在Python中跨多个列进行计数

Question

I'm pretty new to Python and have searched the web for an answer to this but it is tricky to find without showing it as an example!

The data I have data is here: Dataset

What I'm after is the number of times each 'HomeTeam' has appeared in both the 'HomeTeam' and 'AwayTeam' columns up to and including the date. So for the last row of data in the sample, the input would be 'Fulham', and the output = 4. This is because 'Fulham' has appeared 4 times in the 'HomeTeam' and 'AwayTeam' columns. For the first row of data, again, the input would be 'Fulham', but the output = 1, as it is the first time 'Fulham' has appeared. For the sample dataset, the output should be:

[1,1,2,1,3,1,4]

My code so far only allows me to get the number of times each team has appeared in the 'HomeTeam' column only:

df['H Count'] =  df.groupby(['HomeTeam']).cumcount()+1

This gives me the output:

[1,1,1,1,2,1,2]

Any help would be much appreciated!

Answer 1

As I understand, the team currently in the HomeTeam is being used as input. I don't know how you read in the dataset, but I have just created lists below. The logic should however be clear. Having the below, I get [1, 1, 3]

HomeTeam = list()
HomeTeam.append("Fulham")
HomeTeam.append("Tottenham")
HomeTeam.append("Fulham")
AwayTeam = list()
AwayTeam.append("Chelsea")
AwayTeam.append("Fulham")
AwayTeam.append("Liverpool")
H_Count = []

p = 1
''' The team in the HomeTeam is used as input'''
for team in HomeTeam:
    ''' Get the list up until the current row'''
    tmp_Home = HomeTeam[:p]
    tmp_Away = AwayTeam[:p]

    ''' Count the number of times team has occured in home and away'''
    H_Count.append(tmp_Home.count(team) + tmp_Away.count(team))

    p+=1