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Treating missing values as empty strings rather than NaN for read_csv in Pandas

schedule Aug 11, 2023
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Consider the following my_data.txt file:

A,B
a,3
,4

To use an empty string instead of a NaN when parsing missing values:

df = pd.read_csv("my_data.txt", keep_default_na=False)
df
A B
0 a 3
1 4

Here, by setting keep_default_na=False, we prevent values like empty strings '' and "NaN" to be parsed as missing values.

robocat
Published by Isshin Inada
Edited by 0 others
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