Get the Data

Below are the aggregate data used in the Eviction Tracking System. We hope that you find new and productive ways to make use of them. When you do so, please cite as follows:

Peter Hepburn, Jacob Haas, Renee Louis, Adam Chapnik, Danny Grubbs-Donovan, Olivia Jin, Jasmine Rangel, and Matthew Desmond. Eviction Tracking System: Version 2.0. Princeton: Princeton University, 2020. www.evictionlab.org

Scroll below the data table to find code samples for using the data in your own applications. Please submit additional examples!

A data dictionary for these downloadable files can be found here.

Note: Some eviction filing data have a number of cases with missing or incorrect tract/zip code information. These cases will be listed in rows where the tract/zip is described as “sealed”. Values of filings by tract/zip may be underestimates as a result.

Site Baseline Years Smallest Geography Weekly Data Monthly Data
All Cities - Census Tract / ZIP Code Download CSV Download CSV
All States - Census Tract / ZIP Code Download CSV Download CSV
Albuquerque 2017-2019 Census Tract Download CSV Download CSV
Austin 2014-2019 ZIP Code Download CSV Download CSV
Boston 2012, 2013, 2015, 2016 Census Tract Download CSV Download CSV
Bridgeport 2017-2019 Census Tract Download CSV Download CSV
Charleston 2016-2019 Census Tract Download CSV Download CSV
Cincinnati 2012-2016 Census Tract Download CSV Download CSV
Cleveland 2016-2019 Census Tract Download CSV Download CSV
Columbus 2012, 2013, 2015 Census Tract Download CSV Download CSV
Connecticut 2017-2019 Census Tract Download CSV Download CSV
Dallas 2017-2019 Census Tract Download CSV Download CSV
Delaware 2016-2019 Census Tract Download CSV Download CSV
Fort Worth 2016-2019 Census Tract Download CSV Download CSV
Gainesville 2017-2019 Census Tract Download CSV Download CSV
Greenville 2016-2019 Census Tract Download CSV Download CSV
Hartford 2017-2019 Census Tract Download CSV Download CSV
Houston 2012-2015 Census Tract Download CSV Download CSV
Indiana 2016-2019 Census Tract Download CSV Download CSV
Indianapolis 2016-2019 Census Tract Download CSV Download CSV
Jacksonville 2012-2016 Census Tract Download CSV Download CSV
Kansas City 2012-2015 Census Tract Download CSV Download CSV
Las Vegas 2016-2019 Census Tract Download CSV Download CSV
Miami-Ft. Lauderdale 2014-2019 Tract (County for Miami-Dade) Download CSV Download CSV
Memphis 2016-2019 Census Tract Download CSV Download CSV
Milwaukee 2012-2016 Census Tract Download CSV Download CSV
Minneapolis-Saint Paul 2012-2019 Census Tract Download CSV Download CSV
Minnesota 2012-2019 Census Tract Download CSV Download CSV
Missouri 2012-2015 Census Tract Download CSV Download CSV
Nashville 2017-2019 ZIP Code Download CSV Download CSV
New Mexico 2017-2019 Census Tract Download CSV Download CSV
New Orleans 2019 Census Tract Download CSV Download CSV
New York 2016-2018 ZIP Code Download CSV Download CSV
Pennsylvania 2016-2019 ZIP Code Download CSV Download CSV
Philadelphia 2016-2019 Census Tract Download CSV Download CSV
Phoenix 2015-2019 Census Tract Download CSV Download CSV
Pittsburgh 2016-2019 ZIP Code Download CSV Download CSV
Providence 2016-2019 Census Tract Download CSV Download CSV
Rhode Island 2016-2019 Census Tract Download CSV Download CSV
Richmond 2016-2019 ZIP Code Download CSV Download CSV
South Bend 2016-2019 Census Tract Download CSV Download CSV
St Louis 2012, 2013, 2015, 2016 Census Tract Download CSV Download CSV
Tampa 2016-2019 Census Tract Download CSV Download CSV
Virginia 2016-2019 ZIP Code Download CSV Download CSV
Wilmington 2016-2019 Census Tract Download CSV Download CSV
Wisconsin 2016-2018 Census Tract Download CSV Download CSV

Sample code:

# Sample R code to plot weekly filings
# For Milwaukee until week 24 (06/13/2020)

# library(dplyr)
# library(tidyr)
# library(ggplot2)

mke_tract_week_2020 %>%   
  group_by(week, week_date) %>% 
  summarize(filings_2020 = sum(filings_2020),
            filings_avg = sum(filings_avg, na.rm = T)) %>%
  pivot_longer(cols = filings_2020:filings_avg,
               names_to = "year",
               values_to = "filings",
               names_prefix = "filings_") %>% 
  mutate(year = recode(year,
                       avg = "2012-2016")) %>% 
  ggplot(aes(x = week,
             y = filings)) +
  geom_line(aes(color = year)) +
  labs(title = "Milwaukee Weekly Eviction Filings")

Last Updated: January 28, 2022