Python :How to use loc with multiple columns in pandas

Question

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'

akuiper · Accepted Answer · 2021-06-13 17:52:34Z

3

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.

answered Jun 13, 2021 at 17:52

akuiper

216k33 gold badges362 silver badges379 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

ah bon · Accepted Answer · 2022-10-29 10:43:02Z

1

You have to use () each condition,

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

edited Oct 29, 2022 at 10:43

ah bon

10.1k22 gold badges82 silver badges184 bronze badges

answered Jun 13, 2021 at 17:55

Handri Mauludin Maulana

752 silver badges14 bronze badges

Collectives™ on Stack Overflow

Python :How to use loc with multiple columns in pandas

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related