Data@Urban’s Top 5 Posts of 2021
Although researchers have developed an alternate method for comparing food insufficiency datasets from before and after the pandemic, three graphing tactics could more effectively visualize the sector's methodological challenges around missing data and comparability.
An automated quality check system is critical to project efficiency and data integrity. To meet that challenge for the Housing Policy Finance Center, we developed a comprehensive quality-checking system using an open-source, Python-based tool called Great Expectations.
A daily updated dashboard allows users to explore vaccination trends across the US, incorporating perspective on vaccine rollout disparities and how economic factors, like median income and job type, correlate with vaccination rates.
Urban partnered with Twin Cities organizations to inform equitable housing policy, showing the importance of working with local leaders, identifying data gaps early on, and using methods to make manual cleaning less painful.
Like good headlines, images, and pull quotes, a good chart can pack a punch. The Urban Institute revisited its data viz style guide to rethink not just the “what” and “how” of chart creation — but also the “why.”
The Data@Urban team: