I am trying to use this dataset to build a predictive model.
hubway.db file contains 3 tables. One of which is is
bike_trips which has ~1 million entries. Some of my variables have high number of missing values:
Moreover these variables are fundamentally different. Gender can take 1 of 2 values but birthdate cannot, same with zip codes.
The 2 other tables contain
bike_station and weather data. The end goal is to find underlying patterns and ultimately build a model to predict trip duration and final destination (from a given starting station). However I first need to clean the data, hence my issue.
How am I supposed to either impute or generally deal with this?