R/geotype.R
In ejanalysis/ejanalysis: Tools for Environmental Justice (EJ) Analysis
Defines functions
geotype
Documented in
geotype
#' @title Infer Type of Data as FIPS / ANSI Codes or Names of U.S. Geographies - obsolete.
#' See EJAM package function called fipstype()
#' @description
#' Tries to interpret vector of one or more FIPS codes and/or names of geographies.
#' @param x Required vector of one or more numeric or character FIPS and/or names of geographic locations.
#' Allowed types are State, County (or equivalent), tract, block group, and block.
#' Names for tracts, blockgroups, and blocks are not provided or interpreted.
#' FIPS codes here are all the relevant digits starting with the 2-character state FIPS,
#' so county fips must be 4-5 digits or characters for example (leading zeroes are inferred where
#' possible and included in outputs). See [clean.fips()] for details.
#' @param cleancounties whether to try to validate county FIPS based on list that ideally is always up to date
#' @return ***TBD *** Returns *** types as character strings, and maybe cleaned values themselves? ***
#' @seealso [geofips()], [ejanalysis::get.fips.st()] and related functions noted there, [ejanalysis::clean.fips()], [ejanalysis::get.state.info()]
#' @examples # none yet
#' @export
geotype <- function(x, cleancounties=TRUE) {
stop('not done yet')
# figure out what type of geo these are
# BUT DO I CLEAN THEM UP AND RETURN CLEANED VERSIONS,
# AND/OR
# FIGURE OUT THE TYPE HERE?
#
# WHAT FUNCTION DOES WHICH OF THOSE?? SENSIBLE TO DO BOTH AT ONCE?
# PRECLEAN FIRST,
# THEN INFER TYPE BY FORM,
# THEN VALIDATE TYPE AGAINST LIST OF VALIDS OF THAT TYPE,
# THEN
# 1-RETURN CLEANED AND VALIDATED VERSION &
# 2-RETURN NAME OF THE TYPE.
# What type of fips or name was provided if any?
# from clean.fips():
# If FIPS provided is 1-2 digits long assume it is a State.
# If FIPS provided is 3 digits long, it is a mistake and return NA.
# If FIPS provided is 4-5 digits, assume it is a County.
# If FIPS provided is 6-9 digits, it is a mistake and return NA.
# If FIPS provided is 10 digits long, assume it is a tract missing a leading zero on the state portion (should have 11 characters).
# If FIPS provided is 11 digits long, assume it is a tract (correctly 11 characters), not simply a block group FIPS missing a leading zero (block group FIPS would correctly would have 12 characters).
# If FIPS provided is 12 digits long, assume it is a block group (correctly 12 characters).
# If FIPS provided is 13 digits long, it is a mistake and return NA.
# If FIPS provided is 14 OR 15 digits long, assume it is a block.
if (1==0) {
fips <- as.character(fips)
if (nchar(fips)==1) {fips <- lead.zeroes(fips, 2)}
if (nchar(fips)==4) {fips <- lead.zeroes(fips, 5)}
if (nchar(fips)==2 && (fips %in% valid.FIPS.ST$FIPS.ST)) {fipstype <- 'fips.state'} else {
if (nchar(fips)==5 && (fips %in% valid.FIPS.COUNTY)) {fipstype <- 'fips.county'} else {
if (tolower(fips) %in% valid.FIPS.ST$statename) {fipstype <- 'name.state'} else {
# TRY TO FIGURE OUT COUNTY FROM COUNTYNAME BUT NEED STATE ALSO AND NOT YET IMPLEMENTED:
# obtain countyname list here to check that, since it isn't any of the other types checked so far ****** UNTESTED - NOT WORKING YET
countyinfo <- get.county.info()
countyportion <- gsub(', [[:alnum:]_]+', '', tolower(fips))
stateportion <- gsub('^.+, ', '', tolower(fips))
stateok <- FALSE
if (stateportion %in% valid.FIPS.ST$statename) { stateok <- TRUE }
if (stateportion %in% tolower(valid.FIPS.ST$ST)) { stateportion <- valid.FIPS.ST$statename[match(tolower(stateportion), tolower(valid.FIPS.ST$ST))]; stateok <- TRUE}
cat(stateportion, countyportion, stateok,'\n')
if ((countyportion %in% tolower(countyinfo$countyname)) & stateok ) { fips <- countyinfo$FIPS.COUNTY[match(tolower(fips), tolower(countyinfo$countyname))]; fipstype <- 'name.county'} else {
#if ( charmatch(tolower(fips), .... xxx ) {warning(paste('only partial match on countyname - not used: ', partmatch, sep='') )}
fipstype='invalid'
}
}
}
}
######## another version / started on this but likely incomplete...
valid.states <- ejanalysis::get.state.info()[ , c('FIPS.ST', 'statename', 'ST')]
# ejanalysis::get.state.info uses data(lookup.states, package='proxistat')
valid.states$statename <- tolower(valid.states$statename)
valid.counties <- ejanalysis::get.county.info() # but that has to be updated regularly in proxistat...
# that uses data(countiesall, package='proxistat') # has "ST", "countyname", "FIPS.COUNTY", "statename", "fullname"
# What type of fips or name was provided if any?
if (missing(x)) {warning('No x specified'); return(NA)}
nx <- length(x)
x <- as.character(x)
type <- rep('invalid', nx) # default is 'invalid'
# where x is 1 character, assume it was a state fips that dropped the leading zero
x[nchar(x)==1] <- lead.zeroes(x[nchar(x)==1], 2)
# where fips represents a 4 digit number, not name like Ohio, add the missing leading zero to get county fips
fips[nchar(fips)==4 & suppressWarnings(!is.na(as.numeric(fips)))] <- lead.zeroes(fips[nchar(fips)==4 & suppressWarnings(!is.na(as.numeric(fips)))], 5)
fipstype[nchar(fips)==2 & (fips %in% valid.states$FIPS.ST)] <- 'fips.state'
fipstype[nchar(fips)==2 & (fips %in% valid.states$ST)] <- 'abbrev.state'
fipstype[tolower(fips) %in% valid.states$statename] <- 'name.state'
fips[nchar(fips)==4 & (analyze.stuff::lead.zeroes(fips, 5) %in% valid.counties$FIPS.COUNTY)] <- analyze.stuff::lead.zeroes(fips, 5)
fipstype[nchar(fips)==5 & (fips %in% valid.counties$FIPS.COUNTY)] <- 'fips.county'
#print('fipstypes');print(fipstype);print("")
# if (1==0) {
# WILL TRY TO FIGURE OUT COUNTY FROM COUNTYNAME BUT NEED STATE ALSO AND NOT YET IMPLEMENTED:
# obtain countyname list here to check that, since it isn't any of the other types checked so far
# ****** UNTESTED - NOT WORKING YET
countyportion <- gsub(', [[:alnum:]_]+', '', tolower(fips))
stateportion <- gsub('^.+, ', '', tolower(fips))
STportion <- valid.states$FIPS.ST[match(tolower(stateportion), tolower(valid.states$ST))]
# convert state abbreviation to full state name
stateportion[stateportion %in% valid.states$FIPS.ST] <- valid.states$statename[match(tolower(stateportion[stateportion %in% valid.states$FIPS.ST]), tolower(valid.states$FIPS.ST))]
stateok <- rep(FALSE, length(fips) )
stateok[stateportion %in% valid.states$statename] <- TRUE
stateok[STportion %in% valid.states$FIPS.ST] <- TRUE
#cat(stateportion, countyportion, stateok,'\n')
if (cleancounties) {
countyok <- (tolower(countyportion) %in% tolower(valid.counties$countyname))
} else {
}
fips[countyok & stateok] <- valid.counties$FIPS.COUNTY[match(
paste(tolower(countyportion[countyok & stateok]), tolower(stateportion[countyok & stateok]), sep = ''),
paste(tolower(valid.counties$countyname), tolower(valid.counties$statename), sep = '')
)]
fipstype[countyok & stateok] <- 'name.county'
#fipstype[countyok & stateok] <- 'fips.county'
#if ( charmatch(tolower(fips), .... xxx ) {warning(paste('only partial match on countyname - not used: ', partmatch, sep='') )}
# }
if (all(fipstype=='invalid')) {
stop('no valid fips')
}
if (any(fipstype=='invalid')) {
warning('some invalid fips - returning USA URL for those')
fipstype[fipstype=='invalid'] <- 'usa'
}
return(type)
}
}
ejanalysis/ejanalysis documentation built on April 2, 2024, 10:12 a.m.
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Defines functions geotype
Documented in geotype
#' @title Infer Type of Data as FIPS / ANSI Codes or Names of U.S. Geographies - obsolete.
#' See EJAM package function called fipstype()
#' @description
#' Tries to interpret vector of one or more FIPS codes and/or names of geographies.
#' @param x Required vector of one or more numeric or character FIPS and/or names of geographic locations.
#' Allowed types are State, County (or equivalent), tract, block group, and block.
#' Names for tracts, blockgroups, and blocks are not provided or interpreted.
#' FIPS codes here are all the relevant digits starting with the 2-character state FIPS,
#' so county fips must be 4-5 digits or characters for example (leading zeroes are inferred where
#' possible and included in outputs). See [clean.fips()] for details.
#' @param cleancounties whether to try to validate county FIPS based on list that ideally is always up to date
#' @return ***TBD *** Returns *** types as character strings, and maybe cleaned values themselves? ***
#' @seealso [geofips()], [ejanalysis::get.fips.st()] and related functions noted there, [ejanalysis::clean.fips()], [ejanalysis::get.state.info()]
#' @examples # none yet
#' @export
geotype <- function(x, cleancounties=TRUE) {
stop('not done yet')
# figure out what type of geo these are
# BUT DO I CLEAN THEM UP AND RETURN CLEANED VERSIONS,
# AND/OR
# FIGURE OUT THE TYPE HERE?
#
# WHAT FUNCTION DOES WHICH OF THOSE?? SENSIBLE TO DO BOTH AT ONCE?
# PRECLEAN FIRST,
# THEN INFER TYPE BY FORM,
# THEN VALIDATE TYPE AGAINST LIST OF VALIDS OF THAT TYPE,
# THEN
# 1-RETURN CLEANED AND VALIDATED VERSION &
# 2-RETURN NAME OF THE TYPE.
# What type of fips or name was provided if any?
# from clean.fips():
# If FIPS provided is 1-2 digits long assume it is a State.
# If FIPS provided is 3 digits long, it is a mistake and return NA.
# If FIPS provided is 4-5 digits, assume it is a County.
# If FIPS provided is 6-9 digits, it is a mistake and return NA.
# If FIPS provided is 10 digits long, assume it is a tract missing a leading zero on the state portion (should have 11 characters).
# If FIPS provided is 11 digits long, assume it is a tract (correctly 11 characters), not simply a block group FIPS missing a leading zero (block group FIPS would correctly would have 12 characters).
# If FIPS provided is 12 digits long, assume it is a block group (correctly 12 characters).
# If FIPS provided is 13 digits long, it is a mistake and return NA.
# If FIPS provided is 14 OR 15 digits long, assume it is a block.
if (1==0) {
fips <- as.character(fips)
if (nchar(fips)==1) {fips <- lead.zeroes(fips, 2)}
if (nchar(fips)==4) {fips <- lead.zeroes(fips, 5)}
if (nchar(fips)==2 && (fips %in% valid.FIPS.ST$FIPS.ST)) {fipstype <- 'fips.state'} else {
if (nchar(fips)==5 && (fips %in% valid.FIPS.COUNTY)) {fipstype <- 'fips.county'} else {
if (tolower(fips) %in% valid.FIPS.ST$statename) {fipstype <- 'name.state'} else {
# TRY TO FIGURE OUT COUNTY FROM COUNTYNAME BUT NEED STATE ALSO AND NOT YET IMPLEMENTED:
# obtain countyname list here to check that, since it isn't any of the other types checked so far ****** UNTESTED - NOT WORKING YET
countyinfo <- get.county.info()
countyportion <- gsub(', [[:alnum:]_]+', '', tolower(fips))
stateportion <- gsub('^.+, ', '', tolower(fips))
stateok <- FALSE
if (stateportion %in% valid.FIPS.ST$statename) { stateok <- TRUE }
if (stateportion %in% tolower(valid.FIPS.ST$ST)) { stateportion <- valid.FIPS.ST$statename[match(tolower(stateportion), tolower(valid.FIPS.ST$ST))]; stateok <- TRUE}
cat(stateportion, countyportion, stateok,'\n')
if ((countyportion %in% tolower(countyinfo$countyname)) & stateok ) { fips <- countyinfo$FIPS.COUNTY[match(tolower(fips), tolower(countyinfo$countyname))]; fipstype <- 'name.county'} else {
#if ( charmatch(tolower(fips), .... xxx ) {warning(paste('only partial match on countyname - not used: ', partmatch, sep='') )}
fipstype='invalid'
}
}
}
}
######## another version / started on this but likely incomplete...
valid.states <- ejanalysis::get.state.info()[ , c('FIPS.ST', 'statename', 'ST')]
# ejanalysis::get.state.info uses data(lookup.states, package='proxistat')
valid.states$statename <- tolower(valid.states$statename)
valid.counties <- ejanalysis::get.county.info() # but that has to be updated regularly in proxistat...
# that uses data(countiesall, package='proxistat') # has "ST", "countyname", "FIPS.COUNTY", "statename", "fullname"
# What type of fips or name was provided if any?
if (missing(x)) {warning('No x specified'); return(NA)}
nx <- length(x)
x <- as.character(x)
type <- rep('invalid', nx) # default is 'invalid'
# where x is 1 character, assume it was a state fips that dropped the leading zero
x[nchar(x)==1] <- lead.zeroes(x[nchar(x)==1], 2)
# where fips represents a 4 digit number, not name like Ohio, add the missing leading zero to get county fips
fips[nchar(fips)==4 & suppressWarnings(!is.na(as.numeric(fips)))] <- lead.zeroes(fips[nchar(fips)==4 & suppressWarnings(!is.na(as.numeric(fips)))], 5)
fipstype[nchar(fips)==2 & (fips %in% valid.states$FIPS.ST)] <- 'fips.state'
fipstype[nchar(fips)==2 & (fips %in% valid.states$ST)] <- 'abbrev.state'
fipstype[tolower(fips) %in% valid.states$statename] <- 'name.state'
fips[nchar(fips)==4 & (analyze.stuff::lead.zeroes(fips, 5) %in% valid.counties$FIPS.COUNTY)] <- analyze.stuff::lead.zeroes(fips, 5)
fipstype[nchar(fips)==5 & (fips %in% valid.counties$FIPS.COUNTY)] <- 'fips.county'
#print('fipstypes');print(fipstype);print("")
# if (1==0) {
# WILL TRY TO FIGURE OUT COUNTY FROM COUNTYNAME BUT NEED STATE ALSO AND NOT YET IMPLEMENTED:
# obtain countyname list here to check that, since it isn't any of the other types checked so far
# ****** UNTESTED - NOT WORKING YET
countyportion <- gsub(', [[:alnum:]_]+', '', tolower(fips))
stateportion <- gsub('^.+, ', '', tolower(fips))
STportion <- valid.states$FIPS.ST[match(tolower(stateportion), tolower(valid.states$ST))]
# convert state abbreviation to full state name
stateportion[stateportion %in% valid.states$FIPS.ST] <- valid.states$statename[match(tolower(stateportion[stateportion %in% valid.states$FIPS.ST]), tolower(valid.states$FIPS.ST))]
stateok <- rep(FALSE, length(fips) )
stateok[stateportion %in% valid.states$statename] <- TRUE
stateok[STportion %in% valid.states$FIPS.ST] <- TRUE
#cat(stateportion, countyportion, stateok,'\n')
if (cleancounties) {
countyok <- (tolower(countyportion) %in% tolower(valid.counties$countyname))
} else {
}
fips[countyok & stateok] <- valid.counties$FIPS.COUNTY[match(
paste(tolower(countyportion[countyok & stateok]), tolower(stateportion[countyok & stateok]), sep = ''),
paste(tolower(valid.counties$countyname), tolower(valid.counties$statename), sep = '')
)]
fipstype[countyok & stateok] <- 'name.county'
#fipstype[countyok & stateok] <- 'fips.county'
#if ( charmatch(tolower(fips), .... xxx ) {warning(paste('only partial match on countyname - not used: ', partmatch, sep='') )}
# }
if (all(fipstype=='invalid')) {
stop('no valid fips')
}
if (any(fipstype=='invalid')) {
warning('some invalid fips - returning USA URL for those')
fipstype[fipstype=='invalid'] <- 'usa'
}
return(type)
}
}
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