This dashboard, allows a user to view state specific noncancerous mortality data the was collected and published by the Centers for Disease Control and Prevention (CDC). The dataset, Chronic Disease Indicators (CDI), contains over 100,000 data points. This file had to be sorted for valid data that pertained to diseases with mortality rates. The data was processed and converted to graphs for the user to visualize. The user is able to see trends with the diseases and is even able to see mortality rates for a future year given the current trends.
What was learned:
- This dashboard required a variety of Python libraries: Numpy, Pandas, SKLearn, Matplotlib, Ipywidgets to be able to process and visualize.
- How to clean data prior to using it
What can be improved:
- The dashboard is very basic and there are a variety of tools that could be use to enhance it
- Only a small fraction of the data was processed and visualized. Starting at over 100,000 data points, the final dataset only contained a few hundred to thousand points. More data could be viewed from this dataset