Mastering Python for Economics and Finance

No two programming languages are alike, even if they do share many qualities. Python, in particular, is easier for people to pick up than others like C++, as it is designed specifically with readability and simplicity in mind. While this means that Python is often the first programming language many beginners learn, it is still an extremely useful programming language that can be applied to many real-world problems. Economic and financial solutions are well within the capabilities of Python as a programming language, and here is some information to consider if you want to use it in this way.

Python is Open Source

If something is open source, then it can be tested and developed by anyone who wants to put the time and effort into doing so. The most commonly cited downside to open-source software is that anyone can figure out how it works and attempt to find a vulnerability. The flipside of this argument, however, is that there are at least just as many people — if not more — looking for vulnerabilities within Python who intend to improve the language as a whole. The majority of open-source software is free as well, making it far more accessible to people who want to program than, say, Matlab.

Python Has Lots of User-Friendly Documentation

While most programming languages can take advantage of coding techniques that are largely similar, the details will vary from language to language and it is likely that you will want to look online somewhere for help with learning the specifics. If you want to learn more about the Python zip function, for example, there is a wealth of explanations ranging from concise, information-dense explanations in the official Python documentation to more drawn-out explanations that go over specific details or advice for common applications. There is also a community of people who aim to help people learn about and use Python effectively, guaranteeing you the tools needed to master the programming language.

Python Is Capable of Providing Real Solutions

Despite Python’s apparent simplicity, it can be and is used in many important programs like those in finance. If you need to parse your financial data for use in an online portfolio rebalancing tool, you can use Python code for the task. Indeed, there are many financial professionals who use Python for their work. You don’t necessarily have to use all your own code, either, since you can import Python libraries to save you the time and headache of programming what are essentially the same functions as those that already exist and are ready to use.

Scheduling, emailing, and even machine learning libraries exist, which can be helpful in many financial applications. Python might not be the fastest of all the programming languages, however. The simplicity of Python does mean that it will run more slowly than other more complex programming languages as a result of how much is built into it natively, making it operate at a slightly higher level than many other languages. Still, the advantages simplicity brings should not be underestimated; how long a program takes to make and how well the programmers understand that program are both major parts of getting real work done, and languages like C++ require a lot of effort and knowledge to do the same things as Python, even if the runtime is slower.

Ultimately, for domestic applications like finance, Python is a practical language that is good at what it sets out to do and a fair bit more besides. Regardless of where you are with your programming skills, professionally, you might want to learn some Python even if you are already familiar with other more “professional” languages simply because it is so prevalent and easy to use.