in search for a solution to an unsolved problem, I came across the acs package. I assume, there's no way within the choropleth package to get any county information from data in the format [city, state]. That's why pre-processing with acs needs to be done.
I tried following code to get the county information on a city:
library(acs)
geo.lookup(state="CA", place="San Francisco")
> geo.lookup(state="CA", place="San Francisco")
state state.name county.name place place.name
1 6 California <NA> NA <NA>
2 6 California San Francisco County 67000 San Francisco city
3 6 California San Mateo County 73262 South San Francisco city
As we know, cities can be part of different counties. Most likely, I will go with the second
> geo.lookup(state="CA", place="San Francisco")[2,]
state state.name county.name place place.name
2 6 California San Francisco County 67000 San Francisco city
by default.
My question: Is there a way to get the state abbreviation, county name and county FIPS, too? I could not find the answer in the documentation.
Also, for further processing (matching with choroplethr), the last "County" in county.name and "city" in place.name need to be removed.
Here's how to add the state abbreviation, county name, and county FIPS to your example. R has built-in variables for state names and state abbreviations. For the FIPS codes, I read a csv file from the Census Bureau's website.
library(acs)
library(tidyverse)
states <- cbind(state.name, state.abb) %>% tbl_df()
fips <-
read_csv(
"https://www2.census.gov/geo/docs/reference/codes/files/national_county.txt",
col_names = c("state.abb", "statefp", "countyfp", "county.name", "classfp")
)
query <- geo.lookup(state = "CA", place = "San Francisco")[2, ] %>%
tbl_df() %>%
left_join(states, by = "state.name") %>%
left_join(fips, by = c("county.name", "state.abb"))
query
# # A tibble: 1 x 9
# state state.name county.name place place.name state.abb statefp countyfp classfp
# <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr> <chr>
# 1 6 California San Francisco County 67000 San Francisco city CA 06 075 H6
As you note at the end of your question, you may need to clean up this data a bit more to make it fit choroplethr.