How to retain Scikit-learn OneHotEncoding from model generation to use on new data?
I think you are using fit_transform on both training and test dataset, which is not the right approach because the encoding schema has to be consistent on both the dataset for the model to understand the information from the features. 
The correct way is do 

fit_transform on training data
transform on test data

By doing this way, you will get consistent number of columns.
I'm using OneHotEncoding to generate dummies for a classification problem. When used on the training data, I get ~300 dummy columns, which is fine. However, when I input new data (which is fewer rows), the OneHotEncoding only generates ~250 dummies, which isn't surprising considering the smaller dataset, but then I can't use the new data with the model because the features don't align.
Is there a way to retain the OneHotEncoding schema to use on new incoming data?