I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...

The language R is in the midst of a sizzling resurgence this summer. One might hypothesize that this growth is coming at the expense of Python, by far the dominant language for data science. But some ...

Statistical programming language R has fallen off Tiobe index's list of the 20 most popular languages, having spent three years in the top tier. Tiobe now places R in 21st position and suggests the ...

Reticulate is a handy way to combine Python and R code. From the reticulate help page suggests that reticulate allows for: "Calling Python from R in a variety of ways including R Markdown, sourcing ...

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis. Hoping to settle ...

R vs Python: What are the main differences? Your email has been sent More people will find their way to Python for data science workloads, but there’s a case to for making R and Python complementary, ...

With the emergence of the era of Big Data, frameworks like Hadoop arose and the focus of the enterprise shifted to which was processing this data. This is where data science came into the picture.

As programming languages go, there’s no denying that Python is hot. Originally created as a general-purpose scripting language, Python somehow became the most popular language for data science. But is ...