PYTHON

train test split python

from sklearn.model_selection import train_test_split
				
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)

train test split python

import numpy as np
from sklearn.model_selection import train_test_split

# Data example 
X, y = np.arange(10).reshape((5, 2)), range(5)

# Split data into train and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)

python train test val split

#You could just use sklearn.model_selection.train_test_split twice. First to split to train,
#test and then split train again into validation and train.
#Something like this:
X_train, X_test, y_train, y_test 
    = train_test_split(X, y, test_size=0.2, random_state=1)

X_train, X_val, y_train, y_val 
	= train_test_split(X_train, y_train, test_size=0.25, random_state=1) # 0.25 x 0.8 = 0.2