That’s exciting, but how are you going to get passed the inevitable conception that this is just another web framework in another hipster language? What would be the value prop to them?
Love it! Excited to try it out!
Excellent result. Congratulations
This library looks really interesting!
Does it support some kind of interaction between plots and tables? E.g. when a time range is selected in a plot, a table is automatically filtered to that range only.
Everything is fully reactive. I’m currently extending this demo by adding a form to filter the dataset which will update the whole dashboard.
Changing UI elements automatically updates a corresponding Julia value, for example a Julia range. If this range is Reactive/Observable then it triggers changes in its dependents: it updates the dataset, and the updated dataset is then propagated, updating all the UI components which display it.
In your example, the plot would need to trigger an event and update an underlying value in the model (for example a range), which would filter the dataset on the server, which would then propagate the new data onto the UI. I’m not sure if the plotting library I use here does it, but if not, the great part is that it’s relatively simple to integrate a different plotting library which exposes this behaviour.
One of the top goals was to allow using any Vue.js library, exposing all its features. And this part seems to work well already. The next part would be to create a rich ecosystem of packages and libraries which support a wide range of features.
I’m very excited to see this package.
Moving on with forms support: reactive check boxes!
This is looking great @essenciary! Keep the updates coming
Custom select with multiple options
Server-side loading state for data tables (the stripe under the header )
As an Interact.jl user, I’m glad to hear you’ll be supporting Observables! Along with the excellent plotting and dataframe elements posted here, I’m super excited to try Stipple.jl.
I would like to echo the sentiments others have expressed here. I find myself looking for updates on the progress almost daily. It looks fantastic.
New demo time!
k-means clustering exploratory data visualisation using the iris data set! Featuring the newly added slider component and the new scatter plots.
The full code:
Thank you, that’s very inspiring and motivating!
Agree! Really excited about the capabilities in this package. When do you expect to release it?