But, Python and R also bring their own unique strengths to data science, making it harder to decide which to use. R is an open-source, interactive environment for doing statistical analysis.

There’s an intriguing new option for people who want to do data-wrangling and analysis in R or Python but visualization in JavaScript: Quarto. This article shows you how to set up a Quarto ...

In fact, R was the core focus at DataCamp, which provides education and training in data science, data analysis, and machine learning. Since then, interest in Python has exploded, and today DataCamp ...

EconometricLinks.com was established in 2025 with a vision to democratize econometric knowledge and promote innovation in ...

Python is more efficient when deploying machine learning and deep learning. For this reason, R is the best for deep statistical analysis using beautiful data visualizations and a few lines of code.

The Python ecosystem is loaded with libraries, tools, and applications that make the work of scientific computing and data analysis fast ... as easy for statistics as R, as natural for string ...

Translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays). Flexible binding to different versions of Python including virtual ...