Get list of column names of values >0 for specific row (date) in Python-CodePudding

I have a DataFrame df1 and I want to get at a specific date, for example 2022-01-04 all the column names of df1 in a list which would be: 01G, 02G, 04G. So far I was only able to get the number of each row, but not the column names.

This would be a simple example:

df1:
            01G 02G 03G 04G
Dates               
2022-01-01  0   1   0   1
2022-01-02  1   1   1   0
2022-01-03  0   1   1   1
2022-01-04  1   1   0   1

For reproducibility:

import pandas as pd
import numpy as np

df1 = pd.DataFrame({
    'Dates':['2022-01-01', '2022-01-02', '2022-01-03', '2022-01-04'],
    '01G':[0, 1, 0, 1], 
    '02G':[1, 1, 1, 1], 
    '03G':[0, 1, 1, 0], 
    '04G':[1, 0, 1, 1]})
df1 = df1.set_index('Dates')

np.count_nonzero(df1, axis=1)

Thanks a lot!

CodePudding user response：

Use DataFrame.loc for filter row by datetime, compare for greater like 0 and filter columns names:

print (df1.columns[df1.loc['2022-01-04'].gt(0)].tolist())
['01G', '02G', '04G']

CodePudding user response：

For your special case, it seems we can also filter using the row values directly after changing dtype to bool:

out = df1.columns[df1.loc['2022-01-04'].astype(bool)].tolist()

Output:

['01G', '02G', '04G']