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Python numpy.ones() function returns a new array of given shape and data type, where the element’s value is set to 1. This function is very similar to numpy zeros() function.
The numpy.ones() function syntax is:
ones(shape, dtype=None, order='C')
Let’s look at some examples of creating arrays using the numpy ones() function.
import numpy as np array_1d = np.ones(3) print(array_1d)
[1. 1. 1.]
Notice that the elements are having the default data type as the float. That’s why the ones are 1. in the array.
import numpy as np array_2d = np.ones((2, 3)) print(array_2d)
[[1. 1. 1.] [1. 1. 1.]]
import numpy as np array_2d_int = np.ones((2, 3), dtype=int) print(array_2d_int)
[[1 1 1] [1 1 1]]
We can specify the array elements as a tuple and specify their data types too.
import numpy as np array_mix_type = np.ones((2, 2), dtype=[('x', 'int'), ('y', 'float')]) print(array_mix_type) print(array_mix_type.dtype)
[[(1, 1.) (1, 1.)] [(1, 1.) (1, 1.)]] [('x', '<i8'), ('y', '<f8')]
Reference: API Doc
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