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for every row find the last column with value 1 in binary data frame

Time:04-10

consider a data frame of binary numbers:

import pandas 
import numpy
numpy.random.seed(123)
this_df = pandas.DataFrame((numpy.random.random(100) < 1/3).astype(int).reshape(10, 10))


   0  1  2  3  4  5  6  7  8  9
0  0  1  1  0  0  0  0  0  0  0
1  0  0  0  1  0  0  1  1  0  0
2  0  0  0  0  0  1  0  1  1  0
3  1  0  0  0  0  1  0  0  0  0
4  0  1  1  0  0  1  0  0  0  0
5  1  0  0  0  0  1  0  0  0  0
6  0  0  0  0  0  1  0  1  1  0
7  1  0  0  0  1  0  0  1  1  0
8  1  0  0  0  0  0  0  1  1  0
9  0  0  0  0  0  0  1  0  1  0

how do I find, for each row, the rightmost column in which a 1 is observed?

so for the dataframe above it would be:

[2, 7, 8,....,8]

CodePudding user response:

One option is to reverse the column order, then use idxmax:

df['rightmost 1'] = df.loc[:,::-1].idxmax(axis=1)

Output:

   0  1  2  3  4  5  6  7  8  9 rightmost 1
0  0  1  1  0  0  0  0  0  0  0           2
1  0  0  0  1  0  0  1  1  0  0           7
2  0  0  0  0  0  1  0  1  1  0           8
3  1  0  0  0  0  1  0  0  0  0           5
4  0  1  1  0  0  1  0  0  0  0           5
5  1  0  0  0  0  1  0  0  0  0           5
6  0  0  0  0  0  1  0  1  1  0           8
7  1  0  0  0  1  0  0  1  1  0           8
8  1  0  0  0  0  0  0  1  1  0           8
9  0  0  0  0  0  0  1  0  1  0           8
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