I have a pandas dataframe and I wish to divide it to 3 separate sets. I know that using train_test_split from sklearn.cross_validation, one can divide the data in two sets (train and test). However, I couldn’t find any solution about splitting the data into three sets. Preferably, I’d like to have the indices of the original data.
I know that a workaround would be to use train_test_split two times and somehow adjust the indices. But is there a more standard / built-in way to split the data into 3 sets instead of 2?