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A Complete Guide to an Interactive Geographical Map using Python

Ever wondered how these beautiful geographical maps are created? Our World in Data has an extensive collection of interactive data visualizations on aspects dedicated to the global changes in health, population growth, education, culture, violence, political power, technology and several things that we care about. These visualizations help us understand how and why the world has changed over the last few decades. I was intrigued with this wealth of information and motivated to dive deeper.

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Pre-requisites

Directory Layout

.
├── Interactive-choropleth-map-obesity.mov
├── README.md
├── bokeh-app
│   ├── data
│   │   ├── countries_110m
│   │   │   ├── ne_110m_admin_0_countries.README.html
│   │   │   ├── ne_110m_admin_0_countries.VERSION.txt
│   │   │   ├── ne_110m_admin_0_countries.cpg
│   │   │   ├── ne_110m_admin_0_countries.dbf
│   │   │   ├── ne_110m_admin_0_countries.prj
│   │   │   ├── ne_110m_admin_0_countries.shp
│   │   │   └── ne_110m_admin_0_countries.shx
│   │   └── obesity.csv
│   └── world_obesity.ipynb
├── docker
│   └── Dockerfile
└── docker-compose.yml

Running the sample

Step 1 : Starting docker container

$ git clone 
$ cd /root-dir-of-the-repository
$ docker-compose up

On the console output copy the jupyter notebook url e.g. http://localhost:8888/token?=xxxx and paste in your browser.

Step 2 : Execute Code

Open world_obesity.ipynb file and rull all cells.

Step 3 : Start bokeh server

In the browser using the jupyter notebook go to the Terminal

bokeh serve --show world_obesity.ipynb

Step 4 : Browse the interactive map

The interactive map is rendered by bokeh server which can be browsed at http://localhost:5006/

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Contains data and code used to create bokeh application of world obesity choropleth map

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  • Jupyter Notebook 98.4%
  • HTML 1.6%