tabla_con_clave <- readRDS("censos/censo_personas_con_clave_17")
tabla_con_clave_u <- filter(tabla_con_clave, tabla_con_clave$AREA == 1)
b <- tabla_con_clave_u$COMUNA
c <- tabla_con_clave_u$P19
cross_tab =  xtabs( ~ unlist(b) + unlist(c))
tabla <- as.data.frame(cross_tab)
d <-tabla[!(tabla$Freq == 0),]
d$anio <- "2017"

d_t <- filter(d,d$unlist.c. == 0)
for(i in 1:23){
  d_i <- filter(d,d$unlist.c. == i)
  d_t = merge( x = d_t, y = d_i, by = "unlist.b.", all.x = TRUE)
}

codigos <- d_t$unlist.b.
rango <- seq(1:nrow(d_t))
cadena <- paste("0",codigos[rango], sep = "")
cadena <- substr(cadena,(nchar(cadena)[rango])-(4),6)
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
comuna_corr <- cbind(d_t,cadena)
comuna_corr <- comuna_corr[,-c(1),drop=FALSE] 
names(comuna_corr)[ncol(comuna_corr)] <- "código"

quitar <- seq(3,(ncol(comuna_corr)-1),3)
comuna_corr <- comuna_corr[,-c(quitar),drop=FALSE]
III <- seq(2,48,2)
 
for (i in 1:100) {
      names(comuna_corr)[III[i]] <- paste0(i-1, "_hijos/as")
}

quitar <- seq(1,(ncol(comuna_corr)-1),2)
comuna_corr <- comuna_corr[,-c(quitar),drop=FALSE]
ingresos_expandidos_2017 <- readRDS("Ingresos_expandidos_urbano_17.rds")
df_2017_2 = merge( x = comuna_corr, y = ingresos_expandidos_2017, by = "código", all.x = TRUE)

union_final_urb <- df_2017_2[,-c(1,(ncol(df_2017_2)-1))]
write_xlsx(union_final_urb, "P19_urbano.xlsx")

data_sum <- summary(union_final_urb)
kbl(head(data_sum)) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "500px")

library(plotly)

df_2017_fig <- df_2017_2[,-c((ncol(df_2017_2)-1))]

fig <- plot_ly(df_2017_fig, x = df_2017_fig$código, y = df_2017_fig[,2]
, name = colnames(df_2017_fig[2]), type = 'scatter', mode = 'lines',
                 width=7000, height=400) 

grafica_fn <- function(g){
  fig <<- fig %>% add_trace(y = ~df_2017_fig[,g]
, name = colnames(df_2017_fig[g]), mode = 'lines',
                 width=7000, height=400) 
}
for (g in 3:(ncol(df_2017_2)-1)) {
grafica_fn(g)

}

fig <- fig %>% layout(autosize = T )
fig 

i <- 1
f <- 10
for (cc in 1:2) {
III <- seq(i,f)
print(paste0(i-1,"-",f-1))
df_2017_2_sub_subset <- union_final_urb[,c(III,ncol(union_final_urb))]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- i+10
f <- f+10
}

print("21 - 23")

df_2017_2_sub_subset <- union_final_urb[,c(22:25)]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- 1
f <- 10
for (cc in 1:2) {
III <- seq(i,f)
print(paste0(i-1,"-",f-1))
df_2017_2_sub_subset <- union_final_urb[,c(III,ncol(union_final_urb))]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- i+10
f <- f+10
}

print("21 - 23")

df_2017_2_sub_subset <- union_final_urb[,c(22:25)]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- 1
f <- 10
for (cc in 1:2) {
III <- seq(i,f)
print(paste0(i-1,"-",f-1))
df_2017_2_sub_subset <- union_final_urb[,c(III,ncol(union_final_urb))]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- i+10
f <- f+10
}

print("21 - 23")

df_2017_2_sub_subset <- union_final_urb[,c(22:25)]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- 1
f <- 10
for (cc in 1:2) {
III <- seq(i,f)
print(paste0(i-1,"-",f-1))
df_2017_2_sub_subset <- union_final_urb[,c(III,ncol(union_final_urb))]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- i+10
f <- f+10
}

print("21")

df_2017_2_sub_subset <- union_final_urb[,c(22,25)]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "kendall"), pch=20)

i <- 1
f <- 10
for (cc in 1:2) {
III <- seq(i,f)
print(paste0(i-1,"-",f-1))
df_2017_2_sub_subset <- union_final_urb[,c(III,ncol(union_final_urb))]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "pearson"), pch=20)

i <- i+10
f <- f+10
}

print("21")

df_2017_2_sub_subset <- union_final_urb[,c(22,25)]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "pearson"), pch=20)

i <- 1
f <- 10
for (cc in 1:2) {
III <- seq(i,f)
print(paste0(i-1,"-",f-1))
df_2017_2_sub_subset <- union_final_urb[,c(III,ncol(union_final_urb))]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "spearman"), pch=20)

i <- i+10
f <- f+10
}

print("21")

df_2017_2_sub_subset <- union_final_urb[,c(22,25)]
chart.Correlation(df_2017_2_sub_subset, histogram=TRUE, method = c( "spearman"), pch=20)