Casen 2011-2020

Tabla 001

Rural-Urbano.

VE-CC

DataIntelligence
date:05-10-2021 
casen_2006 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2006_c.rds")
casen_2006 <- mutate_if(casen_2006, is.factor, as.character)
casen_2009 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2009_c.rds")
casen_2009 <- mutate_if(casen_2009, is.factor, as.character)
casen_2011 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2011_c.rds")
casen_2011 <- mutate_if(casen_2011, is.factor, as.character)
casen_2013 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2013_c.rds")
casen_2013 <- mutate_if(casen_2013, is.factor, as.character)
casen_2015 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2015_c.rds")
casen_2015 <- mutate_if(casen_2015, is.factor, as.character)
casen_2017 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2017_c.rds")
casen_2017 <- mutate_if(casen_2017, is.factor, as.character)
casen_2020 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2020_c.rds")
casen_2020 <- mutate_if(casen_2020, is.factor, as.character)

1 Tabla de urbanidad

casen_2011$z[casen_2011$z == "Urbana"] <- "Urbano"
 
receptaculo <- data.frame(
  lugar = c("1","2")
)
for (i in 1:7) {
  
  switch(i,
        case = casen <- casen_2006,
        case = casen <- casen_2009,
        case = casen <- casen_2011,
        case = casen <- casen_2013,
        case = casen <- casen_2015,
        case = casen <- casen_2017,
        case = casen <- casen_2020
)

expan <-switch(i,"EXPC","EXPC","expc_full","expc","expc_todas","expc","expc")
var1  <-switch(i,"Z","ZONA","z","zona","zona","zona","zona")
################ si solo son 2 categorias no hay que modificar esta seccion
tabla_matp <-xtabs(casen[,(expan)]~casen[,(var1)], data = casen)
tabla_matp <- as.data.frame(tabla_matp)
# print(tabla_matp)
receptaculo <- cbind(receptaculo,tabla_matp)
}
receptaculo <- receptaculo[,-c(1,4,6,8,10,12,14)]
colnames(receptaculo) <- c("Variable","2006","2009","2011","2013","2015","2017","2020")
tabla_t <- receptaculo

tabla_t$a2007 <- NA
tabla_t$a2008 <- NA
tabla_t$a2010 <- NA
tabla_t$a2012 <- NA
tabla_t$a2014 <- NA
tabla_t$a2016 <- NA
tabla_t$a2018 <- NA
tabla_t$a2019 <- NA 
 
tabla_t <- tabla_t[,c("Variable","2006","a2007","a2008","2009","a2010","2011","a2012","2013","a2014","2015","a2016","2017","a2018","a2019","2020" )]
receptaculo <- data.frame()
for (n in 1:nrow(tabla_t)) {
  calculado <- na.approx(c(tabla_t[n,c(2:ncol(tabla_t))])) 
  receptaculo <- rbind(receptaculo,calculado)
}
 
receptaculo <- cbind(tabla_t$Variable,receptaculo)
colnames(receptaculo) <- c("categorias",paste(seq(2006,2020,1)))

################
 
datatable(receptaculo, extensions = 'Buttons', escape = FALSE, rownames = TRUE,
          options = list(dom = 'Bfrtip',
          buttons = list('colvis', list(extend = 'collection',
          buttons = list(
          list(extend='copy'),
          list(extend='excel',
            filename = 'ruralidad'),
          list(extend='pdf',
            filename= 'ruralidad')),
          text = 'Download')), scrollX = TRUE))%>%
    formatRound(columns=c(paste(seq(2006,2020,1))) ,mark = "", digits=0)