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

This is a Python implementation for calculating the Standard Precipitation Index (SPI). This is one of the key indicies in identifying droughts. See [NCAR's Climate ...

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 ...

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 my case, I use FilePicker to read Excel files, and I often used services.append... when doing so. Then, when I started writing code bit by bit to create a new app and ran it, I started getting 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 ...

This article is adapted from an edition of our Off the Charts newsletter originally published in October 2021. Off the Charts is a weekly, subscriber-only guide to The Economist’s award-winning data ...

As a Python user, I frequently interact with Excel files to manage data because business professionals often prefer sharing information in Excel or CSV formats. However, Python can be notably slow ...

Optimized apps and websites start with well-built code. The truth, however, is that you don't need to worry about performance in 90% of your code, and probably 100% for many scripts. It doesn't matter ...