update documentation examples re #90

DESCRIPTION

@@ -8,7 +8,7 @@ Description: A wrapper for the U.S. Census Bureau APIs that returns data frames
 	Small Area Income and Poverty Estimates, Population Estimates and Projections, and more.
 URL: https://www.hrecht.com/censusapi/, https://github.com/hrecht/censusapi
 BugReports: https://github.com/hrecht/censusapi/issues
-Depends: R (>= 3.5.0)
+Depends: R (>= 3.5)
 License: GPL-3
 LazyData: true
 RoxygenNote: 7.3.1

NEWS.md

@@ -1,8 +1,9 @@
 # censusapi 0.9.0 
 * The use of a Census Bureau API key (the `key` parameter) is no longer required with `getCensus()`. Users are still encouraged to register for and use an API key because the Census Bureau may rate limit IP addresses, but it is not required.
 * `getCensus()` automatically converts data columns in the Household Pulse Survey to numeric.
+* Increases required version of R from >=3.0 to >=3.5 based on httr dependency.
 * A new online [frequently asked questions article](https://www.hrecht.com/censusapi/articles/frequently-asked-questions.html) improves documentation.
-* Documentation is updated with new datasets, including more examples from the 2020 Decennial Census and the Household Pulse Survey.
+* Documentation is updated to use newly released datasets.
 
 # censusapi 0.8.0 
 * `listCensusApis()` has new columns in the resulting data frame of available API endpoints: the API `contact` email address and `type`: either Aggregate, Timeseries, or Microdata.

R/getcensus_functions.R

@@ -159,8 +159,8 @@ getFunction <- function(apiurl, name, key, get, region, regionin, time, year, da
 #' @keywords api
 #' @examples
 #' \dontrun{
-#' # Get total population and median household income for places (cities, towns, villages)
-#' # in a single state from the 5-year ACS.
+#' # Get total population and median household income for Census places
+#' # (cities, towns, villages) in a single state from the 5-year American Community Survey.
 #' acs_simple <- getCensus(
 #'   name = "acs/acs5",
 #'   vintage = 2022,
@@ -181,32 +181,34 @@ getFunction <- function(apiurl, name, key, get, region, regionin, time, year, da
 #' # Retreive 2020 Decennial Census block group data within a specific Census tract,
 #' # using the regionin argument to precisely specify the Census tract, county,
 #' # and state.
-#' block_group <- getCensus(
+#' decennial_block_group <- getCensus(
 #' 	name = "dec/dhc",
 #' 	vintage = 2020,
 #' 	vars = c("NAME", "P1_001N"),
 #' 	region = "block group:*",
 #' 	regionin = "state:36+county:027+tract:220300")
-#' head(block_group)
+#' head(decennial_block_group)
 #'
-#' # Get poverty rates for children and for people of all ages over time using the
+#' # Get poverty rates for children and for people of all ages beginning in 2000 using the
 #' # Small Area Income and Poverty Estimates API
 #' saipe <- getCensus(
 #'   name = "timeseries/poverty/saipe",
 #'   vars = c("NAME", "SAEPOVRT0_17_PT", "SAEPOVRTALL_PT"),
 #'   region = "state:01",
-#'   time = "from 2000 to 2022")
+#'   time = "from 2000")
 #' head(saipe)
 #'
-#' # Get County Business Patterns data for a specific NAICS sector.
-#' cbp_2016 <- getCensus(
-#'  name = "cbp",
-#'   vintage = "2016",
-#'   vars = c("EMP", "ESTAB", "NAICS2012_TTL", "GEO_TTL"),
-#'   region = "state:*",
-#'   naics2012 = "23")
-#' head(cbp_2016)
+#' # Get the number of employees and number of establishments in the construction sector,
+#' # NAICS2017 code 23, using the County Business Patterns API
+#' cbp <- getCensus(
+#' 	name = "cbp",
+#' 	vintage = 2021,
+#' 	vars = c("EMP", "ESTAB", "NAICS2017_LABEL"),
+#' 	region = "county:*",
+#' 	NAICS2017 = 23)
+#' head(cbp)
 #' }
+#'
 #' @export
 getCensus <-
 	function(name,

R/metadata_functions.R

@@ -58,53 +58,57 @@ listCensusApis <- function() {
 #' @keywords metadata
 #' @examples
 #' \dontrun{
-#'
+#' # type: variables
 #' # List the variables available in the Small Area Health Insurance Estimates.
-#' sahie_variables <- listCensusMetadata(
+#' variables <- listCensusMetadata(
 #'   name = "timeseries/healthins/sahie",
 #'   type = "variables")
-#'  head(sahie_variables)
+#'  head(variables)
+#'
+#' # type: variables for a single variable group
+#' # List the variables that are included in the B17020 group in the
+#' # 5-year American Community Survey.
+#' variable_group <- listCensusMetadata(
+#'   name = "acs/acs5",
+#'   vintage = 2022,
+#'   type = "variables",
+#'   group = "B17020")
+#'  head(variable_group)
 #'
-#' # List the geographies available in the 5-year 2020 American Community Survey.
-#' acs_geographies <- listCensusMetadata(
+#' # type: variables, with value labels
+#' # Create a data dictionary with all variable names and encoded values for
+#' # a microdata API.
+#' variable_values <- listCensusMetadata(
+#' 	name = "cps/voting/nov",
+#' 	vintage = 2020,
+#' 	type = "variables",
+#' 	include_values = TRUE)
+#' head(variable_values)
+#'
+#'# type: geographies
+#' # List the geographies available in the 5-year American Community Survey.
+#' geographies <- listCensusMetadata(
 #'   name = "acs/acs5",
-#'   vintage = 2020,
+#'   vintage = 2022,
 #'   type = "geographies")
-#'  head(acs_geographies)
+#'  head(geographies)
 #'
-#' # List the variable groups available in the 5-year 2020 American Community Survey.
-#' acs_groups <- listCensusMetadata(
+#' # type: groups
+#' # List the variable groups available in the 5-year American Community Survey.
+#' groups <- listCensusMetadata(
 #'   name = "acs/acs5",
-#'   vintage = 2020,
+#'   vintage = 2022,
 #'   type = "groups")
-#'  head(acs_groups)
-
-#' # Create a data dictionary with all variable names and encoded values for
-#' # a microdata API.
-#' cbp_dict <- listCensusMetadata(
-#'   name = "cbp",
-#'   vintage = 2020,
-#'   type = "variables",
-#'   include_values = TRUE)
-#'  head(cbp_dict)
+#'  head(groups)
 #'
-#' # List the value labels of the NAICS2017 variable in the 2020 County
-#' # Business Patterns dataset.
-#' cbp_naics_values <- listCensusMetadata(
+#' # type: values for a single variable
+#' # List the value labels of the NAICS2017 variable in the County Business Patterns dataset.
+#' naics_values <- listCensusMetadata(
 #'   name = "cbp",
-#'   vintage = 2020,
+#'   vintage = 2021,
 #'   type = "values",
 #'   variable = "NAICS2017")
-#'  head(cbp_naics_values)
-#'
-#' # List of variables that are included in the B17020 group in the
-#' # 5-year American Community Survey.
-#' group_B17020 <- listCensusMetadata(
-#'   name = "acs/acs5",
-#'   vintage = 2017,
-#'   type = "variables",
-#'   group = "B17020")
-#'  head(group_B17020)
+#'  head(naics_values)
 #' }
 #' @export
 listCensusMetadata <-