Why df.fillna is Not Replacing NaN Values with Data from Another DataFrame

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Disclaimer/Disclosure: Some of the content was synthetically produced using various Generative AI (artificial intelligence) tools; so, there may be inaccuracies or misleading information present in the video. Please consider this before relying on the content to make any decisions or take any actions etc. If you still have any concerns, please feel free to write them in a comment. Thank you.
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Mismatched DataFrame Indexes

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In this example, df1 and df2 have different indexes, so the fillna method does not find matching indices to pull data from df2.

Solution: Ensure both DataFrames have matching indexes.

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Column Name Inconsistencies

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The fillna operation fails to find matching columns.

Solution: Ensure that the column names in both DataFrames match.

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Alternative Methods to Fill Missing Values

If you still encounter issues, consider these alternative methods:

Using a Dictionary

You can convert one DataFrame to a dictionary and use it to fill the missing values.

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Using Update Method

The update method can update missing elements with non-NaN values from another DataFrame.

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Conclusion