How to assign new data to validation

Hi all,

I’m working on tabular data at the moment
I was able to create the training data using TabularPandas function

to = TabularPandas(dfFULL, procs=[FillMissing, Categorify, Normalize],
                   cat_names = cat_names,
                   cont_names = cont_names,
                   y_names = dep_var)
dls = to.dataloaders(bs=3)

Now if we check the training data

And the valid data
image

This looks good to me, now I’m trying to add my own valid data, not using the split function
I tried 3 methods, non of them works?

Thanks you all your help

Why are you trying to do this? If you want to do predictions / add a test set you can use the DataLoaders .test_dl method. So:

learn.dls.test_dl(test_df)

If you’r doing it just for the sake of it, I guess you would create the two single ‘DataLoader’ objects with the appropriate sources and combine them to a ‘DataLoaders’ object (yes, those a two different things :smile:); the book should go into that, if I remember correctly. (edit: it does in chapter 19)

Thanks for your reply.
I just need to find a way to add valid data to the dataloaders.

Ah ok, I mistook that :slight_smile:. You do this by passing a splits parameter when creating the TabularPandas. Check the tutorial on tabular data here. Then dls.train holds the training and dls.valid the validation dataloader.

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