Creating Geospatial Heatmaps With Plotly Express MapBox and Folium in Python - Data Visualisation
Heatmaps, also known as Density Maps, are data visualisations that display the spatial distribution of a variable across a geographic area. They can be great tools for visualising and identifying trends, supporting decision-making, detecting outliers, and creating compelling visualisations for presentations.
There are several mapping Python libraries available; however, two very popular and easy-to-use libraries are Folium and Plotly Express.
Folium is a great library that makes it easy to visualise geospatial data. It is powered by Leaflet.js, which is a leading javascript mapping library and is platform-independent. Plotly is a popular library for creating powerful interactive data visualisations with very few lines of code and can be used to create interactive maps with MapBox.
This video will show how we can use these two libraries to visualise acoustic compressional slowness data on the Norwegian Continental Shelf.
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