Alternatives
Products that do what Minard – Generate beautiful charts with natural language does
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.
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Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com
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Hey, guys. I've just made a plugin which turns your pandas dataframe into a tableau-style component. It allows you to explore the dataframe with easy drag-and-drop UI. You can use PyGWalker in Jupyter, Google Colab, or even Kaggle Notebook to easily explore your data and generate interactive visualizations. PyGWalker (pronounced like "Pig Walker", just for fun) is named as an abbreviation of "Python binding of Graphic Walker". Here are some links to check it out: The Github Repo: https://github.com/Kanaries/pygwalker Use PyGWalker in Kaggle:…
2023 · github.com
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Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…
2025 · github.com
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Hey HN! We are Jonathan & Guy, and we are happy to share a project we’ve been working on. ChartDB is a tool to help developers and data analysts quickly visualize database schemas by generating ER diagrams with just one query. A unique feature of our product is AI-Powered export for easy migration. You can give it a try at https://chartdb.io and find the source code on GitHub. Next steps ---> More AI. We’d love feedback :)
2024 · github.com
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2017 · frappe.github.io
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Creating data visualizations with AI nowadays often means chat, chat and more chats...and writing long prompts can be annoying while they are also not the most effective way to describe your visualization designs. Data Formulator blends UI interaction with natural language so that you can create visualizations with AI much more effectively! You can: * create rich visualizations beyond initial datasets, where AI helps transforming and visualizing data along the way * iterate your designs and dive deeper using data threads, a new way to manage your conversation with AI. Here is a demo video:…
2024 · github.com
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Ferrite: Fast Markdown/Text/Code editor in Rust with native Mermaid diagrams Built a Markdown editor using Rust + egui. v0.2.1 just dropped with major Mermaid improvements: → Native Mermaid diagrams - Flowcharts, sequence, state, ER, git graphs - pure Rust, no JS → Split view - Raw + rendered side-by-side with sync scrolling → Syntax highlighting - 40+ languages with large file optimization → JSON/YAML/TOML tree viewer - Structured editing with expand/collapse → Git integration - File tree shows modified/staged/untracked status Also: minimap, zen mode,…
Jan 2026 · github.com
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io
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Hi HN! I'm excited to share Autolabel, an open-source Python library to label and enrich text datasets with any Large Language Model (LLM) of your choice. We built Autolabel because access to clean, labeled data is a huge bottleneck for most ML/data science teams. The most capable LLMs are able to label data with high accuracy, and at a fraction of the cost and time compared to manual labeling. With Autolabel, you can leverage LLMs to label any text dataset with <5 lines of code. We’re eager for your feedback!
2023 · github.com
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Just wanted to share with HN a simple/minimal open source Python library that generates SVG files visualizing two dimensional data and distributions, in case others find it useful or interesting. I wrote it as a fun project, mostly because I found that the standard libraries in Python generated unnecessarily large SVG files. One nice property is that I can configure the visuals through CSS, which allows me to support dark/light mode browser settings. The graphs are specified as JSON files (the repository includes a few examples). It supports scatterplots, line plots, histograms,…
Mar 2026 · github.com
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Many JS libraries exist to build graphs on the web (Vega, chartJS, Plotly...). They allow to make charts quickly. But you lose flexibility: you're limited by the options they offer. I just created a gallery with hundreds of graphs made with d3.js and React. - Examples are split by graph types - They all come with explanation and code sandboxes - Gradual complexity to ease the learning curve It took me ages to create this project! Feedback welcome!
2023 · react-graph-gallery.com
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Hello HN. I've always found writing data visualisation scripts boring and repetitive in data science workflows earlier in my career, so I built this tool to automate it. The available methods are based on my experience in econometrics where histograms and scatterplots were the starting points to check data distributions. The link is to the documentation and the app is freely available at https://visprex.com, and if you're curious about the implementation it's open source at https://github.com/visprex/visprex. I'd appreciate any comments and feedback!
2024 · docs.visprex.com
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Hey HN, I’m Jordan cofounder of Humanloop (YC S20) and I’m excited to show you Programmatic — an annotation tool for building large labeled datasets for NLP without manual annotation. Programmatic is like a REPL for data annotation. You: 1. Write simple rules/functions that can approximately label the data 2. Get near-instant feedback across your entire corpus 3. Iterate and improve your rules Finally, it uses a Bayesian label model [1] to convert these noisy annotations into a single, large, clean dataset, which you can then use for training machine learning models. You can…
2022 · programmatic.humanloop.com
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2022 · colab.research.google.com
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2023 · github.com
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