Pandas Replace NaN with blank/empty string – Stack Overflow

If you are reading the dataframe from a file (say CSV or Excel) then use :

df.read_csv(path , na_filter=False)

df.read_excel(path , na_filter=False)

This will automatically consider the empty fields as empty strings ''

If you already have the dataframe

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

df = df.fillna('')

answered Jul 19, 2017 at 15:16

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na_filter is not available on read_excel() pandas.pydata.org/pandas-docs/stable/…

– Marjorie Roswell

CommentedJul 31, 2017 at 2:39
i have used it in my application . It does exist but for some reason , they haven’t given this argument in the docs . It works nice for me though without errors.

– Natesh bhat

CommentedAug 1, 2017 at 6:40
It works, i’m using it in parse xl.parse('sheet_name', na_filter=False)

– Dmitrii

CommentedNov 22, 2017 at 17:33
I trawled through so many different threads for a fix and this is the only one that worked for my CSV file. Thanks.

– Deskjokey

CommentedJan 9, 2022 at 9:52