I used dropna() on Python but it didn't deleted any rows

Question

My DataFrame has two columns, both of which have NaN values. I need to delete the rows with NaN just on the column user_email.

However, I used df['user_email'] = df['user_email'].dropna() but it returned the exact same DataFrame, with all the NaN values on the second column intact.

How can I delete the rows with NaN on the second column?

https://stackoverflow.com/a/62444845/4909087 – cs95 Jul 03 '20 at 20:52 — cs95, Jul 03 '20 at 20:52

kait · Answer 1 · 2020-07-04T14:27:15.427

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You could use boolean indexing. This allows you to select rows based on a conditional statement (e.g., df.user_email.notna())

df = df[df.user_email.notna()]

edited Jul 04 '20 at 14:27

answered Jul 03 '20 at 20:01

kait

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Code only answers can generally be improved by adding some explanation of how and why they work. Without that explanation it looks like a low quality answer when it hits the review queues. – Jason Aller Jul 04 '20 at 05:14
Thanks for the feedback. I've updated my answer to include an explanation. – kait Jul 04 '20 at 14:28

score 0 · Answer 2 · edited Jul 03 '20 at 22:32

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You can use the subset keyword argument.

df = df.dropna(subset=['user_email'])

edited Jul 03 '20 at 22:32

Joooeey

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answered Jul 03 '20 at 20:02

pecey

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score 0 · Answer 3 · answered Jul 03 '20 at 20:10

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You may need inplace=True:

df.dropna(subset=['user_email'], inplace=True)

answered Jul 03 '20 at 20:10

naccode

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I used dropna() on Python but it didn't deleted any rows

3 Answers3