np.ones() – Create 1D / 2D Numpy Array filled with ones (1’s)

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Create a 1D / 2D Numpy Arrays of zeros or ones

Numpy array of 1s: In this article, we will learn to create array of various shapes where all the values are initialized with 0 & 1.

numpy.zeros() :

Numpy array ones: A function is provided by Python’s numpy module i.e. numpy.zeros() which will create a numpy array of given shape and where all values are initialized with 0’s.

i.e.

numpy.zeros(shape, dtype=float, order='C')

Arguments:-

  • shape : It denotes shape of the numpy array. It may be single int or sequence of int.
  • dtype : It denotes data type of elements. Default value for dtype is float64.
  • order : It denotes the order in which data is stored in a multi-dimension array. It is of two types
  1. ‘F’: Data will be stored Row major order
  2. ‘C’: Data will be stored in Column major order. Default value of order is ‘C’.

Let’s see the below 4 different types implementation with code

Creating a flattened 1D numpy array filled with all zeros :

We can create a flattened numpy array with all values as ‘0’.

import numpy as sc
# create a 1D numpy array with values as 0
numarr = sc.zeros(5)
print('Contents of the Flattened Numpy Array : ')
print(numarr)

Output :
Contents of the Flattened Numpy Array :
[0. 0. 0. 0. 0.]

Creating a 2D numpy array with 4 rows & 3 columns, filled with 0’s :

We can create a 2D numpy array by passing (4,3) as argument in numpy.zeros() which will return all values as ‘0’.

import numpy as sc
# create a 2D numpy array with values as 0 
numarr = sc.zeros((4,3))
print('Contents of the 2D Numpy Array : ')
print(numarr)

Output :
Contents of the 2D Numpy Array :
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]

We know that default value of dtype is float64, let’s try to change the dtype to int64.

import numpy as sc
# create a 2D numpy array with values as 0 which are of int data type
numarr = sc.zeros((4,3), dtype=sc.int64)
print('Contents of the 2D Numpy Array : ')
print(numarr)

Output :
Contents of the 2D Numpy Array :
[[0 0 0]
 [0 0 0]
 [0 0 0]
 [0 0 0]]

numpy.ones() :

A function is provided by Python’s numpy module i.e. numpy.ones() which will create a numpy array of given shape and where all values are initialized with 1’s.

i.e.

numpy.ones(shape, dtype=float, order='C')

Arguments:-

  • shape : It denotes shape of the numpy array. It may be single int or sequence of int.
  • dtype : It denotes data type of elements. Default value for dtype is float64.
  • order : It denotes the order in which data is stored in a multi-dimension array. It is of two types
  1. ‘F’: Data will be stored Row major order
  2. ‘C’: Data will be stored in Column major order. Default value of order is ‘C’.

Creating a flattened 1D numpy array filled with all Ones :

We can make all values as 1 in a flattened array.

import numpy as sc
# create a flattened 1D numpy array of size 5 where all values are 1
numarr = sc.ones(5)
print('Contents of the Flattened Numpy Array : ')
print(numarr)

Output :
Contents of the Flattened Numpy Array :
[ 1.  1.  1.  1.  1.]

Creating a 2D numpy array with 3 rows & 3 columns, filled with 1’s  :

We can create a 2D numpy array by passing row and column as argument in numpy.ones() where all the values are 1.

import numpy as sc
# create a 2D numpy array with 3 rows & 4 columns with all values as 1
numarr = sc.ones((3,3))
print('Contents of the 2D Numpy Array : ')
print(numarr)
print('Data Type of the contents in  given Array : ',numarr.dtype)

Output :
Contents of the 2D Numpy Array :
[[1. 1. 1.]
 [1. 1. 1.]
 [1. 1. 1.]]
Data Type of the contents in  given Array :  float64

We know default type of dtype is float64, let’s try to change it to int64.

import numpy as sc
# create a 2D numpy array with values as 1 which are of int data type
numarr = sc.ones((4,3), dtype=sc.int64)
print('Contents of the 2D Numpy Array : ')
print(numarr)

Output :
Contents of the 2D Numpy Array :
[[1 1 1]
 [1 1 1]
 [1 1 1]
 [1 1 1]]