Cross Validation (sklearn train test split) - ValueError: not enough values to unpack I have written this code and getting error:

from sklearn.model_selection import train_test_split
X0 = pd.read_csv('C:/Users/Desktop/Dataset for Experiment - 2019/ANFIS modeling data/china_data.csv')
train_test_split. X0 = X0.drop(columns = ['EFFORT'], axis = 1)
X_train, X_test, y_train, y_test = train_test_split(X0, test_size=0.8)


The error which is showing for this code 

X_train, X_test, y_train, y_test = train_test_split(X0, test_size=0.8)



  ValueError: not enough values to unpack (expected 4, got 2)


I tried many times to remove this error but it is still persistent. Can anybody explain to me why I am getting this error &amp; how can I remove this error?
Sklearn expects to get X and y in train_test_split().

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)


You only parse X.

See the docs: https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html