How To Handle Missing Values in Categorical Features | Filling Missing Categorical values in Pandas

How to handle missing data machine learning
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Missing Data is something no Data scientist want to come across but there are many reasons for Data to be missing. E.g lets say the customer does not want to give data or we can say that who ever is collecting the data might have missed it or we can say in verbal communication a lot of data is missed. So in today's video we will see how we can impute the missing data .
This particular technique mode or frequent category imputation or simple imputation is very very easy ,extremely useful and takes a lot less time and data analysis.
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Видео How To Handle Missing Values in Categorical Features | Filling Missing Categorical values in Pandas канала Coder's Digest