1 Introducción

2 Despliegue del 2017

3 Despliegue del 2015

4 Despliegue del 2013

5 Despliegue del 2011

6 Despliegue del 2009

7 Despliegue del 2006

7 Despliegue del 2006

8 Gráficos



dataset_2006 <- readRDS(file = "casen_2006_c.rds")
dataset_2009 <- readRDS(file = "casen_2009_c.rds")
dataset_2011 <- readRDS(file = "casen_2011_c.rds")
dataset_2013 <- readRDS(file = "casen_2013_c.rds")
dataset_2015 <- readRDS(file = "casen_2015_c.rds")
dataset_2017 <- readRDS(file = "casen_2017_c.rds")

1 Introducción

Se generaran 4 tablas, una por variable de ingreso(yautcor, yautcor, yoprcor e ytrabajocor), a los largo de las 6 Casen disponibles, por comuna.

Generaremos conjuntos de 4 tablas, una por cada variable de ingreso, una por cada año. Se construirán 24, que luego se unirán por variable de ingreso, todos los años.

2 2017

mifuncion <- function(n){
  
    ingreso <- switch(n,"ytotcor","yautcor","yoprcor","ytrabajocor")
  
    bb <- dataset_2017[,c(ingreso)]
    aa <<-assign( paste(ingreso,  sep = ""), bb )

    a <- dataset_2017$aa
    b <- dataset_2017$comuna

    promedios_2017 <-aggregate(aa, by=list(b), FUN = mean , na.rm = TRUE)
    promedios_2017$Anio <- 2017
    names(promedios_2017)[1] <- "Comunas"
    names(promedios_2017)[2] <- "Promedios 2017"
    
    promedios_2017 <<- promedios_2017
    # head(promedios_2017,5)
    # print(promedios_2017)
    return(promedios_2017)

}
for (n in 1:4){
  ingreso_17 <- mifuncion(n)
  
  
    nom_ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
    nombre <- paste("Ingresos_2017_",nom_ingreso, sep = "")
   ingreso_f <<-assign( paste("Ingresos_2017_",nom_ingreso, sep = ""), ingreso_17 )
   saveRDS(ingreso_f,nombre)
   head(ingreso_f,5)
  
}

3 2015

mifuncion <- function(n){
  
    ingreso <- switch(n,"ytotcor","yautcor","yoprCor","ytrabajoCor")
  
    bb <- dataset_2015[,c(ingreso)]
    aa <<-assign( paste(ingreso,  sep = ""), bb )

    a <- dataset_2015$aa
    b <- dataset_2015$comuna

    promedios_2015 <-aggregate(aa, by=list(b), FUN = mean , na.rm = TRUE)
    promedios_2015$Anio <- 2015
    names(promedios_2015)[1] <- "Comunas"
    names(promedios_2015)[2] <- "Promedios 2015"
    
    promedios_2015 <<- promedios_2015
    # head(promedios_2015,5)
    # print(promedios_2015)
    return(promedios_2015)

}
for (n in 1:4){
  ingreso_15 <- mifuncion(n)
  
  
    nom_ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
    nombre <- paste("Ingresos_2015_",nom_ingreso, sep = "")
   ingreso_f <<-assign( paste("Ingresos_2015_",nom_ingreso, sep = ""), ingreso_15 )
   saveRDS(ingreso_f,nombre)
   head(ingreso_f,5)
  
}

4 2013

mifuncion <- function(n){
  
    ingreso <- switch(n,"ytotcor","yautcor","yoprCor","ytrabajoCor")
  
    bb <- dataset_2013[,c(ingreso)]
    aa <<-assign( paste(ingreso,  sep = ""), bb )

    a <- dataset_2013$aa
    b <- dataset_2013$comuna

    promedios_2013 <-aggregate(aa, by=list(b), FUN = mean , na.rm = TRUE)
    promedios_2013$Anio <- 2013
    names(promedios_2013)[1] <- "Comunas"
    names(promedios_2013)[2] <- "Promedios 2013"
    
    promedios_2013 <<- promedios_2013
    # head(promedios_2013,5)
    # print(promedios_2013)
    return(promedios_2013)

}
for (n in 1:4){
  ingreso_13 <- mifuncion(n)
  
  
    nom_ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
    nombre <- paste("Ingresos_2013_",nom_ingreso, sep = "")
   ingreso_f <<-assign( paste("Ingresos_2013_",nom_ingreso, sep = ""), ingreso_13 )
   saveRDS(ingreso_f,nombre)
   head(ingreso_f,5)
  
}

5 2011

mifuncion <- function(n){
  
    ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
  
    bb <- dataset_2011[,c(ingreso)]
    aa <<-assign( paste(ingreso,  sep = ""), bb )

    a <- dataset_2011$aa
    b <- dataset_2011$comuna

    promedios_2011 <-aggregate(aa, by=list(b), FUN = mean , na.rm = TRUE)
    promedios_2011$Anio <- 2011
    names(promedios_2011)[1] <- "Comunas"
    names(promedios_2011)[2] <- "Promedios 2011"
    
    promedios_2011 <<- promedios_2011
    # head(promedios_2011,5)
    # print(promedios_2011)
    return(promedios_2011)

}
for (n in 1:4){
  ingreso_11 <- mifuncion(n)
  
  
    nom_ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
    nombre <- paste("Ingresos_2011_",nom_ingreso, sep = "")
   ingreso_f <<-assign( paste("Ingresos_2011_",nom_ingreso, sep = ""), ingreso_11 )
   saveRDS(ingreso_f,nombre)
   head(ingreso_f,5)
  
}

6 2009

mifuncion <- function(n){
  
    ingreso <- switch(n,"YTOTAJ","YAUTAJ","YOPRAJ","YTRABAJ")
  
    bb <- dataset_2009[,c(ingreso)]
    aa <<-assign( paste(ingreso,  sep = ""), bb )

    a <- dataset_2009$aa
    b <- dataset_2009$COMUNA

    promedios_2009 <-aggregate(aa, by=list(b), FUN = mean , na.rm = TRUE)
    promedios_2009$Anio <- 2009
    names(promedios_2009)[1] <- "Comunas"
    names(promedios_2009)[2] <- "Promedios 2009"
    
    # promedios_2009<<-promedios_2009
    # print(promedios_2009)
    return(promedios_2009)

}
for (n in 1:4){
  ingreso_09 <- mifuncion(n)
  
  
    nom_ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
    nombre <- paste("Ingresos_2009_",nom_ingreso, sep = "")
   ingreso_f <<-assign( paste("Ingresos_2009_",nom_ingreso, sep = ""), ingreso_09 )
   saveRDS(ingreso_f,nombre)
   head(ingreso_f,5)
  
}

7 2006

mifuncion <- function(n){
  
    ingreso <- switch(n,"YTOTAJ","YAUTAJ","YOPRAJ","YTRABAJ")
  
    bb <- dataset_2006[,c(ingreso)]
    aa <<-assign( paste(ingreso,  sep = ""), bb )

    a <- dataset_2006$aa
    b <- dataset_2006$COMUNA

    promedios_2006 <-aggregate(aa, by=list(b), FUN = mean , na.rm = TRUE)
    promedios_2006$Anio <- 2006
    names(promedios_2006)[1] <- "Comunas"
    names(promedios_2006)[2] <- "Promedios 2006"
    
    promedios_2006<<-promedios_2006
    # head(promedios_2006,5)
    # print(promedios_2006)
    return(promedios_2006)

}
for (n in 1:4){
  ingreso_06 <- mifuncion(n)
  
  
    nom_ingreso <- switch(n,"ytotaj","yautaj","yopraj","ytrabaj")
    nombre <- paste("Ingresos_2006_",nom_ingreso, sep = "")
   ingreso_f <<-assign( paste("Ingresos_2006_",nom_ingreso, sep = ""), ingreso_06 )
   saveRDS(ingreso_f,nombre)
   head(ingreso_f,5)
   
  
}
df_yautaj <- data.frame()
for (n in 1:6) {
  
  anios<-switch(n,"2006","2009","2011","2013","2015","2017")
  nombres_sets <- paste("Ingresos_",anios,"_yautaj", sep = "")
  sets <- readRDS(nombres_sets)
  names(sets)[2]<-"Promedios"
  df_yautaj <- rbind(df_yautaj,sets)
# print(df_yautaj)
}
# write_xlsx(df_yautaj,"Ingresos_yautaj.xlsx")
# saveRDS(df_yautaj,"Ingresos_yautaj.rds")
df_ytotaj <- data.frame()
for (n in 1:6) {
  
  anios<-switch(n,"2006","2009","2011","2013","2015","2017")
  nombres_sets <- paste("Ingresos_",anios,"_ytotaj", sep = "")
  sets <- readRDS(nombres_sets)
  names(sets)[2]<-"Promedios"
  df_ytotaj <- rbind(df_ytotaj,sets)
# print(df_ytotaj)
}
# write_xlsx(df_ytotaj,"Ingresos_ytotaj.xlsx")
# saveRDS(df_ytotaj,"Ingresos_ytotaj.rds")
df_yopraj <- data.frame()
for (n in 1:6) {
  
  anios<-switch(n,"2006","2009","2011","2013","2015","2017")
  nombres_sets <- paste("Ingresos_",anios,"_yopraj", sep = "")
  sets <- readRDS(nombres_sets)
  names(sets)[2]<-"Promedios"
  df_yopraj <- rbind(df_yopraj,sets)
# print(df_yopraj)
}
# write_xlsx(df_yopraj,"Ingresos_2006_yopraj.xlsx")
# saveRDS(df_yopraj,"Ingresos_2006_yopraj.rds")
df_ytrabaj <- data.frame()
for (n in 1:6) {
  
  anios<-switch(n,"2006","2009","2011","2013","2015","2017")
  nombres_sets <- paste("Ingresos_",anios,"_ytrabaj", sep = "")
  sets <- readRDS(nombres_sets)
  names(sets)[2]<-"Promedios"
  df_ytrabaj <- rbind(df_ytrabaj,sets)
# print(df_ytrabaj)
}
# write_xlsx(df_ytrabaj,"Ingresos_2006_ytrabaj.xlsx")
# saveRDS(df_ytrabaj,"Ingresos_2006_ytrabaj.rds")

8. Graficos

ingreso <- readRDS("Ingresos_yautaj.rds")
ingreso <- as.data.frame(ingreso)

fig <- plot_ly(ingreso, x = ~ingreso$Anio, y = ~ingreso$Promedios, color=  ~ingreso$Comunas, type = 'scatter', mode = 'bar')%>% 
  layout(title = "yautaj",
         xaxis = list(title = "yautaj"), yaxis= list(title = "Ingreso"))

fig
## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
ingreso <- readRDS("Ingresos_ytotaj.rds")
ingreso <- as.data.frame(ingreso)

fig <- plot_ly(ingreso, x = ~ingreso$Anio, y = ~ingreso$Promedios, color=  ~ingreso$Comunas, type = 'scatter', mode = 'bar')%>% 
  layout(title = "ytotaj",
         xaxis = list(title = "ytotaj"), yaxis= list(title = "Ingreso"))

fig
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
ingreso <- readRDS("Ingresos_yopraj.rds")
ingreso <- as.data.frame(ingreso)

fig <- plot_ly(ingreso, x = ~ingreso$Anio, y = ~ingreso$Promedios, color=  ~ingreso$Comunas, type = 'scatter', mode = 'bar')%>% 
  layout(title = "yopraj",
         xaxis = list(title = "yopraj"), yaxis= list(title = "Ingreso"))

fig
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
ingreso <- readRDS("Ingresos_ytrabaj.rds")
ingreso <- as.data.frame(ingreso)

fig <- plot_ly(ingreso, x = ~ingreso$Anio, y = ~ingreso$Promedios, color=  ~ingreso$Comunas, type = 'scatter', mode = 'bar')%>% 
  layout(title = "ytrabaj",
         xaxis = list(title = "ytrabaj"), yaxis= list(title = "Ingreso"))

fig
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors