Python vs. R: Which One Works for Online Casinos?

It’s no secret that data analysis has slowly turned into a central part of building web applications. Businesses want to know what attracts clients and why they prefer some options over others. And online casino sites, for example, are collecting and analyzing data to understand user behavior.

However, there is a hot debate going around on whether to use R or Python to create AI applications. Both languages are free to use, open source, and come with huge user communities. And that’s great, but which one is better for an online casino?

Python Programming Language

Python has over 5,000 libraries for data collection, wrangling, manipulation and Machine learning. And according to experienced developers, it’s one of the easiest languages to learn as a beginner. In a nut shell, the language is a great option for data handling and repeated tasks.

Another advantage of Python is that it’s a general programming language. Not only can developers use it for data analysis, but they can also do other things like build websites and play around with command line tools. It also integrates with other programming languages fairly well, making it a good choice for AI projects.

R Programming Language

R is an excellent choice for statistics-heavy projects and one-time dives into datasets. It comes with a better visual presentation which comes in handy when working with tons of raw data. This high-level programming language is also relatively fast compared to Python. And that makes prototyping and working with datasets easier.

On the downside, R does not integrate well with other programming languages. And that might be a problem for casino sites, as you may need to partner with operators who use different programming languages on their apps.


If you look at these two programming languages carefully, you’ll notice that they have different uses. But Python seems to be a better choice for data collection and analysis for online casinos. It makes data handling and repeated tasks look easy. Plus, it has a bigger user community compared to R.

But what if you can make the two languages work together? The results would be great, right? Thanks to Ursa Labs, R and Python developers can now collaborate on the same project using a new file format.