URL: https://www.progressiverobot.com/numpy-ones-in-python/

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()](/community/tutorials/numpy-zeros-in-python) function.

numpy.ones() function arguments

python illustration for: numpy.ones() function arguments

The numpy.ones() function syntax is:

				
					ones(shape, dtype=None, order='C')
				
			
  • The shape is an int or tuple of ints to define the size of the array. If we just specify an int variable, a one-dimensional array will be returned. For a tuple of ints, the array of given shape will be returned.
  • The dtype is an optional parameter with default value as a float. It's used to specify the data type of the array, for example, int.
  • The order defines the whether to store multi-dimensional array in row-major (C-style) or column-major (Fortran-style) order in memory.

Python numpy.ones() Examples

Let's look at some examples of creating arrays using the [numpy](/community/tutorials/python-numpy-tutorial) ones() function.

1. Creating one-dimensional array with ones

				
					import numpy as np

array_1d = np.ones(3)
print(array_1d)
				
			

Output:

				
					[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.

2. Creating Multi-dimensional array

				
					import numpy as np

array_2d = np.ones((2, 3))
print(array_2d)
				
			

Output:

				
					[[1. 1. 1.]
 [1. 1. 1.]]
				
			

3. NumPy ones array with int data type

				
					import numpy as np

array_2d_int = np.ones((2, 3), dtype=int)
print(array_2d_int)
				
			

Output:

				
					[[1 1 1]
 [1 1 1]]
				
			

4. NumPy Array with Tuple Data Type and Ones

We can specify the array elements as a [tuple](/community/tutorials/python-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)
				
			

Output:

				
					[[(1, 1.) (1, 1.)]
 [(1, 1.) (1, 1.)]]
[('x', '<i8'), ('y', '<f8')]
				
			

Reference: API Doc