Expansión de la CASEN sobre el CENSO (Región 05)

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$REGION == 5) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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
5101011001	1	5101	1042	2017
5101011002	1	5101	1299	2017
5101011003	1	5101	742	2017
5101011004	1	5101	743	2017
5101011005	1	5101	782	2017
5101011006	1	5101	947	2017
5101011007	1	5101	998	2017
5101021001	1	5101	28	2017
5101021002	1	5101	639	2017
5101021003	1	5101	539	2017
5101021004	1	5101	415	2017
5101031001	1	5101	473	2017
5101031002	1	5101	525	2017
5101031003	1	5101	360	2017
5101031004	1	5101	233	2017
5101031005	1	5101	156	2017
5101031006	1	5101	331	2017
5101031007	1	5101	621	2017
5101031008	1	5101	726	2017
5101031009	1	5101	307	2017
5101031010	1	5101	467	2017
5101031011	1	5101	742	2017
5101031012	1	5101	192	2017
5101041001	1	5101	72	2017
5101051001	1	5101	623	2017
5101051002	1	5101	535	2017
5101051003	1	5101	755	2017
5101051004	1	5101	846	2017
5101051005	1	5101	463	2017
5101051006	1	5101	844	2017
5101051007	1	5101	569	2017
5101061001	1	5101	489	2017
5101061002	1	5101	301	2017
5101061003	1	5101	559	2017
5101061004	1	5101	320	2017
5101061005	1	5101	498	2017
5101071001	1	5101	500	2017
5101081001	1	5101	243	2017
5101081002	1	5101	225	2017
5101081003	1	5101	196	2017
5101081004	1	5101	182	2017
5101081005	1	5101	341	2017
5101081006	1	5101	434	2017
5101081007	1	5101	557	2017
5101081008	1	5101	392	2017
5101081009	1	5101	496	2017
5101081010	1	5101	405	2017
5101081011	1	5101	350	2017
5101091001	1	5101	675	2017
5101091002	1	5101	490	2017
5101091003	1	5101	451	2017
5101091004	1	5101	514	2017
5101101001	1	5101	371	2017
5101101002	1	5101	338	2017
5101101003	1	5101	297	2017
5101101004	1	5101	244	2017
5101101005	1	5101	295	2017
5101101006	1	5101	489	2017
5101101007	1	5101	198	2017
5101101008	1	5101	711	2017
5101101009	1	5101	1027	2017
5101111001	1	5101	856	2017
5101121001	1	5101	527	2017
5101121002	1	5101	695	2017
5101121003	1	5101	525	2017
5101131001	1	5101	241	2017
5101131002	1	5101	184	2017
5101131003	1	5101	194	2017
5101131004	1	5101	257	2017
5101131005	1	5101	187	2017
5101141001	1	5101	486	2017
5101141002	1	5101	311	2017
5101141003	1	5101	332	2017
5101141004	1	5101	198	2017
5101141005	1	5101	210	2017
5101141006	1	5101	378	2017
5101151001	1	5101	181	2017
5101151002	1	5101	163	2017
5101151003	1	5101	198	2017
5101151004	1	5101	175	2017
5101151005	1	5101	151	2017
5101151006	1	5101	224	2017
5101151007	1	5101	453	2017
5101161001	1	5101	194	2017
5101161002	1	5101	212	2017
5101161003	1	5101	163	2017
5101161004	1	5101	273	2017
5101161005	1	5101	162	2017
5101161006	1	5101	342	2017
5101161007	1	5101	306	2017
5101161008	1	5101	343	2017
5101161009	1	5101	251	2017
5101161010	1	5101	340	2017
5101161011	1	5101	523	2017
5101161012	1	5101	655	2017
5101171001	1	5101	357	2017
5101171002	1	5101	381	2017
5101171003	1	5101	540	2017
5101171004	1	5101	360	2017
5101171005	1	5101	409	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
5101011001	1042	2017	05101
5101011002	1299	2017	05101
5101011003	742	2017	05101
5101011004	743	2017	05101
5101011005	782	2017	05101
5101011006	947	2017	05101
5101011007	998	2017	05101
5101021001	28	2017	05101
5101021002	639	2017	05101
5101021003	539	2017	05101
5101021004	415	2017	05101
5101031001	473	2017	05101
5101031002	525	2017	05101
5101031003	360	2017	05101
5101031004	233	2017	05101
5101031005	156	2017	05101
5101031006	331	2017	05101
5101031007	621	2017	05101
5101031008	726	2017	05101
5101031009	307	2017	05101
5101031010	467	2017	05101
5101031011	742	2017	05101
5101031012	192	2017	05101
5101041001	72	2017	05101
5101051001	623	2017	05101
5101051002	535	2017	05101
5101051003	755	2017	05101
5101051004	846	2017	05101
5101051005	463	2017	05101
5101051006	844	2017	05101
5101051007	569	2017	05101
5101061001	489	2017	05101
5101061002	301	2017	05101
5101061003	559	2017	05101
5101061004	320	2017	05101
5101061005	498	2017	05101
5101071001	500	2017	05101
5101081001	243	2017	05101
5101081002	225	2017	05101
5101081003	196	2017	05101
5101081004	182	2017	05101
5101081005	341	2017	05101
5101081006	434	2017	05101
5101081007	557	2017	05101
5101081008	392	2017	05101
5101081009	496	2017	05101
5101081010	405	2017	05101
5101081011	350	2017	05101
5101091001	675	2017	05101
5101091002	490	2017	05101
5101091003	451	2017	05101
5101091004	514	2017	05101
5101101001	371	2017	05101
5101101002	338	2017	05101
5101101003	297	2017	05101
5101101004	244	2017	05101
5101101005	295	2017	05101
5101101006	489	2017	05101
5101101007	198	2017	05101
5101101008	711	2017	05101
5101101009	1027	2017	05101
5101111001	856	2017	05101
5101121001	527	2017	05101
5101121002	695	2017	05101
5101121003	525	2017	05101
5101131001	241	2017	05101
5101131002	184	2017	05101
5101131003	194	2017	05101
5101131004	257	2017	05101
5101131005	187	2017	05101
5101141001	486	2017	05101
5101141002	311	2017	05101
5101141003	332	2017	05101
5101141004	198	2017	05101
5101141005	210	2017	05101
5101141006	378	2017	05101
5101151001	181	2017	05101
5101151002	163	2017	05101
5101151003	198	2017	05101
5101151004	175	2017	05101
5101151005	151	2017	05101
5101151006	224	2017	05101
5101151007	453	2017	05101
5101161001	194	2017	05101
5101161002	212	2017	05101
5101161003	163	2017	05101
5101161004	273	2017	05101
5101161005	162	2017	05101
5101161006	342	2017	05101
5101161007	306	2017	05101
5101161008	343	2017	05101
5101161009	251	2017	05101
5101161010	340	2017	05101
5101161011	523	2017	05101
5101161012	655	2017	05101
5101171001	357	2017	05101
5101171002	381	2017	05101
5101171003	540	2017	05101
5101171004	360	2017	05101
5101171005	409	2017	05101

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
05101	5101011004	743	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011005	782	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011006	947	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011007	998	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021001	28	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021002	639	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021003	539	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021004	415	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031001	473	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031002	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011001	1042	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011002	1299	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011003	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031006	331	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031007	621	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031008	726	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031009	307	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031010	467	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031011	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031012	192	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101041001	72	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051001	623	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051002	535	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051003	755	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051004	846	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051005	463	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051006	844	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051007	569	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061001	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061002	301	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061003	559	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061004	320	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061005	498	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101071001	500	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081001	243	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081002	225	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081003	196	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081004	182	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081005	341	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081006	434	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081007	557	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081008	392	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081009	496	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081010	405	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081011	350	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091001	675	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091002	490	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091003	451	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091004	514	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101001	371	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031003	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031004	233	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031005	156	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101005	295	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101006	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101007	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101008	711	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101009	1027	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101111001	856	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101121001	527	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101121002	695	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101121003	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131001	241	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131002	184	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131003	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131004	257	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131005	187	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141001	486	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141002	311	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141003	332	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141004	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141005	210	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141006	378	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151001	181	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151002	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151003	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151004	175	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151005	151	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151006	224	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151007	453	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161001	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161002	212	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161003	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161004	273	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161005	162	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161006	342	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161007	306	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161008	343	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161009	251	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161010	340	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101002	338	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101003	297	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101004	244	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171002	381	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171003	540	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171004	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171005	409	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171006	288	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171007	506	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171008	85	2017	Valparaíso	306572.5	2017	5101	296655	90946261553

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
05101	5101011004	743	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011005	782	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011006	947	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011007	998	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021001	28	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021002	639	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021003	539	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101021004	415	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031001	473	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031002	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011001	1042	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011002	1299	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101011003	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031006	331	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031007	621	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031008	726	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031009	307	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031010	467	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031011	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031012	192	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101041001	72	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051001	623	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051002	535	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051003	755	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051004	846	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051005	463	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051006	844	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101051007	569	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061001	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061002	301	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061003	559	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061004	320	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101061005	498	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101071001	500	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081001	243	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081002	225	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081003	196	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081004	182	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081005	341	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081006	434	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081007	557	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081008	392	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081009	496	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081010	405	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101081011	350	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091001	675	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091002	490	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091003	451	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101091004	514	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101001	371	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031003	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031004	233	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101031005	156	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101005	295	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101006	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101007	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101008	711	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101009	1027	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101111001	856	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101121001	527	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101121002	695	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101121003	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131001	241	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131002	184	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131003	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131004	257	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101131005	187	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141001	486	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141002	311	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141003	332	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141004	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141005	210	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101141006	378	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151001	181	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151002	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151003	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151004	175	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151005	151	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151006	224	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101151007	453	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161001	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161002	212	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161003	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161004	273	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161005	162	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161006	342	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161007	306	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161008	343	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161009	251	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101161010	340	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101002	338	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101003	297	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101101004	244	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171002	381	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171003	540	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171004	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171005	409	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171006	288	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171007	506	2017	Valparaíso	306572.5	2017	5101	296655	90946261553
05101	5101171008	85	2017	Valparaíso	306572.5	2017	5101	296655	90946261553

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
5101011001	05101	1042	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3280	0.0110566	05101
5101011002	05101	1299	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3761	0.0126780	05101
5101011003	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2365	0.0079722	05101
5101011004	05101	743	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2690	0.0090678	05101
5101011005	05101	782	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2518	0.0084880	05101
5101011006	05101	947	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2848	0.0096004	05101
5101011007	05101	998	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3131	0.0105543	05101
5101021001	05101	28	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	273	0.0009203	05101
5101021002	05101	639	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1881	0.0063407	05101
5101021003	05101	539	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1696	0.0057171	05101
5101021004	05101	415	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1415	0.0047699	05101
5101031001	05101	473	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1402	0.0047260	05101
5101031002	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1780	0.0060002	05101
5101031003	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1071	0.0036103	05101
5101031004	05101	233	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	739	0.0024911	05101
5101031005	05101	156	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	457	0.0015405	05101
5101031006	05101	331	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1051	0.0035428	05101
5101031007	05101	621	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2154	0.0072610	05101
5101031008	05101	726	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2337	0.0078778	05101
5101031009	05101	307	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1059	0.0035698	05101
5101031010	05101	467	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1678	0.0056564	05101
5101031011	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2610	0.0087981	05101
5101031012	05101	192	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	659	0.0022214	05101
5101041001	05101	72	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	177	0.0005967	05101
5101051001	05101	623	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1872	0.0063104	05101
5101051002	05101	535	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1714	0.0057778	05101
5101051003	05101	755	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2345	0.0079048	05101
5101051004	05101	846	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3014	0.0101600	05101
5101051005	05101	463	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1688	0.0056901	05101
5101051006	05101	844	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3387	0.0114173	05101
5101051007	05101	569	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2233	0.0075273	05101
5101061001	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1196	0.0040316	05101
5101061002	05101	301	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	878	0.0029597	05101
5101061003	05101	559	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1642	0.0055350	05101
5101061004	05101	320	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	862	0.0029057	05101
5101061005	05101	498	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1546	0.0052114	05101
5101071001	05101	500	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101
5101081001	05101	243	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	687	0.0023158	05101
5101081002	05101	225	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	634	0.0021372	05101
5101081003	05101	196	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	619	0.0020866	05101
5101081004	05101	182	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	620	0.0020900	05101
5101081005	05101	341	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	979	0.0033001	05101
5101081006	05101	434	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101
5101081007	05101	557	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1791	0.0060373	05101
5101081008	05101	392	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1274	0.0042946	05101
5101081009	05101	496	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1519	0.0051204	05101
5101081010	05101	405	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1320	0.0044496	05101
5101081011	05101	350	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1143	0.0038530	05101
5101091001	05101	675	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1689	0.0056935	05101
5101091002	05101	490	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1322	0.0044564	05101
5101091003	05101	451	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1275	0.0042979	05101
5101091004	05101	514	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	4201	0.0141612	05101
5101101001	05101	371	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1044	0.0035192	05101
5101101002	05101	338	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	988	0.0033305	05101
5101101003	05101	297	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	849	0.0028619	05101
5101101004	05101	244	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	717	0.0024169	05101
5101101005	05101	295	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	936	0.0031552	05101
5101101006	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1453	0.0048979	05101
5101101007	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	604	0.0020360	05101
5101101008	05101	711	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2358	0.0079486	05101
5101101009	05101	1027	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3502	0.0118050	05101
5101111001	05101	856	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2120	0.0071463	05101
5101121001	05101	527	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101
5101121002	05101	695	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1941	0.0065430	05101
5101121003	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1528	0.0051508	05101
5101131001	05101	241	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1170	0.0039440	05101
5101131002	05101	184	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	572	0.0019282	05101
5101131003	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101
5101131004	05101	257	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	880	0.0029664	05101
5101131005	05101	187	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	664	0.0022383	05101
5101141001	05101	486	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1502	0.0050631	05101
5101141002	05101	311	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101
5101141003	05101	332	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1031	0.0034754	05101
5101141004	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101
5101141005	05101	210	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	704	0.0023731	05101
5101141006	05101	378	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101
5101151001	05101	181	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	532	0.0017933	05101
5101151002	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	455	0.0015338	05101
5101151003	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	640	0.0021574	05101
5101151004	05101	175	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	543	0.0018304	05101
5101151005	05101	151	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	503	0.0016956	05101
5101151006	05101	224	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	774	0.0026091	05101
5101151007	05101	453	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1448	0.0048811	05101
5101161001	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	625	0.0021068	05101
5101161002	05101	212	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	697	0.0023495	05101
5101161003	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	496	0.0016720	05101
5101161004	05101	273	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	892	0.0030069	05101
5101161005	05101	162	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	518	0.0017461	05101
5101161006	05101	342	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1016	0.0034249	05101
5101161007	05101	306	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	950	0.0032024	05101
5101161008	05101	343	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1194	0.0040249	05101
5101161009	05101	251	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	856	0.0028855	05101
5101161010	05101	340	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1235	0.0041631	05101
5101161011	05101	523	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1840	0.0062025	05101
5101161012	05101	655	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2467	0.0083161	05101
5101171001	05101	357	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	932	0.0031417	05101
5101171002	05101	381	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1142	0.0038496	05101
5101171003	05101	540	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1447	0.0048777	05101
5101171004	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101
5101171005	05101	409	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1452	0.0048946	05101

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
5101011001	05101	1042	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3280	0.0110566	05101	1005557762
5101011002	05101	1299	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3761	0.0126780	05101	1153019129
5101011003	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2365	0.0079722	05101	725043935
5101011004	05101	743	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2690	0.0090678	05101	824679994
5101011005	05101	782	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2518	0.0084880	05101	771949526
5101011006	05101	947	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2848	0.0096004	05101	873118447
5101011007	05101	998	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3131	0.0105543	05101	959878461
5101021001	05101	28	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	273	0.0009203	05101	83694289
5101021002	05101	639	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1881	0.0063407	05101	576662851
5101021003	05101	539	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1696	0.0057171	05101	519946940
5101021004	05101	415	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1415	0.0047699	05101	433800071
5101031001	05101	473	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1402	0.0047260	05101	429814629
5101031002	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1780	0.0060002	05101	545699029
5101031003	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1071	0.0036103	05101	328339135
5101031004	05101	233	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	739	0.0024911	05101	226557069
5101031005	05101	156	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	457	0.0015405	05101	140103627
5101031006	05101	331	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1051	0.0035428	05101	322207685
5101031007	05101	621	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2154	0.0072610	05101	660357140
5101031008	05101	726	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2337	0.0078778	05101	716459905
5101031009	05101	307	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1059	0.0035698	05101	324660265
5101031010	05101	467	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1678	0.0056564	05101	514428636
5101031011	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2610	0.0087981	05101	800154195
5101031012	05101	192	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	659	0.0022214	05101	202031270
5101041001	05101	72	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	177	0.0005967	05101	54263330
5101051001	05101	623	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1872	0.0063104	05101	573903698
5101051002	05101	535	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1714	0.0057778	05101	525465245
5101051003	05101	755	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2345	0.0079048	05101	718912485
5101051004	05101	846	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3014	0.0101600	05101	924009480
5101051005	05101	463	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1688	0.0056901	05101	517494360
5101051006	05101	844	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3387	0.0114173	05101	1038361018
5101051007	05101	569	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2233	0.0075273	05101	684576367
5101061001	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1196	0.0040316	05101	366660696
5101061002	05101	301	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	878	0.0029597	05101	269170645
5101061003	05101	559	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1642	0.0055350	05101	503392026
5101061004	05101	320	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	862	0.0029057	05101	264265485
5101061005	05101	498	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1546	0.0052114	05101	473961067
5101071001	05101	500	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101	387814198
5101081001	05101	243	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	687	0.0023158	05101	210615300
5101081002	05101	225	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	634	0.0021372	05101	194366958
5101081003	05101	196	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	619	0.0020866	05101	189768370
5101081004	05101	182	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	620	0.0020900	05101	190074943
5101081005	05101	341	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	979	0.0033001	05101	300134466
5101081006	05101	434	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101	439931521
5101081007	05101	557	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1791	0.0060373	05101	549071327
5101081008	05101	392	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1274	0.0042946	05101	390573350
5101081009	05101	496	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1519	0.0051204	05101	465683610
5101081010	05101	405	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1320	0.0044496	05101	404675685
5101081011	05101	350	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1143	0.0038530	05101	350412354
5101091001	05101	675	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1689	0.0056935	05101	517800933
5101091002	05101	490	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1322	0.0044564	05101	405288830
5101091003	05101	451	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1275	0.0042979	05101	390879923
5101091004	05101	514	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	4201	0.0141612	05101	1287911024
5101101001	05101	371	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1044	0.0035192	05101	320061678
5101101002	05101	338	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	988	0.0033305	05101	302893619
5101101003	05101	297	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	849	0.0028619	05101	260280043
5101101004	05101	244	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	717	0.0024169	05101	219812474
5101101005	05101	295	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	936	0.0031552	05101	286951849
5101101006	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1453	0.0048979	05101	445449826
5101101007	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	604	0.0020360	05101	185169783
5101101008	05101	711	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2358	0.0079486	05101	722897928
5101101009	05101	1027	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3502	0.0118050	05101	1073616854
5101111001	05101	856	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2120	0.0071463	05101	649933675
5101121001	05101	527	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101	439931521
5101121002	05101	695	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1941	0.0065430	05101	595057200
5101121003	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1528	0.0051508	05101	468442762
5101131001	05101	241	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1170	0.0039440	05101	358689811
5101131002	05101	184	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	572	0.0019282	05101	175359463
5101131003	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101	195593248
5101131004	05101	257	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	880	0.0029664	05101	269783790
5101131005	05101	187	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	664	0.0022383	05101	203564132
5101141001	05101	486	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1502	0.0050631	05101	460471878
5101141002	05101	311	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101	343974332
5101141003	05101	332	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1031	0.0034754	05101	316076236
5101141004	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101	195593248
5101141005	05101	210	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	704	0.0023731	05101	215827032
5101141006	05101	378	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101	387814198
5101151001	05101	181	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	532	0.0017933	05101	163096564
5101151002	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	455	0.0015338	05101	139490482
5101151003	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	640	0.0021574	05101	196206393
5101151004	05101	175	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	543	0.0018304	05101	166468861
5101151005	05101	151	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	503	0.0016956	05101	154205962
5101151006	05101	224	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	774	0.0026091	05101	237287106
5101151007	05101	453	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1448	0.0048811	05101	443916963
5101161001	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	625	0.0021068	05101	191607805
5101161002	05101	212	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	697	0.0023495	05101	213681024
5101161003	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	496	0.0016720	05101	152059954
5101161004	05101	273	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	892	0.0030069	05101	273462660
5101161005	05101	162	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	518	0.0017461	05101	158804549
5101161006	05101	342	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1016	0.0034249	05101	311477648
5101161007	05101	306	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	950	0.0032024	05101	291243864
5101161008	05101	343	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1194	0.0040249	05101	366047551
5101161009	05101	251	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	856	0.0028855	05101	262426050
5101161010	05101	340	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1235	0.0041631	05101	378617023
5101161011	05101	523	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1840	0.0062025	05101	564093379
5101161012	05101	655	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2467	0.0083161	05101	756314329
5101171001	05101	357	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	932	0.0031417	05101	285725559
5101171002	05101	381	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1142	0.0038496	05101	350105782
5101171003	05101	540	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1447	0.0048777	05101	443610391
5101171004	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101	343974332
5101171005	05101	409	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1452	0.0048946	05101	445143253

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 
## -559994620  -70638096     905997   53109769  756990602 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -15896297    9139167  -1.739   0.0824 .  
## Freq.x        1063846      10913  97.483   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 128600000 on 705 degrees of freedom
## Multiple R-squared:  0.9309, Adjusted R-squared:  0.9308 
## F-statistic:  9503 on 1 and 705 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	0.62049560568565	linearMod <- lm( multi_pob~log(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 ln X \]
7	raíz-log	0.805645623553596	linearMod <- lm( sqrt(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = {''beta_0}^2 + 2 ''beta_0 ''beta_1 ''ln{X}+ ''beta_1^2 ln^2X \]
6	log-raíz	0.839623433864429	linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = e^{''beta_0 + ''beta_1 ''sqrt{X}} \]
4	raíz cuadrada	0.872898393565099	linearMod <- lm( multi_pob~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 ''sqrt {X} \]
1	cuadrático	0.930838753560001	linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)	\[ ''hat Y = ''beta_0 + ''beta_1 X^2 \]
2	cúbico	0.930838753560001	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	0.952458165663509	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	0.964750369203958	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 
## -0.8233 -0.1225 -0.0120  0.1034  2.4881 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.804325   0.045532   303.2   <2e-16 ***
## log(Freq.x)  1.004829   0.007229   139.0   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2207 on 705 degrees of freedom
## Multiple R-squared:  0.9648, Adjusted R-squared:  0.9648 
## F-statistic: 1.932e+04 on 1 and 705 DF,  p-value: < 2.2e-16

aa <- linearMod$coefficients[1]
aa

## (Intercept) 
##    13.80432

bb <- linearMod$coefficients[2]
bb

## log(Freq.x) 
##    1.004829

9 Modelo log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.9648).

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 
## -0.8233 -0.1225 -0.0120  0.1034  2.4881 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.804325   0.045532   303.2   <2e-16 ***
## log(Freq.x)  1.004829   0.007229   139.0   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2207 on 705 degrees of freedom
## Multiple R-squared:  0.9648, Adjusted R-squared:  0.9648 
## F-statistic: 1.932e+04 on 1 and 705 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

\[ \hat Y = e^{13.80432 +1.004829 \cdot ln{X}} \]

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
5101011001	05101	1042	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3280	0.0110566	05101	1005557762	1065573015
5101011002	05101	1299	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3761	0.0126780	05101	1153019129	1329802005
5101011003	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2365	0.0079722	05101	725043935	757543007
5101011004	05101	743	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2690	0.0090678	05101	824679994	758568888
5101011005	05101	782	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2518	0.0084880	05101	771949526	798583360
5101011006	05101	947	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2848	0.0096004	05101	873118447	967976878
5101011007	05101	998	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3131	0.0105543	05101	959878461	1020365001
5101021001	05101	28	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	273	0.0009203	05101	83694289	28137696
5101021002	05101	639	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1881	0.0063407	05101	576662851	651914781
5101021003	05101	539	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1696	0.0057171	05101	519946940	549441946
5101021004	05101	415	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1415	0.0047699	05101	433800071	422505973
5101031001	05101	473	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1402	0.0047260	05101	429814629	481859303
5101031002	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1780	0.0060002	05101	545699029	535102718
5101031003	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1071	0.0036103	05101	328339135	366259658
5101031004	05101	233	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	739	0.0024911	05101	226557069	236553882
5101031005	05101	156	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	457	0.0015405	05101	140103627	158072888
5101031006	05101	331	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1051	0.0035428	05101	322207685	336618858
5101031007	05101	621	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2154	0.0072610	05101	660357140	633463572
5101031008	05101	726	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2337	0.0078778	05101	716459905	741129826
5101031009	05101	307	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1059	0.0035698	05101	324660265	312097986
5101031010	05101	467	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1678	0.0056564	05101	514428636	475717595
5101031011	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2610	0.0087981	05101	800154195	757543007
5101031012	05101	192	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	659	0.0022214	05101	202031270	194746421
5101041001	05101	72	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	177	0.0005967	05101	54263330	72684823
5101051001	05101	623	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1872	0.0063104	05101	573903698	635513580
5101051002	05101	535	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1714	0.0057778	05101	525465245	545344838
5101051003	05101	755	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2345	0.0079048	05101	718912485	770879977
5101051004	05101	846	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3014	0.0101600	05101	924009480	864268817
5101051005	05101	463	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1688	0.0056901	05101	517494360	471623335
5101051006	05101	844	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3387	0.0114173	05101	1038361018	862215773
5101051007	05101	569	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2233	0.0075273	05101	684576367	580174863
5101061001	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1196	0.0040316	05101	366660696	498239018
5101061002	05101	301	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	878	0.0029597	05101	269170645	305969186
5101061003	05101	559	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1642	0.0055350	05101	503392026	569929667
5101061004	05101	320	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	862	0.0029057	05101	264265485	325379020
5101061005	05101	498	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1546	0.0052114	05101	473961067	507453751
5101071001	05101	500	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101	387814198	509501579
5101081001	05101	243	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	687	0.0023158	05101	210615300	246756478
5101081002	05101	225	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	634	0.0021372	05101	194366958	228393323
5101081003	05101	196	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	619	0.0020866	05101	189768370	198823434
5101081004	05101	182	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	620	0.0020900	05101	190074943	184555701
5101081005	05101	341	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	979	0.0033001	05101	300134466	346838460
5101081006	05101	434	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101	439931521	441945147
5101081007	05101	557	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1791	0.0060373	05101	549071327	567880734
5101081008	05101	392	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1274	0.0042946	05101	390573350	398980111
5101081009	05101	496	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1519	0.0051204	05101	465683610	505405963
5101081010	05101	405	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1320	0.0044496	05101	404675685	412276542
5101081011	05101	350	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1143	0.0038530	05101	350412354	356037341
5101091001	05101	675	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1689	0.0056935	05101	517800933	688824662
5101091002	05101	490	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1322	0.0044564	05101	405288830	499262837
5101091003	05101	451	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1275	0.0042979	05101	390879923	459341583
5101091004	05101	514	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	4201	0.0141612	05101	1287911024	523837475
5101101001	05101	371	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1044	0.0035192	05101	320061678	377505790
5101101002	05101	338	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	988	0.0033305	05101	302893619	343772426
5101101003	05101	297	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	849	0.0028619	05101	260280043	301883647
5101101004	05101	244	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	717	0.0024169	05101	219812474	247776850
5101101005	05101	295	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	936	0.0031552	05101	286951849	299840977
5101101006	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1453	0.0048979	05101	445449826	498239018
5101101007	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	604	0.0020360	05101	185169783	200862092
5101101008	05101	711	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2358	0.0079486	05101	722897928	725744054
5101101009	05101	1027	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3502	0.0118050	05101	1073616854	1050160136
5101111001	05101	856	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2120	0.0071463	05101	649933675	874534385
5101121001	05101	527	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101	439931521	537151067
5101121002	05101	695	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1941	0.0065430	05101	595057200	709334293
5101121003	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1528	0.0051508	05101	468442762	535102718
5101131001	05101	241	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1170	0.0039440	05101	358689811	244715794
5101131002	05101	184	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	572	0.0019282	05101	175359463	186593634
5101131003	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101	195593248	196784876
5101131004	05101	257	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	880	0.0029664	05101	269783790	261043502
5101131005	05101	187	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	664	0.0022383	05101	203564132	189650732
5101141001	05101	486	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1502	0.0050631	05101	460471878	495167622
5101141002	05101	311	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101	343974332	316184174
5101141003	05101	332	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1031	0.0034754	05101	316076236	337640752
5101141004	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101	195593248	200862092
5101141005	05101	210	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	704	0.0023731	05101	215827032	213096093
5101141006	05101	378	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101	387814198	384663261
5101151001	05101	181	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	532	0.0017933	05101	163096564	183536776
5101151002	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	455	0.0015338	05101	139490482	165200916
5101151003	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	640	0.0021574	05101	196206393	200862092
5101151004	05101	175	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	543	0.0018304	05101	166468861	177423798
5101151005	05101	151	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	503	0.0016956	05101	154205962	152982382
5101151006	05101	224	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	774	0.0026091	05101	237287106	227373351
5101151007	05101	453	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1448	0.0048811	05101	443916963	461388433
5101161001	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	625	0.0021068	05101	191607805	196784876
5101161002	05101	212	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	697	0.0023495	05101	213681024	215135426
5101161003	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	496	0.0016720	05101	152059954	165200916
5101161004	05101	273	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	892	0.0030069	05101	273462660	277376123
5101161005	05101	162	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	518	0.0017461	05101	158804549	164182534
5101161006	05101	342	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1016	0.0034249	05101	311477648	347860501
5101161007	05101	306	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	950	0.0032024	05101	291243864	311076479
5101161008	05101	343	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1194	0.0040249	05101	366047551	348882556
5101161009	05101	251	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	856	0.0028855	05101	262426050	254920019
5101161010	05101	340	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1235	0.0041631	05101	378617023	345816434
5101161011	05101	523	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1840	0.0062025	05101	564093379	533054406
5101161012	05101	655	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2467	0.0083161	05101	756314329	668317965
5101171001	05101	357	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	932	0.0031417	05101	285725559	363192817
5101171002	05101	381	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1142	0.0038496	05101	350105782	387730945
5101171003	05101	540	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1447	0.0048777	05101	443610391	550466246
5101171004	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101	343974332	366259658
5101171005	05101	409	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1452	0.0048946	05101	445143253	416368170

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
5101011001	05101	1042	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3280	0.0110566	05101	1005557762	1065573015	324869.8
5101011002	05101	1299	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3761	0.0126780	05101	1153019129	1329802005	353576.7
5101011003	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2365	0.0079722	05101	725043935	757543007	320314.2
5101011004	05101	743	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2690	0.0090678	05101	824679994	758568888	281995.9
5101011005	05101	782	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2518	0.0084880	05101	771949526	798583360	317149.9
5101011006	05101	947	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2848	0.0096004	05101	873118447	967976878	339879.5
5101011007	05101	998	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3131	0.0105543	05101	959878461	1020365001	325891.1
5101021001	05101	28	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	273	0.0009203	05101	83694289	28137696	103068.5
5101021002	05101	639	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1881	0.0063407	05101	576662851	651914781	346578.8
5101021003	05101	539	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1696	0.0057171	05101	519946940	549441946	323963.4
5101021004	05101	415	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1415	0.0047699	05101	433800071	422505973	298590.8
5101031001	05101	473	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1402	0.0047260	05101	429814629	481859303	343694.2
5101031002	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1780	0.0060002	05101	545699029	535102718	300619.5
5101031003	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1071	0.0036103	05101	328339135	366259658	341979.1
5101031004	05101	233	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	739	0.0024911	05101	226557069	236553882	320100.0
5101031005	05101	156	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	457	0.0015405	05101	140103627	158072888	345892.5
5101031006	05101	331	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1051	0.0035428	05101	322207685	336618858	320284.4
5101031007	05101	621	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2154	0.0072610	05101	660357140	633463572	294087.1
5101031008	05101	726	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2337	0.0078778	05101	716459905	741129826	317128.7
5101031009	05101	307	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1059	0.0035698	05101	324660265	312097986	294710.1
5101031010	05101	467	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1678	0.0056564	05101	514428636	475717595	283502.7
5101031011	05101	742	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2610	0.0087981	05101	800154195	757543007	290246.4
5101031012	05101	192	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	659	0.0022214	05101	202031270	194746421	295518.1
5101041001	05101	72	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	177	0.0005967	05101	54263330	72684823	410648.7
5101051001	05101	623	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1872	0.0063104	05101	573903698	635513580	339483.8
5101051002	05101	535	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1714	0.0057778	05101	525465245	545344838	318170.9
5101051003	05101	755	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2345	0.0079048	05101	718912485	770879977	328733.5
5101051004	05101	846	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3014	0.0101600	05101	924009480	864268817	286751.4
5101051005	05101	463	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1688	0.0056901	05101	517494360	471623335	279397.7
5101051006	05101	844	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3387	0.0114173	05101	1038361018	862215773	254566.2
5101051007	05101	569	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2233	0.0075273	05101	684576367	580174863	259818.6
5101061001	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1196	0.0040316	05101	366660696	498239018	416587.8
5101061002	05101	301	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	878	0.0029597	05101	269170645	305969186	348484.3
5101061003	05101	559	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1642	0.0055350	05101	503392026	569929667	347094.8
5101061004	05101	320	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	862	0.0029057	05101	264265485	325379020	377469.9
5101061005	05101	498	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1546	0.0052114	05101	473961067	507453751	328236.6
5101071001	05101	500	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101	387814198	509501579	402768.0
5101081001	05101	243	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	687	0.0023158	05101	210615300	246756478	359179.7
5101081002	05101	225	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	634	0.0021372	05101	194366958	228393323	360241.8
5101081003	05101	196	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	619	0.0020866	05101	189768370	198823434	321201.0
5101081004	05101	182	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	620	0.0020900	05101	190074943	184555701	297670.5
5101081005	05101	341	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	979	0.0033001	05101	300134466	346838460	354278.3
5101081006	05101	434	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101	439931521	441945147	307975.7
5101081007	05101	557	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1791	0.0060373	05101	549071327	567880734	317074.7
5101081008	05101	392	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1274	0.0042946	05101	390573350	398980111	313171.2
5101081009	05101	496	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1519	0.0051204	05101	465683610	505405963	332722.8
5101081010	05101	405	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1320	0.0044496	05101	404675685	412276542	312330.7
5101081011	05101	350	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1143	0.0038530	05101	350412354	356037341	311493.7
5101091001	05101	675	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1689	0.0056935	05101	517800933	688824662	407829.9
5101091002	05101	490	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1322	0.0044564	05101	405288830	499262837	377657.2
5101091003	05101	451	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1275	0.0042979	05101	390879923	459341583	360267.9
5101091004	05101	514	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	4201	0.0141612	05101	1287911024	523837475	124693.5
5101101001	05101	371	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1044	0.0035192	05101	320061678	377505790	361595.6
5101101002	05101	338	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	988	0.0033305	05101	302893619	343772426	347947.8
5101101003	05101	297	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	849	0.0028619	05101	260280043	301883647	355575.6
5101101004	05101	244	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	717	0.0024169	05101	219812474	247776850	345574.4
5101101005	05101	295	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	936	0.0031552	05101	286951849	299840977	320342.9
5101101006	05101	489	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1453	0.0048979	05101	445449826	498239018	342903.7
5101101007	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	604	0.0020360	05101	185169783	200862092	332553.1
5101101008	05101	711	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2358	0.0079486	05101	722897928	725744054	307779.5
5101101009	05101	1027	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	3502	0.0118050	05101	1073616854	1050160136	299874.4
5101111001	05101	856	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2120	0.0071463	05101	649933675	874534385	412516.2
5101121001	05101	527	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1435	0.0048373	05101	439931521	537151067	374321.3
5101121002	05101	695	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1941	0.0065430	05101	595057200	709334293	365447.9
5101121003	05101	525	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1528	0.0051508	05101	468442762	535102718	350198.1
5101131001	05101	241	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1170	0.0039440	05101	358689811	244715794	209158.8
5101131002	05101	184	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	572	0.0019282	05101	175359463	186593634	326212.6
5101131003	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101	195593248	196784876	308440.2
5101131004	05101	257	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	880	0.0029664	05101	269783790	261043502	296640.3
5101131005	05101	187	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	664	0.0022383	05101	203564132	189650732	285618.6
5101141001	05101	486	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1502	0.0050631	05101	460471878	495167622	329672.2
5101141002	05101	311	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101	343974332	316184174	281804.1
5101141003	05101	332	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1031	0.0034754	05101	316076236	337640752	327488.6
5101141004	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	638	0.0021506	05101	195593248	200862092	314830.9
5101141005	05101	210	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	704	0.0023731	05101	215827032	213096093	302693.3
5101141006	05101	378	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1265	0.0042642	05101	387814198	384663261	304081.6
5101151001	05101	181	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	532	0.0017933	05101	163096564	183536776	344993.9
5101151002	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	455	0.0015338	05101	139490482	165200916	363078.9
5101151003	05101	198	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	640	0.0021574	05101	196206393	200862092	313847.0
5101151004	05101	175	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	543	0.0018304	05101	166468861	177423798	326747.3
5101151005	05101	151	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	503	0.0016956	05101	154205962	152982382	304139.9
5101151006	05101	224	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	774	0.0026091	05101	237287106	227373351	293764.0
5101151007	05101	453	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1448	0.0048811	05101	443916963	461388433	318638.4
5101161001	05101	194	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	625	0.0021068	05101	191607805	196784876	314855.8
5101161002	05101	212	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	697	0.0023495	05101	213681024	215135426	308659.1
5101161003	05101	163	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	496	0.0016720	05101	152059954	165200916	333066.4
5101161004	05101	273	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	892	0.0030069	05101	273462660	277376123	310959.8
5101161005	05101	162	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	518	0.0017461	05101	158804549	164182534	316954.7
5101161006	05101	342	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1016	0.0034249	05101	311477648	347860501	342382.4
5101161007	05101	306	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	950	0.0032024	05101	291243864	311076479	327448.9
5101161008	05101	343	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1194	0.0040249	05101	366047551	348882556	292196.4
5101161009	05101	251	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	856	0.0028855	05101	262426050	254920019	297803.8
5101161010	05101	340	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1235	0.0041631	05101	378617023	345816434	280013.3
5101161011	05101	523	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1840	0.0062025	05101	564093379	533054406	289703.5
5101161012	05101	655	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	2467	0.0083161	05101	756314329	668317965	270903.1
5101171001	05101	357	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	932	0.0031417	05101	285725559	363192817	389691.9
5101171002	05101	381	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1142	0.0038496	05101	350105782	387730945	339519.2
5101171003	05101	540	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1447	0.0048777	05101	443610391	550466246	380419.0
5101171004	05101	360	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1122	0.0037822	05101	343974332	366259658	326434.6
5101171005	05101	409	2017	Valparaíso	306572.5	2017	5101	296655	90946261553	1452	0.0048946	05101	445143253	416368170	286754.9

Guardamos:

saveRDS(h_y_m_comuna_corr, "P03C/region_05_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