Have you heard that Python is swallowing the data analytics space whole? While this may not literally be true, this language is gaining steam in a variety of areas and dominating the current Machine Learning/AI pack.

A recent developer survey from JetBrains found that 49% of respondents say they use Python for data analytics, which came in ahead of the 46% who say they use this tech for web development. Closely following at 42% is machine learning, and 37% for system administration. So, why is this ubiquitous tech gaining so much steam when it comes to data analytics and Machine Learning?

Part of the reason is that the Machine Learning and AI space is really taking off right now. Python was already favored among technical professionals and its use among analytics professionals has grown from 53% to 69% since 2017. Python is ubiquitous, especially among technologists who need to crunch data at work, and it’s popular because of its relative ease of use.

But what about R? R has its place in the data analytics space as a whole, but it’s generally not preferred in the Machine Learning and AI ecosystem the way Python is. In fact, R’s general user base shrank by nearly a third since 2016. That doesn’t mean the technology is phasing out, but it’s finding its own niche and it happens to be smaller than Python’s

And, while Python is great for building libraries and frameworks, it wasn’t designed for interactive data analysis. Some technologists prefer to use R because it was designed for that and data analysis is fundamentally an interactive activity & a necessary activity. Others say that R has a place when it comes to traditional statistics but Python is still preferable for Machine Learning.

If you’re going to dive into Python now, it’s important to know that a substantial majority of developers 87% are on Python 3 while just 13% of developers are still on Python 2. If you’re looking to break into the Machine Learning or AI space, Python is a vital language to learn because so many developers are currently using it to build out machine learning tools. It’s widely viewed as a technology that plays an important part in most company’s future tech strategy so deepening your existing Python knowledge or diving into this tech is important if you have any interest in Machine Learning or AI.