Use Pivot Chart to Replace Your Pivot Table

Hacker News

Pivot-Chart is an open-souece comprehensive data visualization tool that enhances pivot tables with visualizations and charts, offering a more intuitive and informative way to analyze your data. With Pivot-Chart, you can elevate your data analysis and take a new approach to exploring your data. Unlike other pivot-table + vis solution, pivot chart retains nest multi-level aggregation feature of pivot table, which allows you to compare between different aggregation levels and make it easier to drill down and roll up. Integrating Pivot-Chart into your data applications is easy, simply import the npm package. While this is a proof-of-concept project, your feedback and suggestions are valued and appreciated. features: * All pivot table features * Supports cell display as charts * Retains nest multi-level aggregation feature of pivot table * Easy to use and integrate with your projects as a component in web. * Open-source and customizable to meet your needs Github Repo: https://github.com/ObservedObserver/pivot-chart Demo on Vercel: https://pivot-chart.vercel.app/

Visit product View on Hacker NewsJan 29, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, visual, open · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: intuitive · Missing: plus, platform, reviews

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

10%10% 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.

Correct prediction on native model

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