X2DDGzdhbevl0BpGcVzTqbcrXzi\nxkZIwsJiM8X1eFRu3UT79HpqWvdT1t3BcEERbXWzqNy6ybXHSJczRcmkqhYikos0c53DZnW30lNQ\nOmZbT0Eps7pbkzqOeBpHPLn4M9DVTXFfDx4DxX090NXtbJ/AvObtDJSU0VM9nZ7pM+mpns5ASRnz\nmre78lwmdIKW5P3DAYwxgA3liluMMfQPBybdXbR6X3sD/5Zt5A0PESgpIW94CP+WbfS+lrrW4dHq\nWHQm/V09mOFhvHlghofp7+qhY9GZrux/3sHd+DoOM1hWTvv0egbLyvF1HGbewd2u7B/S50zRid6P\nblPdahHJRQquc1jVovl4e7vHdL3z9nZTtSi5jTni+QLedNLpfP+zN9BbVsH07jZ6yyr4/mdvYNNJ\nE1c/LvR6qCgpwJNnCAQtnjxDRUkBhV7PhLeP2xQpGYVeD+e07Wb1cw/y3R+vZvVzD3JO225Xx9N7\nuB2LoR8P/cNB+vFgMfQenrxMXsRCgdqBcy9iw3kruf7mB/id7/yWn77RHP++wzxx4XV01NZjjKFw\nYABjDB219TxxoTtnWGrsEEFrGPY4J/OGPV6C1lBj3TuDMOZMkTFOC3efzzlTlCxNTXTfdQ+bN73P\nS30FbN70Pt133ZOwAFuNdkQkFyktJIfV3nELhXfdw4fDfbSNFFEzMsgpJZbyO25J6jjiKStVVuhl\na/3p7J6zEK/HEBixDPlHqC+c5K199tkUvfIKRSUlUFro1JXuH3TqSifCFCXeLh/az6dfXMdAsY/u\nmjpq+3u55cV1/PaPvuzaEDo8hdQOt1E10IsnGGQkL48hTz4dnhpmxLPjUKC2pQ96ugc44/AOzt/4\nEu/MOYMfbP8DYCXXnD3blefwWs1c/Df9Jct/88zROtdvXng5b9XM5Usu7L+kehre7i56RvwMGi9F\nNoCvyENBtXtB4KzuVg6X15Ifti3ZZ4oOf/dh3u83BHyllHgNXYFStvV0Mfe7D1P7o8RUmVFVCxHJ\nNQquc1ljI+Vr7mfJ0SoSc92rIhGlWL+AF51UQXG+h0Oh3OWyQi8nTyvm1NpJysDdfTfs3+/MIPf1\nOXWx58xxtifCFB0kb/rgZd7zVdCXX8JI0NJXXEaBN4+bPngZiKD9ewQO+6qZ2boPAxgsBvDaIId9\n1cSzjHM0UOvv7eeMj97H7/HSU1DMvI8+4I7f/Cs/LingmrPdCH2d1KH3Chdw4OYzjm7rHvBzcmmB\nK/vnrLMoKCmh+uBB6OkBXwXMnAmnu9b/kapF8+nY/iF+XwX5XoM/YJN+pqh9604C5bXke52Tlvle\ng7+snPatO1UVRUTEJQquc12y6yK7bLSN9vw635hOZZOmlDQ2wgMPJKYs3UQaGuhoPsDuYe/YUoGh\nluS1bQcxp9ezp30grL7yNGraDsb0cBPVC/d68vDneeguLMXv8ZI/EqDYP4jXE19W2GigdsrenQx7\nvPg9XrCWksAQA8VlnP/qv4Mr88rO6/y3z2xlS4ufocAIhV4P00rzJ22XHrVVq5x0ncWLx3ZoXOXO\nDxxIjzNF+8vrqBnuYTC//Og233Af+8vr3GsjLyKS4xRcS0aLKaUkyh8U8TS42fG5Kxm69+vklZVT\n4vOR19XFvt5uDn3xdieYaWigpq2NmjlVx+7U2ekE/VGarF74n/uHeHfWAk450kLJcD/9BSXsqmug\nLuiP+jHC7S+vw9ffRenQAP35RVgL+SMBevOLOeIpoqHncFz7P87R3kBm3HUXNDay47av0fnQWoq2\nbWVw1mwqb/sap7v5o6uxkfIbrmfJt78Nra1QV5f4Dprj7FpxFTXr/pn+Pj9d+cVU+Aco8veza9UN\nXJy0UYiIZDcF15LxEpnTGW+HuX8LzqDsmtu44NVnj+YKv3DZ9fQGZ3AfHJsxhbEzppO0bz+RyRp2\n7PFNp6y3k62nnkGegaCF4v5u2mrjSwTYteIqzvrBd/B78skP+LEGCkZGeK+2nqL+XvJPOzWu/Ydb\n/3YL9dNKWHDSsYzl7gG/a81INjZ38I+Hffiuv/vYGZDDfv6iucO991ZTEzzxBCxaBJ/8pPNaj15P\nUoBdddF5fGv3YX7/3Reo72ylpbKOtY0r+fxF5yXl8UVEcoGqhUjO2bHhBV5fcS2blpzL6yuuZceG\nFya9bTwNbsCp4d2+aCkbbv5rHv36/2PDzX9N+6Klx2p4NzbCN74BNTXQ0uJcfuMbMQVbkzXs+NmS\ni5nJMOVDfYyMBCkf6mMmw/z2nN+N+jHCnXPtpTzw6et5b8aplPkHsMawuW4ufo+XSn8/r19weVz7\nD5foZiTxvs4RCV/cmpfnXFZUONuTZHNLN+cPt7Js72bm73uPZXs3c/5wK5tbupM2BhGRbKeZa8kp\nOza8wNC9X8dbVs7gjJl4O9oZuvfr7ABOv+KS424fT4MbiLCJhkt575M91qEFZ/LsrEouePVZTjrU\nQvuMep499zICZyyL6/GWzp6G7/xz+XLtPBbu385VW15kdtchjpTV8KMzriJQerJLGdeJb0YS7+sc\nkSkWtybD7J8/wXXrH8RfWMRwZRWVQwNcv/5BHjN5sHJx0sZxQk1NyVsTISKSAAquJad0PrSWYFEp\nR0wRga4hvJ4iqotGGHhoLUwQXJ9cVcL7h3o51DtE31CA0kIv08sKmTt9kmok44wuuATGLLh0bSFe\nBI9106ca+MW7RTT/8eIx2//ChUYeX/r0XF7e1cZ7sxfwrTkLCVon7aSkII/q4ZG49z8q0ccxKZ0E\nGxqcKjWj5RjBSQ2JIb8+Vpe/+BjDBYX4i5znNVxUgrWWy198DHCvXX3MRuvCV1SMrQsf49kcEZFU\nUFqI5BRv84d8RBHBoMXjMQSDlo8owtv84YS3X1JfzvaPuukbClCUn0ffUIDtH3WzpL58wtuPl8wm\nGpM91jVnz07YGJbOnsasyiIM4B9xmvL4irx48/Iom6zWeIyPk8jjmJROgqtWOfn0nZ0QDDqXLlck\nmUp1XycD+UUErbMaNGgtA/lFVPd1Jm0MJ5QGqTMiIvHSzLXklJbKOnzdnQyWOcGxyYOS/j5aKuv4\n+AS339zSzcKZ5WPqaJ9aU8rmlm6uOTuyx0xmE43JHiuRY/jEqTUU7evkw/Y+Bv1BjIFTqkpZdFKF\nq4+TyOcQTyOjiI3m14enPCS5Wkj+zBnUtnfSmefBP2LJ9xiq7Qj5M+NqJ+SeNEidERGJl4JrySn/\nee5l/P7T38cYQ39xKSUDfZQM9vHLS/+QKya4/b72fmZVlTC7uvTotqC17ubiZrgl9eX84t0DlBR4\nqSrNY9AfZF9HP9ef4053xmRJxo+gjTPmsf6ztx4r6zijnqUJfcRx7ryTgrvuYnqxgfJSp5HS8GBM\n1WkSIg1SZ0RE4qW0EMkpReedy79f/SV6fRVUdx6i11fBv1/9JYrOO3fC259cVULvYGDMNtdzcTPc\n5pZuFswop7TQy6A/SGmhlwUzylWBYpzRso7tfcNjyjpubO5I3iBuvBHWrHFSLY4ccS7XrHG2p4M0\nSJ0REYmXZq4lp1y1rJ5/PLKYjsVnRbS4L5kLEjPVvvZ+Tq4u4ZQaze6fyGR1yN2q1R2pjRevZP20\ns8c2RUrao08hDVJnRETipeBackq0ubVJycXNcEmptJEE8XTijERSyv1NId6mSEnhUmlKEZFUUXAt\nOSfa3NpkLkjMRNkwu5+MoDMdfoSky+y5iEg2U861iMQlmeUGEyUZHRqTUu5vConudOmGjc0drH56\nCzf8sInVT29Jbk66iIgLNHMtInHL9Nn9ZKRspEOKUTrMnp9IRqStiIhMQcG1iOS8ZAWdqf4Rku4p\nPEpbEZFsoLQQEcl56ZCykQzpnsKTCWkrIiJT0cy1iOS8dEjZSJZUz56fSLqnrYiIRELBtYgI6R10\n5op0T1sREYmE0kJERCQtpHvaiohIJDRzLSIiaUNnEEQk02nmWkRERETEJQquRURERERcouBaRERE\nRMQlCq5FRERERFyi4FpERERExCUKrkVEREREXKLgWkRERETEJQquRURERERcouBaRERERMQlCq5F\nRERERFxirLWpHkPMjDGHgQ9TPY40UgO0pXoQOUbHPPl0zJNPxzz5dMyTT8c8+TLtmJ9ira2d6kYZ\nHVzLWMaYN621y1M9jlyiY558OubJp2OefDrmyadjnnzZesyVFiIiIiIi4hIF1yIiIiIiLlFwnV2+\nl+oB5CAd8+TTMU8+HfPk0zFPPh3z5MvKY66caxERERERl2jmWkRERETEJQquM5AxpsgY02SM2WSM\n2WqM+V+h7Q3GmNeNMbuMMU8YYwpSPdZsY4zxGGPeMcb8InRdxzyBjDF7jTGbjTEbjTFvhrZVGWN+\nHTrmvzbGTEv1OLOJMabSGPOkMeY9Y8x2Y8wndcwTxxhzeuj9Pfqv2xjzZzrmiWWM+fPQ9+cWY8xj\noe9VfZ4nkDHmq6HjvdUY82ehbVn5PldwnZmGgM9Ya88ElgKXGmPOAf4P8B1r7TygA/jTFI4xW30V\n2B52Xcc88S6y1i4NK9f0V8CLoWP+Yui6uOefgeettR8DzsR5v+uYJ4i1dkfo/b0U+DjQDzyFjnnC\nGGPqga8Ay621iwEPcC36PE8YY8xi4ItAI87nyu8ZY+aRpe9zBdcZyDp6Q1fzQ/8s8BngydD2dcDK\nFAwvaxljZgG/C6wNXTfomKfC53GONeiYu8oYUw5cAPwAwFo7bK3tRMc8WS4G3rfWfoiOeaJ5gWJj\njBcoAQ6iz/NEWgC8Zq3tt9YGgN8CV5Kl73MF1xkqlJ6wETgE/Bp4H+gMvWkB9gP1qRpflvon4G4g\nGLpejY55olngV8aYt4wxN4e21VlrDwKELqenbHTZ51TgMPBIKP1prTGmFB3zZLkWeCz0t455glhr\nW4B/AJpxguou4C30eZ5IW4ALjDHVxpgS4DLgZLL0fa7gOkNZa0dCpxFn4ZxmWTDRzZI7quxljPk9\n4JC19q3wzRPcVMfcXedZa5cBK4DbjTEXpHpAWc4LLAMestaeBfSRJadp010ov/cK4P+neizZLpTX\n+3mgATgJKMX5jBlPn+cusdZux0m7+TXwPLAJCJzwThlMwXWGC52y/Q1wDlAZOsUFTtB9IFXjykLn\nAVcYY/YCj+OcPvwndMwTylp7IHR5CCcPtRFoNcbMBAhdHkrdCLPOfmC/tfb10PUncYJtHfPEWwG8\nba1tDV3XMU+cS4A91trD1lo/8DPgXPR5nlDW2h9Ya5dZay8A2oFdZOn7XMF1BjLG1BpjKkN/F+N8\nUGwHXgKuDt1sFfDz1Iww+1hr77HWzrLWzsE5dfsf1to/Qsc8YYwxpcYY3+jfwO/gnFrcgHOsQcfc\nVdbaj4B9xpjTQ5suBrahY54M13EsJQR0zBOpGTjHGFMSWjsz+j7X53kCGWOmhy5nA7+P837Pyve5\nmshkIGPMGTiJ/x6cH0g/tdZ+wxhzKs6sahXwDnC9tXYodSPNTsaYC4GvWWt/T8c8cULH9qnQVS/w\nE2vt/zbGVAM/BWbjfEn+gbW2PUXDzDrGmKU4i3YLgA+AGwl9zqBjnhChHNR9wKnW2q7QNr3PEyhU\nwvYLOKkJ7wA34eRY6/M8QYwx/4mzVskP/IW19sVsfZ8ruBYRERERcYnSQkREREREXKLgWkRERETE\nJQquRURERERcouBaRERERMQlCq5FRERERFyi4FpEJEmMMSPGmI1h//4qtP18Y8zW0LZiY8ya0PU1\nMTzGveOuvzrF7ZcbYx4I/X2hMebcKB/vUWPMHmPMl0LXv2yM2WKMeTbUdRBjzKeMMf8Ydp+5oefa\nG81jiYhkApXiExFJEmNMr7W2bILt/wK8bq19JHS9G6iNpcbuZI8R4X3/Fui11v5DFPd5FPiFtfbJ\n0PVNwFnAfcBrwC9w2h1fa63tcGusIiLpSjPXIiIpZIy5CbgG+BtjzI+NMRuAUuB1Y8wXQh1Z1xtj\n3gj9Oy90vzJjzCPGmM3GmHeNMVcZY74JFIdmhX8cul1v6PIJY8xlYY/7aOg+FxpjfmGMmQN8Cfjz\n0P3PD81I54duX26M2Tt6fQr5QAlOs4g/Bp4dH1iLiGQrb6oHICKSQ4qNMRvDrt9vrV1rjPkUY2d/\ne621S0N//wT4jrX2lVDb4F8CC4DVQJe1dknodtOsteuNMXeM3necx3E60o2ma1wM3Ap8AsBauzc0\ng3505toY8xvgd4GngWuB9dZa/xTP8R9wZqy3Av8Vuu+lURwjEZGMpuBaRCR5BiYJfE/kEmChMWb0\nerkxxhfafu3oxghmhp8DHjDGFOIEuy9bawfC9juRtcDdOAHyjcAXpxqstfZfgX8FMMb8T+ABYIUx\n5n/gtPi+01obnGo/IiKZSmkhIiLpLQ/4pLV2aehfvbW2BzBAxItmrLWDwG+Az+HMYD8ewX3+C5hj\njPk04LHWbon08YwxJwFnW2t/Dnw99JhDODPmIiJZS8G1iEh6+xVwx+gVY8zSSbZPC/3pP0Fe9OM4\nM9Dn46SXjNcD+MZt+xHwGPBIlOO+Dyd1BaAY54dAECcXW0Qkaym4FhFJntHFhqP/vhnBfb4CLA8t\nWtyGs+gQ4O+AaaGyd5uAi0Lbvwe8O7qgcZxfARcAL1hrhyf4788AV44uaAxt+zEwDSfAjogx5iwA\na+07oU0/ADYDy3Aqh4iIZC2V4hMRkUkZY64GPm+t/eNJ/vujhC3GjHLfKsUnIllHCxpFRGRCxpj/\nC6wALjvBzbqA+4wxNdbaf4lwv3OB9UBr/KMUEUkvmrkWEREREXGJcq5FRERERFyi4FpERERExCUK\nrkVEREREXKLgWkRERETEJQquRURERERcouBaRERERMQl/w1YxfKbkDfFqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11022a4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Scatter plot of a team effectivity against the total goals conceded at home and away\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.scatter(x=df_all['overall_effectivity'],y=df_all['total_home_goals_conceded']\\\n",
    "            , alpha=0.6, label='Home')\n",
    "plt.scatter(x=df_all['overall_effectivity'],y=df_all['total_away_goals_conceded'],\\\n",
    "            alpha=0.6, color='r', label = 'Away')\n",
    "plt.xlabel('Effectivity [%]')\n",
    "plt.ylabel('Goals Received')\n",
    "plt.title('Correlation of Effectivty and Goals Against')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There seems to be no correlation, but to be entirely sure we can run a pearson coefficient showing a low value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>overall_effectivity</th>\n",
       "      <th>total_home_goals_conceded</th>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>overall_effectivity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.478743</td>\n",
       "      <td>0.485431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_home_goals_conceded</th>\n",
       "      <td>0.478743</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.964019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "      <td>0.485431</td>\n",
       "      <td>0.964019</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           overall_effectivity  total_home_goals_conceded  \\\n",
       "overall_effectivity                   1.000000                   0.478743   \n",
       "total_home_goals_conceded             0.478743                   1.000000   \n",
       "total_away_goals_conceded             0.485431                   0.964019   \n",
       "\n",
       "                           total_away_goals_conceded  \n",
       "overall_effectivity                         0.485431  \n",
       "total_home_goals_conceded                   0.964019  \n",
       "total_away_goals_conceded                   1.000000  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Calculate pearson coefficient to verify if there is correlation between the chosen columns\n",
    "df_all[['overall_effectivity','total_home_goals_conceded'\\\n",
    "        ,'total_away_goals_conceded']].corr('pearson')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pearson coefficient confirmed our thoughts, but we found something interesting again.\n",
    "The goals conceded home and away are correlated similar to the scored goals. This definitively is showing information we did not ask, but that is insightful.\n",
    "\n",
    "As an exercise of curiosity, we can plot the effectivity, goals scored and received, home and away. Then we can mark the top teams and verify that our effectivity distribution is a little skewed, the goals scored home and away overlap and we have a big scatter plot thanks to the received goals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LS/HSSy+hqqoKX3/9NU6cOIH/9//+HwB0eJ6rqqpQXFwc8jsQxwkE/ua6mq9VVVUBn+/s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\n/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WEYhEIhhoaG8Pl8bNmyZc4xssuBoihVMeHrRiGdTtPf308kEilNDlvVsKwqJSJzrUve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WiVPTlx4gRZWVl4eHjQvXt3pTk+Njb2kmUrrc2yXlur1Sr12nWzJ46OjhQVFZGWloaXlxdh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\nAABgJyIAAMBORAAAgF15dkzCQ5W+VQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112567470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3D Scatter plot of a team effectivity against the total goals scored/conceded at home and away\n",
    "\n",
    "# All teams plot\n",
    "fig = plt.figure(figsize=(14,8))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "ax.scatter(xs=df_all['overall_effectivity'], ys=df_all['total_away_goals'], zs=df_all['total_away_goals_conceded'],\\\n",
    "            alpha=0.4, marker='^', color='r', label = 'Away',s=50)\n",
    "ax.scatter(xs=df_all['overall_effectivity'], ys=df_all['total_home_goals'], zs=df_all['total_home_goals_conceded']\\\n",
    "            , alpha=0.4, marker='o', label='Home',s=50)\n",
    "\n",
    "# Top 25 teams markers/identifiers\n",
    "df_top25 = df_all.head(25)\n",
    "ax.scatter(xs=df_top25['overall_effectivity'], ys=df_top25['total_home_goals'], zs=df_top25['total_home_goals_conceded'],\\\n",
    "            alpha=0.4, marker='s', color='m', label = 'Top Home', s=80)\n",
    "ax.scatter(xs=df_top25['overall_effectivity'], ys=df_top25['total_away_goals'], zs=df_top25['total_away_goals_conceded'],\\\n",
    "            alpha=0.45, marker='s', color='c', label = 'Top Away', s=80)\n",
    "\n",
    "ax.set_xlabel('Team Effectivity [%]')\n",
    "ax.set_ylabel('Goals Scored')\n",
    "ax.set_zlabel('Goals Received')\n",
    "plt.title('Spread of Teams\\' Effectivity, Goals Scored and Received', y=1.04)\n",
    "\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The 3D plot help us distinguish what we were looking and we can also see the top teams have the correlation that the more they score the more effectivity they have."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='home_away_goals'></a>\n",
    "### Home and Away Goals are Correlated!\n",
    "\n",
    "Thanks to our pearson coefficient calculations we found that:\n",
    "* Goals Scored Home and Away are strongly correlated\n",
    "* Goals Received Home and Away are strongly correlated\n",
    "\n",
    "We can show this correlation in the following scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BLzD1s+fw4YKlbfSHw7QGAtO2zbcqiZRe/1A/rQ2t07Y1VjXSP9RfohHNTiks\nIiefos1cO+cOOeee8H4PAc8CrbMc8l7gdufchHOuHzgA6L9AIgXUc/gwUed4anSU/3z1VZ4aHSXq\n3Lxmc+cyC12McnwztVVXMxyb/t28EFVJpLTamtsYnhietm14Ypi25rYSjSgzpbCInJwWJOfazNYA\nG4HHvE2fMLN9ZnazmZ3ibWsFXko5bIDZg3ERydOToRC/HB0lHI9T5/MRjsf55egoT4ZCcz7nXNIv\nFiLwVVWSpalzfSfBiSBD4SHiLs5QeIjgRJDO9Z2lHtoJlMIicnIqenBtZvXA94H/4ZwbBv4OeC2w\nATgE/J/krmkOd2nO9xEz22Vmu44ePVqkUYssTcOxGGZGwOcD76eZnRDo5mMus9C5BL7ZcsOzva7G\nMktTx6oObrj4BlpqWzgYOkhLbQs3XHxDWaZa9A/101jVOG1bOaewiEhhFLUUn5lVkgisb3PO/QDA\nOXc45fV/BO72ng4AZ6Qcvgp4eeY5nXPfAL4BsGnTphOCbxHJrNHvZygaZSIeJ2BGxDmct32u5tIU\nJls5vmy54bnmjquxzNLUsaqjLIPpmdqa2xgcG6S5unlqW7mmsIhI4RQtuDYzA74JPOuc+6uU7Sud\nc4e8p+8HnvJ+vwv4FzP7KxILGl8HKDFNpIA2NjRQ6/NxaHKSUDRKQ0UFZ1VVsbaubs7n7Fyxgh3P\nPw8kgvThWIxgNMr2VatmPW62wDfbgseFWBApMl+d6zvZ8eAOIDFjPTwxTHAiyPYt27XQUWQJK2Za\nyJuBDwOXzCi79yUz+4WZ7QPeBnwawDn3NHAn8AzwH0CXKoWIFFbnihVU+HycX1fHZaeeyvl1dVT4\nfPPKQy5G+kW2VJOFWBApMl+ZUlgALXQUWcLMucWbWbFp0ya3a9euUg9DZFHJVDavnLoZdvX1nZBq\nMhSN0lJZSXd7e9bXRcpZ1z1dJ6SLDIWHaKltofvd3Qs2Ds2ei+THzHY75zZl208dGkVOMh1NTXS3\nt3PvunV0t7dPy2Eul26G2RY8qhKILGblsNBRZQJFikfBtYjkXU6vUF0eM50nW6qJKoHIYlYOtbpV\nJlCkeIpaLUREFod8uhkWqstjtvNkq/ShSiCyWM220HGhLLZOlyKLiWauRSSvpi5zaRqTTqHOI0tb\n70AvXfd0sfW2rXTd07Uk0hbKoVZ3OcyeiyxVmrkWkbzK6eU7y51pkWQ+55GTUzIvuKmqaVpecD6B\naCkX7c2jn/fsAAAgAElEQVR27VLX6i6H2XORpUoz1yIylcMci8e579VX+fnwMPUZGsskZ7mPRCI8\nEgzyo+PHeWBoiFrf9P+cZFskuRAt0GVxm29ecCkX7ZX7gsFymD0XWao0cy0iU0bicd7U2Dg1e50u\nl7pzxQquOXCA/nCYWp+PCmAkFmMgHKY3GJzaN1ujl7k2n5GTx3zzglODc2DqZ8/enqIHkaW8dq5K\nPXsuslRp5lpEgNxzoDuammgNBKj3+4k6R43fz5bGRlbX1EzbN1ujF1X8kGzmmxdcypJ35VBuT0RK\nQzPXIgJkz4FOzZ9+enSUjXV1rKiqmto37ty0fOm26uoTGr3MTPtQxQ+ZzXzbh7c1t53QrGWhFu2V\n8toiUlqauRYRYPYc6Jn505Vm/DwU4kgkcsK+SWr0IvM13/bhnes7CU4EGQoPEXdxhsJDBCeCdK7v\nLPrYS3ltESkttT8XEWB63enUHOgb1qyh5/DhabPQRyIRdnqLHt/W3Dxt39SZ6HJqqS5LRz7tw8u1\nWoiILD65tj9XcC0iUzIFw1v37aM1EMBnNrXvKxMT7Bkd5by6urSBcz6BtYJwycfW27bS2tCKz37z\nx9e4i3MwdJB7P3RvCUcmIktZrsG1cq5FlrB8g9ZMOdDp8qer/X4uX7aM7vb2tNfNtYtjoTo+SnpL\ncfZU+cwiUs6Ucy2yRGWrMz3bcV19fWzdt4+uvj56g8G886fz6b6oTo3FU4xay+XQMVH5zCJSzhRc\niyxRcwlaMwXkQF5l87KV4ZvrvpKf+TZhmalcGqOoAYqIlDOlhYgsUXNpLz5b45fu9vac0zRyKcM3\nl30lP/NtwjJTOTVGUQMUESlXmrkWWaLm0l68ULPI+aSRqGRf8cy3CctMaowiIpKdgmuRMpcuBzqX\nfQ9HIrwwPp5z0NobDPJiOMzdx47xSDA4VcN6LrPI+XRfVKfG4il0bnKhg/VU5ZDLLSJSCCrFJ1LG\nZqs9PVvVjeS+L3qpIWPOzVotJHls1Dl+OTqKmeGA19fUUOHzKdhdxApZLSSZc91U1TStY+J8852L\ndV4RkUJSnWuRJaCrr++EfOShaJSWysoTSuDls+9s1zkSidA3Ps7xyUmWVVZy89q18w6sVcd66ShG\nab98msKIiJSK6lyLLAGZFiU+GQrR1dc3LVidywLGdNc5LRDgtECAuHMcjEQKElirjvXSUYyFhIVe\neCkiUkoKrkXKWLpKGv3hMAORCGfMKJdX76WCzKXqRiErdsycpT48MZGxAkm24Foz3otbrrPcagoj\nIkuJFjSKlLF0lTT6xsdpr64mEo/zs+FhdgaDHBgf59djY+wcHuauwUF+OjTEr8bGcq66UaiKHenq\nZD8UDBKeUbUkdfY900LNuTbBkfKQT01sNYURkaVEwbVIGUtXSWNVIECd38+uUIjxeJxav5+xaJSn\nxsZ4TWUlp1RU8Go0Sl84zLblywGyVhspVMWOTI1rnh4bm7ZfcvZ9tsB55rki8TgHxsf5wDPPZK2a\nIoWXTzWP3oFe/vSuP2XvK3t56shTDI4OztrARk1hRGQp0YJGkUWmq6+P/zx+nDhQ5Ut8P355YoKY\nc6yurua3vYB4KBol5hwjsVhO1UYKYeu+fbQGAvjMprYdnpjg0eFhLjnllKkx7Bwepr26mtfW1k7t\nN3PxZeq5jkQi7AqFqDRj0jkubGoq6n3IdPlU80juu/eVvTRVNRGJR5iMTbJp5SZa6hLB870furdE\ndyIiMne5LmjUzLXIIpNM4cA5cI5IPM5EPM6yigpCKekXjX4/j4dCebdAz2a2utvpGtdU+f1c1Nx8\nwux7W03NtP1mLr5MPVff+DiVPh9mRqN3P/O9D8ldPm3Uk/ueWnMqk/FJqiqqqPRX0ne8r+h51KqV\nLSLlQMG1yCLT0dTERc3N+MwYjcep9vk4PRAgDjSkdFdMBqaF6LiYlC0POlPu9rVnnEF3ezv3rltH\nd3s7GxsasnaPTD3XsPdlIhKP0+4F5fO5D8lPPp0Zk/u2L2snEo8QiUYI+AIcHz9e1DzqfHK8RUSK\nKWtwbWbfN7N3m5kCcZEyce0ZZ3B2TQ1bGhu5sLGRs6qrGY/HWemV0EsGtZvr6/NugT6bTDnVyRnk\njqYmti1fztOjo/zb4CBPj46ybfnyE1I3cllAmZoH7jPDZ8amhgZO80oGzuc+JD/5dGZM7nta3Wls\nWrmJ6opqghNBltUuK2oedT6z6yIixZRLwPx3wAeB58zsi2b2+iKPSUSymLkAcW1dHV8+6yzW1tZO\nW5B47Zln5l0FZLa0j/5weNaZ8N5gkDuOHuW8ujre19LCeXV13HH06AmLD3NdQNnR1ER3ezvfPfdc\nzq6pIeDzzauaycmmUGkS+VTzSN23pbaF8087n/WvWc/NV9w8a2A937HmM7suIlJMOS9oNLMm4A+B\nzwMvAf8I3Oqcmyze8GanBY0i2eVTKzpbu/VsXSDn0yWykPchhW8pnk9nxny7OBZirOryKCLFVtAO\njWa2DPgj4MPAk8BtwG8DncDFcx+miBRbR1NTzkFoatoHnNjwpXPFCnY8/zzAtOB7+6pVQOaOkoXI\njc7nPmR6mgQw9bNnb8+cgut8OjPm28WxEGPtXN/Jjgd3AEwL0Ldv2Z7zOERECiGXnOsfAD8FaoH3\nOOeucM7d4Zz7JFBf7AGKyMLJlvaRLZ1jZrWQI5EIDwwN8fToqGpTL7DFlCZRiLGqVraIlItcZq6/\n7py7P90LuUyNi0ju5pr6UKiUiVzaoM82g5w6sx2OxXgsFALgTQ0NU5VFVJt6YRSipXi+6R2lHCvk\nP2Oeq4V6H0Rkacgp59rMzgfOBab+H9Y59+0ijisnyrmWYkoXsAIZg9j5Brjp8p1fGB9nVXU1Y/F4\nxnPOlicN8KUXX+TxkREANjc0cO0ZZ8w55zqf9+3uY8eoNOOCurqpCh+Fyr+W7Oabx1zonO1yudZS\nGpuILKxcc66zBtdmdh2JvOpzgXuBdwGPOOeuzHLcGcC3gdcAceAbzrmbzOxU4A5gDfA88PvOuVfN\nzICbgK3AGPAnzrknZruGgmsplnRB5ovhMM45VtfUpA1i5xuUzlwMeCQSYefwMPV+P29rbs54zkyL\nCGPxOAMTEzw/MUGt18kxGaTfdPbZswbYhZgFT9etMe4cByMR7l23Lu/zSf7mM+O60AsEy3V2WAsl\nRSSpkAsarwTWA086564ysxXAP+VwXBTY7px7wswagN1m9l/AnwA/cc590cw+C3wW+AyJoP113uO3\nSJQA/K0criNScOkW9u2eTBTGWZ9msR8w60LAXMxcDNg3Pk6tz0fEuama0unOmWkR4X3Dw1SaUev3\nT7VJNzOOTk7OOq5CLRzMJcVEims+aRL9Q/20NrRO21bMnO1ipXTM10K/DyKy+OUSXI875+JmFjWz\nRuAIcFa2g5xzh4BD3u8hM3sWaAXey28qjPQAD5IIrt8LfNslptJ/bmbNZrbSO4/IgkoXsE7E4yfs\nl7rYL7n/kUiEvvFxhqNRfGZ0BoM5Baszg9FQNEqFGRXAI8EgoViMep9vWrCa7jj4TXfGiXicupQF\nigEzRmKxBelsmK2yiJS3QuVB56vcZrBL9T6IyOKVSxOZXWbWTKKu9W7gCSCv6v5mtgbYCDwGrEgG\nzN7P07zdWknUz04a8LbNPNdHzGyXme06evRoPsMQyVmy6sWRSIRHgkF+dPw4w7EYM5OokjOxqfvv\nCoUIx+NUmhFzjiufeYYLd++mq6+Pb738csYGLTO7FgZ8vsTzWIyBiQmOT07y4sQEvw6HZz1uqjtj\nQwNV3sx3UsQ5qny+BZk9zrVRjJSnfBrHFEo5tjAvxfsgIotbzk1kYCpIbnTO7cvjmHrgIeBG59wP\nzGzIOdec8vqrzrlTzOwe4P91zj3ibf8JcK1zbnemcyvnWoqlNxjkmgMH6A+Hp/KVg7EY0XiczQ0N\ntNXUpM25PjA+Ttw5MGM0FsPF41T5/TT4/ZweCLBndJQN9fXU+3w8NTZGMBrloqYmrj3zTDqamqbl\nO9ea8cDQEKNeoG5A1DmqfT4uOeUUvnf++dPGm27x5aeeey7vnGuZXbnNrBbTQt9rueY3n0yfuYhk\nVsgFjd8mUef6p865X+Y5iErgbuA/nXN/5W3bD1zsnDtkZiuBB51za83sH7zfvzNzv0znV3AtxXTl\nL37BntFRIvE4DRUVtNfUEIrFeCUS4UxvtnpmtZAPPPMMcedorKhgLBbDzKgyYzQep8HvZzgapdKM\nSW9m2nn51GfX1KSd1V3xyCOMx+PEgUqfj0a/Hz8QA17YsiXrPfQGg3lVC5HZlUvliKUa7G29bSut\nDa347Dd/VI27OAdDB7n3Q/eWcGQiIoVd0HgLiW6Mf2NmZwF7gIedczdlGYAB3wSeTQbWnrtIdHb8\novfz31O2f8LMbiexkDGofGsppTHneFtz87RqFy1eUJyu2kVHUxOXL1s2lf/8o2PHphYkNvj9hKJR\n6nw+DkYinBYITAXXY7EYTRUVaRcZVvv91Pn9VKXkTU+kNGnJpqOpie9dcEFe960245nNtZNgIYPh\n1AA/NXViMZWGy/R+KL9ZRJaCrDnXXgOZG4G/JFElZBPw8RzO/WYS7dIvMbM93mMriaD6HWb2HPAO\n7zkkyvz9GjhAIr/76jzvRaSgZnYbhOzVLlLzn+v9fkZjMSLxOO01NTRUVDDqLYoMeAF7xDkavPJ9\n6RYZbq6vZyweZyIexznHRDzOWDzO5vriNEdNliAcnJykNRCYavySa2fF3mAwY075UjCXToKFziNO\nDfB95qO5upmmqiZ69vbM6XwLbbb3Q/nNIrIU5NL+/CfAo8A2YD+w2Tn3+mzHOececc6Zc26dc26D\n97jXOXfMOfc7zrnXeT+Pe/s751yXc+61zrkLnHPK95CSyrRQMJnPnE7qIr7migrMjLW1tbRUVrKy\nspLxeJymigomvIB50gu8MwXt1555JmuqqvABo7EYPmBNVRXXnnlmUe45tQRhsvxfclY9m/kG5otB\nW3MbwxPD07Zlm1ktdDC8mNqapzPb+6EW5iKyFOSSFrIPeCNwPhAEhsxsp3NuvKgjEymxZKCcmiKx\nfdWqrCkSqXWiU1Ms1tbV8aEVK7jn+HF+fPw4zgyfc9w/NIQBbz/lFHpnlO3raGria697XUHSNHJJ\n98hUMzuX0n3paoMnty+VtJLO9Z3seHAHwLSc6+1btmc8ptB1khd76kS296Nc612LiOQqa3DtnPs0\nTFX9uAr4Fomui1XFHZrI4peuIct5dXUcnJjgxXCYY9EoFUCtz8dQNMqO55+fWtiYDIafDIUYjsVo\n9PthjiX0UjtOps4qz1xEOVvjl2zB+XwC88UiObOami+8fcv2WYPBTMFwbUUtXfd05Z2HPZcAv1jm\nkku+2L8ciIhkk0u1kE8AbyExe/0C8DCJyiH3F394s1O1ECmmdC3QZ2tpnutCwGS78qdGRxmPxxO1\nqONxqn0+zq+ro6WycqoBSzQe55fj4xjgnOP1dXVUmOVdLzpTi/SWykq629uz3vO25cu54+jRWd+L\nXK9xsklXYeTF4Is451jdvHpOVUfKoVrIXCunlEvFFRGRfBWyFN9fkAiodzvnogUaX0EouJZiyidY\nzCcQ37pvH62BAHcdO8ZEPE7UOSrNCPh8XLFsGQcjkakZ5NkC8EwBa7og//oXXqA1EJhW+STuHAcj\nkRMqn6Q7vufw4azvRb5fRk4mM4PhwyOH8fv8ZVfPOR/zqUldDl8ORETyVbBSfM65L6ectA54H/BB\n59y75zdEkfKWT5pDPvnGbdXV7B8bY9SrRJKsez3ptSVfW1s7de1QNEqtV4YvYEbISw/JlGqRKf2j\n3udjOBZLm+4xU7pUlmRwPtt7Mdcc9ZPBzDziZD3nVItpUSLML5e8EHnVCtBFpFzlUi0kYGbvM7M7\ngUPA24G/L/rIREosn1J8/eFwIic6RaYgeFN9PT8fHmYiHifsPZxz1Pn99I2P07lixdS1/Wa8HInw\nUjjMy5EI/lnGAJmrfWCWd+WTubwXHU1NdLe3c++6dXS3tyuwzmAuVUfKTSnvoRzbpIuIJGUMrs3s\nHWZ2M9APXAn8M3DcOXeVc+6HCzVAkVLJpxRfrsFnbzDIHUePUmVGvddtMeocVT4fyyoqWBUI0NHU\nROeKFbwwPs5wNMqkF3xH4nGGYzFe8ALwdDIF+WPx+FSJwIORCC2VlXmla8ylLKFkthTqOZfyHhZ7\nrW8RWdoy5lybWZxE2/M/cc71e9t+7Zw7awHHNyvlXEux5bpIcbZ8Y2DqHC+Gw7wmEOBQJJI1l/rK\np55iz8gIoViMSS8vu8HvZ0N9Pd87//y04y3mokJ1biysUqU1FLpbZCnuQW3SRaQUCpFz/UbgD4Af\nm9mvgdsB/yz7iyw56fKPM+2XLt8YmJYD/WQoxNDkJK+tqeHXXspIADg+OUkwGp06BmAsHp9qv34k\nEqHPm8l+PBQ6oR52UrLKCDAtyE89bz4UUBdPKeo5z6d1eqZAuhR5zirnJyLlLGNaiHPuSefcZ5xz\nrwWuBzYCATP7kZl9ZKEGKLJYpMs3npkDfWplJWbGYDTKpoYGanw+grEYy9KkaSRTTY5EIuwKhQjH\n41SaUWmWsfNhaofIuaR/pDoZOi6Wi96BXrru6WLrbVvpuqeraLnDc02nKLcc56WQViMiS1fWUnzT\ndjbzAe8A/sA5d1XRRpUjpYVIOUqd7X16dJTVgQDHYjFC0SgVZomfPh+XL1s2a7m6ZHB7YHycuHNg\nxmgsRq3Px3A0ijPj9TU1bGxoKMqMsupWZ1eItIiZdZ/7h/rpO9bHqoZVbFy5saCpFnNNp5hP2b1i\nUbUQEVlouaaFZK0Wkso5F3fO/Wc5BNYi5WjmbO9YNMqjoRAHxsYYjsWIxOPEgRqfL+vMcnIWetI5\nJp0D53Dx+FSVkbFYjBfDYfaPjRVlRjmfCigno0LN5qbOJg+ODbL/2H6ccwxNDBV8hniuFT76h/pp\nrGqctq3UpQM7VnXQ/e5u7v3QvXS/u1uBtYiUjbyCaxGZXWoayODkJKPO4QBHomnLca+iyBsaGnIq\nV9fR1MTly5ZxYVMTNX4/9ZWVjDuHmVHj91Pl93MoEqGpooKew4dnHVtvMEhXXx9b9+2jq68vazCe\nTynCk1EuKRa5pHukBq59x/oI+ALUBeoYiYwUvArGXNMplkLpQBGRhaLgWk5K+QaauUqd7e0bHweg\n1iwRXJNoGNNYUcFYPJ7zOZNl8I5PThIAJrzSfM1+f06NZWBu+dMqvze7bLO5uc5spwauoUiIgD9A\nJBahIdBwwjlzMVtA37GqgxsuvoGW2hYOhg7SUtuS02JG5TiLiOQulyYyrzWzKu/3i83sU2bWnO04\nkXJVzIV6qbO9oViMKjMwo76igjOqqzk9ECAcj9NWXZ1zgJ9MD1lWWUkwFqPa5+OUigqq/X4iztHg\nVQWZbUY5U3OZ2Wa7C7k4cinKNpub6+LB1MC1vrKekcgIk7FJ2k9tP+Gc2eQS0M8lnWKuQbmIyMko\nl5nr7wMxMzsb+CbQBvxLUUclUkRzCTRzlTrbW+/zUUmiSUydGc45RmIxKn0+NtXX5x3gv762lqhz\n1JgRcY6RaJSJWIyVgUDWGeW55k+r42Jm2WZzc81TTg1cm2uaMTPWLltLS11L3jPExWyuohxnEZHc\nzFbnOinunIua2fuBrzrn/sbMniz2wESKpT8cpjUQmLatUAv1UutdN1dUMBKPs7qigtF4nFejUSp9\nPr6wejW7RkamAnxg6mfP4cMZq4Y0VVTw5sZGnhobYzQSocHvZ0VVFWtra6dVC0lXm7qtuvqEyh/K\nn56fZFCcWrFi+5btU0FnPrWYU+tFz6yCkXrObPqH+mltaJ22rdQLD0VETja5BNeTZvaHQCfwHm9b\nZfGGJFJc+Qaa+TZSSW08k3rs21KO/e6+fTkH+Kkz7VRUsKKqKmNJvNRAPHVGfNvy5dxx9OjUdebb\nXEYSZmui0rm+kx0P7gASAe7wxDDBiSDbt2yf8zmzUXMVEZHSyyUt5CpgC3Cjc67fzNqAW4s7LJHi\nyWeh3nzzs5NpFdevXg3A9S+8QFdfX6JWdY6VOPJJ6ciU8rJrZET50wsslzzlQjeP0cJDEZHSy6uJ\nTLlRExmZq1xnowvRSCV1Njk5a/zC+DhmxpnV1dNmktMFvPmMYas3I+4zm9oWd46DkQj3rluX03hl\nYcxsHpOc2Z7vQkE1VxERKY5cm8hkTAsxs1+QKM+blnNO/08ti1Zq6sZsCpGfPS2tAy+/uqaGWDxO\nS2XlVIC/fdWqtGPqXLGCHc8/P3Xt2VI6yjW3WgHfiVIXHwJTP3v29szrvZlPWomIiMzfbDnXly/Y\nKETK1HyD1d5gkLuPHSPuHI0VFbTX1HBaIECj38/BWCyn2e/URZKFDMQXSuoMbWp5uKVYyi2fLxGF\nXnyoLzAiIuUhY861c+6F2R4LOUiRUplPI5VkOkilGZVmjMfj7AqFOBKJ5D2bnGtJvHKsTV3M8nDF\nlG8+dL7t0AvZ9bBQrdhFRGT+cmki8yYze9zMRswsYmYxMxvOdpzIUjCfYDWZDnJBXR2TzmEkOjT+\nYnS0qJ0Oy602da71nsvJXILVfL9EzHXxYbqgf7F+gRERWYpyKcX3deAPgO8Cm4A/Bs4u5qBEssm3\nPN585JqfPVMyX9tXUcGmhgb6xscZjkbxQclnkxdSOZSH6x3o5UuPfonHX34cgM2nb+baN1+bMW1i\nLvnQ+aZ5ZKuTnTr25D61FbUMDA+wunn1tKB/eGKY85afl/O1RUSkeHIJrnHOHTAzv3MuBnzLzH5W\n5HGJZJSplnOpA9aZAX+y3F5zRQWnBQKcFghMVfk4WQJrmHu950LpHejlmv+4Zio4xeCRlx5h4EcD\nfO1dX0sbLM8lH3ouXyKyLT6cma/+QP8DjEyOsLJ+Jb5q39S1BoYHGJ4YVn1rEZEykEud6zEzCwB7\nzOxLZvZpoK7I4xLJqJjty+cqXT3sgXCYF8PhOeVrLyW51Hsupp69PRwdPUpdZR1VlVVUVVRRW1nL\n4PhgxrSJueRDF6PG9Mx0j0g8Qm1lLX3H+6b2aaxqpDHQqPrWIiJlIpeZ6w+TCMI/AXwaOAP4vWIO\nSk4Oc03tKGb78rmab7m9pa6U5eH6h/qZiE1QH6if2hbwBxiNjGaciZ7LbHuuaR75jj11Br0h0MD4\n5DihSGhq2/DEMBtXbqRzfWdBry0iInOTNbh2zr3gzVyfCXwf2O+cmyz6yGRJm09qRznWcs4U8Gcq\nt1esnPFczruQ+erloK25jb7BPiKxCIGKxGcUiUWoqqjKOBM910C50F8iZqaatC9rZ+fATuoD9cRd\nfFrQr/rWIiLlIZdqIRcDzwHdwN8CfWb21iKPS5a4+aR2zKc8XrG0VVfn3M58vi3VM8nlvMW6dk7j\nK3Cr71x1ru9ked1yRidHmZicYCI6wdjkGC01LbOmTXSs6qD73d3c+6F76X53d0kC15mpJgF/gLbm\nNjas2FCSFBsREckua/tzM9sNfNA5t9973g58xzn3xgUY36zU/nzxmm+b7lxnX+czS5vPselanBei\nnXk+cjlvsa6dTbFafedz/XyqheRz3mI3blFzGBGR8pBr+/Ncgut9M1udp9tWCgquF6+FCPLyCXgL\ncWyuwfh8v1hkkst5i3XtbLru6TqhksZQeIiW2ha6391dtOsWU6m/MIiIyMLKNbjOZUHjLjP7JvDP\n3vMPAbvnMziRhWjTnXaRobc9W3A9l2NzrYddrJzxXM5bqnz1Qrf6LgdzqYUtIiJLXy6l+D4OPA18\nCrgGeAb4WLaDzOxmMztiZk+lbLvezA6a2R7vsTXltc+Z2QEz229ml+V/K7KYLESb7v5wmEa/f9q2\nXKuKzHZsbzDIlU89xeqdO1nxyCO8dudOLty9m66+vpxyl4uVM57LeUuVr16IVt/JnO0Lv3kh5//t\n+Vz4TxcuaO72TIux86SIiBRf1uDaOTfhnPsr59zvOufe75z7a+fcRA7nvgV4Z5rtf+2c2+A97gUw\ns3NJdIE8zzvmb83Mn+ZYWUKK3aY7n0WGuR5ba8Y1Bw7wSDDIZCxGKBbjYCTCgbEx9o+N5bQ4sFhf\nLHI570J8qUlnvjWgkykY+4/t58XgiwTDQV4cfpH9g/uztiUvlkJ8YRARkaUnY1qImb0XWOWc6/ae\nPwYs917+jHPuu7Od2Dn3sJmtyXEc7wVu94L2fjM7AHQAO3M8XuQE80k9yXRsvd/P0clJ6vx+jkej\nVPgS308ngEORCOfX1Z2QOpIpF7sYAW0u5y3GtbMtustW2i7b8ckUjKeOPEWVv4pARYCJ6ASHRg5x\n/mnnlyQVI7UW9kR0gqeOPEUwEuSiMy+id6BXqSEiIiep2WaurwXuSnleBWwGLiaHtJBZfMLM9nlp\nI6d421qBl1L2GfC2iczZfGZpMx07Fo8zEY8TMGMyHsdH4n9EMecIxWInpJ2UsvTdQknOKg+ODdLa\n0Mrg2GDa2eRMpe1yOT6ZghGKhAj4E7WqA/4AoUioZKkYyS8MsXiMR196FAwuXHUhfp+/ZLPpIiJS\nerMtaAw451ID3kecc8eAY2Y21/bnfwf834Dzfv4f4E8BS7Nv2jImZvYR4CMAZ5555hyHIUtFtgod\n85mlTXdsW3U1fWNjRJyj0ucj5lXb8ZvR4M1wp6adzGdR5WIx34V9uRyfbKbSEGggHA0TqAgQiUVo\nCDQsWCpGptn1FfUruKTtkmmVUGaOX0RETh6zzVyfkvrEOfeJlKfLmQPn3GHnXMw5Fwf+kUTqByRm\nqs9I2XUV8HKGc3zDObfJObdp+fI5DUOWiIWaFe4NBunq62Prvn0cnpigxudjNBajBojG40TicaqA\nlYHACYsD57OocrGY78K+XI5P5myvbFjJRGyC42PHOTJ6hFdCr7BzYCebVmatjDQvs82ua2GjiIik\nmsAXtJoAACAASURBVC24fszM/mzmRjP7KDCnv3ea2cqUp+8HkpVE7gL+wMyqzKwNeN1cryEnj/l0\neczVzADe7/NR5/Nxbm0tlX4/DX4/rYEAZ9fWsra29oS0k/ksqlws5ruwL5fjkykYa5et5dTqUxmd\nHKXKV8WK+hW0L2vnjmfu4FtPfKtoHSBTZ9d95qO5upmmqiZ69vZoYaOIiEwzW1rIp4F/M7MPAk94\n295IIvf6fdlObGbfIZGf3WJmA8B1wMVmtoFEysfzwEcBnHNPm9mdJMr8RYEu51ws3XlFkvrDYVoD\ngWnb0uU8z7VDI2RI66ipoaWykvs3bsx6/ELU8y611IV9qc1Utm/ZXtDjO1Z10LGqg657ujhn+TnT\n0jB+dfxXXPfQdWxZtWXazPK2c7ex69CueXc3nK1O9/UXXT+v+y8EdXEUESkfuXRovIREiTyAp51z\n9xd9VDlSh8aTW7Yuj/Pp0JhUiI6G8w3wZz13mQRV8x1HPsdvvW0rrQ2t+Ow3f3j76Ys/5dXxV7li\n7RVT2351/Ff0He9jy6ot8+6g2HVPF/sH93No5BChSIiGQAMr61eytmUt3e/uLunnoE6RIiILo2Ad\nGr1gumwCapGkbLPCX3rpJQ6MjxNxjga/n/aamqm0kVyD20J0NCxW2b3UoCp1trYUQVVyVnkhjk8u\nbkyduX51/FVOqZ62TISXR15mMjZZkA6Km1Zu4o6n76Cmooa6yjqGJ4Y5PHqYD13wobzHX2jqFCki\nUl5y6dAoUpZmK7XXGwzy0NAQceeo8/kIx+PsCoV4ZWKCu48dY+u+fTl1VCxVR8NczJYHvJSla0hT\n6a/k9MbTp+2XLuCe60LDXYd2seE1G2isamQsOkZjVSMbXrOBXYdK/5czLagUESkvWWeuRcpZplnh\nZK50HMCMgBnheJzHQyFOr6qaVl1ktjSRZACfmtbxzlNO4UsvvcTjzzwDwOb6eq4988ycZqcLmSIy\nWx7wUpauIc0XLvoCdzxzB0PhoanUiHQB91wXGiav89pTXju1Le7iZfFep5vJ14JKEZHSUXAtS1J/\nOMx5tbU8MTICQMCMUDRKzDkuqKubqi4C2WtOpwbwvcEg1xw4QH84jM85RuJxfnj8OD8NBvniWWdx\n1emnZzxPag54rsH9bE7moCpdGsZ5p52XNeCe60LDcn6v57ugVERECkvBtSy4Yi7wS0rmSm9qaKBv\nfJxQNEqURC3q01IqjORbc7rn8GGOTk7iB4LxOD4zAsBoPM51L7zAeXV1Ge+l0A1lyjWoKtXivlwC\n7tSW6/ko1/casreWFxGRhZW1Wkg5U7WQxacQFTzmep2dw8O019Tw2pqaqf1Sq4vkYuu+ffxiZISR\nWIwYic6Mzjmi3qLJ312+POO5ClF55IT7zCOQXYigdylXriiXyiwiIlIaBasWIlJIC9UOPF2u9BdW\nr+aOo0cZikZzqjmdboY92f78WDRKwAuS4ySC7FMqKmadBS9E5ZET7jPHKhULVVmknCtXzDc4LmVF\nEBERWTxULUQW1GztwFPbjOdSySObjqYmutvbuXfdOrrb27nq9NMzVheZKVNr9U319SyvrAQSrc9j\n8ThR56i2/7+9ew+O6zzvPP99z+kbGpcGSRAQCYgiTAm0JEsUPSBjSsrKkmPHkTy215GjpLwTxs6W\na3e4Fe8WJ9rspWRLlWxlVJXN2gnHu96JNEzKcWhr7FhjKba1tiXHlhQKulGSJUIXkOIVIEGiG7fu\n033Ou3+gG2oADaAbaKBx+X1cqkYfnD7nJY5MPXz4vM9j2BqNzhko17LzyHJ1FlmpnSvmGl8uIiJS\nTQquZVnNNg48bkzJYHaxAfZCFTLsXhDwdCrFM6kUb42P89ilS3z16qv5tcZGfMC3lrZQiBsaGggZ\nM2egPFfrwKW2XEHvco4CP3r6aNnjztdr20IREVl+Cq5lWc2WvcWYyXKRQiePwsCXapktG10qgO9L\np8n4Pj3Dw6SDgHrHIbCWp4aGAPjZ7t08ddNN/MGWLVzb0MDOeLysQHl6Nn05AmtYvqC3VA/qZCbJ\n/l37y/p8uQFzpZnolZpRFxGRtUcbGmXZlapl/srJk1Xf7DfdfOPSp5/7o0uXsEDEmfgzaCYIcIDf\n3Lix7A2QK8VybjScXtvcvaWbnnM9U2qdgRn1z0DJNd5z3T0zPn/45cMzWuMNpYdoibdw6K5DM9Z0\n4LEDFZ0vIiIyXbkbGhVcy4pQSeBbqUIw/+2BATaHw+yMxyfb8c0WwB9NJrnrlVdodF0ijoNnLdkg\n4IMNDWShagH/cqpFt4tSQf27yXex1nJV81VTguiGcAOu404JgN++9Da9l3rZ17FvyrmpTIrrN1+P\nY977y7fABpwZPsPjn3u8rHWslS4mIiKyPNQtRFaV/W1t3HfiBEBZnTygvH7ZxS35NofDDOdLPbob\nG2mNRGbt1rE3keC2RIKXRkcZ830aQyF21dcTcRw68hsay7EcPb3LVYtuF6W6hzx/9nkwsOuKXZPH\nAJ49/Swf2/GxKZ8/O3KWrJ+d0X3kdOo0qUyq7KEuy9ULWu36RERENdeyIlS62a/c+uni1n874/HJ\n48fHxubt1nHvtm1cXVfHvkSCm5uaiDhORd09KqnxXqtK1Tpn/AyZXGbKscI50+vCL49fZkNsw4xz\nmyJNJWu7u7d0z1qzvbdjL4fuOsTjn3ucQ3cdWrIe3+pIIiKyvim4lhWjks1+xUHzXBsgi1v/tUYi\ndDc20ui6XMhm5w3gF9vdo9w1rmbzbUAstZEy6kaJhqJTjqUyKfZs3TMjYA67YbY2bZ1x7u4tu3ng\nww/QEm/hzPAZWuIt3HPdPRz51ZGaBbfqSCIiIqCyEFml+tJp2ovGmEPpUebTB7e0RiJEHKfsWu69\nicSCyzjKXeNqVc5gmlJjwzfXb8Zay1B6aEb9M0zd6Hj/bfdz5FdHZpxbKOkozj4feOxATQfY9A31\n0d7YPuWYOpKIiKw/Cq6lJhZbi1zutMOF1HJXy1JMZFyIpaoDLmca42y1zoXzStU/T1/b9a3Xl1Ur\nXevgtrO5c0ZHkqXq8S0iIiuXgmtZdsWbDItrkSspuSg3aC41Bv1gR8eybCqsZWBfsJRjz8sJZucK\n7Mu9f7kbMWsd3JbK0hey7CIisn6o5lqWXTVqkSuph16OwS2lao9rOZGxYCnrgOcbTLPcG/wWO8Bm\nsQpZ+uI6cLX6ExFZf5S5lmW3EmqRq9kib77scK1a78HSlkrMl6ktp2ykmuZqt7dcLfJq0e5QRERW\nFmWuZdl1xmKkfH/KsUprkRfT5q7aLfJWcpeIpRx7Pl+mthYjx0u121OLPBERWU7KXMuyq0YtcnFp\nCTD5eri/f95M8WI+W8p82eFaDhZZ6jrguTK1ta6BLljuDLqIiKxvylzLsqtGLXJx/+qCQmnJ0WSS\nA7293HnsGAd6e2dkpOf67ELMlR2udda0lnXAta6BLqhFBl1ERNYvZa6lJhbTPxpmb3MXd5x5O5FU\nu0XeXNnhlZA1Xco64Pm6gSzHyPH5rJQMuoiIrA/KXMuSmy+TvBD729pI5nIM5XIE1k6OMsfaeTuR\nzPbZcseaTzdXdriSrOl80w5XmnKy8ks9crwcKyWDLiIi64Ox1tZ6DQvW3d1te3p6ar0MmUNxT+vi\n+upqtKQr1fHjKydP0h6J4BgzeV5gLWc8j8dvvHHOzxbWU80a6QOPHZiRNR1KD9ESb+HQXYfeW09R\nx5HpUwtXal1wub+2laCWde8iIrI2GGOet9Z2z3eeykJkSVV78+B8yi35mK0spdyhK+UGa+VuKFwJ\n5SOVqvVExEqoRZ6IiCwXBdeypKrd07qQcX5xeJjTnkdXLEZnXd1kbfWehgb+y+Ag2SBgQyjE1kiE\nkOOU3YmknCD36Omj/NE//REXxy+SyWXoHezl+bPP87Xf+tqMAK7cuuPl7jhSjeuplllERGQm1VzL\nkpqtp3XccSquwy7uTz2Uy2Gt5fj4+GSmOhcEHB4YoKuujg2hEJdzOXrTae7ZvLnsLHk5NdIP/vJB\nTiRPENiA+kg9gQ04kTzBg798sOQ1y6k7Xs6OI9W6nmqZRUREZlJwLUuq1ObBd9NpTqfTFQ9xKS4x\nGQkCGlyXsOPQOz4OwFnPIxsE7Kir49ebm/lkSwv7mproGRkpe73lDF157uxzxMNxoqEoxhiioSjx\ncJznzj5XwU9mqrkC1WoPqanW9TTuW0REZCYF17KkCj2t/SDgx5cv82wqxYDn0eC6c3b0KKW4P3Wj\n6+JZS8QYhnM5AC7ncmwITa10qrQEpexs7PR9wIvcF1ytjiPlqOb1VkI3EBERkZVENdeyLEaCgA81\nNdHkuvxgcJA3xsdpDIVozddjlxMEF29W7Kqro2d4GI+JQHsolyPsOGyNRqd8ptL+1eXUSO/Zuodf\nnPoFxhgibgTP9xjLjXHrlbeW/wOZ5d6zlYxUs7ZZtdIiIiJLR5lrWXLF5RyOMWwMhzEwWc4B5QXB\nxSUmLeEwO+NxTD7z3RIOc/9VVxEyZtH9q+fLxt57y710NndiMIx4IxgMnc2d3HvLvRXdp1zVrm1W\nrbSIiMjSUZ9rWXJ3Hjs2pff0gOfxXCqFD3xi06ZZe1+X6kUNzNqferbPLEXLv+Xumzzb/Ra6DvV9\nFhERqUy5fa6XLLg2xjwEfAIYsNZ+IH9sI3AE2A6cAH7HWnvZGGOArwJ3AmPAH1hrX5jvHgquV4cD\nvb0zek+/PT7Oec9jWyxWMnCOG8OZ/PerPXwG1kZwuRoHz4iIiKxW5QbXS1kW8p+Aj0879ifAT6y1\n1wA/yb8H+C3gmvw/XwS+voTrkmVWqmNIyBge2rmTx2+8kUNdXQCTbfbaIxFeGh2lL53GC4KKNj2W\no9qt7Wql2l1EREREZPGWLLi21v4cuDTt8KeAwn/5DwOfLjr+t3bCs0CzMWbLUq1NllehY0hLOMwZ\nz6MlHJ6RgS7UZXtBwNOpFGcyGcZ8n5dHRyfPWczwmWIrPSg9evooBx47wJ3fvJMDjx2YNeivdhcR\nERERWbzl7hbSZq09B2CtPWeMac0fbwdOFZ13On/s3PQLGGO+yER2m23bti3taqVqZhs3XtCXThMB\nnh8ZIeI4xByHbBBwLpNhwPNojUQq7vwx671W8Njucsevw0TXj+ODxzk3fI5hb5jGSCNbGrewc9PO\nGq1eREREVkq3EFPiWMlicGvtN6y13dba7s2bNy/xsqRcR5PJiicuFuuMxXh1bIyI4xBxHJpCIQLA\nNYbjY2ML7vxR8l5lDIqplUqy6t1bunnp/EukMimMNZxMnuTnJ3/O6xden7fEpdzsuIiIiFRmuYPr\n/kK5R/51IH/8NHBl0XkdwNllXpssUPFY8komLhYr1GVba7HW4hpDg+OwORzmQjZbspRkoUq1ojs5\ndJL+kf6aB5vTSz0GRgZ4ZeAVvv2rb89YV8+5Hm5qu4mQE6J/rB/HOLTUtfBu8t05a8jLrTlXAC4i\nIlK55Q6uHwUKzXT3A98vOv77ZsKHgGShfERWvul9rBey+XBvIsFtiQSOMYz5PnWOwy3NzextauJ3\nWls51NVVtZZ606ch+oGPMQbXcWu+wbE4qz4wMkDPuR6GM8Nsrts8Y119Q310bugkHo6ztXEr7U3t\nJGIJvMCbs4a8nOz4Wtn0KSIistyWLLg2xnwLeAbYaYw5bYz5Q+DPgY8aY94EPpp/D/A48A7wFvD/\nAv92qdYl1Vc8lrxgIZsP7922javr6tiXSHBzUxMRx6laKch0xYNi2hra2JbYtiI2OBZn1Y9fOj5x\n0MDOlp0z1lUIxIe9YSLuxKRLz/dojDTOWUNezkbIhW76VLZbRETWu6XsFvJ71tot1tqwtbbDWvs3\n1tpBa+1HrLXX5F8v5c+11toD1tod1tobrLVqXr2KdMZipHx/yrGFbD4sp6vIUlhJXTeKs+oXxi7Q\nGGmke0s3rfWtM9ZVCMQLI9i9nMeIN8J4bpwf9P6Ad5Pvlgxuy6k5X8jPRNluERGRlbOhUVaxUn2s\nCxnnSjc67k0kONTVNdn/eqkDa1h5GxwLWfXfue53uKHthsnAevq6CoH4TW03MewNk/EzWGvJ+llc\nx+WK+itKBrfljD9fyM9kpbc4FBERWQ4KrmXRZss4AxVtdFxsx5GFmi/YrFWpQzlB8N6OvTxyzyM8\n9nuP0RxrxnVcmqJN7Nmyhx0bd5QMbqfXnLfEW2a0+ivn3tOtpL8BEBERqZUlG3++HDT+fG5Hk8nJ\nceKFEePLkQkuKDX2fCiXoyUcnpzKWLzW+06cIBEKLcm48/nMNg691iPGKxnTfuc376S9sR3HvPdn\n5sAGnBk+w+Ofe3xJ7w1w4LEDXBy7SHOsefLYUHqIlngLh+46VPH9RUREVpJyx58v9xAZWSbFwWpx\n1ni5glWY2OjYHolMOTbbRsfijiPA5Ovh/v5lWe/ejr0lA8fiUgdg8vXwy4eXJbiebV2ldDZ3zghu\nF1PeUsm9YSLbfd+T9wFM+YPIwX0HF3R/ERGR1UhlIWtUNdrjLVYlGx2r1XFksaaXgLx47sVVU+qw\nkFKOaiqn3ERERGStU+Z6jZova1xJychCz407DqfTaairm1LqcbCjY8bnOmOxGSUk1Rp3Xq5So8dP\nD58mHo6zY+OO99a1QqY5TlcIbotLOQ7uO7iswW2l2W4REZG1RsH1GjVXsFpJycjRZJIvvfUWF7JZ\nMkFA79gYLwwP89Wrry55bvF1U/7EcBY/CDiTv/fBjo6Sgfn+tjbuO3ECYN5AfKmUKgHp2tRF72Av\nm+KbVkWpg4JbERGR2lJwvUbNFaxWUt/84KlT9KXT1LsuDa6LZy196TQPnjrFI9POLXndWKzkBsbp\nCh1HijPkswXiS6VvqI/2xvYpxzqbOxnLjtESb5kzG1zY/PfiuRdJeSmaok3svmL3vJsAp5tvE2Gl\nmwxFRERkealbyBo2WznHnceO0R6J4BgzeW5gLWc8j8dvvHHK5z/y8sv41hJ1XZpcl7jrkvF9fODk\nvn1T7lfudVeqhXa7KJST5Pwcbwy+gcFgsby/5f2MeqO0N7YzlhubNxierzNJrTuXiIiIrGfqFiLs\nTSRKZn7LqW8ulHgE1uICvrUMZrMAuNMvWMF157KUWdm5Wu0VjsdDcc4MnwEq63ZRKCd5deBVIm6E\naCiKl/N45/I7jGXHuDB2gdu33z45sXC2YHi+ziS17lwiIiIi81O3kHVoromKBYUSj7ZIBD+fiTbA\n5VyOsSBgT0PDgq47m6UcnT3btR9+4eEpx13HxVqLH/gVdbsoDE8Z9oaJuBObSCNuhAujF4iH4ni+\nV9bEwvmGsGhIi4iIyMqnzPU6VE59c6HbyK6GBkaTSdLW4luLBbZHo9y7bVvZ14WJgTJzdRtZqqzs\n0dNH+cKjX2BwbJCNdRvp2tQ1OU78T//5TzHG4PkejZFGujZ2cVXzVRUPPSn0l26MNDKeG5/IXPve\nxDcNNIYbJ8+dKxier091tftYi4iISPUpuF6nZisZKSiUeLRGItycSNA7Ps6lbJZN4TBfu+aaWT87\n/brldiYptZmw0qzs9NKP7i3dHPnVEQbHBklEE6RzaXrO9dC9pRtrLadSp9gc38xodpSLYxc5mTzJ\nB6/4IMPecNn3hPeGp2xp2MIbg2+Q9bNYLIlYgrHsGLtad02eO1cwPN8QFg1pERERWflUFiIlFZd4\ntITDfKC+nl0NDTy0c2dFHTymD7PxMpd5a+BlPvvPf8OBxw5Mln10NneSyqSmfLaSrGyp0o8vP/Vl\nckGOjXUb8QKPSChCxInQO9g7WR99OX2ZwAaT5Rw953qIh+Jl//rgvf7SO1t2sq1pG4lYgm2JbXyo\n/UNsT2wnEoqUNdRlviEsGtIiIiKy8qlbiEya3l2ku6GBnpGRsobHzKa4g8jA6AV6zj5H2I2QDTVz\n89Cjk90ugEV1wijV6ePR44+yIbaBnZt20nOuh7AbJuJESGaS5GyOkAmRzCQJOSFc45ILcni+x7/u\n+tc8cs8jlf3wZqHWeSIiImuDuoVIRUqVbxy5cKHkYJlKFHcQ6R08TsSNYN0GmuzolLrqQ3cdWtR0\nwVJlJRvqNnB5/DKtDa10b+mm91Ivl8YvsSm+ifdvej+/PPVLWutbSWaSZP0sjnHY2riVsdzYgn+9\n02moi4iIyPqi4FqAWQbAUHqwTCWKh9mkvGHC4WayTphdmTeAqXXViwlES23229qwlRFvZKJXdX0L\nkVBkSqb87u/cjR/4tNW34fkeWT/Ljg07tEFQREREFkw116vE0WSSA7293HnsGAd6ezmaTFb1+n3p\nNE3u1A7WTa5LXzq9qOsWOoi0hMM40Tac3AjdmVdoDS4B1et2sX/XfpKZJEPpocn65pAb4je2/wZP\nvPMEh18+zBPvPMGeLXsmg/j7b7sfYwzJdJJYKMbOTTsJuaFZa6JFRERE5qPgehUolGxczGandNwo\nFWAvNAjvjMVI+f6UY5UMgJnT8HF486u0n/grvOMPMjz4XFkb/CpRarPfni17ePTNR6kP1/O+5vdR\nH67n689/nYdfeBiAz3/w8zzy2Uf4zLWfYXvzdna27NQGQREREVkUbWhcBQ709s6YfFjo4nGoq2vy\nWHHddJPrkvJ9To6P0xGLMRYEc25KLPXZZC636Jrr6SO7+y730Xupl46mDnZfsXtJN/h94D98gGQ6\nSUP0vYE3I5kRErEEr/7bV5fkniIiIrI2lbuhUZnrVaDcko0Zbe+CgBOZDC+NjMyb8S4u3zjjebSE\nw4sOrGHqcBjHOOzYuIN9HfvYfcVuDt11aEmzxP2j/dSH66ccqw/X0z/av2T3FBERkfVNGxpXgeKO\nGwWlSjYKUxULesfHiTsOnrU4xkzZpFh4nd5mb7HB9HTzDYdZylZ1bfVtMzLXo9lR2urnH8cuIiIi\nshDKXK8CxQNdAmsZyuVI5nLsb5saJE6vmx7O5QBoLMp6N7kuLw4Pl13DvVhzDYcpNfjlvifvmxws\nM5ejp49y4LED3PnNO6cMozl6+ih3H7mbq/7yKs4Nn+P8yHkGRwexgWUkM8KwN8zmus0zPiciIiJS\nDQquV4FySzamB+ERx2EsCOiqq5s8J+X7pHx/SvlIcyhEIhSazGhXU6kuHoVNjNNLRppjzSSiCQ6/\nfHjOa84WlD/8wsN86Ydf4henfoFrXBKxBPFwnJSX4vzoeSJuhI7GDlobWisO5kVERETKoQ2Na8zD\nZ8/yF6dP0+95NLou9a7LdfX1UzYppnI5rq+vxzFm8nOBtZzxPB6/8cbJY8UlG/GNH4S2jzMWaqp4\nWuNspR93fvNO2hvbccx7f8YLbMBrF15j9xW7Zy0VKZ7GODAyMDkcJuNnqHPriIVjREIT5TGZXAbH\nOPzmjt8EmNELeyg9REu8hUN3HVrYD1xERETWBU1oXIeOJpMcuXCB6+vr2dfUNNktxM8Hzp2xGAc7\nOjjc3z9vDXdxl49w4gZ+4XTBuWN86IobuOi63HfiRNkbHmcbDlNq8EvfUB+nU6e5sunKKdnl4hZ5\nhTrugZGBybHmiWiCvmQfY9kx2tw2IkwE1xE3wqg3OlnjPVf9t4iIiMhiqSxkDXnw1CneGh/nmVSK\np1MpvCDgqro62iIRHr/xRg51dbE3kSirhru4ZOOtyA7ixlLvWN681Fu1MpJSJSO9g710beyas1Sk\nUMfde6mXsBsmGoqSDbLUh+sJOSGG0kOT53q+RzQUpbO5c876bxEREZFqUHC9RhxNJnlqaIjAWuod\nh3QQ0DM8TMb3eXF4eMpgGWDeGu6+oT6aok0ADJsGImSJuBGGvWGgStMbSwx+6WjsoHPD1GB3ena5\nEJRfGr9ExIng5Ty8wOPG1huJh+Kkc2ky2QyZXIax7BgtdS3s37V/zvpvERERkWpQWcga8eC77+JZ\ny/lslqjj0OS6RByHnuFhHMfhymmdQR7Yvn3KAJrpiks2Gu0I40Qx/giNkUagetMbp5eMFNdTF0zP\nLheC8i88+gUGxwbZWLeRGzfdSGt9KyE3RN/lPnJBDizceuWt3HvLvZP3eODDD0yp/z6476AmMoqI\niEjVKLheA44mkzyVTNLgOAzlcmSDgItBQMJxuOz73NLUNFlfXdzreq566f279nPfk/cBsCnTQ0/0\nBnwvxaZIjO+d+BeG3QRNZOkfGeDeHTcsuD/29M2O3Vu6OfKrI8BExjqVSZHMJDm47+CUz+3t2MtD\nn3xoyvTHofQQISfEt377W7MGzLPVf4uIiIhUg8pC1oDCZMaY69IaiRB2HKy1jFpLk+vSWdSKD8or\n6Shkh/3A5/W+77Hh3PfZFApzgQYGqaM+N0R9tp9fnDvGl46/vKAe2aVa6h351RHuue6eKaUixZsZ\nS62xnHNFREREloMy12tAXzrNB+Jxnh8ZIeI4XBEOk3Fdhn2fX29uJuX78053LGVvx17aGtq4Y/sd\nNMea+cW7hxlt+2383BC+zRJtuAJDhgvJExzuvwKGj1c0bbF40yQw+dpzrqfs1njKRIuIiMhKosz1\nGtAZixF1XbobG4k5DqNBgGMMtzU3c++VV5Y13XE2UzY2esP40VZcmyGdS3N+5Dz9I/2cT77Nj04f\n4+7v3M13X/8uJ4ZOcPzi8XkHtBRfu0Ct8URERGQ1q0lwbYw5YYx5xRjzkjGmJ39sozHmCWPMm/nX\nDbVY22rU3dDAM6kUz6ZSWGvpqqvj6ro67r3yyrKnO86muH1dY6QRNzNA2rpk/DTDXgrP98iaCH3n\nnyHjZ0jEEqRzaY4PHifn5+actliL1nizjU0XERERqYZaZq5vt9beVDTp5k+An1hrrwF+kn+/ph1N\nJqe0yFtQ3XJ+cExXLMaGUIjLuRy94+Pcs3nzZAC9N5HgUFfXlF7X5SpuX3fNxmuw53+IZ8LgNmJw\n8N06siaK6f8RXs7DGEM0FCXshjk7cnbOLPRyt8abbWy6AmwRERGplpVUFvIpoJDmPAx8uoZrGIp3\nNQAAGNpJREFUWXJHk0nuO3GCi9Na5FUaYBc2M+6Ix/n15mY+2dLCvqYmekZGqrLO4k2DXuCx2R/E\nPfl3uP4wRDcTJ0v41N/hDPeS8TOTn4u4ES6PX54zCz19Q6If+DSEG/jKU19ZkqxycY33bANqRERE\nRBajVhsaLfBjY4wF/h9r7TeANmvtOQBr7TljTGuN1rYkjiaTHO7vpy+dpjMWoz+TIREKVdwib7q+\ndJr2SGTKsXK6gUxvgTfX5sPiTYN3fvNOokMnSA98l2goCsD58fOMAo5x8HLe5MjxsBuekYUudd9D\ndx2aMm59trHni1UYm15MNd4iIiJSTbXKXN9irf0g8FvAAWPMf1XuB40xXzTG9Bhjei5cuLB0K6yi\nUlnqp5JJ0r4/5byFTD3sjMVITbvOfN1AFlIeUahVfm3gNVKZFCOZETK5DNZawk4Yx3G4ruU6om6U\nofQQxhjuv+3+KYHxXPddjqyyxp+LiIjIUqtJcG2tPZt/HQC+B+wF+o0xWwDyrwOzfPYb1tpua233\n5s2bl2vJi1Io3WgOhXCMoTkUIhEK8drY2JTz+tJp3k2nK6rB3t/WVnE3kEoD2eKgePcVu8kFOXzr\nE9iAZDpJLBzjj/f9MXva97B9w3Y+c+1neOSzj/D5D36+7PsuR+cQjT8XERGRpbbsZSHGmHrAsdYO\n57/+GPAA8CiwH/jz/Ov3l3ttS6VU6cYH4nF+mUoxlMtNZqxfGhnhpvr6GWPK5yoTKXQDKS45OdjR\nMednKi2PmN6Pel/HPl7pf4VskOUz135m3n7W5dy3eNx6QbWzyoUab40/FxERkaVSi5rrNuB7xpjC\n/f/eWvtDY8xzwLeNMX8IvAt8tgZrWxKdsRgXs9kpg1yirsttzc20hMP0pdOc9zxuqq9nRzwOVFaD\nvTeRqKhOu9JAdnpQ3Frfyu2dt3Nm+EzZw17mu2/xuPW5xp4vlobOiIiIyFJa9uDaWvsOsKvE8UHg\nI8u9nuWwv62N+06cACbqqlO+TzKXm5KVvvPYsVk3Jk7fDNnd0EDPyMjk+/1tbexNJGacVzg+Yz0V\nBrLVyirPdV9llUVERGQtMNbaWq9hwbq7u21PT0+tl1GWuQLfo8kkXzh+nMFslo3hMF11dbRGIgzl\ncgxkMrydyZANAjaEQjS4Lu+k09xUX09nXd1koH7P5s0cuXCBRCg0awA/ZT0VdAsp7uRRHBQvpJNH\nJfcVERERWSmMMc8XzWeZ/TwF17VV6CSSs5Y3RkcxxpD2faKuy4jv41lLo+tS5zhczuUY9X3CxrAl\nEuGjGzcC8HZqgBdSg0Qz59gYjtC1aSet9ZsZyuVoCYc51NW1uDWePsqDv3yQ584+B8CerXu495Z7\nFRSLiIjIulFucF2rPteSV9xJpNF1eWlkhJTvEwM2hkKc8zySuRwpIOxMNHfJWctZz2PA8yCb5I3+\nHkbrdtIaCpHOpek5+xzdW/fQEm+ZbO230Ixxcdb6Yzs+Npm1FhEREZGZFFwvsfnKQX4wOMi475MD\nDDCa71kdWMtYEFDnOIz4PsYYYsbgGkPOWqJYnhp4h+zlF7BuPdHIGB4Roq4BoHfwOJHoBuK5FHcf\nuZunTj5FIpbg+s3XVzSgZXqnkMLr4ZcPK3MtIiIiMo2C6yorDqbjxnDG89gWi01pr3fP5s08dukS\nTw0NMR4EpIMAgMIoGMPEgxn1fUJADsBaRnM5ACyW0cwlxq3FWBfXiVJ37hFG2z4OTpiIa7mU9Xh3\ndBDb9xAXz79EY6SRwAa8cO4Furd0T/aXni9A1lRDERERkfIpuK6iQv10IhSiPRLhZ0NDjPg+V0Qi\nOPnSj0HP48snTxIxhkbXZSSXw592HQtkggAHGM0fM7wXfDN+Fte4GCeMyQ3D2f9Mfe4iNjPA0Kbb\nGA01Ue8PEzv1D7Q645wNPOrD9RMXAXov9XLzlTeXFSAvR/9pERERkbVCwXUVFddPA3hBQNxx6B0f\npzXfZu+s55ENAnAc6h1nshxk+rbSyUDaTmS1LWCNM/E+vAknfYrIiW/gJ18l62cZwBCMnic88DRh\nJ8SOTdfyauoEN3fcTGOkkXQuTSQUIeJGGPaGyw6Ql6v/tIiIiMhaUJPx52tVXzpNk+tOvm/MB9nD\nvs+A5/GLZJK302nSQUAI8KwlYGZgXeBbfzK4BvPe126UrBMnCHyibhTXccnZHIENiIVi1IXqeH3w\ndVLpFE+efJKWeAte4OHlPDzfI+JGyh77Xeg/3RJv4czwGVriLQtqwSciIiKyHihzXUXTJzG2hEI8\nNz5OYC1PZLPUuy5hY4g4DqNBQDYIZg2syddhYwp//rE4BASF1onhBF7LHfhvv4YXeAA4OGT8DKPZ\nUUImRMSNkM6mOT54nK6NXZwdPkvKS3HbttsqaqWnqYYiIiIi5VFwXUXFkxgzvs/x8XFijkPOWjxr\nGfV9uurquJDN4lnLiO/PHlxjido0GROffD9RQGIgyIATxo+2YoPc5CcCArK5LMYxZIMsFkt7UzsO\nDieTJ/lE1yc0tEVERERkCSm4rqK9iQQPbN/O4f5+fpBK0eC63NDUxPPDw8Rdl6y1ZKzlfbEYT6dS\ns9ZbF1hrwVowE0G1tZYQAdYJ4fserjdAY6yJUW8U3/oENiAgIEQIi8W3Prvadk2WdBy669Dy/TBE\nRERE1iEF11W2N5FgbyJB37FjtEciOMbQGAoxHgREjeFiNksql8My8cO3MKNbCACOi2fi+TprBzBY\nA8aEATDj52hNvUCi/gr6sn341ifqRPECDz/wcYxDQ7iB1vpWhtJD6u4hIiIisgy0oXGJdMZipPID\nYbrq6sgGwcQ480ItNRBmsjveFG7+uGMcHFPYyBhgjIsFbk0kuC39L8TT7zKaHSUejrMxtpFIKDKx\noTFcx4bYBrY0bGEoPVT25kURERERWRxlrpdIcf11SzjMzro6evOjyBtdFz8UYigIMIXSjzyHfJcQ\nDBaDY1zirkNzKISxlm2xGD/bvZujm/+A+8bfIRFNkMllePbMs8SdOL/W/muMeqP0Xuqlua6ZlngL\nB/cdVJ21iIiIyDJQcL0EClMaU7kcpzMZmlyX3Y2N/B/vex+H+/u5mM3iBQFPJ5OM+D7Zos8GgZ+v\nsQaw2CBHUyhMUyjESC7Hec/jQG8vfekYDdf97/j9P8S79AK3Xnkrg2ODvHT+JQD2bt1bUUcQERER\nEVk8Y+3s/SpWuu7ubtvT01PrZQDw8JvP8Bd9r3E6iJGLbOC6eAO7mttI+T7JXI4Htm9nbyIxZYpj\nxvd5dWyM8+k0GSBn85lsAqyZKA4JB+PEybKxvo3hbJYs8JsbN9LkulOuzfBx7nvyPhLRxJRhL+pJ\nLSIiIrJ4xpjnrbXd852nzHUVPPzmM/zxW7+izlhMuIEgCDg2MkTcMexMtAET0xv3JhIwfJyGs4/y\nrL8RYlvYs/FK7r12Nw+++y7/pf8dAqeOiYExObABFsNILksudQrrxtkQrZ/so114PdzfD28eJhFN\nTI4pL7wefvnwjOD66OmjHH75MH1DfXQ2d6o9n4iIiEiVKLiugr/oe406Y2lwDJcJEzE5chaODV+G\n7BAvDxxj1MT5p8f/GoPBOIZ0Zpi0n+b/swbe9xuc7fwjdtiLZDJpIm6UMRNlwDSTCXI0jLxGS+NV\nnKEBL3WcgXiI1vrNADS5Ln3pNAz10d7YPmVdTdEm+ob6phw7evroZIa7vbGdi2MXue/J+5ThFhER\nEakCdQupgn7fUJ//SYbJEuAQMhNjz5898ywZG6I+l+LsyFneSb7D4OggI94IfuDj+R7PnHqG0/3P\n0VDXhud7eH6GuE1jx97FyQ5TV7+NOjza/QtEHYfeweOT9075Pp2xGJ3NnaQyqSnrSmVSM1rwHX75\nvQy3YxyaY80kogkOv3x4yX9OIiIiImudgusqaHMto/kOe03BMIFx8KyDnxvBuvVknQjjZ7+P53sY\nDKlsCtdxCbthQk6IpJekK9fH+fQIO9u6iYZiDOVyGHxuHv8ln84+y62Z59mVfR3r1nMp6xFYy1Au\nRzKXY39bG/t37SeZSTKUHiKwwawt+PqG+miKNk05VirDLSIiIiKVU3BdBQc7r2fcOowEFrzLeMNv\nM54bw2ZTeOmLOCcOExubCF4tlsAGOMaZfA/Q6WbouPRjdiba2N62h89c/RHuCg+wxQ5N3qc1uMT7\nR55mUyjMGc+jJRye3Ci5t2MvD3z4gclpjC3xlpKlHuVmuEVERESkcqq5rlCpzYCfv2YfAH/a+xzv\nells+hybzn6HwYFfAOABvnFxjJPvYQ3JTHLymlsatpDKpNhd38Khrq737hX/JPc9eR/AZAeQUCbJ\nQ3t+n70dN85Y296OvfPWTe/ftX/GNZOZJAf3HVz4D0VEREREAGWuK1LYDHhx7OKUzYBHTx/l89fs\n4+Mc56pTX2fbwHdpzJzGFM1f9K0/GVhPd27kHE+eeJLuLVO7u5Sbja7EUlxTRERERCYoc12B4s2A\nMLPd3YvnX+R06jR+MHsgXYrBEHbDHPnVEa5vvX5KoFtONrpSS3FNEREREVHmuiJzbQZ8+IWHeen8\nS2T8DDmbw+b/Vw6LxTGOunaIiIiIrHIKrisw22bAeCjOl5/6ctnBdCkj3ghPn3qaH/T+gKOnjy52\nqSIiIiJSAwquK1Dc7u78yHl+0vcTftr3U148/yKj3uiirh0PxQk7YcJOeLKOW0RERERWFwXXFShs\nBvQDn6dPPw0WbrnyFsayY4xmR8nkMgu6bn24nmFvmHMj5wgIyAU5lYeIiIiIrELa0FihvR17aWto\n447td0xuaDQYPN9bUFlIPBQnF+RwXZe2hjYMhjcuvsFYdqzaSxcRERGRJabM9QIUb2wcGBngUvrS\nlLZ78zEYHBy21m/FGEMilmBr01bqwnVEQpGJKY7TartFREREZOVTcL0AxRsbey/14hiHiBsh7IRx\nyviRFkafX73panJ+jotjFzmTOsOYN0Yml8FiaYo0zXsdEREREVlZFFwvQPHGxlQmRcgJYYyhvbGd\nbYltNEQacHCoC9WxtWEriUiC9sZ2ok6UulAdUTfKtZuu5Z3L7xAJRQjlq3P6R/ux1vL+Te9n95bd\nNf5VioiIiEilFFwvQPGUQ8c4NIYbaYw0YowhGorSHG2mvamdJ/c/yZmDZ/jxv/kxn9r5Kdoa2tja\nuJWPdn4UL/AIu2EaI42EQ2E2xzeztXErruMSckPs37W/1r9MEREREamQsXbhvZlrrbu72/b09NR0\nDYWR6Dk/x9mRs1wev0zYDXP/bffz+Q9+vuS5iWiCp089TdgJk7VZdjTv4MLYBVKZFI5x+M5nv6MJ\niiIiIiIriDHmeWtt93znrbhuIcaYjwNfBVzgP1pr/7zGS5pTIYt9+OXDREIRbt9+O/t37S8ZHBef\n6xgHxzh0X9FNa30rO9nJUHqIlniLAmsRERGRVWpFZa6NMS7QC3wUOA08B/yetfZXpc5fCZnrhSrO\nYjdFm0hlUiQzSR748AMKrkVERERWmHIz1yut5nov8Ja19h1rrQf8A/CpGq9pSRTXbZ8ZPkNLvEWB\ntYiIiMgqt9LKQtqBU0XvTwO/VnyCMeaLwBcBtm3btnwrWwJ7O/YqmBYRERFZQ1Za5rrUJJYpdSvW\n2m9Ya7uttd2bN29epmWJiIiIiMxvpQXXp4Eri953AGdrtBYRERERkYqstOD6OeAaY0ynMSYC/C7w\naI3XJCIiIiJSlhVVc22tzRlj/gfgR0y04nvIWvtajZclIiIiIlKWFRVcA1hrHwcer/U6REREREQq\ntdLKQkREREREVi0F1yIiIiIiVaLgWkRERESkShRci4iIiIhUiYJrEREREZEqMdba+c9aoYwxF4CT\nVbhUC3CxCteRlU/Pev3Qs14/9KzXDz3r9WMlPuurrLXzjgdf1cF1tRhjeqy13bVehyw9Pev1Q896\n/dCzXj/0rNeP1fysVRYiIiIiIlIlCq5FRERERKpEwfWEb9R6AbJs9KzXDz3r9UPPev3Qs14/Vu2z\nVs21iIiIiEiVKHMtIiIiIlIl6z64NsZ83Bhz3BjzljHmT2q9HlkcY8xDxpgBY8yrRcc2GmOeMMa8\nmX/dkD9ujDFfyz/7Y8aYD9Zu5VIpY8yVxpifGWNeN8a8Zoz5Uv64nvcaY4yJGWOOGmNezj/r+/PH\nO40x/5J/1keMMZH88Wj+/Vv572+v5fqlMsYY1xjzojHmB/n3es5rlDHmhDHmFWPMS8aYnvyxVf97\n+LoOro0xLnAI+C3gOuD3jDHX1XZVskj/Cfj4tGN/AvzEWnsN8JP8e5h47tfk//ki8PVlWqNURw44\naK29FvgQcCD//18977UnA9xhrd0F3AR83BjzIeDfA3+Zf9aXgT/Mn/+HwGVr7dXAX+bPk9XjS8Dr\nRe/1nNe22621NxW13Vv1v4ev6+Aa2Au8Za19x1rrAf8AfKrGa5JFsNb+HLg07fCngMP5rw8Dny46\n/rd2wrNAszFmy/KsVBbLWnvOWvtC/uthJv5j3I6e95qTf2Yj+bfh/D8WuAN4JH98+rMu/DvwCPAR\nY4xZpuXKIhhjOoC7gP+Yf2/Qc15vVv3v4es9uG4HThW9P50/JmtLm7X2HEwEZEBr/rie/xqR/+vg\n3cC/oOe9JuVLBV4CBoAngLeBIWttLn9K8fOcfNb57yeBTcu7Ylmg/wu4Fwjy7zeh57yWWeDHxpjn\njTFfzB9b9b+Hh2q9gBor9SdctU9ZP/T81wBjTAPwn4H/0VqbmiNxpee9illrfeAmY0wz8D3g2lKn\n5V/1rFchY8wngAFr7fPGmA8XDpc4Vc957bjFWnvWGNMKPGGMeWOOc1fN817vmevTwJVF7zuAszVa\niyyd/sJfHeVfB/LH9fxXOWNMmInA+pvW2u/mD+t5r2HW2iHgSSbq7JuNMYUkUfHznHzW+e8nmFku\nJivPLcAnjTEnmCjTvIOJTLae8xplrT2bfx1g4g/Ne1kDv4ev9+D6OeCa/E7kCPC7wKM1XpNU36PA\n/vzX+4HvFx3//fwO5A8BycJfRcnKl6+t/BvgdWvt/1n0LT3vNcYYszmfscYYUwf8BhM19j8D7s6f\nNv1ZF/4duBv4qdVQhxXPWvu/WGs7rLXbmfjv8U+ttZ9Dz3lNMsbUG2MaC18DHwNeZQ38Hr7uh8gY\nY+5k4k/GLvCQtfbParwkWQRjzLeADwMtQD/wZeAfgW8D24B3gc9aay/lg7O/ZqK7yBjweWttTy3W\nLZUzxtwK/DPwCu/VZ/6vTNRd63mvIcaYG5nY2OQykRT6trX2AWPM+5jIcG4EXgT+G2ttxhgTA/6O\niTr8S8DvWmvfqc3qZSHyZSH/zlr7CT3ntSn/XL+XfxsC/t5a+2fGmE2s8t/D131wLSIiIiJSLeu9\nLEREREREpGoUXIuIiIiIVImCaxERERGRKlFwLSIiIiJSJQquRURERESqRMG1iEgNGWPajDF/b4x5\nJz8C+BljzH+9wGttN8a8WsH5J4wxLUXvP2yM+cFC7i0iIhMUXIuI1Ei+b+s/Aj+31r7PWvuvmBie\n0VHblYmIyEIpuBYRqZ07AM9a+38XDlhrT1pr/wrAGBMzxjxsjHnFGPOiMeb2/PHtxph/Nsa8kP/n\n5ukXNsZcb4w5aox5yRhzzBhzTSULM8ZsNMb8Y/6zz+YHuWCM+Yox5rAx5sf5zPdnjDEP5tf4w/xI\neowx/8oY81Q+G/+jwjhjEZG1LlTrBYiIrGPXAy/M8f0DANbaG4wx7wd+bIzpAgaAj1pr0/mg+VtA\n97TP/nfAV6213zTGRJiYbljKz4wxfv7rBuCN/Nf3Ay9aaz9tjLkD+Fvgpvz3dgC3A9cBzwC/ba29\n1xjzPeAuY8xjwF8Bn7LWXjDG3AP8GfCFeX8iIiKrnIJrEZEVwhhzCLiViWz2nvzXfwVgrX3DGHMS\n6AJOAn9tjLkJ8PPHpnsG+N+MMR3Ad621b85y29uttRfz9/8w8O/yx28Ffjt/758aYzYZYxL57/2T\ntTZrjHmFiaD9h/njrwDbgZ3AB4AnJipfcIFzFf44RERWJQXXIiK18xr5ABbAWnsgv8GwJ3/IzPK5\n/wnoB3YxUd6Xnn6CtfbvjTH/AtwF/MgY899aa39awdpK3dvmXzP5ewTGmKy1tnA8YOK/KwZ4zVq7\nr4L7iYisCaq5FhGpnZ8CMWPMf190LF709c+BzwHky0G2AceBBHDOWhsA/4YSJR/GmPcB71hrvwY8\nCtxY4dqK7/1h4KK1NlXmZ48Dm40x+/KfDxtjrq/w/iIiq5KCaxGRGslnfD8N3GaM6TPGHAUOA/9z\n/pT/ALj58osjwB9YazP54/uNMc8yURIyWuLy9wCvGmNeAt7PRM10Jb4CdBtjjgF/Duyv4NflAXcD\n/94Y8zLwEjBj06WIyFpk3vvbPBERERERWQxlrkVEREREqkTBtYiIiIhIlSi4FhERERGpEgXXIiIi\nIiJVouBaRERERKRKFFyLiIiIiFSJgmsRERERkSpRcC0iIiIiUiX/P43c9SW/6gq4AAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1102d9f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Create a new figure\n",
    "plt.figure(figsize=(12,6))\n",
    "\n",
    "#Scatter plot of a team's total goals at home against away \n",
    "plt.scatter(x=df_all['total_home_goals'], y=df_all['total_away_goals'], alpha=0.6\\\n",
    "            , color='g', label = 'Scored')\n",
    "\n",
    "#Scatter plot of a team's total goals conceded at home against away \n",
    "plt.scatter(x=df_all['total_home_goals_conceded'], y=df_all['total_away_goals_conceded']\\\n",
    "            , alpha=0.6, color='c', label = 'Received')\n",
    "\n",
    "plt.title('Correlation Goals Home vs Away')\n",
    "plt.xlabel('Goals Home')\n",
    "plt.ylabel('Goals Away')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_home_goals</th>\n",
       "      <th>total_away_goals</th>\n",
       "      <th>total_home_goals_conceded</th>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>total_home_goals</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.981976</td>\n",
       "      <td>0.739852</td>\n",
       "      <td>0.736638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_away_goals</th>\n",
       "      <td>0.981976</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.733147</td>\n",
       "      <td>0.735996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_home_goals_conceded</th>\n",
       "      <td>0.739852</td>\n",
       "      <td>0.733147</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.964019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_away_goals_conceded</th>\n",
       "      <td>0.736638</td>\n",
       "      <td>0.735996</td>\n",
       "      <td>0.964019</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           total_home_goals  total_away_goals  \\\n",
       "total_home_goals                   1.000000          0.981976   \n",
       "total_away_goals                   0.981976          1.000000   \n",
       "total_home_goals_conceded          0.739852          0.733147   \n",
       "total_away_goals_conceded          0.736638          0.735996   \n",
       "\n",
       "                           total_home_goals_conceded  \\\n",
       "total_home_goals                            0.739852   \n",
       "total_away_goals                            0.733147   \n",
       "total_home_goals_conceded                   1.000000   \n",
       "total_away_goals_conceded                   0.964019   \n",
       "\n",
       "                           total_away_goals_conceded  \n",
       "total_home_goals                            0.736638  \n",
       "total_away_goals                            0.735996  \n",
       "total_home_goals_conceded                   0.964019  \n",
       "total_away_goals_conceded                   1.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Calculate pearson coefficient to verify if there is correlation between the chosen columns\n",
    "df_all[['total_home_goals','total_away_goals','total_home_goals_conceded'\\\n",
    "        ,'total_away_goals_conceded']].corr('pearson')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we expected it, goals scored (home and away) and goals received (home and away) are strongly correlated. This means that when a team scores more goals home it will tend to score more goals away. The same applies to the received goals. However the received goals have a greater slope which means they tend to be less than the scored goals."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='scored_recv_goals'></a>\n",
    "### Goals Scored correlate to Received Goals?\n",
    "\n",
    "The next question we had was to know if scored goals correlate to received goals, adn we might be expectig somehow of a correlation thanks to our insight found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AgIgQXAMAAAARIbgGAAAAIkJwDQAAAESE4BoAAACISKrVAwCAVpjeO63J3ZPKHcgpuyWr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1129e7ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Scatter plot of a team's total goals scored against total goals conceded \n",
    "plt.figure(figsize=(12,6))\n",
    "plt.scatter(x=df_all['total_goals_conceded'],y=df_all['total_goals'], alpha=0.5, color='m');\n",
    "plt.title('Correlation Goals Score vs Received')\n",
    "plt.xlabel('Goals Received')\n",
    "plt.ylabel('Goals Scored');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_goals</th>\n",
       "      <th>total_goals_conceded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>total_goals</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.746472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_goals_conceded</th>\n",
       "      <td>0.746472</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      total_goals  total_goals_conceded\n",
       "total_goals              1.000000              0.746472\n",
       "total_goals_conceded     0.746472              1.000000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Calculate pearson coefficient to verify if there is correlation between the chosen columns\n",
    "df_all[['total_goals','total_goals_conceded']].corr('pearson')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To our surprise the goals scored and received are somehow linearly correlated, but not as strong as we would have expected. This might be caused by the star teams as they tend to score more and receive less goals."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='home_win'></a>\n",
    "### Home Games and the Winning Factor\n",
    "\n",
    "If you are a soccer fan you have heard fo the home winning factor because it is said that if a team plays home it tends to win. Here we will investigate this idea."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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P7aC79/hrAyNOn1NGZXE+j6hWUCQhclIdgIhktqd2NNLb71xwYhISwVml3P3s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nL4Pw57HYqIHKdSJoKPAWvNbLWZhYCNwKYpYzYB1xUeXwPc7/Iucs6tcs6tAv4J+Ixz7osljFU8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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112b99978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Distribution of average victories at home and \n",
    "# the distribution of the proportion of victories of a team at home out of total games\n",
    "plt.figure(figsize=(15,9))\n",
    "plt.subplot(221)\n",
    "#plt.hist(df_all['avg_home_win'], bins=10 ) #matplotlib\n",
    "sns.distplot(df_all['avg_home_win'], bins=10 )\n",
    "plt.title('Average Wins @ Home Distribution')\n",
    "plt.xlabel('')\n",
    "plt.ylabel('Frequency')\n",
    "plt.subplot(222)\n",
    "#plt.hist(df_all['prop_home_win'], bins=10) #matplotlib\n",
    "sns.distplot(df_all['prop_home_win'], bins=10)\n",
    "plt.xlabel('')\n",
    "plt.title('Proportion of Wins @ Home Distribution')\n",
    "\n",
    "#Distribution of average victories away and \n",
    "# the distribution of the proportion of victories of a team away out of total games\n",
    "plt.subplot(223)\n",
    "#plt.hist(df_all['avg_away_win'], bins=10, color ='m', alpha=0.5 ) #matplotlib\n",
    "sns.distplot(df_all['avg_away_win'], bins=10, color ='m')\n",
    "plt.title('Average Wins Away Distribution')\n",
    "plt.xlabel('Wins')\n",
    "plt.ylabel('Frequency')\n",
    "plt.subplot(224)\n",
    "#plt.hist(df_all['prop_away_win'], bins=10, color ='m', alpha=0.5) #matplotlib\n",
    "sns.distplot(df_all['prop_away_win'], bins=10, color ='m')\n",
    "plt.title('Proportion of Wins Away Distribution')\n",
    "plt.xlabel('Percentage');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is something very interesting in this histograms. \n",
    "\n",
    "If a team plays away it tends to win less in average compared to the average victories at home.\n",
    "The histogram of average victories away also matches with the distribution of the proportion of wins away histogram. This confirms that a team wins less when it plays away.\n",
    "\n",
    "However, the most interesting graph comparison is between the average wins home and the proportion of wins at home. These show a shift in the data. Meaning that on average, teams tend to win more at home than away based on the blue upper left histogram, but the proportion of wins at home histogram shows that most teams only win 40% of their games played at home. This is a very interesting discovery.\n",
    "\n",
    "All in all, we can confirm that the teams do actually perfom better at home since on averag they win more games home than away, and the majority of teams wins a higher porportion of their games at home.\n",
    "\n",
    "To illustrate our conclusion even more we can also check if draws are more related to wins at home or away"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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XQhaaTHquvw0MG2POAW4C9gH/WtBWyfFFg9KkWLS0uImJrrjCPc5G7/E8+fzP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\nHwgmoITbUyHxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112ba42b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of the average draws against the average victories\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.scatter(x=df_all['avg_home_win'],y=df_all['avg_home_draw'],\\\n",
    "            alpha=0.6, label = 'Home')\n",
    "plt.scatter(x=df_all['avg_away_win'],y=df_all['avg_away_draw'],\\\n",
    "            alpha=0.6, color='r', label = 'Away')\n",
    "plt.title('Correlation of Wins vs Draws')\n",
    "plt.xlabel('Average Wins')\n",
    "plt.ylabel('Average Draws')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the scatter plot above we can confirm our thoughts on teams winning more at home and we can say draws are almost the same home or away."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='leagues'></a>\n",
    "### Leagues Performance\n",
    "\n",
    "Finally, we want to analyze the performance of each league to understand which league has a better overall effectivity based on its teams. We had already displayed the dtaframe that contains all our information before starting our EDA.\n",
    "\n",
    "The analysis to find that out is t first use boxplots of each league, then plot a bar chart to distinguish their heights and finally try to correlate each league performance to the total goals in each league"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NhE7Q/A48KslBSX4ReOGU43b6PlbVVTRDP76m/f04EtjA3L89kLTEmZhL6kf/TDP75cTj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\n0rxN7mC2F82kJhezY02dBsPfAO+kqR3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duojhJWk+8Brgpq5e1pwGGhERq1xaWepcBVxq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11259cba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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q50VEVlaW88Jh0KBBNG/evMR9e6F169axe/du5/Dp06c5c+YMaWlpTJw4kYSE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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11259c7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# BoxPlot of each league distribution of effectivity\n",
    "df_all.boxplot(column='overall_effectivity', by='league', figsize=(12,5))\n",
    "plt.ylabel('Effectivity [%]')\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Leagues Effectivity Distribution');\n",
    "\n",
    "c = ['orange', 'blue', 'c', 'g','m','k'] \n",
    "\n",
    "\n",
    "# Bar plot of avg effectivity on each league\n",
    "plt.figure(figsize=(12,5))\n",
    "\n",
    "plt.subplot(1,2,1)\n",
    "plt.bar(range(df_leagues.shape[0]), df_leagues['overall_effectivity']\\\n",
    "        , alpha= 0.75, color=c )\n",
    "plt.xticks(range(df_leagues.shape[0]),df_leagues.index, rotation=90)\n",
    "plt.ylabel('Effectivity [%]')\n",
    "plt.title('League Performance');\n",
    "\n",
    "# Scatter plot effectivity vs total goals scored\n",
    "plt.subplot(1,2,2)\n",
    "labels = [l for l in df_leagues.index]\n",
    "for i in range(df_leagues.shape[0]):\n",
    "    plt.scatter(x=df_leagues.query('league == \"{}\"'.format(labels[i]))['overall_effectivity']\n",
    "                , y=df_leagues.query('league == \"{}\"'.format(labels[i]))['total_goals']\n",
    "                , alpha= 0.75, color= c[i]\n",
    "                , s=2*df_leagues['total_matches'].astype(int)\n",
    "                , label=labels[i]\n",
    "                )\n",
    "\n",
    "plt.legend(handletextpad=0.8, markerscale=0.5)\n",
    "plt.ylabel('Total Goals')\n",
    "plt.xlabel('Effectivity [%]')\n",
    "plt.title('Leagues Mean Performance vs Mean Goals Scored');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The boxplot is the most useful from all our plots in this analysis as it also show outliers, but we should not ignore the other plots as they convey important information to complete our analysis.\n",
    "\n",
    "1. France Ligue 1 seems to be the league with better performance, but it has less goals scored and it has a team that has a performance extremely low compared to the other teams in the league. This causes the distribution to have mean shifted to the left. All in all, this might be the most balanced league and that is the reason to have the highest average with less goals scored.\n",
    "\n",
    "2. England Premier League is the second league based on performance, and the goals scored are close to other 3 leagues. The boxplot tells us that in this league there are no outliers and that there is a skew toward the positive performance (right). This means that in this league there are many good teams as 2 teams from this league (Manchester United, Chelsea) are part of the top 10 teams from all leagues, but they are not outliers in their league. They are only part of the right skew.\n",
    "\n",
    "3. Italy Serie A is the third rank and right away the boxplot tell us that these league has a really bad team and an extremly good team. The good team is Juventus. Besides that we can see the distribution is close to normal, but a bit left skewed. However, it seems to be a balanced league and it has more goals than the previous two.\n",
    "\n",
    "4. Netherlands Erdivisie shows the same exact behavior the Premier League did except for the fact that in this league we have the maximum number of goals and the most right skewed and widest distribution. However, there were no outliers marked. This tell us that in this league there are some top teams that score a lot when they win.\n",
    "\n",
    "5. Spain Liga BBVA takes the fifth place with a very tight distribution very close to normal and with 2 outliers that we all know them: Real Madrid and Barcelona. These two teams outperform every other team in their league and Barcelona is the number 1 rank in all teams. Thus, we do expect this distribution to be a bit skewed. If we were to remove these 2 outperformers we will probably get a normal distribution.\n",
    "\n",
    "6. Germany 1. Bundesliga takes the last place from all leagues performance, but the goals scored are very close to other leagues. This league just like Liga BBVA has two outperformers: Ajax and PSV. They are the resposibles of shifting the distribution.\n",
    "\n",
    "Once we got the leagues distribution and analyzed that only total goals scored are related to a team effectivity, but not the goals received; curiosity drove me to check if there are clusters made beetween the league effectivity, team effectivity and goal difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MvfTSS2zSpEm1+m8ymZhYLGaXL1/mv9uzZ4/Dw1Jz0BAxazAw9uyztYWsvaB99lnG/ves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YZOnKDvk5/k5Kg/LaATO1VVkSRJX+CpqordbicajVJZWcm73vWuWRMxVVVpbGzk7NmziKKI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\nUpgVEREREdP6Ey63k8ZyeoFWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112a2cba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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S3WlSnamRbXTe3NnwHKVaQxVwPtfVbF6Py0QKuA74z+7+L2b2h4x2AWykqR4v7v4p4FMA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\ny3DDHUlhdpoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11359aa20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3D plot of league's clusters\n",
    "fig = plt.figure(figsize=(12,10))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "query_str = ['league == \"England Premier League\"'\n",
    "             ,'league == \"Spain LIGA BBVA\"'\n",
    "             ,'league == \"Germany 1. Bundesliga\"'\n",
    "             ,'league == \"Italy Serie A\"'\n",
    "             ,'league == \"Netherlands Eredivisie\"'\n",
    "             ,'league == \"France Ligue 1\"'\n",
    "             ]\n",
    "\n",
    "labels = ['Premier League'\n",
    "         ,'Liga BBVA'\n",
    "         ,'Bundesliga'\n",
    "         ,'Serie A'\n",
    "         ,'Eredivisie'\n",
    "         ,'France']\n",
    "\n",
    "c= ['b','r','gray','g','orange','m']\n",
    "\n",
    "# Leagues clusters based on team's effectivity, league's effectivity of the team, team's total goals difference\n",
    "for i in range(len(labels)):\n",
    "    ax.scatter(xs=df_all.query(query_str[i])['overall_effectivity']\\\n",
    "            ,zs=df_all.query(query_str[i])['league_overall_effectivity']\\\n",
    "            ,ys=df_all.query(query_str[i])['total_goals_difference'], \\\n",
    "            alpha=0.45, label = labels[i], color = c[i], s=80)\n",
    "\n",
    "#Top teams markers\n",
    "df_top = df_all.head(10)\n",
    "ax.scatter(xs=df_top['overall_effectivity']\n",
    "           , ys=df_top['total_goals_difference']\n",
    "           , zs=df_top['league_overall_effectivity']\n",
    "           , alpha=1, marker='*', color='k'\n",
    "           , label = 'Top Teams', s=50)\n",
    "\n",
    "ax.set_zorder(len(labels))\n",
    "ax.set_xlabel('Team Effectivity [%]')\n",
    "ax.set_zlabel('League Effectivity [%]')\n",
    "ax.set_ylabel('Goals Difference')\n",
    "plt.title('Cluster of Leagues and Teams Performance by Goals Difference', y=1.04)\n",
    "\n",
    "ax.legend();\n",
    "\n",
    "#subplots that split up the 3D plot in different planes\n",
    "fig = plt.figure(figsize=(16,5))\n",
    "\n",
    "# Team's effectivity vs team's league's effectivity \n",
    "plt.subplot(1,3,1)\n",
    "for i in range(len(labels)):\n",
    "    plt.scatter(x=df_all.query(query_str[i])['overall_effectivity']\\\n",
    "            ,y=df_all.query(query_str[i])['league_overall_effectivity']\\\n",
    "            ,alpha=0.45, label = labels[i], color = c[i], s=80)\n",
    "\n",
    "plt.xlabel('Team Effectivity [%]')\n",
    "plt.ylabel('League Effectivity [%]')\n",
    " \n",
    "# Team's effectivity vs total goals difference    \n",
    "plt.subplot(1,3,2)\n",
    "for i in range(len(labels)):\n",
    "    plt.scatter(x=df_all.query(query_str[i])['overall_effectivity']\\\n",
    "            ,y=df_all.query(query_str[i])['total_goals_difference']\\\n",
    "            ,alpha=0.55, label = labels[i], color = c[i], s=80)\n",
    "\n",
    "plt.xlabel('Team Effectivity [%]')\n",
    "plt.ylabel('Goals Difference')\n",
    "    \n",
    "# Team's league's effectivity vs total goals difference\n",
    "plt.subplot(1,3,3)\n",
    "for i in range(len(labels)):\n",
    "    plt.scatter(x=df_all.query(query_str[i])['league_overall_effectivity']\\\n",
    "            ,y=df_all.query(query_str[i])['total_goals_difference']\\\n",
    "            ,alpha=0.55, label = labels[i], color = c[i], s=80)\n",
    "\n",
    "plt.xlabel('League Effectivity [%]')   \n",
    "plt.ylabel('Goals Difference');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mainly, I did this plot to show clusters from the data because leagues have different average performances, but teams have a similar effectivity as shown in the first distribution plotted. This leads to overlaps that we can see in the bottom middle subplot. Especially, our overlap is due to the difference in goals. We discovered that teams that peformed better scored more goals and must have won or draw the most. That doesn't necessarily meant the top teams goal difference will be higher than all other teams, but we hope that is the case as they kept winning and increasing their goals difference with positive numbers. This 3D plot shows exactly that and the most interesting part is that not necesarily a high positive goal difference makes a team the one with high effectivity. In other words, it is confirming that effectivity of teams depends more on scoring goals and not necessarily to receiving less goals."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "## Conclusions\n",
    "\n",
    "The main conclusion we can make from the soccer data are:\n",
    "\n",
    "* The **teams' effectivity distribution** is close to normal with a slight skewness to the right. However, if we were to get more leagues and plot a distrbution we might find it is actually normal and we just needed more teams as 189 teams (samples) might be a small set to determine this. In any case, I decided to calculate the mean, median and standard deviation of this distribution which are 57.65%, 56.58%  and 12.13% respectively. This tell us that the median being very close to the mean is a good sign of a distribution close to a normal distribution, but in this case it confirms our conclusion of having a slight right skewness.\n",
    "\n",
    "* The **teams' effectivity is strongly correlated (positive) to how many goals a team scores** \n",
    "\n",
    "* The **teams' effectivity is weakly correlated (positive) to how many goals a team receives**\n",
    "\n",
    "> From the two conclusions above we also discovered that the goals scored home and way is strongly correlated meaning that if a teams scores a lot at home, it tends to score away more goals as well. The same applies for goals received. If a team receives more goals at home it also tends to receive more goals away.\n",
    "\n",
    "* The **home winning factor** was proven to be true after we analyzed histogram of proportion of wins home and away, avergae games won at hoem and away, and we made a scatter plot of draw vs wins home and away. These visualizations helped us realized that team on average win more at home although that doesn't mean all teams win at home. In fact, a little proportion of teams win most fo the games at home.\n",
    "\n",
    "* Finally, the **league effectivity rank** we performed helped us to rank the leagues based on effectivity and it actually open many more questions that we didn't address here such as why a league is better than another? is it because a greater amount of better teams play there? what is a 'better team'? Are balanced leagues performing better? All in all, the conlusion we got from analyzing data for each league helped us realize that all these leagues have a very similar average effectivity and that the distribution are quite tight among the teams playing in each league. The top performers teams were easily seen as outliers in our plots, and we also determine that each league has its own characteristics, because th total goals varies. For example the Eredivisie has the most goals, and that can indicate there are better teams than the average and less team below the average, which our boxplot confirms. On the other side the League 1 has the best effectivity but the least amount of goals whihc tell us it most be a very balanced league in which teams either score a lot but end up in a draw or they win a lot and lose a lot. We can say that as the goal difference distribution of its teams is almost center around zero. We could containue making sense out of these plots for a long times, and more and more questions will continue to pop up. \n",
    "\n",
    "\n",
    "If there is a big take away from this analysis is realizing the truth behind the phrase:\n",
    " >\"The worst team can beat the position 1 on the table team on a sunday match\" \n",
    "\n",
    "Now, we can agree with that and stop beliving it is black magic. In fact, it is just that the lowest on the table teams of each league are actually not awful teams, they are in a decent standing within a distribution and might have an average effectivity below the average of the legaue, but that doesn't mean a zero chance to win. That is the beauty of football and we just proved by analyzing the leagues and teams.\n",
    "\n",
    "<a id='limitations'></a>\n",
    "## Limitations on Analysis\n",
    "\n",
    "1. The first limitation described in conclusions is the size of our dataset. We only had 189 teams which each had a lot of data, but we needed to compacted it to have an overall performance and data over the year for all teams. The 189 samples seems a small number for a massive study of soccer in Europe. If we were able to get all teams in all leagues we might get different distributions or correlations as we found in here.\n",
    "\n",
    "2. This dataset is only for European teams and only a small sample of all european soccer teams. The conclusions made here are valid only for the European leagues and maybe even narrower to only teh leagues we chose. This is due to the lack of a hypothesis testing or confidence interval statistics for our data.\n",
    "\n",
    "3. The data used is from 2008 to 2015 which means that if we want to make predictions of 2016 to 2018 we will be out of the time we analyzed and we do not know if the behavior, distributions of the soccer matches and teams have changed. It is not recommended to predict anything with out data unless we use more advance techniques such as machine learning and predictive algorithms.\n",
    "\n",
    "4. The effectivity of each team and the league were calculated based on the win and draw games, meaning that the variables of goals difference/scored/received were not taken into account. This limits us to only say a team is better than another based on its rating on less matches lost. Someone might be more interested in getting and effectivity considering more variables and that is valid. For the purpose of thsi analysis I was more interested in effectivity as the teams that win/draw more as such teams tend to be the best positions on their league table.\n",
    "\n",
    "The above are some of the limitations, but not all the ones taken to restrict this analysis and narrow it down to team performance, league performance, goals scored relationship and the famous winning factor.\n",
    "\n",
    "Hope this notebook helps people understand more about the data analysis process and how a dataset can be limited to an specific set fo questions, but there are almost an infinite number fo questions one can asked and try to answer with a single dataset. \n"
   ]
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