I am facing a multilabel classification challenge.
My goal is to remove rows that have a value of 0 in all 35 columns of the data frame, except for the ['Doc'] column.
Below is an example of the dataframe:
Doc Big Small Int Bor Drama
j2 0 0 0 0 0
i9 1 0 1 1 0
ui8 0 0 0 1 0
po4 0 1 0 0 0
po9 0 0 0 0 0
The expected outcome should look like this:
Doc Big Small Int Bor Drama
i9 1 0 1 1 0
ui8 0 0 0 1 0
po4 0 1 0 0 0
The following are the rows that need to be deleted:
j2 0 0 0 0 0
po9 0 0 0 0 0
To identify and count these rows, follow this code snippet:
rowSums = df.iloc[:,2:].sum(axis=1)
no_labelled = (rowSums==0).sum(axis=0)
print("Number of docs with no label =", no_labelled)
Number of docs with no label = 60
If you're wondering how to delete these 60 rows from the dataframe, feel free to ask for further assistance.
Thank you