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$REGION == 10) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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
1 10101011001 1 10101 181 2017
2 10101011002 1 10101 964 2017
3 10101021001 1 10101 1249 2017
4 10101021002 1 10101 328 2017
5 10101021003 1 10101 699 2017
6 10101021004 1 10101 1043 2017
7 10101021005 1 10101 773 2017
8 10101031001 1 10101 1468 2017
9 10101031002 1 10101 1424 2017
10 10101031003 1 10101 1163 2017
11 10101031004 1 10101 836 2017
12 10101031005 1 10101 1701 2017
13 10101031006 1 10101 704 2017
14 10101031007 1 10101 652 2017
15 10101031008 1 10101 1013 2017
16 10101031009 1 10101 1347 2017
17 10101031010 1 10101 910 2017
18 10101031011 1 10101 666 2017
19 10101031012 1 10101 499 2017
20 10101031013 1 10101 1055 2017
21 10101031014 1 10101 645 2017
22 10101031015 1 10101 541 2017
23 10101031016 1 10101 773 2017
24 10101031017 1 10101 821 2017
25 10101041001 1 10101 1331 2017
26 10101041002 1 10101 644 2017
27 10101041003 1 10101 1650 2017
28 10101051001 1 10101 825 2017
29 10101051002 1 10101 579 2017
30 10101051003 1 10101 888 2017
31 10101051004 1 10101 1372 2017
32 10101061001 1 10101 2344 2017
33 10101061002 1 10101 928 2017
34 10101061003 1 10101 1153 2017
35 10101061004 1 10101 987 2017
36 10101061005 1 10101 746 2017
37 10101061006 1 10101 1398 2017
38 10101061007 1 10101 242 2017
39 10101061008 1 10101 627 2017
40 10101061009 1 10101 46 2017
41 10101061010 1 10101 483 2017
42 10101071001 1 10101 547 2017
43 10101071002 1 10101 1125 2017
44 10101071003 1 10101 1131 2017
45 10101071004 1 10101 847 2017
46 10101071005 1 10101 789 2017
47 10101071006 1 10101 963 2017
48 10101071007 1 10101 611 2017
49 10101071008 1 10101 1179 2017
50 10101071009 1 10101 866 2017
51 10101071010 1 10101 862 2017
52 10101071011 1 10101 742 2017
53 10101071012 1 10101 753 2017
54 10101071013 1 10101 26 2017
55 10101071014 1 10101 235 2017
56 10101131001 1 10101 204 2017
57 10101151001 1 10101 1170 2017
58 10101151002 1 10101 1499 2017
59 10101151003 1 10101 146 2017
60 10101151004 1 10101 118 2017
61 10101151005 1 10101 128 2017
62 10101161001 1 10101 190 2017
63 10101161002 1 10101 1550 2017
64 10101161003 1 10101 611 2017
65 10101161004 1 10101 366 2017
66 10101161005 1 10101 52 2017
67 10101161006 1 10101 134 2017
68 10101171001 1 10101 550 2017
69 10101171002 1 10101 814 2017
70 10101171003 1 10101 863 2017
71 10101171004 1 10101 1489 2017
72 10101171005 1 10101 1130 2017
73 10101171006 1 10101 1028 2017
74 10101181001 1 10101 978 2017
75 10101181002 1 10101 765 2017
76 10101181003 1 10101 425 2017
77 10101181004 1 10101 452 2017
78 10101991999 1 10101 107 2017
311 10102051001 1 10102 938 2017
312 10102051002 1 10102 1185 2017
313 10102141001 1 10102 972 2017
314 10102141002 1 10102 1641 2017
315 10102991999 1 10102 20 2017
548 10104011001 1 10104 853 2017
549 10104011002 1 10104 1280 2017
550 10104991999 1 10104 3 2017
783 10105011001 1 10105 1055 2017
784 10105011002 1 10105 951 2017
785 10105011003 1 10105 1023 2017
786 10105011004 1 10105 810 2017
787 10105991999 1 10105 33 2017
1020 10106011001 1 10106 1519 2017
1021 10106011002 1 10106 878 2017
1022 10106991999 1 10106 64 2017
1255 10107011001 1 10107 977 2017
1256 10107011002 1 10107 306 2017
1257 10107011003 1 10107 877 2017
1258 10107021001 1 10107 642 2017
1259 10107021002 1 10107 926 2017
1260 10107991999 1 10107 47 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
1 10101011001 181 2017 10101
2 10101011002 964 2017 10101
3 10101021001 1249 2017 10101
4 10101021002 328 2017 10101
5 10101021003 699 2017 10101
6 10101021004 1043 2017 10101
7 10101021005 773 2017 10101
8 10101031001 1468 2017 10101
9 10101031002 1424 2017 10101
10 10101031003 1163 2017 10101
11 10101031004 836 2017 10101
12 10101031005 1701 2017 10101
13 10101031006 704 2017 10101
14 10101031007 652 2017 10101
15 10101031008 1013 2017 10101
16 10101031009 1347 2017 10101
17 10101031010 910 2017 10101
18 10101031011 666 2017 10101
19 10101031012 499 2017 10101
20 10101031013 1055 2017 10101
21 10101031014 645 2017 10101
22 10101031015 541 2017 10101
23 10101031016 773 2017 10101
24 10101031017 821 2017 10101
25 10101041001 1331 2017 10101
26 10101041002 644 2017 10101
27 10101041003 1650 2017 10101
28 10101051001 825 2017 10101
29 10101051002 579 2017 10101
30 10101051003 888 2017 10101
31 10101051004 1372 2017 10101
32 10101061001 2344 2017 10101
33 10101061002 928 2017 10101
34 10101061003 1153 2017 10101
35 10101061004 987 2017 10101
36 10101061005 746 2017 10101
37 10101061006 1398 2017 10101
38 10101061007 242 2017 10101
39 10101061008 627 2017 10101
40 10101061009 46 2017 10101
41 10101061010 483 2017 10101
42 10101071001 547 2017 10101
43 10101071002 1125 2017 10101
44 10101071003 1131 2017 10101
45 10101071004 847 2017 10101
46 10101071005 789 2017 10101
47 10101071006 963 2017 10101
48 10101071007 611 2017 10101
49 10101071008 1179 2017 10101
50 10101071009 866 2017 10101
51 10101071010 862 2017 10101
52 10101071011 742 2017 10101
53 10101071012 753 2017 10101
54 10101071013 26 2017 10101
55 10101071014 235 2017 10101
56 10101131001 204 2017 10101
57 10101151001 1170 2017 10101
58 10101151002 1499 2017 10101
59 10101151003 146 2017 10101
60 10101151004 118 2017 10101
61 10101151005 128 2017 10101
62 10101161001 190 2017 10101
63 10101161002 1550 2017 10101
64 10101161003 611 2017 10101
65 10101161004 366 2017 10101
66 10101161005 52 2017 10101
67 10101161006 134 2017 10101
68 10101171001 550 2017 10101
69 10101171002 814 2017 10101
70 10101171003 863 2017 10101
71 10101171004 1489 2017 10101
72 10101171005 1130 2017 10101
73 10101171006 1028 2017 10101
74 10101181001 978 2017 10101
75 10101181002 765 2017 10101
76 10101181003 425 2017 10101
77 10101181004 452 2017 10101
78 10101991999 107 2017 10101
311 10102051001 938 2017 10102
312 10102051002 1185 2017 10102
313 10102141001 972 2017 10102
314 10102141002 1641 2017 10102
315 10102991999 20 2017 10102
548 10104011001 853 2017 10104
549 10104011002 1280 2017 10104
550 10104991999 3 2017 10104
783 10105011001 1055 2017 10105
784 10105011002 951 2017 10105
785 10105011003 1023 2017 10105
786 10105011004 810 2017 10105
787 10105991999 33 2017 10105
1020 10106011001 1519 2017 10106
1021 10106011002 878 2017 10106
1022 10106991999 64 2017 10106
1255 10107011001 977 2017 10107
1256 10107011002 306 2017 10107
1257 10107011003 877 2017 10107
1258 10107021001 642 2017 10107
1259 10107021002 926 2017 10107
1260 10107991999 47 2017 10107


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
10101 10101021005 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031001 1468 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101011001 181 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101011002 964 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021001 1249 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021002 328 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021003 699 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021004 1043 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031013 1055 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031014 645 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031002 1424 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031003 1163 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031004 836 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031005 1701 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031006 704 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031007 652 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031008 1013 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031009 1347 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031010 910 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031011 666 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031012 499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061002 928 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061003 1153 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061004 987 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061005 746 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061006 1398 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061007 242 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061008 627 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061009 46 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061010 483 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071001 547 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071002 1125 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071003 1131 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071004 847 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071005 789 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071006 963 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071007 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071008 1179 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071009 866 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071010 862 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071011 742 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071012 753 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071013 26 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071014 235 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101131001 204 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151001 1170 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151002 1499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151003 146 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151004 118 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151005 128 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031015 541 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031016 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031017 821 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101041001 1331 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101041002 644 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101041003 1650 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051001 825 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051002 579 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051003 888 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051004 1372 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061001 2344 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171006 1028 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181001 978 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181002 765 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181003 425 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181004 452 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101991999 107 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161004 366 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161005 52 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161006 134 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171001 550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171002 814 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171003 863 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171004 1489 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171005 1130 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161003 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161001 190 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161002 1550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10102 10102051001 938 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102141002 1641 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102991999 20 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102051002 1185 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102141001 972 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10104 10104991999 3 2017 Fresia 223666.2 2017 10104 12261 2742371891
10104 10104011001 853 2017 Fresia 223666.2 2017 10104 12261 2742371891
10104 10104011002 1280 2017 Fresia 223666.2 2017 10104 12261 2742371891
10105 10105011002 951 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105011001 1055 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105991999 33 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105011003 1023 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105011004 810 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10106 10106011001 1519 2017 Los Muermos 233220.1 2017 10106 17068 3980600731
10106 10106011002 878 2017 Los Muermos 233220.1 2017 10106 17068 3980600731
10106 10106991999 64 2017 Los Muermos 233220.1 2017 10106 17068 3980600731
10107 10107991999 47 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107011002 306 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107011001 977 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107011003 877 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107021001 642 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107021002 926 2017 Llanquihue 251391.8 2017 10107 17591 4422233283


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
10101 10101021005 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031001 1468 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101011001 181 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101011002 964 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021001 1249 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021002 328 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021003 699 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101021004 1043 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031013 1055 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031014 645 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031002 1424 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031003 1163 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031004 836 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031005 1701 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031006 704 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031007 652 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031008 1013 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031009 1347 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031010 910 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031011 666 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031012 499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061002 928 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061003 1153 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061004 987 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061005 746 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061006 1398 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061007 242 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061008 627 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061009 46 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061010 483 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071001 547 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071002 1125 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071003 1131 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071004 847 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071005 789 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071006 963 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071007 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071008 1179 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071009 866 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071010 862 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071011 742 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071012 753 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071013 26 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101071014 235 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101131001 204 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151001 1170 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151002 1499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151003 146 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151004 118 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101151005 128 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031015 541 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031016 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101031017 821 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101041001 1331 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101041002 644 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101041003 1650 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051001 825 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051002 579 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051003 888 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101051004 1372 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101061001 2344 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171006 1028 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181001 978 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181002 765 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181003 425 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101181004 452 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101991999 107 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161004 366 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161005 52 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161006 134 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171001 550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171002 814 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171003 863 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171004 1489 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101171005 1130 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161003 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161001 190 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10101 10101161002 1550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754
10102 10102051001 938 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102141002 1641 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102991999 20 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102051002 1185 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10102 10102141001 972 2017 Calbuco 280878.2 2017 10102 33985 9545646863
10104 10104991999 3 2017 Fresia 223666.2 2017 10104 12261 2742371891
10104 10104011001 853 2017 Fresia 223666.2 2017 10104 12261 2742371891
10104 10104011002 1280 2017 Fresia 223666.2 2017 10104 12261 2742371891
10105 10105011002 951 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105011001 1055 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105991999 33 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105011003 1023 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10105 10105011004 810 2017 Frutillar 281543.9 2017 10105 18428 5188291726
10106 10106011001 1519 2017 Los Muermos 233220.1 2017 10106 17068 3980600731
10106 10106011002 878 2017 Los Muermos 233220.1 2017 10106 17068 3980600731
10106 10106991999 64 2017 Los Muermos 233220.1 2017 10106 17068 3980600731
10107 10107991999 47 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107011002 306 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107011001 977 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107011003 877 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107021001 642 2017 Llanquihue 251391.8 2017 10107 17591 4422233283
10107 10107021002 926 2017 Llanquihue 251391.8 2017 10107 17591 4422233283


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
10101011001 10101 181 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 584 0.0023749 10101
10101011002 10101 964 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2941 0.0119600 10101
10101021001 10101 1249 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3953 0.0160755 10101
10101021002 10101 328 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1107 0.0045018 10101
10101021003 10101 699 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2294 0.0093289 10101
10101021004 10101 1043 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3391 0.0137900 10101
10101021005 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2564 0.0104269 10101
10101031001 10101 1468 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4530 0.0184220 10101
10101031002 10101 1424 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4740 0.0192760 10101
10101031003 10101 1163 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4107 0.0167018 10101
10101031004 10101 836 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2856 0.0116144 10101
10101031005 10101 1701 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5690 0.0231393 10101
10101031006 10101 704 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2460 0.0100040 10101
10101031007 10101 652 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2292 0.0093208 10101
10101031008 10101 1013 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3585 0.0145790 10101
10101031009 10101 1347 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4436 0.0180397 10101
10101031010 10101 910 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3566 0.0145017 10101
10101031011 10101 666 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2757 0.0112118 10101
10101031012 10101 499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1849 0.0075193 10101
10101031013 10101 1055 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3945 0.0160430 10101
10101031014 10101 645 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2265 0.0092110 10101
10101031015 10101 541 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1930 0.0078487 10101
10101031016 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3071 0.0124887 10101
10101031017 10101 821 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3885 0.0157990 10101
10101041001 10101 1331 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4342 0.0176574 10101
10101041002 10101 644 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2169 0.0088206 10101
10101041003 10101 1650 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5202 0.0211548 10101
10101051001 10101 825 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2463 0.0100162 10101
10101051002 10101 579 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1913 0.0077795 10101
10101051003 10101 888 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3272 0.0133061 10101
10101051004 10101 1372 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3633 0.0147742 10101
10101061001 10101 2344 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6787 0.0276004 10101
10101061002 10101 928 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2729 0.0110979 10101
10101061003 10101 1153 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3668 0.0149165 10101
10101061004 10101 987 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2995 0.0121796 10101
10101061005 10101 746 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2571 0.0104554 10101
10101061006 10101 1398 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4130 0.0167953 10101
10101061007 10101 242 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 817 0.0033225 10101
10101061008 10101 627 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2109 0.0085766 10101
10101061009 10101 46 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 168 0.0006832 10101
10101061010 10101 483 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1543 0.0062749 10101
10101071001 10101 547 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2352 0.0095648 10101
10101071002 10101 1125 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3919 0.0159372 10101
10101071003 10101 1131 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4978 0.0202438 10101
10101071004 10101 847 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3443 0.0140015 10101
10101071005 10101 789 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2751 0.0111874 10101
10101071006 10101 963 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4214 0.0171369 10101
10101071007 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2345 0.0095363 10101
10101071008 10101 1179 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5480 0.0222853 10101
10101071009 10101 866 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3549 0.0144326 10101
10101071010 10101 862 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3521 0.0143187 10101
10101071011 10101 742 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3094 0.0125822 10101
10101071012 10101 753 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2621 0.0106587 10101
10101071013 10101 26 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 84 0.0003416 10101
10101071014 10101 235 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 875 0.0035583 10101
10101131001 10101 204 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 604 0.0024563 10101
10101151001 10101 1170 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3973 0.0161568 10101
10101151002 10101 1499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4655 0.0189303 10101
10101151003 10101 146 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 592 0.0024075 10101
10101151004 10101 118 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 325 0.0013217 10101
10101151005 10101 128 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 384 0.0015616 10101
10101161001 10101 190 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 739 0.0030053 10101
10101161002 10101 1550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6507 0.0264618 10101
10101161003 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2841 0.0115534 10101
10101161004 10101 366 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1224 0.0049776 10101
10101161005 10101 52 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 188 0.0007645 10101
10101161006 10101 134 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 435 0.0017690 10101
10101171001 10101 550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1747 0.0071045 10101
10101171002 10101 814 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2902 0.0118014 10101
10101171003 10101 863 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2873 0.0116835 10101
10101171004 10101 1489 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4707 0.0191418 10101
10101171005 10101 1130 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3782 0.0153801 10101
10101171006 10101 1028 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3515 0.0142943 10101
10101181001 10101 978 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3155 0.0128303 10101
10101181002 10101 765 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2282 0.0092801 10101
10101181003 10101 425 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1312 0.0053355 10101
10101181004 10101 452 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1466 0.0059617 10101
10101991999 10101 107 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1400 0.0056933 10101
10102051001 10102 938 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3082 0.0906871 10102
10102051002 10102 1185 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3879 0.1141386 10102
10102141001 10102 972 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3356 0.0987494 10102
10102141002 10102 1641 2017 Calbuco 280878.2 2017 10102 33985 9545646863 5586 0.1643666 10102
10102991999 10102 20 2017 Calbuco 280878.2 2017 10102 33985 9545646863 93 0.0027365 10102
10104011001 10104 853 2017 Fresia 223666.2 2017 10104 12261 2742371891 2769 0.2258380 10104
10104011002 10104 1280 2017 Fresia 223666.2 2017 10104 12261 2742371891 4559 0.3718294 10104
10104991999 10104 3 2017 Fresia 223666.2 2017 10104 12261 2742371891 3 0.0002447 10104
10105011001 10105 1055 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3426 0.1859127 10105
10105011002 10105 951 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3126 0.1696332 10105
10105011003 10105 1023 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3037 0.1648036 10105
10105011004 10105 810 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3287 0.1783699 10105
10105991999 10105 33 2017 Frutillar 281543.9 2017 10105 18428 5188291726 76 0.0041242 10105
10106011001 10106 1519 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 5180 0.3034919 10106
10106011002 10106 878 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 2748 0.1610030 10106
10106991999 10106 64 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 178 0.0104289 10106
10107011001 10107 977 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 4286 0.2436473 10107
10107011002 10107 306 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 1159 0.0658860 10107
10107011003 10107 877 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3146 0.1788415 10107
10107021001 10107 642 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 2292 0.1302939 10107
10107021002 10107 926 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3221 0.1831050 10107
10107991999 10107 47 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 118 0.0067080 10107


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
10101011001 10101 181 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 584 0.0023749 10101 177775197.6
10101011002 10101 964 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2941 0.0119600 10101 895268589.3
10101021001 10101 1249 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3953 0.0160755 10101 1203331089.2
10101021002 10101 328 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1107 0.0045018 10101 336981410.5
10101021003 10101 699 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2294 0.0093289 10101 698315587.8
10101021004 10101 1043 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3391 0.0137900 10101 1032252902.5
10101021005 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2564 0.0104269 10101 780506175.8
10101031001 10101 1468 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4530 0.0184220 10101 1378975419.7
10101031002 10101 1424 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4740 0.0192760 10101 1442901432.6
10101031003 10101 1163 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4107 0.0167018 10101 1250210165.3
10101031004 10101 836 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2856 0.0116144 10101 869393774.6
10101031005 10101 1701 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5690 0.0231393 10101 1732090538.3
10101031006 10101 704 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2460 0.0100040 10101 748847578.9
10101031007 10101 652 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2292 0.0093208 10101 697706768.7
10101031008 10101 1013 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3585 0.0145790 10101 1091308362.0
10101031009 10101 1347 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4436 0.0180397 10101 1350360918.8
10101031010 10101 910 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3566 0.0145017 10101 1085524579.9
10101031011 10101 666 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2757 0.0112118 10101 839257225.7
10101031012 10101 499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1849 0.0075193 10101 562853322.5
10101031013 10101 1055 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3945 0.0160430 10101 1200895812.6
10101031014 10101 645 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2265 0.0092110 10101 689487709.9
10101031015 10101 541 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1930 0.0078487 10101 587510498.9
10101031016 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3071 0.0124887 10101 934841835.3
10101031017 10101 821 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3885 0.0157990 10101 1182631237.5
10101041001 10101 1331 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4342 0.0176574 10101 1321746417.8
10101041002 10101 644 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2169 0.0088206 10101 660264389.7
10101041003 10101 1650 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5202 0.0211548 10101 1583538660.8
10101051001 10101 825 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2463 0.0100162 10101 749760807.7
10101051002 10101 579 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1913 0.0077795 10101 582335536.0
10101051003 10101 888 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3272 0.0133061 10101 996028161.9
10101051004 10101 1372 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3633 0.0147742 10101 1105920022.1
10101061001 10101 2344 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6787 0.0276004 10101 2066027852.9
10101061002 10101 928 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2729 0.0110979 10101 830733757.3
10101061003 10101 1153 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3668 0.0149165 10101 1116574357.5
10101061004 10101 987 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2995 0.0121796 10101 911706706.9
10101061005 10101 746 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2571 0.0104554 10101 782637042.9
10101061006 10101 1398 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4130 0.0167953 10101 1257211585.8
10101061007 10101 242 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 817 0.0033225 10101 248702630.9
10101061008 10101 627 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2109 0.0085766 10101 641999814.6
10101061009 10101 46 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 168 0.0006832 10101 51140810.3
10101061010 10101 483 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1543 0.0062749 10101 469703989.6
10101071001 10101 547 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2352 0.0095648 10101 715971343.8
10101071002 10101 1125 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3919 0.0159372 10101 1192981163.4
10101071003 10101 1131 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4978 0.0202438 10101 1515350913.8
10101071004 10101 847 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3443 0.0140015 10101 1048082200.9
10101071005 10101 789 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2751 0.0111874 10101 837430768.2
10101071006 10101 963 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4214 0.0171369 10101 1282781990.9
10101071007 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2345 0.0095363 10101 713840476.7
10101071008 10101 1179 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5480 0.0222853 10101 1668164525.4
10101071009 10101 866 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3549 0.0144326 10101 1080349616.9
10101071010 10101 862 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3521 0.0143187 10101 1071826148.6
10101071011 10101 742 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3094 0.0125822 10101 941843255.8
10101071012 10101 753 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2621 0.0106587 10101 797857522.1
10101071013 10101 26 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 84 0.0003416 10101 25570405.1
10101071014 10101 235 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 875 0.0035583 10101 266358386.8
10101131001 10101 204 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 604 0.0024563 10101 183863389.3
10101151001 10101 1170 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3973 0.0161568 10101 1209419280.9
10101151002 10101 1499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4655 0.0189303 10101 1417026617.9
10101151003 10101 146 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 592 0.0024075 10101 180210474.3
10101151004 10101 118 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 325 0.0013217 10101 98933115.1
10101151005 10101 128 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 384 0.0015616 10101 116893280.6
10101161001 10101 190 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 739 0.0030053 10101 224958683.3
10101161002 10101 1550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6507 0.0264618 10101 1980793169.2
10101161003 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2841 0.0115534 10101 864827630.8
10101161004 10101 366 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1224 0.0049776 10101 372597332.0
10101161005 10101 52 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 188 0.0007645 10101 57229002.0
10101161006 10101 134 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 435 0.0017690 10101 132418169.4
10101171001 10101 550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1747 0.0071045 10101 531803544.9
10101171002 10101 814 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2902 0.0118014 10101 883396615.5
10101171003 10101 863 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2873 0.0116835 10101 874568737.5
10101171004 10101 1489 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4707 0.0191418 10101 1432855916.3
10101171005 10101 1130 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3782 0.0153801 10101 1151277050.2
10101171006 10101 1028 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3515 0.0142943 10101 1069999691.0
10101181001 10101 978 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3155 0.0128303 10101 960412240.5
10101181002 10101 765 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2282 0.0092801 10101 694662672.8
10101181003 10101 425 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1312 0.0053355 10101 399385375.4
10101181004 10101 452 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1466 0.0059617 10101 446264451.5
10101991999 10101 107 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1400 0.0056933 10101 426173418.9
10102051001 10102 938 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3082 0.0906871 10102 865666724.5
10102051002 10102 1185 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3879 0.1141386 10102 1089526678.9
10102141001 10102 972 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3356 0.0987494 10102 942627361.2
10102141002 10102 1641 2017 Calbuco 280878.2 2017 10102 33985 9545646863 5586 0.1643666 10102 1568985828.3
10102991999 10102 20 2017 Calbuco 280878.2 2017 10102 33985 9545646863 93 0.0027365 10102 26121676.0
10104011001 10104 853 2017 Fresia 223666.2 2017 10104 12261 2742371891 2769 0.2258380 10104 619331846.2
10104011002 10104 1280 2017 Fresia 223666.2 2017 10104 12261 2742371891 4559 0.3718294 10104 1019694433.8
10104991999 10104 3 2017 Fresia 223666.2 2017 10104 12261 2742371891 3 0.0002447 10104 670998.8
10105011001 10105 1055 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3426 0.1859127 10105 964569538.4
10105011002 10105 951 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3126 0.1696332 10105 880106356.4
10105011003 10105 1023 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3037 0.1648036 10105 855048945.8
10105011004 10105 810 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3287 0.1783699 10105 925434930.8
10105991999 10105 33 2017 Frutillar 281543.9 2017 10105 18428 5188291726 76 0.0041242 10105 21397339.4
10106011001 10106 1519 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 5180 0.3034919 10106 1208080137.5
10106011002 10106 878 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 2748 0.1610030 10106 640888845.2
10106991999 10106 64 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 178 0.0104289 10106 41513178.5
10107011001 10107 977 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 4286 0.2436473 10107 1077465286.3
10107011002 10107 306 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 1159 0.0658860 10107 291363104.7
10107011003 10107 877 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3146 0.1788415 10107 790878625.9
10107021001 10107 642 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 2292 0.1302939 10107 576190022.4
10107021002 10107 926 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3221 0.1831050 10107 809733011.4
10107991999 10107 47 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 118 0.0067080 10107 29664233.3

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 
## -360593324  -68258025  -17285575   63784378  532632297 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 24451807   20137759   1.214    0.226    
## Freq.x        942392      21916  43.000   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 146800000 on 219 degrees of freedom
## Multiple R-squared:  0.8941, Adjusted R-squared:  0.8936 
## F-statistic:  1849 on 1 and 219 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 0.618209552916693 linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 ln X \]
6 log-raíz 0.818962177922309 linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = e^{''beta_0 + ''beta_1 ''sqrt{X}} \]
7 raíz-log 0.828372561516629 linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = {''beta_0}^2 + 2 ''beta_0 ''beta_1 ''ln{X}+ ''beta_1^2 ln^2X \]
4 raíz cuadrada 0.847906008657413 linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 ''sqrt {X} \]
1 cuadrático 0.893615994239683 linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 X^2 \]
2 cúbico 0.893615994239683 linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01) \[ ''hat Y = ''beta_0 + ''beta_1 X^3 \]
5 raíz-raíz 0.942888878648375 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 0.973442101545255 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 
## -1.23560 -0.12406 -0.00031  0.12397  1.49960 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.50912    0.07395   182.7   <2e-16 ***
## log(Freq.x)  1.04041    0.01159    89.8   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2529 on 219 degrees of freedom
## Multiple R-squared:  0.9736, Adjusted R-squared:  0.9734 
## F-statistic:  8065 on 1 and 219 DF,  p-value: < 2.2e-16
aa <- linearMod$coefficients[1]
aa
## (Intercept) 
##    13.50912
bb <- linearMod$coefficients[2]
bb
## log(Freq.x) 
##    1.040405

9 Modelo log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.9734).

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 
## -1.23560 -0.12406 -0.00031  0.12397  1.49960 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.50912    0.07395   182.7   <2e-16 ***
## log(Freq.x)  1.04041    0.01159    89.8   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2529 on 219 degrees of freedom
## Multiple R-squared:  0.9736, Adjusted R-squared:  0.9734 
## F-statistic:  8065 on 1 and 219 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


\[ \hat Y = e^{13.50912 +1.040405 \cdot ln{X}} \]


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
10101011001 10101 181 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 584 0.0023749 10101 177775197.6 164375484
10101011002 10101 964 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2941 0.0119600 10101 895268589.3 936668481
10101021001 10101 1249 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3953 0.0160755 10101 1203331089.2 1226355339
10101021002 10101 328 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1107 0.0045018 10101 336981410.5 305115865
10101021003 10101 699 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2294 0.0093289 10101 698315587.8 670417688
10101021004 10101 1043 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3391 0.0137900 10101 1032252902.5 1016659068
10101021005 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2564 0.0104269 10101 780506175.8 744412386
10101031001 10101 1468 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4530 0.0184220 10101 1378975419.7 1450824666
10101031002 10101 1424 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4740 0.0192760 10101 1442901432.6 1405610084
10101031003 10101 1163 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4107 0.0167018 10101 1250210165.3 1138627671
10101031004 10101 836 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2856 0.0116144 10101 869393774.6 807635200
10101031005 10101 1701 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5690 0.0231393 10101 1732090538.3 1691134907
10101031006 10101 704 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2460 0.0100040 10101 748847578.9 675407721
10101031007 10101 652 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2292 0.0093208 10101 697706768.7 623583257
10101031008 10101 1013 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3585 0.0145790 10101 1091308362.0 986253013
10101031009 10101 1347 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4436 0.0180397 10101 1350360918.8 1326621367
10101031010 10101 910 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3566 0.0145017 10101 1085524579.9 882142387
10101031011 10101 666 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2757 0.0112118 10101 839257225.7 637520105
10101031012 10101 499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1849 0.0075193 10101 562853322.5 472122210
10101031013 10101 1055 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3945 0.0160430 10101 1200895812.6 1028831446
10101031014 10101 645 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2265 0.0092110 10101 689487709.9 616619351
10101031015 10101 541 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1930 0.0078487 10101 587510498.9 513534052
10101031016 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3071 0.0124887 10101 934841835.3 744412386
10101031017 10101 821 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3885 0.0157990 10101 1182631237.5 792564118
10101041001 10101 1331 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4342 0.0176574 10101 1321746417.8 1310230674
10101041002 10101 644 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2169 0.0088206 10101 660264389.7 615624755
10101041003 10101 1650 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5202 0.0211548 10101 1583538660.8 1638414228
10101051001 10101 825 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2463 0.0100162 10101 749760807.7 796581993
10101051002 10101 579 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1913 0.0077795 10101 582335536.0 551114386
10101051003 10101 888 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3272 0.0133061 10101 996028161.9 859965084
10101051004 10101 1372 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3633 0.0147742 10101 1105920022.1 1352247546
10101061001 10101 2344 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6787 0.0276004 10101 2066027852.9 2360794199
10101061002 10101 928 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2729 0.0110979 10101 830733757.3 900303599
10101061003 10101 1153 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3668 0.0149165 10101 1116574357.5 1128443423
10101061004 10101 987 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2995 0.0121796 10101 911706706.9 959930479
10101061005 10101 746 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2571 0.0104554 10101 782637042.9 717379626
10101061006 10101 1398 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4130 0.0167953 10101 1257211585.8 1378918789
10101061007 10101 242 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 817 0.0033225 10101 248702630.9 222367053
10101061008 10101 627 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2109 0.0085766 10101 641999814.6 598726259
10101061009 10101 46 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 168 0.0006832 10101 51140810.3 39525585
10101061010 10101 483 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1543 0.0062749 10101 469703989.6 456382667
10101071001 10101 547 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2352 0.0095648 10101 715971343.8 519460886
10101071002 10101 1125 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3919 0.0159372 10101 1192981163.4 1099946610
10101071003 10101 1131 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4978 0.0202438 10101 1515350913.8 1106050681
10101071004 10101 847 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3443 0.0140015 10101 1048082200.9 818694285
10101071005 10101 789 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2751 0.0111874 10101 837430768.2 760449900
10101071006 10101 963 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4214 0.0171369 10101 1282781990.9 935657595
10101071007 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2345 0.0095363 10101 713840476.7 582838687
10101071008 10101 1179 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5480 0.0222853 10101 1668164525.4 1154929816
10101071009 10101 866 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3549 0.0144326 10101 1080349616.9 837809972
10101071010 10101 862 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3521 0.0143187 10101 1071826148.6 833784196
10101071011 10101 742 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3094 0.0125822 10101 941843255.8 713378100
10101071012 10101 753 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2621 0.0106587 10101 797857522.1 724384380
10101071013 10101 26 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 84 0.0003416 10101 25570405.1 21831421
10101071014 10101 235 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 875 0.0035583 10101 266358386.8 215679004
10101131001 10101 204 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 604 0.0024563 10101 183863389.3 186160596
10101151001 10101 1170 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3973 0.0161568 10101 1209419280.9 1145758752
10101151002 10101 1499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4655 0.0189303 10101 1417026617.9 1482713391
10101151003 10101 146 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 592 0.0024075 10101 180210474.3 131443909
10101151004 10101 118 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 325 0.0013217 10101 98933115.1 105325444
10101151005 10101 128 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 384 0.0015616 10101 116893280.6 114627468
10101161001 10101 190 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 739 0.0030053 10101 224958683.3 172887508
10101161002 10101 1550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6507 0.0264618 10101 1980793169.2 1535233251
10101161003 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2841 0.0115534 10101 864827630.8 582838687
10101161004 10101 366 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1224 0.0049776 10101 372597332.0 341975994
10101161005 10101 52 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 188 0.0007645 10101 57229002.0 44902986
10101161006 10101 134 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 435 0.0017690 10101 132418169.4 120222952
10101171001 10101 550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1747 0.0071045 10101 531803544.9 522425290
10101171002 10101 814 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2902 0.0118014 10101 883396615.5 785534740
10101171003 10101 863 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2873 0.0116835 10101 874568737.5 834790569
10101171004 10101 1489 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4707 0.0191418 10101 1432855916.3 1472423767
10101171005 10101 1130 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3782 0.0153801 10101 1151277050.2 1105033245
10101171006 10101 1028 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3515 0.0142943 10101 1069999691.0 1001451559
10101181001 10101 978 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3155 0.0128303 10101 960412240.5 950825321
10101181002 10101 765 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2282 0.0092801 10101 694662672.8 736398640
10101181003 10101 425 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1312 0.0053355 10101 399385375.4 399508562
10101181004 10101 452 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1466 0.0059617 10101 446264451.5 425947840
10101991999 10101 107 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1400 0.0056933 10101 426173418.9 95130091
10102051001 10102 938 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3082 0.0906871 10102 865666724.5 910399331
10102051002 10102 1185 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3879 0.1141386 10102 1089526678.9 1161045432
10102141001 10102 972 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3356 0.0987494 10102 942627361.2 944757094
10102141002 10102 1641 2017 Calbuco 280878.2 2017 10102 33985 9545646863 5586 0.1643666 10102 1568985828.3 1629117354
10102991999 10102 20 2017 Calbuco 280878.2 2017 10102 33985 9545646863 93 0.0027365 10102 26121676.0 16616315
10104011001 10104 853 2017 Fresia 223666.2 2017 10104 12261 2742371891 2769 0.2258380 10104 619331846.2 824728964
10104011002 10104 1280 2017 Fresia 223666.2 2017 10104 12261 2742371891 4559 0.3718294 10104 1019694433.8 1258038913
10104991999 10104 3 2017 Fresia 223666.2 2017 10104 12261 2742371891 3 0.0002447 10104 670998.8 2308531
10105011001 10105 1055 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3426 0.1859127 10105 964569538.4 1028831446
10105011002 10105 951 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3126 0.1696332 10105 880106356.4 923530279
10105011003 10105 1023 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3037 0.1648036 10105 855048945.8 996384375
10105011004 10105 810 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3287 0.1783699 10105 925434930.8 781519048
10105991999 10105 33 2017 Frutillar 281543.9 2017 10105 18428 5188291726 76 0.0041242 10105 21397339.4 27977325
10106011001 10106 1519 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 5180 0.3034919 10106 1208080137.5 1503300943
10106011002 10106 878 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 2748 0.1610030 10106 640888845.2 849891795
10106991999 10106 64 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 178 0.0104289 10106 41513178.5 55730825
10107011001 10107 977 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 4286 0.2436473 10107 1077465286.3 949813845
10107011002 10107 306 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 1159 0.0658860 10107 291363104.7 283853369
10107011003 10107 877 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3146 0.1788415 10107 790878625.9 848884721
10107021001 10107 642 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 2292 0.1302939 10107 576190022.4 613635752
10107021002 10107 926 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3221 0.1831050 10107 809733011.4 898284978
10107991999 10107 47 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 118 0.0067080 10107 29664233.3 40419945


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
10101011001 10101 181 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 584 0.0023749 10101 177775197.6 164375484 281464.87
10101011002 10101 964 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2941 0.0119600 10101 895268589.3 936668481 318486.39
10101021001 10101 1249 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3953 0.0160755 10101 1203331089.2 1226355339 310234.09
10101021002 10101 328 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1107 0.0045018 10101 336981410.5 305115865 275624.09
10101021003 10101 699 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2294 0.0093289 10101 698315587.8 670417688 292248.34
10101021004 10101 1043 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3391 0.0137900 10101 1032252902.5 1016659068 299810.99
10101021005 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2564 0.0104269 10101 780506175.8 744412386 290332.44
10101031001 10101 1468 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4530 0.0184220 10101 1378975419.7 1450824666 320270.35
10101031002 10101 1424 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4740 0.0192760 10101 1442901432.6 1405610084 296542.21
10101031003 10101 1163 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4107 0.0167018 10101 1250210165.3 1138627671 277240.73
10101031004 10101 836 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2856 0.0116144 10101 869393774.6 807635200 282785.43
10101031005 10101 1701 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5690 0.0231393 10101 1732090538.3 1691134907 297211.76
10101031006 10101 704 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2460 0.0100040 10101 748847578.9 675407721 274555.98
10101031007 10101 652 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2292 0.0093208 10101 697706768.7 623583257 272069.48
10101031008 10101 1013 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3585 0.0145790 10101 1091308362.0 986253013 275105.44
10101031009 10101 1347 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4436 0.0180397 10101 1350360918.8 1326621367 299058.02
10101031010 10101 910 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3566 0.0145017 10101 1085524579.9 882142387 247375.88
10101031011 10101 666 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2757 0.0112118 10101 839257225.7 637520105 231236.89
10101031012 10101 499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1849 0.0075193 10101 562853322.5 472122210 255339.22
10101031013 10101 1055 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3945 0.0160430 10101 1200895812.6 1028831446 260793.78
10101031014 10101 645 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2265 0.0092110 10101 689487709.9 616619351 272238.12
10101031015 10101 541 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1930 0.0078487 10101 587510498.9 513534052 266079.82
10101031016 10101 773 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3071 0.0124887 10101 934841835.3 744412386 242400.65
10101031017 10101 821 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3885 0.0157990 10101 1182631237.5 792564118 204006.21
10101041001 10101 1331 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4342 0.0176574 10101 1321746417.8 1310230674 301757.41
10101041002 10101 644 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2169 0.0088206 10101 660264389.7 615624755 283828.84
10101041003 10101 1650 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5202 0.0211548 10101 1583538660.8 1638414228 314958.52
10101051001 10101 825 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2463 0.0100162 10101 749760807.7 796581993 323419.40
10101051002 10101 579 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1913 0.0077795 10101 582335536.0 551114386 288089.07
10101051003 10101 888 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3272 0.0133061 10101 996028161.9 859965084 262825.51
10101051004 10101 1372 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3633 0.0147742 10101 1105920022.1 1352247546 372212.37
10101061001 10101 2344 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6787 0.0276004 10101 2066027852.9 2360794199 347840.61
10101061002 10101 928 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2729 0.0110979 10101 830733757.3 900303599 329902.38
10101061003 10101 1153 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3668 0.0149165 10101 1116574357.5 1128443423 307645.43
10101061004 10101 987 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2995 0.0121796 10101 911706706.9 959930479 320511.01
10101061005 10101 746 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2571 0.0104554 10101 782637042.9 717379626 279027.47
10101061006 10101 1398 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4130 0.0167953 10101 1257211585.8 1378918789 333878.64
10101061007 10101 242 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 817 0.0033225 10101 248702630.9 222367053 272175.10
10101061008 10101 627 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2109 0.0085766 10101 641999814.6 598726259 283891.07
10101061009 10101 46 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 168 0.0006832 10101 51140810.3 39525585 235271.34
10101061010 10101 483 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1543 0.0062749 10101 469703989.6 456382667 295776.19
10101071001 10101 547 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2352 0.0095648 10101 715971343.8 519460886 220859.22
10101071002 10101 1125 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3919 0.0159372 10101 1192981163.4 1099946610 280670.22
10101071003 10101 1131 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4978 0.0202438 10101 1515350913.8 1106050681 222187.76
10101071004 10101 847 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3443 0.0140015 10101 1048082200.9 818694285 237785.15
10101071005 10101 789 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2751 0.0111874 10101 837430768.2 760449900 276426.72
10101071006 10101 963 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4214 0.0171369 10101 1282781990.9 935657595 222035.50
10101071007 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2345 0.0095363 10101 713840476.7 582838687 248545.28
10101071008 10101 1179 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 5480 0.0222853 10101 1668164525.4 1154929816 210753.62
10101071009 10101 866 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3549 0.0144326 10101 1080349616.9 837809972 236069.31
10101071010 10101 862 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3521 0.0143187 10101 1071826148.6 833784196 236803.24
10101071011 10101 742 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3094 0.0125822 10101 941843255.8 713378100 230568.23
10101071012 10101 753 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2621 0.0106587 10101 797857522.1 724384380 276377.10
10101071013 10101 26 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 84 0.0003416 10101 25570405.1 21831421 259897.86
10101071014 10101 235 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 875 0.0035583 10101 266358386.8 215679004 246490.29
10101131001 10101 204 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 604 0.0024563 10101 183863389.3 186160596 308212.91
10101151001 10101 1170 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3973 0.0161568 10101 1209419280.9 1145758752 288386.30
10101151002 10101 1499 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4655 0.0189303 10101 1417026617.9 1482713391 318520.60
10101151003 10101 146 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 592 0.0024075 10101 180210474.3 131443909 222033.63
10101151004 10101 118 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 325 0.0013217 10101 98933115.1 105325444 324078.29
10101151005 10101 128 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 384 0.0015616 10101 116893280.6 114627468 298509.03
10101161001 10101 190 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 739 0.0030053 10101 224958683.3 172887508 233947.91
10101161002 10101 1550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 6507 0.0264618 10101 1980793169.2 1535233251 235935.65
10101161003 10101 611 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2841 0.0115534 10101 864827630.8 582838687 205152.65
10101161004 10101 366 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1224 0.0049776 10101 372597332.0 341975994 279392.15
10101161005 10101 52 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 188 0.0007645 10101 57229002.0 44902986 238845.67
10101161006 10101 134 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 435 0.0017690 10101 132418169.4 120222952 276374.60
10101171001 10101 550 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1747 0.0071045 10101 531803544.9 522425290 299041.38
10101171002 10101 814 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2902 0.0118014 10101 883396615.5 785534740 270687.37
10101171003 10101 863 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2873 0.0116835 10101 874568737.5 834790569 290564.07
10101171004 10101 1489 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 4707 0.0191418 10101 1432855916.3 1472423767 312815.76
10101171005 10101 1130 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3782 0.0153801 10101 1151277050.2 1105033245 292182.24
10101171006 10101 1028 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3515 0.0142943 10101 1069999691.0 1001451559 284907.98
10101181001 10101 978 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 3155 0.0128303 10101 960412240.5 950825321 301370.94
10101181002 10101 765 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 2282 0.0092801 10101 694662672.8 736398640 322698.79
10101181003 10101 425 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1312 0.0053355 10101 399385375.4 399508562 304503.48
10101181004 10101 452 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1466 0.0059617 10101 446264451.5 425947840 290551.05
10101991999 10101 107 2017 Puerto Montt 304409.6 2017 10101 245902 74854925754 1400 0.0056933 10101 426173418.9 95130091 67950.06
10102051001 10102 938 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3082 0.0906871 10102 865666724.5 910399331 295392.39
10102051002 10102 1185 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3879 0.1141386 10102 1089526678.9 1161045432 299315.66
10102141001 10102 972 2017 Calbuco 280878.2 2017 10102 33985 9545646863 3356 0.0987494 10102 942627361.2 944757094 281512.84
10102141002 10102 1641 2017 Calbuco 280878.2 2017 10102 33985 9545646863 5586 0.1643666 10102 1568985828.3 1629117354 291642.92
10102991999 10102 20 2017 Calbuco 280878.2 2017 10102 33985 9545646863 93 0.0027365 10102 26121676.0 16616315 178670.06
10104011001 10104 853 2017 Fresia 223666.2 2017 10104 12261 2742371891 2769 0.2258380 10104 619331846.2 824728964 297843.61
10104011002 10104 1280 2017 Fresia 223666.2 2017 10104 12261 2742371891 4559 0.3718294 10104 1019694433.8 1258038913 275946.24
10104991999 10104 3 2017 Fresia 223666.2 2017 10104 12261 2742371891 3 0.0002447 10104 670998.8 2308531 769510.20
10105011001 10105 1055 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3426 0.1859127 10105 964569538.4 1028831446 300301.06
10105011002 10105 951 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3126 0.1696332 10105 880106356.4 923530279 295435.15
10105011003 10105 1023 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3037 0.1648036 10105 855048945.8 996384375 328081.78
10105011004 10105 810 2017 Frutillar 281543.9 2017 10105 18428 5188291726 3287 0.1783699 10105 925434930.8 781519048 237760.59
10105991999 10105 33 2017 Frutillar 281543.9 2017 10105 18428 5188291726 76 0.0041242 10105 21397339.4 27977325 368122.70
10106011001 10106 1519 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 5180 0.3034919 10106 1208080137.5 1503300943 290212.54
10106011002 10106 878 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 2748 0.1610030 10106 640888845.2 849891795 309276.49
10106991999 10106 64 2017 Los Muermos 233220.1 2017 10106 17068 3980600731 178 0.0104289 10106 41513178.5 55730825 313094.52
10107011001 10107 977 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 4286 0.2436473 10107 1077465286.3 949813845 221608.46
10107011002 10107 306 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 1159 0.0658860 10107 291363104.7 283853369 244912.31
10107011003 10107 877 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3146 0.1788415 10107 790878625.9 848884721 269829.85
10107021001 10107 642 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 2292 0.1302939 10107 576190022.4 613635752 267729.39
10107021002 10107 926 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 3221 0.1831050 10107 809733011.4 898284978 278883.88
10107991999 10107 47 2017 Llanquihue 251391.8 2017 10107 17591 4422233283 118 0.0067080 10107 29664233.3 40419945 342541.91


Guardamos:

saveRDS(h_y_m_comuna_corr, "P03C/region_10_P03C_u.rds")