Filling NaN values

According to my knowledge, before filling nan values we have to check whether data is missing because of MCAR, MAR or MNAR and it depends on how features are correlated with each other and then make a decision, which one to apply. So, my question is, is it a good practice to check the dependency of features with chi square independence test. If not please suggest me, what techniques to use or apply to fill nan values.

I will be really appreciated, if you can reply me.

Thanks in advance.

Regards

Topic chi-square-test exploratory-factor-analysis missing-data correlation statistics

Category Data Science

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