Introduction to Maps in Folium and Python

Install Python and verify it’s added to your system path by typing Python in the terminal, then install Jupyter Notebook via Anaconda for Windows, launch it, and rename the notebook.

Create your folium map by loading Waterwatch suburbs dataset from GitHub, installing folium, pandas, and openpyxl, and building an interactive map with OpenStreetMap centered on Cape Town at zoom 10.

Plot and style markers on a folium map, switching from the default base map to Cartodb dark matter, and add popups with suburb names while customizing marker icons.

Classify markers by water consumption thresholds on folium maps, using five and eight kiloliters to color suburbs green, blue, or red, with popups and icons.

Use the measure control to measure boundaries by importing datasets from GitHub, merging them into a single dataframe, and plotting dam locations on a folium map with markers and popups.

Create a Folium map using a custom web map tile service, then plot dam locations and attach a measure control to measure dam boundaries and display area measurements.

Learn to build an interactive folium map in Python by creating and configuring a layer control with multiple web map tile services, updating the base map, and displaying tile layers.

Create a heat map in folium by plotting suburb coordinates as circle markers on a Cartodb base map and feeding them to a heat map layer to show concentration density.

Export heat map and unemployment choropleth map as HTML files to run as interactive web maps in a browser, using an export_maps function to save Leaflet.js powered content.