Hello I have a csv file of sports results for the english premier league that I am wanting to manipulate a single team that is located either in a home or away column. I then want to be able to create a series of columns which are sorted by that team and then return the results as per below. I have been able to do this in a loop but would love to know the pandas method. I have attempted to group by team- arsenal, but am finding it difficult to do that with two column options, where i would need to flip subsets of the opposing team.
df = pd.read_csv(
'http://www.football-data.co.uk/mmz4281/1516/E0.csv',
sep=',')
result= df[(df['HomeTeam'] == "Arsenal") | (df.AwayTeam == "Arsenal")]
for index, row in result.iterrows():
if row['HomeTeam'] == "Arsenal":
if row['FTR'] == "H":
print ('Win' , 'Home', row['FTHG'], '-', row['FTAG'])
elif row['FTR'] == "D":
print ('Draw' , 'Home', row['FTHG'], '-', row['FTAG'])
else:
print ('Lose' , 'Home', row['FTHG'], '-', row['FTAG'])
# we dont need to put the conditons for else because we know if arsenal are not the home team they must be the away team,
# this is because we already set out dataframe filter above to show only games where arsenal is home or away, if we didnt
# do this we would do an elif and then do an improper result print for else
else:
if row['FTR'] == "H":
print ('Win' , 'Home', row['FTHG'], '-', row['FTAG'])
elif row['FTR'] == "D":
print ('Draw' , 'Home', row['FTHG'], '-', row['FTAG'])
else:
print ('Lose' , 'Home', row['FTHG'], '-', row['FTAG'])
