Python is a widely used programming language. It’s utilized in a variety of industries, including web development, data science, machine learning, and others. Arrays are a key data structure in Python. Arrays enable us to store and manipulate several values at the same time. In this Python tutorial, we’ll look at Python arrays, array operations, and other topics.
We’ll go over:
- What exactly are Python arrays?
- Create Python array
- Common array operations
- 2D Python arrays
- Conclusion and next actions
1) What exactly are Python arrays?
A Python array is a container that can hold several elements of the same data type in one single variable. This enables us to store several elements of the same type together. Arrays are highly common. Arrays are used to perform algorithms in most data structures, and they are widely employed in fields such as data science and machine learning. When we need to manipulate data of a specific type, we can use arrays. Because arrays can hold a huge number of elements, they are extremely handy when working with enormous volumes of data.
An array element is a piece of data that is stored in an array. As a result, the items “Spot,” “Max,” and “Sam” in our dogs array are elements. Each element’s numerical index location is referred to as the index. The index can be used to find and access elements.
What exactly are Python lists?
A Python list is not the same as a Python array, despite popular belief. A list is a collection of items that contain various types of data. This means that the first entry of the list can be a string, the second an integer, the third a list of strings, and so on. Lists are ordered, mutable, and their elements do not have to be distinct.
Using the NumPy Python library, we can transform our Python lists to arrays using one of the NumPy array functions:
2) Create Python array
Using the array module and the import array command, we can construct a new array. Consider the following Python program:
Now, let’s look at the many operations that may be performed on Python arrays.
3) Common array operations
There are several methods for adding elements to an array. Using the add() method, we may append elements to the end of the array:
To add an element to a certain index location within our array, we can use the insert() method. Here’s an illustration:
We can get to an array item by using its index number. For example, to obtain the value of the first array item, we can use the following code:
If we wish to access a certain element, we access the index number and set it equal to the modified value. As an example:
There are several methods for removing elements from an array. To delete an element at a certain place, we can use the pop() Python function. Assume we want to get rid of the last entry in our dogs array:
Find array length
Sort Python array
4) 2D Python arrays
A 2D array, often known as a two-dimensional array, is an array within an array. Each element in a typical array has an index. Each element in a 2D array has two indexes. Let’s look at an example. Assume we need to monitor how the temperature varies throughout the day. We’ll take four readings: one early in the morning, one late in the morning, one in the afternoon, and one in the evening. These temperatures can be stored in a 2D array.
We can do the same things with 2D arrays that we can with standard arrays.
5) Conclusion and next actions
Congratulations on making your first forays into Python arrays! Arrays are a popular and useful data structure. They have a wide range of applications and are frequently used to perform algorithms. There is still much to learn about the Python programming language. The following are some ideas for topics to explore next:
- a) Python dictionaries
- b) Python tuples
- c) Python strings
- d) Python syntax
Check out Hong Kong Coding Club’s Python for Programmers learning path to get started on these subjects and more. This curriculum will begin with the fundamentals of Python and progress to more sophisticated concepts such as modules and web-related activities. By the conclusion, you’ll have gained advanced knowledge that will allow you to confidently use Python in your next project.
Have fun learning!