pandas split train test

from sklearn.model_selection import train_test_split


y = df.pop('output')
X = df

X_train,X_test,y_train,y_test = train_test_split(X.index,y,test_size=0.2)
X.iloc[X_train] # return dataframe train

from sklearn.model_selection import train_test_split

train, test = train_test_split(df, test_size=0.2)

train=df.sample(frac=0.8,random_state=200) #random state is a seed value
test=df.drop(train.index)