Python Pandas replace() not working

Question

I have some fields that have some junk in them from an upstream process. I'm trying to delete '\r\nName: hwowneremail, dtype: object' from a column that has this junk appended to an email address.

report_df['Owner'].replace('\r\nName: hwowneremail, dtype: object',inplace=True)
report_df['Owner'][26]

Output:

'   [email protected]\r\nName: hwowneremail, dtype: object'

I've also tried the following variants w/o success:

replace('Name: hwowneremail, dtype: object', inplace=True)

replace('\\r\\nName: hwowneremail, dtype: object', inplace=True

replace(r'\r\nName: hwowneremail, dtype: object', inplace=True)

replace('\r\nName: hwowneremail, dtype: object', "", inplace=True)

replace(to_value='\r\nName: hwowneremail, dtype: object', value=' ',inplace=True)

replace('\\r\\nName: hwowneremail, dtype: object',regex=True,inplace=True)

Thanks in advance for your insight!

L33T · Accepted Answer · 2016-03-03 19:10:29Z

4

As far as I remember, Python Pandas was changed a little bit in replace. You should try passing over a regex keyword argument.

Like so;

report_df['Owner'].replace({'\r\nName: hwowneremail, dtype: object':''},regex=True)

answered Mar 3, 2016 at 19:10

L33T

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2 Comments

Harvey Summers Over a year ago

That did it! Interestingly I started with that, but didn't have regex=True. I added inplace=True and problem solved. Thank You!

Alex Petralia Over a year ago

This stumped me for a while as well. regex=True is now required, apparently.

MaxU - stand with Ukraine · Accepted Answer · 2016-03-03 19:16:40Z

0

alternatively you can use:

report_df.Owner.str.replace(r'\r\n.*', '')

edited Mar 3, 2016 at 19:16

answered Mar 3, 2016 at 19:09

MaxU - stand with Ukraine

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Comments

AS Mackay · Accepted Answer · 2019-07-31 16:51:11Z

0

Or sometimes just make sure there is no white space before or after the character/str you are looking for(expl. ? ):

df.replace(r'\s*\?\s*', np.nan, regex=True)

or just make sure you specify you are looking for a string:

df.replace(r'\?', np.nan, regex=True)

and for both cases: and don`t forget

regex=True

edited Jul 31, 2019 at 16:51

AS Mackay

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answered Jul 31, 2019 at 16:34

Daniel Moraite

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