dataset_06 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2006_c.rds")
dataset_06 <- mutate_if(dataset_06, is.factor, as.character)
dataset_09 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2009_c.rds")
dataset_09 <- mutate_if(dataset_09, is.factor, as.character)
dataset_11 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2011_c.rds")
dataset_11 <- mutate_if(dataset_11, is.factor, as.character)
dataset_13 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2013_c.rds")
dataset_13 <- mutate_if(dataset_13, is.factor, as.character)
dataset_15 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2015_c.rds")
dataset_15 <- mutate_if(dataset_15, is.factor, as.character)
dataset_17 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2017_c.rds")
dataset_17 <- mutate_if(dataset_17, is.factor, as.character)
dataset_20 <<- readRDS("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2020.rds")
dataset_20 <- mutate_if(dataset_20, is.factor, as.character)

tab_ytotcor <- data.frame(
  ytotcor_06 = head(dataset_06$YTOTAJ,20), 
  ytotcor_09 = head(dataset_09$YTOTAJ,20), 
  ytotcor_11 = head(dataset_11$ytotaj,20), 
  ytotcor_13 = head(dataset_13$ytotcor,20), 
  ytotcor_15 = head(dataset_15$ytotcor,20), 
  ytotcor_17 = head(dataset_17$ytotcor,20), 
  ytotcor_20 = head(dataset_20$ytotcor,20)
)
datatable(tab_ytotcor, extensions = 'Buttons', escape = FALSE, rownames = FALSE,
          options = list(dom = 'Bfrtip',
          buttons = list('colvis', list(extend = 'collection',
          buttons = list(
          list(extend='copy'),
          list(extend='excel',
            filename = 'tabla_etnia_ytotcor'),
          list(extend='pdf',
            filename= 'tabla_etnia_ytotcor')),
          text = 'Download')), scrollX = TRUE)) 

df_tablas <- data.frame()

for (var2 in 1:1) {

 
funcion1 <- function(n){

  comunales<-switch(n,"codigos_comunales_2006.rds","codigos_comunales_2009.rds","codigos_comunales_2011-2017.rds","codigos_comunales_2011-2017.rds","codigos_comunales_2011-2017.rds","codigos_comunales_2011-2017.rds","codigos_comunales_2011-2017.rds")
 xx<-switch(n,"2006","2009","2011","2013","2015","2017","2020")
 tanio <<- xx

 
 

if(xx==2006) {
  
  ingreso <- switch(var2,"YTOTAJ","YAUTAJ","YTRABAJ","YOPRAJ")  
eliminated <- mutate_at(dataset_06, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated$YTOTAJ
b <- eliminated$COMUNA
c <- eliminated$SEXO
d <- eliminated$E1 #alfabetismo
e <- eliminated$T4 #etnia 
anio <- 2006
}

if(xx==2009) {

  ingreso <- switch(var2,"YTOTAJ","YAUTAJ","YTRABAJ","YOPRAJ") 
eliminated <- mutate_at(dataset_09, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated[,c(ingreso)]
b <- eliminated$COMUNA
c <- eliminated$SEXO
d <- eliminated$E1 #alfabetismo
e <- eliminated$T5 #etnia 
anio <- 2009

}

if(xx==2011) {
  
  ingreso <- switch(var2,"ytotaj","yautaj","ytrabaj","yopraj") 
eliminated <- mutate_at(dataset_11, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated[,c(ingreso)]
b <- eliminated$comuna
c <- eliminated$sexo
d <- eliminated$e1 #alfabetismo
e <- eliminated$r6 #etnia 
anio <- 2011

}

if(xx==2013) {
  
  ingreso <- switch(var2,"ytotcor","yautcor","ytrabajoCor","yoprCor") 
eliminated <- mutate_at(dataset_13, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated[,c(ingreso)]
b <- eliminated$comuna
c <- eliminated$sexo
d <- eliminated$e1 #alfabetismo
e <- eliminated$r6 #etnia 
anio <- 2013

}
 

if(xx==2015) {
  
  ingreso <- switch(var2,"ytotcor","yautcor","ytrabajoCor","yoprCor") 
eliminated <- mutate_at(dataset_15, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated[,c(ingreso)]
b <- eliminated$comuna
c <- eliminated$sexo
d <- eliminated$e1 #alfabetismo
e <- eliminated$r3 #etnia 
anio <- 2015
}

if(xx==2017) {
  
  ingreso <- switch(var2,"ytotcor","yautcor","ytrabajocor","yoprcor")
eliminated <- mutate_at(dataset_17, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated[,c(ingreso)]
b <- eliminated$comuna
c <- eliminated$sexo
d <- eliminated$e1 #alfabetismo
e <- eliminated$r3 #etnia 
anio <- 2017
}

if(xx==2020) {
  
  ingreso <- switch(var2,"ytotcor","yautcor","ytrabajocor","yoprcor") 
eliminated <- mutate_at(dataset_20, c(ingreso), ~replace(., is.na(.), 0))
a <- eliminated[,c(ingreso)]
b <- eliminated$comuna
c <- eliminated$sexo
d <- eliminated$sexo #alfabetismo
e <- eliminated$r3 #etnia 
anio <- 2020
}

promedios_grupales <-aggregate(a, by=list(b,  c,  e ), FUN = mean , na.rm = TRUE)
promedios_grupales_sd <-aggregate(a, by=list(b, c,    e ), FUN = sd , na.rm = TRUE)
promedios_grupales_gini <-aggregate(a, by=list(b, c,     e ), FUN = gini , na.rm = TRUE)

promedios_grupales$sd = promedios_grupales_sd$sd.a
promedios_grupales$gini = promedios_grupales_gini$gini.a
df <- promedios_grupales

################ -- frecuencia
expan<-switch(n,"EXPC","EXPC","expc_full","expc","expc_todas","expc","expc")

tabla_matp <-xtabs(eliminated[,(expan)]~b+c +e , data = eliminated)
tabla_matp <- as.data.frame(tabla_matp)
tabla_matp <-tabla_matp[!(tabla_matp$Freq == 0),]
df$freq <- tabla_matp$Freq
df <- df[complete.cases(df), ]
################ 


names(df)[1] <- "Comuna"
names(df)[2] <- "Sexo"
# names(df)[3] <- "Alfabetismo"
names(df)[3] <- "Etnia"
names(df)[4] <- "Promedio del Ingreso"
names(df)[5] <- "Desviación standard"
names(df)[6] <- "Gini"
names(df)[7] <- "freq" 
df$Año = xx

direc_cod_com <- paste0("C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/",comunales)
codigos_comunales <- readRDS(file = direc_cod_com)
names(codigos_comunales)[1] <- "Código"
names(codigos_comunales)[2] <- "Comuna"

tabla_df = merge( x = df, y = codigos_comunales, by = "Comuna", all.x = TRUE)
tabla_df <-tabla_df[!(tabla_df$Promedio == 0),]

tabla_df2 <<- tabla_df 

}

data_df3 <- data.frame()
for (n in 1:7){
  funcion1(n)

  data_df3 <- rbind(data_df3,tabla_df2)

} 
variable_i <- switch(var2,"ytotcor","yautcor","ytrabajocor","yoprcor")

data_df3$var_id <- paste0(variable_i,"_id")
assign(paste0("tabla_etnia_",variable_i),data_df3)
print(paste0("tabla_etnia_",variable_i))
 
 
}

datatable(tabla_final, extensions = 'Buttons', escape = FALSE, rownames = FALSE,
          options = list(dom = 'Bfrtip',
          buttons = list('colvis', list(extend = 'collection',
          buttons = list(
          list(extend='copy'),
          list(extend='excel',
            filename = 'tabla_etnia_ytotcor'),
          list(extend='pdf',
            filename= 'tabla_etnia_ytotcor')),
          text = 'Download')), scrollX = TRUE))%>%
    formatRound(columns=c("Promedio del Ingreso","Desviación standard","Gini") ,mark = "", digits=3)