read.acs: Reads a comma-delimited file from the American Community Survey and creates an acs object with data, standard errors, and associated metadata.

Description

When passed a comma-delimited file downloaded from the U.S. Census American Community Survey (typically downloaded via the FactFinder website and unzipped), read.acs returns an acs object with data, standard errors, and associated metadata.

Usage

read.acs(filename, endyear = "auto", span = "auto", acs.units = "auto",
geocols = "auto", skip = 1)

Arguments

filename

the csv (or .txt) file to be input

endyear

an integer indicating the latest year of the data in the survey (e.g., for data from the 2005-2009 5-year ACS data, endyear would be 2009)

span

an integer (should be 1, 3, or 5), or "auto" to have read.acs guess the span from the filename (e.g., for data from the 2005-2009 5-year ACS data, span would be 5)

acs.units

a vector of factors indicating what sort of data is contained within each column of data ("count","dollars","proportion", "ratio", "other")

geocols

a vector of integers (length must be 4) indicating which columns contain the geographic header information; defaults to "auto", which is the same as 1:4

skip

an integer indicating how many rows to skip before processing the csv file; defaults to 1

Value

Returns a valid acs-class object with estimates, standard errors (derived from the census 90% margins of error), and metadata associated with the survey,

Details

After executing a query on the U.S. Census American FactFinder site (http://factfinder2.census.gov), users can download their results as a zip file containing data in comma-delimited file format(for example, "dt_acs_2009_5yr_g00__data1.txt"). read.acs simplifies the creation of new acs objects from these files.

At present, read.acs is somewhat limited, and much work needs to be done to improve import of data. Currently, the function expects the first four columns of filename to include geographic headers (this can be overidden through the geocols option), and by default skips the first row of data (which usually contains the Census Bureau's non-descriptive table codes). Column names are extracted from the second row of the file, as would normally happen with read.csv(skip=1). When no other values are provided, read.acs will attempt to determine endyear and span from the filename.

(The Census Bureau is also in the process of converting from "legacy" FactFinder to "FactFinder2," which has introduced additional confusion about the exact export format to use as a standard. Future versions are intended to resolve/avoid this problem.)