Interactive Data Visualization Python. Before we build anything let s install dependencies. Any good data visualization starts with you guessed.
Generating your first figure. Let s explore each step in more detail. Study and use python interactive libraries such as bokeh and plotly explore different visualization principles and understand when to use which one create interactive data visualizations with real world data.
I like to use pipenv but the same applies.
Since this article is not a tutorial on jupyter. The library is also provided for r and javascript and is written on the basis of the very popular javascript visualization library d3. Once we are there we can start adding some code. Since this article is not a tutorial on jupyter.
