In the world of data science, a significant 75% of professionals utilize both R and Python languages. This statistic highlights the importance of seamless integration between the two. A new R package, rixpress, is being developed to facilitate this integration by setting up reproducible pipelines using Nix as the build tool. Rixpress allows for the creation of targets in both R and Python, making it a versatile tool for data scientists who work across these platforms. The package aims to simplify the process of passing objects between R and Python, enhancing workflow efficiency. The developer of rixpress is currently seeking feedback from Python users on which R packages they use, to further refine the package’s capabilities. This initiative could potentially lead to a Python version of rixpress in the future, broadening its accessibility.
Matt Dancho (Business Science)
@mdancho84
·
Apr 2 I’m excited to share a new GitHub repository that compiles 100 free resources for becoming a Generative AI Data Scientist in 2025.Over the past year, I’ve gathered 100+ Python and R libraries, use cases, and tools that can help you grow in this emerging field.I’d love your
Joachim Schork
@JoachimSchork
·
Feb 1 Choosing between R and Python for statistical analysis involves understanding their specific strengths and popularity in different contexts. Python is a versatile programming language, widely favored for its general-purpose capabilities and extensive use in data science and
Cambridge University Press – Mathematics
@cambUP_maths
·
Apr 16 A Practical Guide to Data Analysis Using R by Professor John H. Maindonald, Professor W. John Braun & Professor Jeffrey L. Andrews
Examples from diverse areas of statistical application demonstrate the use of R for data analysis and associated graphics.
https://cup.org/44oLBVR
Dr. Stylianos Kampakis
@s_kampakis
·
Jan 27 Python remains the top choice for data scientists. Some argue R’s stronger stats focus is better. Yet, Python’s ease of use and community support outweigh that. What do you think? #DataScience #Python
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
Functional
Always active
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.
