A Step by step guide to create interactive map visuals in python using opensource libraries - Altair, Plotly, and Folium
Interactive choropleth map using Plotly in python — Image by author
Looking for a simple python library to create a choropleth map for your next web app or blog? Spent hours online looking for tutorials on how to get started? While there are a lot of popular libraries that can get you started with the simple implementation of static choropleth maps(matplotlib, seaborn etc), if Interactivity is what you are looking for, this is the article for you! While there are libraries like d3.js which can build custom maps, there are few simpler tools that you can explore. This blog talks about 3 such easy to implement but powerful opensource python libraries!
Overwhelmed and lost in Documentation?
Few months back , I wanted to create an interactive map for an interesting web app that we were developing. I spent hours online looking for the perfect library to get started with,but found it very difficult to run through the documentations, for there was no proper step by step guide for implementation and customizing the visuals as required. I wish I had a guide that compared the features and a proper implementation along with the details about customization.
This is an attempt to create such a guide.The following write-up compares and contrasts the implementation of an interactive choropleth map along with the details and possible customizations to get the final output as required, using three of the popular map libraries available for Python —
- Altair —Simple and fast implementation with readily available set of features and pre-defined functionalities.
- **Plotly **— Variety of available implementations including Mapbox,Custom configurations and styling.
- **Folium **— Leaflet implementation with complete customization and interactivity including tool-tips, pop-ups and a lot more features.
#folium #choropleth-map #plotly #data-visualization #python
