Array in Python

What is an Array in Python?

An array is a facts structure which could comprise or preserve a fixed wide variety of factors that are of the same Python facts type. An array consists of an element and an index. Index in an array is the location in which an detail resides. All factors have their respective indices. Index of an array continually begins with zero.

not like different programming languages, including Java, C, C++, and more, arrays are not that famous in Python because there are numerous iterable records kinds in Python which might be bendy and rapid to use which include Python lists. however, arrays in Python are nevertheless utilized in positive instances. in this module, we can research all approximately all of the crucial components of arrays in Python , from what they’re to whilst they’re used.

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

• Array Vs List in Python
• Creating an Array in Python
• Accessing a Python Array Element
• Basic Operations of Arrays in Python
• 2D Arrays in Python
• Dynamic Array in Python
• Array Input in Python
• Array Index in Python
• Array Programs in Python
• Python Array vs List

Array Vs List in Python

The simple distinction among arrays and lists in Python is that lists are bendy and might hold absolutely arbitrary records of any statistics type whilst arrays can best preserve statistics of the identical facts kind.

Arrays are taken into consideration useful in terms of memory performance, but they’re generally slower than lists. As noted above, the Python array module is not that popular to apply, but they do get used in positive instances such as:

Creating an Array in Python 

The array module supports numeric arrays in Python. So to create arrays in Python we need to import the array module. Below is the syntax to create an array. Now to understand how to declare an array in Python, let’s look at the following python array example:

from array import *

arraname = array(typecode, [Initializers])

here, type code is what we use to define the sort of price that is going to be saved inside the array. a number of the common type codes used within the creation of arrays in Python are described in the following table.

Type code	Data Type	Description
‘b’	signed char	Signed integer (1 byte)
‘B’	unsigned char	Unsigned integer (1 byte)
‘i’	int	Signed integer (2 bytes)
‘I’	unsigned int	Unsigned integer (2 bytes)
‘l’	long	Signed integer (4 bytes)
‘L’	unsigned long	Unsigned integer (4 bytes)
‘f’	float	Floating point (4 bytes)
‘d’	double	Floating point (8 bytes)

 

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

Example

import array

arr = array.array('i', [1, 2, 3, 4, 5])

print(arr)

Output

array(‘i’, [1, 2, 3, 4, 5])

Accessing a Python Array Element

we will get right of entry to the elements of an array in Python the use of the respective indices of these elements, as shown inside the following instance

Example

import array

# Create an array of integers

arr = array.array(‘i’, [10, 20, 30, 40, 50])

# Access elements using indices

print(“Element at index 0:”, arr[0])

print(“Element at index 2:”, arr[2])

print(“Element at index 4:”, arr[4])

Output

Element at index 0: 10

Element at index 2: 30

Element at index 4: 50

Basic Operations of Arrays in Python

1. Traverse of an Array in Python: Iterating among elements in an array is called traversing. we are able to without difficulty iterate through the elements of an array the usage of Python for loop as proven in the example underneath.

Example

import array

# Create an array of integers

arr = array.array(‘i’, [10, 20, 30, 40, 50])

# Traverse through the array elements

print(“Array elements:”)

for elem in arr:

print(elem)

Output

Array elements:

10

20

30

40

50

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

Example

import array

# Create an array of integers

arr = array.array(‘i’, [10, 20, 30, 40, 50])

# Insert a new element at index 2

arr.insert(2, 25)

# Print the updated array

print(“Updated array after insertion:”)

for elem in arr:

print(elem)

Output

Updated array after insertion:

10

20

25

30

40

50

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

import array

# Create an array of integers

arr = array.array(‘i’, [10, 20, 30, 40, 50])

# Delete the element at index 2

del arr[2]

# Print the updated array

print(“Updated array after deletion:”)

for elem in arr:

print(elem)

Output

Updated array after deletion:

10

20

40

50

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

Example

import array

# Create an array of integers

arr = array.array(‘i’, [10, 20, 30, 40, 50])

# Element to search

search_elem = 30

# Search for the element in the array

for i, elem in enumerate(arr):

if elem == search_elem:

print(f”Element {search_elem} found at index {i}”)

break

else:

print(f”Element {search_elem} not found in the array”)

Output

Element 30 found at index 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.

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

Example

import array

# Create an array of integers

arr = array.array(‘i’, [10, 20, 30, 40, 50])

# Update element at index 2

arr[2] = 35

# Print the updated array

print(“Updated array:”, arr)

Output

Updated array: array(‘i’, [10, 20, 35, 40, 50])

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.

Here’s an example of creating and accessing elements of a 2D array using lists of lists:

Example

# Creating a 2D array using lists of lists

matrix = [[1, 2, 3],

[4, 5, 6],

[7, 8, 9]]

# Accessing elements of the 2D array

print(matrix[0][0])

print(matrix[1][2])

print(matrix[2][1])

Output

1

6

8

We can also create 2D arrays using the array module in Python. Here’s an example:

Example

import array

# Creating a 2D array using the array module

matrix = [array.array(‘i’, [1, 2, 3]),

array.array(‘i’, [4, 5, 6]),

array.array(‘i’, [7, 8, 9])]

# Accessing elements of the 2D array

print(matrix[0][0])

print(matrix[1][2])

print(matrix[2][1])

Output

1

6

8

Dynamic Array in Python

A dynamic array is similar to an array, but the distinction is that its size can be dynamically changed at runtime. The programmer doesn’t need to specify how huge an array could be, ahead.

The elements of a regular array occupy a contiguous block of memory, and as soon as created, the dimensions can’t be changed. A dynamic array can, as soon as the array is filled, allocate a larger chew of memory, replica the contents from the original array to this new area, and keep to fill the available slots.

Example

from array import array

# Creating a dynamic array of integers

dynamic_array = array(‘i’)

# Appending elements to the dynamic array

dynamic_array.append(10)

dynamic_array.append(20)

dynamic_array.append(30)

# Printing the dynamic array

print(“Dynamic Array:”, dynamic_array)

# Accessing elements by index

print(“Element at index 0:”, dynamic_array[0])

print(“Element at index 1:”, dynamic_array[1])

# Updating an element

dynamic_array[1] = 25

print(“Updated dynamic array:”, dynamic_array)

# Deleting an element

del dynamic_array[1]

print(“Dynamic array after deletion:”, dynamic_array)

Output

Dynamic Array: array(‘i’, [10, 20, 30])

Element at index 0: 10

Element at index 1: 20

Updated dynamic array: array(‘i’, [10, 25, 30])

Dynamic array after deletion: array(‘i’, [10, 30])

Array Index in Python

The index of a value in an array is the position of the value in the array. Calculating array indices in Python starts at 0 and ends at n-1; where n is the total number of elements in the array.

Element	Index
10	0
20	1
30	2
40	3
50	4

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).

Example

# Define the array

friends = [“Ramkrishna”, “Vishnu”, “Shubham Kashyap”, “Jitendra Sharma”]

# Get the length of the array

length = len(friends)

# Print the length

print(“Length of the array:”, length)

Output

Length of the array: 4

Sum of Array in Python

Example

# Define the array

numbers = [1, 2, 3, 4, 5]

# Initialize a variable to store the sum

sum_of_numbers = 0

# Iterate through each element and accumulate their values

for num in numbers:

sum_of_numbers += num

# Print the sum

print(“Sum of the array:”, sum_of_numbers)

Output

Sum of the array: 15

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.

Example

# Input array

array = [3, 1, 4, 2, 5]

# Sort the array using sort() method

array.sort()

# Print the sorted array

print(“Sorted array using sort():”, array)

Output

Sorted array using sort(): [1, 2, 3, 4, 5]

Reverse Array in Python

Example

arr = [1, 2, 3, 4, 5]

reversed_arr = arr[::-1]

print(“Original array:”, arr)

print(“Reversed array:”, reversed_arr)

Output

Original array: [1, 2, 3, 4, 5]

Reversed array: [5, 4, 3, 2, 1]

Array Slice in Python

Example

import numpy as np

# Create a NumPy array

a = np.array([2, 4, 6])

# Create a slice of the array

b = a[0:2]

# Print the slice

print(b)

Output

[2 4]

List to Array in Python

Example

import numpy as np

# Create a list

my_list = [1, 2, 3, 4, 5]

# Convert the list to an array using numpy

my_array = np.array(my_list)

# Print the array

print(my_array)

print (type(my_array))

Output

[1 2 3 4 5]

<class ‘numpy.ndarray’>

Python Array vs List

 

Feature	Python List	Python Array (using array module)	Python Array (using numpy library)
Definition	Collection of elements, ordered sequence	Collection of elements, ordered sequence	Collection of elements, ordered sequence
Data Type	Supports heterogeneous data types	Supports homogeneous data types	Supports homogeneous data types
Memory Efficiency	Less memory efficient	More memory efficient	More memory efficient
Performance	Slower performance for large datasets	Faster performance for large datasets	Faster performance for large datasets
Flexibility	Flexible, can contain any data type	Less flexible, must be of the same type	Less flexible, must be of the same type
Access Time	Slower access time	Faster access time	Faster access time
Implementation	Built-in Python data structure	Provided by the array module	Provided by the numpy library