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Interactive-Data-Visualization-Dale-2023

These examples on Interactive Data Visualization in the web browser using Flask RESTful API and D3.js are compiled with some modifications from the book "Data Visualization with Python and JavaScript: Scrape, Clean, Explore, and Transform Your Data", Second Edition, written by Kyran Dale and published by O'Reilly Media in 2023. Some of them with D3.js are also duplicated on my VizHub. The examples related to Flask, SQLAlchemy, and marshmallow, and also MongoDB, BeautifulSoup (bs4), Scrapy, and Pandas were moved to my other repository.

In the book, Kyran Dale presents two web applications. The first one is built on Flask and is a RESTful API for communication between the database and other web applications. The second one is responsible for fetching the data and their interactive visualization. Those represent the microservice architecture.

The content of this repository is mainly front-end oriented and consists of two parts: a short introduction to JavaScript, HTML, CSS, Flex, SVG, Plotly, and D3.js in the sandbox folder and a final visualization project in the final_viz folder. The final_viz project with local data in JSON files (without using Flask and any database) running on a local HTTP server is shown in the image below.

.../project/final_viz$ python -m http.server 8080

Original code by Kyran Dale

https://github.com/Kyrand/dataviz-with-python-and-js-ed-2

Add JavaScript libs

By using Cloudflare’s Content Delivery Network JS

https://cdnjs.com/libraries/d3

<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/7.8.5/d3.min.js" charset="utf-8"></script>

or by using libraries placed locally

project/
|--static/
   |--libs/
      |--d3.v7.min.js
   |--js/

<script src="/static/libs/d3.v7.min.js"></script>

Use JavaScript scripts in Chrome

Start a development server in the project directory using Python’s http module:

python -m http.server 8080

Open the browser at:

http://localhost:8080/

Press Ctrl+Shift+J to open the Console tab in Chrome.

Press Ctrl+C to stop the web server.

Chrome

Press Ctrl+Shift+I to open the Elements tab (or More Tools -> Developer Tools / Weitere Tools -> Entwicklertools).

Jupyter

Start Jupyter notebooks:

$ jupyter notebook

Install TopoJSON globally

preconditions:

$ sudo apt update
$ sudo apt install npm

source: https://github.com/topojson/topojson-server/tree/master

$ sudo npm install -g topojson-server

Convert an input GeoJSON into an output TopoJSON

$ geo2topo geo_input.json > topo_output.json

You can also use the Python's topojson package.