Data scientists, analysts, and developers are proficient in creating static maps but what about interactive ones? An interactive map of Los Angeles neighborhoods will be made via Python’s Bokeh library to show how quickly one can be built.
Maps are crucial for showing differences between regions. However, what happens when users want to see regional changes over a range of time periods for a variety of variables? One map may not be enough. Rather than creating many maps for all your user’s needs, an interactive map allows the viewer to choose the time period and variables of interest. In order to get a better sense of the process of making an interactive map, a map of Los Angeles neighborhoods will be built live using Python’s Bokeh library.
The presentation will cover how to add features and widgets such as a hovertool, selection form, and mouse selection click to a map. We will also go over the important modify_doc and update functions that are crucial for an interactive map to be able to respond to input changes from a viewer. We’ll deploy to a Google Cloud server, discuss when to build an interactive map, and best practices for designing one.
Knowledge of certain data visual python libraries such as matplotlib or seaborn, in addition to basic python functionality, will be assumed. This is a presentation geared for intermediate python users.