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Replacing NaN with blank string in Pandas DataFrame

schedule Aug 12, 2023
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To replace missing values (NaN) with a blank string in Pandas, use the DataFrame's fillna("") method.

Consider the following DataFrame with a missing value:

import numpy as np
df = pd.DataFrame({"A":[np.nan,"a"]})
df
A
0 NaN
1 a

To replace the NaN with a blank string:

df.fillna("")
A
0
1 a

Note that a new DataFrame is returned and so the original df is kept intact. To directly modify df, set inplace=True.

robocat
Published by Isshin Inada
Edited by 0 others
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