![]() ![]() The biggest challenge for beginner programmers is finding useful tutorials and resources. Trying to decide between R and Python? Check out this article to learn more about these two competing languages. Owing to the myriad of open-source data analysis libraries, developing fintech applications in Python doesn't take nearly as much time as it does with data analysis tools such as Microsoft Excel and R because you don't have to waste time writing code from scratch. Quick application development timeįintech and traditional finance areas prefer Python to other languages because of its quick application development time. And it's also very easy to set it up and jump right in. Unlike R and MATLAB, two other popular languages in science and engineering, Python has very simple syntax and coding rules, making it the perfect language for beginners. You don't need to have any programming experience to start performing data analysis in Python. Ease of use for beginnersįirst and foremost, Python is one of the easiest programming languages to learn. Not convinced that Python is the right language for you? Well, it's time to change your mind. In this article, we'll take a look at the benefits of learning Python and why financial experts should consider it, even if they have no prior programming experience. And the Popularity of Programming Language Index ranks Python as the most popular programming language in the world in October 2018. ![]() Currently, it's perching comfortably in the fourth spot after Java, C, and C++ on the Tiobe Index of Language Popularity. Python is quickly becoming the most popular coding language in the world. But what makes Python so special? And why is it a better language for data analysis compared to traditional software? An increasing number of fintech companies are using Python for data analysis. ![]()
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