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I made an interactive pandas cheat sheet using PyScript
Hacker NewsI made an interactive pandas cheat sheet using PyScript
I wanted to learn a bit more about PyScript, so this weekend I took on a small project. I used PyScript to create an interactive Pandas cheat sheet. It was a fun project, and I thought that it might be useful for those learning Pandas. You can check out the cheat sheet here: https://pandas.dylancastillo.co/ And the code is available here: https://github.com/dylanjcastillo/pandas-cheatsheet/ P.S. Right now the site isn't that mobile-friendly.
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Analyze your own launch →Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
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AppSumoStrong fit for a featured deal · Strong signals: friendly · Missing: plus, platform, intuitive51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using, code · Missing: mac, agents, macos42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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