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GitHub Repo Visualizer Using D3

Hacker News

GitHub Repo Visualizer Using D3

I built this as part of my quest to properly learn data visualization. The code is the easy part! Some lessons learned: - personal verification of the the general truth that pie charts are tough! and the returns are not great for the effort due to people's difficulties perceiving angles - may not use "vanilla" d3 with no React. was difficult to adapt for mobile - the GitHub API provides fairly standardized responses so building dynamic charts wasn't too bad. But when working with streaming data (say Kafka) I can see this getting interesting... schema registry should help but creating a view into the data with a lookback would be interesting with d3, done it with altair before.

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, using, code · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, visualize · Missing: mobile apps, ios, entrepreneurs
41%41% 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, podcasting
32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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