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The other day I was exploring Kaggle and I found most of them don't use scikit-learn or any other library but instead they write these long python scripts.
For example, why they write a function for train/test split when you can just use the scikit-learn library which is hassle free
are there any advantages of not using any library and writing python code directly.
p.s: I'm a Data Science Beginner.
There can be multiple reasons to write a custom code instead of using a library.
For example - you can use the train_test_split from sklearn and that will generate a random split of data for training and validation. But let's assume you want to have a specific distribution of target in training and validation then you need to write a custom function to apply that specific distribution while preparing the training and validation
