fillna() in Pandas

The fillna() method in Pandas replaces columns (one or multiple) that contain NA, NaN, and None with a specified value, such as an empty string "".

main.py

import pandas as pd

# 👇️ create a pandas dataframe
df = pd.read_csv("example_data.csv")

# Replace all NA, NaN, and None with an empty string ""
df_clean = df.fillna("")

Syntax

dataframe.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None)

Parameters

Paramter	Value	Description
value	Number String Dictionary Series DataFrame	Required. Specifies the value to replace the `NULL` values with. This can also be values for the entire row or column.
method	`backfill` `bfill` `pad` `ffill</div> <div>`None	Optional, default `None`. Specifies the method to use when replacing
axis	`0` `1` `index` `columns`	Optional, default `0`. The axis to fill the `NULL` values along
inplace	`True` `False`	Optional, default `False`. If `True`: the replacing is done on the current DataFrame. If `False`: returns a copy where the replacing is done.
limit	Number `None`	Optional, default `None`. Specifies the maximum number of `NULL` values to fill (if method is specified)
downcase	Dictionary `None`	Optional, a dictionary of values to fill for specific data types

Conclusion

The fillna() method in Pandas replaces columns (one or multiple) that contain NA, NaN, and None with a specified value, such as an empty string "".

fillna() in Pandas

fillna() in Pandas

Syntax

Parameters

Conclusion

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