Select columns in pandas dataframe by value in rows

I have a pandas.DataFrame with too much columns. I want to select all columns with values in rows equals to 0 and 1. Type of all columns is int64 and I can't select they by object or other type. How can I do this?


IIUC then you can use isin and filter the columns:

In [169]: df = pd.DataFrame({'a':[0,1,1,0], 'b':list('abcd'), 'c':[1,2,3,4]}) df Out[169]: a b c 0 0 a 1 1 1 b 2 2 1 c 3 3 0 d 4 In [174]: df[df.columns[df.isin([0,1]).all()]] Out[174]: a 0 0 1 1 2 1 3 0

The output from the inner condition:

In [175]: df.isin([0,1]).all() Out[175]: a True b False c False dtype: bool

We can use the boolean mask to filter the columns:

In [176]: df.columns[df.isin([0,1]).all()] Out[176]: Index(['a'], dtype='object')


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