R/Measure.getMeasure.R

In umatter/pvsR: Interact with the Project Vote Smart API for Scientific Research

##' Get details of a ballot measure
##' 
##' This function is a wrapper for the Measure.getMeasure() method of the PVS API Measure class which grabs details of a ballot measure. The function sends a request with this method to the PVS API for all measure IDs given as a function input, extracts the XML values from the returned XML file(s) and returns them arranged in one data frame.
##' @usage Measure.getMeasure(measureId)
##' @param measureId a character string or list of character strings with the measure ID(s) (see references for details)
##' @return A data frame with a row for each ballot measure and columns with the following variables describing the ballot measure:\cr measure.measureId,\cr measure.measureCode,\cr measure.title,\cr measure.electionDate,\cr measure.electionType,\cr measure.source,\cr measure.url,\cr measure.summary,\cr measure.summaryUrl,\cr measure.measureText,\cr measure.textUrl,\cr measure.proUrl,\cr measure.conUrl,\cr measure.yes,\cr measure.no,\cr measure.outcome.
##' @references http://api.votesmart.org/docs/Measure.html\cr
##' Use Measure.getMeasuresByYearState() to get a list of measure IDs.\cr
##' See also: Matter U, Stutzer A (2015) pvsR: An Open Source Interface to Big Data on the American Political Sphere. PLoS ONE 10(7): e0130501. doi: 10.1371/journal.pone.0130501
##' @author Ulrich Matter <ulrich.matter-at-unibas.ch>
##' @examples
##' # First, make sure your personal PVS API key is saved as an option
##' # (options("pvs.key" = "yourkey")) or in the pvs.key variable:
##' \dontrun{pvs.key <- "yourkey"}
##' # get details on certain ballot measures
##' \dontrun{measure <- Measure.getMeasure(list(1632,1633))}
##' \dontrun{measure}

##' @export



Measure.getMeasure <-
	function (measureId) {

		# internal function
		Measure.getMeasure.basic <- 
			function (.measureId) {

				request <-  "Measure.getMeasure?"
				inputs  <-  paste("&measureId=",.measureId, sep="")
				output  <-  pvsRequest(request,inputs)
				output$measureId <-.measureId
				
				return(output)
		}

		# Main function
		output.list <- lapply(measureId, FUN= function (b) {
			Measure.getMeasure.basic(.measureId=b)
		}
		)
		
# 		# which list entry has the most columns, how many are these?
# 		coln <- which.is.max(sapply(output.list, ncol));
# 		max.cols <- max(sapply(output.list, ncol));
# 		
# 		# give all list entries (dfs in list) the same number of columns and the same names
# 		output.list2 <- lapply(output.list, function(x){
# 			if (ncol(x) < max.cols) x <- data.frame(cbind(matrix(NA, ncol=max.cols-ncol(x), nrow = 1),x),row.names=NULL, stringsAsFactors = FALSE)
# 			names(x) <- names(output.list[[coln]])
# 			x
# 		})
		
		#output <- do.call("rbind",output.list2)
		output <- bind_rows(output.list)
			
		return(output)

		}