Python Data Science NumPy Array Shape

How to Get the Shape of an Array?

NumPy arrays have an attribute called shape that returns a tuple with each index having the number of corresponding elements.

Example 1: Print the shape of a 2-D array.

Code

import numpy as np

arr = np.array([[11, 12, 13, 14], [15, 16, 17, 18]])

print(arr.shape)

the output will be

(2, 4)

Note: The example above returns (2, 4), which means that the array has 2 dimensions, where the first dimension has 2 elements and the second has 4.

Example 2: Create an array with 5 dimensions using ndmin using a vector with values 11,12,13,14 and verify that last dimension has value 4.

Code

import numpy as np

arr = np.array([11, 12, 13, 14], ndmin=5)

print(arr)
print('shape of array :', arr.shape)

the output will be

[[[[[11 12 13 14]]]]]
shape of array : (1, 1, 1, 1, 4)

What does the shape of tuple represent?

Integers at every index tells about the number of elements the corresponding dimension has.

In the example above at index-4 we have value 4, so we can say that 5th ( 4 + 1 th) dimension has 4 elements.