#' @name paro
#' @rdname paro
#'
#' @title Imports into R data of unemployed at a municipality level..
#'
#' @description \code{paro} imports the unemployed of the Spanish municipalities by province.
#'
#' @param year a numerical value from 2005 and the latest available, which indicates the year of the required database.
#' @param mes one of the 12 months –in Spanish language– indicating the month of the data collection. See \link{getbase.paro} for details.
#' @param provincia one of the 52 Spain’s province.
#'
#' @return It is a data frame containing the fallowing variables:.
#' - \code{cod} is the municipality identification number based in the INE codification
#' - \code{Name} is the municipality name.
#' - \code{Total unemployment} unemployment is the number of unemployed in the municipality
#' - \code{Total male unemployment} is the number of unemployed males in the municipality
#' - \code{Total female unemployment} is the number of unemployed females in the municipality
#'
#' @family Loading functions
#' @examples
#' #paro(2005,"julio","Madrid")
#'
#' @export
paro<-function(year,mes="julio",provincia){
year<-as.character(year)
Cap<-provincia
provincia<-toupper(provincia)
provincia<-a.letter(provincia)
if(as.numeric(year)<=2011){
if(provincia=="ARABA"){provincia1 <- "ALAVA"}
else if(provincia=="BIZKAIA"){provincia1 <- "VIZCAYA"}
else if(provincia=="GIPUZKOA"){provincia1 <- "GUIPUZCOA"}
else {provincia1 <- provincia}
} else {
provincia1 <- provincia
}
mes<-tolower(mes)
nn.mes<-seq(1,12,1)
names(nn.mes)<-c("enero","febrero","marzo","abril","mayo","junio","julio","agosto","septiembre","octubre","noviembre","diciembre")
cod<-paste("0",nn.mes[mes],substr(year,3,4),sep="")
dirc<-paste(getwd(),"/data_paro/",sep="")
name1<-paste(paste("MUNI",provincia1,cod,sep="_"),".xls",sep="")
file1<-paste("paro_",name1,sep="")
if(sum(dir(dirc)==file1)==0){
getbase.paro(year,mes,provincia)
}
if(as.numeric(year)<2013){
cod1<-paste("0",nn.mes[mes],"16",sep="")
name<-paste(paste("MUNI",provincia,cod1,sep="_"),".xls",sep="")
file<-paste("paro_",name,sep="")
if(sum(dir(dirc)==file)==0){
getbase.paro(2016,mes,provincia)
}
open<-paste(dirc,file,sep="")
abre<-paste(dirc,file1,sep="")
sh <- gdata::sheetNames(abre)
hoja <- agrep("PARO",sh)
#datos<-xlsx::read.xlsx(abre,hoja, encoding ="UTF-8")
datos <- gdata::read.xls(abre,sheet=hoja,skip=1,check.names=F)
if(colnames(datos)[1]=="X") {datos[,1]<-NULL}
#idn<-xlsx::read.xlsx(open,1,colIndex=c(1:3), encoding ="UTF-8")
idn <- gdata::read.xls(open,sheet=1,skip=1,check.names=F)
datos<-apply(datos,2,as.character)
idn<-apply(idn,2,as.character)
datos<-datos[-dim(datos)[1],]
idn<-idn[-dim(idn)[1],]
p<-which(datos[,1]=="MUNICIPIOS")+1
f<-dim(datos)[1]
pi<-max(which(is.na(idn[,1])))+1
fi<-dim(idn)[1]
datos<-datos[p:f,]
datos<-cbind(datos[,1],datos)
v<-intersect(datos[,1],idn[,2])
for( k in 1:length(v)){
if(length(which(idn[,2]==v[k]))>1){
datos[which(datos[,2]==v[k]),1]<-idn[which(idn[,2]==v[k])[2],1]
}else{
datos[which(datos[,2]==v[k]),1]<-idn[which(idn[,2]==v[k]),1]
}
}
if(stringi::stri_count(datos[min(which(!is.na(datos[,1]))),1],regex="[[:number:]]")==4){
cero<-rep(0,dim(datos)[1])
datos[,1]<-paste(cero,datos[,1],sep="")
}
datos<-datos[-1,]
if(is.null(dim(datos))){datos <- t(matrix(datos ))}
datos <- datos[,colSums(is.na(datos))!=nrow(datos)]
if(is.null(dim(datos))){datos <- t(matrix(datos ))}
cod<-datos[,1]
n.m<-datos[,2]
total<-as.numeric.factor(datos[,3])
total.h<-as.numeric(datos[,4]) + as.numeric(datos[,5]) + as.numeric(datos[,6])
total.m<-as.numeric(datos[,7])+as.numeric(datos[,8])+as.numeric(datos[,9])
#total.h<-NA
#total.m<-NA
salida<-as.data.frame(cbind(cod,n.m,total,total.h,total.m))
salida[,3:5]<-apply(salida[,3:5],2,as.numeric)
salida[,1]<-as.character(salida[,1])
salida[,2]<-as.character(salida[,2])
colnames(salida)<-c("cod","nombre","paro total","paro total hombres","paro total mujeres")
salida[which(is.na(salida[,3])),3]<-0
salida[which(is.na(salida[,4])),4]<-0
salida[which(is.na(salida[,5])),5]<-0
#salida<-rbind(salida,rep(NA,5))
nd<-dim(salida)[1]
if(nd==1){
salida <- salida
}else{
salida <- salida[-nd,]
}
#salida[nd,1]<-"Total"
#salida[nd,2]<-Cap
#salida[nd,3]<-sum(salida[1:nd-1,3])
#salida[nd,4]<-sum(salida[1:nd-1,4])
#salida[nd,5]<-sum(salida[1:nd-1,5])
fallas<-apply(as.matrix(salida[,1]),1,nchar)
n.fallas<-which(fallas!=5)
if (length(n.fallas)!=0){
for (i in seq_along(n.fallas)){
salida[n.fallas[i],1]<-codifica(salida[n.fallas[i],2],provincia)
}
}
salida
} else {
abre<-paste(dirc,file1,sep="")
sh <- gdata::sheetNames(abre)
hoja <- agrep("PARO",sh)
#datos<-xlsx::read.xlsx(abre,hoja, encoding ="UTF-8")
datos<-as.data.frame(gdata::read.xls(abre,sheet=hoja,skip=1,check.names=F))
datos<-apply(datos,2,as.character)
datos<-datos[-dim(datos)[1],]
p<-max(which(is.na(datos[,1])))+1
f<-dim(datos)[1]
ind<-datos[p:f,1]
if(stri_count(ind[1],regex="[[:number:]]")==4){
cero<-rep(0,length(ind))
ind<-paste(cero,ind,sep="")
}
n.m<-datos[p:f,2]
total<-as.numeric(datos[p:f,3])
total.h<-as.numeric(datos[p:f,4]) + as.numeric(datos[p:f,5]) + as.numeric(datos[p:f,6])
total.m<-as.numeric(datos[p:f,7])+as.numeric(datos[p:f,8])+as.numeric(datos[p:f,9])
salida<-as.data.frame(cbind(ind,n.m,total,total.h,total.m))
salida[,3:5]<-apply(salida[,3:5],2,as.numeric)
salida[,1]<-as.character(salida[,1])
salida[,2]<-as.character(salida[,2])
colnames(salida)<-c("cod","nombre","paro total","paro total hombres","paro total mujeres")
salida[which(is.na(salida[,3])),3]<-0
salida[which(is.na(salida[,4])),4]<-0
salida[which(is.na(salida[,5])),5]<-0
#salida<-rbind(salida,rep(NA,5))
nd<-dim(salida)[1]
if(nd==1){
salida <- salida
}else{
salida <- salida[-nd,]
}
#salida[nd,1]<-"Total"
#salida[nd,2]<-Cap
#salida[nd,3]<-sum(salida[1:nd-1,3])
#salida[nd,4]<-sum(salida[1:nd-1,4])
#salida[nd,5]<-sum(salida[1:nd-1,5])
}
salida
}
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