docs: Split interactive docs section into subpages (#3561)

* Split interactivity doc section into subpages To make it easier to navigate instead of having one giant page. * Move JupyterChart under main interactivity section The parts about performance and JupyterChart are under the Large Datasets section, so it seems natural that the part about interactivity would go together with the other interactive parts of the library. * Note that streamlit can access params from python * Standardize use of ampersand in headings * Remove dashboard sentence from JupyterChart page * Add heading to interaction landing page I think this looks more pleasing as content without a right-side ToC stretches wider across the page. * fix: Add missing imports to `altair-plot` directives * Reword interactive intro * Apply suggestions from code review Co-authored-by: Dan Redding <125183946+dangotbanned@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: Dan Redding <125183946+dangotbanned@users.noreply.github.com> --------- Co-authored-by: Dan Redding <125183946+dangotbanned@users.noreply.github.com>
vega · Aug 31, 2024 · 5b58779 · 5b58779
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diff --git a/doc/user_guide/compound_charts.rst b/doc/user_guide/compound_charts.rst
@@ -2,8 +2,8 @@
 
 .. _user-guide-compound:
 
-Layered and Multi-View Charts
------------------------------
+Layered & Multi-View Charts
+---------------------------
 Along with the basic :class:`Chart` object, Altair provides a number of
 compound plot types that can be used to create stacked, layered, faceted,
 and repeated charts. They are summarized in the following tables:

diff --git a/doc/user_guide/data.rst b/doc/user_guide/data.rst
@@ -620,14 +620,13 @@ data before usage in Altair using GeoPandas for example as such:
    encodings/index
    marks/index
    transform/index
-   interactions
+   interactions/index
    compound_charts
    scale_resolve
    times_and_dates
    customization
    configuration
    saving_charts
-   jupyter_chart
 
 
 .. toctree::

diff --git a/doc/user_guide/display_frontends.rst b/doc/user_guide/display_frontends.rst
@@ -171,7 +171,7 @@ Package
 `Marimo <https://docs.marimo.io/guides/plotting.html>`_                                                                              ✔                                    ✔
 `Shiny <https://shiny.posit.co/py/docs/ipywidgets.html#quick-start>`_ using :ref:`JupyterChart <user-guide-jupyterchart>`            ✔                                    ✔
 `Solara <https://solara.dev/api/altair>`_                                                                                            ✔                                    ✔
-`Streamlit <https://docs.streamlit.io/library/api-reference/charts/st.altair_chart>`_                                                ✔                                              
+`Streamlit <https://docs.streamlit.io/library/api-reference/charts/st.altair_chart>`_                                                ✔                                    ✔
 ===================================================================================================================================  ===================================  =============================
 
 The above mentioned frameworks all require you to run a web application on a server if you want to share your work with others. A web application gives you a lot of flexibility, you can for example fetch data from a database based on the value of a dropdown menu in the dashboard. However, it comes with some complexity as well.