How to Remove Rows with NaN Values in a Specific Pandas DataFrame Column?

Removing Rows with NaN Values from a Pandas DataFrame

A Pandas DataFrame can contain missing values represented as NaN. This may pose challenges when manipulating data. This article addresses how to efficiently remove rows where a specific column contains NaN values.

Problem:

Consider the following DataFrame where we want to keep only rows where the 'EPS' column is not NaN:

Solution:

To remove rows with NaN values in the 'EPS' column, we can utilize the notna() function. This function creates a boolean mask where True represents non-NaN values.

This operation will select only the rows where 'EPS' is not NaN, resulting in the following DataFrame:

By using the notna() function, we effectively filter out the rows containing NaN values in the specified column.

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