NumPy | Create array filled with all ones
Last Updated :
09 Feb, 2024
To create an array filled with all ones, given the shape and type of array we can use numpy.ones() method of NumPy library in Python.
Example:
Python3
import numpy as np
array = np.ones( 5 )
print (array)
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Output:
[1. 1. 1. 1. 1.]
Syntax
Syntax: np.ones(shape, dtype=None, order=’C’, *, like=None)
Parameters:
- shape : integer or sequence of integers
- order :
- C_contiguous or F_contiguous
- C-contiguous order in memory(last index varies the fastest)
- C order means that operating row-rise on the array will be slightly quicker
- FORTRAN-contiguous order in memory (first index varies the fastest).
- F order means that column-wise operations will be faster.
- dtype : [optional, float(byDefault)] Data type of returned array.
- like: [optional] allows you to create an array with the same shape and data type as another array-like object
More Examples
Let’s look at more example on how to create array with all ones with NumPy:
Example 1:
Python3
import numpy as geek
a = geek.ones( 3 , dtype = int )
print ( "Matrix a : \n" , a)
b = geek.ones([ 3 , 3 ], dtype = int )
print ( "\nMatrix b : \n" , b)
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Output:
Matrix a :
[1 1 1]
Matrix b :
[[1 1 1]
[1 1 1]
[1 1 1]]
Example 2:
Python3
import numpy as geek
c = geek.ones([ 5 , 3 ])
print ( "\nMatrix c : \n" , c)
d = geek.ones([ 5 , 2 ], dtype = float )
print ( "\nMatrix d : \n" , d)
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Output:
Matrix c :
[[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]]
Matrix d :
[[ 1. 1.]
[ 1. 1.]
[ 1. 1.]
[ 1. 1.]
[ 1. 1.]]
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