There are several R packages that make working with US Census data easier. The two I use most frequently are tigris(for loading the spatial data) and acs (for loading the tabular data).
However, one problem I keep running into is that I can't figure out an efficient, reliable way to determine all of the tracts (or block groups, zip codes, etc.) within a Place without leaving the R console.
For instance, if I wanted to work with census block data in Seattle I would begin by using tigris::tracts to download the spatial data for King County, WA:
library(tigris)
tr <- tigris::tracts(state = "WA", county = "King")
But unfortunately there's no obvious way to subset this data to include only the tracts in Seattle.
glimpse(tr)
Observations: 398
Variables: 12
$ STATEFP (chr) "53", "53", "53", "53", "53", "53", "53", ...
$ COUNTYFP (chr) "033", "033", "033", "033", "033", "033", ...
$ TRACTCE (chr) "003800", "021500", "032704", "026200", "0...
$ GEOID (chr) "53033003800", "53033021500", "53033032704...
$ NAME (chr) "38", "215", "327.04", "262", "327.03", "3...
$ NAMELSAD (chr) "Census Tract 38", "Census Tract 215", "Ce...
$ MTFCC (chr) "G5020", "G5020", "G5020", "G5020", "G5020...
$ FUNCSTAT (chr) "S", "S", "S", "S", "S", "S", "S", "S", "S...
$ ALAND (dbl) 624606, 3485578, 17160645, 15242622, 10319...
$ AWATER (dbl) 0, 412526, 447367, 526886, 175464, 0, 4360...
$ INTPTLAT (chr) "+47.6794093", "+47.7643848", "+47.4940877...
$ INTPTLON (chr) "-122.2955292", "-122.2737863", "-121.7717...
Similarly, the acs package allows users to create subsets of census data using the geo.make function, but in my example this won't help me if I don't already have the list of tracts GEOIDs for all of the Seattle tracts.
For the record, I am aware that it is possible to determine this information elsewhere. This page in the Census.gov FAQ gives clear instructions on how to determine all the tracts in a given census Place. But given that this is a crucial step in many census-related analyses, it would be best if there was a convenient way to do it from the R console.
Thanks in advance.
Although this question deals with spatial data, I am most interested in finding a non-spatial solution. For instance, I would prefer to a solution that queries the Census API and returns the returns a vector of the desired GEOIDs to a solution that employs a spatial analysis tool (e.g., rgeos::intersects) to create the vector. Why? Because spatial approaches are simply more prone to error in this process and this is known information we're talking about, not something that needs to be inferred spatially.
I often need the same kind of data so I wrote a R package to do this job. This package is called totalcensus. You can find it here https://github.com/GL-Li/totalcensus.
With this package, you can get data at tract, block group, or block level of towns, cities, counties, metro areas and all other geographic areas very easily. For example if you want to get the race data at block group level of various areas from 2011-2015 ACS 5-year survey, simply run code like below:
mixed <- read_acs5year(
year = 2015,
states = c("ut", "ri"),
table_contents = c(
"white = B02001_002",
"black = B02001_003",
"asian = B02001_005"
),
areas = c(
"Lincoln town, RI",
"Salt Lake City city, UT",
"Salt Lake City metro",
"Kent county, RI",
"COUNTY = UT001",
"PLACE = UT62360"
),
summary_level = "block group"
)
It returns data like:
# area GEOID lon lat state population white black asian GEOCOMP SUMLEV NAME
# 1: Lincoln town, RI 15000US440070115001 -71.46686 41.94419 RI 1561 1386 128 47 all 150 Block Group 1, Census Tract 115, Providence County, Rhode Island
# 2: Lincoln town, RI 15000US440070115002 -71.47159 41.96754 RI 916 806 97 0 all 150 Block Group 2, Census Tract 115, Providence County, Rhode Island
# 3: Lincoln town, RI 15000US440070115003 -71.47820 41.96364 RI 2622 2373 77 86 all 150 Block Group 3, Census Tract 115, Providence County, Rhode Island
# 4: Lincoln town, RI 15000US440070115004 -71.47830 41.97346 RI 1605 1516 43 0 all 150 Block Group 4, Census Tract 115, Providence County, Rhode Island
# 5: Lincoln town, RI 15000US440070116001 -71.44665 41.93120 RI 948 764 0 0 all 150 Block Group 1, Census Tract 116, Providence County, Rhode Island
# ---
# 1129: Providence city, UT 15000US490050012011 -111.82424 41.69198 UT 2018 1877 0 0 all 150 Block Group 1, Census Tract 12.01, Cache County, Utah
# 1130: Providence city, UT 15000US490050012012 -111.80736 41.69323 UT 1486 1471 0 0 all 150 Block Group 2, Census Tract 12.01, Cache County, Utah
# 1131: Providence city, UT 15000US490050012013 -111.81310 41.65837 UT 1563 1440 15 0 all 150 Block Group 3, Census Tract 12.01, Cache County, Utah
# 1132: Providence city, UT 15000US490050012022 -111.85231 41.68674 UT 3894 3594 0 0 all 150 Block Group 2, Census Tract 12.02, Cache County, Utah
# 1133: Providence city, UT 15000US490059801001 -111.64525 41.67498 UT 118 118 0 0 all 150 Block Group 1, Census Tract 9801, Cache County, Utah