按行数值选择pandas dataframe中的列

Question

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?

Answer 1

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')