Added new dashboarding tool overview article and updated the dashboar…

…ding section

doc/dashboarding/index.md

@@ -1,18 +1,22 @@
 # Dashboarding tools
 
-Just about any Python library can be used to create a "static" PNG, SVG, HTML, or other output that can be pasted into a presentation, sent in an email, published as a figure in a paper, and so on.  Many people also want or need to create "live" Python-backed applications or dashboards that a user can interact with to explore or analyze some data. Python offers several libraries for this purpose. The four main tools designed specifically for web-based dashboarding in Python are:
+Just about any Python library can be used to create a "static" PNG, SVG, HTML, or other output that can be pasted into a presentation, sent in an email, published as a figure in a paper, and so on.  Many people also want or need to create "live" Python-backed applications or dashboards that a user can interact with to explore or analyze some data. Python offers several libraries for this purpose. When PyViz.org was created, the four main tools designed specifically for web-based dashboarding in Python were:
 
 - [Dash](https://plot.ly/products/dash) (from [Plotly](https://plot.ly)); see the [blog post](https://medium.com/@plotlygraphs/introducing-dash-5ecf7191b503)
 - [Panel](https://panel.pyviz.org) (from [Anaconda](http://anaconda.com)); see the [blog post](https://medium.com/@philipp.jfr/panel-announcement-2107c2b15f52)
 - [Voila](https://github.com/QuantStack/voila) (from [QuantStack](http://quantstack.net)); see the [blog post](https://blog.jupyter.org/and-voil%C3%A0-f6a2c08a4a93); used with separate layout tools like 
 [jupyter-flex](https://github.com/danielfrg/jupyter-flex) or templates like [voila-vuetify](https://github.com/voila-dashboards/voila-vuetify).
 - [Streamlit](https://www.streamlit.io); see the [blog post](https://towardsdatascience.com/coding-ml-tools-like-you-code-ml-models-ddba3357eace)
 
-You can see comparisons of these tools in:
+Since then, dozens of other libraries have been created, all of which are listed at [pyviz.org/tools#dashboarding](https://pyviz.org/tools#dashboarding). Some of them are compared in these overview articles:
+
+- [A Survey of Python Frameworks](https://ploomber.io/blog/survey-python-frameworks/), 25 Sep 2024: Ellie Ko. Comparing Streamlit, Shiny for Python, Panel, Flask, Chainlit, Dash, Voila, and Gradio.
+
 - [Streamlit vs Dash vs Voilà vs Panel — Battle of The Python Dashboarding Giants](https://medium.datadriveninvestor.com/streamlit-vs-dash-vs-voil%C3%A0-vs-panel-battle-of-the-python-dashboarding-giants-177c40b9ea57)
-  30 Mar 2021 Stephen Kilcommins. Comparing Streamlit, Dash, Voilà, and Panel for dashboarding. Links to more detailed explorations for each library individually.
+  30 Mar 2021: Stephen Kilcommins. Comparing Streamlit, Dash, Voilà, and Panel for dashboarding. Links to more detailed explorations for each library individually.
+
 - [Are Dashboards for Me?](https://towardsdatascience.com/are-dashboards-for-me-7f66502986b1)
-  7 Jul 2020 Dan Lester. Overview of Python and R dashboard tools, including Voila, ipywidgets, binder, Shiny, Dash, Streamlit, Bokeh, and Panel.
+  7 Jul 2020: Dan Lester. Overview of Python and R dashboard tools, including Voila, ipywidgets, binder, Shiny, Dash, Streamlit, Bokeh, and Panel.
 
 There are also other tools that can be used for some aspects of dashboarding as well as many other tasks:
 

doc/overviews/index.md

@@ -6,6 +6,8 @@ The Python visualization landscape can seem daunting at first. These overviews a
 
 <em>Adaptation of <a href="https://www.youtube.com/watch?v=FytuB8nFHPQ">Jake VanderPlas' graphic</a> about the Python visualization landscape, by Nicolas P. Rougier</em>
 
+- [A Survey of Python Frameworks](https://ploomber.io/blog/survey-python-frameworks/), 25 Sep 2024: Ellie Ko. Comparing Streamlit, Shiny for Python, Panel, Flask, Chainlit, Dash, Voila, and Gradio.
+
 - [The Power of Pandas Plots: Backends](https://towardsdatascience.com/the-power-of-pandas-plots-backends-6a08d52071d2), 29 Aug 2024: Pierre-Etienne Toulemonde. Comparing matplotlib, plotly, and hvPlot for plotting with Pandas.
 
 - [7 Best Python Libraries For Data Visualisation](https://medium.com/@inverita/7-best-python-libraries-for-data-visualisation-517020f725a4), 25 Jan 2024: inVerita. Comparing Matplotlib, Seaborn, Plotly, Bokeh, Altair, and HoloViews.