Partitioning algorithms

random_partition(df, test_size, random_state=42, **kwargs)

Use random partitioning algorithm to generate training and evaluation subsets. Wrapper around the train_test_split function from scikit-learn.

Parameters:

Name	Type	Description	Default
df	DataFrame	DataFrame with the entities to partition	required
test_size	float	Proportion of entities to be allocated to test subset, defaults to 0.2	required
random_state	int	Seed for pseudo-random number generator algorithm, defaults to 42	42

Returns:

Type	Description
Tuple[pd.DataFrame, pd.DataFrame]	A tuple with the indexes of training and evaluation samples.