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Filling missing values when using read_csv in Pandas
schedule Aug 12, 2023
Last updated local_offer
Tags Python●Pandas
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Consider the following my_data.txt file:
A,B3,5,6
The read_csv(~) method does not have a parameter to fill missing values, and hence you must call fillna(~) after reading the file:
df = pd.read_csv("my_data.txt").fillna(4)df
A B0 3 4.01 5 6.0
The reason column B is of type float is that read_csv(~) places a NaN in empty cells, and hence the column ends up being a float.
Related
Pandas | read_csv method
Reads a file, and parses its content into a DataFrame.
Pandas DataFrame | fillna method
Fills missing values (NaN) with a specified value or with a filling rule.
Published by Isshin Inada
Edited by 0 others
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