How to handle missing values in a dataset using imputation techniques like mean, median, and mode?

I’m working on a machine learning project, and I’m dealing with missing data in my dataset. I’ve heard that imputation using the mean/median/mode is a common technique to handle missing values. However, I’m not quite sure how to implement it in Python using Scikit-Learn.

Can anyone provide some guidance on how to impute missing values using mean/median/mode in Scikit-Learn? Also, are there any potential drawbacks or limitations to this technique that I should be aware of?

I’m using a dataset from Scikit-Learn, specifically the diabetes dataset. Here’s how I loaded the data:

Any help would be greatly appreciated! Thank you in advance.

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