Minard – Generate beautiful charts with natural language

Hacker News

Hi HN – Excited to share a beta for Minard, a new data visualization toolkit we've been working on that lets you generate publication-quality charts with simple natural language (throw away your matplotlib docs and rejoice!). Upload or import CSVs, Excel, and JSON, give it a spin, and please let us know what you think! (Long format data works best for now) For those curious, the stack is a simple Django app with HTMX/Alpine and all of the charts are specified and rendered as Vega ( https://vega.github.io/vega/ ). Lots of LLM function calling under the hood as well.

Visit product View on Hacker NewsApr 18, 2024

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

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

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

15%15% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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