Thank you! I completely agree—TSVs/CSVs are such a simple yet powerful format, and it's great to hear you're making good use of them. I'm also a big fan of doing as much as possible locally—our machines are incredibly capable these days. Good news: I'm currently working on the macOS version of Data.olllo and plan to submit it to the Mac App Store soon. Stay tuned!

Ok, if we are all tagging and promoting our own projects, check out mine.

I created Buckaroo to provide a better table viewing experience inside of notebooks. I also built a low code UI and auto cleaning to expedite the wrote data cleaning tasks that take up a large portion of data analysis. Autocleaning is heuristically powered - no LLMs, so it's fast and your data stays local. You can apply different autocleaning strategies and visually inspect the results. When you are happy with the cleaning, you can copy and paste the python code as a reusable function.

All of this is open source, and its extendable/customizable.

Here's a video walking through autocleaning and how to extend it https://youtu.be/A-GKVsqTLMI

Here's the repo: https://github.com/paddymul/buckaroo

QStudio allows querying CSV on mac via DuckDB: https://www.timestored.com/qstudio/csv-file-viewer I've been improving the Mac version a lot lately, key bindings, icon, an App package to download. So if you find any problems please raise a github issue.

… I‘m trying to use our super computers in our pockets, like an iPhone ;-) But still struggling with the way how to present CSV data effectively on a small screen, although it‘s huge in terms of pixels compared to computer screens from the 90s

It‘s interesting to research how capable applications like Lotus123 have been even on low resolutions like 800x600 pixel compared to today’s standard

If you are wrangling CSV/TSV files on Mac, it might be worth taking a look at Easy Data Transform.