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

The new features, including connectors to third-party data sources, are aimed at making the AI assistant more useful for finance professionals.

The days of manually copying and pasting data into Excel. That is the worst kind of bad debt, throwing away your precious resources (time and brain processing power) down the drain. If you think of ...

This project is maintained again as of 2026-06. The current goal is to keep the original py2neo v3 / Neo4j 3.x example usable for learners, notebooks, and legacy projects while adding a current Neo4j ...

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a ...

Excel is my database, Python is my brain.

When it comes to working with data in a tabular form, most people reach for a spreadsheet. That’s not a bad choice: Microsoft Excel and similar programs are familiar and loaded with functionality for ...

Have you ever wished Excel could do more of the heavy lifting for you? Imagine transforming hours of tedious data cleaning and analysis into just a few clicks. That’s exactly what Microsoft’s ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your toolkit. Python’s rich ecosystem of data science tools is a big draw for ...

Fama–French Factor Graphs is a Python-based analytical tool for visualising factor model regressions using the Fama–French framework. The program enables users to plot and compare exposures to the ...

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 ...