Portfolio

Baltimore Quality of Life Index

Project Overview + Objective

Have you ever wondered how various aspects of a neighborhood affect the quality of life for its residents? For this project, I used data points from Baltimore's Neighborhood Indicators Alliance (BNIA) database to create a Quality of Life (QOL) score. My QOL score assigns a value to each neighborhood based on its rank in six different connectedness measures concerning: commute time to work, rent affordability, number of businesses, public art per 1,000 residents, and number of residents living below the poverty line.

Have you ever wondered how various aspects of a neighborhood affect the quality of life for its residents? This project used Baltimore neighborhood data, such as proliferation of art installations, average commute times, and number of small businesses from Baltimore City's open source data (data.baltimorecity.gov) to plot neighborhoods on a quality of life score. The resulting visual is evidence for city council and administrative team to argue for business and art development dollars in under served areas of the city.

Data Exploration + Design Iteration

Initial data exploration involved looking through correlations between all neighborhood indicators from the BNIA database. I used R to calculate correlations and examined results in Excel. After this first pass, it was back to the drawing board. I wasn't happy with the correlation data and needed to find a different approach for analyzing and creating discourse around Baltimore neighborhood quality of life.

R script running correlations between neighborhood environmental variables.

Correlations were as expected but not compelling in regards to neighborhood relationships.

Data Exploration + Design Iteration

After some sketching and deciding on a scatterplot for the main visual, an index started to emerge as a way to plot an assigned score for each neighborhood. The six data points listed above stood out in the R correlation analysis and were what I moved forward with.

I chose these 6 indicators because a discourse around connectedness and disconnectedness started to emerge. I assigned 3 to each and plotted each neighborhood against the mean. In the visual below, Canton, is a neighborhood with a higher quality of life score. Its residents experience lower levels of disconnectedness and higher levels of connectedness (compared to the mean).

Sketching design layout and graph ideas.

After doing my initial work in Tableau, assigning neighborhood to their calculated scores, I exported the main scatter plot graph image and uploaded into Illustrator for high-touch design work on layout and color. From there, I added the stacked bar charts in the top right using Illustrator to create.

Scatterplot uploaded into Illustrator for continued design work.

Click to view final piece.