PyData London 2018 Lightning Talks - Day 2
summary
Day‑long lightning rounds deliver concrete wins: a pandas sprint yields 2–3 pull requests ready for review fixing string and docs issues; an astronomy project trains a random forest that reports 95% accuracy on ~8.3k neutron star and ~7k black hole spectra; a civic hack shows polling PDFs scraped into Excel (not yet dataframes) and a quick model using scikit‑learn/CatBoost that outperforms prior open forecasts; demos include BinderHub live notebooks and a playable JSON API game prototype.
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chapters (10)
- 0:00NumFocus and community roles
- 2:56Becoming a NumFocus volunteer
- 4:46Pandas docs sprint highlights
- 8:31Pandas sprints participant experience
- 11:19Hacking open election data
- 16:39Black hole ML classification
- 23:49Sharing notebooks with BinderHub
- 30:02Visualizing Gaia star data
- 33:15Community in open source
- 36:28Space programming game
