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

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 ...

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 ...

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.

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, ...

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

Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and ...

Overview AI and big data posted the sharpest jump on WEF's 2025 skills ranking, up 17 percentage points in two years, while ...