[CARD] Population Demographics and Home Ownership Rates (Over Time?) #5
Description
Story Card Request
Project:
Card Title:
Card Document: (link here)
https://docs.google.com/document/d/1Uc3Xx2WId3Ni1hTBpGFrdf-vNJjaZ_Ez5hBCOTRJMIk/edit#heading=h.x803ue7k634x
Milestones
Setup
- Create Card Document from this template and link above
UI Components:
Chart / Map Components: CIVIC Sandbox Map
(Can we overlay two different metrics at once? Color & pattern, for example, for population share and homeownership rate?)
What types of user interaction are required?
Click a Census Tract to view detailed information about tract. (Demographic + Homeownership) (User changes years displayed on map?)
Type of data processing / analysis this story card uses
Each card can belong to one or more categories listed below
Proportion of Residents Identified as Black
Proportion of Residents Identified as Homeowners
- descriptive - simple data (re)-representation, doing summary statistics belongs to this category, we do this for all data sets
- explanatory - testing hypotheses and / or comparing data points
- predictive - any regression, model fitting, classification or clustering tasks
- prescriptive - when you want to recommend any action to be taken (we do this rarely, if at all)
Data documentation and proposed analysis
- Document metadata
- Decide whether to load to database or S3 with proper metadata documentation
- Review metadata and proposed data analysis
Include all API calls that will need to be made, including all params and the possible values for the params. The more specific the better! This will help prevent back and forth and ultimately make for a quicker turnaround.
Set up data processing development environment
- Clone repo from [template] (https://github.com/karenng-civicsoftware/HackORDataScienceTemplate)
- Set up access to GitHub repo for all team members
- Set up a container from a suitable version of the Dockerfile template
- Prototyping and testing analysis proposals
- Review additional proposed data analysis identified through prototyping
- Write code for reproducible data processing steps with proper version control & data lineage
- Data science results produced and documented
- Data science peer reviewed
Build APIs
- Database deployed to CIVIC Cloud
- Data science results available through API with all needed calculations, filters and queries
- Basic API in container
- Basic API deployed to CIVIC Cloud
- TBD process for API design - standardization?
- API endpoint with all needed calculations, filters and queries
Data visualization:
- Clear concept
- All components needed available in Storybook
- Components available in Storybook demonstrate all needed features
- Follows data visualization and interface guidelines available in Storybook
Design
- TBD Wireframes?
- TBD Design review?
Written content / additional links
- Write content
- Review content