# Converting the continuous numerical features into gaussian distribution and how to deal with NaN values after that?

I have a dataset in which there are few continuous numerical features that distribution over them is non gaussian and this means, skewness is nonzero (positive or negative).

I read that it is good to use a log transformation to bring them to a gaussian distribution before using the features. After doing this step, I see Nan values in the numerical data.

Is this expected?

If yes. How do you fix the Nan values (with mean or median replacement)?

To add on - when do you remove outliers? After gaussian distribution conversion or before that??

Any immediate help on this is much appreciated. Thank you.