在Pandas数据框中查找行唯一的列

Question

I have a dataframe of the below structure. I want to get the column numbers which are unique to a particular row.

1 1 0 1 1 1 0 0 0
0 1 0 1 0 0 0 0 0
0 1 0 0 1 0 0 0 0
1 0 0 0 1 0 0 0 1
0 0 0 0 0 0 1 1 0
1 0 0 0 1 0 0 0 0

In the above example I should get coln6, coln7, coln8, coln9 (as there is only one row which has a value specific to these columns). Also I should be able to distinguish among the columns like coln7 and coln8 should group together as they are unique to the same row. Is there an efficient solution in Python for this?

Answer 1

Here is my first approach:

import numpy as np
import pandas as pd

df = pd.DataFrame(np.array([
    1,1,0,1,1,1,0,0,0,
    0,1,0,1,0,0,0,0,0,
    0,1,0,0,1,0,0,0,0,
    1,0,0,0,1,0,0,0,1,
    0,0,0,0,0,0,1,1,0,
    1,0,0,0,1,0,0,0,0]).reshape(6,9))

print df.sum(axis=0).apply(lambda x: True if x == 1 else False)

Output:

0    False
1    False
2    False
3    False
4    False
5     True
6     True
7     True
8     True
dtype: bool

Answer 2

You can call sum on the df and compare against 1 and use this to mask the columns:

In [19]:
df.columns[df.sum(axis=0) == 1]

Out[19]:
Int64Index([5, 6, 7, 8], dtype='int64')