Preprocessing-phase-of-Data

Data needs to be checked and preprocessed for missing values and categorization before training and testing.
Here, the data is to be checked for two things ie., whether they have missing or null values in them and categorising or removing particular features in them. For dealing with missing values, we are doing imputation. For categorising data we are using labelencoder or onehotencoder.