currently I just met a case and Give the context below:
I got a 1000 (rows) x 6 (columns) data set.
The variables are Date, Hour, average temperature, average humidity, the sum of water consumed in one hour, average ph value in the water.
How should I build a model to predict the daily water consumption in the next few days?
The given test data set only has the average temperature, average humidity and the average ph value in the water. So I suppose I should mainly focus on these three variables to build models right?
At the same time, since this data set contains date and hour as variables, there are some missing value or some time line there is not data be recorded, shall I try to replace them back with KNN or other methods?