Work From Home: A Rich vs. Poor Issue/An Urban vs. Rural Issue by Leonardo Nicoletti
For this project, I collaborated with another data scientist, Caroline Cullinan, to analyze Google mobility data from twelve countries. In conducting this analysis, Caroline and I had the goal of illustrating some of the inequalities that exist in the work-from-home paradigm. Conscious of the fact that this topic had already received a great deal of attention, we wanted to illustrate it through a novel visual storytelling angle.
In preparing this piece, we chose to tell the story with a cartogram approach. As such, preparing the data for this project was challenging. The UK local authority-level cartogram was relatively straightforward to create thanks to the d3-hexjson plugin (https://github.com/olihawkins/d3-hexjson). However, we could not find a publicly available data set representing a county-level cartogram for the US. Therefore, in order to create this data set, we used the tilemaps R library (https://github.com/kaerosen/tilemaps) and a greatly simplified version of US county geometries. Aside from this aspect of the project, the rest of the data preparation for this piece was done inside an Observable notebook (https://observablehq.com/@lnicoletti/wfh).
Creditshttps://www.carolinecullinan.com/ Caroline and I equally contributed to the storyboarding, data collection, data analysis, and data-preparation phases of the project. Caroline was responsible for writing the text throughout the piece. I designed and developed all data visualizations and interactive components. I also built the web-page in which hosts the piece.