StepsForDataCleaning.txt

DATA CLEANING
1) Replace -unknown- values with NaNs - Adding other and unknown in gender to other.
2) Age values are uncleaned - added value nan for people with age<10 or greater than 100. Calculated the age if the year is given.
-Removed the nans(we dont need data for age<10 or reater than 100)
3) Remove dimensions that are redundant(be careful to not remove a feature if there isnt any good reason behind  as that is data loss)
4) Increase the cardinality by splitting date_account_created and timestamp_first_active
into day, is_weekday, month, year
5) In session file there are some redundancy which we can remove like action, action_type, action_detail
6) OHE for categorical variables
7) Extract information from dates
8) Session dataset is less than the user dataset- so need to decide how to merge and also do we need session dataset at all? We anyway don’t have it for all users.
9)