Question

Write a python code to divide the data set into two parts as 70 % for training and 30 % for testing

Answer 1

The simplest way would be to use train_test_split (sklearn module) and set shuffle to False. Shuffle takes priority over the random_state parameter. So, if you set shuffle as FALSE, the first n observations (i.e. 90 rows) in your dataset will go to the train dataset, and the last 10 rows would go to the test dataset. Code:

X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.10, shuffle=False)

If the partition is fixed, then you can use this code

train_pct_index = int(0.9 * len(X))

X_train, X_test = X[:train_pct_index], X[train_pct_index:]

y_train, y_test = y[:train_pct_index], y[train_pct_index:]