How can I use Pandas `fillna()` to fill missing values with corresponding values from another column?

Passing Columns as Arguments to Pandas fillna()

In pandas, the fillna() method is commonly used to replace missing values in a given column with a specified value or a calculated value. However, it is possible to go beyond simple value substitution and utilize the values from another entire column as the fill values.

Problem:

Consider a scenario where you have a dataset with missing values in one column, but you wish to fill these values with the corresponding values from another column. Looping through each row manually is considered inefficient, so a more elegant solution is sought.

Solution:

The fillna() method supports the functionality of passing an entire column as an argument to serve as the fill values. This allows you to perform the operation in a single step, leveraging pandas' vectorized operations for efficiency.

In this example, the 'Cat2' column is provided as the fill parameter. fillna() then uses the corresponding values in 'Cat2' to fill the missing values in 'Cat1' where the row indices match.

This approach provides a convenient and efficient way to populate missing values based on related data from another column in your dataset.

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