Plotly.js 4.0 is out! 🥳 New trace type, many more customization options, lots of bug fixes, and a few low-key, strictly-better changes to the defaults. See the full release notes and examples here: plotly.com/blog/announcing-p….

easy peasy lemon squeezy 🍋 Want a data-querying, chart-making chatbot on top of your Dash app? 1. Define a `get_data()` function that returns some dataframes. You can literally connect to _anything_ with Python, so this data can come from anywhere. 2. Publish your app to Plotly Cloud: `$ plotly app publish` 3. Flip on the chatbot switch in your app settings That's it! We love this solution because it's super easy but it also gives you full control over data access. You can restrict access to certain tables or columns, or just clean things up in the data between the data warehouse and your end users. Join our launch event next week: plotly.com/webinars/plotly-s…

It's launch day! Introducing Plotly Studio Embedded 🥳 Plotly Studio Embedded brings agentic analytics directly into your Dash app. It enables the viewers of your application to ask questions about data and generate charts, tables, maps and reports with AI. There's a few things that make this product really unique: 1. Configuration as code: Data access is managed in code in advance, so end users don't need to fuss around with connectors or credentials themselves. 2. Data is front-and-center: Most AI chat experiences show you a wall of text. That's not what we think data analytics should feel like. Plotly Studio Embedded is designed to show you the queries, graphs, and tables every step of the way. 3. Secure: Rather than engineering an agent that can do anything (including escape sandboxes), we engineered this agent to only perform data analytics and visualization tasks. There's no arbitrary code execution, no network access, no filesystem access. 4. Embedded: The AI experiences co-exists alongside predefined views. So end users can have the best of both worlds and so that you can save on token$ by placing the common charts and tables in the Dash app itself. Read more: plotly.com/blog/plotly-studi… Join the launch event: plotly.com/webinars/plotly-s…

Fascinating staff research by Robert Claus and Matthew Brown measuring the cost savings in time & tokens by building on Dash vs Full-Stack for data apps, internal tools, and reports. Using the right framework saves you far more $$ than any model or harness. Read the research here: plotly.com/blog/dash-vs-full… Watch the discussion: plotly.com/webinars/dash-ful…

On choosing the right framework Join the discussion tomorrow: plotly.com/blog/dash-vs-full…

Long live great libraries.

Our Sr. Sales Ops Admin, Megan, built a real-time dashboard connected directly to her live Salesforce data source. Check out her dashboard, replicated using mock/dummy data: bit.ly/4wTuUNw Get started with Plotly Studio: bit.ly/3TMOAUR

Ever wonder what's actually inside Google Maps? Turns out you can build a surprisingly capable version yourself, in a single Python file. We just published a breakdown of Dash Navigation, a working maps + turn-by-turn routing app built entirely on open data: - OpenStreetMap for street geometry, speed limits, and road names - Custom-rendered map tiles (Leaflet) instead of a commercial tile server - Auto-generated turn-by-turn directions from raw intersection geometry The whole thing runs with one command, downloads its own map data on first launch, and deploys as easily as any other Dash app, using Plotly Cloud. The code is open source, and the app is running live if you want to point it at your own city. Read the full article: bit.ly/4fNE4Ed GitHub: bit.ly/3TuubDY App: bit.ly/45BpM4I

Your app deserves a better URL. ✨ Vanity URLs are now free for every Plotly Cloud user. 🌐 Pro teams can now publish Dash apps on their own custom domains with automatic HTTPS. Professional apps deserve professional URLs. Learn more: tinyurl.com/mryd8ybj

We just turned our product marketing team's brain into a tool anyone at Plotly can use inside Claude Desktop. Here's the problem we solved: our product messaging framework (personas, competitive analysis, feature benefits, talking points) lived in one person's head and a pile of docs. Everyone needed it, but almost no one had easy access. Instead of building another app or dumping everything into Confluence, we built an MCP server using Dash's new native MCP support and deployed it on Plotly Cloud. Then we connected it to Claude Desktop as a custom connector. Read the full article here: bit.ly/4x6FbFZ

Plotly community member Robert just connected a Dash MCP server to his FX and macro dashboard. As a result, rather than asking an AI to guess at what's on screen from a screenshot, the AI now calls the same Python functions and callbacks that power the dashboard. Check out his article: bit.ly/4x6wmfz

What does it take to serve a month of Polymarket orderbook data, with 16 billion events and 500 GB of Parquet, as a live interactive dashboard? Less than you'd think. We partnered with the Polars Cloud team to take this dataset to production: - Polars Cloud handles the heavy compute; the same code that processes an hour of data on your laptop scales to a full month across a cluster, unchanged - A Dash app serves it as a thin, stateless layer reading query-optimized Parquet - Plotly Cloud handles the ops: machine sizing, Always-On compute, and metered billing And with Dash 4.3, the app doubles as an MCP server. Claude, Cursor, or ChatGPT can connect and query the actual dataset, to answer users' questions. Explore the live dashboard and read the full breakdown 👇 bit.ly/4yMQcOk bit.ly/4wtMlUQ

Dash or full stack for your next AI-built data app? 🤔 On August 13, Matthew Brown and Robert Claus run the comparison. Token costs, package counts, long-term maintenance, and when to pick which. Register below tinyurl.com/fbbv3kcs

Looking to level up your data visualization skills? Plotly University is a growing hub of practical, real-world learning for anyone working with Python and interactive analytics. Whether you're building production dashboards, exploring data visualization best practices, or looking for industry-specific tutorials, you'll find hands-on content designed to help you create impactful data apps. Topics range from responsive Dash design and machine learning integration to real-world dashboards. Check it out here: bit.ly/4fd1Pqn

We're less than 48 hours away from our webinar, "Turn Scientific Models into Decision-Making Tools with Dash." Here's a sneak peek of what Dr. Nicholas Siemons of STEER Stanford will demo. In the GIF below, you'll see an interactive visualization of a battery cross-section, where you can zoom in to explore the different layers inside. Join us! bit.ly/4wlPpCB

Meet Aamir, our newest Technical Account Manager 🌟 In our latest People in Focus blog, Aamir shares what it's like to go from being a Dash Enterprise customer to helping customers succeed at Plotly. Read all about his first 90 days at Plotly: bit.ly/4yFpiYP

What does an interactive battery design application look like? Built with Dash, OpenCell from Stanford's STEER program helps researchers explore battery design, cost intelligence, and technology roadmapping through an interactive interface. The preview below showcases just a few of its capabilities: • Update cell properties such as encapsulation and layup • Visualize assembly construction • Analyze results with load balancing Join us on July 29 for a live walkthrough with Dr. Nicholas Siemons and get a behind-the-scenes look at how Dash powers production-ready scientific applications. Register here: bit.ly/4yBlZly