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
y = df['target'].values
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)
Example 3: sklearn split train test
import numpy as np
from sklearn.model_selection import train_test_split
X, y = np.arange(10).reshape((5, 2)), range(5)
X_train, X_test, y_train, y_test = train_test_split(
X, y, test_size=0.33, random_state=42)
X_train
y_train
X_test
y_test
Example 4: pandas split dataframe to train and test
train=df.sample(frac=0.8,random_state=200)
test=df.drop(train.index)
Example 5: 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]
Example 6: how to distribute a dataset in train and test using scikit
from sklearn.model_selection import train_test_split
xTrain, xTest, yTrain, yTest = train_test_split(x, y, test_size = 0.2, random_state = 0)