Do we have to remove target variable from data in Scikit-learn's linearmodel.fit()?
To my understand, you shouldn't predict tomorrow's weather by tomorrow's weather. If you already know what's the correct value, it is pointless to predict one. 
However, you don't need to remove target variable in your dataset either, just don't include it in your X-axis. 
What we are trying to do with a predictive model? Based on past records(both x and y), we trained our model to find their relationships. In future, we may no longer have y, but we still have x in our hands, assuming their relationship doesn't change, we predict what is the y for the future.
Scikit-learn's documentation says there are two arguments to the function: X(data) and y(Target Values). Do we remove the target variable from our data and provide it separately as y? Or do we keep target variable in X and also provide it separately as y? I have come across both approaches and was wondering which was correct.