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?
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1 Answer
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')
