Who work with psychometrics. R is for you if what you’re looking for includes: Functions designed to prepare the data for specific analysis Functions ready to run the analysis and interpret the results Functions that build custom graphics for those analyses All of it backed with documentation based on academic books, Python’s versatility is unbeatable If R is the old but trusty Mustang your father bought when he was a teenager, then Python is a flamboyant Tesla.
Python was originally built with
Readability in mind so that it could act country email list as a gateway to new programmers, and it shows. The syntax is human-friendly, and even a new programmer can read a Pythonista’s (an advanced developer) code and get an overall idea of what it’s doing. Since Python is a multi-purpose language, it’s a lot more versatile than R, which makes it the ideal language for integration with other platforms.
A colleague of mine is currently
Developing a game in Python that our company has over a thousand registers decision-making data. Uploads it to a server where it’s analyzed. Eventually will be automatically uploaded to a webpage so other scientists can take a look at the data. A few years ago most data scientists would have preferred R since it had a more robust set of tools for machine learning.
But that’s no longer the case
Python nowadays equals (and sometimes email data surpasses R) as the best language for Artificial Intelligence. Python is growing at a gigantic pace. The main reason is that the developer space (at least for data science) is shared between programmers and scientists. Working with teams experienced in outsourcing. Python development can help balance these skill sets.