How can i filter a Pandas DataFrame which looks like this:
Head Cat1 Cat2 Cat3
"A" 0 0 1
"B" 1 0 1
So that it returns for every row the Category-Column-Names if not 0
For example
"A" "Cat3"
"B" "Cat1" "Cat3"
I have no idea how to solve this and i deeply appreciate every help
You can filter the columns first to get the cols of interest and then call apply and use the boolean mask to mask the cols:
In [18]:
cat_cols = df.columns[df.columns.str.contains('Cat')]
df[cat_cols].apply(lambda row: ', '.join(cat_cols[row == 1]), axis=1)
Out[18]:
0 Cat3
1 Cat1, Cat3
dtype: object
Also possible to retrieve the columns by accessing the .index attribute:
df[cat_cols].apply(lambda row: ', '.join(row.index[row == 1]), axis=1)
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