NumPy | Create array filled with all ones
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.]]
Last Updated :
09 Feb, 2024
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