python - Creating new column based on multiple columns pandas

Question

I'm trying to create categories based on multiple columns in pandas but it is taking forever to run so i'm not sure it is correct. I left for 30 mns and was still running so stopped it. I'm trying to create a new column based on several other columns (in my actual data it is about 15 cols). However when I try on a smaller dataset it is very quick. Any suggestions?

other_cols = ['col1', 'col2', 'col3', 'col4', 'col5']


def labels(row):
    if ((row['col 6'] > 1) & (row[other_cols] < 1)).all():
        return 'Yes'
    if ((row['col 6'] >1) & (row['col 7'] >1) & (row[other_cols] <1)).all():
        return 'Maybe'
    if ((row['col 6'] <1) & (row['col 7']>1) & (row[other_cols] <1)).all():
        return 'no'

df['category'] = df.apply(lambda row: labels(row), axis=1)

question from:https://stackoverflow.com/questions/65940888/creating-new-column-based-on-multiple-columns-pandas

Answer 1

You can try that maybe :

ther_cols = ['col1', 'col2', 'col3', 'col4', 'col5']


def labels(row):
    elif ((row['col 6'] > 1) & (row[other_cols] < 1)).all():
        row['category'] = 'Yes'
    elif ((row['col 6'] >1) & (row['col 7'] >1) & (row[other_cols] <1)).all():
        row['category'] = 'Maybe'
    elif ((row['col 6'] <1) & (row['col 7']>1) & (row[other_cols] <1)).all():
        row['category'] = 'no'
    else:
        row['category'] = ''

df = df.apply(labels, axis=1)

What is the size of your dataset ?

I'm sorry i can not comment I am still new here