Python - Arrays

Array is a container which can hold a fix number of items and these items should be of the same type. Most of the data structures make use of arrays to implement their algorithms. Following are the important terms to understand the concept of Array.

Element− Each item stored in an array is called an element.
Index − Each location of an element in an array has a numerical index, which is used to identify the element.

Array Representation

Arrays can be declared in various ways in different languages. Below is an illustration.

As per the above illustration, following are the important points to be considered.

Index starts with 0.
Array length is 10 which means it can store 10 elements.
Each element can be accessed via its index. For example, we can fetch an element at index 6 as 9.

Basic Operations

Following are the basic operations supported by an array.

Traverse − Print all the array elements one by one.
Insertion − Adds an element at the given index.
Deletion − Deletes an element at the given index.
Search − Searches an element using the given index or by the value.
Update − Updates an element at the given index.

Arrays in Python

Python's standard data types list, tuple and string are sequences. A sequence object is an ordered collection of items. Each item is characterized by incrementing index starting with zero. Moreover, items in a sequence need not be of same type. In other words, a list or tuple may consist of items of different data type.

This feature is different from the concept of an array in C or C++. In C/C++, an array is also an indexed collection of items, but the items must be of similar data type. In C/C++, you have an array of integers or floats, or strings, but you cannot have an array with some elements of integer type and some of different type. A C/C++ array is therefore a homogenous collection of data types.

Python's standard library has array module. The array class in it allows you to construct an array of three basic types, integer, float and Unicode characters.

Syntax

The syntax of creating array is −

import array
obj = array.array(typecode[, initializer])

Parameters

typecode − The typecode character used to create the array.
initializer − array initialized from the optional value, which must be a list, a bytes-like object, or iterable over elements of the appropriate type.

Return type

The array() constructor returns an object of array.array class

Example

import array as arr

# creating an array with integer type
a = arr.array('i', [1, 2, 3])
print (type(a), a)

# creating an array with char type
a = arr.array('u', 'BAT')
print (type(a), a)

# creating an array with float type
a = arr.array('d', [1.1, 2.2, 3.3])
print (type(a), a)

It will produce the following output −

<class 'array.array'> array('i', [1, 2, 3])
<class 'array.array'> array('u', 'BAT')
<class 'array.array'> array('d', [1.1, 2.2, 3.3])

Arrays are sequence types and behave very much like lists, except that the type of objects stored in them is constrained.

Python array type is decided by a single character Typecode argument. The type codes and the intended data type of array is listed below −

typecode	Python data type	Byte size
'b'	signed integer	1
'B'	unsigned integer	1
'u'	Unicode character	2
'h'	signed integer	2
'H'	unsigned integer	2
'i'	signed integer	2
'I'	unsigned integer	2
'l'	signed integer	4
'L'	unsigned integer	4
'q'	signed integer	8
'Q'	unsigned integer	8
'f'	floating point	4
'd'	floating point	8

Before looking at various array operations lets create and print an array using python. The below code creates an array named array1.

from array import *
array1 = array('i', [10,20,30,40,50])
for x in array1:
 print(x)

Output

When we compile and execute the above program, it produces the following result −

Accessing Array Element

We can access each element of an array using the index of the element. The below code shows how

from array import *
array1 = array('i', [10,20,30,40,50])
print (array1[0])
print (array1[2])

Output

When we compile and execute the above program, it produces the following result − which shows the element is inserted at index position 1.

10
30

Insertion Operation

Insert operation is to insert one or more data elements into an array. Based on the requirement, a new element can be added at the beginning, end, or any given index of array.

Here, we add a data element at the middle of the array using the python in-built insert() method.

from array import *
array1 = array('i', [10,20,30,40,50])
array1.insert(1,60)
for x in array1:
 print(x)

Output

When we compile and execute the above program, it produces the following result which shows the element is inserted at index position 1.

Deletion Operation

Deletion refers to removing an existing element from the array and re-organizing all elements of an array.

Here, we remove a data element at the middle of the array using the python in-built remove() method.

from array import *
array1 = array('i', [10,20,30,40,50])
array1.remove(40)
for x in array1:
   print(x)

Output

When we compile and execute the above program, it produces the following result which shows the element is removed form the array.

Search Operation

You can perform a search for an array element based on its value or its index. Here, we search a data element using the python in-built index() method.

from array import *
array1 = array('i', [10,20,30,40,50])
print (array1.index(40))

Output

When we compile and execute the above program, it produces the following result which shows the index of the element. If the value is not present in the array then the program returns an error.

Update Operation

Update operation refers to updating an existing element from the array at a given index. Here, we simply reassign a new value to the desired index we want to update.

from array import *
array1 = array('i', [10,20,30,40,50])
array1[2] = 80
for x in array1:
   print(x)

Output

When we compile and execute the above program, it produces the following result which shows the new value at the index position 2.