29 Mar NumPy Array Shape
In Python Numpy, the number of elements in each dimension of an array is called the shape. To get the shape of a Numpy array, use the numpy.shape attribute in Python.
In this lesson, we have covered the following examples:
- Check the shape of a Zero-Dimensional NumPy array
- Check the shape of a One-Dimensional NumPy array
- Check the shape of a Two-Dimensional NumPy array
- Check the shape of a Three-Dimensional NumPy array
Check the shape of a Zero-Dimensional NumPy array
Let us see an example and create a Zero-Dimensional NumPy array to check the shape:
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import numpy as np n = np.array(10) print(n) print(n.dim) print(n.shape) |
Output
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1 2 3 4 5 |
10 0 () |
Check the shape of a One-Dimensional NumPy array
Let us see an example and create a One-Dimensional NumPy array to check the shape:
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import numpy as np n = np.array([10, 20, 30]) print(n) print(n.ndim) print(n.shape) |
Output
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1 2 3 4 5 |
[10 20 30] 1 (3,) |
Checking the shape of a Two-Dimensional NumPy array
Let us see an example and create a Two-Dimensional NumPy array to check the shape:
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import numpy as np n = np.array([[1, 3, 5], [4, 8, 12]]) print(n) print(n.ndim) print(n.shape) |
Output
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1 2 3 4 5 6 |
[[ 1 3 5] [ 4 8 12]] 2 (2, 3) |
Check the shape of a Three-Dimensional NumPy array
Let us see an example and create a Three-Dimensional NumPy array to check the shape:
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import numpy as np n = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]) print(n) print(n.ndim) print(n.shape) |
Output
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[[[ 1 2 3] [ 4 5 6]] [[ 7 8 9] [10 11 12]]] 3 (2, 2, 3) |
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