Conclusion
In this workshop we’ve worked through an end-to-end data processing workflow with Clojure’s toolkit:
We’ve explored how to:
- Load and manipulate data using tablecloth’s dataframe-like operations
- Perform exploratory data analysis with Clojure’s functional approach
- Visualize data with tableplot
- Apply statistical methods and data transformations in a clean, composable way
- Leverage Clojure’s REPL-driven development for interactive data exploration
Keep in touch!
One thing we didn’t get to fully experience in this workshop is the amazing community working on all of these tools. To keep in touch, the best place is to join the Clojurians zulip instance. Most of the Clojure-for-data people hang out in the #data-science channel there.
Join the Clojurians Zulip #data-science channel
You can also always reach out to me personally, I’m happy to chat about any of this stuff or connect you to anyone you might be interested in meeting or working with:
Bluesky: https://bsky.app/profile/kirahowe.com
linkedin: https://linkedin.com/in/kirahowe
Resources
- The source code for this workshop - All the code and examples we’ve covered
- Noj documentation - The scientific computing umbrella library for Clojure
- Scicloj - The Clojure scientific computing and data science community
- Tablecloth documentation - Data manipulation
- Tableplot documentation - Data visualization
- Clojure.org - More about Clojure in general