this adds a bit of context about when to use which library

Author: pvgenuchten

workshop/jupyter/content/notebooks/07-visualization.ipynb

@@ -8,10 +8,10 @@
     "When it comes to visualizing geospatial data with/on maps with Python, a great number of tools and techniques\n",
     "are available. In this lesson we will explore several of these:\n",
     "\n",
-    "* [Folium](https://github.com/python-visualization/folium)\n",
-    "* [ipyleaflet](https://ipyleaflet.readthedocs.io)\n",
-    "* [Bokeh](https://bokeh.pydata.org)\n",
-    "* [pydeck](https://pydeck.gl) - optional\n"
+    "* [Folium](#Folium)\n",
+    "* [ipyleaflet](#ipyleaflet)\n",
+    "* [Bokeh](#Bokeh)\n",
+    "* [pydeck](#pydeck)\n"
    ]
   },
   {
@@ -21,9 +21,8 @@
     "## Folium\n",
     "Whenever you visit a website that has some kind of interactive map, it\n",
     "is quite probable that you are witnessing a map that has been made with\n",
-    "a JavaScript library called [Leaflet](http://leafletjs.com). The\n",
-    "other popular libraries you may encounter are\n",
-    "[OpenLayers](https://openlayers.org) or [maplibre](https://maplibre.org/).\n",
+    "a JavaScript library called [Leaflet](http://leafletjs.com). Other popular libraries you may encounter are\n",
+    "[OpenLayers](https://openlayers.org) and [maplibre](https://maplibre.org/).\n",
     "\n",
     "The Python module \n",
     "[Folium](https://github.com/python-visualization/folium) makes\n",
@@ -167,7 +166,7 @@
    "source": [
     "### Folium and Streamlit\n",
     "Folium can also be [combined with Streamlit](https://folium.streamlit.app/). \n",
-    "[Streamlit](https://streamlit.io) is a platform to create interactive web apps for your python data scripts.",
+    "[Streamlit](https://streamlit.io) is a platform to create interactive web apps for your python data scripts.\n",
     "\n"
    ]
   },
@@ -179,12 +178,10 @@
     }
    },
    "source": [
-    "## Interactive maps in the Jupyter notebook with ipyleaflet\n",
-    "ipyleaflet is a Jupyter/Leaflet bridge enabling interactive maps in the Jupyter notebook.\n",
-    "(Although one can always save the results and use these maps in non-Jupyter contexts!).\n",
-    "\n",
-    "`ipyleaflet` is based on [ipywidgets](https://ipywidgets.readthedocs.io).\n",
-    "ipywidgets are interactive HTML widgets for Jupyter notebooks and the IPython kernel.\n",
+    "## ipyleaflet\n",
+    "[ipyleaflet](https://ipyleaflet.readthedocs.io) provides similar functionality as folium, however because\n",
+    "it is based on [ipywidgets](https://ipywidgets.readthedocs.io), it integrates with other components from\n",
+    "the ipywidgets ecosystem (sliders, datagrids, tabs).\n",
     "\n",
     "Links:\n",
     "\n",
@@ -453,8 +450,10 @@
    "source": [
     "## Bokeh\n",
     "\n",
-    "Bokeh is a very powerful framework to produce powerful maps in combination\n",
-    "with data. With Geopandas and Bokeh one can produce nice looking interactive maps like in the image below:\n",
+    "Bokeh is a powerful framework to produce tailored interactive map and data visualisations.\n",
+    "Map features are limited compared to Folium, but there are more options to tailor the behaviour.\n",
+    "Bokeh provides mechanisms to interact with a server side application. With Geopandas and Bokeh\n",
+    "one can produce a nice looking interactive map like in the image below:\n",
     "\n",
     "![Bokeh and Geopandas Example](images/bokeh-example1.jpg)\n",
     "*Interactive Map with Bokeh and GeoPandas - Source: [CSC L6](https://automating-gis-processes.github.io/CSC/lessons/L6/interactive-map-bokeh.html)*\n"
@@ -895,16 +894,16 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## pydeck - OPTIONAL\n",
-    "\n",
-    "[pydeck](https://pydeck.gl/) is a WebGL2-powered, highly performant large-scale data visualization framework.\n",
-    "We leave it you to explore pydeck through [its documentation](https://pydeck.gl/).\n",
+    "## pydeck\n",
     "\n",
-    "pydeck is part of [deck.gl](https://deck.gl/).\n",
+    "Up till this point we've looked at 2D data visualisations. With [pydeck](https://pydeck.gl/)\n",
+    "we switch to WebGL-powered data visualization, including 3D and vector tiles.\n",
+    "pydeck is a python wrapper for the [deck.gl](https://deck.gl/) javascript library.\n",
+    "deck.gl visualisations typically use a vector tile background (from [mapbox](https://mapbox.com), [maptiler](https://www.maptiler.com/), or similar)\n",
     "\n",
-    "![From deck.gl repo Example](images/deck.gl.jpg)\n",
+    "![Example by deck.gl](images/deck.gl.jpg)\n",
     "\n",
-    "From their [GitHub README](https://github.com/visgl/deck.gl):\n",
+    "From the [GitHub deck.gl README](https://github.com/visgl/deck.gl):\n",
     "\n",
     "*\"deck.gl is designed to simplify high-performance, WebGL-based visualization of large data sets.\n",
     "Users can quickly get impressive visual results with minimal effort by composing existing layers,\n",