Answers for "train test split parameters"

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)

code for test and train split

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(
 X, y, test_size=0.33, random_state=42)

code for test and train split

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, 
	test_size = 0.33, random_state = 42)

train-test split code in pandas

df_permutated = df.sample(frac=1)

train_size = 0.8
train_end = int(len(df_permutated)*train_size)

df_train = df_permutated[:train_end]
df_test = df_permutated[train_end:]