Pandas - Blanking out values of one column if value of another column has a specific value

Question

I have the following DataFrame:

import pandas as pd

df = pd.DataFrame({'Status': ['','To Do', '','Completed', 'To Do', 'In Progress', 'Completed'], 
'Date': ['','9/1/2022','','12/5/2019','8/12/2020','4/19/2020','12/31/2018']})

I want to blank out the Date column for those rows where the Status is anything but "Completed". Using .loc, I am getting an error.

df = df.loc[df['Status'] != 'Completed', 'Date'] = ''

AttributeError: 'str' object has no attribute 'loc'

As specified by the answer bellow you don't need to assign the result of df.loc[] to df as it will modify your data frame in place. — Anoushiravan R
– Anoushiravan R, Commented Nov 6, 2022 at 23:08

Juliano Negri · Accepted Answer · 2022-11-06 22:55:25Z

3

There is a typo here:

df = df.loc[df['Status'] != 'Completed', 'Date'] = ''

Should be

df.loc[df['Status'] != 'Completed', 'Date'] = ''

answered Nov 6, 2022 at 22:55

Juliano Negri

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4 Comments

Michael Kessler Over a year ago

That's not a typo, I'm using df = to redefine the DataFrame based on the .loc. Regardless, this doesn't resolve the error.

Anoushiravan R Over a year ago

First code chunk can be removed as it could be mistaken as a valid answer.

user19077881 Over a year ago

An alternative expression which does the same thing is df['Date'][df['Status'] != 'Completed'] = ''

Michael Kessler Over a year ago

Oh I see that now. I was used to redefining df, like when I just wanted it to reflect a certain value in a column. But this worked, many thanks!

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