how to split train and test data in python code example

Example 1: train test split pandas

from sklearn.model_selection import train_test_split

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

Example 2: 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 3: 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)

Example 4: 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

Example 5: sklearn train test split

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

Example 6: split data train, test by id python

train_inds, test_inds = next(GroupShuffleSplit(test_size=.20, n_splits=2, random_state = 7).split(df, groups=df['Group_Id']))

train = df.iloc[train_inds]
test = df.iloc[test_inds]