Stuff I Learned during Hanukkah of Data 2023

1. polars

   1 149 33,298 10.0 Rust

   Dataframes powered by a multithreaded, vectorized query engine, written in Rust

   

   That turned out to be related to pola-rs/polars#11912, and this linked comment provided a deceptively simple solution - use PARSE_DECLTYPES when creating the connection:

2. Judoscale

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3. Pandas

   2 425 45,260 9.9 Python

   Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

   

   Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.

4. nbdime

   3 7 2,736 6.9 TypeScript

   Tools for diffing and merging of Jupyter notebooks.

   

   I remember hearing about nbdime and thinking it sounded useful, but I've never really needed it since I rarely use Jupyter in the first place. But then I made some changes to my Hanukkah of Data 2023 notebook to work with the follow-up "speed run" challenge (a new dataset and slightly tweaked clues), and the native Git diff was too noisy to be useful. nbdime came to the rescue! Here are the changes I had to make for days 2 and 3 during the speed run:

5. datasette

   4 197 9,971 8.5 Python

   An open source multi-tool for exploring and publishing data

   

   Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.

6. advent-of-code-jq

   5 246 216 6.5 jq

   Solving Advent of Code with jq

   

   Hanukkah of Data is a series of data-themed puzzles, where you solve puzzles to move your way through a holiday-themed story using a fictional dataset. I think of it as "Advent of Code meets SQL Murder Mystery".

7. CodeRabbit

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