Extracting columns from multiindex csv file

Asked Nov 25 '20 at 08:17

Active Nov 25 '20 at 08:18

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I have a csv file that I read into a pandas dataframe

platesStatistics= pd.read_csv('cells.csv',index_col=[0,1], header=[0,1])

I then want to get all 'mean' columns. I tried

platesStatistics['mean']
platesStatistics[:,'mean']

but it doesn't work (I also tried some commands with loc). What confuses me is that platesStatistics['A','mean'] works fine and returns a single series.

What is the right way to get the reduced dataframe? It is important to note that the actual file I'm working with is much larger, so extracting columns explicitly would be hard.

asked Nov 25 '20 at 08:17

Shaharg

What should be expected output? MultiIndex (A, B) and `mean` levels or columns `A, B` ? – jezrael Nov 25 '20 at 08:26
I expect to get columns ```A, B``` – Shaharg Nov 25 '20 at 08:40
1

Ok, then use `df = platesStatistics.xs('mean', axis=1, level=1)` – jezrael Nov 25 '20 at 08:41
1

This is exactly what I have been looking for. thanks! I now see that this question has been answered before (I didn't manage to find the answer earlier). – Shaharg Nov 25 '20 at 08:51

Extracting columns from multiindex csv file

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