This article will teach you how to use Python arrays. You'll learn how to define them as well as the various methods for performing operations on them.
The article discusses arrays created by importing the
array module in python.
An array is a concept that stores multiple items of the same type together and makes calculating the position of each element easier by simply adding an offset to the base value. Combining the arrays could save a significant amount of time by reducing the overall size of the code. It is used to keep several values in a single variable.
Arrays are a fundamental data structure that is used in almost all programming languages. They are containers in Python that can hold more than one item at a time.
They are an ordered collection of elements, with each value of the same data type. The most important thing to remember about Python arrays is that they can only contain a sequence of multiple items of the same type.
Lists are a common data structure in Python and an essential part of the language. Arrays and lists behave similarly. Lists, like arrays, are composed of an ordered sequence of elements. They are also mutable and not fixed in size, so they can grow and shrink throughout the program's lifespan. Items can be added and removed, making them extremely adaptable.
However, lists and arrays are not synonymous.
Lists contain items of various data types. This means that a list can contain integers, floating point numbers, strings, or any other Python data type. This is not true of arrays.
As stated in the preceding section, arrays only store items of the same single data type. There are arrays that only contain integers, arrays that only contain floating point numbers, and arrays that only contain any other Python data type you want to use.
Arrays are not included in the Python programming language, but lists are.
Because arrays are not a built-in data structure, they must be imported with the
array module before being used.
Arrays in the
array module are a thin wrapper around C arrays and are useful when working with homogeneous data.
They are also more compact than lists and take up less memory and space, making them more space efficient.
Because python array use less mermoy than python list they are much faster than list.
Python arrays are used when you need to use a large number of variables of the same type. It can also be used to store data collections. Arrays are especially useful when you need to process data in a dynamic manner.
In order to create python array you first need to import the
array module which has all the necassay fucntions:
import array as arr
python array now let's define python array. This can be done using syntax:
array_name = arr.array(typecode,[initializer])
array_name as the name suggest it will be the variable name of our python array
typecode specifies the types of elements that will be stored in the array.
Whether it's an array of integers, an array of floats, or any other Python data type.
Keep in mind that all elements must be of the same data type.
array_name = arr.array(typecode)
import array as arr num = arr.array("i",[1,2,3,5,6]) print(num) # Output: array('i', [1, 2, 3, 4, 5, 6]) float_num = arr.array('f',[1.2,2.3,4.5,6.7]) print(float_num) # Output: array('f',[1.2,2.3,4.5,6.7])
You can use the index operator  to reach a specific item in an array. The index must be an integer.
Time Complexity: 0(1) Space: 0(1)
import array as arr num_arr = arr.array("i",[1,2,3,4]) alpha_arr = arr.array("c",['a','b','c']) print(num_arr) #Output: 3 print(alpha_arr) #Output: a
insert() function can be used to add elements to the Array.
insert() is a function that is used to insert one or more data elements into an array.A new element can be added at the beginning, end, or any given index of the array depending on the requirement.
append() can also be used to append the value specified in its arguments to the end of an array.
import array as arr num_arr = arr.array("i",[1,2,3,4]) alpha_arr = arr.array("c",['a','b','c']) float_arr = arr.array("f",[1.2,2.4]) num_arr.insert(1,5) # Inserting at certain position print(num_arr) # Output: array('i', [1, 5, 2, 3, 4]) alpha_arr.append('d') # Inserting at the end of an array print(alpha_arr) #Output: array(['a', 'b', 'c', 'd']) float_arr.extend([3.5,6.6,8.9]) # Insering more the one element print(float_arr) # Output: array('f', [1.2,2.4,3.5,6.6,8.9])
Elements can be removed using the array's built-in
remove() function, however if the element doesn't already exist in the set, an error is raised.Because the
remove() method only removes one element at a time, iterators are used to remove a selection of elements.
remove() method in python array will only remove first occurrence of the searched element from array
pop() function, however, just delete the final element in the array by default. The
pop() function accepts the element's index as an input to delete the element from a specific location in the array.
import array as arr num_arr = arr.array("i",[1,2,3,4]) alpha_arr = arr.array("c",['a','b','c']) num_arr.remove(1) print(num_arr) #Output: array('i',[2,3,4]) alpha_arr.pop(2) print(alpha_arr) #Output: array('c',['a','b'])
Use the slicing operator, which is represented by the colon ":", to access a specific range of values inside the array.
By default, the counting starts at 0 when you use the slicing operator and only include one item. The first item is obtained, followed by items up to but excluding the index number you specify.
import array as arr num_arr = arr.array("i",[1,2,3,4,5,6]) print(num_arr[:4]) #Output: array('i',[1,2,3,4])
When you pass two numbers as parameters, you give a range of numbers.In this case, counting goes from the first number in the range to the second, but not beyond it:
import array as arr num_arr = arr.array("i",[1,2,3,4,5,6]) print(num_arr[2:4]) #Output: array('i',[3,4])
By specifying an element's position and giving it a new value, you can change its value.
Time Complexity: O(n) Space: O(1)
import array as arr num_arr = arr.array("i",[1,2,3,4,5,6]) alpha_arr = arr.array("c",['a','b','c']) num_arr = 53 alpha_arr = 'z' print(num_arr) # Output: array('i',[53,2,3,4,5,6]) print(alpha_arr) # Output: array('c',['a','b','z'])
We use the
index() method that is built into Python to search for a specific element in the array. The index of the first time a value mentioned in parameters appears is returned by this method.
Time Complexity: O(n) Space : O(1)
import array as arr num_arr = arr.array("i",[1,2,3,4,5,6]) alpha_arr = arr.array("c",['a','b','c']) print(num_arr.index(4)) # Output: 3 print(alpha_arr.index('c')) # Output: 2
Compared to arrays, lists are far more flexible. They can keep strings and other items of various data kinds. Additionally, you are far better off using something like NumPy if you need to perform mathematical computation on arrays and matrices.
What applications are there for arrays produced by the Python array module?
array.array module offers space-efficient storage of fundamental C-style data types, is really a thin shell on C arrays. Arrays can be faster and use less memory than lists if you need to allocate an array that won't change.