And as always, defined directly in the SQL query. More in the docs: taleshape.com/shaper/docs/da…

New @tale_shape Visualization Option: Confidence Bands Allows you to show a band for a line chart which is great to show extra statistical context (the confidence of a prediction, the spread of a distribution, etc) Nnice middle ground between only a line and a full Boxplot.

Did you know you can download @tale_shape dashboards with SQL? Use Shaper's API to download PDFs, images, Excel files and so on. Call the API with the DuckDB http_client extensions from a Shaper task to post charts to Slack, email a weekly PDF report, etc

Skills for @tale_shape are here: Use with Claude Code/Codex/Gemini to create dashboards quickly. With the skills the agent knows Shaper SQL, validates the create dashboard and gives you a preview URL once ready. More here: github.com/taleshape-com/sha…

Last week I ran into a great use case for UNPIVOT: The dataset had the columns p25, p50, p75. But to visualize it with @tale_shape we want to use the column name as CATEGORY and the column value as LINECHART. And UNPIVOT does exactly that in a single line of code:

@tale_shape Cloud is now in beta! The simplest way to start building dashboards and customer-facing analytics with Shaper. Let me know what you think: taleshape.com/plans-and-pric…

The @tale_shape docs now have live examples 📊 Examples are now embedded as live dashboards instead of only screenshots. With this you can also directly see the differences between light and dark mode:

I have seen @tale_shape provide the most value to companies in healthcare and other regulated industries. I like to double down on that and need your help: 1/2

for details: taleshape.com/blog/build-you…

I built a Slack data analytics agent on top of @tale_shape. The agent answers your questions and uses our new API to directly send charts, Excel files or PDF reports into Slack: 1/2

I set up a minimal self-hosted data lake platform with DuckDB, DuckLake and @tale_shape. The whole setup is a single docker compose file that covers all basic data needs from ingest and storage to transform and visualization:

Today @tale_shape launched on @UneedLists and people seem to like it 👀 If you have a minute, I am happy about your support 🙏

@tale_shape now offers hosting + support for Shaper! Fully-managed, On-Premise BI + White-Labeling for 150/m anyone? Happy about any feedback🙏 And if you can think of any company that might be interested in code-first embedded analytics powered by DuckDB, please reach out 👀

I haven't updated my personal blog since starting @tale_shape so I used that as a chance to give an update on why I am building Taleshape and where things stand right now: jorin.me/building-taleshape/ Also: I am always happy about any ideas on where to take Taleshape next 🙏

@tale_shape now has "watermarks" for chart download to make it easy for your customers to credit you. One of the companies I work with integrated Shaper into their product. And now their customers use various dashboards regularly as part of their daily work. 1/2

Got surprised by sudden spike in Github stars and turns out someone posted @tale_shape on HN frontpage

I couldn't imagine a better fit than DuckDB for @tale_shape: Shaper is all about using SQL to build data visualizations and sharing them. There are many databases, but DuckDB and its extension system allow Shaper to query many different data sources, all from a single binary.

I sometimes forget that @tale_shape supports dark mode:

Shaper is open source for one reason: I am building the tool I wish I had. I don't want to keep user data in-house and not bother with regulations. And I never want to worry about integrating analytics too deeply into our product because the vendor might some day raise prices.