What is Python Used For?

Let's clarify first. This article is not about snakes, it's about coding in the fastest-growing programming language. That language happens to be named Python. In this article, we'll go through a number of inspiring ways to use Python.

So, what is Python used for?

Why Code in Python?

You have probably heard about many different programming languages, including JavaScript, Java, C++, Ruby, and others. Why should you choose Python? That's actually a very simple question. Python is the best programming language to start with because:

• Its simple syntax (structure) makes it very accessible to new learners.
• It is easy to read and understand because of its English-like commands.
• It is highly productive and usually requires fewer lines of code than other programming languages.
• It is very versatile and can be used for just about anything.
• Its many amazing libraries help programmers cut down on the initial development cycle.

I can continue like this, but I think you get the point.

I'm sure you understand what I did with this short Python code snippet. (From the Introduction to Python for Data Science course.)

Where Is Python Used?

Python is often recognized as the second most popular programming language after JavaScript. And its popularity is continuously growing.

There are many fields where Python already dominates – for example, developers working in machine learning and Artificial Intelligence use Python almost exclusively.

Python can apply to whatever you are interested in. For example, it is already being used in space projects, physical laboratories, astronomy, medicine, the music industry, and by movie studios, game developers, and smart-home developers.

This programming language is also very popular among tech leaders. Companies including Google, YouTube, Yahoo, Instagram, IBM, Uber, NASA, and Dropbox use Python.

What Can You Do with Python?

It's not super exciting just to know that other people can do cool stuff with Python. It's much more fun to do something yourself. So, let's see how YOU can use Python after just a little bit of learning:

• Automating routine tasks. Python is perfect for writing scripts (small programs that automate simple tasks). For example, you can use Python to automatically generate and update Excel spreadsheets, crawl websites and pull information from online sources, parse PDFs and Word documents, or send out email notifications.

• Analyzing data. Python is also very popular in data analytics. When you code your own programs instead of using spreadsheets or other tools, you have more freedom and greater possibilities. And no, you don't spend more time when using code. On the contrary, after you get some experience with Python – I'm talking about months, not years – you will be able to do the same analytics much faster.

As already mentioned, Python is a very productive language. Often, you'll need only a few lines of code to generate a table with detailed analytics. This is possible because of Python's great libraries. Beginners should start with the pandas library, which provides easy-to-use tools for manipulating tables and time series.

• Visualizing data. With Python, you can create visually appealing, professional, and informative visualizations. Because of Python's simplicity and productivity, you don't need to write lots of code to create complex visualizations.

  The Python community has introduced a number of libraries that make the graph-generation process very quick and comfortable. The standard matplotlib library is good and teaches the basics of data visualization with Python. However, plots generated with matplotlib are often not very aesthetically pleasing, or they may require more than a few lines of code to become visually appealing. The seaborn library is highly recommended for plots, as it will help you to create very professional and complex visualizations with just a line of code. There are other free data visualization libraries available that also facilitate the generation of attractive, web-ready plots.

• Getting insights from unstructured text. When data is in an unstructured text form, its usefulness is limited if you're working with standard data analytics tools. Python opens up lots of possibilities for working with unstructured text.

  Moreover, if the text data is not yet ready for analysis but resides on the web, you can use Python for web scraping. For example, you can easily analyze tweets with Python. It can be a beginner-level project ( e.g. counting the number of specific words mentioned in tweets) or more advanced tasks (e.g. building a classifier to detect anti-semitic tweets, as illustrated in Abraham Starosta's article. Please note that this article contains offensive language used in examples of racist tweets.)

If you are not impressed yet, here comes the coolest stuff you can do with Python:

• Build a blockchain. Yes, you can even build your own blockchain with Python. Furthermore, you don't need a strong understanding of blockchain before you start coding. Actually, the fastest way to learn how blockchain works can be through building one.
• Get into Artificial Intelligence. Are you interested in data science, machine learning, and AI? As I already mentioned earlier, Python is a dominant programming language in these areas. It can be used to predict exchange rates, build a facial recognition system, program a self-driving car, teach robots how to jump, create chatbots, enable machine translation, and more.

Yet again, Python has multiple open-source libraries and frameworks that make the implementation of these complicated tasks relatively easy and fast.

After you get some experience in Python, you might fall in love with this simple programming language. Then you might choose to dive deeper into the programming world and discover other uses of Python, including web development, mobile/desktop app development, game graphics, and much more. Actually, with Python, you can do just about anything.

How to Start Your Python Journey

Ok, now you know what Python is used for. Do you also feel like knowing this programming language is some kind of superpower? How do you join the superheroes' team?

If you have a little bit of time and lots of motivation, you can easily develop your Python skills through self-learning:

• Learn the Python basics with our courses Python Basics Part 1, Python Basics Part 2, and Python Basics Part 3.
• Learn the essential skills you'll need for data analytics and data science with our Introduction to Python for Data Science course.
• Learn how to process unstructured text with our Working with Strings in Python course.

All the above courses contain lots of interactive exercises – you'll start coding with Python right away, without any additional software or tutorials.