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NumPy: Get the number of dimensions, shape, and size of ndarray

Modified: | Tags: Python, NumPy

You can get the number of dimensions, shape (length of each dimension), and size (total number of elements) of a NumPy array (numpy.ndarray) using the ndim, shape, and size attributes. The built-in len() function returns the size of the first dimension.

Contents

Use the following one- to three-dimensional arrays as examples.

import numpy as np

a_1d = np.arange(3)
print(a_1d)
# [0 1 2]

a_2d = np.arange(12).reshape((3, 4))
print(a_2d)
# [[ 0  1  2  3]
#  [ 4  5  6  7]
#  [ 8  9 10 11]]

a_3d = np.arange(24).reshape((2, 3, 4))
print(a_3d)
# [[[ 0  1  2  3]
#   [ 4  5  6  7]
#   [ 8  9 10 11]]
# 
#  [[12 13 14 15]
#   [16 17 18 19]
#   [20 21 22 23]]]
source: numpy_ndim_shape_size.py

Number of dimensions of a NumPy array: ndim

You can get the number of dimensions of a NumPy array as an integer value with the ndim attribute of numpy.ndarray.

print(a_1d.ndim)
# 1

print(type(a_1d.ndim))
# <class 'int'>

print(a_2d.ndim)
# 2

print(a_3d.ndim)
# 3
source: numpy_ndim_shape_size.py

To add a new dimension, use numpy.newaxis or numpy.expand_dims(). See the following article for details.

Shape of a NumPy array: shape

You can get the shape, i.e., the length of each dimension, of a NumPy array as a tuple with the shape attribute of numpy.ndarray.

For a one-dimensional array, shape is still represented as a tuple with one element rather than an integer value. Note that a tuple with a single element has a trailing comma.

print(a_1d.shape)
# (3,)

print(type(a_1d.shape))
# <class 'tuple'>

print(a_2d.shape)
# (3, 4)

print(a_3d.shape)
# (2, 3, 4)
source: numpy_ndim_shape_size.py

For example, in the case of a two-dimensional array, shape represents (number of rows, number of columns). If you want to access either the number of rows or columns, you can retrieve each element of the tuple individually.

print(a_2d.shape[0])
# 3

print(a_2d.shape[1])
# 4
source: numpy_ndim_shape_size.py

You can also unpack the tuple and assign its elements to different variables.

row, col = a_2d.shape
print(row)
# 3

print(col)
# 4
source: numpy_ndim_shape_size.py

Use reshape() to convert the shape. See the following article for details.

Size of a NumPy array: size

You can get the size, i.e., the total number of elements, of a NumPy array with the size attribute of numpy.ndarray.

print(a_1d.size)
# 3

print(type(a_1d.size))
# <class 'int'>

print(a_2d.size)
# 12

print(a_3d.size)
# 24
source: numpy_ndim_shape_size.py

Size of the first dimension of a NumPy array: len()

len() is the Python built-in function that returns the number of elements in a list or the number of characters in a string.

For a numpy.ndarray, len() returns the size of the first dimension, which is equivalent to shape[0]. It is also equal to size only for one-dimensional arrays.

print(len(a_1d))
# 3

print(a_1d.shape[0])
# 3

print(a_1d.size)
# 3

print(len(a_2d))
# 3

print(a_2d.shape[0])
# 3

print(len(a_3d))
# 2

print(a_3d.shape[0])
# 2
source: numpy_ndim_shape_size.py

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