CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
crawler
crawler

Reputation: 43

Python :How to use loc with multiple columns in pandas

I have a df with multiple columns. We need to check if any of the columns has a value 0; if 0 is there we have to add new column with tag.

I tried this :

df.loc[df['maths'] == '0', 'mark_student'] = 'fail'

This it working for single column, but when I tried it for multiple columns, it's failing

Like this :

df.loc[df['maths','chemistry'] == '0', 'mark_student'] = 'fail'

df.loc[df[['maths','chemistry']] == '0', 'mark_student'] = 'fail'

Upvotes: 1

Views: 3276

Answers (2)

Handri Mauludin Maulana
Handri Mauludin Maulana

Reputation: 75

You have to use () each condition,

df.loc[(df['maths'] == 0) & (df['chemistry'] ==  0) & (df['mark_student'] == 'fail')

Upvotes: 1

akuiper
akuiper

Reputation: 214957

df[['maths','chemistry']] == '0' returns a data frame, which can't be directly used as boolean index at row level. You can use .any(1) to reduce it to a Series and then use it with .loc:

df.loc[(df[['maths','chemistry']] == '0').any(1), 'mark_student'] = 'fail'

Should work.

Upvotes: 3

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