NumPy: Creating Arrays

Creating Arrays

• Array is a collection of elements. The array can be created using the function np.array ().

For example

In [1]:

import numpy as np

arr = np.array([10,20,30,40])

print(arr)

Output

[10 20 30 40]

Creating array using built‒in function

We can create arrays using built‒in functions –

1) Using np.zeros()

The np.zeros function creates an array which is filled with zeros. For example ‒

In [2]: import numpy as np

arr = np.zeros(5)

print(arr)

Output

 [0.0.0.0.0.]

2) Using np.ones()

The np.ones() function creates array of all ones. For example

import numpy as np

arr = np.ones(5)

print(arr)

Output

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

3) Using np.arange()

Using np.arange() function we can create an array with the values of specific interval.

Syntax

np.arange(start, stop, step)

For example ‒ to create an array of 1 to 10 we use following command

import numpy as np

arr = np.arange(1,10,2)

print(arr)

Output

[1 3 5 7 9]

4) Using np.linspace()

This function divides range into equal parts

In [4]:

import numpy as np

arr = np.linspace(0,1,3)

print(arr)

Output

[0. 0.5 1. ]

Creating Multi‒dimensional Arrays

• Using NumPy we can create n‒dimensional arrays.

create of two‒D arrays

We can create a two‒dimensional array using the function np.array( ) For example ‒ In order to create 3 by 2 array (i.e. 3 rows and 2 columns) we use lists as follows ‒

In [8]: import numpy as np

a = np.array([[1,2],

[3,4],

[5,6]])

print(a)

[[12]

[34]

[5 6]]

Note that we have created an array of three rows and two columns using above numpy code.

Creation of three‒D array

We can create three dimensional array using the slices of a two dimensional array. For example ‒ In the following illustration we have created two slices of 2 by 3 array.

In [10]: import numpy as np

a = np.array([[[1,2,3], [4,5,6]], [[10,20,30],[40,50,60]]])

print(a)

[[[ 1 2 3]

  [ 4 5 6]]

[[10 20 30]

 [40 50 60]]]

Similarly we can create an array of two slices of 3 by 3 matrix.

In [13]: import numpy as np

a = np.array([[[1,2,3],[4,5,6], [7,8,9]], [[10,20,30], [40, 50, 60], [70,80,90]]])

print(a)

[[[ 1 2 3]

  [ 4 5 61

  [ 7 8 9]]

[[10 20 30]

 [40 50 60]

 [70 80 90]]]

We can find the array dimensions using the command ndim. The illustration is as follows‒

In [14]: print(a.ndim)

3

Creation of n‒dimensional array

In NumPy we can use np.full() to create a multidimensional array with a specified value.

In [20]: import numpy as np

a = np.full((3,3,3),10)

print(a)

[[[10 10 10]

  [10 10 10]

  [10 10 10]]

[[10 10 10]

 [10 10 10]

 [10 10 10]]

[[10 10 10]

 [10 10 10]

 [10 10 10]]]

In above code, we have created 3 slices of 3 by 3 array which is initialized with the value 10.