NumPy: numpy.ones() function
numpy.ones() function
The numpy.ones() function is used to create a new array of given shape and type, filled with ones. The ones() function is useful in situations where we need to create an array of ones with a specific shape and data type, for example in matrix operations or in initializing an array with default values.
Syntax:
numpy.ones(shape, dtype=None, order='C')

Parameters:
Name | Description | Required / Optional |
---|---|---|
shape | Shape of the new array, e.g., (2, 3) or 2. | Required |
dtype | The desired data-type for the array, e.g., numpy.int8. Default is numpy.float64. | optional |
order | Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory | optional |
Return value:
[ndarray] Array of ones with the given shape, dtype, and order.
Example-1: Create arrays of ones with NumPy's ones() function
>>> import numpy as np
>>> np.ones(7)
array([ 1., 1., 1., 1., 1., 1., 1.])
>>> np.ones((2, 1))
array([[ 1.],
[ 1.]])
>>> np.ones(7,)
array([ 1., 1., 1., 1., 1., 1., 1.])
>>> x = (2, 3)
>>> np.ones(x)
array([[ 1., 1., 1.],
[ 1., 1., 1.]])
>>>
In the above code:
np.ones(7): This creates a 1-dimensional array of length 7 with all elements set to 1.
np.ones((2, 1)): This creates a 2-dimensional array with 2 rows and 1 column, with all elements set to 1.
np.ones(7,): This is equivalent to np.ones(7) and creates a 1-dimensional array of length 7 with all elements set to 1.
x = (2, 3) and np.ones(x): This creates a 2-dimensional array with 2 rows and 3 columns, with all elements set to 1.
Pictorial Presentation:


Example: Createng a 3D array with ones along a specified axis
Code:
import numpy as np
# Create a 3D array with ones along the second axis
arr = np.ones((2, 3, 4), dtype=int)
arr[:, 1, :] = 2
print(arr)
Output:
[[[1 1 1 1] [2 2 2 2] [1 1 1 1]] [[1 1 1 1] [2 2 2 2] [1 1 1 1]]]
In the above example, we create a 3D array with dimensions (2, 3, 4) using np.ones() function. We then set the values of the second axis to 2, resulting in a 3D array with ones along the first and third axis and 2's along the second axis.
Example: Create a 2D array with a custom data type and byte order
Code:
import numpy as np
# Create a 2D array of unsigned 16-bit integers with little-endian byte order
nums = np.ones((2, 3), dtype=np.dtype('<u2'))
print(nums)
Output:
[[1 1 1] [1 1 1]]
In the above example, we create a 2D array with dimensions (2, 3) using np.ones() function. We specify the data type using np.dtype() function, which represents unsigned 16-bit integers with little-endian byte order. The resulting array has values of 1 and the specified data type and byte order.
Python - NumPy Code Editor:
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