You can get the number of dimensions, shape [length of each dimension], and size [number of all elements] of the NumPy array with ndim
, shape
, and size
attributes of numpy.ndarray
. The built-in function len[]
returns the size of the first dimension.
- Number of dimensions of the NumPy array:
ndim
- Shape of the NumPy array:
shape
- Size of the NumPy array:
size
- Size of the first dimension of the NumPy array:
len[]
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]]]
Number of dimensions of the NumPy array: ndim
You can get the number of dimensions of the NumPy array as an integer value int
with the ndim
attribute of numpy.ndarray
.
print[a_1d.ndim]
# 1
print[type[a_1d.ndim]]
#
print[a_2d.ndim]
# 2
print[a_3d.ndim]
# 3
If you want to add a new dimension, use numpy.newaxis
or numpy.expand_dims[]
. See the following article for details.
- NumPy: Add new dimensions to ndarray [np.newaxis, np.expand_dims]
Shape of the NumPy array: shape
You can get the shape [= length of each dimension] of the NumPy array as a tuple with the shape
attribute of numpy.ndarray
.
Even in the case of a one-dimensional array, it is a tuple with one element instead of an integer value. Note that a tuple with one element has a trailing comma.
- A tuple with one element requires a comma in Python
print[a_1d.shape]
# [3,]
print[type[a_1d.shape]]
#
print[a_2d.shape]
# [3, 4]
print[a_3d.shape]
# [2, 3, 4]
For example, in the case of a two-dimensional array, shape
is [number of rows, number of columns]
. If you only want to get either the number of rows or columns, you can get each element of the tuple.
print[a_2d.shape[0]]
# 3
print[a_2d.shape[1]]
# 4
You can also unpack and assign them to different variables.
- Unpack a tuple and list in Python
row, col = a_2d.shape
print[row]
# 3
print[col]
# 4
Use reshape[]
to convert the shape. See the following article for details.
- NumPy: How to use reshape[] and the meaning of -1
Size of the NumPy array: size
You can get the size [= total number of elements] of
the NumPy array with the size
attribute of numpy.ndarray
.
print[a_1d.size]
# 3
print[type[a_1d.size]]
#
print[a_2d.size]
# 12
print[a_3d.size]
# 24
Size of the first dimension of the 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.
- How to use len[] in Python
For numpy.ndarray
, len[]
returns the size of the
first dimension. Equivalent to shape[0]
and 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