Expansión de la CASEN sobre el CENSO (Región 06)

DataIntelligence

Abstract

Expandiremos los ingresos promedios comunales obtenidos de la CASEN sobre la categoría de respuesta: “Parquet, piso flotante, cerámico, madera, alfombra, flexit, cubrepiso u otro similar, sobre radier o vigas de madera” del campo P03C del CENSO de viviendas, que fue la categoría de respuesta que más alto correlaciona con los ingresos expandidos (obtenidos de la multiplicación del ingreso promedio y los habitantes), ambos a nivel comunal.

Haremos el análisis sobre la región 06.

Ensayaremos diferentes modelos dentro del análisis de regresión cuya variable independiente será: “frecuencia de población que posee la variable Censal respecto a la zona” y la dependiente: “ingreso expandido por zona”

Lo anterior para elegir el que posea el mayor coeficiente de determinación y así contruir una tabla de valores predichos.

1 Variable CENSO

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

1.1 Lectura y filtrado de la tabla censal de viviendas

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

tabla_con_clave <- readRDS("../censo_viviendas_con_clave_17.rds")
r3_100 <- tabla_con_clave[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

REGION	PROVINCIA	COMUNA	DC	AREA	ZC_LOC	ID_ZONA_LOC	NVIV	P01	P02	P03A	P03B	P03C	P04	P05	CANT_HOG	CANT_PER	REGION_15R	PROVINCIA_15R	COMUNA_15R	clave
15	152	15202	1	2	6	13225	1	3	1	5	3	5	1	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	2	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	3	1	1	5	3	5	2	3	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	4	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	5	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	6	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	7	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	8	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	9	3	1	5	3	5	1	4	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	10	1	1	5	3	4	1	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	11	1	2	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	12	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	13	1	1	5	3	4	1	4	1	3	15	152	15202	15202012006
15	152	15202	1	2	6	13225	14	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	15	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	16	1	1	5	3	5	1	3	1	3	15	152	15202	15202012006
15	152	15202	1	2	6	13225	17	1	1	5	3	5	2	4	1	8	15	152	15202	15202012006
15	152	15202	1	2	6	13225	18	3	1	5	3	5	1	1	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	19	3	1	5	3	5	1	3	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	20	1	1	5	3	5	2	1	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	21	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	22	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	23	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	24	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	25	1	1	5	3	5	1	4	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	26	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	27	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	28	3	1	5	3	5	1	4	1	5	15	152	15202	15202012006
15	152	15202	1	2	6	13225	29	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	30	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	31	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	32	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	33	1	1	5	3	5	3	4	1	4	15	152	15202	15202012006
15	152	15202	1	2	6	13225	34	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	35	3	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	36	1	1	5	3	5	3	2	1	9	15	152	15202	15202012006
15	152	15202	1	2	6	13225	37	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	38	1	1	5	3	5	99	4	1	1	15	152	15202	15202012006
15	152	15202	1	2	6	13225	39	1	1	5	3	5	1	4	1	2	15	152	15202	15202012006
15	152	15202	1	2	6	13225	40	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	41	1	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	42	3	3	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	43	3	1	5	3	5	2	1	1	5	15	152	15202	15202012006
15	152	15202	1	2	6	13225	44	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	6	13225	45	1	4	98	98	98	98	98	0	0	15	152	15202	15202012006
15	152	15202	1	2	8	13910	1	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	2	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	3	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	4	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	5	3	1	5	3	5	2	3	1	3	15	152	15202	15202012008
15	152	15202	1	2	8	13910	6	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	7	1	1	5	99	5	2	4	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	8	3	1	5	3	5	3	3	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	9	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	10	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	11	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	12	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	13	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	14	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	15	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	16	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	17	3	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	18	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	19	3	1	99	99	99	99	99	1	1	15	152	15202	15202012008
15	152	15202	1	2	8	13910	20	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	21	1	1	5	3	5	1	4	1	2	15	152	15202	15202012008
15	152	15202	1	2	8	13910	22	3	1	5	3	5	2	4	1	1	15	152	15202	15202012008
15	152	15202	1	2	8	13910	23	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	24	3	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	25	3	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	26	1	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	27	1	4	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	28	3	2	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	29	1	3	98	98	98	98	98	0	0	15	152	15202	15202012008
15	152	15202	1	2	8	13910	30	1	1	5	1	4	2	4	1	1	15	152	15202	15202012008
15	152	15202	1	2	12	8394	1	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	2	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	3	3	1	5	3	5	2	3	1	4	15	152	15202	15202012012
15	152	15202	1	2	12	8394	4	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	5	3	3	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	6	3	3	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	7	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	8	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	9	3	1	5	3	5	1	4	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	10	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	11	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	12	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	13	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	14	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	15	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	16	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	17	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	18	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	19	3	1	99	99	99	99	99	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	20	3	1	5	3	5	3	99	1	1	15	152	15202	15202012012
15	152	15202	1	2	12	8394	21	3	1	5	99	5	1	4	1	2	15	152	15202	15202012012
15	152	15202	1	2	12	8394	22	3	2	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	23	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012
15	152	15202	1	2	12	8394	24	3	1	5	3	5	1	2	1	2	15	152	15202	15202012012
15	152	15202	1	2	12	8394	25	3	4	98	98	98	98	98	0	0	15	152	15202	15202012012

Despleguemos los códigos de regiones de nuestra tabla:

regiones <- unique(tabla_con_clave$REGION)

Hagamos un subset con la 1:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 6) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$AREA== 1) 

1.2 Cálculo de frecuencias

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

aterial de construcción del piso

names(tabla_con_clave_f)[2] <- "Tipo de piso"

# Ahora filtramos por Tipo de techo = 1.
tabla_con_clave_ff <- filter(tabla_con_clave_f, tabla_con_clave_f$`Tipo de piso` == 1)

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

Veamos los primeros 100 registros:

r3_100 <- d[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	zona	unlist.c.	unlist.d.	Freq	anio
1	6101011001	1	6101	1185	2017
2	6101021001	1	6101	467	2017
3	6101031001	1	6101	251	2017
4	6101041001	1	6101	478	2017
5	6101041002	1	6101	1490	2017
6	6101051001	1	6101	749	2017
7	6101051002	1	6101	549	2017
8	6101051003	1	6101	685	2017
9	6101051004	1	6101	586	2017
10	6101051005	1	6101	466	2017
11	6101061001	1	6101	1223	2017
12	6101061002	1	6101	514	2017
13	6101061003	1	6101	672	2017
14	6101061004	1	6101	624	2017
15	6101061005	1	6101	646	2017
16	6101061006	1	6101	500	2017
17	6101061007	1	6101	574	2017
18	6101061008	1	6101	414	2017
19	6101061009	1	6101	495	2017
20	6101071001	1	6101	823	2017
21	6101071002	1	6101	519	2017
22	6101071003	1	6101	410	2017
23	6101071004	1	6101	739	2017
24	6101071005	1	6101	136	2017
25	6101071006	1	6101	482	2017
26	6101071007	1	6101	290	2017
27	6101081001	1	6101	465	2017
28	6101081002	1	6101	762	2017
29	6101081003	1	6101	865	2017
30	6101081004	1	6101	828	2017
31	6101081005	1	6101	831	2017
32	6101081006	1	6101	871	2017
33	6101081007	1	6101	773	2017
34	6101091001	1	6101	603	2017
35	6101091002	1	6101	527	2017
36	6101091003	1	6101	1474	2017
37	6101091004	1	6101	595	2017
38	6101091005	1	6101	591	2017
39	6101091006	1	6101	447	2017
40	6101091007	1	6101	2437	2017
41	6101091008	1	6101	3397	2017
42	6101101001	1	6101	1196	2017
43	6101101002	1	6101	1309	2017
44	6101101003	1	6101	1331	2017
45	6101101004	1	6101	2074	2017
46	6101111001	1	6101	444	2017
47	6101111002	1	6101	1560	2017
48	6101111003	1	6101	611	2017
49	6101111004	1	6101	1011	2017
50	6101111005	1	6101	1530	2017
51	6101111006	1	6101	284	2017
52	6101131001	1	6101	47	2017
53	6101141001	1	6101	2154	2017
54	6101141002	1	6101	261	2017
55	6101141003	1	6101	264	2017
56	6101151001	1	6101	3067	2017
57	6101151002	1	6101	322	2017
58	6101151003	1	6101	491	2017
59	6101151004	1	6101	1578	2017
60	6101151005	1	6101	863	2017
61	6101151006	1	6101	919	2017
62	6101151007	1	6101	801	2017
63	6101151008	1	6101	975	2017
64	6101151009	1	6101	1774	2017
65	6101151010	1	6101	1392	2017
66	6101161001	1	6101	2203	2017
67	6101161002	1	6101	1863	2017
68	6101161003	1	6101	598	2017
69	6101161004	1	6101	1903	2017
70	6101161005	1	6101	1365	2017
71	6101161006	1	6101	470	2017
72	6101161007	1	6101	592	2017
73	6101171001	1	6101	507	2017
74	6101171002	1	6101	602	2017
75	6101171003	1	6101	1121	2017
76	6101171004	1	6101	1142	2017
77	6101171005	1	6101	1307	2017
78	6101171006	1	6101	551	2017
79	6101991999	1	6101	177	2017
372	6102011001	1	6102	607	2017
373	6102011002	1	6102	989	2017
374	6102021001	1	6102	86	2017
375	6102991999	1	6102	7	2017
668	6103011001	1	6103	105	2017
669	6103021001	1	6103	487	2017
670	6103031001	1	6103	342	2017
671	6103991999	1	6103	7	2017
964	6104011001	1	6104	439	2017
965	6104041001	1	6104	340	2017
966	6104051001	1	6104	12	2017
967	6104061001	1	6104	1025	2017
968	6104061002	1	6104	10	2017
969	6104071001	1	6104	591	2017
970	6104081001	1	6104	509	2017
971	6104081002	1	6104	32	2017
972	6104991999	1	6104	19	2017
1265	6105011001	1	6105	1458	2017
1266	6105011002	1	6105	632	2017
1267	6105021001	1	6105	8	2017
1268	6105031001	1	6105	1003	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	6101011001	1185	2017	06101
2	6101021001	467	2017	06101
3	6101031001	251	2017	06101
4	6101041001	478	2017	06101
5	6101041002	1490	2017	06101
6	6101051001	749	2017	06101
7	6101051002	549	2017	06101
8	6101051003	685	2017	06101
9	6101051004	586	2017	06101
10	6101051005	466	2017	06101
11	6101061001	1223	2017	06101
12	6101061002	514	2017	06101
13	6101061003	672	2017	06101
14	6101061004	624	2017	06101
15	6101061005	646	2017	06101
16	6101061006	500	2017	06101
17	6101061007	574	2017	06101
18	6101061008	414	2017	06101
19	6101061009	495	2017	06101
20	6101071001	823	2017	06101
21	6101071002	519	2017	06101
22	6101071003	410	2017	06101
23	6101071004	739	2017	06101
24	6101071005	136	2017	06101
25	6101071006	482	2017	06101
26	6101071007	290	2017	06101
27	6101081001	465	2017	06101
28	6101081002	762	2017	06101
29	6101081003	865	2017	06101
30	6101081004	828	2017	06101
31	6101081005	831	2017	06101
32	6101081006	871	2017	06101
33	6101081007	773	2017	06101
34	6101091001	603	2017	06101
35	6101091002	527	2017	06101
36	6101091003	1474	2017	06101
37	6101091004	595	2017	06101
38	6101091005	591	2017	06101
39	6101091006	447	2017	06101
40	6101091007	2437	2017	06101
41	6101091008	3397	2017	06101
42	6101101001	1196	2017	06101
43	6101101002	1309	2017	06101
44	6101101003	1331	2017	06101
45	6101101004	2074	2017	06101
46	6101111001	444	2017	06101
47	6101111002	1560	2017	06101
48	6101111003	611	2017	06101
49	6101111004	1011	2017	06101
50	6101111005	1530	2017	06101
51	6101111006	284	2017	06101
52	6101131001	47	2017	06101
53	6101141001	2154	2017	06101
54	6101141002	261	2017	06101
55	6101141003	264	2017	06101
56	6101151001	3067	2017	06101
57	6101151002	322	2017	06101
58	6101151003	491	2017	06101
59	6101151004	1578	2017	06101
60	6101151005	863	2017	06101
61	6101151006	919	2017	06101
62	6101151007	801	2017	06101
63	6101151008	975	2017	06101
64	6101151009	1774	2017	06101
65	6101151010	1392	2017	06101
66	6101161001	2203	2017	06101
67	6101161002	1863	2017	06101
68	6101161003	598	2017	06101
69	6101161004	1903	2017	06101
70	6101161005	1365	2017	06101
71	6101161006	470	2017	06101
72	6101161007	592	2017	06101
73	6101171001	507	2017	06101
74	6101171002	602	2017	06101
75	6101171003	1121	2017	06101
76	6101171004	1142	2017	06101
77	6101171005	1307	2017	06101
78	6101171006	551	2017	06101
79	6101991999	177	2017	06101
372	6102011001	607	2017	06102
373	6102011002	989	2017	06102
374	6102021001	86	2017	06102
375	6102991999	7	2017	06102
668	6103011001	105	2017	06103
669	6103021001	487	2017	06103
670	6103031001	342	2017	06103
671	6103991999	7	2017	06103
964	6104011001	439	2017	06104
965	6104041001	340	2017	06104
966	6104051001	12	2017	06104
967	6104061001	1025	2017	06104
968	6104061002	10	2017	06104
969	6104071001	591	2017	06104
970	6104081001	509	2017	06104
971	6104081002	32	2017	06104
972	6104991999	19	2017	06104
1265	6105011001	1458	2017	06105
1266	6105011002	632	2017	06105
1267	6105021001	8	2017	06105
1268	6105031001	1003	2017	06105

2 Variable CASEN

2.1 Tabla de ingresos expandidos

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

h_y_m_2017_censo <- readRDS("../ingresos_expandidos_urbano_17.rds")
tablamadre <- head(h_y_m_2017_censo,50)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

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

3 Unión Censo-Casen

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

comunas_con_ing_exp = merge( x = comuna_corr, y = h_y_m_2017_censo, by = "código", all.x = TRUE)
comunas_con_ing_exp <-comunas_con_ing_exp[!(is.na(comunas_con_ing_exp$Ingresos_expandidos)),]
r3_100 <- comunas_con_ing_exp[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

código	zona	Freq	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos
06101	6101011001	1185	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101021001	467	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101031001	251	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101041001	478	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101041002	1490	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051001	749	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051002	549	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051003	685	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051004	586	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051005	466	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061001	1223	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061002	514	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061003	672	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061004	624	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061005	646	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061006	500	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061007	574	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061008	414	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061009	495	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071001	823	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071002	519	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071003	410	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071004	739	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071005	136	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071006	482	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071007	290	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081001	465	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081002	762	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081003	865	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081004	828	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081005	831	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081006	871	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081007	773	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091001	603	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091002	527	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091003	1474	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091004	595	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091005	591	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091006	447	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091007	2437	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091008	3397	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101001	1196	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101002	1309	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101003	1331	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101004	2074	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111001	444	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111002	1560	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111003	611	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111004	1011	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111005	1530	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111006	284	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101131001	47	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101141001	2154	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101141002	261	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101141003	264	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151001	3067	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151002	322	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151003	491	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151004	1578	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151005	863	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151006	919	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151007	801	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151008	975	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151009	1774	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151010	1392	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161001	2203	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161002	1863	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161003	598	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161004	1903	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161005	1365	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161006	470	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161007	592	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171001	507	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171002	602	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171003	1121	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171004	1142	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171005	1307	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171006	551	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101991999	177	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06102	6102011001	607	2017	Codegua	289405.7	2017	6102	12988	3758801352
06102	6102011002	989	2017	Codegua	289405.7	2017	6102	12988	3758801352
06102	6102021001	86	2017	Codegua	289405.7	2017	6102	12988	3758801352
06102	6102991999	7	2017	Codegua	289405.7	2017	6102	12988	3758801352
06103	6103011001	105	2017	Coinco	224485.0	2017	6103	7359	1651985453
06103	6103021001	487	2017	Coinco	224485.0	2017	6103	7359	1651985453
06103	6103031001	342	2017	Coinco	224485.0	2017	6103	7359	1651985453
06103	6103991999	7	2017	Coinco	224485.0	2017	6103	7359	1651985453
06104	6104011001	439	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104041001	340	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104051001	12	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104061001	1025	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104061002	10	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104071001	591	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104081001	509	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104081002	32	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104991999	19	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06105	6105011001	1458	2017	Doñihue	306532.0	2017	6105	20887	6402533884
06105	6105011002	632	2017	Doñihue	306532.0	2017	6105	20887	6402533884
06105	6105021001	8	2017	Doñihue	306532.0	2017	6105	20887	6402533884
06105	6105031001	1003	2017	Doñihue	306532.0	2017	6105	20887	6402533884

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
06101	6101011001	1185	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101021001	467	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101031001	251	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101041001	478	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101041002	1490	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051001	749	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051002	549	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051003	685	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051004	586	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101051005	466	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061001	1223	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061002	514	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061003	672	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061004	624	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061005	646	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061006	500	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061007	574	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061008	414	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101061009	495	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071001	823	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071002	519	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071003	410	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071004	739	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071005	136	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071006	482	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101071007	290	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081001	465	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081002	762	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081003	865	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081004	828	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081005	831	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081006	871	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101081007	773	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091001	603	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091002	527	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091003	1474	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091004	595	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091005	591	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091006	447	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091007	2437	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101091008	3397	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101001	1196	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101002	1309	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101003	1331	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101101004	2074	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111001	444	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111002	1560	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111003	611	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111004	1011	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111005	1530	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101111006	284	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101131001	47	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101141001	2154	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101141002	261	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101141003	264	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151001	3067	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151002	322	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151003	491	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151004	1578	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151005	863	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151006	919	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151007	801	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151008	975	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151009	1774	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101151010	1392	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161001	2203	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161002	1863	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161003	598	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161004	1903	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161005	1365	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161006	470	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101161007	592	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171001	507	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171002	602	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171003	1121	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171004	1142	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171005	1307	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101171006	551	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06101	6101991999	177	2017	Rancagua	318384.5	2017	6101	241774	76977097284
06102	6102011001	607	2017	Codegua	289405.7	2017	6102	12988	3758801352
06102	6102011002	989	2017	Codegua	289405.7	2017	6102	12988	3758801352
06102	6102021001	86	2017	Codegua	289405.7	2017	6102	12988	3758801352
06102	6102991999	7	2017	Codegua	289405.7	2017	6102	12988	3758801352
06103	6103011001	105	2017	Coinco	224485.0	2017	6103	7359	1651985453
06103	6103021001	487	2017	Coinco	224485.0	2017	6103	7359	1651985453
06103	6103031001	342	2017	Coinco	224485.0	2017	6103	7359	1651985453
06103	6103991999	7	2017	Coinco	224485.0	2017	6103	7359	1651985453
06104	6104011001	439	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104041001	340	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104051001	12	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104061001	1025	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104061002	10	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104071001	591	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104081001	509	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104081002	32	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06104	6104991999	19	2017	Coltauco	278925.9	2017	6104	19597	5466110795
06105	6105011001	1458	2017	Doñihue	306532.0	2017	6105	20887	6402533884
06105	6105011002	632	2017	Doñihue	306532.0	2017	6105	20887	6402533884
06105	6105021001	8	2017	Doñihue	306532.0	2017	6105	20887	6402533884
06105	6105031001	1003	2017	Doñihue	306532.0	2017	6105	20887	6402533884

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
6101011001	06101	1185	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2931	0.0121229	06101
6101021001	06101	467	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1326	0.0054845	06101
6101031001	06101	251	2017	Rancagua	318384.5	2017	6101	241774	76977097284	893	0.0036935	06101
6101041001	06101	478	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1599	0.0066136	06101
6101041002	06101	1490	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3616	0.0149561	06101
6101051001	06101	749	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2105	0.0087065	06101
6101051002	06101	549	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1634	0.0067584	06101
6101051003	06101	685	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1810	0.0074863	06101
6101051004	06101	586	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1724	0.0071306	06101
6101051005	06101	466	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1297	0.0053645	06101
6101061001	06101	1223	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3575	0.0147865	06101
6101061002	06101	514	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1868	0.0077262	06101
6101061003	06101	672	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1945	0.0080447	06101
6101061004	06101	624	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2013	0.0083260	06101
6101061005	06101	646	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1941	0.0080282	06101
6101061006	06101	500	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1440	0.0059560	06101
6101061007	06101	574	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1880	0.0077759	06101
6101061008	06101	414	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1255	0.0051908	06101
6101061009	06101	495	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1458	0.0060304	06101
6101071001	06101	823	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3085	0.0127599	06101
6101071002	06101	519	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1951	0.0080695	06101
6101071003	06101	410	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1805	0.0074656	06101
6101071004	06101	739	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2369	0.0097984	06101
6101071005	06101	136	2017	Rancagua	318384.5	2017	6101	241774	76977097284	411	0.0016999	06101
6101071006	06101	482	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101
6101071007	06101	290	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1281	0.0052983	06101
6101081001	06101	465	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1438	0.0059477	06101
6101081002	06101	762	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2053	0.0084914	06101
6101081003	06101	865	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2627	0.0108655	06101
6101081004	06101	828	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2379	0.0098398	06101
6101081005	06101	831	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2188	0.0090498	06101
6101081006	06101	871	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2502	0.0103485	06101
6101081007	06101	773	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2234	0.0092400	06101
6101091001	06101	603	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2303	0.0095254	06101
6101091002	06101	527	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1991	0.0082350	06101
6101091003	06101	1474	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4641	0.0191956	06101
6101091004	06101	595	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1903	0.0078710	06101
6101091005	06101	591	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2187	0.0090456	06101
6101091006	06101	447	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1472	0.0060883	06101
6101091007	06101	2437	2017	Rancagua	318384.5	2017	6101	241774	76977097284	8109	0.0335396	06101
6101091008	06101	3397	2017	Rancagua	318384.5	2017	6101	241774	76977097284	11700	0.0483923	06101
6101101001	06101	1196	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3965	0.0163996	06101
6101101002	06101	1309	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4110	0.0169993	06101
6101101003	06101	1331	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4224	0.0174709	06101
6101101004	06101	2074	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5803	0.0240018	06101
6101111001	06101	444	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1303	0.0053893	06101
6101111002	06101	1560	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5050	0.0208873	06101
6101111003	06101	611	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2031	0.0084004	06101
6101111004	06101	1011	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3455	0.0142902	06101
6101111005	06101	1530	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5041	0.0208501	06101
6101111006	06101	284	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1279	0.0052901	06101
6101131001	06101	47	2017	Rancagua	318384.5	2017	6101	241774	76977097284	175	0.0007238	06101
6101141001	06101	2154	2017	Rancagua	318384.5	2017	6101	241774	76977097284	7033	0.0290891	06101
6101141002	06101	261	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1110	0.0045911	06101
6101141003	06101	264	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1183	0.0048930	06101
6101151001	06101	3067	2017	Rancagua	318384.5	2017	6101	241774	76977097284	9988	0.0413113	06101
6101151002	06101	322	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1136	0.0046986	06101
6101151003	06101	491	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1480	0.0061214	06101
6101151004	06101	1578	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5748	0.0237743	06101
6101151005	06101	863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3234	0.0133761	06101
6101151006	06101	919	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2829	0.0117010	06101
6101151007	06101	801	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2757	0.0114032	06101
6101151008	06101	975	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3771	0.0155972	06101
6101151009	06101	1774	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6283	0.0259871	06101
6101151010	06101	1392	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4858	0.0200931	06101
6101161001	06101	2203	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6794	0.0281006	06101
6101161002	06101	1863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6040	0.0249820	06101
6101161003	06101	598	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2230	0.0092235	06101
6101161004	06101	1903	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6100	0.0252302	06101
6101161005	06101	1365	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4455	0.0184263	06101
6101161006	06101	470	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1457	0.0060263	06101
6101161007	06101	592	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101
6101171001	06101	507	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1666	0.0068907	06101
6101171002	06101	602	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1913	0.0079123	06101
6101171003	06101	1121	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3730	0.0154276	06101
6101171004	06101	1142	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4000	0.0165444	06101
6101171005	06101	1307	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5138	0.0212513	06101
6101171006	06101	551	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1713	0.0070851	06101
6101991999	06101	177	2017	Rancagua	318384.5	2017	6101	241774	76977097284	520	0.0021508	06101
6102011001	06102	607	2017	Codegua	289405.7	2017	6102	12988	3758801352	2483	0.1911765	06102
6102011002	06102	989	2017	Codegua	289405.7	2017	6102	12988	3758801352	4176	0.3215276	06102
6102021001	06102	86	2017	Codegua	289405.7	2017	6102	12988	3758801352	345	0.0265630	06102
6102991999	06102	7	2017	Codegua	289405.7	2017	6102	12988	3758801352	15	0.0011549	06102
6103011001	06103	105	2017	Coinco	224485.0	2017	6103	7359	1651985453	377	0.0512298	06103
6103021001	06103	487	2017	Coinco	224485.0	2017	6103	7359	1651985453	1770	0.2405218	06103
6103031001	06103	342	2017	Coinco	224485.0	2017	6103	7359	1651985453	1260	0.1712189	06103
6103991999	06103	7	2017	Coinco	224485.0	2017	6103	7359	1651985453	17	0.0023101	06103
6104011001	06104	439	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1464	0.0747053	06104
6104041001	06104	340	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1450	0.0739909	06104
6104051001	06104	12	2017	Coltauco	278925.9	2017	6104	19597	5466110795	48	0.0024494	06104
6104061001	06104	1025	2017	Coltauco	278925.9	2017	6104	19597	5466110795	4056	0.2069705	06104
6104061002	06104	10	2017	Coltauco	278925.9	2017	6104	19597	5466110795	37	0.0018880	06104
6104071001	06104	591	2017	Coltauco	278925.9	2017	6104	19597	5466110795	2247	0.1146604	06104
6104081001	06104	509	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1713	0.0874113	06104
6104081002	06104	32	2017	Coltauco	278925.9	2017	6104	19597	5466110795	125	0.0063785	06104
6104991999	06104	19	2017	Coltauco	278925.9	2017	6104	19597	5466110795	71	0.0036230	06104
6105011001	06105	1458	2017	Doñihue	306532.0	2017	6105	20887	6402533884	5036	0.2411069	06105
6105011002	06105	632	2017	Doñihue	306532.0	2017	6105	20887	6402533884	2266	0.1084885	06105
6105021001	06105	8	2017	Doñihue	306532.0	2017	6105	20887	6402533884	99	0.0047398	06105
6105031001	06105	1003	2017	Doñihue	306532.0	2017	6105	20887	6402533884	3661	0.1752765	06105

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
6101011001	06101	1185	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2931	0.0121229	06101	933185008
6101021001	06101	467	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1326	0.0054845	06101	422177864
6101031001	06101	251	2017	Rancagua	318384.5	2017	6101	241774	76977097284	893	0.0036935	06101	284317370
6101041001	06101	478	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1599	0.0066136	06101	509096837
6101041002	06101	1490	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3616	0.0149561	06101	1151278400
6101051001	06101	749	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2105	0.0087065	06101	670199400
6101051002	06101	549	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1634	0.0067584	06101	520240294
6101051003	06101	685	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1810	0.0074863	06101	576275969
6101051004	06101	586	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1724	0.0071306	06101	548894901
6101051005	06101	466	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1297	0.0053645	06101	412944714
6101061001	06101	1223	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3575	0.0147865	06101	1138224635
6101061002	06101	514	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1868	0.0077262	06101	594742271
6101061003	06101	672	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1945	0.0080447	06101	619257878
6101061004	06101	624	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2013	0.0083260	06101	640908025
6101061005	06101	646	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1941	0.0080282	06101	617984340
6101061006	06101	500	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1440	0.0059560	06101	458473699
6101061007	06101	574	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1880	0.0077759	06101	598562885
6101061008	06101	414	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1255	0.0051908	06101	399572564
6101061009	06101	495	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1458	0.0060304	06101	464204620
6101071001	06101	823	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3085	0.0127599	06101	982216223
6101071002	06101	519	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1951	0.0080695	06101	621168185
6101071003	06101	410	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1805	0.0074656	06101	574684046
6101071004	06101	739	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2369	0.0097984	06101	754252912
6101071005	06101	136	2017	Rancagua	318384.5	2017	6101	241774	76977097284	411	0.0016999	06101	130856035
6101071006	06101	482	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101	579778198
6101071007	06101	290	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1281	0.0052983	06101	407850561
6101081001	06101	465	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1438	0.0059477	06101	457836930
6101081002	06101	762	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2053	0.0084914	06101	653643406
6101081003	06101	865	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2627	0.0108655	06101	836396116
6101081004	06101	828	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2379	0.0098398	06101	757436757
6101081005	06101	831	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2188	0.0090498	06101	696625315
6101081006	06101	871	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2502	0.0103485	06101	796598052
6101081007	06101	773	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2234	0.0092400	06101	711271002
6101091001	06101	603	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2303	0.0095254	06101	733239534
6101091002	06101	527	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1991	0.0082350	06101	633903566
6101091003	06101	1474	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4641	0.0191956	06101	1477622526
6101091004	06101	595	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1903	0.0078710	06101	605885729
6101091005	06101	591	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2187	0.0090456	06101	696306930
6101091006	06101	447	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1472	0.0060883	06101	468662003
6101091007	06101	2437	2017	Rancagua	318384.5	2017	6101	241774	76977097284	8109	0.0335396	06101	2581780017
6101091008	06101	3397	2017	Rancagua	318384.5	2017	6101	241774	76977097284	11700	0.0483923	06101	3725098804
6101101001	06101	1196	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3965	0.0163996	06101	1262394595
6101101002	06101	1309	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4110	0.0169993	06101	1308560349
6101101003	06101	1331	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4224	0.0174709	06101	1344856184
6101101004	06101	2074	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5803	0.0240018	06101	1847585330
6101111001	06101	444	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1303	0.0053893	06101	414855021
6101111002	06101	1560	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5050	0.0208873	06101	1607841791
6101111003	06101	611	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2031	0.0084004	06101	646638946
6101111004	06101	1011	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3455	0.0142902	06101	1100018493
6101111005	06101	1530	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5041	0.0208501	06101	1604976331
6101111006	06101	284	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1279	0.0052901	06101	407213792
6101131001	06101	47	2017	Rancagua	318384.5	2017	6101	241774	76977097284	175	0.0007238	06101	55717290
6101141001	06101	2154	2017	Rancagua	318384.5	2017	6101	241774	76977097284	7033	0.0290891	06101	2239198281
6101141002	06101	261	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1110	0.0045911	06101	353406810
6101141003	06101	264	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1183	0.0048930	06101	376648879
6101151001	06101	3067	2017	Rancagua	318384.5	2017	6101	241774	76977097284	9988	0.0413113	06101	3180024517
6101151002	06101	322	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1136	0.0046986	06101	361684807
6101151003	06101	491	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1480	0.0061214	06101	471209079
6101151004	06101	1578	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5748	0.0237743	06101	1830074182
6101151005	06101	863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3234	0.0133761	06101	1029655516
6101151006	06101	919	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2829	0.0117010	06101	900709788
6101151007	06101	801	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2757	0.0114032	06101	877786103
6101151008	06101	975	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3771	0.0155972	06101	1200627999
6101151009	06101	1774	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6283	0.0259871	06101	2000409896
6101151010	06101	1392	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4858	0.0200931	06101	1546711965
6101161001	06101	2203	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6794	0.0281006	06101	2163104382
6101161002	06101	1863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6040	0.0249820	06101	1923042459
6101161003	06101	598	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2230	0.0092235	06101	709997464
6101161004	06101	1903	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6100	0.0252302	06101	1942145530
6101161005	06101	1365	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4455	0.0184263	06101	1418403006
6101161006	06101	470	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1457	0.0060263	06101	463886236
6101161007	06101	592	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101	579778198
6101171001	06101	507	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1666	0.0068907	06101	530428599
6101171002	06101	602	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1913	0.0079123	06101	609069574
6101171003	06101	1121	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3730	0.0154276	06101	1187574234
6101171004	06101	1142	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4000	0.0165444	06101	1273538053
6101171005	06101	1307	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5138	0.0212513	06101	1635859629
6101171006	06101	551	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1713	0.0070851	06101	545392671
6101991999	06101	177	2017	Rancagua	318384.5	2017	6101	241774	76977097284	520	0.0021508	06101	165559947
6102011001	06102	607	2017	Codegua	289405.7	2017	6102	12988	3758801352	2483	0.1911765	06102	718594376
6102011002	06102	989	2017	Codegua	289405.7	2017	6102	12988	3758801352	4176	0.3215276	06102	1208558242
6102021001	06102	86	2017	Codegua	289405.7	2017	6102	12988	3758801352	345	0.0265630	06102	99844970
6102991999	06102	7	2017	Codegua	289405.7	2017	6102	12988	3758801352	15	0.0011549	06102	4341086
6103011001	06103	105	2017	Coinco	224485.0	2017	6103	7359	1651985453	377	0.0512298	06103	84630862
6103021001	06103	487	2017	Coinco	224485.0	2017	6103	7359	1651985453	1770	0.2405218	06103	397338531
6103031001	06103	342	2017	Coinco	224485.0	2017	6103	7359	1651985453	1260	0.1712189	06103	282851158
6103991999	06103	7	2017	Coinco	224485.0	2017	6103	7359	1651985453	17	0.0023101	06103	3816246
6104011001	06104	439	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1464	0.0747053	06104	408347513
6104041001	06104	340	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1450	0.0739909	06104	404442550
6104051001	06104	12	2017	Coltauco	278925.9	2017	6104	19597	5466110795	48	0.0024494	06104	13388443
6104061001	06104	1025	2017	Coltauco	278925.9	2017	6104	19597	5466110795	4056	0.2069705	06104	1131323436
6104061002	06104	10	2017	Coltauco	278925.9	2017	6104	19597	5466110795	37	0.0018880	06104	10320258
6104071001	06104	591	2017	Coltauco	278925.9	2017	6104	19597	5466110795	2247	0.1146604	06104	626746490
6104081001	06104	509	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1713	0.0874113	06104	477800061
6104081002	06104	32	2017	Coltauco	278925.9	2017	6104	19597	5466110795	125	0.0063785	06104	34865737
6104991999	06104	19	2017	Coltauco	278925.9	2017	6104	19597	5466110795	71	0.0036230	06104	19803739
6105011001	06105	1458	2017	Doñihue	306532.0	2017	6105	20887	6402533884	5036	0.2411069	06105	1543695152
6105011002	06105	632	2017	Doñihue	306532.0	2017	6105	20887	6402533884	2266	0.1084885	06105	694601512
6105021001	06105	8	2017	Doñihue	306532.0	2017	6105	20887	6402533884	99	0.0047398	06105	30346668
6105031001	06105	1003	2017	Doñihue	306532.0	2017	6105	20887	6402533884	3661	0.1752765	06105	1122213652

7 Análisis de regresión

Aplicaremos un análisis de regresión donde:

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

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

7.1 Diagrama de dispersión loess

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

7.2 Outliers

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

7.3 Modelo lineal

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

linearMod <- lm( multi_pob~(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -398994690  -38506526   -3413955   43221375  338806994 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  3061300    8523956   0.359     0.72    
## Freq.x       1038397       9871 105.193   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 91130000 on 290 degrees of freedom
## Multiple R-squared:  0.9745, Adjusted R-squared:  0.9744 
## F-statistic: 1.107e+04 on 1 and 290 DF,  p-value: < 2.2e-16

7.4 Gráfica de la recta de regresión lineal

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

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

8 Modelos alternativos

### 8.1 Modelo cuadrático

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

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

kbl(modelos_bind) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	modelo	dato	sintaxis	latex
3	logarítmico	0.560077556898266	linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 ln X \]
6	log-raíz	0.799532370556495	linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = e^{''beta_0 + ''beta_1 ''sqrt{X}} \]
7	raíz-log	0.8202600529737	linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = {''beta_0}^2 + 2 ''beta_0 ''beta_1 ''ln{X}+ ''beta_1^2 ln^2X \]
4	raíz cuadrada	0.879451747617343	linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 ''sqrt {X} \]
1	cuadrático	0.974373927338671	linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 X^2 \]
2	cúbico	0.974373927338671	linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 X^3 \]
5	raíz-raíz	0.983329238506347	linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = {''beta_0}^2 + 2 ''beta_0 ''beta_1 ''sqrt{X}+ ''beta_1^2 X \]
8	log-log	0.985090264362618	linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = e^{''beta_0+''beta_1 ln{X}} \]

h_y_m_comuna_corr <- h_y_m_comuna_corr_01
metodo <- 8


switch (metodo,
        case = linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( sqrt(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr),
        case = linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr)
)
summary(linearMod)

## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.24745 -0.09811 -0.00592  0.09980  1.44675 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.629650   0.045295   300.9   <2e-16 ***
## log(Freq.x)  1.034797   0.007463   138.7   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2116 on 290 degrees of freedom
## Multiple R-squared:  0.9851, Adjusted R-squared:  0.9851 
## F-statistic: 1.923e+04 on 1 and 290 DF,  p-value: < 2.2e-16

aa <- linearMod$coefficients[1]
aa

## (Intercept) 
##    13.62965

bb <- linearMod$coefficients[2]
bb

## log(Freq.x) 
##    1.034797

9 Modelo log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.9851).

9.1 Diagrama de dispersión sobre log-log

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

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

9.2 Modelo log-log

Observemos nuevamente el resultado sobre log-log.

linearMod <- lm(log( multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr)
summary(linearMod) 

## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.24745 -0.09811 -0.00592  0.09980  1.44675 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.629650   0.045295   300.9   <2e-16 ***
## log(Freq.x)  1.034797   0.007463   138.7   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2116 on 290 degrees of freedom
## Multiple R-squared:  0.9851, Adjusted R-squared:  0.9851 
## F-statistic: 1.923e+04 on 1 and 290 DF,  p-value: < 2.2e-16

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

9.3 Análisis de residuos

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

9.4 Ecuación del modelo

\[ \hat Y = e^{13.62965 +1.034797 \cdot ln{X}} \]

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

Esta nueva variable se llamará: est_ing

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

r3_100 <- h_y_m_comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing
6101011001	06101	1185	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2931	0.0121229	06101	933185008	1258802889
6101021001	06101	467	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1326	0.0054845	06101	422177864	480268531
6101031001	06101	251	2017	Rancagua	318384.5	2017	6101	241774	76977097284	893	0.0036935	06101	284317370	252614389
6101041001	06101	478	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1599	0.0066136	06101	509096837	491979475
6101041002	06101	1490	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3616	0.0149561	06101	1151278400	1595463513
6101051001	06101	749	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2105	0.0087065	06101	670199400	783047811
6101051002	06101	549	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1634	0.0067584	06101	520240294	567785509
6101051003	06101	685	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1810	0.0074863	06101	576275969	713916136
6101051004	06101	586	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1724	0.0071306	06101	548894901	607428581
6101051005	06101	466	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1297	0.0053645	06101	412944714	479204373
6101061001	06101	1223	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3575	0.0147865	06101	1138224635	1300597290
6101061002	06101	514	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1868	0.0077262	06101	594742271	530370734
6101061003	06101	672	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1945	0.0080447	06101	619257878	699900559
6101061004	06101	624	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2013	0.0083260	06101	640908025	648233860
6101061005	06101	646	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1941	0.0080282	06101	617984340	671897879
6101061006	06101	500	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1440	0.0059560	06101	458473699	515429306
6101061007	06101	574	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1880	0.0077759	06101	598562885	594561548
6101061008	06101	414	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1255	0.0051908	06101	399572564	423981699
6101061009	06101	495	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1458	0.0060304	06101	464204620	510096587
6101071001	06101	823	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3085	0.0127599	06101	982216223	863237184
6101071002	06101	519	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1951	0.0080695	06101	621168185	535710412
6101071003	06101	410	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1805	0.0074656	06101	574684046	419743427
6101071004	06101	739	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2369	0.0097984	06101	754252912	772231966
6101071005	06101	136	2017	Rancagua	318384.5	2017	6101	241774	76977097284	411	0.0016999	06101	130856035	133986939
6101071006	06101	482	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101	579778198	496240337
6101071007	06101	290	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1281	0.0052983	06101	407850561	293335756
6101081001	06101	465	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1438	0.0059477	06101	457836930	478140293
6101081002	06101	762	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2053	0.0084914	06101	653643406	797115915
6101081003	06101	865	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2627	0.0108655	06101	836396116	908863374
6101081004	06101	828	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2379	0.0098398	06101	757436757	868664704
6101081005	06101	831	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2188	0.0090498	06101	696625315	871921764
6101081006	06101	871	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2502	0.0103485	06101	796598052	915387786
6101081007	06101	773	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2234	0.0092400	06101	711271002	809026226
6101091001	06101	603	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2303	0.0095254	06101	733239534	625672536
6101091002	06101	527	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1991	0.0082350	06101	633903566	544257613
6101091003	06101	1474	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4641	0.0191956	06101	1477622526	1577738176
6101091004	06101	595	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1903	0.0078710	06101	605885729	617084885
6101091005	06101	591	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2187	0.0090456	06101	696306930	612792562
6101091006	06101	447	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1472	0.0060883	06101	468662003	459000646
6101091007	06101	2437	2017	Rancagua	318384.5	2017	6101	241774	76977097284	8109	0.0335396	06101	2581780017	2654552247
6101091008	06101	3397	2017	Rancagua	318384.5	2017	6101	241774	76977097284	11700	0.0483923	06101	3725098804	3743264164
6101101001	06101	1196	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3965	0.0163996	06101	1262394595	1270896538
6101101002	06101	1309	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4110	0.0169993	06101	1308560349	1395349552
6101101003	06101	1331	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4224	0.0174709	06101	1344856184	1419623906
6101101004	06101	2074	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5803	0.0240018	06101	1847585330	2246503259
6101111001	06101	444	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1303	0.0053893	06101	414855021	455813283
6101111002	06101	1560	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5050	0.0208873	06101	1607841791	1673088866
6101111003	06101	611	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2031	0.0084004	06101	646638946	634264153
6101111004	06101	1011	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3455	0.0142902	06101	1100018493	1068047716
6101111005	06101	1530	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5041	0.0208501	06101	1604976331	1639805690
6101111006	06101	284	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1279	0.0052901	06101	407213792	287057830
6101131001	06101	47	2017	Rancagua	318384.5	2017	6101	241774	76977097284	175	0.0007238	06101	55717290	44623585
6101141001	06101	2154	2017	Rancagua	318384.5	2017	6101	241774	76977097284	7033	0.0290891	06101	2239198281	2336231973
6101141002	06101	261	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1110	0.0045911	06101	353406810	263036048
6101141003	06101	264	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1183	0.0048930	06101	376648879	266165281
6101151001	06101	3067	2017	Rancagua	318384.5	2017	6101	241774	76977097284	9988	0.0413113	06101	3180024517	3367629726
6101151002	06101	322	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1136	0.0046986	06101	361684807	326892303
6101151003	06101	491	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1480	0.0061214	06101	471209079	505831761
6101151004	06101	1578	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5748	0.0237743	06101	1830074182	1693069493
6101151005	06101	863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3234	0.0133761	06101	1029655516	906688919
6101151006	06101	919	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2829	0.0117010	06101	900709788	967638540
6101151007	06101	801	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2757	0.0114032	06101	877786103	839369816
6101151008	06101	975	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3771	0.0155972	06101	1200627999	1028717615
6101151009	06101	1774	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6283	0.0259871	06101	2000409896	1911132211
6101151010	06101	1392	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4858	0.0200931	06101	1546711965	1487002446
6101161001	06101	2203	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6794	0.0281006	06101	2163104382	2391248390
6101161002	06101	1863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6040	0.0249820	06101	1923042459	2010433621
6101161003	06101	598	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2230	0.0092235	06101	709997464	620304786
6101161004	06101	1903	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6100	0.0252302	06101	1942145530	2055117752
6101161005	06101	1365	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4455	0.0184263	06101	1418403006	1457166209
6101161006	06101	470	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1457	0.0060263	06101	463886236	483461483
6101161007	06101	592	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101	579778198	613865548
6101171001	06101	507	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1666	0.0068907	06101	530428599	522898225
6101171002	06101	602	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1913	0.0079123	06101	609069574	624598862
6101171003	06101	1121	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3730	0.0154276	06101	1187574234	1188518462
6101171004	06101	1142	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4000	0.0165444	06101	1273538053	1211565527
6101171005	06101	1307	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5138	0.0212513	06101	1635859629	1393143492
6101171006	06101	551	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1713	0.0070851	06101	545392671	569926056
6101991999	06101	177	2017	Rancagua	318384.5	2017	6101	241774	76977097284	520	0.0021508	06101	165559947	175986293
6102011001	06102	607	2017	Codegua	289405.7	2017	6102	12988	3758801352	2483	0.1911765	06102	718594376	629967852
6102011002	06102	989	2017	Codegua	289405.7	2017	6102	12988	3758801352	4176	0.3215276	06102	1208558242	1044006751
6102021001	06102	86	2017	Codegua	289405.7	2017	6102	12988	3758801352	345	0.0265630	06102	99844970	83386532
6102991999	06102	7	2017	Codegua	289405.7	2017	6102	12988	3758801352	15	0.0011549	06102	4341086	6219954
6103011001	06103	105	2017	Coinco	224485.0	2017	6103	7359	1651985453	377	0.0512298	06103	84630862	102518768
6103021001	06103	487	2017	Coinco	224485.0	2017	6103	7359	1651985453	1770	0.2405218	06103	397338531	501568144
6103031001	06103	342	2017	Coinco	224485.0	2017	6103	7359	1651985453	1260	0.1712189	06103	282851158	347924960
6103991999	06103	7	2017	Coinco	224485.0	2017	6103	7359	1651985453	17	0.0023101	06103	3816246	6219954
6104011001	06104	439	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1464	0.0747053	06104	408347513	450502679
6104041001	06104	340	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1450	0.0739909	06104	404442550	345819725
6104051001	06104	12	2017	Coltauco	278925.9	2017	6104	19597	5466110795	48	0.0024494	06104	13388443	10864653
6104061001	06104	1025	2017	Coltauco	278925.9	2017	6104	19597	5466110795	4056	0.2069705	06104	1131323436	1083356018
6104061002	06104	10	2017	Coltauco	278925.9	2017	6104	19597	5466110795	37	0.0018880	06104	10320258	8996619
6104071001	06104	591	2017	Coltauco	278925.9	2017	6104	19597	5466110795	2247	0.1146604	06104	626746490	612792562
6104081001	06104	509	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1713	0.0874113	06104	477800061	525032863
6104081002	06104	32	2017	Coltauco	278925.9	2017	6104	19597	5466110795	125	0.0063785	06104	34865737	29978315
6104991999	06104	19	2017	Coltauco	278925.9	2017	6104	19597	5466110795	71	0.0036230	06104	19803739	17479654
6105011001	06105	1458	2017	Doñihue	306532.0	2017	6105	20887	6402533884	5036	0.2411069	06105	1543695152	1560019533
6105011002	06105	632	2017	Doñihue	306532.0	2017	6105	20887	6402533884	2266	0.1084885	06105	694601512	656835652
6105021001	06105	8	2017	Doñihue	306532.0	2017	6105	20887	6402533884	99	0.0047398	06105	30346668	7141626
6105031001	06105	1003	2017	Doñihue	306532.0	2017	6105	20887	6402533884	3661	0.1752765	06105	1122213652	1059303419

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

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

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

r3_100 <- h_y_m_comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	comuna.y	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing	ing_medio_zona
6101011001	06101	1185	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2931	0.0121229	06101	933185008	1258802889	429478.98
6101021001	06101	467	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1326	0.0054845	06101	422177864	480268531	362193.46
6101031001	06101	251	2017	Rancagua	318384.5	2017	6101	241774	76977097284	893	0.0036935	06101	284317370	252614389	282882.85
6101041001	06101	478	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1599	0.0066136	06101	509096837	491979475	307679.47
6101041002	06101	1490	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3616	0.0149561	06101	1151278400	1595463513	441223.32
6101051001	06101	749	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2105	0.0087065	06101	670199400	783047811	371994.21
6101051002	06101	549	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1634	0.0067584	06101	520240294	567785509	347481.95
6101051003	06101	685	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1810	0.0074863	06101	576275969	713916136	394428.80
6101051004	06101	586	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1724	0.0071306	06101	548894901	607428581	352336.76
6101051005	06101	466	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1297	0.0053645	06101	412944714	479204373	369471.37
6101061001	06101	1223	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3575	0.0147865	06101	1138224635	1300597290	363803.44
6101061002	06101	514	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1868	0.0077262	06101	594742271	530370734	283924.38
6101061003	06101	672	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1945	0.0080447	06101	619257878	699900559	359846.05
6101061004	06101	624	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2013	0.0083260	06101	640908025	648233860	322023.78
6101061005	06101	646	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1941	0.0080282	06101	617984340	671897879	346160.68
6101061006	06101	500	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1440	0.0059560	06101	458473699	515429306	357937.02
6101061007	06101	574	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1880	0.0077759	06101	598562885	594561548	316256.14
6101061008	06101	414	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1255	0.0051908	06101	399572564	423981699	337834.02
6101061009	06101	495	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1458	0.0060304	06101	464204620	510096587	349860.49
6101071001	06101	823	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3085	0.0127599	06101	982216223	863237184	279817.56
6101071002	06101	519	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1951	0.0080695	06101	621168185	535710412	274582.48
6101071003	06101	410	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1805	0.0074656	06101	574684046	419743427	232544.83
6101071004	06101	739	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2369	0.0097984	06101	754252912	772231966	325973.81
6101071005	06101	136	2017	Rancagua	318384.5	2017	6101	241774	76977097284	411	0.0016999	06101	130856035	133986939	326002.28
6101071006	06101	482	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101	579778198	496240337	272509.80
6101071007	06101	290	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1281	0.0052983	06101	407850561	293335756	228989.66
6101081001	06101	465	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1438	0.0059477	06101	457836930	478140293	332503.68
6101081002	06101	762	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2053	0.0084914	06101	653643406	797115915	388268.83
6101081003	06101	865	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2627	0.0108655	06101	836396116	908863374	345970.07
6101081004	06101	828	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2379	0.0098398	06101	757436757	868664704	365138.59
6101081005	06101	831	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2188	0.0090498	06101	696625315	871921764	398501.72
6101081006	06101	871	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2502	0.0103485	06101	796598052	915387786	365862.42
6101081007	06101	773	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2234	0.0092400	06101	711271002	809026226	362142.45
6101091001	06101	603	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2303	0.0095254	06101	733239534	625672536	271677.18
6101091002	06101	527	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1991	0.0082350	06101	633903566	544257613	273358.92
6101091003	06101	1474	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4641	0.0191956	06101	1477622526	1577738176	339956.51
6101091004	06101	595	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1903	0.0078710	06101	605885729	617084885	324269.51
6101091005	06101	591	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2187	0.0090456	06101	696306930	612792562	280197.79
6101091006	06101	447	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1472	0.0060883	06101	468662003	459000646	311821.09
6101091007	06101	2437	2017	Rancagua	318384.5	2017	6101	241774	76977097284	8109	0.0335396	06101	2581780017	2654552247	327358.77
6101091008	06101	3397	2017	Rancagua	318384.5	2017	6101	241774	76977097284	11700	0.0483923	06101	3725098804	3743264164	319937.11
6101101001	06101	1196	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3965	0.0163996	06101	1262394595	1270896538	320528.76
6101101002	06101	1309	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4110	0.0169993	06101	1308560349	1395349552	339501.11
6101101003	06101	1331	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4224	0.0174709	06101	1344856184	1419623906	336085.20
6101101004	06101	2074	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5803	0.0240018	06101	1847585330	2246503259	387127.91
6101111001	06101	444	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1303	0.0053893	06101	414855021	455813283	349818.33
6101111002	06101	1560	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5050	0.0208873	06101	1607841791	1673088866	331304.73
6101111003	06101	611	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2031	0.0084004	06101	646638946	634264153	312291.56
6101111004	06101	1011	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3455	0.0142902	06101	1100018493	1068047716	309131.03
6101111005	06101	1530	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5041	0.0208501	06101	1604976331	1639805690	325293.73
6101111006	06101	284	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1279	0.0052901	06101	407213792	287057830	224439.27
6101131001	06101	47	2017	Rancagua	318384.5	2017	6101	241774	76977097284	175	0.0007238	06101	55717290	44623585	254991.91
6101141001	06101	2154	2017	Rancagua	318384.5	2017	6101	241774	76977097284	7033	0.0290891	06101	2239198281	2336231973	332181.43
6101141002	06101	261	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1110	0.0045911	06101	353406810	263036048	236969.41
6101141003	06101	264	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1183	0.0048930	06101	376648879	266165281	224991.78
6101151001	06101	3067	2017	Rancagua	318384.5	2017	6101	241774	76977097284	9988	0.0413113	06101	3180024517	3367629726	337167.57
6101151002	06101	322	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1136	0.0046986	06101	361684807	326892303	287757.31
6101151003	06101	491	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1480	0.0061214	06101	471209079	505831761	341778.22
6101151004	06101	1578	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5748	0.0237743	06101	1830074182	1693069493	294549.32
6101151005	06101	863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3234	0.0133761	06101	1029655516	906688919	280361.45
6101151006	06101	919	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2829	0.0117010	06101	900709788	967638540	342042.61
6101151007	06101	801	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2757	0.0114032	06101	877786103	839369816	304450.42
6101151008	06101	975	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3771	0.0155972	06101	1200627999	1028717615	272797.03
6101151009	06101	1774	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6283	0.0259871	06101	2000409896	1911132211	304175.11
6101151010	06101	1392	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4858	0.0200931	06101	1546711965	1487002446	306093.55
6101161001	06101	2203	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6794	0.0281006	06101	2163104382	2391248390	351964.73
6101161002	06101	1863	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6040	0.0249820	06101	1923042459	2010433621	332853.25
6101161003	06101	598	2017	Rancagua	318384.5	2017	6101	241774	76977097284	2230	0.0092235	06101	709997464	620304786	278163.58
6101161004	06101	1903	2017	Rancagua	318384.5	2017	6101	241774	76977097284	6100	0.0252302	06101	1942145530	2055117752	336904.55
6101161005	06101	1365	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4455	0.0184263	06101	1418403006	1457166209	327085.57
6101161006	06101	470	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1457	0.0060263	06101	463886236	483461483	331819.82
6101161007	06101	592	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1821	0.0075318	06101	579778198	613865548	337103.54
6101171001	06101	507	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1666	0.0068907	06101	530428599	522898225	313864.48
6101171002	06101	602	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1913	0.0079123	06101	609069574	624598862	326502.28
6101171003	06101	1121	2017	Rancagua	318384.5	2017	6101	241774	76977097284	3730	0.0154276	06101	1187574234	1188518462	318637.66
6101171004	06101	1142	2017	Rancagua	318384.5	2017	6101	241774	76977097284	4000	0.0165444	06101	1273538053	1211565527	302891.38
6101171005	06101	1307	2017	Rancagua	318384.5	2017	6101	241774	76977097284	5138	0.0212513	06101	1635859629	1393143492	271145.09
6101171006	06101	551	2017	Rancagua	318384.5	2017	6101	241774	76977097284	1713	0.0070851	06101	545392671	569926056	332706.40
6101991999	06101	177	2017	Rancagua	318384.5	2017	6101	241774	76977097284	520	0.0021508	06101	165559947	175986293	338435.18
6102011001	06102	607	2017	Codegua	289405.7	2017	6102	12988	3758801352	2483	0.1911765	06102	718594376	629967852	253712.39
6102011002	06102	989	2017	Codegua	289405.7	2017	6102	12988	3758801352	4176	0.3215276	06102	1208558242	1044006751	250001.62
6102021001	06102	86	2017	Codegua	289405.7	2017	6102	12988	3758801352	345	0.0265630	06102	99844970	83386532	241700.09
6102991999	06102	7	2017	Codegua	289405.7	2017	6102	12988	3758801352	15	0.0011549	06102	4341086	6219954	414663.60
6103011001	06103	105	2017	Coinco	224485.0	2017	6103	7359	1651985453	377	0.0512298	06103	84630862	102518768	271933.07
6103021001	06103	487	2017	Coinco	224485.0	2017	6103	7359	1651985453	1770	0.2405218	06103	397338531	501568144	283371.83
6103031001	06103	342	2017	Coinco	224485.0	2017	6103	7359	1651985453	1260	0.1712189	06103	282851158	347924960	276130.92
6103991999	06103	7	2017	Coinco	224485.0	2017	6103	7359	1651985453	17	0.0023101	06103	3816246	6219954	365879.65
6104011001	06104	439	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1464	0.0747053	06104	408347513	450502679	307720.41
6104041001	06104	340	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1450	0.0739909	06104	404442550	345819725	238496.36
6104051001	06104	12	2017	Coltauco	278925.9	2017	6104	19597	5466110795	48	0.0024494	06104	13388443	10864653	226346.94
6104061001	06104	1025	2017	Coltauco	278925.9	2017	6104	19597	5466110795	4056	0.2069705	06104	1131323436	1083356018	267099.61
6104061002	06104	10	2017	Coltauco	278925.9	2017	6104	19597	5466110795	37	0.0018880	06104	10320258	8996619	243151.86
6104071001	06104	591	2017	Coltauco	278925.9	2017	6104	19597	5466110795	2247	0.1146604	06104	626746490	612792562	272715.87
6104081001	06104	509	2017	Coltauco	278925.9	2017	6104	19597	5466110795	1713	0.0874113	06104	477800061	525032863	306499.04
6104081002	06104	32	2017	Coltauco	278925.9	2017	6104	19597	5466110795	125	0.0063785	06104	34865737	29978315	239826.52
6104991999	06104	19	2017	Coltauco	278925.9	2017	6104	19597	5466110795	71	0.0036230	06104	19803739	17479654	246192.31
6105011001	06105	1458	2017	Doñihue	306532.0	2017	6105	20887	6402533884	5036	0.2411069	06105	1543695152	1560019533	309773.54
6105011002	06105	632	2017	Doñihue	306532.0	2017	6105	20887	6402533884	2266	0.1084885	06105	694601512	656835652	289865.69
6105021001	06105	8	2017	Doñihue	306532.0	2017	6105	20887	6402533884	99	0.0047398	06105	30346668	7141626	72137.63
6105031001	06105	1003	2017	Doñihue	306532.0	2017	6105	20887	6402533884	3661	0.1752765	06105	1122213652	1059303419	289348.11

Guardamos:

saveRDS(h_y_m_comuna_corr, "P03C/region_06_P03C_u.rds")

12 Referencias

https://rpubs.com/osoramirez/316691

https://dataintelligencechile.shinyapps.io/casenfinal

Manual_de_usuario_Censo_2017_16R.pdf

http://www.censo2017.cl/microdatos/

Censo de Población y Vivienda

https://www.ine.cl/estadisticas/sociales/censos-de-poblacion-y-vivienda/poblacion-y-vivienda

http://r-statistics.co/Linear-Regression.html