An R package with various functions to study neighborhood dynamics.
devtools::install_github("timathomas/neighborhood", ref = "main")
The Neighborhood Racial Typologies function is a descriptive, categorical tool to help identify racial and ethnic divides within a region (e.g. city, county, state, etc.). Traditional segregation measures, such as the disimilarity index, provide a single measure for a large geographical area. This descripitve function is useful for mapping tract level, small area (e.g. neighborhood level) divisions between ethnic and racial groups.
This function is based off this paper: Hall, Matthew, Kyle Crowder, and Amy Spring. 2015. “Neighborhood Foreclosures, Racial/Ethnic Transitions, and Residential Segregation.” American Sociological Review 80:526–549.
nt: Neighborhood Racial Typologies
ntdf: create the dataframe for nt
ntcheck: identify counts that can be concatenated
You can view an interactive map using this function here.
Baltimore_nt <- ntdf(state = "MD", county = "Baltimore City", geometry = TRUE) cal <- ntdf(state = "CA") ny <- ntdf(state = "NY") glimpse(Baltimore_nt) ps_nt <- ntdf(state = "WA", county = c("Snohomish", "King", "Pierce"), geometry = TRUE) # Check to see if there are duplicate tract assumptions. Baltimore_nt %>% st_set_geometry(NULL) %>% mutate(val = 1) %>% spread(NeighType, val, fill = 0) %>% mutate_at(vars(`All Black`:`White-Shared`), list(as.numeric)) %>% select(13:ncol(.)) %>% mutate(rowsum = rowSums(.)) %>% filter(rowsum > 1) %>% glimpse()
After running the above code, look at the counts and consider concatenating and/or reducing outlying (small count) neighborhood types.
ntcheck(Baltimore_nt) ntcheck(cal) ntcheck(ny) ntcheck(ps_nt)
nt_conc field concatenates the
NeighType field automatically and may satisfy most people.
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