Python has some wonderful libraries for statistical analysis, but they might be overkill for simple tasks. The built-in statistics library might be what you want instead. Here are some things you can ...

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 ...

What if the tools you already use could do more than you ever imagined? Picture this: you’re working on a massive dataset in Excel, trying to make sense of endless rows and columns. It’s slow, ...

Overview: Real-world Python projects build stronger practical development skills than theory alone.AI, cloud development, and ...

Vienna, Austria, June 25, 2026 -- digna, the European data quality and observability platform, today announced the release of ...