Answers for "np.random.randn(...)"

np.random.randn()

>>> 2.5 * np.random.randn(2, 4) + 3
array([[-4.49401501,  4.00950034, -1.81814867,  7.29718677],  #random
       [ 0.39924804,  4.68456316,  4.99394529,  4.84057254]]) #random

np.random.rand()

# train test split
df = pd.read_csv('file_location')
mask = np.random.rand(len(df)) < 0.8
train  = df[mask]
test = df[~mask]