Uncover the hidden pitfalls of Excel regression and learn why Python is the key to unlocking clean, efficient data analysis.

This vibe coding cheat sheet explains how plain-language prompts can build apps fast, plus the planning, testing, and security checks needed.

These tricks show how AI tools, new import formulas, and classic features improve productivity. Excel has outlasted many tech trends, and in the age of AI, it remains very much in the mix. While new ...

pandas is the premier library for data analysis in Python. Here are some advanced things I like to do with pandas DataFrames to take my analysis to the next level. Change the index of a DataFrame On a ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Why write SQL queries when you can get an LLM to write the code for you? Query NFL data using querychat, a new chatbot component that works with the Shiny web framework and is compatible with R and ...

The reticulate package provides a comprehensive set of tools for interoperability between Python and R. The package includes facilities for: Calling Python from R in a variety of ways including R ...

Authentication using Application passwords now works - for OIDC and SAML-backed authentication providers (OP) - but note below how this has been implemented to perhaps work around the fact that ...

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, ...

Information is gold. But to get that information, you need to process and refine raw data. But what happens when the data you need isn’t presented to you in a CSV or an API? And you have to source it ...