1 Variable CENSO

Necesitamos calcular las frecuencias a nivel censal de las respuestas correspondientes a la categoría: “tejas o tejuelas de arcilla, metálicas, de cemento, de madera, asfálticas o plásticas” del campo P03B 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 Casen 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)
regiones
##  [1] 15 14 13 12 11 10  9 16  8  7  6  5  4  3  2  1

Hagamos un subset con la 1:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 11)

1.2 Cálculo de frecuencias

tabla_con_clave_f <- tabla_con_clave[,-c(1,2,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20),drop=FALSE] 
names(tabla_con_clave_f)[2] <- "Tipo de techo" 
# Ahora filtramos por Tipo de techo = 1.
tabla_con_clave_ff <- filter(tabla_con_clave_f, tabla_con_clave_f$`Tipo de techo` == 1)
# Determinamos las frecuencias por zona:
b <- tabla_con_clave_ff$clave
c <- tabla_con_clave_ff$`Tipo de techo`
d <- tabla_con_clave_ff$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 11101011001 1 11101 30 2017
2 11101011002 1 11101 80 2017
3 11101011003 1 11101 20 2017
4 11101011004 1 11101 22 2017
5 11101011005 1 11101 32 2017
6 11101011006 1 11101 93 2017
7 11101011007 1 11101 75 2017
8 11101022003 1 11101 2 2017
9 11101022010 1 11101 2 2017
10 11101022031 1 11101 1 2017
11 11101022038 1 11101 3 2017
12 11101032005 1 11101 1 2017
13 11101032032 1 11101 5 2017
14 11101032034 1 11101 1 2017
15 11101032901 1 11101 2 2017
16 11101042022 1 11101 3 2017
17 11101042024 1 11101 3 2017
18 11101042027 1 11101 6 2017
19 11101052004 1 11101 6 2017
20 11101052008 1 11101 5 2017
21 11101052014 1 11101 6 2017
22 11101052901 1 11101 3 2017
23 11101062023 1 11101 1 2017
24 11101062025 1 11101 2 2017
25 11101072014 1 11101 4 2017
26 11101072018 1 11101 57 2017
27 11101072019 1 11101 7 2017
28 11101072020 1 11101 4 2017
29 11101072035 1 11101 3 2017
30 11101072036 1 11101 8 2017
31 11101072037 1 11101 7 2017
32 11101082021 1 11101 1 2017
33 11101092007 1 11101 1 2017
34 11101102011 1 11101 10 2017
35 11101102020 1 11101 20 2017
36 11101102033 1 11101 69 2017
37 11101112001 1 11101 3 2017
38 11101112009 1 11101 23 2017
39 11101112011 1 11101 78 2017
40 11101112012 1 11101 5 2017
41 11101112013 1 11101 61 2017
42 11101121001 1 11101 26 2017
43 11101121002 1 11101 41 2017
44 11101121003 1 11101 161 2017
45 11101121004 1 11101 81 2017
46 11101121005 1 11101 115 2017
47 11101121006 1 11101 110 2017
48 11101121007 1 11101 36 2017
49 11101121008 1 11101 31 2017
50 11101122011 1 11101 36 2017
51 11101131001 1 11101 67 2017
52 11101131002 1 11101 67 2017
53 11101131003 1 11101 93 2017
54 11101131004 1 11101 72 2017
55 11101131005 1 11101 42 2017
56 11101131006 1 11101 3 2017
57 11101131007 1 11101 41 2017
58 11101132011 1 11101 1 2017
59 11101991999 1 11101 20 2017
194 11102012004 1 11102 1 2017
195 11102042003 1 11102 4 2017
196 11102052002 1 11102 3 2017
331 11201011001 1 11201 47 2017
332 11201011002 1 11201 62 2017
333 11201011003 1 11201 83 2017
334 11201012009 1 11201 3 2017
335 11201012013 1 11201 2 2017
336 11201012055 1 11201 1 2017
337 11201012067 1 11201 1 2017
338 11201012901 1 11201 2 2017
339 11201021001 1 11201 8 2017
340 11201022011 1 11201 2 2017
341 11201022057 1 11201 1 2017
342 11201032068 1 11201 4 2017
343 11201041001 1 11201 12 2017
344 11201041002 1 11201 68 2017
345 11201041003 1 11201 36 2017
346 11201042006 1 11201 13 2017
347 11201042007 1 11201 3 2017
348 11201052901 1 11201 2 2017
349 11201062044 1 11201 35 2017
350 11201071001 1 11201 9 2017
351 11201072901 1 11201 3 2017
486 11202011001 1 11202 51 2017
487 11202021001 1 11202 15 2017
488 11202022016 1 11202 10 2017
489 11202022020 1 11202 14 2017
490 11202032022 1 11202 1 2017
491 11202052021 1 11202 2 2017
492 11202052023 1 11202 16 2017
493 11202052901 1 11202 1 2017
494 11202991999 1 11202 1 2017
629 11203011001 1 11203 13 2017
630 11203012004 1 11203 3 2017
631 11203012005 1 11203 1 2017
632 11203012901 1 11203 3 2017
767 11301011001 1 11301 87 2017
768 11301012002 1 11301 1 2017
769 11301012003 1 11301 1 2017
770 11301012004 1 11301 2 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 11101011001 30 2017 11101
2 11101011002 80 2017 11101
3 11101011003 20 2017 11101
4 11101011004 22 2017 11101
5 11101011005 32 2017 11101
6 11101011006 93 2017 11101
7 11101011007 75 2017 11101
8 11101022003 2 2017 11101
9 11101022010 2 2017 11101
10 11101022031 1 2017 11101
11 11101022038 3 2017 11101
12 11101032005 1 2017 11101
13 11101032032 5 2017 11101
14 11101032034 1 2017 11101
15 11101032901 2 2017 11101
16 11101042022 3 2017 11101
17 11101042024 3 2017 11101
18 11101042027 6 2017 11101
19 11101052004 6 2017 11101
20 11101052008 5 2017 11101
21 11101052014 6 2017 11101
22 11101052901 3 2017 11101
23 11101062023 1 2017 11101
24 11101062025 2 2017 11101
25 11101072014 4 2017 11101
26 11101072018 57 2017 11101
27 11101072019 7 2017 11101
28 11101072020 4 2017 11101
29 11101072035 3 2017 11101
30 11101072036 8 2017 11101
31 11101072037 7 2017 11101
32 11101082021 1 2017 11101
33 11101092007 1 2017 11101
34 11101102011 10 2017 11101
35 11101102020 20 2017 11101
36 11101102033 69 2017 11101
37 11101112001 3 2017 11101
38 11101112009 23 2017 11101
39 11101112011 78 2017 11101
40 11101112012 5 2017 11101
41 11101112013 61 2017 11101
42 11101121001 26 2017 11101
43 11101121002 41 2017 11101
44 11101121003 161 2017 11101
45 11101121004 81 2017 11101
46 11101121005 115 2017 11101
47 11101121006 110 2017 11101
48 11101121007 36 2017 11101
49 11101121008 31 2017 11101
50 11101122011 36 2017 11101
51 11101131001 67 2017 11101
52 11101131002 67 2017 11101
53 11101131003 93 2017 11101
54 11101131004 72 2017 11101
55 11101131005 42 2017 11101
56 11101131006 3 2017 11101
57 11101131007 41 2017 11101
58 11101132011 1 2017 11101
59 11101991999 20 2017 11101
194 11102012004 1 2017 11102
195 11102042003 4 2017 11102
196 11102052002 3 2017 11102
331 11201011001 47 2017 11201
332 11201011002 62 2017 11201
333 11201011003 83 2017 11201
334 11201012009 3 2017 11201
335 11201012013 2 2017 11201
336 11201012055 1 2017 11201
337 11201012067 1 2017 11201
338 11201012901 2 2017 11201
339 11201021001 8 2017 11201
340 11201022011 2 2017 11201
341 11201022057 1 2017 11201
342 11201032068 4 2017 11201
343 11201041001 12 2017 11201
344 11201041002 68 2017 11201
345 11201041003 36 2017 11201
346 11201042006 13 2017 11201
347 11201042007 3 2017 11201
348 11201052901 2 2017 11201
349 11201062044 35 2017 11201
350 11201071001 9 2017 11201
351 11201072901 3 2017 11201
486 11202011001 51 2017 11202
487 11202021001 15 2017 11202
488 11202022016 10 2017 11202
489 11202022020 14 2017 11202
490 11202032022 1 2017 11202
491 11202052021 2 2017 11202
492 11202052023 16 2017 11202
493 11202052901 1 2017 11202
494 11202991999 1 2017 11202
629 11203011001 13 2017 11203
630 11203012004 3 2017 11203
631 11203012005 1 2017 11203
632 11203012901 3 2017 11203
767 11301011001 87 2017 11301
768 11301012002 1 2017 11301
769 11301012003 1 2017 11301
770 11301012004 2 2017 11301


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_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 354820.7 2017 1101 191468 67936815240
01107 Alto Hospicio 301933.4 2017 1107 108375 32722034397
01401 Pozo Almonte 285981.8 2017 1401 15711 4493059532
01402 Camiña 262850.3 2017 1402 1250 328562901
01404 Huara 253968.5 2017 1404 2730 693334131
01405 Pica 313007.5 2017 1405 9296 2909717399
02101 Antofagasta 347580.2 2017 2101 361873 125779893517
02102 Mejillones 369770.7 2017 2102 13467 4979702302
02103 Sierra Gorda 403458.5 2017 2103 10186 4109628188
02104 Taltal 364539.1 2017 2104 13317 4854566842
02201 Calama 409671.3 2017 2201 165731 67895226712
02203 San Pedro de Atacama 426592.0 2017 2203 10996 4690805471
02301 Tocopilla 246615.3 2017 2301 25186 6211253937
02302 María Elena 466266.9 2017 2302 6457 3010685220
03101 Copiapó 330075.2 2017 3101 153937 50810778473
03102 Caldera 299314.8 2017 3102 17662 5286498241
03103 Tierra Amarilla 314643.9 2017 3103 14019 4410992711
03201 Chañaral 286389.3 2017 3201 12219 3499391196
03202 Diego de Almagro 336256.8 2017 3202 13925 4682376047
03301 Vallenar 304336.7 2017 3301 51917 15800246795
03302 Alto del Carmen 227130.4 2017 3302 5299 1203563833
03303 Freirina 253086.7 2017 3303 7041 1781983257
03304 Huasco 287406.6 2017 3304 10149 2916889629
04101 La Serena 270221.9 2017 4101 221054 59733627577
04102 Coquimbo 261852.6 2017 4102 227730 59631700074
04103 Andacollo 248209.3 2017 4103 11044 2741223967
04104 La Higuera 228356.8 2017 4104 4241 968461330
04105 Paiguano 205942.1 2017 4105 4497 926121774
04106 Vicuña 211431.9 2017 4106 27771 5871675449
04201 Illapel 238674.4 2017 4201 30848 7362627007
04202 Canela 207933.6 2017 4202 9093 1890740321
04203 Los Vilos 255200.4 2017 4203 21382 5456695139
04204 Salamanca 242879.5 2017 4204 29347 7127783272
04301 Ovalle 266522.9 2017 4301 111272 29656533187
04302 Combarbalá 210409.7 2017 4302 13322 2803077721
04303 Monte Patria 211907.9 2017 4303 30751 6516380780
04304 Punitaqui 194997.8 2017 4304 10956 2136395349
04305 Río Hurtado 182027.2 2017 4305 4278 778712384
05101 Valparaíso 298720.7 2017 5101 296655 88616992249
05102 Casablanca 312802.7 2017 5102 26867 8404070481
05103 Concón 318496.3 2017 5103 42152 13425257057
05105 Puchuncaví 288737.2 2017 5105 18546 5354920887
05107 Quintero 316659.1 2017 5107 31923 10108709691
05109 Viña del Mar 337006.1 2017 5109 334248 112643604611
05301 Los Andes 338182.5 2017 5301 66708 22559476922
05302 Calle Larga 245165.4 2017 5302 14832 3636293159
05303 Rinconada 281633.2 2017 5303 10207 2874630315
05304 San Esteban 220958.4 2017 5304 18855 4166170587
05401 La Ligua 229623.7 2017 5401 35390 8126381563
05402 Cabildo 249717.7 2017 5402 19388 4841527150

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)
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
11101 11101022031 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101022038 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011001 30 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011002 80 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011004 22 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011005 32 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011006 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032005 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101022003 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101022010 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101062023 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101062025 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072014 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072018 57 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072019 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072020 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011003 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101042024 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101042027 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052004 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011007 75 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101102011 10 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101102020 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101102033 69 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112001 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112009 23 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112011 78 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112012 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112013 61 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121001 26 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121002 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121003 161 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121004 81 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121005 115 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121006 110 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121007 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121008 31 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101122011 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131001 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131002 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032032 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032034 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032901 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101042022 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131007 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101132011 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101991999 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052008 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052014 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052901 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131003 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131004 72 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072035 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072036 8 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072037 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101082021 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101092007 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131005 42 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131006 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11102 11102012004 1 2017 NA NA NA NA NA NA
11102 11102042003 4 2017 NA NA NA NA NA NA
11102 11102052002 3 2017 NA NA NA NA NA NA
11201 11201011002 62 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201011003 83 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012009 3 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201011001 47 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201041002 68 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201041003 36 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201032068 4 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201041001 12 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012013 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012055 1 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201042006 13 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201042007 3 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012901 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201021001 8 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201022011 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201022057 1 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201072901 3 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201052901 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201062044 35 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201071001 9 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012067 1 2017 Aysén 297661.2 2017 11201 23959 7131665204
11202 11202032022 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202052023 16 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202052901 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202991999 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202052021 2 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202021001 15 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202022016 10 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202022020 14 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202011001 51 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11203 11203012004 3 2017 NA NA NA NA NA NA
11203 11203012005 1 2017 NA NA NA NA NA NA
11203 11203012901 3 2017 NA NA NA NA NA NA
11203 11203011001 13 2017 NA NA NA NA NA NA
11301 11301022009 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231
11301 11301022016 2 2017 Cochrane 314076.9 2017 11301 3490 1096128231
11301 11301032005 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231
11301 11301012901 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231


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
11101 11101022031 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101022038 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011001 30 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011002 80 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011004 22 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011005 32 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011006 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032005 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101022003 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101022010 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101062023 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101062025 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072014 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072018 57 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072019 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072020 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011003 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101042024 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101042027 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052004 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101011007 75 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101102011 10 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101102020 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101102033 69 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112001 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112009 23 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112011 78 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112012 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101112013 61 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121001 26 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121002 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121003 161 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121004 81 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121005 115 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121006 110 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121007 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101121008 31 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101122011 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131001 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131002 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032032 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032034 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101032901 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101042022 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131007 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101132011 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101991999 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052008 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052014 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101052901 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131003 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131004 72 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072035 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072036 8 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101072037 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101082021 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101092007 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131005 42 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11101 11101131006 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735
11102 11102012004 1 2017 NA NA NA NA NA NA
11102 11102042003 4 2017 NA NA NA NA NA NA
11102 11102052002 3 2017 NA NA NA NA NA NA
11201 11201011002 62 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201011003 83 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012009 3 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201011001 47 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201041002 68 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201041003 36 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201032068 4 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201041001 12 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012013 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012055 1 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201042006 13 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201042007 3 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012901 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201021001 8 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201022011 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201022057 1 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201072901 3 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201052901 2 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201062044 35 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201071001 9 2017 Aysén 297661.2 2017 11201 23959 7131665204
11201 11201012067 1 2017 Aysén 297661.2 2017 11201 23959 7131665204
11202 11202032022 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202052023 16 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202052901 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202991999 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202052021 2 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202021001 15 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202022016 10 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202022020 14 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11202 11202011001 51 2017 Cisnes 255244.8 2017 11202 6517 1663430085
11203 11203012004 3 2017 NA NA NA NA NA NA
11203 11203012005 1 2017 NA NA NA NA NA NA
11203 11203012901 3 2017 NA NA NA NA NA NA
11203 11203011001 13 2017 NA NA NA NA NA NA
11301 11301022009 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231
11301 11301022016 2 2017 Cochrane 314076.9 2017 11301 3490 1096128231
11301 11301032005 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231
11301 11301012901 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231


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
11101011001 11101 30 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 324 0.0056038 11101
11101011002 11101 80 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1672 0.0289183 11101
11101011003 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 499 0.0086305 11101
11101011004 11101 22 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 667 0.0115362 11101
11101011005 11101 32 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 977 0.0168979 11101
11101011006 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1595 0.0275866 11101
11101011007 11101 75 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2251 0.0389325 11101
11101022003 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 11 0.0001903 11101
11101022010 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101
11101022031 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 55 0.0009513 11101
11101022038 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 339 0.0058632 11101
11101032005 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101
11101032032 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 257 0.0044450 11101
11101032034 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 31 0.0005362 11101
11101032901 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 43 0.0007437 11101
11101042022 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 27 0.0004670 11101
11101042024 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 47 0.0008129 11101
11101042027 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 77 0.0013318 11101
11101052004 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 474 0.0081981 11101
11101052008 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 76 0.0013145 11101
11101052014 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101
11101052901 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 50 0.0008648 11101
11101062023 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101
11101062025 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 24 0.0004151 11101
11101072014 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 107 0.0018506 11101
11101072018 11101 57 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 806 0.0139403 11101
11101072019 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 102 0.0017642 11101
11101072020 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 190 0.0032862 11101
11101072035 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 109 0.0018852 11101
11101072036 11101 8 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 539 0.0093224 11101
11101072037 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 265 0.0045833 11101
11101082021 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 8 0.0001384 11101
11101092007 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 29 0.0005016 11101
11101102011 11101 10 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 143 0.0024733 11101
11101102020 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101
11101102033 11101 69 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 763 0.0131966 11101
11101112001 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 186 0.0032170 11101
11101112009 11101 23 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 198 0.0034245 11101
11101112011 11101 78 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 579 0.0100142 11101
11101112012 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101
11101112013 11101 61 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 615 0.0106368 11101
11101121001 11101 26 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 903 0.0156180 11101
11101121002 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3281 0.0567470 11101
11101121003 11101 161 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2413 0.0417344 11101
11101121004 11101 81 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3717 0.0642879 11101
11101121005 11101 115 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2462 0.0425819 11101
11101121006 11101 110 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2381 0.0411809 11101
11101121007 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3498 0.0605002 11101
11101121008 11101 31 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3334 0.0576637 11101
11101122011 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 206 0.0035629 11101
11101131001 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1906 0.0329655 11101
11101131002 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3237 0.0559860 11101
11101131003 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3439 0.0594797 11101
11101131004 11101 72 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3238 0.0560033 11101
11101131005 11101 42 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2580 0.0446228 11101
11101131006 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1524 0.0263586 11101
11101131007 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3756 0.0649625 11101
11101132011 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 44 0.0007610 11101
11101991999 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 301 0.0052060 11101
11102012004 11102 1 2017 NA NA NA NA NA NA 308 0.3615023 11102
11102042003 11102 4 2017 NA NA NA NA NA NA 244 0.2863850 11102
11102052002 11102 3 2017 NA NA NA NA NA NA 203 0.2382629 11102
11201011001 11201 47 2017 Aysén 297661.2 2017 11201 23959 7131665204 2035 0.0849368 11201
11201011002 11201 62 2017 Aysén 297661.2 2017 11201 23959 7131665204 3187 0.1330189 11201
11201011003 11201 83 2017 Aysén 297661.2 2017 11201 23959 7131665204 3870 0.1615259 11201
11201012009 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 52 0.0021704 11201
11201012013 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 35 0.0014608 11201
11201012055 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 148 0.0061772 11201
11201012067 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 98 0.0040903 11201
11201012901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 172 0.0071789 11201
11201021001 11201 8 2017 Aysén 297661.2 2017 11201 23959 7131665204 1561 0.0651530 11201
11201022011 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 32 0.0013356 11201
11201022057 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 58 0.0024208 11201
11201032068 11201 4 2017 Aysén 297661.2 2017 11201 23959 7131665204 149 0.0062190 11201
11201041001 11201 12 2017 Aysén 297661.2 2017 11201 23959 7131665204 2623 0.1094787 11201
11201041002 11201 68 2017 Aysén 297661.2 2017 11201 23959 7131665204 2692 0.1123586 11201
11201041003 11201 36 2017 Aysén 297661.2 2017 11201 23959 7131665204 3034 0.1266330 11201
11201042006 11201 13 2017 Aysén 297661.2 2017 11201 23959 7131665204 244 0.0101841 11201
11201042007 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 54 0.0022539 11201
11201052901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 14 0.0005843 11201
11201062044 11201 35 2017 Aysén 297661.2 2017 11201 23959 7131665204 541 0.0225802 11201
11201071001 11201 9 2017 Aysén 297661.2 2017 11201 23959 7131665204 1239 0.0517133 11201
11201072901 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 208 0.0086815 11201
11202011001 11202 51 2017 Cisnes 255244.8 2017 11202 6517 1663430085 2558 0.3925119 11202
11202021001 11202 15 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1431 0.2195796 11202
11202022016 11202 10 2017 Cisnes 255244.8 2017 11202 6517 1663430085 280 0.0429646 11202
11202022020 11202 14 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1037 0.1591223 11202
11202032022 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 6 0.0009207 11202
11202052021 11202 2 2017 Cisnes 255244.8 2017 11202 6517 1663430085 239 0.0366733 11202
11202052023 11202 16 2017 Cisnes 255244.8 2017 11202 6517 1663430085 170 0.0260856 11202
11202052901 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 40 0.0061378 11202
11202991999 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 125 0.0191806 11202
11203011001 11203 13 2017 NA NA NA NA NA NA 1329 0.7211069 11203
11203012004 11203 3 2017 NA NA NA NA NA NA 32 0.0173630 11203
11203012005 11203 1 2017 NA NA NA NA NA NA 31 0.0168204 11203
11203012901 11203 3 2017 NA NA NA NA NA NA 75 0.0406945 11203
11301011001 11301 87 2017 Cochrane 314076.9 2017 11301 3490 1096128231 2789 0.7991404 11301
11301012002 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 26 0.0074499 11301
11301012003 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 78 0.0223496 11301
11301012004 11301 2 2017 Cochrane 314076.9 2017 11301 3490 1096128231 76 0.0217765 11301


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
11101011001 11101 30 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 324 0.0056038 11101 97924642
11101011002 11101 80 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1672 0.0289183 11101 505339508
11101011003 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 499 0.0086305 11101 150816037
11101011004 11101 22 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 667 0.0115362 11101 201591778
11101011005 11101 32 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 977 0.0168979 11101 295285107
11101011006 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1595 0.0275866 11101 482067294
11101011007 11101 75 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2251 0.0389325 11101 680334470
11101022003 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 11 0.0001903 11101 3324602
11101022010 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101 16018537
11101022031 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 55 0.0009513 11101 16623010
11101022038 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 339 0.0058632 11101 102458190
11101032005 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101 16018537
11101032032 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 257 0.0044450 11101 77674793
11101032034 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 31 0.0005362 11101 9369333
11101032901 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 43 0.0007437 11101 12996172
11101042022 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 27 0.0004670 11101 8160387
11101042024 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 47 0.0008129 11101 14205118
11101042027 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 77 0.0013318 11101 23272214
11101052004 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 474 0.0081981 11101 143260124
11101052008 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 76 0.0013145 11101 22969978
11101052014 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101 75559137
11101052901 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 50 0.0008648 11101 15111827
11101062023 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101 16320774
11101062025 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 24 0.0004151 11101 7253677
11101072014 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 107 0.0018506 11101 32339311
11101072018 11101 57 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 806 0.0139403 11101 243602658
11101072019 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 102 0.0017642 11101 30828128
11101072020 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 190 0.0032862 11101 57424944
11101072035 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 109 0.0018852 11101 32943784
11101072036 11101 8 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 539 0.0093224 11101 162905499
11101072037 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 265 0.0045833 11101 80092685
11101082021 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 8 0.0001384 11101 2417892
11101092007 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 29 0.0005016 11101 8764860
11101102011 11101 10 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 143 0.0024733 11101 43219826
11101102020 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101 75559137
11101102033 11101 69 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 763 0.0131966 11101 230606486
11101112001 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 186 0.0032170 11101 56215998
11101112009 11101 23 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 198 0.0034245 11101 59842837
11101112011 11101 78 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 579 0.0100142 11101 174994961
11101112012 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101 16320774
11101112013 11101 61 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 615 0.0106368 11101 185875477
11101121001 11101 26 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 903 0.0156180 11101 272919603
11101121002 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3281 0.0567470 11101 991638114
11101121003 11101 161 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2413 0.0417344 11101 729296790
11101121004 11101 81 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3717 0.0642879 11101 1123413249
11101121005 11101 115 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2462 0.0425819 11101 744106381
11101121006 11101 110 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2381 0.0411809 11101 719625221
11101121007 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3498 0.0605002 11101 1057223445
11101121008 11101 31 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3334 0.0576637 11101 1007656651
11101122011 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 206 0.0035629 11101 62260729
11101131001 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1906 0.0329655 11101 576062861
11101131002 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3237 0.0559860 11101 978339706
11101131003 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3439 0.0594797 11101 1039391489
11101131004 11101 72 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3238 0.0560033 11101 978641943
11101131005 11101 42 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2580 0.0446228 11101 779770294
11101131006 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1524 0.0263586 11101 460608499
11101131007 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3756 0.0649625 11101 1135200474
11101132011 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 44 0.0007610 11101 13298408
11101991999 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 301 0.0052060 11101 90973201
11102012004 11102 1 2017 NA NA NA NA NA NA 308 0.3615023 11102 NA
11102042003 11102 4 2017 NA NA NA NA NA NA 244 0.2863850 11102 NA
11102052002 11102 3 2017 NA NA NA NA NA NA 203 0.2382629 11102 NA
11201011001 11201 47 2017 Aysén 297661.2 2017 11201 23959 7131665204 2035 0.0849368 11201 605740586
11201011002 11201 62 2017 Aysén 297661.2 2017 11201 23959 7131665204 3187 0.1330189 11201 948646313
11201011003 11201 83 2017 Aysén 297661.2 2017 11201 23959 7131665204 3870 0.1615259 11201 1151948927
11201012009 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 52 0.0021704 11201 15478384
11201012013 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 35 0.0014608 11201 10418143
11201012055 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 148 0.0061772 11201 44053861
11201012067 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 98 0.0040903 11201 29170800
11201012901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 172 0.0071789 11201 51197730
11201021001 11201 8 2017 Aysén 297661.2 2017 11201 23959 7131665204 1561 0.0651530 11201 464649167
11201022011 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 32 0.0013356 11201 9525159
11201022057 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 58 0.0024208 11201 17264351
11201032068 11201 4 2017 Aysén 297661.2 2017 11201 23959 7131665204 149 0.0062190 11201 44351522
11201041001 11201 12 2017 Aysén 297661.2 2017 11201 23959 7131665204 2623 0.1094787 11201 780765384
11201041002 11201 68 2017 Aysén 297661.2 2017 11201 23959 7131665204 2692 0.1123586 11201 801304008
11201041003 11201 36 2017 Aysén 297661.2 2017 11201 23959 7131665204 3034 0.1266330 11201 903104146
11201042006 11201 13 2017 Aysén 297661.2 2017 11201 23959 7131665204 244 0.0101841 11201 72629338
11201042007 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 54 0.0022539 11201 16073706
11201052901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 14 0.0005843 11201 4167257
11201062044 11201 35 2017 Aysén 297661.2 2017 11201 23959 7131665204 541 0.0225802 11201 161034721
11201071001 11201 9 2017 Aysén 297661.2 2017 11201 23959 7131665204 1239 0.0517133 11201 368802253
11201072901 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 208 0.0086815 11201 61913534
11202011001 11202 51 2017 Cisnes 255244.8 2017 11202 6517 1663430085 2558 0.3925119 11202 652916090
11202021001 11202 15 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1431 0.2195796 11202 365255248
11202022016 11202 10 2017 Cisnes 255244.8 2017 11202 6517 1663430085 280 0.0429646 11202 71468532
11202022020 11202 14 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1037 0.1591223 11202 264688814
11202032022 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 6 0.0009207 11202 1531469
11202052021 11202 2 2017 Cisnes 255244.8 2017 11202 6517 1663430085 239 0.0366733 11202 61003497
11202052023 11202 16 2017 Cisnes 255244.8 2017 11202 6517 1663430085 170 0.0260856 11202 43391609
11202052901 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 40 0.0061378 11202 10209790
11202991999 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 125 0.0191806 11202 31905595
11203011001 11203 13 2017 NA NA NA NA NA NA 1329 0.7211069 11203 NA
11203012004 11203 3 2017 NA NA NA NA NA NA 32 0.0173630 11203 NA
11203012005 11203 1 2017 NA NA NA NA NA NA 31 0.0168204 11203 NA
11203012901 11203 3 2017 NA NA NA NA NA NA 75 0.0406945 11203 NA
11301011001 11301 87 2017 Cochrane 314076.9 2017 11301 3490 1096128231 2789 0.7991404 11301 875960355
11301012002 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 26 0.0074499 11301 8165998
11301012003 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 78 0.0223496 11301 24497995
11301012004 11301 2 2017 Cochrane 314076.9 2017 11301 3490 1096128231 76 0.0217765 11301 23869841

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

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 
## -651509854  -69724042  -56531592   -5827010  739477894 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 59152192   24815637   2.384   0.0187 *  
## Freq.x       8209034     669460  12.262   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 226300000 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.5561, Adjusted R-squared:  0.5525 
## F-statistic: 150.4 on 1 and 120 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

\[ \hat Y = \beta_0 + \beta_1 X^2 \]

linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^2), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -651509854  -69724042  -56531592   -5827010  739477894 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 59152192   24815637   2.384   0.0187 *  
## Freq.x       8209034     669460  12.262   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 226300000 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.5561, Adjusted R-squared:  0.5525 
## F-statistic: 150.4 on 1 and 120 DF,  p-value: < 2.2e-16

8.2 Modelo cúbico

\[ \hat Y = \beta_0 + \beta_1 X^3 \]

linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^3), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -651509854  -69724042  -56531592   -5827010  739477894 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 59152192   24815637   2.384   0.0187 *  
## Freq.x       8209034     669460  12.262   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 226300000 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.5561, Adjusted R-squared:  0.5525 
## F-statistic: 150.4 on 1 and 120 DF,  p-value: < 2.2e-16

8.3 Modelo logarítmico

\[ \hat Y = \beta_0 + \beta_1 ln X \]

linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = multi_pob ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -450947005 -117900754  -18067584   83416082  611725132 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -68182944   30929282  -2.204   0.0294 *  
## log(Freq.x) 159323227   12535054  12.710   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 221700000 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.5738, Adjusted R-squared:  0.5702 
## F-statistic: 161.5 on 1 and 120 DF,  p-value: < 2.2e-16

8.4 Modelo exponencial

\[ \hat Y = \beta_0 + \beta_1 e^X \]

No es aplicable sin una transformación pues los valores elevados a \(e\) de Freq.x tienden a infinito.

8.5 Modelo con raíz cuadrada

\[ \hat Y = \beta_0 + \beta_1 \sqrt {X} \]

linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = multi_pob ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -541274423  -78148701   -3528161   18477712  641472905 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -93006102   29733374  -3.128  0.00221 ** 
## sqrt(Freq.x)  91632405    6501054  14.095  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 208400000 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6203 
## F-statistic: 198.7 on 1 and 120 DF,  p-value: < 2.2e-16

8.6 Modelo raíz-raíz

\[ \hat Y = {\beta_0}^2 + 2 \beta_0 \beta_1 \sqrt{X}+ \beta_1^2 X \]

linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = sqrt(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13584.8  -2608.9   -903.5   1827.3  16718.1 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    1163.3      777.1   1.497    0.137    
## sqrt(Freq.x)   2904.3      169.9  17.092   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5448 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.7088, Adjusted R-squared:  0.7064 
## F-statistic: 292.2 on 1 and 120 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

\[ \hat Y = e^{\beta_0 + \beta_1 \sqrt{X}} \]

linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.31438 -0.64062 -0.05497  0.72751  3.00989 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  16.03421    0.15351  104.45   <2e-16 ***
## sqrt(Freq.x)  0.52190    0.03356   15.55   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.076 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.6683, Adjusted R-squared:  0.6655 
## F-statistic: 241.8 on 1 and 120 DF,  p-value: < 2.2e-16

8.8 Modelo raíz-log

\[ \hat Y = {\beta_0}^2 + 2 \beta_0 \beta_1 \ln{X}+ \beta_1^2 ln^2X \]

linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = sqrt(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -12511.6  -3299.4    167.5   2509.9  14126.5 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1558.3      761.7   2.046    0.043 *  
## log(Freq.x)   5258.5      308.7  17.034   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5461 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.7074, Adjusted R-squared:  0.705 
## F-statistic: 290.2 on 1 and 120 DF,  p-value: < 2.2e-16

8.9 Modelo log-log

\[ \hat Y = e^{\beta_0+\beta_1 ln{X}} \]

linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.10835 -0.68027  0.02081  0.61873  2.85477 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.98455    0.12746  125.41   <2e-16 ***
## log(Freq.x)  1.00922    0.05166   19.54   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9138 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.7608, Adjusted R-squared:  0.7588 
## F-statistic: 381.7 on 1 and 120 DF,  p-value: < 2.2e-16

9 Modelo log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.7588).

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_01$Freq.x), y=log(h_y_m_comuna_corr_01$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_01)
summary(linearMod) 
## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.10835 -0.68027  0.02081  0.61873  2.85477 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.98455    0.12746  125.41   <2e-16 ***
## log(Freq.x)  1.00922    0.05166   19.54   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9138 on 120 degrees of freedom
##   (12 observations deleted due to missingness)
## Multiple R-squared:  0.7608, Adjusted R-squared:  0.7588 
## F-statistic: 381.7 on 1 and 120 DF,  p-value: < 2.2e-16
ggplot(h_y_m_comuna_corr_01, 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


\[ \hat Y = e^{15.98455+1.00922 \cdot ln{X}} \]


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_01$est_ing <- exp(15.98455+1.00922 * log(h_y_m_comuna_corr_01$Freq.x)) 

r3_100 <- h_y_m_comuna_corr_01[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
11101011001 11101 30 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 324 0.0056038 11101 97924642 270858316
11101011002 11101 80 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1672 0.0289183 11101 505339508 728850301
11101011003 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 499 0.0086305 11101 150816037 179898422
11101011004 11101 22 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 667 0.0115362 11101 201591778 198062236
11101011005 11101 32 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 977 0.0168979 11101 295285107 289087506
11101011006 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1595 0.0275866 11101 482067294 848465567
11101011007 11101 75 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2251 0.0389325 11101 680334470 682890685
11101022003 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 11 0.0001903 11101 3324602 17611946
11101022010 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101 16018537 17611946
11101022031 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 55 0.0009513 11101 16623010 8749875
11101022038 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 339 0.0058632 11101 102458190 26516865
11101032005 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101 16018537 8749875
11101032032 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 257 0.0044450 11101 77674793 44403415
11101032034 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 31 0.0005362 11101 9369333 8749875
11101032901 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 43 0.0007437 11101 12996172 17611946
11101042022 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 27 0.0004670 11101 8160387 26516865
11101042024 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 47 0.0008129 11101 14205118 26516865
11101042027 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 77 0.0013318 11101 23272214 53373744
11101052004 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 474 0.0081981 11101 143260124 53373744
11101052008 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 76 0.0013145 11101 22969978 44403415
11101052014 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101 75559137 53373744
11101052901 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 50 0.0008648 11101 15111827 26516865
11101062023 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101 16320774 8749875
11101062025 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 24 0.0004151 11101 7253677 17611946
11101072014 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 107 0.0018506 11101 32339311 35449723
11101072018 11101 57 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 806 0.0139403 11101 243602658 517685359
11101072019 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 102 0.0017642 11101 30828128 62357932
11101072020 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 190 0.0032862 11101 57424944 35449723
11101072035 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 109 0.0018852 11101 32943784 26516865
11101072036 11101 8 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 539 0.0093224 11101 162905499 71354002
11101072037 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 265 0.0045833 11101 80092685 62357932
11101082021 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 8 0.0001384 11101 2417892 8749875
11101092007 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 29 0.0005016 11101 8764860 8749875
11101102011 11101 10 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 143 0.0024733 11101 43219826 89376195
11101102020 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101 75559137 179898422
11101102033 11101 69 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 763 0.0131966 11101 230606486 627776624
11101112001 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 186 0.0032170 11101 56215998 26516865
11101112009 11101 23 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 198 0.0034245 11101 59842837 207149947
11101112011 11101 78 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 579 0.0100142 11101 174994961 710463180
11101112012 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101 16320774 44403415
11101112013 11101 61 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 615 0.0106368 11101 185875477 554360703
11101121001 11101 26 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 903 0.0156180 11101 272919603 234434359
11101121002 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3281 0.0567470 11101 991638114 371240701
11101121003 11101 161 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2413 0.0417344 11101 729296790 1476300175
11101121004 11101 81 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3717 0.0642879 11101 1123413249 738045457
11101121005 11101 115 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2462 0.0425819 11101 744106381 1051233846
11101121006 11101 110 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2381 0.0411809 11101 719625221 1005116000
11101121007 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3498 0.0605002 11101 1057223445 325576815
11101121008 11101 31 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3334 0.0576637 11101 1007656651 279971555
11101122011 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 206 0.0035629 11101 62260729 325576815
11101131001 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1906 0.0329655 11101 576062861 609414907
11101131002 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3237 0.0559860 11101 978339706 609414907
11101131003 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3439 0.0594797 11101 1039391489 848465567
11101131004 11101 72 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3238 0.0560033 11101 978641943 655328360
11101131005 11101 42 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2580 0.0446228 11101 779770294 380379856
11101131006 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1524 0.0263586 11101 460608499 26516865
11101131007 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3756 0.0649625 11101 1135200474 371240701
11101132011 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 44 0.0007610 11101 13298408 8749875
11101991999 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 301 0.0052060 11101 90973201 179898422
11102012004 11102 1 2017 NA NA NA NA NA NA 308 0.3615023 11102 NA 8749875
11102042003 11102 4 2017 NA NA NA NA NA NA 244 0.2863850 11102 NA 35449723
11102052002 11102 3 2017 NA NA NA NA NA NA 203 0.2382629 11102 NA 26516865
11201011001 11201 47 2017 Aysén 297661.2 2017 11201 23959 7131665204 2035 0.0849368 11201 605740586 426104834
11201011002 11201 62 2017 Aysén 297661.2 2017 11201 23959 7131665204 3187 0.1330189 11201 948646313 563533063
11201011003 11201 83 2017 Aysén 297661.2 2017 11201 23959 7131665204 3870 0.1615259 11201 1151948927 756438898
11201012009 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 52 0.0021704 11201 15478384 26516865
11201012013 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 35 0.0014608 11201 10418143 17611946
11201012055 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 148 0.0061772 11201 44053861 8749875
11201012067 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 98 0.0040903 11201 29170800 8749875
11201012901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 172 0.0071789 11201 51197730 17611946
11201021001 11201 8 2017 Aysén 297661.2 2017 11201 23959 7131665204 1561 0.0651530 11201 464649167 71354002
11201022011 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 32 0.0013356 11201 9525159 17611946
11201022057 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 58 0.0024208 11201 17264351 8749875
11201032068 11201 4 2017 Aysén 297661.2 2017 11201 23959 7131665204 149 0.0062190 11201 44351522 35449723
11201041001 11201 12 2017 Aysén 297661.2 2017 11201 23959 7131665204 2623 0.1094787 11201 780765384 107431876
11201041002 11201 68 2017 Aysén 297661.2 2017 11201 23959 7131665204 2692 0.1123586 11201 801304008 618595143
11201041003 11201 36 2017 Aysén 297661.2 2017 11201 23959 7131665204 3034 0.1266330 11201 903104146 325576815
11201042006 11201 13 2017 Aysén 297661.2 2017 11201 23959 7131665204 244 0.0101841 11201 72629338 116470455
11201042007 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 54 0.0022539 11201 16073706 26516865
11201052901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 14 0.0005843 11201 4167257 17611946
11201062044 11201 35 2017 Aysén 297661.2 2017 11201 23959 7131665204 541 0.0225802 11201 161034721 316450811
11201071001 11201 9 2017 Aysén 297661.2 2017 11201 23959 7131665204 1239 0.0517133 11201 368802253 80360473
11201072901 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 208 0.0086815 11201 61913534 26516865
11202011001 11202 51 2017 Cisnes 255244.8 2017 11202 6517 1663430085 2558 0.3925119 11202 652916090 462717403
11202021001 11202 15 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1431 0.2195796 11202 365255248 134566415
11202022016 11202 10 2017 Cisnes 255244.8 2017 11202 6517 1663430085 280 0.0429646 11202 71468532 89376195
11202022020 11202 14 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1037 0.1591223 11202 264688814 125515453
11202032022 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 6 0.0009207 11202 1531469 8749875
11202052021 11202 2 2017 Cisnes 255244.8 2017 11202 6517 1663430085 239 0.0366733 11202 61003497 17611946
11202052023 11202 16 2017 Cisnes 255244.8 2017 11202 6517 1663430085 170 0.0260856 11202 43391609 143622946
11202052901 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 40 0.0061378 11202 10209790 8749875
11202991999 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 125 0.0191806 11202 31905595 8749875
11203011001 11203 13 2017 NA NA NA NA NA NA 1329 0.7211069 11203 NA 116470455
11203012004 11203 3 2017 NA NA NA NA NA NA 32 0.0173630 11203 NA 26516865
11203012005 11203 1 2017 NA NA NA NA NA NA 31 0.0168204 11203 NA 8749875
11203012901 11203 3 2017 NA NA NA NA NA NA 75 0.0406945 11203 NA 26516865
11301011001 11301 87 2017 Cochrane 314076.9 2017 11301 3490 1096128231 2789 0.7991404 11301 875960355 793237945
11301012002 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 26 0.0074499 11301 8165998 8749875
11301012003 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 78 0.0223496 11301 24497995 8749875
11301012004 11301 2 2017 Cochrane 314076.9 2017 11301 3490 1096128231 76 0.0217765 11301 23869841 17611946


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_01$ing_medio_zona <- h_y_m_comuna_corr_01$est_ing  /( h_y_m_comuna_corr_01$personas  * h_y_m_comuna_corr_01$p_poblacional)

r3_100 <- h_y_m_comuna_corr_01[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
11101011001 11101 30 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 324 0.0056038 11101 97924642 270858316 835982.46
11101011002 11101 80 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1672 0.0289183 11101 505339508 728850301 435915.25
11101011003 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 499 0.0086305 11101 150816037 179898422 360517.88
11101011004 11101 22 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 667 0.0115362 11101 201591778 198062236 296944.88
11101011005 11101 32 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 977 0.0168979 11101 295285107 289087506 295893.05
11101011006 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1595 0.0275866 11101 482067294 848465567 531953.33
11101011007 11101 75 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2251 0.0389325 11101 680334470 682890685 303372.14
11101022003 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 11 0.0001903 11101 3324602 17611946 1601086.03
11101022010 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101 16018537 17611946 332300.87
11101022031 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 55 0.0009513 11101 16623010 8749875 159088.64
11101022038 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 339 0.0058632 11101 102458190 26516865 78220.84
11101032005 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 53 0.0009167 11101 16018537 8749875 165091.99
11101032032 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 257 0.0044450 11101 77674793 44403415 172775.93
11101032034 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 31 0.0005362 11101 9369333 8749875 282254.04
11101032901 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 43 0.0007437 11101 12996172 17611946 409580.15
11101042022 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 27 0.0004670 11101 8160387 26516865 982106.10
11101042024 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 47 0.0008129 11101 14205118 26516865 564188.61
11101042027 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 77 0.0013318 11101 23272214 53373744 693165.50
11101052004 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 474 0.0081981 11101 143260124 53373744 112602.83
11101052008 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 76 0.0013145 11101 22969978 44403415 584255.46
11101052014 11101 6 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101 75559137 53373744 213494.97
11101052901 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 50 0.0008648 11101 15111827 26516865 530337.29
11101062023 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101 16320774 8749875 162034.73
11101062025 11101 2 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 24 0.0004151 11101 7253677 17611946 733831.10
11101072014 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 107 0.0018506 11101 32339311 35449723 331305.82
11101072018 11101 57 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 806 0.0139403 11101 243602658 517685359 642289.53
11101072019 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 102 0.0017642 11101 30828128 62357932 611352.28
11101072020 11101 4 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 190 0.0032862 11101 57424944 35449723 186577.49
11101072035 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 109 0.0018852 11101 32943784 26516865 243273.99
11101072036 11101 8 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 539 0.0093224 11101 162905499 71354002 132382.19
11101072037 11101 7 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 265 0.0045833 11101 80092685 62357932 235312.95
11101082021 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 8 0.0001384 11101 2417892 8749875 1093734.41
11101092007 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 29 0.0005016 11101 8764860 8749875 301719.84
11101102011 11101 10 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 143 0.0024733 11101 43219826 89376195 625008.36
11101102020 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 250 0.0043239 11101 75559137 179898422 719593.69
11101102033 11101 69 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 763 0.0131966 11101 230606486 627776624 822774.08
11101112001 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 186 0.0032170 11101 56215998 26516865 142563.79
11101112009 11101 23 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 198 0.0034245 11101 59842837 207149947 1046211.86
11101112011 11101 78 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 579 0.0100142 11101 174994961 710463180 1227052.13
11101112012 11101 5 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 54 0.0009340 11101 16320774 44403415 822285.46
11101112013 11101 61 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 615 0.0106368 11101 185875477 554360703 901399.52
11101121001 11101 26 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 903 0.0156180 11101 272919603 234434359 259617.23
11101121002 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3281 0.0567470 11101 991638114 371240701 113148.64
11101121003 11101 161 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2413 0.0417344 11101 729296790 1476300175 611811.10
11101121004 11101 81 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3717 0.0642879 11101 1123413249 738045457 198559.45
11101121005 11101 115 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2462 0.0425819 11101 744106381 1051233846 426983.69
11101121006 11101 110 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2381 0.0411809 11101 719625221 1005116000 422140.28
11101121007 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3498 0.0605002 11101 1057223445 325576815 93075.13
11101121008 11101 31 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3334 0.0576637 11101 1007656651 279971555 83974.67
11101122011 11101 36 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 206 0.0035629 11101 62260729 325576815 1580469.98
11101131001 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1906 0.0329655 11101 576062861 609414907 319735.00
11101131002 11101 67 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3237 0.0559860 11101 978339706 609414907 188265.34
11101131003 11101 93 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3439 0.0594797 11101 1039391489 848465567 246718.69
11101131004 11101 72 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3238 0.0560033 11101 978641943 655328360 202386.77
11101131005 11101 42 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 2580 0.0446228 11101 779770294 380379856 147434.05
11101131006 11101 3 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 1524 0.0263586 11101 460608499 26516865 17399.52
11101131007 11101 41 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 3756 0.0649625 11101 1135200474 371240701 98839.38
11101132011 11101 1 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 44 0.0007610 11101 13298408 8749875 198860.80
11101991999 11101 20 2017 Coyhaique 302236.5 2017 11101 57818 17474712735 301 0.0052060 11101 90973201 179898422 597669.17
11102012004 11102 1 2017 NA NA NA NA NA NA 308 0.3615023 11102 NA 8749875 NA
11102042003 11102 4 2017 NA NA NA NA NA NA 244 0.2863850 11102 NA 35449723 NA
11102052002 11102 3 2017 NA NA NA NA NA NA 203 0.2382629 11102 NA 26516865 NA
11201011001 11201 47 2017 Aysén 297661.2 2017 11201 23959 7131665204 2035 0.0849368 11201 605740586 426104834 209388.12
11201011002 11201 62 2017 Aysén 297661.2 2017 11201 23959 7131665204 3187 0.1330189 11201 948646313 563533063 176822.42
11201011003 11201 83 2017 Aysén 297661.2 2017 11201 23959 7131665204 3870 0.1615259 11201 1151948927 756438898 195462.25
11201012009 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 52 0.0021704 11201 15478384 26516865 509939.71
11201012013 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 35 0.0014608 11201 10418143 17611946 503198.47
11201012055 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 148 0.0061772 11201 44053861 8749875 59120.78
11201012067 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 98 0.0040903 11201 29170800 8749875 89284.44
11201012901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 172 0.0071789 11201 51197730 17611946 102395.04
11201021001 11201 8 2017 Aysén 297661.2 2017 11201 23959 7131665204 1561 0.0651530 11201 464649167 71354002 45710.44
11201022011 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 32 0.0013356 11201 9525159 17611946 550373.32
11201022057 11201 1 2017 Aysén 297661.2 2017 11201 23959 7131665204 58 0.0024208 11201 17264351 8749875 150859.92
11201032068 11201 4 2017 Aysén 297661.2 2017 11201 23959 7131665204 149 0.0062190 11201 44351522 35449723 237917.60
11201041001 11201 12 2017 Aysén 297661.2 2017 11201 23959 7131665204 2623 0.1094787 11201 780765384 107431876 40957.63
11201041002 11201 68 2017 Aysén 297661.2 2017 11201 23959 7131665204 2692 0.1123586 11201 801304008 618595143 229790.17
11201041003 11201 36 2017 Aysén 297661.2 2017 11201 23959 7131665204 3034 0.1266330 11201 903104146 325576815 107309.43
11201042006 11201 13 2017 Aysén 297661.2 2017 11201 23959 7131665204 244 0.0101841 11201 72629338 116470455 477337.93
11201042007 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 54 0.0022539 11201 16073706 26516865 491053.05
11201052901 11201 2 2017 Aysén 297661.2 2017 11201 23959 7131665204 14 0.0005843 11201 4167257 17611946 1257996.17
11201062044 11201 35 2017 Aysén 297661.2 2017 11201 23959 7131665204 541 0.0225802 11201 161034721 316450811 584936.80
11201071001 11201 9 2017 Aysén 297661.2 2017 11201 23959 7131665204 1239 0.0517133 11201 368802253 80360473 64859.14
11201072901 11201 3 2017 Aysén 297661.2 2017 11201 23959 7131665204 208 0.0086815 11201 61913534 26516865 127484.93
11202011001 11202 51 2017 Cisnes 255244.8 2017 11202 6517 1663430085 2558 0.3925119 11202 652916090 462717403 180890.31
11202021001 11202 15 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1431 0.2195796 11202 365255248 134566415 94036.63
11202022016 11202 10 2017 Cisnes 255244.8 2017 11202 6517 1663430085 280 0.0429646 11202 71468532 89376195 319200.70
11202022020 11202 14 2017 Cisnes 255244.8 2017 11202 6517 1663430085 1037 0.1591223 11202 264688814 125515453 121037.08
11202032022 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 6 0.0009207 11202 1531469 8749875 1458312.54
11202052021 11202 2 2017 Cisnes 255244.8 2017 11202 6517 1663430085 239 0.0366733 11202 61003497 17611946 73690.15
11202052023 11202 16 2017 Cisnes 255244.8 2017 11202 6517 1663430085 170 0.0260856 11202 43391609 143622946 844840.86
11202052901 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 40 0.0061378 11202 10209790 8749875 218746.88
11202991999 11202 1 2017 Cisnes 255244.8 2017 11202 6517 1663430085 125 0.0191806 11202 31905595 8749875 69999.00
11203011001 11203 13 2017 NA NA NA NA NA NA 1329 0.7211069 11203 NA 116470455 NA
11203012004 11203 3 2017 NA NA NA NA NA NA 32 0.0173630 11203 NA 26516865 NA
11203012005 11203 1 2017 NA NA NA NA NA NA 31 0.0168204 11203 NA 8749875 NA
11203012901 11203 3 2017 NA NA NA NA NA NA 75 0.0406945 11203 NA 26516865 NA
11301011001 11301 87 2017 Cochrane 314076.9 2017 11301 3490 1096128231 2789 0.7991404 11301 875960355 793237945 284416.62
11301012002 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 26 0.0074499 11301 8165998 8749875 336533.66
11301012003 11301 1 2017 Cochrane 314076.9 2017 11301 3490 1096128231 78 0.0223496 11301 24497995 8749875 112177.89
11301012004 11301 2 2017 Cochrane 314076.9 2017 11301 3490 1096128231 76 0.0217765 11301 23869841 17611946 231736.14


Guardamos:

saveRDS(h_y_m_comuna_corr_01, "casen_censo_region_11.rds")