I have been using one-hot encoding for a while now in all pre-processing data pipelines that I have had.
But I have run into an issue now that I am trying to pre-process new data automatically with flask server running a model.
TLDR of what I am trying to do is to search new data for a specific Date, region and type and run a .predict on it.
The problem arises as after I search for a specific data point I have to change the columns from objects to the one-hot encoded ones.
My question is, how do I know which column is for which category inside a feature? As I have around 240 columns after one hot encoding.