1 Variable CENSO

Necesitamos calcular las frecuencias a nivel censal de las respuestas correspondientes a la categoría: “Parquet, piso flotante, cerámico, madera, alfombra, flexit, cubrepiso u otro similar, sobre radier o vigas de madera” del campo P03C del Censo de viviendas. Recordemos que ésta fué la más alta correlación en relación a los ingresos expandidos (ver punto 1.2 aquí).

1.1 Lectura y filtrado de la tabla censal de viviendas

Leemos la tabla Censo 2017 de viviendas que ya tiene integrada la clave zonal:

tabla_con_clave <- readRDS("../censo_viviendas_con_clave_17.rds")
r3_100 <- tabla_con_clave[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
REGION PROVINCIA COMUNA DC AREA ZC_LOC ID_ZONA_LOC NVIV P01 P02 P03A P03B P03C P04 P05 CANT_HOG CANT_PER REGION_15R PROVINCIA_15R COMUNA_15R clave
15 152 15202 1 2 6 13225 1 3 1 5 3 5 1 4 1 1 15 152 15202 15202012006
15 152 15202 1 2 6 13225 2 1 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 3 1 1 5 3 5 2 3 1 4 15 152 15202 15202012006
15 152 15202 1 2 6 13225 4 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 5 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 6 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 7 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 8 3 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 9 3 1 5 3 5 1 4 1 4 15 152 15202 15202012006
15 152 15202 1 2 6 13225 10 1 1 5 3 4 1 4 1 1 15 152 15202 15202012006
15 152 15202 1 2 6 13225 11 1 2 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 12 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 13 1 1 5 3 4 1 4 1 3 15 152 15202 15202012006
15 152 15202 1 2 6 13225 14 1 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 15 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 16 1 1 5 3 5 1 3 1 3 15 152 15202 15202012006
15 152 15202 1 2 6 13225 17 1 1 5 3 5 2 4 1 8 15 152 15202 15202012006
15 152 15202 1 2 6 13225 18 3 1 5 3 5 1 1 1 1 15 152 15202 15202012006
15 152 15202 1 2 6 13225 19 3 1 5 3 5 1 3 1 1 15 152 15202 15202012006
15 152 15202 1 2 6 13225 20 1 1 5 3 5 2 1 1 2 15 152 15202 15202012006
15 152 15202 1 2 6 13225 21 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 22 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 23 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 24 1 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 25 1 1 5 3 5 1 4 1 2 15 152 15202 15202012006
15 152 15202 1 2 6 13225 26 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 27 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 28 3 1 5 3 5 1 4 1 5 15 152 15202 15202012006
15 152 15202 1 2 6 13225 29 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 30 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 31 1 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 32 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 33 1 1 5 3 5 3 4 1 4 15 152 15202 15202012006
15 152 15202 1 2 6 13225 34 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 35 3 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 36 1 1 5 3 5 3 2 1 9 15 152 15202 15202012006
15 152 15202 1 2 6 13225 37 3 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 38 1 1 5 3 5 99 4 1 1 15 152 15202 15202012006
15 152 15202 1 2 6 13225 39 1 1 5 3 5 1 4 1 2 15 152 15202 15202012006
15 152 15202 1 2 6 13225 40 1 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 41 1 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 42 3 3 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 43 3 1 5 3 5 2 1 1 5 15 152 15202 15202012006
15 152 15202 1 2 6 13225 44 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 6 13225 45 1 4 98 98 98 98 98 0 0 15 152 15202 15202012006
15 152 15202 1 2 8 13910 1 1 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 2 1 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 3 1 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 4 3 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 5 3 1 5 3 5 2 3 1 3 15 152 15202 15202012008
15 152 15202 1 2 8 13910 6 1 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 7 1 1 5 99 5 2 4 1 2 15 152 15202 15202012008
15 152 15202 1 2 8 13910 8 3 1 5 3 5 3 3 1 2 15 152 15202 15202012008
15 152 15202 1 2 8 13910 9 3 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 10 3 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 11 1 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 12 1 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 13 1 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 14 3 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 15 1 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 16 1 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 17 3 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 18 1 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 19 3 1 99 99 99 99 99 1 1 15 152 15202 15202012008
15 152 15202 1 2 8 13910 20 1 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 21 1 1 5 3 5 1 4 1 2 15 152 15202 15202012008
15 152 15202 1 2 8 13910 22 3 1 5 3 5 2 4 1 1 15 152 15202 15202012008
15 152 15202 1 2 8 13910 23 1 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 24 3 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 25 3 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 26 1 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 27 1 4 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 28 3 2 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 29 1 3 98 98 98 98 98 0 0 15 152 15202 15202012008
15 152 15202 1 2 8 13910 30 1 1 5 1 4 2 4 1 1 15 152 15202 15202012008
15 152 15202 1 2 12 8394 1 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 2 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 3 3 1 5 3 5 2 3 1 4 15 152 15202 15202012012
15 152 15202 1 2 12 8394 4 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 5 3 3 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 6 3 3 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 7 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 8 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 9 3 1 5 3 5 1 4 1 1 15 152 15202 15202012012
15 152 15202 1 2 12 8394 10 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 11 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 12 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 13 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 14 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 15 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 16 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 17 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 18 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 19 3 1 99 99 99 99 99 1 1 15 152 15202 15202012012
15 152 15202 1 2 12 8394 20 3 1 5 3 5 3 99 1 1 15 152 15202 15202012012
15 152 15202 1 2 12 8394 21 3 1 5 99 5 1 4 1 2 15 152 15202 15202012012
15 152 15202 1 2 12 8394 22 3 2 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 23 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012
15 152 15202 1 2 12 8394 24 3 1 5 3 5 1 2 1 2 15 152 15202 15202012012
15 152 15202 1 2 12 8394 25 3 4 98 98 98 98 98 0 0 15 152 15202 15202012012

Despleguemos los códigos de regiones de nuestra tabla:

regiones <- unique(tabla_con_clave$REGION)

Hagamos un subset con la 1:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 13) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$AREA== 1)

1.2 Cálculo de frecuencias

tabla_con_clave_f <- tabla_con_clave[,-c(1,2,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20),drop=FALSE]

aterial de construcción del piso

names(tabla_con_clave_f)[2] <- "Tipo de piso"
# Ahora filtramos por Tipo de techo = 1.
tabla_con_clave_ff <- filter(tabla_con_clave_f, tabla_con_clave_f$`Tipo de piso` == 1)
# Determinamos las frecuencias por zona:
b <- tabla_con_clave_ff$clave
c <- tabla_con_clave_ff$`Tipo de piso`
d <- tabla_con_clave_ff$COMUNA
cross_tab =  xtabs( ~ unlist(b) + unlist(c)+ unlist(d))
tabla <- as.data.frame(cross_tab)
d <-tabla[!(tabla$Freq == 0),]
names(d)[1] <- "zona" 
d$anio <- "2017"

Veamos los primeros 100 registros:

r3_100 <- d[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona unlist.c. unlist.d. Freq anio
13101011001 1 13101 1133 2017
13101011002 1 13101 1226 2017
13101011003 1 13101 1079 2017
13101011004 1 13101 892 2017
13101011005 1 13101 970 2017
13101021001 1 13101 1414 2017
13101021002 1 13101 1347 2017
13101021003 1 13101 1318 2017
13101021004 1 13101 1383 2017
13101021005 1 13101 961 2017
13101021006 1 13101 1161 2017
13101021007 1 13101 1041 2017
13101021008 1 13101 750 2017
13101031001 1 13101 1075 2017
13101031002 1 13101 2508 2017
13101031003 1 13101 2225 2017
13101031004 1 13101 1868 2017
13101031005 1 13101 821 2017
13101031006 1 13101 783 2017
13101031007 1 13101 1325 2017
13101041001 1 13101 1110 2017
13101041002 1 13101 1036 2017
13101041003 1 13101 1140 2017
13101041004 1 13101 1137 2017
13101041005 1 13101 1172 2017
13101051001 1 13101 1185 2017
13101051002 1 13101 1432 2017
13101051003 1 13101 658 2017
13101061001 1 13101 1504 2017
13101061002 1 13101 1495 2017
13101061003 1 13101 850 2017
13101071001 1 13101 1583 2017
13101071002 1 13101 1043 2017
13101071003 1 13101 1208 2017
13101081001 1 13101 1240 2017
13101081002 1 13101 1700 2017
13101081003 1 13101 1110 2017
13101081004 1 13101 907 2017
13101091001 1 13101 1048 2017
13101091002 1 13101 1325 2017
13101091003 1 13101 1251 2017
13101091004 1 13101 945 2017
13101101001 1 13101 1071 2017
13101101002 1 13101 843 2017
13101101003 1 13101 1374 2017
13101101004 1 13101 1244 2017
13101101005 1 13101 961 2017
13101101006 1 13101 652 2017
13101101007 1 13101 1473 2017
13101101008 1 13101 796 2017
13101101009 1 13101 721 2017
13101101010 1 13101 1371 2017
13101111001 1 13101 953 2017
13101111002 1 13101 1272 2017
13101111003 1 13101 1132 2017
13101111004 1 13101 932 2017
13101111005 1 13101 985 2017
13101111006 1 13101 799 2017
13101111007 1 13101 879 2017
13101111008 1 13101 1090 2017
13101111009 1 13101 1483 2017
13101111010 1 13101 1253 2017
13101111011 1 13101 698 2017
13101111012 1 13101 1976 2017
13101111013 1 13101 1595 2017
13101111014 1 13101 822 2017
13101111015 1 13101 1340 2017
13101111016 1 13101 1185 2017
13101111017 1 13101 833 2017
13101111018 1 13101 1267 2017
13101111019 1 13101 1214 2017
13101121001 1 13101 907 2017
13101121002 1 13101 855 2017
13101121003 1 13101 940 2017
13101121004 1 13101 1984 2017
13101121005 1 13101 818 2017
13101121006 1 13101 1415 2017
13101121007 1 13101 1286 2017
13101121008 1 13101 2163 2017
13101121009 1 13101 2202 2017
13101131001 1 13101 945 2017
13101131002 1 13101 897 2017
13101131003 1 13101 1873 2017
13101131004 1 13101 1152 2017
13101131005 1 13101 1434 2017
13101131006 1 13101 1062 2017
13101131007 1 13101 1435 2017
13101131008 1 13101 1433 2017
13101131009 1 13101 1664 2017
13101141001 1 13101 1444 2017
13101141002 1 13101 1302 2017
13101141003 1 13101 1851 2017
13101151001 1 13101 1703 2017
13101151002 1 13101 1572 2017
13101151003 1 13101 1404 2017
13101151004 1 13101 752 2017
13101161001 1 13101 1362 2017
13101161002 1 13101 1909 2017
13101161003 1 13101 2070 2017
13101171001 1 13101 1637 2017

Agregamos un cero a los códigos comunales de cuatro dígitos:

codigos <- d$unlist.d.
rango <- seq(1:nrow(d))
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,cadena)
comuna_corr <- comuna_corr[,-c(2,3),drop=FALSE]
names(comuna_corr)[4] <- "código" 
r3_100 <- comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona Freq anio código
13101011001 1133 2017 13101
13101011002 1226 2017 13101
13101011003 1079 2017 13101
13101011004 892 2017 13101
13101011005 970 2017 13101
13101021001 1414 2017 13101
13101021002 1347 2017 13101
13101021003 1318 2017 13101
13101021004 1383 2017 13101
13101021005 961 2017 13101
13101021006 1161 2017 13101
13101021007 1041 2017 13101
13101021008 750 2017 13101
13101031001 1075 2017 13101
13101031002 2508 2017 13101
13101031003 2225 2017 13101
13101031004 1868 2017 13101
13101031005 821 2017 13101
13101031006 783 2017 13101
13101031007 1325 2017 13101
13101041001 1110 2017 13101
13101041002 1036 2017 13101
13101041003 1140 2017 13101
13101041004 1137 2017 13101
13101041005 1172 2017 13101
13101051001 1185 2017 13101
13101051002 1432 2017 13101
13101051003 658 2017 13101
13101061001 1504 2017 13101
13101061002 1495 2017 13101
13101061003 850 2017 13101
13101071001 1583 2017 13101
13101071002 1043 2017 13101
13101071003 1208 2017 13101
13101081001 1240 2017 13101
13101081002 1700 2017 13101
13101081003 1110 2017 13101
13101081004 907 2017 13101
13101091001 1048 2017 13101
13101091002 1325 2017 13101
13101091003 1251 2017 13101
13101091004 945 2017 13101
13101101001 1071 2017 13101
13101101002 843 2017 13101
13101101003 1374 2017 13101
13101101004 1244 2017 13101
13101101005 961 2017 13101
13101101006 652 2017 13101
13101101007 1473 2017 13101
13101101008 796 2017 13101
13101101009 721 2017 13101
13101101010 1371 2017 13101
13101111001 953 2017 13101
13101111002 1272 2017 13101
13101111003 1132 2017 13101
13101111004 932 2017 13101
13101111005 985 2017 13101
13101111006 799 2017 13101
13101111007 879 2017 13101
13101111008 1090 2017 13101
13101111009 1483 2017 13101
13101111010 1253 2017 13101
13101111011 698 2017 13101
13101111012 1976 2017 13101
13101111013 1595 2017 13101
13101111014 822 2017 13101
13101111015 1340 2017 13101
13101111016 1185 2017 13101
13101111017 833 2017 13101
13101111018 1267 2017 13101
13101111019 1214 2017 13101
13101121001 907 2017 13101
13101121002 855 2017 13101
13101121003 940 2017 13101
13101121004 1984 2017 13101
13101121005 818 2017 13101
13101121006 1415 2017 13101
13101121007 1286 2017 13101
13101121008 2163 2017 13101
13101121009 2202 2017 13101
13101131001 945 2017 13101
13101131002 897 2017 13101
13101131003 1873 2017 13101
13101131004 1152 2017 13101
13101131005 1434 2017 13101
13101131006 1062 2017 13101
13101131007 1435 2017 13101
13101131008 1433 2017 13101
13101131009 1664 2017 13101
13101141001 1444 2017 13101
13101141002 1302 2017 13101
13101141003 1851 2017 13101
13101151001 1703 2017 13101
13101151002 1572 2017 13101
13101151003 1404 2017 13101
13101151004 752 2017 13101
13101161001 1362 2017 13101
13101161002 1909 2017 13101
13101161003 2070 2017 13101
13101171001 1637 2017 13101


2 Variable CASEN

2.1 Tabla de ingresos expandidos

Hemos calculado ya éste valor como conclusión del punto 1.1 de aquí

h_y_m_2017_censo <- readRDS("../ingresos_expandidos_urbano_17.rds")
tablamadre <- head(h_y_m_2017_censo,50)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
código comuna.x promedio_i año comuna.y personas Ingresos_expandidos
01101 Iquique 375676.9 2017 1101 191468 71930106513
01107 Alto Hospicio 311571.7 2017 1107 108375 33766585496
01401 Pozo Almonte 316138.5 2017 1401 15711 4966851883
01405 Pica 330061.1 2017 1405 9296 3068247619
02101 Antofagasta 368221.4 2017 2101 361873 133249367039
02102 Mejillones 369770.7 2017 2102 13467 4979702302
02104 Taltal 383666.2 2017 2104 13317 5109282942
02201 Calama 434325.1 2017 2201 165731 71981127235
02203 San Pedro de Atacama 442861.0 2017 2203 10996 4869699464
02301 Tocopilla 286187.2 2017 2301 25186 7207910819
02302 María Elena 477748.0 2017 2302 6457 3084818966
03101 Copiapó 343121.0 2017 3101 153937 52819016037
03102 Caldera 318653.2 2017 3102 17662 5628052276
03103 Tierra Amarilla 333194.9 2017 3103 14019 4671058718
03201 Chañaral 286389.3 2017 3201 12219 3499391196
03202 Diego de Almagro 351583.9 2017 3202 13925 4895805596
03301 Vallenar 315981.5 2017 3301 51917 16404810756
03303 Freirina 289049.9 2017 3303 7041 2035200054
03304 Huasco 337414.8 2017 3304 10149 3424422750
04101 La Serena 279340.1 2017 4101 221054 61749247282
04102 Coquimbo 269078.6 2017 4102 227730 61277269093
04103 Andacollo 258539.7 2017 4103 11044 2855312920
04104 La Higuera 214257.0 2017 4104 4241 908664019
04106 Vicuña 254177.0 2017 4106 27771 7058750373
04201 Illapel 282139.3 2017 4201 30848 8703433491
04202 Canela 233397.3 2017 4202 9093 2122281844
04203 Los Vilos 285214.0 2017 4203 21382 6098444926
04204 Salamanca 262056.9 2017 4204 29347 7690585032
04301 Ovalle 280373.5 2017 4301 111272 31197719080
04302 Combarbalá 234537.3 2017 4302 13322 3124505460
04303 Monte Patria 225369.1 2017 4303 30751 6930326684
04304 Punitaqui 212496.1 2017 4304 10956 2328107498
05101 Valparaíso 306572.5 2017 5101 296655 90946261553
05102 Casablanca 348088.6 2017 5102 26867 9352095757
05103 Concón 333932.4 2017 5103 42152 14075920021
05105 Puchuncaví 296035.5 2017 5105 18546 5490274928
05107 Quintero 308224.7 2017 5107 31923 9839456903
05109 Viña del Mar 354715.9 2017 5109 334248 118563074323
05301 Los Andes 355446.2 2017 5301 66708 23711104774
05302 Calle Larga 246387.3 2017 5302 14832 3654416747
05303 Rinconada 279807.9 2017 5303 10207 2855998928
05304 San Esteban 219571.6 2017 5304 18855 4140022481
05401 La Ligua 259482.3 2017 5401 35390 9183080280
05402 Cabildo 262745.9 2017 5402 19388 5094117762
05403 Papudo 302317.1 2017 5403 6356 1921527704
05404 Petorca 237510.8 2017 5404 9826 2333781007
05405 Zapallar 294389.2 2017 5405 7339 2160521991
05501 Quillota 288694.2 2017 5501 90517 26131733924
05502 Calera 282823.6 2017 5502 50554 14297866792
05503 Hijuelas 268449.7 2017 5503 17988 4828872604

3 Unión Censo-Casen

Integramos a la tabla censal de frecuencias la tabla de ingresos expandidos de la Casen.

comunas_con_ing_exp = merge( x = comuna_corr, y = h_y_m_2017_censo, by = "código", all.x = TRUE)
comunas_con_ing_exp <-comunas_con_ing_exp[!(is.na(comunas_con_ing_exp$Ingresos_expandidos)),]
r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
código zona Freq anio comuna.x promedio_i año comuna.y personas Ingresos_expandidos
13101 13101011001 1133 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011002 1226 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011003 1079 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011004 892 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011005 970 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021001 1414 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021002 1347 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021003 1318 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021004 1383 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021005 961 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021006 1161 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021007 1041 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021008 750 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031001 1075 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031002 2508 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031003 2225 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031004 1868 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031005 821 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031006 783 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031007 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041001 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041002 1036 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041003 1140 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041004 1137 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041005 1172 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101051001 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101051002 1432 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101051003 658 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101061001 1504 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101061002 1495 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101061003 850 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101071001 1583 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101071002 1043 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101071003 1208 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081001 1240 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081002 1700 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081003 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081004 907 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091001 1048 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091002 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091003 1251 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091004 945 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101001 1071 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101002 843 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101003 1374 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101004 1244 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101005 961 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101006 652 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101007 1473 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101008 796 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101009 721 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101010 1371 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111001 953 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111002 1272 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111003 1132 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111004 932 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111005 985 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111006 799 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111007 879 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111008 1090 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111009 1483 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111010 1253 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111011 698 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111012 1976 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111013 1595 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111014 822 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111015 1340 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111016 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111017 833 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111018 1267 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111019 1214 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121001 907 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121002 855 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121003 940 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121004 1984 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121005 818 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121006 1415 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121007 1286 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121008 2163 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121009 2202 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131001 945 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131002 897 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131003 1873 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131004 1152 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131005 1434 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131006 1062 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131007 1435 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131008 1433 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131009 1664 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101141001 1444 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101141002 1302 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101141003 1851 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151001 1703 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151002 1572 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151003 1404 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151004 752 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101161001 1362 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101161002 1909 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101161003 2070 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101171001 1637 2017 Santiago 450851.7 2017 13101 404495 182367246208


4 Proporción poblacional zonal respecto a la comunal

Del censo obtenemos la cantidad de población a nivel de zona y estimamos su proporción a nivel comunal. Ya hemos calculado ésta proporción aquí.

prop_pob <- readRDS("../tabla_de_prop_pob.rds")
names(prop_pob)[1] <- "zona"
names(prop_pob)[3] <- "p_poblacional"

Veamos los 100 primeros registros:

r3_100 <- prop_pob[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona Freq p_poblacional código
1101011001 2491 0.0130100 01101
1101011002 1475 0.0077036 01101
1101021001 1003 0.0052385 01101
1101021002 54 0.0002820 01101
1101021003 2895 0.0151200 01101
1101021004 2398 0.0125243 01101
1101021005 4525 0.0236332 01101
1101031001 2725 0.0142321 01101
1101031002 3554 0.0185618 01101
1101031003 5246 0.0273988 01101
1101031004 3389 0.0177001 01101
1101041001 1800 0.0094010 01101
1101041002 2538 0.0132555 01101
1101041003 3855 0.0201339 01101
1101041004 5663 0.0295767 01101
1101041005 4162 0.0217373 01101
1101041006 2689 0.0140441 01101
1101051001 3296 0.0172144 01101
1101051002 4465 0.0233198 01101
1101051003 4656 0.0243174 01101
1101051004 2097 0.0109522 01101
1101051005 3569 0.0186402 01101
1101051006 2741 0.0143157 01101
1101061001 1625 0.0084871 01101
1101061002 4767 0.0248971 01101
1101061003 4826 0.0252053 01101
1101061004 4077 0.0212934 01101
1101061005 2166 0.0113126 01101
1101071001 2324 0.0121378 01101
1101071002 2801 0.0146291 01101
1101071003 3829 0.0199981 01101
1101071004 1987 0.0103777 01101
1101081001 5133 0.0268087 01101
1101081002 3233 0.0168853 01101
1101081003 2122 0.0110828 01101
1101081004 2392 0.0124929 01101
1101092001 57 0.0002977 01101
1101092004 247 0.0012900 01101
1101092005 76 0.0003969 01101
1101092006 603 0.0031494 01101
1101092007 84 0.0004387 01101
1101092010 398 0.0020787 01101
1101092012 58 0.0003029 01101
1101092014 23 0.0001201 01101
1101092016 20 0.0001045 01101
1101092017 8 0.0000418 01101
1101092018 74 0.0003865 01101
1101092019 25 0.0001306 01101
1101092021 177 0.0009244 01101
1101092022 23 0.0001201 01101
1101092023 288 0.0015042 01101
1101092024 14 0.0000731 01101
1101092901 30 0.0001567 01101
1101101001 2672 0.0139553 01101
1101101002 4398 0.0229699 01101
1101101003 4524 0.0236280 01101
1101101004 3544 0.0185096 01101
1101101005 4911 0.0256492 01101
1101101006 3688 0.0192617 01101
1101111001 3886 0.0202958 01101
1101111002 2312 0.0120751 01101
1101111003 4874 0.0254560 01101
1101111004 4543 0.0237272 01101
1101111005 4331 0.0226200 01101
1101111006 3253 0.0169898 01101
1101111007 4639 0.0242286 01101
1101111008 4881 0.0254925 01101
1101111009 5006 0.0261454 01101
1101111010 366 0.0019115 01101
1101111011 4351 0.0227244 01101
1101111012 2926 0.0152819 01101
1101111013 3390 0.0177053 01101
1101111014 2940 0.0153550 01101
1101112003 33 0.0001724 01101
1101112013 104 0.0005432 01101
1101112019 34 0.0001776 01101
1101112025 21 0.0001097 01101
1101112901 6 0.0000313 01101
1101991999 1062 0.0055466 01101
1107011001 4104 0.0378685 01107
1107011002 4360 0.0402307 01107
1107011003 8549 0.0788835 01107
1107012003 3 0.0000277 01107
1107012901 17 0.0001569 01107
1107021001 6701 0.0618316 01107
1107021002 3971 0.0366413 01107
1107021003 6349 0.0585836 01107
1107021004 5125 0.0472895 01107
1107021005 4451 0.0410704 01107
1107021006 3864 0.0356540 01107
1107021007 5235 0.0483045 01107
1107021008 4566 0.0421315 01107
1107031001 4195 0.0387082 01107
1107031002 7099 0.0655040 01107
1107031003 4720 0.0435525 01107
1107032005 38 0.0003506 01107
1107032006 2399 0.0221361 01107
1107032008 4 0.0000369 01107
1107041001 3630 0.0334948 01107
1107041002 5358 0.0494394 01107


5 Ingreso medio

Deseamos el valor del ingreso promedio a nivel comunal, pero expandido a nivel zonal. Ésta información está contenida en el campo promedio_i de la tabla obtenida en el punto 3.

r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
código zona Freq anio comuna.x promedio_i año comuna.y personas Ingresos_expandidos
13101 13101011001 1133 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011002 1226 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011003 1079 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011004 892 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101011005 970 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021001 1414 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021002 1347 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021003 1318 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021004 1383 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021005 961 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021006 1161 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021007 1041 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101021008 750 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031001 1075 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031002 2508 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031003 2225 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031004 1868 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031005 821 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031006 783 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101031007 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041001 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041002 1036 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041003 1140 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041004 1137 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101041005 1172 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101051001 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101051002 1432 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101051003 658 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101061001 1504 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101061002 1495 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101061003 850 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101071001 1583 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101071002 1043 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101071003 1208 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081001 1240 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081002 1700 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081003 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101081004 907 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091001 1048 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091002 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091003 1251 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101091004 945 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101001 1071 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101002 843 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101003 1374 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101004 1244 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101005 961 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101006 652 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101007 1473 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101008 796 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101009 721 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101101010 1371 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111001 953 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111002 1272 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111003 1132 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111004 932 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111005 985 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111006 799 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111007 879 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111008 1090 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111009 1483 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111010 1253 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111011 698 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111012 1976 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111013 1595 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111014 822 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111015 1340 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111016 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111017 833 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111018 1267 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101111019 1214 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121001 907 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121002 855 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121003 940 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121004 1984 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121005 818 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121006 1415 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121007 1286 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121008 2163 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101121009 2202 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131001 945 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131002 897 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131003 1873 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131004 1152 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131005 1434 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131006 1062 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131007 1435 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131008 1433 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101131009 1664 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101141001 1444 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101141002 1302 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101141003 1851 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151001 1703 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151002 1572 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151003 1404 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101151004 752 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101161001 1362 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101161002 1909 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101161003 2070 2017 Santiago 450851.7 2017 13101 404495 182367246208
13101 13101171001 1637 2017 Santiago 450851.7 2017 13101 404495 182367246208


6 Ingreso promedio expandido por zona (multi_pob)

En éste momento vamos a construir nuestra variable dependiente de regresión aplicando la siguiente fórmula:

\[ multi\_pob = promedio\_i \cdot personas \cdot p\_poblacional \]

Para ello integramos a la tabla de ingresos expandidos a nivel zonal (punto 3) la tabla de proporciones poblacionales zonales respecto al total comunal (punto 4) :

h_y_m_comuna_corr_01 = merge( x = comunas_con_ing_exp, y = prop_pob, by = "zona", all.x = TRUE)
tablamadre <- head(h_y_m_comuna_corr_01,100)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona código.x Freq.x anio comuna.x promedio_i año comuna.y personas Ingresos_expandidos Freq.y p_poblacional código.y
13101011001 13101 1133 2017 Santiago 450851.7 2017 13101 404495 182367246208 2174 0.0053746 13101
13101011002 13101 1226 2017 Santiago 450851.7 2017 13101 404495 182367246208 2282 0.0056416 13101
13101011003 13101 1079 2017 Santiago 450851.7 2017 13101 404495 182367246208 2209 0.0054611 13101
13101011004 13101 892 2017 Santiago 450851.7 2017 13101 404495 182367246208 1821 0.0045019 13101
13101011005 13101 970 2017 Santiago 450851.7 2017 13101 404495 182367246208 1741 0.0043041 13101
13101021001 13101 1414 2017 Santiago 450851.7 2017 13101 404495 182367246208 3448 0.0085242 13101
13101021002 13101 1347 2017 Santiago 450851.7 2017 13101 404495 182367246208 2856 0.0070607 13101
13101021003 13101 1318 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101
13101021004 13101 1383 2017 Santiago 450851.7 2017 13101 404495 182367246208 3279 0.0081064 13101
13101021005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 2258 0.0055823 13101
13101021006 13101 1161 2017 Santiago 450851.7 2017 13101 404495 182367246208 2478 0.0061262 13101
13101021007 13101 1041 2017 Santiago 450851.7 2017 13101 404495 182367246208 2326 0.0057504 13101
13101021008 13101 750 2017 Santiago 450851.7 2017 13101 404495 182367246208 1541 0.0038097 13101
13101031001 13101 1075 2017 Santiago 450851.7 2017 13101 404495 182367246208 2313 0.0057182 13101
13101031002 13101 2508 2017 Santiago 450851.7 2017 13101 404495 182367246208 5950 0.0147097 13101
13101031003 13101 2225 2017 Santiago 450851.7 2017 13101 404495 182367246208 4955 0.0122498 13101
13101031004 13101 1868 2017 Santiago 450851.7 2017 13101 404495 182367246208 3903 0.0096491 13101
13101031005 13101 821 2017 Santiago 450851.7 2017 13101 404495 182367246208 1791 0.0044277 13101
13101031006 13101 783 2017 Santiago 450851.7 2017 13101 404495 182367246208 1697 0.0041954 13101
13101031007 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 2973 0.0073499 13101
13101041001 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 2790 0.0068975 13101
13101041002 13101 1036 2017 Santiago 450851.7 2017 13101 404495 182367246208 2668 0.0065959 13101
13101041003 13101 1140 2017 Santiago 450851.7 2017 13101 404495 182367246208 2729 0.0067467 13101
13101041004 13101 1137 2017 Santiago 450851.7 2017 13101 404495 182367246208 2828 0.0069914 13101
13101041005 13101 1172 2017 Santiago 450851.7 2017 13101 404495 182367246208 2550 0.0063042 13101
13101051001 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 3135 0.0077504 13101
13101051002 13101 1432 2017 Santiago 450851.7 2017 13101 404495 182367246208 4424 0.0109371 13101
13101051003 13101 658 2017 Santiago 450851.7 2017 13101 404495 182367246208 2355 0.0058221 13101
13101061001 13101 1504 2017 Santiago 450851.7 2017 13101 404495 182367246208 3968 0.0098098 13101
13101061002 13101 1495 2017 Santiago 450851.7 2017 13101 404495 182367246208 4747 0.0117356 13101
13101061003 13101 850 2017 Santiago 450851.7 2017 13101 404495 182367246208 2864 0.0070804 13101
13101071001 13101 1583 2017 Santiago 450851.7 2017 13101 404495 182367246208 5009 0.0123833 13101
13101071002 13101 1043 2017 Santiago 450851.7 2017 13101 404495 182367246208 3511 0.0086800 13101
13101071003 13101 1208 2017 Santiago 450851.7 2017 13101 404495 182367246208 3368 0.0083264 13101
13101081001 13101 1240 2017 Santiago 450851.7 2017 13101 404495 182367246208 3716 0.0091868 13101
13101081002 13101 1700 2017 Santiago 450851.7 2017 13101 404495 182367246208 5244 0.0129643 13101
13101081003 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 3326 0.0082226 13101
13101081004 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2794 0.0069074 13101
13101091001 13101 1048 2017 Santiago 450851.7 2017 13101 404495 182367246208 3393 0.0083882 13101
13101091002 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 3321 0.0082102 13101
13101091003 13101 1251 2017 Santiago 450851.7 2017 13101 404495 182367246208 3210 0.0079358 13101
13101091004 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 2956 0.0073079 13101
13101101001 13101 1071 2017 Santiago 450851.7 2017 13101 404495 182367246208 2491 0.0061583 13101
13101101002 13101 843 2017 Santiago 450851.7 2017 13101 404495 182367246208 1820 0.0044994 13101
13101101003 13101 1374 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101
13101101004 13101 1244 2017 Santiago 450851.7 2017 13101 404495 182367246208 2423 0.0059902 13101
13101101005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 1805 0.0044624 13101
13101101006 13101 652 2017 Santiago 450851.7 2017 13101 404495 182367246208 1296 0.0032040 13101
13101101007 13101 1473 2017 Santiago 450851.7 2017 13101 404495 182367246208 2965 0.0073301 13101
13101101008 13101 796 2017 Santiago 450851.7 2017 13101 404495 182367246208 1624 0.0040149 13101
13101101009 13101 721 2017 Santiago 450851.7 2017 13101 404495 182367246208 1345 0.0033251 13101
13101101010 13101 1371 2017 Santiago 450851.7 2017 13101 404495 182367246208 2930 0.0072436 13101
13101111001 13101 953 2017 Santiago 450851.7 2017 13101 404495 182367246208 2555 0.0063165 13101
13101111002 13101 1272 2017 Santiago 450851.7 2017 13101 404495 182367246208 2594 0.0064129 13101
13101111003 13101 1132 2017 Santiago 450851.7 2017 13101 404495 182367246208 2269 0.0056095 13101
13101111004 13101 932 2017 Santiago 450851.7 2017 13101 404495 182367246208 1996 0.0049345 13101
13101111005 13101 985 2017 Santiago 450851.7 2017 13101 404495 182367246208 1960 0.0048455 13101
13101111006 13101 799 2017 Santiago 450851.7 2017 13101 404495 182367246208 1677 0.0041459 13101
13101111007 13101 879 2017 Santiago 450851.7 2017 13101 404495 182367246208 1859 0.0045959 13101
13101111008 13101 1090 2017 Santiago 450851.7 2017 13101 404495 182367246208 2552 0.0063091 13101
13101111009 13101 1483 2017 Santiago 450851.7 2017 13101 404495 182367246208 3455 0.0085415 13101
13101111010 13101 1253 2017 Santiago 450851.7 2017 13101 404495 182367246208 2560 0.0063289 13101
13101111011 13101 698 2017 Santiago 450851.7 2017 13101 404495 182367246208 1550 0.0038319 13101
13101111012 13101 1976 2017 Santiago 450851.7 2017 13101 404495 182367246208 4104 0.0101460 13101
13101111013 13101 1595 2017 Santiago 450851.7 2017 13101 404495 182367246208 3191 0.0078888 13101
13101111014 13101 822 2017 Santiago 450851.7 2017 13101 404495 182367246208 1894 0.0046824 13101
13101111015 13101 1340 2017 Santiago 450851.7 2017 13101 404495 182367246208 2747 0.0067912 13101
13101111016 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 2452 0.0060619 13101
13101111017 13101 833 2017 Santiago 450851.7 2017 13101 404495 182367246208 1798 0.0044450 13101
13101111018 13101 1267 2017 Santiago 450851.7 2017 13101 404495 182367246208 2724 0.0067343 13101
13101111019 13101 1214 2017 Santiago 450851.7 2017 13101 404495 182367246208 2430 0.0060075 13101
13101121001 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2320 0.0057355 13101
13101121002 13101 855 2017 Santiago 450851.7 2017 13101 404495 182367246208 1774 0.0043857 13101
13101121003 13101 940 2017 Santiago 450851.7 2017 13101 404495 182367246208 2011 0.0049716 13101
13101121004 13101 1984 2017 Santiago 450851.7 2017 13101 404495 182367246208 4425 0.0109396 13101
13101121005 13101 818 2017 Santiago 450851.7 2017 13101 404495 182367246208 2095 0.0051793 13101
13101121006 13101 1415 2017 Santiago 450851.7 2017 13101 404495 182367246208 3272 0.0080891 13101
13101121007 13101 1286 2017 Santiago 450851.7 2017 13101 404495 182367246208 3067 0.0075823 13101
13101121008 13101 2163 2017 Santiago 450851.7 2017 13101 404495 182367246208 4682 0.0115749 13101
13101121009 13101 2202 2017 Santiago 450851.7 2017 13101 404495 182367246208 4441 0.0109791 13101
13101131001 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 1811 0.0044772 13101
13101131002 13101 897 2017 Santiago 450851.7 2017 13101 404495 182367246208 1759 0.0043486 13101
13101131003 13101 1873 2017 Santiago 450851.7 2017 13101 404495 182367246208 3953 0.0097727 13101
13101131004 13101 1152 2017 Santiago 450851.7 2017 13101 404495 182367246208 2442 0.0060372 13101
13101131005 13101 1434 2017 Santiago 450851.7 2017 13101 404495 182367246208 3683 0.0091052 13101
13101131006 13101 1062 2017 Santiago 450851.7 2017 13101 404495 182367246208 2197 0.0054315 13101
13101131007 13101 1435 2017 Santiago 450851.7 2017 13101 404495 182367246208 2952 0.0072980 13101
13101131008 13101 1433 2017 Santiago 450851.7 2017 13101 404495 182367246208 3025 0.0074785 13101
13101131009 13101 1664 2017 Santiago 450851.7 2017 13101 404495 182367246208 3631 0.0089766 13101
13101141001 13101 1444 2017 Santiago 450851.7 2017 13101 404495 182367246208 4373 0.0108110 13101
13101141002 13101 1302 2017 Santiago 450851.7 2017 13101 404495 182367246208 3048 0.0075353 13101
13101141003 13101 1851 2017 Santiago 450851.7 2017 13101 404495 182367246208 4067 0.0100545 13101
13101151001 13101 1703 2017 Santiago 450851.7 2017 13101 404495 182367246208 4797 0.0118592 13101
13101151002 13101 1572 2017 Santiago 450851.7 2017 13101 404495 182367246208 3915 0.0096787 13101
13101151003 13101 1404 2017 Santiago 450851.7 2017 13101 404495 182367246208 3644 0.0090088 13101
13101151004 13101 752 2017 Santiago 450851.7 2017 13101 404495 182367246208 2038 0.0050384 13101
13101161001 13101 1362 2017 Santiago 450851.7 2017 13101 404495 182367246208 2637 0.0065192 13101
13101161002 13101 1909 2017 Santiago 450851.7 2017 13101 404495 182367246208 5341 0.0132041 13101
13101161003 13101 2070 2017 Santiago 450851.7 2017 13101 404495 182367246208 5331 0.0131794 13101
13101171001 13101 1637 2017 Santiago 450851.7 2017 13101 404495 182367246208 5638 0.0139384 13101


Hacemos la multiplicación que queda almacenada en la variable multi_pob:

h_y_m_comuna_corr_01$multi_pob <- h_y_m_comuna_corr_01$promedio_i * h_y_m_comuna_corr_01$personas * h_y_m_comuna_corr_01$p_poblacional
tablamadre <- head(h_y_m_comuna_corr_01,100)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona código.x Freq.x anio comuna.x promedio_i año comuna.y personas Ingresos_expandidos Freq.y p_poblacional código.y multi_pob
13101011001 13101 1133 2017 Santiago 450851.7 2017 13101 404495 182367246208 2174 0.0053746 13101 980151530
13101011002 13101 1226 2017 Santiago 450851.7 2017 13101 404495 182367246208 2282 0.0056416 13101 1028843511
13101011003 13101 1079 2017 Santiago 450851.7 2017 13101 404495 182367246208 2209 0.0054611 13101 995931339
13101011004 13101 892 2017 Santiago 450851.7 2017 13101 404495 182367246208 1821 0.0045019 13101 821000891
13101011005 13101 970 2017 Santiago 450851.7 2017 13101 404495 182367246208 1741 0.0043041 13101 784932757
13101021001 13101 1414 2017 Santiago 450851.7 2017 13101 404495 182367246208 3448 0.0085242 13101 1554536558
13101021002 13101 1347 2017 Santiago 450851.7 2017 13101 404495 182367246208 2856 0.0070607 13101 1287632369
13101021003 13101 1318 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101 1247957422
13101021004 13101 1383 2017 Santiago 450851.7 2017 13101 404495 182367246208 3279 0.0081064 13101 1478342626
13101021005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 2258 0.0055823 13101 1018023071
13101021006 13101 1161 2017 Santiago 450851.7 2017 13101 404495 182367246208 2478 0.0061262 13101 1117210438
13101021007 13101 1041 2017 Santiago 450851.7 2017 13101 404495 182367246208 2326 0.0057504 13101 1048680984
13101021008 13101 750 2017 Santiago 450851.7 2017 13101 404495 182367246208 1541 0.0038097 13101 694762423
13101031001 13101 1075 2017 Santiago 450851.7 2017 13101 404495 182367246208 2313 0.0057182 13101 1042819912
13101031002 13101 2508 2017 Santiago 450851.7 2017 13101 404495 182367246208 5950 0.0147097 13101 2682567436
13101031003 13101 2225 2017 Santiago 450851.7 2017 13101 404495 182367246208 4955 0.0122498 13101 2233970024
13101031004 13101 1868 2017 Santiago 450851.7 2017 13101 404495 182367246208 3903 0.0096491 13101 1759674068
13101031005 13101 821 2017 Santiago 450851.7 2017 13101 404495 182367246208 1791 0.0044277 13101 807475341
13101031006 13101 783 2017 Santiago 450851.7 2017 13101 404495 182367246208 1697 0.0041954 13101 765095284
13101031007 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 2973 0.0073499 13101 1340382015
13101041001 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 2790 0.0068975 13101 1257876159
13101041002 13101 1036 2017 Santiago 450851.7 2017 13101 404495 182367246208 2668 0.0065959 13101 1202872255
13101041003 13101 1140 2017 Santiago 450851.7 2017 13101 404495 182367246208 2729 0.0067467 13101 1230374207
13101041004 13101 1137 2017 Santiago 450851.7 2017 13101 404495 182367246208 2828 0.0069914 13101 1275008522
13101041005 13101 1172 2017 Santiago 450851.7 2017 13101 404495 182367246208 2550 0.0063042 13101 1149671758
13101051001 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 3135 0.0077504 13101 1413419985
13101051002 13101 1432 2017 Santiago 450851.7 2017 13101 404495 182367246208 4424 0.0109371 13101 1994567788
13101051003 13101 658 2017 Santiago 450851.7 2017 13101 404495 182367246208 2355 0.0058221 13101 1061755683
13101061001 13101 1504 2017 Santiago 450851.7 2017 13101 404495 182367246208 3968 0.0098098 13101 1788979426
13101061002 13101 1495 2017 Santiago 450851.7 2017 13101 404495 182367246208 4747 0.0117356 13101 2140192877
13101061003 13101 850 2017 Santiago 450851.7 2017 13101 404495 182367246208 2864 0.0070804 13101 1291239183
13101071001 13101 1583 2017 Santiago 450851.7 2017 13101 404495 182367246208 5009 0.0123833 13101 2258316014
13101071002 13101 1043 2017 Santiago 450851.7 2017 13101 404495 182367246208 3511 0.0086800 13101 1582940213
13101071003 13101 1208 2017 Santiago 450851.7 2017 13101 404495 182367246208 3368 0.0083264 13101 1518468424
13101081001 13101 1240 2017 Santiago 450851.7 2017 13101 404495 182367246208 3716 0.0091868 13101 1675364805
13101081002 13101 1700 2017 Santiago 450851.7 2017 13101 404495 182367246208 5244 0.0129643 13101 2364266157
13101081003 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 3326 0.0082226 13101 1499532654
13101081004 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2794 0.0069074 13101 1259679566
13101091001 13101 1048 2017 Santiago 450851.7 2017 13101 404495 182367246208 3393 0.0083882 13101 1529739716
13101091002 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 3321 0.0082102 13101 1497278396
13101091003 13101 1251 2017 Santiago 450851.7 2017 13101 404495 182367246208 3210 0.0079358 13101 1447233860
13101091004 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 2956 0.0073079 13101 1332717536
13101101001 13101 1071 2017 Santiago 450851.7 2017 13101 404495 182367246208 2491 0.0061583 13101 1123071510
13101101002 13101 843 2017 Santiago 450851.7 2017 13101 404495 182367246208 1820 0.0044994 13101 820550039
13101101003 13101 1374 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101 1247957422
13101101004 13101 1244 2017 Santiago 450851.7 2017 13101 404495 182367246208 2423 0.0059902 13101 1092413596
13101101005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 1805 0.0044624 13101 813787264
13101101006 13101 652 2017 Santiago 450851.7 2017 13101 404495 182367246208 1296 0.0032040 13101 584303764
13101101007 13101 1473 2017 Santiago 450851.7 2017 13101 404495 182367246208 2965 0.0073301 13101 1336775201
13101101008 13101 796 2017 Santiago 450851.7 2017 13101 404495 182367246208 1624 0.0040149 13101 732183112
13101101009 13101 721 2017 Santiago 450851.7 2017 13101 404495 182367246208 1345 0.0033251 13101 606395496
13101101010 13101 1371 2017 Santiago 450851.7 2017 13101 404495 182367246208 2930 0.0072436 13101 1320995393
13101111001 13101 953 2017 Santiago 450851.7 2017 13101 404495 182367246208 2555 0.0063165 13101 1151926017
13101111002 13101 1272 2017 Santiago 450851.7 2017 13101 404495 182367246208 2594 0.0064129 13101 1169509232
13101111003 13101 1132 2017 Santiago 450851.7 2017 13101 404495 182367246208 2269 0.0056095 13101 1022982439
13101111004 13101 932 2017 Santiago 450851.7 2017 13101 404495 182367246208 1996 0.0049345 13101 899899933
13101111005 13101 985 2017 Santiago 450851.7 2017 13101 404495 182367246208 1960 0.0048455 13101 883669273
13101111006 13101 799 2017 Santiago 450851.7 2017 13101 404495 182367246208 1677 0.0041459 13101 756078250
13101111007 13101 879 2017 Santiago 450851.7 2017 13101 404495 182367246208 1859 0.0045959 13101 838133254
13101111008 13101 1090 2017 Santiago 450851.7 2017 13101 404495 182367246208 2552 0.0063091 13101 1150573462
13101111009 13101 1483 2017 Santiago 450851.7 2017 13101 404495 182367246208 3455 0.0085415 13101 1557692519
13101111010 13101 1253 2017 Santiago 450851.7 2017 13101 404495 182367246208 2560 0.0063289 13101 1154180275
13101111011 13101 698 2017 Santiago 450851.7 2017 13101 404495 182367246208 1550 0.0038319 13101 698820088
13101111012 13101 1976 2017 Santiago 450851.7 2017 13101 404495 182367246208 4104 0.0101460 13101 1850295253
13101111013 13101 1595 2017 Santiago 450851.7 2017 13101 404495 182367246208 3191 0.0078888 13101 1438667679
13101111014 13101 822 2017 Santiago 450851.7 2017 13101 404495 182367246208 1894 0.0046824 13101 853913063
13101111015 13101 1340 2017 Santiago 450851.7 2017 13101 404495 182367246208 2747 0.0067912 13101 1238489537
13101111016 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 2452 0.0060619 13101 1105488295
13101111017 13101 833 2017 Santiago 450851.7 2017 13101 404495 182367246208 1798 0.0044450 13101 810631302
13101111018 13101 1267 2017 Santiago 450851.7 2017 13101 404495 182367246208 2724 0.0067343 13101 1228119949
13101111019 13101 1214 2017 Santiago 450851.7 2017 13101 404495 182367246208 2430 0.0060075 13101 1095569558
13101121001 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2320 0.0057355 13101 1045975874
13101121002 13101 855 2017 Santiago 450851.7 2017 13101 404495 182367246208 1774 0.0043857 13101 799810862
13101121003 13101 940 2017 Santiago 450851.7 2017 13101 404495 182367246208 2011 0.0049716 13101 906662708
13101121004 13101 1984 2017 Santiago 450851.7 2017 13101 404495 182367246208 4425 0.0109396 13101 1995018639
13101121005 13101 818 2017 Santiago 450851.7 2017 13101 404495 182367246208 2095 0.0051793 13101 944534248
13101121006 13101 1415 2017 Santiago 450851.7 2017 13101 404495 182367246208 3272 0.0080891 13101 1475186664
13101121007 13101 1286 2017 Santiago 450851.7 2017 13101 404495 182367246208 3067 0.0075823 13101 1382762072
13101121008 13101 2163 2017 Santiago 450851.7 2017 13101 404495 182367246208 4682 0.0115749 13101 2110887518
13101121009 13101 2202 2017 Santiago 450851.7 2017 13101 404495 182367246208 4441 0.0109791 13101 2002232266
13101131001 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 1811 0.0044772 13101 816492374
13101131002 13101 897 2017 Santiago 450851.7 2017 13101 404495 182367246208 1759 0.0043486 13101 793048087
13101131003 13101 1873 2017 Santiago 450851.7 2017 13101 404495 182367246208 3953 0.0097727 13101 1782216651
13101131004 13101 1152 2017 Santiago 450851.7 2017 13101 404495 182367246208 2442 0.0060372 13101 1100979778
13101131005 13101 1434 2017 Santiago 450851.7 2017 13101 404495 182367246208 3683 0.0091052 13101 1660486700
13101131006 13101 1062 2017 Santiago 450851.7 2017 13101 404495 182367246208 2197 0.0054315 13101 990521119
13101131007 13101 1435 2017 Santiago 450851.7 2017 13101 404495 182367246208 2952 0.0072980 13101 1330914129
13101131008 13101 1433 2017 Santiago 450851.7 2017 13101 404495 182367246208 3025 0.0074785 13101 1363826301
13101131009 13101 1664 2017 Santiago 450851.7 2017 13101 404495 182367246208 3631 0.0089766 13101 1637042413
13101141001 13101 1444 2017 Santiago 450851.7 2017 13101 404495 182367246208 4373 0.0108110 13101 1971574352
13101141002 13101 1302 2017 Santiago 450851.7 2017 13101 404495 182367246208 3048 0.0075353 13101 1374195890
13101141003 13101 1851 2017 Santiago 450851.7 2017 13101 404495 182367246208 4067 0.0100545 13101 1833613741
13101151001 13101 1703 2017 Santiago 450851.7 2017 13101 404495 182367246208 4797 0.0118592 13101 2162735460
13101151002 13101 1572 2017 Santiago 450851.7 2017 13101 404495 182367246208 3915 0.0096787 13101 1765084288
13101151003 13101 1404 2017 Santiago 450851.7 2017 13101 404495 182367246208 3644 0.0090088 13101 1642903485
13101151004 13101 752 2017 Santiago 450851.7 2017 13101 404495 182367246208 2038 0.0050384 13101 918835703
13101161001 13101 1362 2017 Santiago 450851.7 2017 13101 404495 182367246208 2637 0.0065192 13101 1188895853
13101161002 13101 1909 2017 Santiago 450851.7 2017 13101 404495 182367246208 5341 0.0132041 13101 2407998769
13101161003 13101 2070 2017 Santiago 450851.7 2017 13101 404495 182367246208 5331 0.0131794 13101 2403490252
13101171001 13101 1637 2017 Santiago 450851.7 2017 13101 404495 182367246208 5638 0.0139384 13101 2541901715

7 Análisis de regresión

Aplicaremos un análisis de regresión donde:

\[ Y(dependiente) = ingreso \ expandido \ por \ zona \ (multi\_pob)\]

\[ X(independiente) = frecuencia \ de \ población \ que \ posee \ la \ variable \ Censal \ respecto \ a \ la \ zona \ (Freq.x) \]

7.1 Diagrama de dispersión loess

scatter.smooth(x=h_y_m_comuna_corr_01$Freq.x, y=h_y_m_comuna_corr_01$multi_pob, main="multi_pob ~ Freq.x",
     xlab = "Freq.x",
     ylab = "multi_pob",
           col = 2)

7.2 Outliers

Hemos demostrado en el punto 5.7.2 de aquí que la exclusión de ouliers no genera ninguna mejora en el modelo de regresión.

7.3 Modelo lineal

Aplicaremos un análisis de regresión lineal del ingreso expandido por zona sobre las frecuencias de respuestas zonales.

linearMod <- lm( multi_pob~(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = multi_pob ~ (Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -605272803 -122612905  -28340472  102322610 4159906322 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 97600533   14617726   6.677 3.19e-11 ***
## Freq.x       1138057      13462  84.540  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 240500000 on 1912 degrees of freedom
## Multiple R-squared:  0.7889, Adjusted R-squared:  0.7888 
## F-statistic:  7147 on 1 and 1912 DF,  p-value: < 2.2e-16

7.4 Gráfica de la recta de regresión lineal

ggplot(h_y_m_comuna_corr_01, aes(x = Freq.x , y = multi_pob)) + 
  geom_point() +
  stat_smooth(method = "lm", col = "red")

Si bien obtenemos nuestro modelo lineal da cuenta del 0.8214 de la variabilidad de los datos de respuesta en torno a su media, modelos alternativos pueden ofrecernos una explicación de la variable dependiente aún mayor.

8 Modelos alternativos

### 8.1 Modelo cuadrático

linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "cuadrático"
sintaxis <- "linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = '\'beta_0 + '\'beta_1  X^2  $$"
modelos1 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.2 Modelo cúbico
 
linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "cúbico"
sintaxis <- "linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = '\'beta_0 + '\'beta_1  X^3  $$"
modelos2 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.3 Modelo logarítmico
 
linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "logarítmico"
sintaxis <- "linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = '\'beta_0 + '\'beta_1 ln X  $$"
modelos3 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.5 Modelo con raíz cuadrada 
 
linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "raíz cuadrada"
sintaxis <- "linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = '\'beta_0 + '\'beta_1  '\'sqrt {X}  $$"
modelos5 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.6 Modelo raíz-raíz
 
linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "raíz-raíz"
sintaxis <- "linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = {'\'beta_0}^2 + 2  '\'beta_0  '\'beta_1 '\'sqrt{X}+  '\'beta_1^2 X  $$"
modelos6 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.7 Modelo log-raíz
 
linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "log-raíz"
sintaxis <- "linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = e^{'\'beta_0 + '\'beta_1 '\'sqrt{X}} $$"
modelos7 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.8 Modelo raíz-log
 
linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "raíz-log"
sintaxis <- "linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = {'\'beta_0}^2 + 2  '\'beta_0  '\'beta_1 '\'ln{X}+  '\'beta_1^2 ln^2X  $$"
modelos8 <- cbind(modelo,dato,sintaxis,latex)
 
### 8.9 Modelo log-log
 
linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
datos <- summary(linearMod)
dato <- datos$adj.r.squared
modelo <- "log-log"
sintaxis <- "linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)"
latex <- "$$ '\'hat Y = e^{'\'beta_0+'\'beta_1  ln{X}} $$"
modelos9 <- cbind(modelo,dato,sintaxis,latex)
 
modelos_bind <- rbind(modelos1,modelos2,modelos3,modelos5,modelos6,modelos7,modelos8,modelos9)
modelos_bind <- as.data.frame(modelos_bind)

modelos_bind <<- modelos_bind[order(modelos_bind$dato ),]
h_y_m_comuna_corr_01 <<- h_y_m_comuna_corr_01

kbl(modelos_bind) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
modelo dato sintaxis latex
3 logarítmico 0.56027220890145 linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 ln X \]
4 raíz cuadrada 0.757859247490565 linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 ''sqrt {X} \]
7 raíz-log 0.771044073366406 linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = {''beta_0}^2 + 2 ''beta_0 ''beta_1 ''ln{X}+ ''beta_1^2 ln^2X \]
1 cuadrático 0.788827421838497 linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 X^2 \]
2 cúbico 0.788827421838497 linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 X^3 \]
6 log-raíz 0.798495990815304 linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = e^{''beta_0 + ''beta_1 ''sqrt{X}} \]
5 raíz-raíz 0.866785828361538 linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = {''beta_0}^2 + 2 ''beta_0 ''beta_1 ''sqrt{X}+ ''beta_1^2 X \]
8 log-log 0.936959151185257 linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = e^{''beta_0+''beta_1 ln{X}} \] 
h_y_m_comuna_corr <- h_y_m_comuna_corr_01
metodo <- 8


switch (metodo,
        case = linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr)
)
summary(linearMod)
## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.1969 -0.1075 -0.0059  0.0968  3.2412 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 14.316470   0.038554   371.3   <2e-16 ***
## log(Freq.x)  0.957046   0.005676   168.6   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1972 on 1912 degrees of freedom
## Multiple R-squared:  0.937,  Adjusted R-squared:  0.937 
## F-statistic: 2.843e+04 on 1 and 1912 DF,  p-value: < 2.2e-16
aa <- linearMod$coefficients[1]
aa
## (Intercept) 
##    14.31647
bb <- linearMod$coefficients[2]
bb
## log(Freq.x) 
##   0.9570461

9 Modelo log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.937).

9.1 Diagrama de dispersión sobre log-log

Desplegamos una curva suavizada por loess en el diagrama de dispersión.

scatter.smooth(x=log(h_y_m_comuna_corr$Freq.x), y=log(h_y_m_comuna_corr$multi_pob), lpars = list(col = "red", lwd = 2, lty = 1), main="multi_pob ~ Freq.x")

9.2 Modelo log-log

Observemos nuevamente el resultado sobre log-log.

linearMod <- lm(log( multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr)
summary(linearMod) 
## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.1969 -0.1075 -0.0059  0.0968  3.2412 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 14.316470   0.038554   371.3   <2e-16 ***
## log(Freq.x)  0.957046   0.005676   168.6   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1972 on 1912 degrees of freedom
## Multiple R-squared:  0.937,  Adjusted R-squared:  0.937 
## F-statistic: 2.843e+04 on 1 and 1912 DF,  p-value: < 2.2e-16
ggplot(h_y_m_comuna_corr, aes(x = log(Freq.x) , y = log(multi_pob))) + geom_point() + stat_smooth(method = "lm", col = "red")

9.3 Análisis de residuos

par(mfrow = c (2,2))
plot(linearMod)

9.4 Ecuación del modelo


\[ \hat Y = e^{14.31647 +0.9570461 \cdot ln{X}} \]


10 Aplicación la regresión a los valores de la variable a nivel de zona

Esta nueva variable se llamará: est_ing

h_y_m_comuna_corr$est_ing <- exp(aa+bb * log(h_y_m_comuna_corr$Freq.x))

r3_100 <- h_y_m_comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona código.x Freq.x anio comuna.x promedio_i año comuna.y personas Ingresos_expandidos Freq.y p_poblacional código.y multi_pob est_ing
13101011001 13101 1133 2017 Santiago 450851.7 2017 13101 404495 182367246208 2174 0.0053746 13101 980151530 1382301237
13101011002 13101 1226 2017 Santiago 450851.7 2017 13101 404495 182367246208 2282 0.0056416 13101 1028843511 1490704736
13101011003 13101 1079 2017 Santiago 450851.7 2017 13101 404495 182367246208 2209 0.0054611 13101 995931339 1319183524
13101011004 13101 892 2017 Santiago 450851.7 2017 13101 404495 182367246208 1821 0.0045019 13101 821000891 1099509672
13101011005 13101 970 2017 Santiago 450851.7 2017 13101 404495 182367246208 1741 0.0043041 13101 784932757 1191357533
13101021001 13101 1414 2017 Santiago 450851.7 2017 13101 404495 182367246208 3448 0.0085242 13101 1554536558 1708791953
13101021002 13101 1347 2017 Santiago 450851.7 2017 13101 404495 182367246208 2856 0.0070607 13101 1287632369 1631221449
13101021003 13101 1318 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101 1247957422 1597595198
13101021004 13101 1383 2017 Santiago 450851.7 2017 13101 404495 182367246208 3279 0.0081064 13101 1478342626 1672921213
13101021005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 2258 0.0055823 13101 1018023071 1180776391
13101021006 13101 1161 2017 Santiago 450851.7 2017 13101 404495 182367246208 2478 0.0061262 13101 1117210438 1414977701
13101021007 13101 1041 2017 Santiago 450851.7 2017 13101 404495 182367246208 2326 0.0057504 13101 1048680984 1274686326
13101021008 13101 750 2017 Santiago 450851.7 2017 13101 404495 182367246208 1541 0.0038097 13101 694762423 931386736
13101031001 13101 1075 2017 Santiago 450851.7 2017 13101 404495 182367246208 2313 0.0057182 13101 1042819912 1314502820
13101031002 13101 2508 2017 Santiago 450851.7 2017 13101 404495 182367246208 5950 0.0147097 13101 2682567436 2957174946
13101031003 13101 2225 2017 Santiago 450851.7 2017 13101 404495 182367246208 4955 0.0122498 13101 2233970024 2637017423
13101031004 13101 1868 2017 Santiago 450851.7 2017 13101 404495 182367246208 3903 0.0096491 13101 1759674068 2230603309
13101031005 13101 821 2017 Santiago 450851.7 2017 13101 404495 182367246208 1791 0.0044277 13101 807475341 1015604533
13101031006 13101 783 2017 Santiago 450851.7 2017 13101 404495 182367246208 1697 0.0041954 13101 765095284 970570948
13101031007 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 2973 0.0073499 13101 1340382015 1605714763
13101041001 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 2790 0.0068975 13101 1257876159 1355433931
13101041002 13101 1036 2017 Santiago 450851.7 2017 13101 404495 182367246208 2668 0.0065959 13101 1202872255 1268826289
13101041003 13101 1140 2017 Santiago 450851.7 2017 13101 404495 182367246208 2729 0.0067467 13101 1230374207 1390473572
13101041004 13101 1137 2017 Santiago 450851.7 2017 13101 404495 182367246208 2828 0.0069914 13101 1275008522 1386971408
13101041005 13101 1172 2017 Santiago 450851.7 2017 13101 404495 182367246208 2550 0.0063042 13101 1149671758 1427805578
13101051001 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 3135 0.0077504 13101 1413419985 1442959135
13101051002 13101 1432 2017 Santiago 450851.7 2017 13101 404495 182367246208 4424 0.0109371 13101 1994567788 1729604580
13101051003 13101 658 2017 Santiago 450851.7 2017 13101 404495 182367246208 2355 0.0058221 13101 1061755683 821742940
13101061001 13101 1504 2017 Santiago 450851.7 2017 13101 404495 182367246208 3968 0.0098098 13101 1788979426 1812744178
13101061002 13101 1495 2017 Santiago 450851.7 2017 13101 404495 182367246208 4747 0.0117356 13101 2140192877 1802361248
13101061003 13101 850 2017 Santiago 450851.7 2017 13101 404495 182367246208 2864 0.0070804 13101 1291239183 1049911845
13101071001 13101 1583 2017 Santiago 450851.7 2017 13101 404495 182367246208 5009 0.0123833 13101 2258316014 1903770529
13101071002 13101 1043 2017 Santiago 450851.7 2017 13101 404495 182367246208 3511 0.0086800 13101 1582940213 1277030001
13101071003 13101 1208 2017 Santiago 450851.7 2017 13101 404495 182367246208 3368 0.0083264 13101 1518468424 1469751836
13101081001 13101 1240 2017 Santiago 450851.7 2017 13101 404495 182367246208 3716 0.0091868 13101 1675364805 1506992292
13101081002 13101 1700 2017 Santiago 450851.7 2017 13101 404495 182367246208 5244 0.0129643 13101 2364266157 2038226333
13101081003 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 3326 0.0082226 13101 1499532654 1355433931
13101081004 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2794 0.0069074 13101 1259679566 1117198633
13101091001 13101 1048 2017 Santiago 450851.7 2017 13101 404495 182367246208 3393 0.0083882 13101 1529739716 1282888347
13101091002 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 3321 0.0082102 13101 1497278396 1605714763
13101091003 13101 1251 2017 Santiago 450851.7 2017 13101 404495 182367246208 3210 0.0079358 13101 1447233860 1519784113
13101091004 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 2956 0.0073079 13101 1332717536 1161954933
13101101001 13101 1071 2017 Santiago 450851.7 2017 13101 404495 182367246208 2491 0.0061583 13101 1123071510 1309821367
13101101002 13101 843 2017 Santiago 450851.7 2017 13101 404495 182367246208 1820 0.0044994 13101 820550039 1041635439
13101101003 13101 1374 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101 1247957422 1662500691
13101101004 13101 1244 2017 Santiago 450851.7 2017 13101 404495 182367246208 2423 0.0059902 13101 1092413596 1511644425
13101101005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 1805 0.0044624 13101 813787264 1180776391
13101101006 13101 652 2017 Santiago 450851.7 2017 13101 404495 182367246208 1296 0.0032040 13101 584303764 814570293
13101101007 13101 1473 2017 Santiago 450851.7 2017 13101 404495 182367246208 2965 0.0073301 13101 1336775201 1776969411
13101101008 13101 796 2017 Santiago 450851.7 2017 13101 404495 182367246208 1624 0.0040149 13101 732183112 985987516
13101101009 13101 721 2017 Santiago 450851.7 2017 13101 404495 182367246208 1345 0.0033251 13101 606395496 896891027
13101101010 13101 1371 2017 Santiago 450851.7 2017 13101 404495 182367246208 2930 0.0072436 13101 1320995393 1659026533
13101111001 13101 953 2017 Santiago 450851.7 2017 13101 404495 182367246208 2555 0.0063165 13101 1151926017 1171367358
13101111002 13101 1272 2017 Santiago 450851.7 2017 13101 404495 182367246208 2594 0.0064129 13101 1169509232 1544191486
13101111003 13101 1132 2017 Santiago 450851.7 2017 13101 404495 182367246208 2269 0.0056095 13101 1022982439 1381133584
13101111004 13101 932 2017 Santiago 450851.7 2017 13101 404495 182367246208 1996 0.0049345 13101 899899933 1146652426
13101111005 13101 985 2017 Santiago 450851.7 2017 13101 404495 182367246208 1960 0.0048455 13101 883669273 1208983420
13101111006 13101 799 2017 Santiago 450851.7 2017 13101 404495 182367246208 1677 0.0041459 13101 756078250 989543644
13101111007 13101 879 2017 Santiago 450851.7 2017 13101 404495 182367246208 1859 0.0045959 13101 838133254 1084168908
13101111008 13101 1090 2017 Santiago 450851.7 2017 13101 404495 182367246208 2552 0.0063091 13101 1150573462 1332051627
13101111009 13101 1483 2017 Santiago 450851.7 2017 13101 404495 182367246208 3455 0.0085415 13101 1557692519 1788513160
13101111010 13101 1253 2017 Santiago 450851.7 2017 13101 404495 182367246208 2560 0.0063289 13101 1154180275 1522109379
13101111011 13101 698 2017 Santiago 450851.7 2017 13101 404495 182367246208 1550 0.0038319 13101 698820088 869490060
13101111012 13101 1976 2017 Santiago 450851.7 2017 13101 404495 182367246208 4104 0.0101460 13101 1850295253 2353877741
13101111013 13101 1595 2017 Santiago 450851.7 2017 13101 404495 182367246208 3191 0.0078888 13101 1438667679 1917580006
13101111014 13101 822 2017 Santiago 450851.7 2017 13101 404495 182367246208 1894 0.0046824 13101 853913063 1016788400
13101111015 13101 1340 2017 Santiago 450851.7 2017 13101 404495 182367246208 2747 0.0067912 13101 1238489537 1623107640
13101111016 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 2452 0.0060619 13101 1105488295 1442959135
13101111017 13101 833 2017 Santiago 450851.7 2017 13101 404495 182367246208 1798 0.0044450 13101 810631302 1029806872
13101111018 13101 1267 2017 Santiago 450851.7 2017 13101 404495 182367246208 2724 0.0067343 13101 1228119949 1538381787
13101111019 13101 1214 2017 Santiago 450851.7 2017 13101 404495 182367246208 2430 0.0060075 13101 1095569558 1476737616
13101121001 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2320 0.0057355 13101 1045975874 1117198633
13101121002 13101 855 2017 Santiago 450851.7 2017 13101 404495 182367246208 1774 0.0043857 13101 799810862 1055821771
13101121003 13101 940 2017 Santiago 450851.7 2017 13101 404495 182367246208 2011 0.0049716 13101 906662708 1156070430
13101121004 13101 1984 2017 Santiago 450851.7 2017 13101 404495 182367246208 4425 0.0109396 13101 1995018639 2362997473
13101121005 13101 818 2017 Santiago 450851.7 2017 13101 404495 182367246208 2095 0.0051793 13101 944534248 1012052559
13101121006 13101 1415 2017 Santiago 450851.7 2017 13101 404495 182367246208 3272 0.0080891 13101 1475186664 1709948507
13101121007 13101 1286 2017 Santiago 450851.7 2017 13101 404495 182367246208 3067 0.0075823 13101 1382762072 1560453437
13101121008 13101 2163 2017 Santiago 450851.7 2017 13101 404495 182367246208 4682 0.0115749 13101 2110887518 2566650283
13101121009 13101 2202 2017 Santiago 450851.7 2017 13101 404495 182367246208 4441 0.0109791 13101 2002232266 2610923437
13101131001 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 1811 0.0044772 13101 816492374 1161954933
13101131002 13101 897 2017 Santiago 450851.7 2017 13101 404495 182367246208 1759 0.0043486 13101 793048087 1105407402
13101131003 13101 1873 2017 Santiago 450851.7 2017 13101 404495 182367246208 3953 0.0097727 13101 1782216651 2236317088
13101131004 13101 1152 2017 Santiago 450851.7 2017 13101 404495 182367246208 2442 0.0060372 13101 1100979778 1404478283
13101131005 13101 1434 2017 Santiago 450851.7 2017 13101 404495 182367246208 3683 0.0091052 13101 1660486700 1731916398
13101131006 13101 1062 2017 Santiago 450851.7 2017 13101 404495 182367246208 2197 0.0054315 13101 990521119 1299285348
13101131007 13101 1435 2017 Santiago 450851.7 2017 13101 404495 182367246208 2952 0.0072980 13101 1330914129 1733072255
13101131008 13101 1433 2017 Santiago 450851.7 2017 13101 404495 182367246208 3025 0.0074785 13101 1363826301 1730760506
13101131009 13101 1664 2017 Santiago 450851.7 2017 13101 404495 182367246208 3631 0.0089766 13101 1637042413 1996898963
13101141001 13101 1444 2017 Santiago 450851.7 2017 13101 404495 182367246208 4373 0.0108110 13101 1971574352 1743473414
13101141002 13101 1302 2017 Santiago 450851.7 2017 13101 404495 182367246208 3048 0.0075353 13101 1374195890 1579029219
13101141003 13101 1851 2017 Santiago 450851.7 2017 13101 404495 182367246208 4067 0.0100545 13101 1833613741 2211171539
13101151001 13101 1703 2017 Santiago 450851.7 2017 13101 404495 182367246208 4797 0.0118592 13101 2162735460 2041668573
13101151002 13101 1572 2017 Santiago 450851.7 2017 13101 404495 182367246208 3915 0.0096787 13101 1765084288 1891107891
13101151003 13101 1404 2017 Santiago 450851.7 2017 13101 404495 182367246208 3644 0.0090088 13101 1642903485 1697224473
13101151004 13101 752 2017 Santiago 450851.7 2017 13101 404495 182367246208 2038 0.0050384 13101 918835703 933763613
13101161001 13101 1362 2017 Santiago 450851.7 2017 13101 404495 182367246208 2637 0.0065192 13101 1188895853 1648602096
13101161002 13101 1909 2017 Santiago 450851.7 2017 13101 404495 182367246208 5341 0.0132041 13101 2407998769 2277437061
13101161003 13101 2070 2017 Santiago 450851.7 2017 13101 404495 182367246208 5331 0.0131794 13101 2403490252 2460936177
13101171001 13101 1637 2017 Santiago 450851.7 2017 13101 404495 182367246208 5638 0.0139384 13101 2541901715 1965878265


11 División del valor estimado entre la población total de la zona para obtener el ingreso medio por zona


\[ Ingreso \_ Medio\_zona = est\_ing / (personas * p\_poblacional) \]


h_y_m_comuna_corr$ing_medio_zona <- h_y_m_comuna_corr$est_ing  /( h_y_m_comuna_corr$personas  * h_y_m_comuna_corr$p_poblacional)

r3_100 <- h_y_m_comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")
zona código.x Freq.x anio comuna.x promedio_i año comuna.y personas Ingresos_expandidos Freq.y p_poblacional código.y multi_pob est_ing ing_medio_zona
13101011001 13101 1133 2017 Santiago 450851.7 2017 13101 404495 182367246208 2174 0.0053746 13101 980151530 1382301237 635833.1
13101011002 13101 1226 2017 Santiago 450851.7 2017 13101 404495 182367246208 2282 0.0056416 13101 1028843511 1490704736 653244.8
13101011003 13101 1079 2017 Santiago 450851.7 2017 13101 404495 182367246208 2209 0.0054611 13101 995931339 1319183524 597185.8
13101011004 13101 892 2017 Santiago 450851.7 2017 13101 404495 182367246208 1821 0.0045019 13101 821000891 1099509672 603794.4
13101011005 13101 970 2017 Santiago 450851.7 2017 13101 404495 182367246208 1741 0.0043041 13101 784932757 1191357533 684295.0
13101021001 13101 1414 2017 Santiago 450851.7 2017 13101 404495 182367246208 3448 0.0085242 13101 1554536558 1708791953 495589.3
13101021002 13101 1347 2017 Santiago 450851.7 2017 13101 404495 182367246208 2856 0.0070607 13101 1287632369 1631221449 571156.0
13101021003 13101 1318 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101 1247957422 1597595198 577165.9
13101021004 13101 1383 2017 Santiago 450851.7 2017 13101 404495 182367246208 3279 0.0081064 13101 1478342626 1672921213 510192.5
13101021005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 2258 0.0055823 13101 1018023071 1180776391 522930.2
13101021006 13101 1161 2017 Santiago 450851.7 2017 13101 404495 182367246208 2478 0.0061262 13101 1117210438 1414977701 571016.0
13101021007 13101 1041 2017 Santiago 450851.7 2017 13101 404495 182367246208 2326 0.0057504 13101 1048680984 1274686326 548016.5
13101021008 13101 750 2017 Santiago 450851.7 2017 13101 404495 182367246208 1541 0.0038097 13101 694762423 931386736 604404.1
13101031001 13101 1075 2017 Santiago 450851.7 2017 13101 404495 182367246208 2313 0.0057182 13101 1042819912 1314502820 568310.8
13101031002 13101 2508 2017 Santiago 450851.7 2017 13101 404495 182367246208 5950 0.0147097 13101 2682567436 2957174946 497004.2
13101031003 13101 2225 2017 Santiago 450851.7 2017 13101 404495 182367246208 4955 0.0122498 13101 2233970024 2637017423 532193.2
13101031004 13101 1868 2017 Santiago 450851.7 2017 13101 404495 182367246208 3903 0.0096491 13101 1759674068 2230603309 571509.9
13101031005 13101 821 2017 Santiago 450851.7 2017 13101 404495 182367246208 1791 0.0044277 13101 807475341 1015604533 567060.0
13101031006 13101 783 2017 Santiago 450851.7 2017 13101 404495 182367246208 1697 0.0041954 13101 765095284 970570948 571933.4
13101031007 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 2973 0.0073499 13101 1340382015 1605714763 540099.1
13101041001 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 2790 0.0068975 13101 1257876159 1355433931 485818.6
13101041002 13101 1036 2017 Santiago 450851.7 2017 13101 404495 182367246208 2668 0.0065959 13101 1202872255 1268826289 475572.1
13101041003 13101 1140 2017 Santiago 450851.7 2017 13101 404495 182367246208 2729 0.0067467 13101 1230374207 1390473572 509517.6
13101041004 13101 1137 2017 Santiago 450851.7 2017 13101 404495 182367246208 2828 0.0069914 13101 1275008522 1386971408 490442.5
13101041005 13101 1172 2017 Santiago 450851.7 2017 13101 404495 182367246208 2550 0.0063042 13101 1149671758 1427805578 559923.8
13101051001 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 3135 0.0077504 13101 1413419985 1442959135 460274.0
13101051002 13101 1432 2017 Santiago 450851.7 2017 13101 404495 182367246208 4424 0.0109371 13101 1994567788 1729604580 390959.4
13101051003 13101 658 2017 Santiago 450851.7 2017 13101 404495 182367246208 2355 0.0058221 13101 1061755683 821742940 348935.4
13101061001 13101 1504 2017 Santiago 450851.7 2017 13101 404495 182367246208 3968 0.0098098 13101 1788979426 1812744178 456840.8
13101061002 13101 1495 2017 Santiago 450851.7 2017 13101 404495 182367246208 4747 0.0117356 13101 2140192877 1802361248 379684.3
13101061003 13101 850 2017 Santiago 450851.7 2017 13101 404495 182367246208 2864 0.0070804 13101 1291239183 1049911845 366589.3
13101071001 13101 1583 2017 Santiago 450851.7 2017 13101 404495 182367246208 5009 0.0123833 13101 2258316014 1903770529 380070.0
13101071002 13101 1043 2017 Santiago 450851.7 2017 13101 404495 182367246208 3511 0.0086800 13101 1582940213 1277030001 363722.6
13101071003 13101 1208 2017 Santiago 450851.7 2017 13101 404495 182367246208 3368 0.0083264 13101 1518468424 1469751836 436387.1
13101081001 13101 1240 2017 Santiago 450851.7 2017 13101 404495 182367246208 3716 0.0091868 13101 1675364805 1506992292 405541.5
13101081002 13101 1700 2017 Santiago 450851.7 2017 13101 404495 182367246208 5244 0.0129643 13101 2364266157 2038226333 388677.8
13101081003 13101 1110 2017 Santiago 450851.7 2017 13101 404495 182367246208 3326 0.0082226 13101 1499532654 1355433931 407526.7
13101081004 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2794 0.0069074 13101 1259679566 1117198633 399856.3
13101091001 13101 1048 2017 Santiago 450851.7 2017 13101 404495 182367246208 3393 0.0083882 13101 1529739716 1282888347 378098.5
13101091002 13101 1325 2017 Santiago 450851.7 2017 13101 404495 182367246208 3321 0.0082102 13101 1497278396 1605714763 483503.4
13101091003 13101 1251 2017 Santiago 450851.7 2017 13101 404495 182367246208 3210 0.0079358 13101 1447233860 1519784113 473453.0
13101091004 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 2956 0.0073079 13101 1332717536 1161954933 393083.5
13101101001 13101 1071 2017 Santiago 450851.7 2017 13101 404495 182367246208 2491 0.0061583 13101 1123071510 1309821367 525821.5
13101101002 13101 843 2017 Santiago 450851.7 2017 13101 404495 182367246208 1820 0.0044994 13101 820550039 1041635439 572327.2
13101101003 13101 1374 2017 Santiago 450851.7 2017 13101 404495 182367246208 2768 0.0068431 13101 1247957422 1662500691 600614.4
13101101004 13101 1244 2017 Santiago 450851.7 2017 13101 404495 182367246208 2423 0.0059902 13101 1092413596 1511644425 623873.1
13101101005 13101 961 2017 Santiago 450851.7 2017 13101 404495 182367246208 1805 0.0044624 13101 813787264 1180776391 654169.7
13101101006 13101 652 2017 Santiago 450851.7 2017 13101 404495 182367246208 1296 0.0032040 13101 584303764 814570293 628526.5
13101101007 13101 1473 2017 Santiago 450851.7 2017 13101 404495 182367246208 2965 0.0073301 13101 1336775201 1776969411 599315.1
13101101008 13101 796 2017 Santiago 450851.7 2017 13101 404495 182367246208 1624 0.0040149 13101 732183112 985987516 607135.2
13101101009 13101 721 2017 Santiago 450851.7 2017 13101 404495 182367246208 1345 0.0033251 13101 606395496 896891027 666833.5
13101101010 13101 1371 2017 Santiago 450851.7 2017 13101 404495 182367246208 2930 0.0072436 13101 1320995393 1659026533 566220.7
13101111001 13101 953 2017 Santiago 450851.7 2017 13101 404495 182367246208 2555 0.0063165 13101 1151926017 1171367358 458460.8
13101111002 13101 1272 2017 Santiago 450851.7 2017 13101 404495 182367246208 2594 0.0064129 13101 1169509232 1544191486 595293.6
13101111003 13101 1132 2017 Santiago 450851.7 2017 13101 404495 182367246208 2269 0.0056095 13101 1022982439 1381133584 608697.0
13101111004 13101 932 2017 Santiago 450851.7 2017 13101 404495 182367246208 1996 0.0049345 13101 899899933 1146652426 574475.2
13101111005 13101 985 2017 Santiago 450851.7 2017 13101 404495 182367246208 1960 0.0048455 13101 883669273 1208983420 616828.3
13101111006 13101 799 2017 Santiago 450851.7 2017 13101 404495 182367246208 1677 0.0041459 13101 756078250 989543644 590067.8
13101111007 13101 879 2017 Santiago 450851.7 2017 13101 404495 182367246208 1859 0.0045959 13101 838133254 1084168908 583200.1
13101111008 13101 1090 2017 Santiago 450851.7 2017 13101 404495 182367246208 2552 0.0063091 13101 1150573462 1332051627 521963.8
13101111009 13101 1483 2017 Santiago 450851.7 2017 13101 404495 182367246208 3455 0.0085415 13101 1557692519 1788513160 517659.4
13101111010 13101 1253 2017 Santiago 450851.7 2017 13101 404495 182367246208 2560 0.0063289 13101 1154180275 1522109379 594574.0
13101111011 13101 698 2017 Santiago 450851.7 2017 13101 404495 182367246208 1550 0.0038319 13101 698820088 869490060 560961.3
13101111012 13101 1976 2017 Santiago 450851.7 2017 13101 404495 182367246208 4104 0.0101460 13101 1850295253 2353877741 573557.0
13101111013 13101 1595 2017 Santiago 450851.7 2017 13101 404495 182367246208 3191 0.0078888 13101 1438667679 1917580006 600933.9
13101111014 13101 822 2017 Santiago 450851.7 2017 13101 404495 182367246208 1894 0.0046824 13101 853913063 1016788400 536847.1
13101111015 13101 1340 2017 Santiago 450851.7 2017 13101 404495 182367246208 2747 0.0067912 13101 1238489537 1623107640 590865.5
13101111016 13101 1185 2017 Santiago 450851.7 2017 13101 404495 182367246208 2452 0.0060619 13101 1105488295 1442959135 588482.5
13101111017 13101 833 2017 Santiago 450851.7 2017 13101 404495 182367246208 1798 0.0044450 13101 810631302 1029806872 572751.3
13101111018 13101 1267 2017 Santiago 450851.7 2017 13101 404495 182367246208 2724 0.0067343 13101 1228119949 1538381787 564751.0
13101111019 13101 1214 2017 Santiago 450851.7 2017 13101 404495 182367246208 2430 0.0060075 13101 1095569558 1476737616 607711.0
13101121001 13101 907 2017 Santiago 450851.7 2017 13101 404495 182367246208 2320 0.0057355 13101 1045975874 1117198633 481551.1
13101121002 13101 855 2017 Santiago 450851.7 2017 13101 404495 182367246208 1774 0.0043857 13101 799810862 1055821771 595164.5
13101121003 13101 940 2017 Santiago 450851.7 2017 13101 404495 182367246208 2011 0.0049716 13101 906662708 1156070430 574873.4
13101121004 13101 1984 2017 Santiago 450851.7 2017 13101 404495 182367246208 4425 0.0109396 13101 1995018639 2362997473 534010.7
13101121005 13101 818 2017 Santiago 450851.7 2017 13101 404495 182367246208 2095 0.0051793 13101 944534248 1012052559 483080.0
13101121006 13101 1415 2017 Santiago 450851.7 2017 13101 404495 182367246208 3272 0.0080891 13101 1475186664 1709948507 522600.4
13101121007 13101 1286 2017 Santiago 450851.7 2017 13101 404495 182367246208 3067 0.0075823 13101 1382762072 1560453437 508788.2
13101121008 13101 2163 2017 Santiago 450851.7 2017 13101 404495 182367246208 4682 0.0115749 13101 2110887518 2566650283 548195.3
13101121009 13101 2202 2017 Santiago 450851.7 2017 13101 404495 182367246208 4441 0.0109791 13101 2002232266 2610923437 587913.4
13101131001 13101 945 2017 Santiago 450851.7 2017 13101 404495 182367246208 1811 0.0044772 13101 816492374 1161954933 641609.6
13101131002 13101 897 2017 Santiago 450851.7 2017 13101 404495 182367246208 1759 0.0043486 13101 793048087 1105407402 628429.4
13101131003 13101 1873 2017 Santiago 450851.7 2017 13101 404495 182367246208 3953 0.0097727 13101 1782216651 2236317088 565726.6
13101131004 13101 1152 2017 Santiago 450851.7 2017 13101 404495 182367246208 2442 0.0060372 13101 1100979778 1404478283 575134.4
13101131005 13101 1434 2017 Santiago 450851.7 2017 13101 404495 182367246208 3683 0.0091052 13101 1660486700 1731916398 470246.1
13101131006 13101 1062 2017 Santiago 450851.7 2017 13101 404495 182367246208 2197 0.0054315 13101 990521119 1299285348 591390.7
13101131007 13101 1435 2017 Santiago 450851.7 2017 13101 404495 182367246208 2952 0.0072980 13101 1330914129 1733072255 587084.1
13101131008 13101 1433 2017 Santiago 450851.7 2017 13101 404495 182367246208 3025 0.0074785 13101 1363826301 1730760506 572152.2
13101131009 13101 1664 2017 Santiago 450851.7 2017 13101 404495 182367246208 3631 0.0089766 13101 1637042413 1996898963 549958.4
13101141001 13101 1444 2017 Santiago 450851.7 2017 13101 404495 182367246208 4373 0.0108110 13101 1971574352 1743473414 398690.5
13101141002 13101 1302 2017 Santiago 450851.7 2017 13101 404495 182367246208 3048 0.0075353 13101 1374195890 1579029219 518054.2
13101141003 13101 1851 2017 Santiago 450851.7 2017 13101 404495 182367246208 4067 0.0100545 13101 1833613741 2211171539 543686.1
13101151001 13101 1703 2017 Santiago 450851.7 2017 13101 404495 182367246208 4797 0.0118592 13101 2162735460 2041668573 425613.6
13101151002 13101 1572 2017 Santiago 450851.7 2017 13101 404495 182367246208 3915 0.0096787 13101 1765084288 1891107891 483041.6
13101151003 13101 1404 2017 Santiago 450851.7 2017 13101 404495 182367246208 3644 0.0090088 13101 1642903485 1697224473 465758.6
13101151004 13101 752 2017 Santiago 450851.7 2017 13101 404495 182367246208 2038 0.0050384 13101 918835703 933763613 458176.5
13101161001 13101 1362 2017 Santiago 450851.7 2017 13101 404495 182367246208 2637 0.0065192 13101 1188895853 1648602096 625180.9
13101161002 13101 1909 2017 Santiago 450851.7 2017 13101 404495 182367246208 5341 0.0132041 13101 2407998769 2277437061 426406.5
13101161003 13101 2070 2017 Santiago 450851.7 2017 13101 404495 182367246208 5331 0.0131794 13101 2403490252 2460936177 461627.5
13101171001 13101 1637 2017 Santiago 450851.7 2017 13101 404495 182367246208 5638 0.0139384 13101 2541901715 1965878265 348683.6


Guardamos:

saveRDS(h_y_m_comuna_corr, "P03C/region_13_P03C_u.rds")