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

Key Takeaways -   To understand data science, one needs a lot of technical expertise along with business understanding. Generative AI, MLOps, and clou ...

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, ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Ruth Linehan explains how migrating ...

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 ...

While Excel is ubiquitous, I prefer Python for my data analysis. Spreadsheets are great for formatting data, but it's Python that's allowed me to build my own super calculator out of regular Python ...

"The Python Interactive experience now comes with a built-in variable explorer along with a data viewer, a highly requested feature from our users," de Melo e Abud said. "Now you can easily view, ...