What is the difference between single and double bracket Numpy array?

Question

import numpy as np
a=np.random.randn(1, 2)
b=np.zeros((1,2))
print("Data type of A: ",type(a))
print("Data type of A: ",type(b))

Output:

Data type of A:  <class 'numpy.ndarray'>
Data type of A:  <class 'numpy.ndarray'>

In np.zeros(), to declare an array we give the input in 2 brackets whereas in np.random.radn(), we give it in 1 bracket?

Is there any specific reason for the syntax,as both of them are of same data type but follow a different syntax?

Answer 1

In an effort to ease the transition for Matlab users to NumPy, some convenience functions like randn were built which use the same call signature as their Matlab equivalents.

The more NumPy-centric (as opposed to Matlab-centric) NumPy functions (such as np.zeros) expect the size (or shape) to be a tuple. This allows other parameters like dtype and order to be passed to the function as well. The Matlab-centric functions assume all the arguments are part of the size.

np.random.randn is one of NumPy's Matlab-centric convenience functions, modeled after Matlab's randn. The more NumPy-centric alternative to np.random.randn is np.random.standard_normal.