Resolving Data Imputation Issues in Pandas with numpy.where and pandas.where

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The Problem

Imagine you are trying to categorize the nutrition scores of various foods in a dataset. You want to create a new column in your DataFrame based on the values in the nutrition-score-fr_100g column, but your attempts are leading to unexpected results.

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Despite your best efforts, you found that all values in df['temp'] were set to 'e'. Even trying a for loop produced incorrect results, where all values were set to 'c'.

Let’s take a closer look at how you can solve this issue effectively.

Step-by-Step Code Implementation

Import the necessary library:

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Create your DataFrame:

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Initialize a default value in the temp column:

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Apply where conditions:

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Print your DataFrame:

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Expected Output

When you run the final print statement, you'll see a DataFrame with the temp column populated as expected:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

If you have further questions or need assistance, feel free to ask! Happy coding!