We recently announced Observable Notebooks 2.0 with a new, open notebook file format + desktop app. Now, we’ve added Python & Node.js data loaders — special cells that run at build time, for better stability and performance. Learn more 👉

Slow-loading tables and overworked browsers can bog down analysis when you're exploring large datasets. In our new post, we explain how table virtualization in Observable Canvas keeps data work fast and fluid — even with big data, and when viewing complex, branching analyses: buff.ly/7cfqsQA

Treemaps help you go beyond donut charts and stacked bars to visualize parts of a whole for hierarchical data. Learn how canvases put state-of-the-art, interactive charts like treemaps, Sankey diagrams, beeswarms, bump charts, and more at your fingertips: buff.ly/DaE8zgO

Observable Plot has crossed 100,000 weekly downloads (and very close to 5,000⭐️s)! observablehq.observablehq.cloud/oss-analytic...

Observable Notebook Kit & Desktop 1.4 now support TypeScript cells, along with TypeScript for Node.js data loader cells. (Just type stripping, but greatly helps interoperability.)

Observable Canvases now support BigQuery making it easy for more companies to connect, query, and build. Get started today at: buff.ly/DaE8zgO

Self-serve analytics sounds great — that is, until tools overwhelm or constrain users, and adoption tanks. Our VP of Sales, Trevor Eddy, shares how collaborative analytics delivers insights and finally fulfills the promise of self-serve BI:

Sankey diagrams make it easy to see how quantities flow through a system, but they're tough to build from scratch. In Observable Canvases, you can create Sankey diagrams (plus arc maps, beeswarms, & more) in minutes — all optimized for clarity and performance: buff.ly/gsd0cpg

Observable Notebook Kit and Desktop 1.3.0 are out, featuring data loader cells. You can now (finally!!) write Python and Node.js in notebooks. 🐍 observablehq.com/notebook-kit...

Bump charts show how rankings shift over time, and are a great option when order matters more than absolute values. In Observable Canvases, you can now build & share responsive bump charts with just a few clicks. See what's new in our summer release: buff.ly/ZDxrAvt

For one of the most common operations in all of data wrangling, implementing UI-based data joins is anything but straightforward. Software engineer Tony Sullivan shares some unexpected challenges behind joins and how we handle them in Observable Canvases: buff.ly/4FRU9C9

Join us tomorrow, Thursday, September 4 at 10am PT, for a webinar showcasing the latest features in Observable Canvases, including new chart types, additional data sources, and improved dashboards: buff.ly/QPox1Oj

Observable Canvases make it lightweight to share interactive charts and tables as a natural extension of your data analysis. Embed canvas nodes into your internal data apps, or draw a frame around part of your canvas to generate a tidy dashboard view. Learn more: buff.ly/Bw8nukG

My most popular interactive @observablehq.com notebook, Math for Journalists, just got a fresh update! 🧑‍🎓 👉 Sample size and confidence: I explain how sample sizes work, like in a survey. 👉 Tests for statistical significance: I break down what "statistically significant" means. Link in comments! 👇

In Observable Canvases, we’re putting advanced, interactive charts at your fingertips. Make Sankey diagrams, beeswarm charts, arc maps, bump charts, and more in just a few clicks. Learn how canvases streamline data visualization and analysis: buff.ly/ATVg0sw

Observable Canvases just got a major upgrade. Join our live webinar on September 4 at 10 AM PT to learn about new chart types, extended sharing options including quick embeds, improved workspace permissions, and more: buff.ly/QPox1Oj

Observable Notebook Kit and Desktop 1.1 are out. Headline feature: database connectors! 🎉 You can now query DuckDB, SQLite, Postgres, and Snowflake directly from notebooks. And it’s self-hosted. And it saves results automatically for performance and stable analysis. observablehq.com/notebook-kit...

📣 Today we’re announcing big updates in Observable Canvases. Learn about our growing suite of built-in, interactive charts (Sankey diagrams, arc maps, beeswarms + more), new embeds and dashboards for fast sharing, added Postgres and Databricks support, and more:

A little demo of reactive SQL in Observable Notebooks 2.0, first using (native) DuckDB to bake data from a remote source, followed by DuckDB-Wasm to create and query reactive views in the client. Should be released this week!

Grid cartograms trade realistic geospatial borders for geometric tiles that make small regions visible, and values more easily comparable. Read our new blog post for grid cartogram essentials, examples, pros/cons, and resources on how to build your own in Observable: buff.ly/HRj56yz

AI adoption doesn’t have to be top-down. At Observable, we’re supporting our team to explore and use AI tools in ways that work for them. The result? A culture where AI feels natural and useful, not forced. 👉 Learn how our team at Observable boosted AI adoption: buff.ly/t0J92IN

AI can speed up steps in throughout data analysis from initial data profiling to final chart development. For exploratory analysis, use AI to summarize database schemas and contents, automate tedious data wrangling tasks, and draft new charts. Learn more: buff.ly/5DzuzZ7

Notebooks 2.0 is here! 📓🔮 Previewing today:
Notebook Kit, an open file format for notebooks with open-source tooling for generating static sites; and
Observable Desktop, a macOS desktop application for editing notebooks as local files, with a radical new approach to AI. observablehq.com/notebooks/2/

In Observable Canvases, AI is transparent and verifiable, so you can confidently use it throughout your data analysis lifecycle. Discover how AI streamlines data exploration by accelerating data profiling, automating data wrangling, and drafting interactive charts:

Speaking with customers, I have been fascinated by the failed promise self-serve analytics. In this post, I will explain the challenges and offer an alternative solution that actually works #dataviz #datavisualization #team-datafam @observablehq.com observablehq.com/blog/the-fai...

AI can fast-track your data analysis, but only if you can trust its outputs. In Observable Canvases, you can see, verify, and interpret AI outputs every step of the way. Learn how our transparent AI gets you from messy tables to trusted insights, faster: buff.ly/B3H8cSG

AI in Observable Canvases is transparent, so you can boost your data analysis while maintaining confidence in the results. We expose the logic and code at each step for AI outputs that you can immediately verify, and more easily interpret. Learn how we’re doing AI differently:

Big data usually means slow charts, but not in Observable Canvases. Our optimized queries power fast, interactive visualizations so you can explore more, and wait less, to find insights faster. Learn how we keep charts fast, even with big data: buff.ly/eOSF8Vt

The hardest part about reusing charts can be getting your data into the expected shape. Learn common data formats consumed by Plot & D3 — and how to transform your data to match — so you can quickly reuse thousands of stunning, interactive visualizations: buff.ly/rJaX6pT

When working with big data for BI, data visualizations can be painfully slow to load. That stifles exploration and iteration, which means you might be missing out on business insights. In our new post, learn how we keep charts fast in Observable Canvases:

Histograms are incredibly useful, interpretable, and common in BI. But building histograms that work well out of the box — no matter the data — is trickier than it sounds. We share some of the challenges faced, and decisions made, when designing histograms for Observable Canvases:

Data analysts are knee-deep in company data on a day-to-day basis, so they are uniquely positioned to help teammates find, use, and trust analyses that can improve their work. Learn how analysts can contribute to a stronger data culture across their organization: buff.ly/JrTdLNH

When data visualization is confined to initial exploration and final storytelling, you can miss out on insights, anomalies, and mistakes that get revealed in the messy middle. Learn how end-to-end visual data analysis helps you and your team uncover insights, and errors:

Most BI and data viz tools let you make histograms with a single click or command. So, you might think that designing good default histograms is simple. Turns out, it's harder than it sounds. Learn how we handle common challenges to make better out-of-the-box histograms in canvases:

Including collaborators and stakeholders throughout analysis helps to avoid redundant work, crossed wires, and rehashing decisions at the project finish line. Learn how collaborative analytics gets you from raw data to trusted business decisions, faster:

With end-to-end visual data analysis, you can keep eyes on your data throughout the analysis process. Learn how that helps you discover unexpected value in your data, catch mistakes earlier, and improve cross-functional collaboration: buff.ly/Y4QGVZx

Collaborative analytics brings data teams and stakeholders into the analysis process from ideation to final product. Discover how that helps you all reach the finish line, faster: buff.ly/v65yvHD

Join us May 20 at 10 AM PT for a first look at Observable Canvases. Learn how canvases support fast, visual data exploration and analysis, with whiteboarding tools that let data teams and stakeholders all participate in the same place. Sign up today: buff.ly/TjsahdU

In Observable Canvases, data teams can break free from linear workflows to explore data in branched, visual analyses across an infinite canvas. Work seamlessly between code and UI, and collaborate with stakeholders using whiteboarding tools:

Ever built a chart only to have people misread it, or miss key insights? Annotations can make all the difference. Here are five ways you can uplevel your chart annotations for improved context, clarity, and interactivity (with reusable examples and code):

In Observable Canvases you can write queries in SQL, build custom charts in JavaScript, or wrangle and visualize data using UI options. Seamlessly mix methods across the infinite canvas, with the freedom to choose how you work with data at each step. Learn more: observablehq.com

Learn how to answer questions about your data by querying your database in our newest blog post. We walk you through the kinds of queries you can ask of a single table and cover the basics of SQL.

Observable Canvases get data teams and stakeholders all in one place, with the context and tools they need to fearlessly explore and analyze data together. Learn how canvases (now in early access) can help teams make faster, better, and more trusted business decisions: buff.ly/F1CCrQn

Say hello to the collaborative data canvas. Observable Canvases give teams a faster, more flexible way to work with data — explore freely, think visually, and uncover better insights, together. Now in early access:

You know that databases are where most data lives, but do you understand how they work? In this series, we'll walk you through what tables and relations are, how data is organized, how you filter and aggregate, and how joins work. We’re starting with Databases 101:

Data visualizations should inspire curiosity, encourage exploration, and leave users excited for more. We spoke with data viz developer Kelsey Nanan to understand her process and guiding principals. Learn more:

When used carelessly, animation can distract from data visualizations. Check out these best practices for delivering better animations in data visualizations.

Charts should speak for themselves — but too often, key insights get lost. Smart annotations help guide the story. Here are five ways to make your charts clearer, more interactive, and more impactful.

Large language models (LLMs) and AI tools have proven to be very useful for programming, but how do they do when writing D3 code? In this blog post, we explore Claude's ability to create and modify some basic charts from time series data.

When it comes to data viz and app development, Kelsey Nanan thinks that collaboration between designers and developers is key to overcoming hard challenges, unlocking creativity, and finding unique solutions: