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I want to drop all rows in the ratings df where the team has no game. So not in the fixtures df in HomeTeam or AwayTeam occur. following I tried:

fixtures = pd.DataFrame({'HomeTeam': ["Team1", "Team3", "Team5", "Team6"], 'AwayTeam': [ "Team2", "Team4", "Team6", "Team8"]}) ratings = pd.DataFrame({'team': ["Team1", "Team2", "Team3", "Team4", "Team5", "Team6", "Team7", "Team8", "Team9", "Team10", "Team11", "Team12"], "rating": ["1,5", "0,2", "0,5", "2", "3", "4,8", "0,9", "-0,4", "-0,6", "1,5", "0,2", "0,5"]}) ratings = ratings[(ratings.team != fixtures.HomeTeam) & (ratings.team != fixtures.AwayTeam)]

but I get the error message:

ValueError: Can only compare identically-labeled Series objects

what can i do to stop the error from occurring?

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  • Why did you deleted your other question? Seemed like an interesting one. In any case check my answer even if you want to leave it deleted. Commented Nov 28, 2022 at 8:31
  • i got a message almost immediately after creating the question that my question was closed by stackoverflow because it was already answered by another question: stackoverflow.com/questions/53010406/… Commented Nov 28, 2022 at 9:02
  • in the end you are the judge, I believe the closing was not really justified. It was not closed by stackoverflow but by one user who judged it should be closed, other users can vote to reopen Commented Nov 28, 2022 at 9:07

1 Answer 1

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Because both dataframes are not of equal size. You can use isin() instead.

ratings = ratings[~ratings.team.isin(fixtures.stack())] #output ''' team rating 6 Team7 0,9 8 Team9 -0,6 9 Team10 1,5 10 Team11 0,2 11 Team12 0,5 '''

Details:

print(fixtures.stack()) ''' 0 HomeTeam Team1 AwayTeam Team2 1 HomeTeam Team3 AwayTeam Team4 2 HomeTeam Team5 AwayTeam Team6 3 HomeTeam Team6 AwayTeam Team8 dtype: object '''

As you can see this returns all values ​​in fixtures. Using the ~ operator in the isin function, we filter out those that do not contain these values.

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i had to remove the ~ and then the code did what i wanted. Thank you

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