R | lubov mckone

Adjusting Course Toward Equity Lessons Learned in Boston's COVID Housing Recovery Plan

Mon, 12 Apr 2021 15:15:00 +0000

A presentation I prepared for the Spring 2021 National Human Services Data Consortium, detailing how the City of Boston’s Supportive Housing Division identified and corrected inequities in its housing matching algorithm.

You can listen to the recording here and find the slides here

TidyTuesday

Tue, 15 Dec 2020 00:00:00 +0000

An archive of my #TidyTuesday visualizations and code. #TidyTuesday is a weekly data challenge founded in 2018 by Thomas Mock and organized by the R4DS (“R for Data Science”) online learning community. Each week, a new dataset is provided at TidyTuesday for members of the community to practice cleaning, reshaping, and visualizing via the tidyverse collection of R packages.

12.15.2020: American Ninja Warrior (code)

11.24.2020: Washington Hiking Trails (code)

Boston Evictions Shiny App

Tue, 01 May 2018 00:00:00 +0000

Purpose and Background

The purpose of this project was to help the Office of Housing Stability gain insight from their eviction data. The main objectives were to help the office understand geographic variation in evictions, the property managers who were evicting the most tenants, and to evaluate the City’s progress on reducing evictions.

Data

The data underlying this application was intially collected by volunteers who transcribed physical records from Boston’s Housing Court into an excel spreadsheet. The data was cleaned and reshaped for visualization in the app. The app includes data on evictions from 2014-2016.

App and Screenshots

Open app (Credentials required)

The app is secured to protect individual-level data. The screenshots below show the appearance and capabilities of the application.

R | lubov mckone

Adjusting Course Toward Equity Lessons Learned in Boston's COVID Housing Recovery Plan

TidyTuesday

12.15.2020: American Ninja Warrior (code)

11.24.2020: Washington Hiking Trails (code)

Boston Evictions Shiny App

Purpose and Background

Data

App and Screenshots

Filters and appearance

Levels of Geographic Visualization

Street-Level Insight

Export the underlying data

Built with