Casen 2011-2017

Tabla 008

Código de Comuna de establecimiento educaciona.

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 008

1.1 Interpolación

df_tablas <- data.frame()


funcion1 <- function(n){

 xx<-switch(n,"2011","2013","2015","2017")
 tanio <<- xx

 v1 <- switch(n,"e8com","e8com_cod","e7com_cod","e9com_c_cod")
 
 
 if(xx==2011) {
   
eliminated <- casen_2011 
c <- eliminated[,c(v1)]
anio <- 2011
}
 
 if(xx==2013) {
   
eliminated <- casen_2013 
c <- eliminated[,c(v1)]
anio <- 2013
}
 
 if(xx==2015) {
   
eliminated <- casen_2015 
c <- eliminated[,c(v1)]
anio <- 2015
}

if(xx==2017) {
    
eliminated <- casen_2017  
c <- eliminated[,c(v1)]
anio <- 2017
}
 
 
 
################ -- frecuencia
expan<-switch(n,"expc_full","expc","expc_todas","expc","expc")
tabla_matp <-xtabs(eliminated[,(expan)]~c, data = eliminated)
tabla_matp <- as.data.frame(tabla_matp) 
names(tabla_matp)[1] <- "categorias"
data_df1 <<- tabla_matp
################ 
} 

for (n in 1:4){
  
  funcion1(n) 
  assign(paste0("tabla_",tanio),data_df1)

}  
tabla_f <- merge(tabla_2011, tabla_2013, by= "categorias",  all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2015, by= "categorias",  all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2017, by= "categorias",  all.x = T, all.y = T)   
colnames(tabla_f) <- c("Variable","2011","2013","2015","2017")
 
tabla_f <- mutate_all(tabla_f, ~replace(., is.na(.), 0))

tabla_t <- tabla_f
# 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", "2011","a2012","2013","a2014","2015","a2016","2017")]
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",paste0(seq(2011,2017,1)))

################
 
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(paste0(seq(2011,2017,1))) ,mark = "", digits=0)