The shape of an array is the number of elements in each dimension.
NumPy arrays have an attribute called shape
that returns a tuple with each index having the number of corresponding elements.
Print the shape of a 2-D array:
import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
print(arr.shape)
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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.
Create an array with 5 dimensions using ndmin
using a vector with values 1,2,3,4 and verify that last dimension has value 4:
import numpy as np
arr = np.array([1, 2, 3, 4], ndmin=5)
print(arr)
print('shape of array :', arr.shape)
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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.
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