how to split data to train and test with sklearn code example

Example 1: train test split sklearn

from sklearn.model_selection import train_test_split

X = df.drop(['target'],axis=1).values   # independant features
y = df['target'].values					# dependant variable

# Choose your test size to split between training and testing sets:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)

Example 2: train dev test split sklearn

train, validate, test = np.split(df.sample(frac=1), [int(.6*len(df)), int(.8*len(df))])