- git remote add origin https://github.com/carlosfugazi/LeagueAnalysis.git
- git push -u origin master
- git pull -u origin master
- Website for fonts
- Results websites
- http://www.worldfootball.net/alle_spiele/ita-serie-a-2011-2012/
- http://www.worldfootball.net/alle_spiele/esp-primera-division-2011-2012/
- http://www.worldfootball.net/alle_spiele/fra-ligue-1/
- http://www.worldfootball.net/alle_spiele/bundesliga/
- http://www.premierleague.com/en-gb/matchday/results.html?paramComp_100=true&view=.dateSeason
- http://football-data.co.uk/englandm.php
- league_table_parsing.py
- Parses the base csv data in ./csv_data/
- Produces the necessary league dictionary from these files
- Also produces the subsidiary dict based on the teams (every key is a team with their table information)
- Parses the base csv data in ./csv_data/
- applications_on_parsed_data.py - Prints league tables, plots... etc...
- classes.py
- Creates a league class object going to be improved considerably.
- Already can print table, plot league position and points evolution as well
- Creates a league class object going to be improved considerably.
- Major keys in league dictionary object
- dict_['League Name'] = LEAGUENAME
- dict_['Country'] = COUNTRY
- dict_['Years'] = YEARS
- dict_['Year1'] = int(YEARS.split('-')[0])
- dict_['Year2'] = int(YEARS.split('-')[1])
- dict_['N_games'] = len(dict_['Home Team'])
- Basic column structure of csv files:
- 'Matchday,Home Team,Away Team,Goals Home,Goals Away,Points Home,Points Away']
- Dict team (generated from league table data)
- Code sample of definition:
dict_teams[team] = {'points':point_totals[i], 'goal difference':goal_differences[i], 'league position':position, 'goals for':goals_for[i], 'goals against':goals_against[i], 'home points':points_home[i], 'away points':points_away[i], 'wins':wins[i],'draws':draws[i],'loses':loses[i]}
- Code sample of definition: