plotly | An interactive graphing library for R | Data Visualization library

This isn't exactly what you're looking for. I was able to create a meaningful color bar, though.

I removed the call for interaction between the groups and created a separate trace. Then I created legend groups and named them to create separate legends for gender and age. When I pull color = out of the call to create a colorbar, this synced the color scales.

However, it assigns colors to the labels for age and gender and that's not meaningful! There are a few things that don't line up with your request, but someone may be able to build on this information.

This may not be what you want but you can do this by adding a runtime of shiny in your yaml

You were almost there.
The contours on z should be defined according to min-max values of z:

Found the problem.
I was installing pandas_profiling, and this package updated pyyaml to version 6.0 which is not compatible with the current way Google Colab imports packages.
So just reverting back to pyyaml version 5.4.1 solved the problem.

For more information check versions of pyyaml here.
See this issue and formal answers in GitHub

##################################################################
For reverting back to pyyaml version 5.4.1 in your code, add the next line at the end of your packages installations:

Looking at the plotly code here (excerpt below), it seems that the raster is only defined for any values of x and y available in the dataset - and whatever happens in between is up the the rest of the plotly code.

I adapted an example from the plotly community to your example and created the code. The point of creation is to create the data for each subplot and then switch between them by means of buttons. The sample data is created using representative companies of US stocks. one issue is that the title is set but not displayed. We are currently investigating this issue.

tran Try to replace your callback with this callback:

Adapting my answer on this post to your case (which draws on this answer) one option would be to manipulate the plotly object.

The issue is that with facetting we end up with one legend entry for each facet in which a group is present, i.e. the numbers in the legend entries correspond to the number of the facet or panel.

In plotly one could prevent the duplicated legend entries via the legendgroup argument. One option to achieve the same result when using ggplotly would be to assign the legendgroup manually like so:

This is serious hack territory, and the whole thing would be a lot simpler if this PR had been completed.

However, the code below should work (see codesandbox).

The key steps are:

1. Have a bit of state that keeps track of whether you have a url from the service or not.
2. When this state is "none", disable the facebook button's default behavior (i.e. openShareDialogOnClick = false)
3. Add an onClick handler to the facebook button that asynchronously fetches the url and sets the state (triggering a re-render)
4. Use an effect + ref so that when the url is set to something real, you manually call the click event on the button (which now has a real address in its url prop), and then re-sets the url to "none"