application_vnd.jupyter.stderr_output_1.png
from sklearn.model_selection import train_test_split

from sklearn.model_selection import train_test_split

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

nRowsRead = 1000
df = pd.read_csv('../input/cusersmarildownloadsgermancsv/german.csv', delimiter=';', encoding='ISO-8859-2', nrows=nRowsRead)
df.dataframeName = 'german.csv'
nRow, nCol = df.shape

y = df['Creditability']
X = df.iloc[:, :-1]

label = y
train = X
(print('train shape: ', train.shape), print('label shape: ', label.shape))

x_train, x_test, y_train, y_test = train_test_split(train, label, test_size=0.3, random_state=42)
print('x_train shape: ', x_train.shape)
print('y_train shape: ', y_train.shape)
print('x_test shape: ', x_test.shape)
print('y_test shape: ', y_test.shape)