These are my go-to libraries for Python data crunching.

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

Anaconda provides a handy GUI, a slew of work environments, and tools to simplify the process of using Python for data science. No question about it, Python is a crucial part of modern data science.

In December 2019 my InfoWorld colleague Sharon Machlis wrote an article called “How to merge data in R using R merge, dplyr, or data.table.” Sharon is a whiz at R programming, and analytics in general ...