Whether for business, research, or personal aims, dashboarding is an in demand feature in today's business and tech worlds. With companies like Salesforce, Power BI, and Domo gaining popularity, learning how to create and maintain dashboards has become an in-demand workforce skill. Although these services offer easy hands-on dashboarding frameworks and other amenities such as training and tech support, none are cheap, and companies may be turned away from purchasing a license unless they can justify the cost.
For this reason, Python presents a simple viable alternative to it's pricey counterparts, offering a free dashboarding framework through its package Dash, a vast online support community, and plenty of examples and entry-level code to get started. This article presents the utility of Python's Dash package as a powerful data dashboarding tool, and illustrate's ability to create powerful and clear data presentation with open source data. The current project will offer a full beginning-to-end demonstration on how to create a data dashboard, starting with COVID data from NYT's Github repository, which provides daily COVID cases and deaths data for all US counties starting in early March 2020, and is updated daily. These data provide a natural opportunity to create a dashboard with meaningful and relevant health trends, and compare trends across counties and states.
The current project uses the Bokeh package to create an interactive dashboard to view and compare user selections across datasets, and allows users to dynamically explore their own data, as well as download it for later reference.
- Tyoe your favorite strains in the text box, and they will appear as dots on the graph:/li>
- Each point is a strain, BLUER strains are more Indica dominant, while REDDER strains are more Sativa
- Strains further UP on the graph are more highly rated, and strains further RIGHT on the graph have higher THC content
- Each strain's flavor profiles are highlighted in the table below the graph. Terpine info to follow!