What is an Array in Python 3?

An array is a data structure that can contain or hold a fixed number of elements that are of the same Python data type. An array is composed of an element and an index. Index in an array is the location where an element resides. All elements have their respective indices. Index of an array always starts with 0.
Unlike other programming languages, such as Java, C, C++, and more, arrays are not that popular in Python since there are many iterable data types in Python that are flexible and fast to use such as Python lists. However, arrays in Python 3 are still used in certain cases. In this module, we will learn all about all the important aspects of arrays in Python 3, from what they are to when they are used.

Following is the list of topics covered in this Python module.

So, without further delay, let’s get started.

Learn more about Python from this Python for Data Science Course to get ahead in your career!

Array Vs List in Python

The basic difference between arrays and lists in Python is that lists are flexible and can hold completely arbitrary data of any data type while arrays can only hold data of the same data type.

Certification in Full Stack Web Development

Arrays are considered useful in terms of memory efficiency, but they are usually slower than lists. As mentioned above, the Python array module is not that popular to use, but they do get used in certain cases such as:

Creating an Array in Python 3

The array module supports numeric arrays in Python 3. So, to create an array in Python 3, we will have to import the array module. Following is the syntax for creating an array. Now to understand how to declare array in Python, let us take a look at the python array example given below:

from array import *
arraname = array(typecode, [Initializers])

Here, typecode is what we use to define the type of the value that is going to be stored in the array. Some of the common typecodes used in the creation of arrays in Python are described in the following table.

Type Code C Type Python Data Type Minimum Size in Bytes
‘b’ signed char int 1
‘B’ unsigned char int 1
‘u’ Py_UNICODE Unicode character 2
‘h’ signed short int 2
‘H’ unsigned short int 2
‘i’ signed int int 2
‘I’ unsigned int int 2
‘l’ signed long int 4
‘L’ unsigned long int 4
‘f’ float float 4
‘d’ double float 8

Now, let’s create a Python array using the above-mentioned syntax.

Example:

import array as arr
a = arr.array(‘I’, [2,4,6,8])
print(a)

Output:
array(‘I’, [2, 4, 6, 8])

Interested in learning Python? Enroll in our Python Course in London now!

Become a Full Stack Web Developer

Accessing a Python Array Element

We can access the elements of an array in Python using the respective indices of those elements, as shown in the following example.

from array import*
array_1 = array(‘i’, [1,2,3,4,5])
print (array_1[0])
print (array_1[3])
1
4

The index of the array elements starts from 0. When we printed the value of array1[0], it displayed the first element.

Have a look at our blog on Data Structure with Python Cheat Sheet for the last-minute revision!

Basic Operations of Arrays in Python

Following are some of the basic operations supported by array module in Python:

  1. Traverse of an Array in Python: Iterating between elements in an array is known as traversing. We can easily iterate through the elements of an array using Python for loop as shown in the example below.

Example:

from array import *
array_1 = array(‘i’, [1,2,3,4,5])
for x in array_1:
print (x)

Output:
1
2
3
4
5
  1. Insertion of Elements in an Array in Python:Using this operation, we can add one or more elements to any given index.

Example:

from array import *
array_1 = array(‘i’, [1,2,3,4,5])
array_1.insert(1,6)
for x in array_1:
print (x)

Output:
1
6
2
3
4
5
  1. Deletion of Elements in an Array in Python:Using this operation, we can delete any element residing at a specified index. We can remove any element using the built in remove() method.

Example:

from array import *
array_1 = array(‘i’, [1,2,3,4,5])
array_1.remove(2)
For x in array_1:
print (x)

Output:
1
3
4
5
  1. Searching Elements in an Array in Python:Using this operation, we can search for an element by its index or its value.

Example:

from array import *
array_1 = array(‘i’, [1,2,3,4,5])
print (array_1.index(3))

Output:
2

In the above example, we have searched for the element using the built-in index() method. Using index(3) returned the output 2 which means that 3 is at the index number 2 in array_1. If the searched value is not present in the array, then the program will return an error.

Certification in Full Stack Web Development

  1. Updating Elements in an Array in Python:Using this operation, we can update an element at a given index.

Example:

from array import *
array_1 = array(‘i’, [1,2,3,4,5])
array_1[2] = 100
for x in array_1:
print(x)

Output:
1
2
100
4
5

In the above example, we have updated the already existing value at index 2 instead of adding a new element.

2D Arrays in Python

A 2D Array is basically an array of arrays. In a 2D array, the position of an element is referred to by two indices instead of just one. So it can be thought of as a table with rows and columns of data.

Student_marks = [[96, 91, 70, 78, 97], [80, 87, 65, 89, 85], [90, 93, 91, 90, 94], [57, 89, 82, 69, 60], [72, 85, 87, 90, 69]]  

print(Student_marks[1])
print(Student_marks[0])
print(Student_marks[2])
print(Student_marks[3][4])

The output will be
[80, 87, 65, 89, 85]
[96, 91, 70, 78, 97]
[90, 93, 91, 90, 94]
60

Dynamic Array in Python

A dynamic array is similar to an array, but the difference is that its size can be dynamically modified at runtime. The programmer doesn’t need to specify how large an array will be, beforehand.

The elements of a normal array occupy a contiguous block of memory, and once created, the size can’t be changed. A dynamic array can, once the array is filled, allocate a bigger chunk of memory, copy the contents from the original array to this new space, and continue to fill the available slots.

We use a built-in library called ctypes, to implement Dynamic Arrays in Python.

import ctypes 
class DynamicArray(object): 
def __init__(self): 
self.n = 0 
self.capacity = 1 
self.A = self.make_array(self.capacity) 
def __len__(self): 
return self.n 
def __getitem__(self, k): 
if not 0 <= k <self.n: 
return IndexError('K is out of bounds !') 
return self.A[k] 
def append(self, ele): 
if self.n == self.capacity: 
self._resize(2 * self.capacity) 
self.A[self.n] = ele 
self.n += 1
def insertAt(self,item,index): 
if index<0 or index>self.n: 
print("please enter appropriate index..") 
return
if self.n==self.capacity: 
self._resize(2*self.capacity) 
for i in range(self.n-1,index-1,-1): 
self.A[i+1]=self.A[i]
self.A[index]=item 
self.n+=1
def delete(self):
if self.n==0: 
print("Array is empty deletion not Possible") 
return
self.A[self.n-1]=0
self.n-=1
def removeAt(self,index):
if self.n==0: 
print("Array is empty deletion not Possible") 
return
if index<0 or index>=self.n: 
return IndexError("Index out of bound")
if index==self.n-1: 
self.A[index]=0
self.n-=1
return
for i in range(index,self.n-1): 
self.A[i]=self.A[i+1]
self.A[self.n-1]=0
self.n-=1
def _resize(self, new_cap):
B = self.make_array(new_cap)
for k in range(self.n):  
B[k] = self.A[k]
self.A = B 
self.capacity = new_cap
def make_array(self, new_cap):
return (new_cap * ctypes.py_object)()

Array Input in Python

string1 = input('Enter the elements separated by space ')
print("\n")
arr1 = string1.split()
print('Array = ', arr1)

The output will be
Enter the elements separated by space
7 8 9 10
Array =  ['7', '8', '9', '10']

Array Index in Python

The index of a value in an array is that value’s location within the array. Counting of array indices in Python starts at 0 and ends at n-1, where n is the total number of elements in the array.

arr1 = [2,5,7,8]
Element Index
2 0
5 1
7 2
8 3

Array Programs in Python

Let’s go through some common Array programs in Python.

Array Length in Python

Use the len() method to return the length of an array (the number of elements in an array).

cars = ["Ford", "Volvo", "BMW"]
x = len(cars)
print(x)

The output will be 3

Sum of Array in Python

string1 = input('Enter the elements separated by space ')
print("\n")
arr1 = string1.split()
print('Array = ', arr1)
for i in range(len(arr1)):
    arr1[i] = int(arr1[i])
print("Sum = ", sum(arr1))
Enter the elements separated by space 5 6 7 8
Array  ['5', '6', '7', '8']
Sum =  26

Sort Arrays in Python

Python provides a built-in function to sort arrays. The sort function can be used to sort the list in both ascending and descending order.

numbers = [1, 3, 4, 2]
numbers.sort()
print(numbers)

The output will be [1, 2, 3, 4]

Reverse Array in Python

arr = [1, 2, 3, 4, 5];
print("The array is:", arr)
arr2 = arr[: : -1]
print("The Array in reversed order:", arr2);

The output will be 
The array is: [1, 2, 3, 4, 5]
The Array in reversed order: [5, 4, 3, 2, 1]

Array Slice in Python

To pull out a section or slice of an array, the colon operator : is used when calling the index.

import numpy as np
a = np.array([2, 4, 6])
b = a[0:2]
print(b)

The output will be [2 4]

List to Array in Python

numpy.array() can be used to convert a list into an array.
import numpy as np
list1 = [2,4,6,8,10]
arr1 = np.array(list1)
print (arr1)
print (type(arr1))

The output will be 
[ 2  4  6  8 10]
<class 'numpy.ndarray'>

String to Array in Python

def Convert(string):
    a = list(string.split(" "))
    return a
str1 = "Intellipaat Python Tutorial"
print(Convert(str1))

The output will be ['Intellipaat', 'Python', 'Tutorial']

Python Array vs List

List Array
Lists are built-in and don’t have to be imported. We need to import Array before using them.
Lists can store different types of values Arrays only have same type of values
Lists are less compatible. Arrays are comparatively more compatible.
Direct Arithmetic Operations can’t be done on Lists Direct Arithmetic Operations can be done on Arrays
The entire list can be printed using explicit looping The entire array can be printed without using explicit looping
Lists are better for storing longer sequences of data items. Arrays are better for storing shorter sequences of data items.
Lists consume more memory. Arrays consume less memory.

Kick-start your career in Python with the perfect Python Course in New York now!

With this, we have come to the end of this module in Python Tutorial. We learnt about arrays in Python 3, how to define array in Python 3, accessing an Python Array, and different operations of Python array. Now, if you are interested in knowing why python is the most preferred language for data science, you can go through this blog on Python for data science

Further, check out our offers for Python training Course and also refer to the trending Python interview questions prepared by the industry experts.

Course Schedule

Name Date
Python Course 2021-12-04 2021-12-05
(Sat-Sun) Weekend batch
View Details
Python Course 2021-12-11 2021-12-12
(Sat-Sun) Weekend batch
View Details
Python Course 2021-12-18 2021-12-19
(Sat-Sun) Weekend batch
View Details

Leave a Reply

Your email address will not be published. Required fields are marked *