Expansión de la CASEN sobre el CENSO (Región 08)

De ingresos sobre una categoría de respuesta RURAL

DataIntelligence

Abstract

Expandiremos los ingresos promedios comunales obtenidos de la CASEN sobre la pregunta (P15): “Nivel del curso más alto aprobado” en la categoría de respuesta “Profesional” (12), que más alto correlaciona con los ingresos expandidos (obtenidos de la multiplicación del ingreso promedio y los habitantes), ambos a nivel comunal.

Haremos el análisis sobre la región 08.

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

Lo anterior para ir combinando a nivel nacional los mejores modelos para construir una tabla de valores predichos.

1 Variable CENSO

Necesitamos calcular las frecuencias a nivel censal de las respuestas correspondientes a la categoría: “Profesional (4 o más años)” del campo P15 a nivel rural del Censo de personas. Recordemos que ésta fué la más alta correlación en relación a los ingresos expandidos (ver punto 3.4 aquí).

1.1 Lectura y filtrado de la tabla censal de personas

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

tabla_con_clave <- readRDS("../censo_personas_con_clave_17")
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	NHOGAR	PERSONAN	P07	P08	P09	P10	P10COMUNA	P10PAIS	P11	P11COMUNA	P11PAIS	P12	P12COMUNA	P12PAIS	P12A_LLEGADA	P12A_TRAMO	P13	P14	P15	P15A	P16	P16A	P16A_OTRO	P17	P18	P19	P20	P21M	P21A	P10PAIS_GRUPO	P11PAIS_GRUPO	P12PAIS_GRUPO	ESCOLARIDAD	P16A_GRUPO	REGION_15R	PROVINCIA_15R	COMUNA_15R	P10COMUNA_15R	P11COMUNA_15R	P12COMUNA_15R	clave
15	152	15202	1	2	6	13225	1	1	1	1	1	73	1	98	998	3	15101	998	1	98	998	9998	98	2	4	6	2	1	2	98	7	98	98	98	98	9998	998	998	998	4	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	3	1	1	1	1	78	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	3	1	2	2	2	78	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	1	1	3	1965	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	3	1	3	5	2	52	1	98	998	2	98	998	1	98	998	9998	98	1	2	5	2	1	2	98	7	98	2	1	4	1995	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	3	1	4	11	1	44	1	98	998	2	98	998	1	98	998	9998	98	1	3	5	2	1	2	98	1	Z	98	98	98	9998	998	998	998	3	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	1	1	1	39	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	8	98	98	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	2	2	2	35	1	98	998	2	98	998	1	98	998	9998	98	2	6	5	2	1	2	98	1	Z	2	2	11	2004	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	3	5	1	13	1	98	998	2	98	998	1	98	998	9998	98	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	7	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	4	5	1	12	1	98	998	2	98	998	1	98	998	9998	98	1	6	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	10	1	1	1	2	65	1	98	998	2	98	998	1	98	998	9998	98	2	4	5	2	1	2	98	6	98	3	3	9	1992	998	998	998	4	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	13	1	1	1	1	50	1	98	998	2	98	998	1	98	998	9998	98	2	5	5	2	1	2	98	1	Z	98	98	98	9998	998	998	998	5	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	13	1	2	4	2	43	1	98	998	2	98	998	1	98	998	9998	98	2	6	5	2	1	2	98	6	98	2	2	3	2002	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	13	1	3	5	1	15	3	15201	998	2	98	998	1	98	998	9998	98	1	1	7	2	1	2	98	8	98	98	98	98	9998	998	998	998	9	2	15	152	15202	15201	98	98	15202012006
15	152	15202	1	2	6	13225	16	1	1	1	1	75	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	16	1	2	16	2	58	4	98	68	6	98	998	5	98	998	9999	1	3	98	98	98	1	2	98	7	98	4	4	99	9999	68	68	68	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	16	1	3	2	2	70	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	5	4	99	9999	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	1	1	2	43	2	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	I	3	3	9	2008	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	2	4	1	55	2	98	998	2	98	998	1	98	998	9998	98	2	6	5	2	1	2	98	6	98	98	98	98	9998	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	3	5	2	13	2	98	998	2	98	998	2	15101	998	9998	98	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	7	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	17	1	4	5	1	8	2	98	998	2	98	998	2	15101	998	9998	98	1	2	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	2	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	17	1	5	15	2	29	2	98	998	4	98	998	3	98	998	2015	1	2	6	5	2	1	2	98	6	98	5	5	11	2014	998	604	604	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	6	15	1	4	2	98	998	1	98	998	5	98	998	2015	1	1	0	1	2	1	2	98	98	98	98	98	98	9998	998	998	68	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	7	15	2	2	2	98	998	1	98	998	3	98	998	2015	1	1	0	1	2	1	2	98	98	98	98	98	98	9998	998	998	604	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	8	15	1	16	2	98	998	6	98	998	1	98	998	9998	98	2	4	5	2	1	2	98	6	98	98	98	98	9998	998	68	998	4	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	18	1	1	1	2	74	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	2	2	12	1976	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	19	1	1	1	1	68	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	20	1	1	1	1	74	1	98	998	3	15101	998	1	98	998	9998	98	2	2	5	2	1	2	98	1	Z	98	98	98	9998	998	998	998	2	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	20	1	2	2	2	65	1	98	998	3	997	998	3	98	998	9999	2	2	2	5	2	1	2	98	6	98	2	2	9	1982	998	998	604	2	2	15	152	15202	98	997	98	15202012006
15	152	15202	1	2	6	13225	25	1	1	1	2	76	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	6	98	8	6	3	1981	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	25	1	2	5	2	36	1	98	998	2	98	998	1	98	998	9998	98	2	4	8	1	1	2	98	1	A	0	98	98	9998	998	998	998	12	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	1	1	2	31	1	98	998	2	98	998	5	98	998	2007	2	2	5	5	2	1	2	98	1	A	2	2	4	2008	998	998	68	5	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	2	4	1	35	1	98	998	2	98	998	5	98	998	2007	2	2	6	5	2	1	2	98	1	F	98	98	98	9998	998	998	68	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	3	5	1	11	1	98	998	2	98	998	5	98	998	2007	2	1	5	5	2	1	2	98	98	98	98	98	98	9998	998	998	68	5	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	4	5	1	8	1	98	998	2	98	998	1	98	998	9998	98	1	2	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	5	15	2	74	1	98	998	2	98	998	1	98	998	9998	98	2	3	5	2	1	2	98	6	98	6	6	99	9999	998	998	998	3	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	1	1	1	41	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	Z	98	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	2	2	2	47	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	A	2	1	4	1996	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	3	14	1	88	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	4	14	1	65	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	7	98	98	98	98	9998	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	1	1	2	59	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	8	8	2	1998	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	2	2	1	56	1	98	998	99	99	999	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	98	98	98	9998	998	999	998	2	2	15	152	15202	98	99	98	15202012006
15	152	15202	1	2	6	13225	36	1	3	5	2	36	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	6	98	2	2	7	2010	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	4	12	2	13	1	98	998	2	98	998	1	98	998	9998	98	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	7	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	5	12	2	6	1	98	998	2	98	998	1	98	998	9998	98	1	0	3	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	6	5	1	24	1	98	998	3	15101	998	1	98	998	9998	98	2	4	7	1	1	2	98	1	Z	98	98	98	9998	998	998	998	12	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	36	1	7	11	2	24	1	98	998	3	15101	998	1	98	998	9998	98	2	4	7	1	1	2	98	1	N	2	2	11	2015	998	998	998	12	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	36	1	8	12	1	6	1	98	998	2	98	998	2	15101	998	9998	98	1	0	3	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	36	1	9	12	2	1	1	98	998	1	98	998	2	15101	998	9998	98	3	98	98	98	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	38	1	1	1	1	19	1	98	998	3	15101	998	2	15101	998	9998	98	1	1	8	2	1	2	98	1	A	98	98	98	9998	998	998	998	9	2	15	152	15202	98	15101	15101	15202012006
15	152	15202	1	2	6	13225	39	1	1	1	1	21	1	98	998	2	98	998	1	98	998	9998	98	2	1	7	2	1	2	98	1	F	98	98	98	9998	998	998	998	9	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	39	1	2	4	2	22	1	98	998	2	98	998	1	98	998	9998	98	2	1	8	2	1	2	98	6	98	0	98	98	9998	998	998	998	9	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	43	1	1	1	2	26	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	6	98	2	2	10	2013	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	43	1	2	2	1	24	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	Z	98	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	43	1	3	13	2	71	1	98	998	2	98	998	1	98	998	9998	98	2	1	5	2	1	2	98	6	98	3	3	12	1974	998	998	998	1	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	43	1	4	5	2	6	1	98	998	2	98	998	1	98	998	9998	98	1	0	3	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	43	1	5	5	2	3	1	98	998	1	98	998	1	98	998	9998	98	1	0	1	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	8	13910	5	1	1	1	1	44	1	98	998	2	98	998	3	98	998	2005	2	2	4	7	1	1	2	98	6	98	98	98	98	9998	998	998	604	12	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	5	1	2	2	2	42	1	98	998	2	98	998	1	98	998	9998	98	2	3	5	2	1	2	98	1	P	3	3	12	2006	998	998	998	3	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	5	1	3	5	2	10	1	98	998	2	98	998	1	98	998	9998	98	1	4	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	4	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	7	1	1	1	2	70	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	7	7	6	1994	998	998	998	2	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	7	1	2	5	1	44	1	98	998	2	98	998	1	98	998	9998	98	2	5	5	2	1	2	98	7	98	98	98	98	9998	998	998	998	5	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	8	1	1	1	1	58	1	98	998	2	98	998	3	98	998	2004	2	2	4	5	2	1	2	98	6	98	98	98	98	9998	998	998	604	4	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	8	1	2	2	2	59	1	98	998	2	98	998	3	98	998	2004	2	2	2	5	2	1	2	98	6	98	3	3	7	1999	998	998	604	2	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	19	1	1	1	1	58	99	99	999	99	99	999	99	99	999	9999	99	99	99	99	99	99	99	99	99	99	98	98	98	9998	999	999	999	99	99	15	152	15202	99	99	99	15202012008
15	152	15202	1	2	8	13910	21	1	1	1	1	53	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	H	98	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	21	1	2	2	2	46	1	98	998	2	98	998	1	98	998	9998	98	2	3	5	2	1	2	98	6	98	3	3	2	1990	998	998	998	3	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	22	1	1	1	2	73	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	6	98	6	5	3	1979	998	998	998	0	2	15	152	15202	98	98	98	15202012008
15	152	15202	1	2	8	13910	30	1	1	1	1	57	1	98	998	2	98	998	2	997	998	9998	98	2	3	5	2	1	2	98	6	98	98	98	98	9998	998	998	998	3	2	15	152	15202	98	98	997	15202012008
15	152	15202	1	2	12	8394	3	1	1	2	2	64	1	98	998	2	98	998	3	98	998	1974	4	3	98	98	98	1	2	98	1	A	12	10	99	9999	998	998	604	0	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	3	1	2	1	1	74	2	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	99	99	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	3	1	3	5	2	38	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	2	A	0	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	3	1	4	14	1	38	99	99	999	99	99	999	99	99	999	9999	99	99	99	99	99	99	99	99	8	98	98	98	98	9998	999	999	999	99	99	15	152	15202	99	99	99	15202012012
15	152	15202	1	2	12	8394	9	1	1	1	2	79	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	8	98	2	2	99	9999	998	998	998	0	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	19	1	1	1	1	46	99	99	999	99	99	999	99	99	999	9999	99	99	99	99	99	99	99	99	99	99	98	98	98	9998	999	999	999	99	99	15	152	15202	99	99	99	15202012012
15	152	15202	1	2	12	8394	20	1	1	1	2	58	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	A	3	3	7	1982	998	998	998	8	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	21	1	1	1	2	45	1	98	998	6	98	998	2	997	998	9998	98	2	4	5	2	1	2	98	1	A	6	6	2	2007	998	68	998	4	2	15	152	15202	98	98	997	15202012012
15	152	15202	1	2	12	8394	21	1	2	5	2	10	1	98	998	6	98	998	2	3201	998	9998	98	1	4	5	2	1	2	98	98	98	98	98	98	9998	998	68	998	4	2	15	152	15202	98	98	3201	15202012012
15	152	15202	1	2	12	8394	24	1	1	1	1	67	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	8	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	24	1	2	2	2	53	1	98	998	2	98	998	3	98	998	9999	99	3	98	98	98	1	2	98	8	98	0	98	98	9998	998	998	604	0	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	27	1	1	1	1	48	1	98	998	2	98	998	1	98	998	9998	98	2	4	7	1	1	2	98	8	98	98	98	98	9998	998	998	998	12	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	31	1	1	1	1	49	1	98	998	4	98	998	3	98	998	2001	2	2	8	5	1	1	2	98	1	A	98	98	98	9998	998	604	604	8	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	42	1	1	1	1	46	1	98	998	2	98	998	3	98	998	1992	3	2	8	5	1	1	2	98	2	A	98	98	98	9998	998	998	604	8	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	42	1	2	2	2	24	1	98	998	6	98	998	5	98	998	2013	1	2	7	5	2	1	2	98	6	98	2	2	6	2016	998	68	68	7	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	42	1	3	6	2	2	1	98	998	1	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	42	1	4	5	1	0	1	98	998	1	98	998	2	15101	998	9998	98	99	99	99	99	1	2	98	98	98	98	98	98	9998	998	998	998	99	2	15	152	15202	98	98	15101	15202012012
15	152	15202	1	2	12	8394	42	1	5	5	2	13	1	98	998	2	98	998	3	98	998	9999	99	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	604	7	2	15	152	15202	98	98	98	15202012012
15	152	15202	1	2	12	8394	42	1	6	5	1	6	1	98	998	2	98	998	2	15101	998	9998	98	1	0	3	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	15101	15202012012
15	152	15202	1	2	15	4094	2	1	1	1	1	41	1	98	998	2	98	998	1	98	998	9998	98	2	4	12	1	1	2	98	1	O	98	98	98	9998	998	998	998	16	2	15	152	15202	98	98	98	15202012015
15	152	15202	1	2	15	4094	8	1	1	17	1	70	2	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012015
15	152	15202	1	2	15	4094	8	1	2	17	1	47	2	98	998	3	15101	998	2	8101	998	9998	98	2	4	8	1	1	2	98	1	Z	98	98	98	9998	998	998	998	12	2	15	152	15202	98	15101	8101	15202012015
15	152	15202	1	2	15	4094	8	1	3	17	1	19	2	98	998	3	15101	998	2	15101	998	9998	98	1	99	7	99	1	2	98	1	I	98	98	98	9998	998	998	998	99	2	15	152	15202	98	15101	15101	15202012015
15	152	15202	1	2	15	4094	8	1	4	17	1	43	2	98	998	3	4302	998	2	8101	998	9998	98	99	4	8	1	1	2	98	1	N	98	98	98	9998	998	998	998	12	2	15	152	15202	98	4302	8101	15202012015
15	152	15202	1	2	15	4094	8	1	5	17	2	35	2	98	998	6	98	998	5	98	998	2016	1	2	8	5	1	1	2	98	1	I	2	2	3	2007	998	68	68	8	2	15	152	15202	98	98	98	15202012015
15	152	15202	1	2	15	4094	8	1	6	17	1	36	3	13123	998	3	13123	998	2	12101	998	9998	98	2	5	12	1	2	98	98	1	J	98	98	98	9998	998	998	998	17	98	15	152	15202	13123	13123	12101	15202012015
15	152	15202	1	2	15	4094	8	1	7	17	2	25	2	98	998	3	15101	998	2	15101	998	9998	98	2	5	12	1	1	2	98	1	Q	1	1	12	2011	998	998	998	17	2	15	152	15202	98	15101	15101	15202012015
15	152	15202	1	2	15	4094	9	1	1	1	1	72	1	98	998	2	98	998	1	98	998	9998	98	2	1	5	2	1	2	98	1	G	98	98	98	9998	998	998	998	1	2	15	152	15202	98	98	98	15202012015
15	152	15202	1	2	15	4094	12	1	1	1	1	21	1	98	998	3	15101	998	2	15101	998	9998	98	2	4	8	1	1	2	98	1	N	98	98	98	9998	998	998	998	12	2	15	152	15202	98	15101	15101	15202012015
15	152	15202	1	2	15	4094	15	1	1	1	1	61	1	98	998	2	98	998	1	98	998	9998	98	2	3	7	2	1	2	98	4	98	98	98	98	9998	998	998	998	11	2	15	152	15202	98	98	98	15202012015
15	152	15202	1	2	15	4094	15	1	2	5	2	31	1	98	998	3	15101	998	1	98	998	9998	98	2	4	12	1	1	2	98	1	P	1	1	10	2007	998	998	998	16	2	15	152	15202	98	15101	98	15202012015
15	152	15202	1	2	15	4094	16	1	1	1	1	34	1	98	998	3	15101	998	1	98	998	9998	98	2	5	12	1	1	2	98	1	O	98	98	98	9998	998	998	998	17	2	15	152	15202	98	15101	98	15202012015

Despleguemos los códigos de regiones de nuestra tabla:

regiones <- unique(tabla_con_clave$REGION)
regiones

##  [1] 15 14 13 12 11 10  9 16  8  7  6  5  4  3  2  1

Hagamos un subset con la region 08 y con la zona = 2:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 8) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$AREA== 2) 

1.2 Cálculo de frecuencias

tabla_con_clave_f <- tabla_con_clave[,-c(1,2,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20),drop=FALSE]

names(tabla_con_clave_f)[9] <- "Nivel del curso más alto aprobado"

# Ahora filtramos por Nivel del curso más alto aprobado = 11.
tabla_con_clave_ff <- filter(tabla_con_clave_f, tabla_con_clave_f$`Nivel del curso más alto aprobado` == 12)

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

Veamos los primeros 100 registros:

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

	zona	unlist.c.	unlist.d.	Freq	anio
1	8101252025	12	8101	9	2017
2	8101282901	12	8101	7	2017
3	8101292012	12	8101	6	2017
4	8101292020	12	8101	10	2017
5	8101292023	12	8101	7	2017
6	8101292901	12	8101	2	2017
7	8101302001	12	8101	24	2017
8	8101302005	12	8101	40	2017
9	8101302008	12	8101	12	2017
10	8101302011	12	8101	18	2017
11	8101302016	12	8101	4	2017
12	8101302018	12	8101	4	2017
13	8101302019	12	8101	10	2017
14	8101302021	12	8101	19	2017
15	8101302024	12	8101	2	2017
16	8101302901	12	8101	3	2017
17	8101312001	12	8101	4	2017
18	8101312004	12	8101	5	2017
19	8101312013	12	8101	94	2017
20	8101312014	12	8101	51	2017
21	8101312017	12	8101	7	2017
22	8101322025	12	8101	31	2017
807	8102052001	12	8102	9	2017
808	8102062004	12	8102	3	2017
809	8102062005	12	8102	118	2017
810	8102062009	12	8102	134	2017
811	8102072005	12	8102	95	2017
812	8102082002	12	8102	2	2017
813	8102092010	12	8102	13	2017
814	8102102007	12	8102	29	2017
815	8102102011	12	8102	16	2017
816	8102112006	12	8102	2	2017
817	8102112008	12	8102	20	2017
1602	8103062006	12	8103	6	2017
1603	8103062901	12	8103	1	2017
2388	8104012005	12	8104	2	2017
2389	8104012023	12	8104	24	2017
2390	8104012029	12	8104	2	2017
2391	8104012037	12	8104	11	2017
2392	8104012043	12	8104	7	2017
2393	8104012044	12	8104	16	2017
2394	8104012052	12	8104	8	2017
2395	8104012054	12	8104	1	2017
2396	8104022001	12	8104	5	2017
2397	8104022023	12	8104	3	2017
2398	8104022035	12	8104	2	2017
2399	8104022036	12	8104	7	2017
2400	8104022040	12	8104	4	2017
2401	8104032004	12	8104	7	2017
2402	8104032007	12	8104	2	2017
2403	8104032012	12	8104	6	2017
2404	8104032028	12	8104	20	2017
2405	8104032045	12	8104	7	2017
2406	8104032050	12	8104	1	2017
2407	8104032053	12	8104	2	2017
2408	8104032901	12	8104	3	2017
2409	8104042012	12	8104	40	2017
2410	8104042014	12	8104	8	2017
2411	8104042017	12	8104	3	2017
2412	8104042030	12	8104	1	2017
2413	8104042042	12	8104	4	2017
2414	8104042043	12	8104	3	2017
2415	8104042047	12	8104	3	2017
2416	8104042062	12	8104	9	2017
2417	8104052003	12	8104	6	2017
2418	8104052010	12	8104	4	2017
2419	8104052025	12	8104	1	2017
2420	8104052027	12	8104	4	2017
2421	8104052029	12	8104	1	2017
2422	8104052031	12	8104	7	2017
2423	8104052032	12	8104	4	2017
2424	8104052039	12	8104	20	2017
2425	8104052043	12	8104	27	2017
2426	8104052051	12	8104	1	2017
2427	8104052054	12	8104	16	2017
2428	8104052056	12	8104	1	2017
2429	8104052059	12	8104	13	2017
2430	8104052901	12	8104	6	2017
2431	8104062002	12	8104	1	2017
2432	8104062003	12	8104	4	2017
2433	8104062013	12	8104	6	2017
2434	8104062024	12	8104	2	2017
2435	8104062035	12	8104	1	2017
2436	8104062036	12	8104	1	2017
2437	8104062049	12	8104	21	2017
2438	8104062051	12	8104	3	2017
2439	8104062056	12	8104	6	2017
2440	8104062060	12	8104	1	2017
2441	8104062901	12	8104	9	2017
3226	8105012014	12	8105	4	2017
3227	8105012028	12	8105	9	2017
3228	8105012034	12	8105	6	2017
3229	8105022024	12	8105	1	2017
3230	8105022025	12	8105	12	2017
3231	8105022034	12	8105	1	2017
3232	8105022038	12	8105	2	2017
3233	8105022044	12	8105	1	2017
3234	8105022901	12	8105	3	2017
3235	8105032001	12	8105	2	2017
3236	8105032003	12	8105	2	2017

Agregamos un cero a los códigos comunales de cuatro dígitos:

codigos <- d$unlist.d.
rango <- seq(1:nrow(d))
cadena <- paste("0",codigos[rango], sep = "")
cadena <- substr(cadena,(nchar(cadena)[rango])-(4),6)
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
comuna_corr <- cbind(d,cadena)
comuna_corr <- comuna_corr[,-c(2,3),drop=FALSE]
names(comuna_corr)[4] <- "código" 
r3_100 <- comuna_corr[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	zona	Freq	anio	código
1	8101252025	9	2017	08101
2	8101282901	7	2017	08101
3	8101292012	6	2017	08101
4	8101292020	10	2017	08101
5	8101292023	7	2017	08101
6	8101292901	2	2017	08101
7	8101302001	24	2017	08101
8	8101302005	40	2017	08101
9	8101302008	12	2017	08101
10	8101302011	18	2017	08101
11	8101302016	4	2017	08101
12	8101302018	4	2017	08101
13	8101302019	10	2017	08101
14	8101302021	19	2017	08101
15	8101302024	2	2017	08101
16	8101302901	3	2017	08101
17	8101312001	4	2017	08101
18	8101312004	5	2017	08101
19	8101312013	94	2017	08101
20	8101312014	51	2017	08101
21	8101312017	7	2017	08101
22	8101322025	31	2017	08101
807	8102052001	9	2017	08102
808	8102062004	3	2017	08102
809	8102062005	118	2017	08102
810	8102062009	134	2017	08102
811	8102072005	95	2017	08102
812	8102082002	2	2017	08102
813	8102092010	13	2017	08102
814	8102102007	29	2017	08102
815	8102102011	16	2017	08102
816	8102112006	2	2017	08102
817	8102112008	20	2017	08102
1602	8103062006	6	2017	08103
1603	8103062901	1	2017	08103
2388	8104012005	2	2017	08104
2389	8104012023	24	2017	08104
2390	8104012029	2	2017	08104
2391	8104012037	11	2017	08104
2392	8104012043	7	2017	08104
2393	8104012044	16	2017	08104
2394	8104012052	8	2017	08104
2395	8104012054	1	2017	08104
2396	8104022001	5	2017	08104
2397	8104022023	3	2017	08104
2398	8104022035	2	2017	08104
2399	8104022036	7	2017	08104
2400	8104022040	4	2017	08104
2401	8104032004	7	2017	08104
2402	8104032007	2	2017	08104
2403	8104032012	6	2017	08104
2404	8104032028	20	2017	08104
2405	8104032045	7	2017	08104
2406	8104032050	1	2017	08104
2407	8104032053	2	2017	08104
2408	8104032901	3	2017	08104
2409	8104042012	40	2017	08104
2410	8104042014	8	2017	08104
2411	8104042017	3	2017	08104
2412	8104042030	1	2017	08104
2413	8104042042	4	2017	08104
2414	8104042043	3	2017	08104
2415	8104042047	3	2017	08104
2416	8104042062	9	2017	08104
2417	8104052003	6	2017	08104
2418	8104052010	4	2017	08104
2419	8104052025	1	2017	08104
2420	8104052027	4	2017	08104
2421	8104052029	1	2017	08104
2422	8104052031	7	2017	08104
2423	8104052032	4	2017	08104
2424	8104052039	20	2017	08104
2425	8104052043	27	2017	08104
2426	8104052051	1	2017	08104
2427	8104052054	16	2017	08104
2428	8104052056	1	2017	08104
2429	8104052059	13	2017	08104
2430	8104052901	6	2017	08104
2431	8104062002	1	2017	08104
2432	8104062003	4	2017	08104
2433	8104062013	6	2017	08104
2434	8104062024	2	2017	08104
2435	8104062035	1	2017	08104
2436	8104062036	1	2017	08104
2437	8104062049	21	2017	08104
2438	8104062051	3	2017	08104
2439	8104062056	6	2017	08104
2440	8104062060	1	2017	08104
2441	8104062901	9	2017	08104
3226	8105012014	4	2017	08105
3227	8105012028	9	2017	08105
3228	8105012034	6	2017	08105
3229	8105022024	1	2017	08105
3230	8105022025	12	2017	08105
3231	8105022034	1	2017	08105
3232	8105022038	2	2017	08105
3233	8105022044	1	2017	08105
3234	8105022901	3	2017	08105
3235	8105032001	2	2017	08105
3236	8105032003	2	2017	08105

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("../corre_ing_exp-censo_casen/Ingresos_expandidos_rural_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	personas	Ingresos_expandidos
01101	Iquique	272529.7	2017	191468	52180713221
01401	Pozo Almonte	243272.4	2017	15711	3822052676
01402	Camiña	226831.0	2017	1250	283538750
01404	Huara	236599.7	2017	2730	645917134
01405	Pica	269198.0	2017	9296	2502464414
02103	Sierra Gorda	322997.9	2017	10186	3290056742
02104	Taltal	288653.8	2017	13317	3844002134
02201	Calama	238080.9	2017	165731	39457387800
02203	San Pedro de Atacama	271472.6	2017	10996	2985112297
02301	Tocopilla	166115.9	2017	25186	4183793832
03101	Copiapó	251396.0	2017	153937	38699138722
03103	Tierra Amarilla	287819.4	2017	14019	4034940816
03202	Diego de Almagro	326439.0	2017	13925	4545663075
03301	Vallenar	217644.6	2017	51917	11299454698
03302	Alto del Carmen	196109.9	2017	5299	1039186477
03303	Freirina	202463.8	2017	7041	1425547554
03304	Huasco	205839.6	2017	10149	2089066548
04101	La Serena	200287.4	2017	221054	44274327972
04102	Coquimbo	206027.8	2017	227730	46918711304
04103	Andacollo	217096.4	2017	11044	2397612293
04104	La Higuera	231674.2	2017	4241	982530309
04105	Paiguano	174868.5	2017	4497	786383423
04106	Vicuña	169077.1	2017	27771	4695441470
04201	Illapel	165639.6	2017	30848	5109649759
04202	Canela	171370.3	2017	9093	1558270441
04203	Los Vilos	173238.5	2017	21382	3704185607
04204	Salamanca	193602.0	2017	29347	5681637894
04301	Ovalle	230819.8	2017	111272	25683781418
04302	Combarbalá	172709.2	2017	13322	2300832587
04303	Monte Patria	189761.6	2017	30751	5835357638
04304	Punitaqui	165862.0	2017	10956	1817183694
04305	Río Hurtado	182027.2	2017	4278	778712384
05101	Valparaíso	251998.5	2017	296655	74756602991
05102	Casablanca	252317.7	2017	26867	6779018483
05105	Puchuncaví	231606.0	2017	18546	4295363979
05107	Quintero	285125.8	2017	31923	9102071069
05301	Los Andes	280548.0	2017	66708	18714795984
05302	Calle Larga	234044.6	2017	14832	3471349123
05303	Rinconada	246136.9	2017	10207	2512319225
05304	San Esteban	211907.3	2017	18855	3995512770
05401	La Ligua	172675.9	2017	35390	6111000517
05402	Cabildo	212985.0	2017	19388	4129354103
05404	Petorca	270139.8	2017	9826	2654393853
05405	Zapallar	235661.4	2017	7339	1729518700
05501	Quillota	212067.6	2017	90517	19195726144
05502	Calera	226906.2	2017	50554	11471016698
05503	Hijuelas	215402.0	2017	17988	3874650405
05504	La Cruz	243333.4	2017	22098	5377180726
05506	Nogales	219800.7	2017	22120	4861992055
05601	San Antonio	230261.5	2017	91350	21034388728

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
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	personas	Ingresos_expandidos
1	08101	8101302001	24	2017	Concepción	197625.8	2017	223574	44183983882
2	08101	8101302018	4	2017	Concepción	197625.8	2017	223574	44183983882
3	08101	8101252025	9	2017	Concepción	197625.8	2017	223574	44183983882
4	08101	8101302024	2	2017	Concepción	197625.8	2017	223574	44183983882
5	08101	8101302901	3	2017	Concepción	197625.8	2017	223574	44183983882
6	08101	8101302019	10	2017	Concepción	197625.8	2017	223574	44183983882
7	08101	8101302021	19	2017	Concepción	197625.8	2017	223574	44183983882
8	08101	8101312013	94	2017	Concepción	197625.8	2017	223574	44183983882
9	08101	8101312014	51	2017	Concepción	197625.8	2017	223574	44183983882
10	08101	8101302005	40	2017	Concepción	197625.8	2017	223574	44183983882
11	08101	8101302008	12	2017	Concepción	197625.8	2017	223574	44183983882
12	08101	8101312004	5	2017	Concepción	197625.8	2017	223574	44183983882
13	08101	8101292023	7	2017	Concepción	197625.8	2017	223574	44183983882
14	08101	8101302011	18	2017	Concepción	197625.8	2017	223574	44183983882
15	08101	8101302016	4	2017	Concepción	197625.8	2017	223574	44183983882
16	08101	8101322025	31	2017	Concepción	197625.8	2017	223574	44183983882
17	08101	8101282901	7	2017	Concepción	197625.8	2017	223574	44183983882
18	08101	8101292901	2	2017	Concepción	197625.8	2017	223574	44183983882
19	08101	8101312001	4	2017	Concepción	197625.8	2017	223574	44183983882
20	08101	8101292012	6	2017	Concepción	197625.8	2017	223574	44183983882
21	08101	8101312017	7	2017	Concepción	197625.8	2017	223574	44183983882
22	08101	8101292020	10	2017	Concepción	197625.8	2017	223574	44183983882
23	08102	8102052001	9	2017	Coronel	217018.1	2017	116262	25230952648
24	08102	8102062004	3	2017	Coronel	217018.1	2017	116262	25230952648
25	08102	8102072005	95	2017	Coronel	217018.1	2017	116262	25230952648
26	08102	8102082002	2	2017	Coronel	217018.1	2017	116262	25230952648
27	08102	8102092010	13	2017	Coronel	217018.1	2017	116262	25230952648
28	08102	8102062009	134	2017	Coronel	217018.1	2017	116262	25230952648
29	08102	8102102011	16	2017	Coronel	217018.1	2017	116262	25230952648
30	08102	8102062005	118	2017	Coronel	217018.1	2017	116262	25230952648
31	08102	8102102007	29	2017	Coronel	217018.1	2017	116262	25230952648
32	08102	8102112006	2	2017	Coronel	217018.1	2017	116262	25230952648
33	08102	8102112008	20	2017	Coronel	217018.1	2017	116262	25230952648
36	08104	8104012005	2	2017	Florida	147425.2	2017	10624	1566245750
37	08104	8104012043	7	2017	Florida	147425.2	2017	10624	1566245750
38	08104	8104012023	24	2017	Florida	147425.2	2017	10624	1566245750
39	08104	8104022040	4	2017	Florida	147425.2	2017	10624	1566245750
40	08104	8104012044	16	2017	Florida	147425.2	2017	10624	1566245750
41	08104	8104012052	8	2017	Florida	147425.2	2017	10624	1566245750
42	08104	8104022036	7	2017	Florida	147425.2	2017	10624	1566245750
43	08104	8104012037	11	2017	Florida	147425.2	2017	10624	1566245750
44	08104	8104032004	7	2017	Florida	147425.2	2017	10624	1566245750
45	08104	8104032007	2	2017	Florida	147425.2	2017	10624	1566245750
46	08104	8104012029	2	2017	Florida	147425.2	2017	10624	1566245750
47	08104	8104032901	3	2017	Florida	147425.2	2017	10624	1566245750
48	08104	8104032045	7	2017	Florida	147425.2	2017	10624	1566245750
49	08104	8104032050	1	2017	Florida	147425.2	2017	10624	1566245750
50	08104	8104032053	2	2017	Florida	147425.2	2017	10624	1566245750
51	08104	8104042030	1	2017	Florida	147425.2	2017	10624	1566245750
52	08104	8104042042	4	2017	Florida	147425.2	2017	10624	1566245750
53	08104	8104042043	3	2017	Florida	147425.2	2017	10624	1566245750
54	08104	8104042047	3	2017	Florida	147425.2	2017	10624	1566245750
55	08104	8104042062	9	2017	Florida	147425.2	2017	10624	1566245750
56	08104	8104052003	6	2017	Florida	147425.2	2017	10624	1566245750
57	08104	8104052010	4	2017	Florida	147425.2	2017	10624	1566245750
58	08104	8104052025	1	2017	Florida	147425.2	2017	10624	1566245750
59	08104	8104052027	4	2017	Florida	147425.2	2017	10624	1566245750
60	08104	8104052029	1	2017	Florida	147425.2	2017	10624	1566245750
61	08104	8104042012	40	2017	Florida	147425.2	2017	10624	1566245750
62	08104	8104042014	8	2017	Florida	147425.2	2017	10624	1566245750
63	08104	8104042017	3	2017	Florida	147425.2	2017	10624	1566245750
64	08104	8104052043	27	2017	Florida	147425.2	2017	10624	1566245750
65	08104	8104052051	1	2017	Florida	147425.2	2017	10624	1566245750
66	08104	8104052054	16	2017	Florida	147425.2	2017	10624	1566245750
67	08104	8104052056	1	2017	Florida	147425.2	2017	10624	1566245750
68	08104	8104052059	13	2017	Florida	147425.2	2017	10624	1566245750
69	08104	8104052901	6	2017	Florida	147425.2	2017	10624	1566245750
70	08104	8104062002	1	2017	Florida	147425.2	2017	10624	1566245750
71	08104	8104062003	4	2017	Florida	147425.2	2017	10624	1566245750
72	08104	8104062013	6	2017	Florida	147425.2	2017	10624	1566245750
73	08104	8104062024	2	2017	Florida	147425.2	2017	10624	1566245750
74	08104	8104052031	7	2017	Florida	147425.2	2017	10624	1566245750
75	08104	8104052032	4	2017	Florida	147425.2	2017	10624	1566245750
76	08104	8104052039	20	2017	Florida	147425.2	2017	10624	1566245750
77	08104	8104022035	2	2017	Florida	147425.2	2017	10624	1566245750
78	08104	8104062056	6	2017	Florida	147425.2	2017	10624	1566245750
79	08104	8104062060	1	2017	Florida	147425.2	2017	10624	1566245750
80	08104	8104062901	9	2017	Florida	147425.2	2017	10624	1566245750
81	08104	8104022001	5	2017	Florida	147425.2	2017	10624	1566245750
82	08104	8104032012	6	2017	Florida	147425.2	2017	10624	1566245750
83	08104	8104032028	20	2017	Florida	147425.2	2017	10624	1566245750
84	08104	8104012054	1	2017	Florida	147425.2	2017	10624	1566245750
85	08104	8104022023	3	2017	Florida	147425.2	2017	10624	1566245750
86	08104	8104062049	21	2017	Florida	147425.2	2017	10624	1566245750
87	08104	8104062051	3	2017	Florida	147425.2	2017	10624	1566245750
88	08104	8104062035	1	2017	Florida	147425.2	2017	10624	1566245750
89	08104	8104062036	1	2017	Florida	147425.2	2017	10624	1566245750
90	08105	8105012014	4	2017	Hualqui	202715.1	2017	24333	4932666876
91	08105	8105022025	12	2017	Hualqui	202715.1	2017	24333	4932666876
92	08105	8105022034	1	2017	Hualqui	202715.1	2017	24333	4932666876
93	08105	8105032039	3	2017	Hualqui	202715.1	2017	24333	4932666876
94	08105	8105032901	1	2017	Hualqui	202715.1	2017	24333	4932666876
95	08105	8105022038	2	2017	Hualqui	202715.1	2017	24333	4932666876
96	08105	8105022024	1	2017	Hualqui	202715.1	2017	24333	4932666876
97	08105	8105042023	5	2017	Hualqui	202715.1	2017	24333	4932666876
98	08105	8105042031	13	2017	Hualqui	202715.1	2017	24333	4932666876
99	08105	8105042001	6	2017	Hualqui	202715.1	2017	24333	4932666876
100	08105	8105042007	16	2017	Hualqui	202715.1	2017	24333	4932666876
101	08105	8105022044	1	2017	Hualqui	202715.1	2017	24333	4932666876
102	08105	8105022901	3	2017	Hualqui	202715.1	2017	24333	4932666876
103	08105	8105052015	1	2017	Hualqui	202715.1	2017	24333	4932666876
104	08105	8105062017	5	2017	Hualqui	202715.1	2017	24333	4932666876
105	08105	8105032034	1	2017	Hualqui	202715.1	2017	24333	4932666876
106	08105	8105082026	3	2017	Hualqui	202715.1	2017	24333	4932666876
107	08105	8105082051	13	2017	Hualqui	202715.1	2017	24333	4932666876
108	08105	8105092008	4	2017	Hualqui	202715.1	2017	24333	4932666876
109	08105	8105092041	28	2017	Hualqui	202715.1	2017	24333	4932666876
110	08105	8105092901	6	2017	Hualqui	202715.1	2017	24333	4932666876
111	08105	8105102007	11	2017	Hualqui	202715.1	2017	24333	4932666876
112	08105	8105102040	22	2017	Hualqui	202715.1	2017	24333	4932666876
113	08105	8105102046	1	2017	Hualqui	202715.1	2017	24333	4932666876
114	08105	8105062901	3	2017	Hualqui	202715.1	2017	24333	4932666876
115	08105	8105072048	1	2017	Hualqui	202715.1	2017	24333	4932666876
116	08105	8105032001	2	2017	Hualqui	202715.1	2017	24333	4932666876
117	08105	8105032003	2	2017	Hualqui	202715.1	2017	24333	4932666876
118	08105	8105082010	1	2017	Hualqui	202715.1	2017	24333	4932666876
119	08105	8105012034	6	2017	Hualqui	202715.1	2017	24333	4932666876
120	08105	8105072053	1	2017	Hualqui	202715.1	2017	24333	4932666876
121	08105	8105012028	9	2017	Hualqui	202715.1	2017	24333	4932666876
122	08105	8105082006	1	2017	Hualqui	202715.1	2017	24333	4932666876
126	08107	8107052901	1	2017	Penco	195212.7	2017	47367	9246639961
127	08107	8107042014	1	2017	Penco	195212.7	2017	47367	9246639961
128	08107	8107032014	4	2017	Penco	195212.7	2017	47367	9246639961
129	08107	8107062901	3	2017	Penco	195212.7	2017	47367	9246639961
130	08107	8107032005	1	2017	Penco	195212.7	2017	47367	9246639961
133	08109	8109012002	1	2017	Santa Juana	198449.1	2017	13749	2728477197
134	08109	8109012009	3	2017	Santa Juana	198449.1	2017	13749	2728477197
135	08109	8109012029	26	2017	Santa Juana	198449.1	2017	13749	2728477197
136	08109	8109012033	14	2017	Santa Juana	198449.1	2017	13749	2728477197
137	08109	8109022012	18	2017	Santa Juana	198449.1	2017	13749	2728477197
138	08109	8109042001	1	2017	Santa Juana	198449.1	2017	13749	2728477197
139	08109	8109042010	8	2017	Santa Juana	198449.1	2017	13749	2728477197
140	08109	8109042014	1	2017	Santa Juana	198449.1	2017	13749	2728477197
141	08109	8109042030	4	2017	Santa Juana	198449.1	2017	13749	2728477197
142	08109	8109042031	3	2017	Santa Juana	198449.1	2017	13749	2728477197
143	08109	8109052004	3	2017	Santa Juana	198449.1	2017	13749	2728477197
144	08109	8109052007	3	2017	Santa Juana	198449.1	2017	13749	2728477197
145	08109	8109052008	4	2017	Santa Juana	198449.1	2017	13749	2728477197
146	08109	8109052015	2	2017	Santa Juana	198449.1	2017	13749	2728477197
147	08109	8109022023	4	2017	Santa Juana	198449.1	2017	13749	2728477197
148	08109	8109022032	3	2017	Santa Juana	198449.1	2017	13749	2728477197
149	08109	8109032005	1	2017	Santa Juana	198449.1	2017	13749	2728477197
150	08109	8109032030	2	2017	Santa Juana	198449.1	2017	13749	2728477197
151	08109	8109072026	1	2017	Santa Juana	198449.1	2017	13749	2728477197
152	08109	8109072028	5	2017	Santa Juana	198449.1	2017	13749	2728477197
153	08109	8109082011	3	2017	Santa Juana	198449.1	2017	13749	2728477197
154	08109	8109082013	4	2017	Santa Juana	198449.1	2017	13749	2728477197
155	08109	8109102009	3	2017	Santa Juana	198449.1	2017	13749	2728477197
156	08109	8109102012	14	2017	Santa Juana	198449.1	2017	13749	2728477197
157	08109	8109102035	1	2017	Santa Juana	198449.1	2017	13749	2728477197
158	08109	8109112006	3	2017	Santa Juana	198449.1	2017	13749	2728477197
159	08109	8109112020	3	2017	Santa Juana	198449.1	2017	13749	2728477197
160	08109	8109062009	11	2017	Santa Juana	198449.1	2017	13749	2728477197
161	08109	8109062025	16	2017	Santa Juana	198449.1	2017	13749	2728477197
162	08109	8109072004	8	2017	Santa Juana	198449.1	2017	13749	2728477197
163	08109	8109072024	3	2017	Santa Juana	198449.1	2017	13749	2728477197
164	08110	8110072004	51	2017	Talcahuano	161731.1	2017	151749	24542535584
165	08110	8110142002	6	2017	Talcahuano	161731.1	2017	151749	24542535584
166	08111	8111022024	8	2017	Tomé	210053.2	2017	54946	11541584520
167	08111	8111022045	3	2017	Tomé	210053.2	2017	54946	11541584520
168	08111	8111042006	25	2017	Tomé	210053.2	2017	54946	11541584520
169	08111	8111042022	49	2017	Tomé	210053.2	2017	54946	11541584520
170	08111	8111022901	1	2017	Tomé	210053.2	2017	54946	11541584520
171	08111	8111032901	6	2017	Tomé	210053.2	2017	54946	11541584520
172	08111	8111062031	2	2017	Tomé	210053.2	2017	54946	11541584520
173	08111	8111062901	6	2017	Tomé	210053.2	2017	54946	11541584520
174	08111	8111052025	11	2017	Tomé	210053.2	2017	54946	11541584520
175	08111	8111062027	1	2017	Tomé	210053.2	2017	54946	11541584520
176	08111	8111072028	6	2017	Tomé	210053.2	2017	54946	11541584520
177	08111	8111072030	1	2017	Tomé	210053.2	2017	54946	11541584520
178	08111	8111072034	10	2017	Tomé	210053.2	2017	54946	11541584520
179	08111	8111072035	9	2017	Tomé	210053.2	2017	54946	11541584520
180	08111	8111072038	8	2017	Tomé	210053.2	2017	54946	11541584520
181	08111	8111072039	5	2017	Tomé	210053.2	2017	54946	11541584520
182	08111	8111082007	1	2017	Tomé	210053.2	2017	54946	11541584520
183	08111	8111082009	3	2017	Tomé	210053.2	2017	54946	11541584520
184	08111	8111082020	9	2017	Tomé	210053.2	2017	54946	11541584520
185	08111	8111082026	1	2017	Tomé	210053.2	2017	54946	11541584520
186	08111	8111082036	1	2017	Tomé	210053.2	2017	54946	11541584520
187	08111	8111072003	17	2017	Tomé	210053.2	2017	54946	11541584520
188	08111	8111072023	5	2017	Tomé	210053.2	2017	54946	11541584520
189	08111	8111092026	3	2017	Tomé	210053.2	2017	54946	11541584520
190	08111	8111092035	9	2017	Tomé	210053.2	2017	54946	11541584520
191	08111	8111092036	1	2017	Tomé	210053.2	2017	54946	11541584520
192	08111	8111092037	7	2017	Tomé	210053.2	2017	54946	11541584520
193	08111	8111092901	4	2017	Tomé	210053.2	2017	54946	11541584520
194	08111	8111102008	3	2017	Tomé	210053.2	2017	54946	11541584520
195	08111	8111102014	6	2017	Tomé	210053.2	2017	54946	11541584520
196	08111	8111102028	1	2017	Tomé	210053.2	2017	54946	11541584520
197	08111	8111102038	3	2017	Tomé	210053.2	2017	54946	11541584520
198	08111	8111112001	1	2017	Tomé	210053.2	2017	54946	11541584520
199	08111	8111112032	110	2017	Tomé	210053.2	2017	54946	11541584520
200	08111	8111082042	3	2017	Tomé	210053.2	2017	54946	11541584520
201	08111	8111092010	4	2017	Tomé	210053.2	2017	54946	11541584520
202	08111	8111012021	3	2017	Tomé	210053.2	2017	54946	11541584520
203	08111	8111022023	2	2017	Tomé	210053.2	2017	54946	11541584520
208	08201	8201012016	5	2017	Lebu	141842.6	2017	25522	3620107931
209	08201	8201022018	25	2017	Lebu	141842.6	2017	25522	3620107931
210	08201	8201022901	1	2017	Lebu	141842.6	2017	25522	3620107931
211	08201	8201032002	1	2017	Lebu	141842.6	2017	25522	3620107931
212	08201	8201032022	6	2017	Lebu	141842.6	2017	25522	3620107931
213	08201	8201032027	2	2017	Lebu	141842.6	2017	25522	3620107931
214	08201	8201032030	3	2017	Lebu	141842.6	2017	25522	3620107931
215	08201	8201052028	2	2017	Lebu	141842.6	2017	25522	3620107931
216	08201	8201052901	1	2017	Lebu	141842.6	2017	25522	3620107931
217	08201	8201062007	2	2017	Lebu	141842.6	2017	25522	3620107931
218	08201	8201072001	1	2017	Lebu	141842.6	2017	25522	3620107931
219	08201	8201072004	1	2017	Lebu	141842.6	2017	25522	3620107931
220	08201	8201072019	1	2017	Lebu	141842.6	2017	25522	3620107931
221	08201	8201072020	7	2017	Lebu	141842.6	2017	25522	3620107931
222	08201	8201072023	6	2017	Lebu	141842.6	2017	25522	3620107931
223	08201	8201072031	1	2017	Lebu	141842.6	2017	25522	3620107931
224	08201	8201082006	4	2017	Lebu	141842.6	2017	25522	3620107931
225	08201	8201082014	2	2017	Lebu	141842.6	2017	25522	3620107931
226	08201	8201082901	2	2017	Lebu	141842.6	2017	25522	3620107931
227	08201	8201092011	20	2017	Lebu	141842.6	2017	25522	3620107931
228	08201	8201102012	1	2017	Lebu	141842.6	2017	25522	3620107931
229	08202	8202012016	2	2017	Arauco	184849.0	2017	36257	6702069405
230	08202	8202022005	8	2017	Arauco	184849.0	2017	36257	6702069405
231	08202	8202022009	7	2017	Arauco	184849.0	2017	36257	6702069405
232	08202	8202022014	26	2017	Arauco	184849.0	2017	36257	6702069405
233	08202	8202032017	5	2017	Arauco	184849.0	2017	36257	6702069405
234	08202	8202032026	26	2017	Arauco	184849.0	2017	36257	6702069405
235	08202	8202032031	33	2017	Arauco	184849.0	2017	36257	6702069405
236	08202	8202042003	2	2017	Arauco	184849.0	2017	36257	6702069405
237	08202	8202042007	8	2017	Arauco	184849.0	2017	36257	6702069405
238	08202	8202042012	2	2017	Arauco	184849.0	2017	36257	6702069405
239	08202	8202042015	3	2017	Arauco	184849.0	2017	36257	6702069405
240	08202	8202042901	1	2017	Arauco	184849.0	2017	36257	6702069405
241	08202	8202052010	23	2017	Arauco	184849.0	2017	36257	6702069405
242	08202	8202052018	8	2017	Arauco	184849.0	2017	36257	6702069405
243	08202	8202052019	7	2017	Arauco	184849.0	2017	36257	6702069405
244	08202	8202052022	3	2017	Arauco	184849.0	2017	36257	6702069405
245	08202	8202052023	3	2017	Arauco	184849.0	2017	36257	6702069405
246	08202	8202052024	1	2017	Arauco	184849.0	2017	36257	6702069405
247	08202	8202052025	2	2017	Arauco	184849.0	2017	36257	6702069405
248	08202	8202052032	1	2017	Arauco	184849.0	2017	36257	6702069405
249	08202	8202062006	3	2017	Arauco	184849.0	2017	36257	6702069405
250	08202	8202062011	1	2017	Arauco	184849.0	2017	36257	6702069405
251	08202	8202062019	3	2017	Arauco	184849.0	2017	36257	6702069405
252	08202	8202062032	1	2017	Arauco	184849.0	2017	36257	6702069405
253	08202	8202072035	45	2017	Arauco	184849.0	2017	36257	6702069405
254	08202	8202082001	1	2017	Arauco	184849.0	2017	36257	6702069405
255	08202	8202082013	1	2017	Arauco	184849.0	2017	36257	6702069405
256	08202	8202082020	13	2017	Arauco	184849.0	2017	36257	6702069405
257	08202	8202082028	29	2017	Arauco	184849.0	2017	36257	6702069405
258	08202	8202082033	3	2017	Arauco	184849.0	2017	36257	6702069405
259	08202	8202092029	2	2017	Arauco	184849.0	2017	36257	6702069405
260	08202	8202092030	7	2017	Arauco	184849.0	2017	36257	6702069405
261	08203	8203012024	5	2017	Cañete	186912.3	2017	34537	6455391501
262	08203	8203012030	1	2017	Cañete	186912.3	2017	34537	6455391501
263	08203	8203012043	4	2017	Cañete	186912.3	2017	34537	6455391501
264	08203	8203022006	7	2017	Cañete	186912.3	2017	34537	6455391501
265	08203	8203022015	13	2017	Cañete	186912.3	2017	34537	6455391501
266	08203	8203022041	15	2017	Cañete	186912.3	2017	34537	6455391501
267	08203	8203032006	8	2017	Cañete	186912.3	2017	34537	6455391501
268	08203	8203032020	56	2017	Cañete	186912.3	2017	34537	6455391501
269	08203	8203032022	15	2017	Cañete	186912.3	2017	34537	6455391501
270	08203	8203032038	6	2017	Cañete	186912.3	2017	34537	6455391501
271	08203	8203032901	9	2017	Cañete	186912.3	2017	34537	6455391501
272	08203	8203042901	1	2017	Cañete	186912.3	2017	34537	6455391501
273	08203	8203052901	1	2017	Cañete	186912.3	2017	34537	6455391501
274	08203	8203062009	20	2017	Cañete	186912.3	2017	34537	6455391501
275	08203	8203062037	3	2017	Cañete	186912.3	2017	34537	6455391501
276	08203	8203062045	18	2017	Cañete	186912.3	2017	34537	6455391501
277	08203	8203062901	1	2017	Cañete	186912.3	2017	34537	6455391501
278	08203	8203072018	84	2017	Cañete	186912.3	2017	34537	6455391501
279	08203	8203072021	20	2017	Cañete	186912.3	2017	34537	6455391501
280	08203	8203072033	55	2017	Cañete	186912.3	2017	34537	6455391501
281	08203	8203072039	5	2017	Cañete	186912.3	2017	34537	6455391501
282	08203	8203072042	4	2017	Cañete	186912.3	2017	34537	6455391501
283	08203	8203082026	5	2017	Cañete	186912.3	2017	34537	6455391501
284	08203	8203082029	9	2017	Cañete	186912.3	2017	34537	6455391501
285	08203	8203082031	3	2017	Cañete	186912.3	2017	34537	6455391501
286	08203	8203082032	10	2017	Cañete	186912.3	2017	34537	6455391501
287	08203	8203082036	12	2017	Cañete	186912.3	2017	34537	6455391501
288	08203	8203082901	1	2017	Cañete	186912.3	2017	34537	6455391501
289	08203	8203092011	3	2017	Cañete	186912.3	2017	34537	6455391501
290	08203	8203092020	70	2017	Cañete	186912.3	2017	34537	6455391501
291	08203	8203092027	15	2017	Cañete	186912.3	2017	34537	6455391501
292	08203	8203092046	17	2017	Cañete	186912.3	2017	34537	6455391501
293	08203	8203092047	24	2017	Cañete	186912.3	2017	34537	6455391501
294	08203	8203102017	15	2017	Cañete	186912.3	2017	34537	6455391501
295	08203	8203102019	9	2017	Cañete	186912.3	2017	34537	6455391501
296	08203	8203102023	12	2017	Cañete	186912.3	2017	34537	6455391501
297	08203	8203102044	2	2017	Cañete	186912.3	2017	34537	6455391501
298	08203	8203112035	5	2017	Cañete	186912.3	2017	34537	6455391501
299	08203	8203122001	1	2017	Cañete	186912.3	2017	34537	6455391501
300	08203	8203122003	4	2017	Cañete	186912.3	2017	34537	6455391501
301	08203	8203122025	8	2017	Cañete	186912.3	2017	34537	6455391501
302	08203	8203122028	22	2017	Cañete	186912.3	2017	34537	6455391501
303	08204	8204012001	8	2017	Contulmo	131551.5	2017	6031	793386801
304	08204	8204012012	1	2017	Contulmo	131551.5	2017	6031	793386801
305	08204	8204012014	4	2017	Contulmo	131551.5	2017	6031	793386801
306	08204	8204012023	14	2017	Contulmo	131551.5	2017	6031	793386801
307	08204	8204012035	7	2017	Contulmo	131551.5	2017	6031	793386801
308	08204	8204012901	3	2017	Contulmo	131551.5	2017	6031	793386801
309	08204	8204022003	1	2017	Contulmo	131551.5	2017	6031	793386801
310	08204	8204022007	1	2017	Contulmo	131551.5	2017	6031	793386801
311	08204	8204022020	1	2017	Contulmo	131551.5	2017	6031	793386801
312	08204	8204022033	1	2017	Contulmo	131551.5	2017	6031	793386801
313	08204	8204032017	4	2017	Contulmo	131551.5	2017	6031	793386801
314	08204	8204032018	2	2017	Contulmo	131551.5	2017	6031	793386801
315	08204	8204032028	2	2017	Contulmo	131551.5	2017	6031	793386801
316	08204	8204032901	2	2017	Contulmo	131551.5	2017	6031	793386801
317	08204	8204042002	13	2017	Contulmo	131551.5	2017	6031	793386801
318	08204	8204042013	18	2017	Contulmo	131551.5	2017	6031	793386801
319	08204	8204042022	5	2017	Contulmo	131551.5	2017	6031	793386801
320	08204	8204042026	2	2017	Contulmo	131551.5	2017	6031	793386801
321	08204	8204042031	2	2017	Contulmo	131551.5	2017	6031	793386801
322	08204	8204042901	6	2017	Contulmo	131551.5	2017	6031	793386801
323	08205	8205022028	4	2017	Curanilahue	252073.4	2017	32288	8138946477
324	08205	8205032023	25	2017	Curanilahue	252073.4	2017	32288	8138946477
325	08205	8205042014	1	2017	Curanilahue	252073.4	2017	32288	8138946477
326	08205	8205042026	15	2017	Curanilahue	252073.4	2017	32288	8138946477
327	08205	8205042901	1	2017	Curanilahue	252073.4	2017	32288	8138946477
328	08205	8205062003	4	2017	Curanilahue	252073.4	2017	32288	8138946477
329	08205	8205072001	4	2017	Curanilahue	252073.4	2017	32288	8138946477
330	08205	8205082901	1	2017	Curanilahue	252073.4	2017	32288	8138946477
331	08205	8205092901	1	2017	Curanilahue	252073.4	2017	32288	8138946477
332	08206	8206012010	11	2017	Los Álamos	189429.4	2017	21035	3984647129
333	08206	8206012012	2	2017	Los Álamos	189429.4	2017	21035	3984647129
334	08206	8206012014	2	2017	Los Álamos	189429.4	2017	21035	3984647129
335	08206	8206012015	1	2017	Los Álamos	189429.4	2017	21035	3984647129
336	08206	8206012017	8	2017	Los Álamos	189429.4	2017	21035	3984647129
337	08206	8206012901	1	2017	Los Álamos	189429.4	2017	21035	3984647129
338	08206	8206022010	3	2017	Los Álamos	189429.4	2017	21035	3984647129
339	08206	8206022018	2	2017	Los Álamos	189429.4	2017	21035	3984647129
340	08206	8206032901	4	2017	Los Álamos	189429.4	2017	21035	3984647129
341	08206	8206042001	12	2017	Los Álamos	189429.4	2017	21035	3984647129
342	08206	8206042003	5	2017	Los Álamos	189429.4	2017	21035	3984647129
343	08206	8206052011	5	2017	Los Álamos	189429.4	2017	21035	3984647129
344	08206	8206052015	8	2017	Los Álamos	189429.4	2017	21035	3984647129
345	08206	8206052016	11	2017	Los Álamos	189429.4	2017	21035	3984647129
346	08207	8207012016	5	2017	Tirúa	144994.9	2017	10417	1510411713
347	08207	8207012019	6	2017	Tirúa	144994.9	2017	10417	1510411713
348	08207	8207012033	5	2017	Tirúa	144994.9	2017	10417	1510411713
349	08207	8207012036	7	2017	Tirúa	144994.9	2017	10417	1510411713
350	08207	8207012037	20	2017	Tirúa	144994.9	2017	10417	1510411713
351	08207	8207012038	19	2017	Tirúa	144994.9	2017	10417	1510411713
352	08207	8207012041	44	2017	Tirúa	144994.9	2017	10417	1510411713
353	08207	8207022012	3	2017	Tirúa	144994.9	2017	10417	1510411713
354	08207	8207022013	2	2017	Tirúa	144994.9	2017	10417	1510411713
355	08207	8207022030	6	2017	Tirúa	144994.9	2017	10417	1510411713
356	08207	8207032001	2	2017	Tirúa	144994.9	2017	10417	1510411713
357	08207	8207032007	1	2017	Tirúa	144994.9	2017	10417	1510411713
358	08207	8207032010	3	2017	Tirúa	144994.9	2017	10417	1510411713
359	08207	8207032023	1	2017	Tirúa	144994.9	2017	10417	1510411713
360	08207	8207032024	9	2017	Tirúa	144994.9	2017	10417	1510411713
361	08207	8207032030	6	2017	Tirúa	144994.9	2017	10417	1510411713
362	08207	8207042006	1	2017	Tirúa	144994.9	2017	10417	1510411713
363	08207	8207042008	1	2017	Tirúa	144994.9	2017	10417	1510411713
364	08207	8207042014	1	2017	Tirúa	144994.9	2017	10417	1510411713
365	08207	8207042020	1	2017	Tirúa	144994.9	2017	10417	1510411713
366	08207	8207042029	3	2017	Tirúa	144994.9	2017	10417	1510411713
367	08207	8207042031	4	2017	Tirúa	144994.9	2017	10417	1510411713
368	08207	8207042032	11	2017	Tirúa	144994.9	2017	10417	1510411713
369	08207	8207042035	10	2017	Tirúa	144994.9	2017	10417	1510411713
370	08207	8207042040	9	2017	Tirúa	144994.9	2017	10417	1510411713
371	08207	8207042042	5	2017	Tirúa	144994.9	2017	10417	1510411713
372	08301	8301042015	114	2017	Los Ángeles	190810.3	2017	202331	38606846296
373	08301	8301042045	36	2017	Los Ángeles	190810.3	2017	202331	38606846296
374	08301	8301042049	8	2017	Los Ángeles	190810.3	2017	202331	38606846296
375	08301	8301052005	68	2017	Los Ángeles	190810.3	2017	202331	38606846296
376	08301	8301052037	5	2017	Los Ángeles	190810.3	2017	202331	38606846296
377	08301	8301052066	75	2017	Los Ángeles	190810.3	2017	202331	38606846296
378	08301	8301062029	35	2017	Los Ángeles	190810.3	2017	202331	38606846296
379	08301	8301062030	40	2017	Los Ángeles	190810.3	2017	202331	38606846296
380	08301	8301062041	25	2017	Los Ángeles	190810.3	2017	202331	38606846296
381	08301	8301062053	26	2017	Los Ángeles	190810.3	2017	202331	38606846296
382	08301	8301062054	24	2017	Los Ángeles	190810.3	2017	202331	38606846296
383	08301	8301062056	59	2017	Los Ángeles	190810.3	2017	202331	38606846296
384	08301	8301072012	144	2017	Los Ángeles	190810.3	2017	202331	38606846296
385	08301	8301072016	30	2017	Los Ángeles	190810.3	2017	202331	38606846296
386	08301	8301072023	33	2017	Los Ángeles	190810.3	2017	202331	38606846296
387	08301	8301072031	2	2017	Los Ángeles	190810.3	2017	202331	38606846296
388	08301	8301072055	93	2017	Los Ángeles	190810.3	2017	202331	38606846296
389	08301	8301072060	41	2017	Los Ángeles	190810.3	2017	202331	38606846296
390	08301	8301082001	8	2017	Los Ángeles	190810.3	2017	202331	38606846296
391	08301	8301082019	36	2017	Los Ángeles	190810.3	2017	202331	38606846296
392	08301	8301082022	5	2017	Los Ángeles	190810.3	2017	202331	38606846296
393	08301	8301082026	52	2017	Los Ángeles	190810.3	2017	202331	38606846296
394	08301	8301082038	30	2017	Los Ángeles	190810.3	2017	202331	38606846296
395	08301	8301092028	24	2017	Los Ángeles	190810.3	2017	202331	38606846296
396	08301	8301092040	10	2017	Los Ángeles	190810.3	2017	202331	38606846296
397	08301	8301092048	71	2017	Los Ángeles	190810.3	2017	202331	38606846296
398	08301	8301092050	68	2017	Los Ángeles	190810.3	2017	202331	38606846296
399	08301	8301092051	8	2017	Los Ángeles	190810.3	2017	202331	38606846296
400	08301	8301102006	21	2017	Los Ángeles	190810.3	2017	202331	38606846296
401	08301	8301102043	35	2017	Los Ángeles	190810.3	2017	202331	38606846296
402	08301	8301102058	36	2017	Los Ángeles	190810.3	2017	202331	38606846296
403	08301	8301102059	251	2017	Los Ángeles	190810.3	2017	202331	38606846296
404	08301	8301102060	63	2017	Los Ángeles	190810.3	2017	202331	38606846296
405	08301	8301112002	54	2017	Los Ángeles	190810.3	2017	202331	38606846296
406	08301	8301112003	78	2017	Los Ángeles	190810.3	2017	202331	38606846296
407	08301	8301112004	385	2017	Los Ángeles	190810.3	2017	202331	38606846296
408	08301	8301112018	48	2017	Los Ángeles	190810.3	2017	202331	38606846296
409	08301	8301112024	3	2017	Los Ángeles	190810.3	2017	202331	38606846296
410	08301	8301112033	17	2017	Los Ángeles	190810.3	2017	202331	38606846296
411	08301	8301112039	315	2017	Los Ángeles	190810.3	2017	202331	38606846296
412	08301	8301112044	187	2017	Los Ángeles	190810.3	2017	202331	38606846296
413	08301	8301112062	14	2017	Los Ángeles	190810.3	2017	202331	38606846296
414	08301	8301112064	5	2017	Los Ángeles	190810.3	2017	202331	38606846296
415	08301	8301122008	168	2017	Los Ángeles	190810.3	2017	202331	38606846296
416	08301	8301122009	87	2017	Los Ángeles	190810.3	2017	202331	38606846296
417	08301	8301132021	149	2017	Los Ángeles	190810.3	2017	202331	38606846296
418	08301	8301132027	18	2017	Los Ángeles	190810.3	2017	202331	38606846296
419	08301	8301142011	195	2017	Los Ángeles	190810.3	2017	202331	38606846296
420	08301	8301142013	45	2017	Los Ángeles	190810.3	2017	202331	38606846296
421	08301	8301142027	20	2017	Los Ángeles	190810.3	2017	202331	38606846296
422	08301	8301142032	24	2017	Los Ángeles	190810.3	2017	202331	38606846296
423	08301	8301152013	8	2017	Los Ángeles	190810.3	2017	202331	38606846296
424	08301	8301152036	3	2017	Los Ángeles	190810.3	2017	202331	38606846296
425	08301	8301152057	10	2017	Los Ángeles	190810.3	2017	202331	38606846296
426	08301	8301162013	15	2017	Los Ángeles	190810.3	2017	202331	38606846296
427	08301	8301162025	9	2017	Los Ángeles	190810.3	2017	202331	38606846296
428	08301	8301172013	9	2017	Los Ángeles	190810.3	2017	202331	38606846296
429	08301	8301172034	1	2017	Los Ángeles	190810.3	2017	202331	38606846296
430	08301	8301172045	132	2017	Los Ángeles	190810.3	2017	202331	38606846296
431	08301	8301172046	91	2017	Los Ángeles	190810.3	2017	202331	38606846296
432	08301	8301172047	16	2017	Los Ángeles	190810.3	2017	202331	38606846296
433	08301	8301172065	150	2017	Los Ángeles	190810.3	2017	202331	38606846296
434	08301	8301182007	33	2017	Los Ángeles	190810.3	2017	202331	38606846296
435	08301	8301182010	36	2017	Los Ángeles	190810.3	2017	202331	38606846296
436	08301	8301182014	53	2017	Los Ángeles	190810.3	2017	202331	38606846296
437	08301	8301182015	97	2017	Los Ángeles	190810.3	2017	202331	38606846296
438	08301	8301182020	14	2017	Los Ángeles	190810.3	2017	202331	38606846296
439	08301	8301182049	35	2017	Los Ángeles	190810.3	2017	202331	38606846296
440	08301	8301192042	22	2017	Los Ángeles	190810.3	2017	202331	38606846296
441	08301	8301192061	49	2017	Los Ángeles	190810.3	2017	202331	38606846296
442	08301	8301202017	2	2017	Los Ángeles	190810.3	2017	202331	38606846296
443	08302	8302012002	5	2017	Antuco	155662.3	2017	4073	634012722
444	08302	8302012003	10	2017	Antuco	155662.3	2017	4073	634012722
445	08302	8302012008	13	2017	Antuco	155662.3	2017	4073	634012722
446	08302	8302012010	17	2017	Antuco	155662.3	2017	4073	634012722
447	08302	8302012014	27	2017	Antuco	155662.3	2017	4073	634012722
448	08302	8302012015	12	2017	Antuco	155662.3	2017	4073	634012722
449	08302	8302022013	2	2017	Antuco	155662.3	2017	4073	634012722
450	08302	8302042001	6	2017	Antuco	155662.3	2017	4073	634012722
451	08302	8302042004	5	2017	Antuco	155662.3	2017	4073	634012722
452	08302	8302042901	5	2017	Antuco	155662.3	2017	4073	634012722
453	08303	8303012002	1	2017	Cabrero	249163.0	2017	28573	7119335384
454	08303	8303012010	9	2017	Cabrero	249163.0	2017	28573	7119335384
455	08303	8303012014	4	2017	Cabrero	249163.0	2017	28573	7119335384
456	08303	8303012020	3	2017	Cabrero	249163.0	2017	28573	7119335384
457	08303	8303012023	2	2017	Cabrero	249163.0	2017	28573	7119335384
458	08303	8303012026	9	2017	Cabrero	249163.0	2017	28573	7119335384
459	08303	8303012030	4	2017	Cabrero	249163.0	2017	28573	7119335384
460	08303	8303012034	8	2017	Cabrero	249163.0	2017	28573	7119335384
461	08303	8303012035	1	2017	Cabrero	249163.0	2017	28573	7119335384
462	08303	8303012037	4	2017	Cabrero	249163.0	2017	28573	7119335384
463	08303	8303012042	2	2017	Cabrero	249163.0	2017	28573	7119335384
464	08303	8303012057	1	2017	Cabrero	249163.0	2017	28573	7119335384
465	08303	8303012901	3	2017	Cabrero	249163.0	2017	28573	7119335384
466	08303	8303022007	22	2017	Cabrero	249163.0	2017	28573	7119335384
467	08303	8303022012	17	2017	Cabrero	249163.0	2017	28573	7119335384
468	08303	8303022013	6	2017	Cabrero	249163.0	2017	28573	7119335384
469	08303	8303022019	11	2017	Cabrero	249163.0	2017	28573	7119335384
470	08303	8303022026	8	2017	Cabrero	249163.0	2017	28573	7119335384
471	08303	8303022028	10	2017	Cabrero	249163.0	2017	28573	7119335384
472	08303	8303022049	5	2017	Cabrero	249163.0	2017	28573	7119335384
473	08303	8303022901	1	2017	Cabrero	249163.0	2017	28573	7119335384
474	08303	8303032003	3	2017	Cabrero	249163.0	2017	28573	7119335384
475	08303	8303032007	14	2017	Cabrero	249163.0	2017	28573	7119335384
476	08303	8303032008	12	2017	Cabrero	249163.0	2017	28573	7119335384
477	08303	8303032009	12	2017	Cabrero	249163.0	2017	28573	7119335384
478	08303	8303032017	9	2017	Cabrero	249163.0	2017	28573	7119335384
479	08303	8303032025	1	2017	Cabrero	249163.0	2017	28573	7119335384
480	08303	8303032036	3	2017	Cabrero	249163.0	2017	28573	7119335384
481	08303	8303032041	4	2017	Cabrero	249163.0	2017	28573	7119335384
482	08303	8303032048	6	2017	Cabrero	249163.0	2017	28573	7119335384
483	08303	8303032053	69	2017	Cabrero	249163.0	2017	28573	7119335384
484	08303	8303032056	3	2017	Cabrero	249163.0	2017	28573	7119335384
485	08303	8303032901	2	2017	Cabrero	249163.0	2017	28573	7119335384
486	08303	8303042003	4	2017	Cabrero	249163.0	2017	28573	7119335384
487	08303	8303042010	3	2017	Cabrero	249163.0	2017	28573	7119335384
488	08303	8303042011	11	2017	Cabrero	249163.0	2017	28573	7119335384
489	08303	8303042013	8	2017	Cabrero	249163.0	2017	28573	7119335384
490	08303	8303042015	1	2017	Cabrero	249163.0	2017	28573	7119335384
491	08303	8303042021	9	2017	Cabrero	249163.0	2017	28573	7119335384
492	08303	8303042024	9	2017	Cabrero	249163.0	2017	28573	7119335384
493	08303	8303042026	5	2017	Cabrero	249163.0	2017	28573	7119335384
494	08303	8303042031	4	2017	Cabrero	249163.0	2017	28573	7119335384
495	08303	8303042042	26	2017	Cabrero	249163.0	2017	28573	7119335384
496	08303	8303042052	3	2017	Cabrero	249163.0	2017	28573	7119335384
497	08303	8303042054	15	2017	Cabrero	249163.0	2017	28573	7119335384
498	08303	8303042901	3	2017	Cabrero	249163.0	2017	28573	7119335384
499	08303	8303052035	2	2017	Cabrero	249163.0	2017	28573	7119335384
500	08303	8303052037	2	2017	Cabrero	249163.0	2017	28573	7119335384
501	08303	8303052040	1	2017	Cabrero	249163.0	2017	28573	7119335384
502	08303	8303052042	4	2017	Cabrero	249163.0	2017	28573	7119335384
503	08303	8303052051	3	2017	Cabrero	249163.0	2017	28573	7119335384
504	08303	8303052052	7	2017	Cabrero	249163.0	2017	28573	7119335384
505	08303	8303052901	2	2017	Cabrero	249163.0	2017	28573	7119335384
506	08304	8304012003	4	2017	Laja	174449.0	2017	22389	3905739533
507	08304	8304012005	8	2017	Laja	174449.0	2017	22389	3905739533
508	08304	8304012008	1	2017	Laja	174449.0	2017	22389	3905739533
509	08304	8304012015	51	2017	Laja	174449.0	2017	22389	3905739533
510	08304	8304012026	12	2017	Laja	174449.0	2017	22389	3905739533
511	08304	8304012029	8	2017	Laja	174449.0	2017	22389	3905739533
512	08304	8304012031	6	2017	Laja	174449.0	2017	22389	3905739533
513	08304	8304012038	83	2017	Laja	174449.0	2017	22389	3905739533
514	08304	8304022005	11	2017	Laja	174449.0	2017	22389	3905739533
515	08304	8304022020	1	2017	Laja	174449.0	2017	22389	3905739533
516	08304	8304022022	1	2017	Laja	174449.0	2017	22389	3905739533
517	08304	8304022033	7	2017	Laja	174449.0	2017	22389	3905739533
518	08304	8304032002	6	2017	Laja	174449.0	2017	22389	3905739533
519	08304	8304032017	3	2017	Laja	174449.0	2017	22389	3905739533
520	08304	8304032018	1	2017	Laja	174449.0	2017	22389	3905739533
521	08304	8304032025	10	2017	Laja	174449.0	2017	22389	3905739533
522	08304	8304032027	7	2017	Laja	174449.0	2017	22389	3905739533
523	08304	8304032035	4	2017	Laja	174449.0	2017	22389	3905739533
524	08304	8304032036	1	2017	Laja	174449.0	2017	22389	3905739533
525	08304	8304032901	8	2017	Laja	174449.0	2017	22389	3905739533
526	08304	8304042010	1	2017	Laja	174449.0	2017	22389	3905739533
527	08304	8304042018	1	2017	Laja	174449.0	2017	22389	3905739533
528	08304	8304042023	2	2017	Laja	174449.0	2017	22389	3905739533
529	08304	8304042035	1	2017	Laja	174449.0	2017	22389	3905739533
530	08304	8304052006	8	2017	Laja	174449.0	2017	22389	3905739533
531	08304	8304052008	7	2017	Laja	174449.0	2017	22389	3905739533
532	08304	8304052009	8	2017	Laja	174449.0	2017	22389	3905739533
533	08304	8304052019	1	2017	Laja	174449.0	2017	22389	3905739533
534	08304	8304052030	10	2017	Laja	174449.0	2017	22389	3905739533
535	08304	8304052031	18	2017	Laja	174449.0	2017	22389	3905739533
536	08304	8304052034	17	2017	Laja	174449.0	2017	22389	3905739533
537	08304	8304052037	2	2017	Laja	174449.0	2017	22389	3905739533
538	08304	8304052901	4	2017	Laja	174449.0	2017	22389	3905739533
539	08305	8305032005	7	2017	Mulchén	198258.1	2017	29627	5873792045
540	08305	8305032013	4	2017	Mulchén	198258.1	2017	29627	5873792045
541	08305	8305032022	10	2017	Mulchén	198258.1	2017	29627	5873792045
542	08305	8305032034	28	2017	Mulchén	198258.1	2017	29627	5873792045
543	08305	8305032036	3	2017	Mulchén	198258.1	2017	29627	5873792045
544	08305	8305032037	4	2017	Mulchén	198258.1	2017	29627	5873792045
545	08305	8305042012	7	2017	Mulchén	198258.1	2017	29627	5873792045
546	08305	8305042013	5	2017	Mulchén	198258.1	2017	29627	5873792045
547	08305	8305042022	10	2017	Mulchén	198258.1	2017	29627	5873792045
548	08305	8305042028	2	2017	Mulchén	198258.1	2017	29627	5873792045
549	08305	8305042030	4	2017	Mulchén	198258.1	2017	29627	5873792045
550	08305	8305042043	26	2017	Mulchén	198258.1	2017	29627	5873792045
551	08305	8305042050	1	2017	Mulchén	198258.1	2017	29627	5873792045
552	08305	8305042901	2	2017	Mulchén	198258.1	2017	29627	5873792045
553	08305	8305082059	1	2017	Mulchén	198258.1	2017	29627	5873792045
554	08305	8305092025	2	2017	Mulchén	198258.1	2017	29627	5873792045
555	08305	8305102020	6	2017	Mulchén	198258.1	2017	29627	5873792045
556	08305	8305102024	7	2017	Mulchén	198258.1	2017	29627	5873792045
557	08305	8305102039	2	2017	Mulchén	198258.1	2017	29627	5873792045
558	08305	8305102056	1	2017	Mulchén	198258.1	2017	29627	5873792045
559	08305	8305102901	1	2017	Mulchén	198258.1	2017	29627	5873792045
560	08305	8305112018	1	2017	Mulchén	198258.1	2017	29627	5873792045
561	08305	8305112019	1	2017	Mulchén	198258.1	2017	29627	5873792045
562	08305	8305112901	1	2017	Mulchén	198258.1	2017	29627	5873792045
563	08305	8305122029	1	2017	Mulchén	198258.1	2017	29627	5873792045
564	08305	8305122038	2	2017	Mulchén	198258.1	2017	29627	5873792045
565	08305	8305122044	4	2017	Mulchén	198258.1	2017	29627	5873792045
566	08305	8305122045	3	2017	Mulchén	198258.1	2017	29627	5873792045
567	08305	8305132048	12	2017	Mulchén	198258.1	2017	29627	5873792045
568	08305	8305132901	3	2017	Mulchén	198258.1	2017	29627	5873792045
569	08305	8305142001	3	2017	Mulchén	198258.1	2017	29627	5873792045
570	08305	8305142010	10	2017	Mulchén	198258.1	2017	29627	5873792045
571	08305	8305142031	2	2017	Mulchén	198258.1	2017	29627	5873792045
572	08305	8305152004	1	2017	Mulchén	198258.1	2017	29627	5873792045
573	08305	8305152011	2	2017	Mulchén	198258.1	2017	29627	5873792045
574	08305	8305152047	4	2017	Mulchén	198258.1	2017	29627	5873792045
575	08305	8305152058	5	2017	Mulchén	198258.1	2017	29627	5873792045
576	08306	8306022017	6	2017	Nacimiento	175829.2	2017	26315	4626944798
577	08306	8306022031	1	2017	Nacimiento	175829.2	2017	26315	4626944798
578	08306	8306032006	1	2017	Nacimiento	175829.2	2017	26315	4626944798
579	08306	8306032021	1	2017	Nacimiento	175829.2	2017	26315	4626944798
580	08306	8306032901	7	2017	Nacimiento	175829.2	2017	26315	4626944798
581	08306	8306052007	1	2017	Nacimiento	175829.2	2017	26315	4626944798
582	08306	8306052010	2	2017	Nacimiento	175829.2	2017	26315	4626944798
583	08306	8306052018	3	2017	Nacimiento	175829.2	2017	26315	4626944798
584	08306	8306052024	8	2017	Nacimiento	175829.2	2017	26315	4626944798
585	08306	8306052025	2	2017	Nacimiento	175829.2	2017	26315	4626944798
586	08306	8306052030	3	2017	Nacimiento	175829.2	2017	26315	4626944798
587	08306	8306052035	3	2017	Nacimiento	175829.2	2017	26315	4626944798
588	08306	8306052901	4	2017	Nacimiento	175829.2	2017	26315	4626944798
589	08306	8306062014	10	2017	Nacimiento	175829.2	2017	26315	4626944798
590	08306	8306062023	4	2017	Nacimiento	175829.2	2017	26315	4626944798
591	08306	8306062901	4	2017	Nacimiento	175829.2	2017	26315	4626944798
592	08306	8306072001	7	2017	Nacimiento	175829.2	2017	26315	4626944798
593	08306	8306072004	1	2017	Nacimiento	175829.2	2017	26315	4626944798
594	08306	8306072007	2	2017	Nacimiento	175829.2	2017	26315	4626944798
595	08306	8306072008	8	2017	Nacimiento	175829.2	2017	26315	4626944798
596	08306	8306072027	2	2017	Nacimiento	175829.2	2017	26315	4626944798
597	08306	8306072034	2	2017	Nacimiento	175829.2	2017	26315	4626944798
598	08307	8307012001	6	2017	Negrete	216999.7	2017	9737	2112926492
599	08307	8307012003	11	2017	Negrete	216999.7	2017	9737	2112926492
600	08307	8307012007	10	2017	Negrete	216999.7	2017	9737	2112926492
601	08307	8307012008	4	2017	Negrete	216999.7	2017	9737	2112926492
602	08307	8307012009	17	2017	Negrete	216999.7	2017	9737	2112926492
603	08307	8307012010	3	2017	Negrete	216999.7	2017	9737	2112926492
604	08307	8307012012	3	2017	Negrete	216999.7	2017	9737	2112926492
605	08307	8307012019	6	2017	Negrete	216999.7	2017	9737	2112926492
606	08307	8307012020	13	2017	Negrete	216999.7	2017	9737	2112926492
607	08307	8307012901	13	2017	Negrete	216999.7	2017	9737	2112926492
608	08307	8307022004	8	2017	Negrete	216999.7	2017	9737	2112926492
609	08307	8307022005	24	2017	Negrete	216999.7	2017	9737	2112926492
610	08307	8307022011	5	2017	Negrete	216999.7	2017	9737	2112926492
611	08307	8307022018	11	2017	Negrete	216999.7	2017	9737	2112926492
612	08307	8307022901	1	2017	Negrete	216999.7	2017	9737	2112926492
613	08307	8307032006	6	2017	Negrete	216999.7	2017	9737	2112926492
614	08307	8307032017	32	2017	Negrete	216999.7	2017	9737	2112926492
615	08308	8308012001	4	2017	Quilaco	167106.1	2017	3988	666419314
616	08308	8308012003	2	2017	Quilaco	167106.1	2017	3988	666419314
617	08308	8308012004	9	2017	Quilaco	167106.1	2017	3988	666419314
618	08308	8308012016	3	2017	Quilaco	167106.1	2017	3988	666419314
619	08308	8308022013	1	2017	Quilaco	167106.1	2017	3988	666419314
620	08308	8308022017	8	2017	Quilaco	167106.1	2017	3988	666419314
621	08308	8308022021	3	2017	Quilaco	167106.1	2017	3988	666419314
622	08308	8308022901	1	2017	Quilaco	167106.1	2017	3988	666419314
623	08308	8308032005	2	2017	Quilaco	167106.1	2017	3988	666419314
624	08308	8308032006	1	2017	Quilaco	167106.1	2017	3988	666419314
625	08308	8308032007	2	2017	Quilaco	167106.1	2017	3988	666419314
626	08308	8308032009	1	2017	Quilaco	167106.1	2017	3988	666419314
627	08308	8308032011	10	2017	Quilaco	167106.1	2017	3988	666419314
628	08308	8308032018	15	2017	Quilaco	167106.1	2017	3988	666419314
629	08308	8308032020	4	2017	Quilaco	167106.1	2017	3988	666419314
630	08308	8308032021	2	2017	Quilaco	167106.1	2017	3988	666419314
631	08308	8308032901	3	2017	Quilaco	167106.1	2017	3988	666419314
632	08308	8308042010	26	2017	Quilaco	167106.1	2017	3988	666419314
633	08308	8308042901	2	2017	Quilaco	167106.1	2017	3988	666419314
634	08309	8309012005	2	2017	Quilleco	222077.0	2017	9587	2129051929
635	08309	8309012016	7	2017	Quilleco	222077.0	2017	9587	2129051929
636	08309	8309012026	2	2017	Quilleco	222077.0	2017	9587	2129051929
637	08309	8309012901	1	2017	Quilleco	222077.0	2017	9587	2129051929
638	08309	8309022001	7	2017	Quilleco	222077.0	2017	9587	2129051929
639	08309	8309022010	9	2017	Quilleco	222077.0	2017	9587	2129051929
640	08309	8309022024	2	2017	Quilleco	222077.0	2017	9587	2129051929
641	08309	8309022029	1	2017	Quilleco	222077.0	2017	9587	2129051929
642	08309	8309022030	1	2017	Quilleco	222077.0	2017	9587	2129051929
643	08309	8309022033	23	2017	Quilleco	222077.0	2017	9587	2129051929
644	08309	8309022035	7	2017	Quilleco	222077.0	2017	9587	2129051929
645	08309	8309032011	4	2017	Quilleco	222077.0	2017	9587	2129051929
646	08309	8309042009	11	2017	Quilleco	222077.0	2017	9587	2129051929
647	08309	8309042017	21	2017	Quilleco	222077.0	2017	9587	2129051929
648	08309	8309042901	3	2017	Quilleco	222077.0	2017	9587	2129051929
649	08309	8309052003	4	2017	Quilleco	222077.0	2017	9587	2129051929
650	08309	8309052007	7	2017	Quilleco	222077.0	2017	9587	2129051929
651	08309	8309052019	3	2017	Quilleco	222077.0	2017	9587	2129051929
652	08309	8309062002	1	2017	Quilleco	222077.0	2017	9587	2129051929
653	08309	8309062031	1	2017	Quilleco	222077.0	2017	9587	2129051929
654	08309	8309062032	3	2017	Quilleco	222077.0	2017	9587	2129051929
655	08310	8310012001	2	2017	San Rosendo	165912.3	2017	3412	566092732
656	08310	8310012006	1	2017	San Rosendo	165912.3	2017	3412	566092732
657	08310	8310032002	6	2017	San Rosendo	165912.3	2017	3412	566092732
658	08310	8310032004	1	2017	San Rosendo	165912.3	2017	3412	566092732
659	08310	8310032012	5	2017	San Rosendo	165912.3	2017	3412	566092732
660	08310	8310032013	6	2017	San Rosendo	165912.3	2017	3412	566092732
661	08311	8311012006	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
662	08311	8311012016	9	2017	Santa Bárbara	176010.5	2017	13773	2424192819
663	08311	8311012019	44	2017	Santa Bárbara	176010.5	2017	13773	2424192819
664	08311	8311012025	4	2017	Santa Bárbara	176010.5	2017	13773	2424192819
665	08311	8311012901	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
666	08311	8311022010	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
667	08311	8311022013	19	2017	Santa Bárbara	176010.5	2017	13773	2424192819
668	08311	8311022019	51	2017	Santa Bárbara	176010.5	2017	13773	2424192819
669	08311	8311022022	6	2017	Santa Bárbara	176010.5	2017	13773	2424192819
670	08311	8311032001	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
671	08311	8311032003	2	2017	Santa Bárbara	176010.5	2017	13773	2424192819
672	08311	8311032023	3	2017	Santa Bárbara	176010.5	2017	13773	2424192819
673	08311	8311032026	10	2017	Santa Bárbara	176010.5	2017	13773	2424192819
674	08311	8311042007	5	2017	Santa Bárbara	176010.5	2017	13773	2424192819
675	08311	8311042011	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
676	08311	8311042024	2	2017	Santa Bárbara	176010.5	2017	13773	2424192819
677	08311	8311052008	6	2017	Santa Bárbara	176010.5	2017	13773	2424192819
678	08311	8311052021	2	2017	Santa Bárbara	176010.5	2017	13773	2424192819
679	08311	8311072002	7	2017	Santa Bárbara	176010.5	2017	13773	2424192819
680	08311	8311072012	4	2017	Santa Bárbara	176010.5	2017	13773	2424192819
681	08311	8311072018	7	2017	Santa Bárbara	176010.5	2017	13773	2424192819
682	08311	8311072021	4	2017	Santa Bárbara	176010.5	2017	13773	2424192819
683	08311	8311082004	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
684	08311	8311082005	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
685	08311	8311082009	5	2017	Santa Bárbara	176010.5	2017	13773	2424192819
686	08311	8311082012	1	2017	Santa Bárbara	176010.5	2017	13773	2424192819
687	08311	8311082014	27	2017	Santa Bárbara	176010.5	2017	13773	2424192819
688	08311	8311082016	14	2017	Santa Bárbara	176010.5	2017	13773	2424192819
689	08312	8312012009	4	2017	Tucapel	155538.6	2017	14134	2198382777
690	08312	8312012011	1	2017	Tucapel	155538.6	2017	14134	2198382777
691	08312	8312012016	3	2017	Tucapel	155538.6	2017	14134	2198382777
692	08312	8312012019	6	2017	Tucapel	155538.6	2017	14134	2198382777
693	08312	8312012901	1	2017	Tucapel	155538.6	2017	14134	2198382777
694	08312	8312022005	7	2017	Tucapel	155538.6	2017	14134	2198382777
695	08312	8312022014	9	2017	Tucapel	155538.6	2017	14134	2198382777
696	08312	8312022901	1	2017	Tucapel	155538.6	2017	14134	2198382777
697	08312	8312042003	4	2017	Tucapel	155538.6	2017	14134	2198382777
698	08312	8312042010	2	2017	Tucapel	155538.6	2017	14134	2198382777
699	08312	8312042012	5	2017	Tucapel	155538.6	2017	14134	2198382777
700	08312	8312042013	1	2017	Tucapel	155538.6	2017	14134	2198382777
701	08312	8312042020	2	2017	Tucapel	155538.6	2017	14134	2198382777
702	08312	8312052003	3	2017	Tucapel	155538.6	2017	14134	2198382777
703	08312	8312052006	13	2017	Tucapel	155538.6	2017	14134	2198382777
704	08312	8312052007	3	2017	Tucapel	155538.6	2017	14134	2198382777
705	08312	8312052011	1	2017	Tucapel	155538.6	2017	14134	2198382777
706	08312	8312052018	43	2017	Tucapel	155538.6	2017	14134	2198382777
707	08312	8312052020	2	2017	Tucapel	155538.6	2017	14134	2198382777
708	08313	8313012006	20	2017	Yumbel	138515.0	2017	21198	2936241535
709	08313	8313012028	2	2017	Yumbel	138515.0	2017	21198	2936241535
710	08313	8313012034	11	2017	Yumbel	138515.0	2017	21198	2936241535
711	08313	8313012036	18	2017	Yumbel	138515.0	2017	21198	2936241535
712	08313	8313012044	4	2017	Yumbel	138515.0	2017	21198	2936241535
713	08313	8313012051	4	2017	Yumbel	138515.0	2017	21198	2936241535
714	08313	8313012052	3	2017	Yumbel	138515.0	2017	21198	2936241535
715	08313	8313012072	7	2017	Yumbel	138515.0	2017	21198	2936241535
716	08313	8313012075	13	2017	Yumbel	138515.0	2017	21198	2936241535
717	08313	8313012901	8	2017	Yumbel	138515.0	2017	21198	2936241535
718	08313	8313022025	14	2017	Yumbel	138515.0	2017	21198	2936241535
719	08313	8313022031	9	2017	Yumbel	138515.0	2017	21198	2936241535
720	08313	8313022032	7	2017	Yumbel	138515.0	2017	21198	2936241535
721	08313	8313022039	2	2017	Yumbel	138515.0	2017	21198	2936241535
722	08313	8313022043	17	2017	Yumbel	138515.0	2017	21198	2936241535
723	08313	8313022047	10	2017	Yumbel	138515.0	2017	21198	2936241535
724	08313	8313022054	3	2017	Yumbel	138515.0	2017	21198	2936241535
725	08313	8313032030	22	2017	Yumbel	138515.0	2017	21198	2936241535
726	08313	8313032038	10	2017	Yumbel	138515.0	2017	21198	2936241535
727	08313	8313032047	6	2017	Yumbel	138515.0	2017	21198	2936241535
728	08313	8313032064	6	2017	Yumbel	138515.0	2017	21198	2936241535
729	08313	8313032080	3	2017	Yumbel	138515.0	2017	21198	2936241535
730	08313	8313032901	7	2017	Yumbel	138515.0	2017	21198	2936241535
731	08313	8313042007	1	2017	Yumbel	138515.0	2017	21198	2936241535
732	08313	8313042010	3	2017	Yumbel	138515.0	2017	21198	2936241535
733	08313	8313042018	2	2017	Yumbel	138515.0	2017	21198	2936241535
734	08313	8313042063	5	2017	Yumbel	138515.0	2017	21198	2936241535
735	08313	8313042070	45	2017	Yumbel	138515.0	2017	21198	2936241535
736	08313	8313042072	2	2017	Yumbel	138515.0	2017	21198	2936241535
737	08313	8313042079	9	2017	Yumbel	138515.0	2017	21198	2936241535
738	08313	8313052003	1	2017	Yumbel	138515.0	2017	21198	2936241535
739	08313	8313052021	2	2017	Yumbel	138515.0	2017	21198	2936241535
740	08313	8313052029	1	2017	Yumbel	138515.0	2017	21198	2936241535
741	08313	8313052067	14	2017	Yumbel	138515.0	2017	21198	2936241535
742	08313	8313052082	2	2017	Yumbel	138515.0	2017	21198	2936241535
743	08313	8313062050	1	2017	Yumbel	138515.0	2017	21198	2936241535
744	08313	8313062055	1	2017	Yumbel	138515.0	2017	21198	2936241535
745	08313	8313062083	1	2017	Yumbel	138515.0	2017	21198	2936241535
746	08313	8313072022	4	2017	Yumbel	138515.0	2017	21198	2936241535
747	08313	8313072045	6	2017	Yumbel	138515.0	2017	21198	2936241535
748	08313	8313072046	2	2017	Yumbel	138515.0	2017	21198	2936241535
749	08313	8313072058	10	2017	Yumbel	138515.0	2017	21198	2936241535
750	08313	8313072065	3	2017	Yumbel	138515.0	2017	21198	2936241535
751	08313	8313072069	3	2017	Yumbel	138515.0	2017	21198	2936241535
752	08313	8313072076	4	2017	Yumbel	138515.0	2017	21198	2936241535
753	08313	8313082004	1	2017	Yumbel	138515.0	2017	21198	2936241535
754	08313	8313082009	1	2017	Yumbel	138515.0	2017	21198	2936241535
755	08313	8313082011	8	2017	Yumbel	138515.0	2017	21198	2936241535
756	08313	8313082013	2	2017	Yumbel	138515.0	2017	21198	2936241535
757	08313	8313082015	3	2017	Yumbel	138515.0	2017	21198	2936241535
758	08313	8313082035	5	2017	Yumbel	138515.0	2017	21198	2936241535
759	08313	8313082068	6	2017	Yumbel	138515.0	2017	21198	2936241535
760	08313	8313082078	1	2017	Yumbel	138515.0	2017	21198	2936241535
761	08313	8313082081	3	2017	Yumbel	138515.0	2017	21198	2936241535
762	08313	8313082085	4	2017	Yumbel	138515.0	2017	21198	2936241535
763	08313	8313092005	2	2017	Yumbel	138515.0	2017	21198	2936241535
764	08313	8313092006	6	2017	Yumbel	138515.0	2017	21198	2936241535
765	08313	8313092028	15	2017	Yumbel	138515.0	2017	21198	2936241535
766	08313	8313092034	23	2017	Yumbel	138515.0	2017	21198	2936241535
767	08313	8313092049	3	2017	Yumbel	138515.0	2017	21198	2936241535
768	08313	8313092065	4	2017	Yumbel	138515.0	2017	21198	2936241535
769	08313	8313092081	17	2017	Yumbel	138515.0	2017	21198	2936241535
770	08314	8314012003	7	2017	Alto Biobío	130542.9	2017	5923	773205492
771	08314	8314012015	13	2017	Alto Biobío	130542.9	2017	5923	773205492
772	08314	8314022006	5	2017	Alto Biobío	130542.9	2017	5923	773205492
773	08314	8314022011	1	2017	Alto Biobío	130542.9	2017	5923	773205492
774	08314	8314022012	27	2017	Alto Biobío	130542.9	2017	5923	773205492
775	08314	8314032011	4	2017	Alto Biobío	130542.9	2017	5923	773205492
776	08314	8314032014	3	2017	Alto Biobío	130542.9	2017	5923	773205492
777	08314	8314032901	5	2017	Alto Biobío	130542.9	2017	5923	773205492
778	08314	8314042001	86	2017	Alto Biobío	130542.9	2017	5923	773205492
779	08314	8314042002	12	2017	Alto Biobío	130542.9	2017	5923	773205492
780	08314	8314042005	7	2017	Alto Biobío	130542.9	2017	5923	773205492
781	08314	8314042009	2	2017	Alto Biobío	130542.9	2017	5923	773205492
782	08314	8314042013	7	2017	Alto Biobío	130542.9	2017	5923	773205492
783	08314	8314042901	3	2017	Alto Biobío	130542.9	2017	5923	773205492
784	08314	8314992999	5	2017	Alto Biobío	130542.9	2017	5923	773205492

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	personas	Ingresos_expandidos
1	08101	8101302001	24	2017	Concepción	197625.8	2017	223574	44183983882
2	08101	8101302018	4	2017	Concepción	197625.8	2017	223574	44183983882
3	08101	8101252025	9	2017	Concepción	197625.8	2017	223574	44183983882
4	08101	8101302024	2	2017	Concepción	197625.8	2017	223574	44183983882
5	08101	8101302901	3	2017	Concepción	197625.8	2017	223574	44183983882
6	08101	8101302019	10	2017	Concepción	197625.8	2017	223574	44183983882
7	08101	8101302021	19	2017	Concepción	197625.8	2017	223574	44183983882
8	08101	8101312013	94	2017	Concepción	197625.8	2017	223574	44183983882
9	08101	8101312014	51	2017	Concepción	197625.8	2017	223574	44183983882
10	08101	8101302005	40	2017	Concepción	197625.8	2017	223574	44183983882
11	08101	8101302008	12	2017	Concepción	197625.8	2017	223574	44183983882
12	08101	8101312004	5	2017	Concepción	197625.8	2017	223574	44183983882
13	08101	8101292023	7	2017	Concepción	197625.8	2017	223574	44183983882
14	08101	8101302011	18	2017	Concepción	197625.8	2017	223574	44183983882
15	08101	8101302016	4	2017	Concepción	197625.8	2017	223574	44183983882
16	08101	8101322025	31	2017	Concepción	197625.8	2017	223574	44183983882
17	08101	8101282901	7	2017	Concepción	197625.8	2017	223574	44183983882
18	08101	8101292901	2	2017	Concepción	197625.8	2017	223574	44183983882
19	08101	8101312001	4	2017	Concepción	197625.8	2017	223574	44183983882
20	08101	8101292012	6	2017	Concepción	197625.8	2017	223574	44183983882
21	08101	8101312017	7	2017	Concepción	197625.8	2017	223574	44183983882
22	08101	8101292020	10	2017	Concepción	197625.8	2017	223574	44183983882
23	08102	8102052001	9	2017	Coronel	217018.1	2017	116262	25230952648
24	08102	8102062004	3	2017	Coronel	217018.1	2017	116262	25230952648
25	08102	8102072005	95	2017	Coronel	217018.1	2017	116262	25230952648
26	08102	8102082002	2	2017	Coronel	217018.1	2017	116262	25230952648
27	08102	8102092010	13	2017	Coronel	217018.1	2017	116262	25230952648
28	08102	8102062009	134	2017	Coronel	217018.1	2017	116262	25230952648
29	08102	8102102011	16	2017	Coronel	217018.1	2017	116262	25230952648
30	08102	8102062005	118	2017	Coronel	217018.1	2017	116262	25230952648
31	08102	8102102007	29	2017	Coronel	217018.1	2017	116262	25230952648
32	08102	8102112006	2	2017	Coronel	217018.1	2017	116262	25230952648
33	08102	8102112008	20	2017	Coronel	217018.1	2017	116262	25230952648
36	08104	8104012005	2	2017	Florida	147425.2	2017	10624	1566245750
37	08104	8104012043	7	2017	Florida	147425.2	2017	10624	1566245750
38	08104	8104012023	24	2017	Florida	147425.2	2017	10624	1566245750
39	08104	8104022040	4	2017	Florida	147425.2	2017	10624	1566245750
40	08104	8104012044	16	2017	Florida	147425.2	2017	10624	1566245750
41	08104	8104012052	8	2017	Florida	147425.2	2017	10624	1566245750
42	08104	8104022036	7	2017	Florida	147425.2	2017	10624	1566245750
43	08104	8104012037	11	2017	Florida	147425.2	2017	10624	1566245750
44	08104	8104032004	7	2017	Florida	147425.2	2017	10624	1566245750
45	08104	8104032007	2	2017	Florida	147425.2	2017	10624	1566245750
46	08104	8104012029	2	2017	Florida	147425.2	2017	10624	1566245750
47	08104	8104032901	3	2017	Florida	147425.2	2017	10624	1566245750
48	08104	8104032045	7	2017	Florida	147425.2	2017	10624	1566245750
49	08104	8104032050	1	2017	Florida	147425.2	2017	10624	1566245750
50	08104	8104032053	2	2017	Florida	147425.2	2017	10624	1566245750
51	08104	8104042030	1	2017	Florida	147425.2	2017	10624	1566245750
52	08104	8104042042	4	2017	Florida	147425.2	2017	10624	1566245750
53	08104	8104042043	3	2017	Florida	147425.2	2017	10624	1566245750
54	08104	8104042047	3	2017	Florida	147425.2	2017	10624	1566245750
55	08104	8104042062	9	2017	Florida	147425.2	2017	10624	1566245750
56	08104	8104052003	6	2017	Florida	147425.2	2017	10624	1566245750
57	08104	8104052010	4	2017	Florida	147425.2	2017	10624	1566245750
58	08104	8104052025	1	2017	Florida	147425.2	2017	10624	1566245750
59	08104	8104052027	4	2017	Florida	147425.2	2017	10624	1566245750
60	08104	8104052029	1	2017	Florida	147425.2	2017	10624	1566245750
61	08104	8104042012	40	2017	Florida	147425.2	2017	10624	1566245750
62	08104	8104042014	8	2017	Florida	147425.2	2017	10624	1566245750
63	08104	8104042017	3	2017	Florida	147425.2	2017	10624	1566245750
64	08104	8104052043	27	2017	Florida	147425.2	2017	10624	1566245750
65	08104	8104052051	1	2017	Florida	147425.2	2017	10624	1566245750
66	08104	8104052054	16	2017	Florida	147425.2	2017	10624	1566245750
67	08104	8104052056	1	2017	Florida	147425.2	2017	10624	1566245750
68	08104	8104052059	13	2017	Florida	147425.2	2017	10624	1566245750
69	08104	8104052901	6	2017	Florida	147425.2	2017	10624	1566245750
70	08104	8104062002	1	2017	Florida	147425.2	2017	10624	1566245750
71	08104	8104062003	4	2017	Florida	147425.2	2017	10624	1566245750
72	08104	8104062013	6	2017	Florida	147425.2	2017	10624	1566245750
73	08104	8104062024	2	2017	Florida	147425.2	2017	10624	1566245750
74	08104	8104052031	7	2017	Florida	147425.2	2017	10624	1566245750
75	08104	8104052032	4	2017	Florida	147425.2	2017	10624	1566245750
76	08104	8104052039	20	2017	Florida	147425.2	2017	10624	1566245750
77	08104	8104022035	2	2017	Florida	147425.2	2017	10624	1566245750
78	08104	8104062056	6	2017	Florida	147425.2	2017	10624	1566245750
79	08104	8104062060	1	2017	Florida	147425.2	2017	10624	1566245750
80	08104	8104062901	9	2017	Florida	147425.2	2017	10624	1566245750
81	08104	8104022001	5	2017	Florida	147425.2	2017	10624	1566245750
82	08104	8104032012	6	2017	Florida	147425.2	2017	10624	1566245750
83	08104	8104032028	20	2017	Florida	147425.2	2017	10624	1566245750
84	08104	8104012054	1	2017	Florida	147425.2	2017	10624	1566245750
85	08104	8104022023	3	2017	Florida	147425.2	2017	10624	1566245750
86	08104	8104062049	21	2017	Florida	147425.2	2017	10624	1566245750
87	08104	8104062051	3	2017	Florida	147425.2	2017	10624	1566245750
88	08104	8104062035	1	2017	Florida	147425.2	2017	10624	1566245750
89	08104	8104062036	1	2017	Florida	147425.2	2017	10624	1566245750
90	08105	8105012014	4	2017	Hualqui	202715.1	2017	24333	4932666876
91	08105	8105022025	12	2017	Hualqui	202715.1	2017	24333	4932666876
92	08105	8105022034	1	2017	Hualqui	202715.1	2017	24333	4932666876
93	08105	8105032039	3	2017	Hualqui	202715.1	2017	24333	4932666876
94	08105	8105032901	1	2017	Hualqui	202715.1	2017	24333	4932666876
95	08105	8105022038	2	2017	Hualqui	202715.1	2017	24333	4932666876
96	08105	8105022024	1	2017	Hualqui	202715.1	2017	24333	4932666876
97	08105	8105042023	5	2017	Hualqui	202715.1	2017	24333	4932666876
98	08105	8105042031	13	2017	Hualqui	202715.1	2017	24333	4932666876
99	08105	8105042001	6	2017	Hualqui	202715.1	2017	24333	4932666876
100	08105	8105042007	16	2017	Hualqui	202715.1	2017	24333	4932666876
101	08105	8105022044	1	2017	Hualqui	202715.1	2017	24333	4932666876
102	08105	8105022901	3	2017	Hualqui	202715.1	2017	24333	4932666876

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	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y
8101252025	08101	9	2017	Concepción	197625.8	2017	223574	44183983882	60	0.0002684	08101
8101282901	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	31	0.0001387	08101
8101292012	08101	6	2017	Concepción	197625.8	2017	223574	44183983882	86	0.0003847	08101
8101292020	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	61	0.0002728	08101
8101292023	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	54	0.0002415	08101
8101292901	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	21	0.0000939	08101
8101302001	08101	24	2017	Concepción	197625.8	2017	223574	44183983882	280	0.0012524	08101
8101302005	08101	40	2017	Concepción	197625.8	2017	223574	44183983882	688	0.0030773	08101
8101302008	08101	12	2017	Concepción	197625.8	2017	223574	44183983882	98	0.0004383	08101
8101302011	08101	18	2017	Concepción	197625.8	2017	223574	44183983882	469	0.0020977	08101
8101302016	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	13	0.0000581	08101
8101302018	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	51	0.0002281	08101
8101302019	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	198	0.0008856	08101
8101302021	08101	19	2017	Concepción	197625.8	2017	223574	44183983882	401	0.0017936	08101
8101302024	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	88	0.0003936	08101
8101302901	08101	3	2017	Concepción	197625.8	2017	223574	44183983882	16	0.0000716	08101
8101312001	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	90	0.0004026	08101
8101312004	08101	5	2017	Concepción	197625.8	2017	223574	44183983882	63	0.0002818	08101
8101312013	08101	94	2017	Concepción	197625.8	2017	223574	44183983882	1045	0.0046741	08101
8101312014	08101	51	2017	Concepción	197625.8	2017	223574	44183983882	534	0.0023885	08101
8101312017	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	47	0.0002102	08101
8101322025	08101	31	2017	Concepción	197625.8	2017	223574	44183983882	100	0.0004473	08101
8102052001	08102	9	2017	Coronel	217018.1	2017	116262	25230952648	62	0.0005333	08102
8102062004	08102	3	2017	Coronel	217018.1	2017	116262	25230952648	29	0.0002494	08102
8102062005	08102	118	2017	Coronel	217018.1	2017	116262	25230952648	350	0.0030104	08102
8102062009	08102	134	2017	Coronel	217018.1	2017	116262	25230952648	382	0.0032857	08102
8102072005	08102	95	2017	Coronel	217018.1	2017	116262	25230952648	624	0.0053672	08102
8102082002	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	24	0.0002064	08102
8102092010	08102	13	2017	Coronel	217018.1	2017	116262	25230952648	298	0.0025632	08102
8102102007	08102	29	2017	Coronel	217018.1	2017	116262	25230952648	744	0.0063993	08102
8102102011	08102	16	2017	Coronel	217018.1	2017	116262	25230952648	503	0.0043264	08102
8102112006	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	55	0.0004731	08102
8102112008	08102	20	2017	Coronel	217018.1	2017	116262	25230952648	104	0.0008945	08102
8104012005	08104	2	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104
8104012023	08104	24	2017	Florida	147425.2	2017	10624	1566245750	163	0.0153426	08104
8104012029	08104	2	2017	Florida	147425.2	2017	10624	1566245750	45	0.0042357	08104
8104012037	08104	11	2017	Florida	147425.2	2017	10624	1566245750	162	0.0152485	08104
8104012043	08104	7	2017	Florida	147425.2	2017	10624	1566245750	68	0.0064006	08104
8104012044	08104	16	2017	Florida	147425.2	2017	10624	1566245750	214	0.0201431	08104
8104012052	08104	8	2017	Florida	147425.2	2017	10624	1566245750	93	0.0087538	08104
8104012054	08104	1	2017	Florida	147425.2	2017	10624	1566245750	43	0.0040474	08104
8104022001	08104	5	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104
8104022023	08104	3	2017	Florida	147425.2	2017	10624	1566245750	13	0.0012236	08104
8104022035	08104	2	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104
8104022036	08104	7	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104
8104022040	08104	4	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104
8104032004	08104	7	2017	Florida	147425.2	2017	10624	1566245750	175	0.0164721	08104
8104032007	08104	2	2017	Florida	147425.2	2017	10624	1566245750	30	0.0028238	08104
8104032012	08104	6	2017	Florida	147425.2	2017	10624	1566245750	26	0.0024473	08104
8104032028	08104	20	2017	Florida	147425.2	2017	10624	1566245750	174	0.0163780	08104
8104032045	08104	7	2017	Florida	147425.2	2017	10624	1566245750	244	0.0229669	08104
8104032050	08104	1	2017	Florida	147425.2	2017	10624	1566245750	67	0.0063065	08104
8104032053	08104	2	2017	Florida	147425.2	2017	10624	1566245750	58	0.0054593	08104
8104032901	08104	3	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104
8104042012	08104	40	2017	Florida	147425.2	2017	10624	1566245750	745	0.0701242	08104
8104042014	08104	8	2017	Florida	147425.2	2017	10624	1566245750	118	0.0111069	08104
8104042017	08104	3	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104
8104042030	08104	1	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104
8104042042	08104	4	2017	Florida	147425.2	2017	10624	1566245750	89	0.0083773	08104
8104042043	08104	3	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104
8104042047	08104	3	2017	Florida	147425.2	2017	10624	1566245750	59	0.0055535	08104
8104042062	08104	9	2017	Florida	147425.2	2017	10624	1566245750	75	0.0070595	08104
8104052003	08104	6	2017	Florida	147425.2	2017	10624	1566245750	34	0.0032003	08104
8104052010	08104	4	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104
8104052025	08104	1	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104
8104052027	08104	4	2017	Florida	147425.2	2017	10624	1566245750	15	0.0014119	08104
8104052029	08104	1	2017	Florida	147425.2	2017	10624	1566245750	11	0.0010354	08104
8104052031	08104	7	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104
8104052032	08104	4	2017	Florida	147425.2	2017	10624	1566245750	47	0.0044239	08104
8104052039	08104	20	2017	Florida	147425.2	2017	10624	1566245750	181	0.0170369	08104
8104052043	08104	27	2017	Florida	147425.2	2017	10624	1566245750	291	0.0273908	08104
8104052051	08104	1	2017	Florida	147425.2	2017	10624	1566245750	6	0.0005648	08104
8104052054	08104	16	2017	Florida	147425.2	2017	10624	1566245750	124	0.0116717	08104
8104052056	08104	1	2017	Florida	147425.2	2017	10624	1566245750	24	0.0022590	08104
8104052059	08104	13	2017	Florida	147425.2	2017	10624	1566245750	115	0.0108245	08104
8104052901	08104	6	2017	Florida	147425.2	2017	10624	1566245750	87	0.0081890	08104
8104062002	08104	1	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104
8104062003	08104	4	2017	Florida	147425.2	2017	10624	1566245750	17	0.0016002	08104
8104062013	08104	6	2017	Florida	147425.2	2017	10624	1566245750	282	0.0265437	08104
8104062024	08104	2	2017	Florida	147425.2	2017	10624	1566245750	141	0.0132718	08104
8104062035	08104	1	2017	Florida	147425.2	2017	10624	1566245750	31	0.0029179	08104
8104062036	08104	1	2017	Florida	147425.2	2017	10624	1566245750	36	0.0033886	08104
8104062049	08104	21	2017	Florida	147425.2	2017	10624	1566245750	499	0.0469691	08104
8104062051	08104	3	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104
8104062056	08104	6	2017	Florida	147425.2	2017	10624	1566245750	122	0.0114834	08104
8104062060	08104	1	2017	Florida	147425.2	2017	10624	1566245750	28	0.0026355	08104
8104062901	08104	9	2017	Florida	147425.2	2017	10624	1566245750	123	0.0115776	08104
8105012014	08105	4	2017	Hualqui	202715.1	2017	24333	4932666876	25	0.0010274	08105
8105012028	08105	9	2017	Hualqui	202715.1	2017	24333	4932666876	137	0.0056302	08105
8105012034	08105	6	2017	Hualqui	202715.1	2017	24333	4932666876	50	0.0020548	08105
8105022024	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	10	0.0004110	08105
8105022025	08105	12	2017	Hualqui	202715.1	2017	24333	4932666876	64	0.0026302	08105
8105022034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	38	0.0015617	08105
8105022038	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	15	0.0006164	08105
8105022044	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	76	0.0031233	08105
8105022901	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	99	0.0040685	08105
8105032001	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	18	0.0007397	08105
8105032003	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	14	0.0005754	08105
8105032034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	32	0.0013151	08105
8105032039	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	94	0.0038631	08105

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	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob
8101252025	08101	9	2017	Concepción	197625.8	2017	223574	44183983882	60	0.0002684	08101	11857546.2
8101282901	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	31	0.0001387	08101	6126398.9
8101292012	08101	6	2017	Concepción	197625.8	2017	223574	44183983882	86	0.0003847	08101	16995816.2
8101292020	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	61	0.0002728	08101	12055172.0
8101292023	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	54	0.0002415	08101	10671791.6
8101292901	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	21	0.0000939	08101	4150141.2
8101302001	08101	24	2017	Concepción	197625.8	2017	223574	44183983882	280	0.0012524	08101	55335215.6
8101302005	08101	40	2017	Concepción	197625.8	2017	223574	44183983882	688	0.0030773	08101	135966529.7
8101302008	08101	12	2017	Concepción	197625.8	2017	223574	44183983882	98	0.0004383	08101	19367325.5
8101302011	08101	18	2017	Concepción	197625.8	2017	223574	44183983882	469	0.0020977	08101	92686486.1
8101302016	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	13	0.0000581	08101	2569135.0
8101302018	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	51	0.0002281	08101	10078914.3
8101302019	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	198	0.0008856	08101	39129902.4
8101302021	08101	19	2017	Concepción	197625.8	2017	223574	44183983882	401	0.0017936	08101	79247933.7
8101302024	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	88	0.0003936	08101	17391067.8
8101302901	08101	3	2017	Concepción	197625.8	2017	223574	44183983882	16	0.0000716	08101	3162012.3
8101312001	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	90	0.0004026	08101	17786319.3
8101312004	08101	5	2017	Concepción	197625.8	2017	223574	44183983882	63	0.0002818	08101	12450423.5
8101312013	08101	94	2017	Concepción	197625.8	2017	223574	44183983882	1045	0.0046741	08101	206518929.6
8101312014	08101	51	2017	Concepción	197625.8	2017	223574	44183983882	534	0.0023885	08101	105532161.1
8101312017	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	47	0.0002102	08101	9288411.2
8101322025	08101	31	2017	Concepción	197625.8	2017	223574	44183983882	100	0.0004473	08101	19762577.0
8102052001	08102	9	2017	Coronel	217018.1	2017	116262	25230952648	62	0.0005333	08102	13455119.2
8102062004	08102	3	2017	Coronel	217018.1	2017	116262	25230952648	29	0.0002494	08102	6293523.5
8102062005	08102	118	2017	Coronel	217018.1	2017	116262	25230952648	350	0.0030104	08102	75956317.9
8102062009	08102	134	2017	Coronel	217018.1	2017	116262	25230952648	382	0.0032857	08102	82900895.5
8102072005	08102	95	2017	Coronel	217018.1	2017	116262	25230952648	624	0.0053672	08102	135419263.8
8102082002	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	24	0.0002064	08102	5208433.2
8102092010	08102	13	2017	Coronel	217018.1	2017	116262	25230952648	298	0.0025632	08102	64671379.2
8102102007	08102	29	2017	Coronel	217018.1	2017	116262	25230952648	744	0.0063993	08102	161461430.0
8102102011	08102	16	2017	Coronel	217018.1	2017	116262	25230952648	503	0.0043264	08102	109160079.7
8102112006	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	55	0.0004731	08102	11935992.8
8102112008	08102	20	2017	Coronel	217018.1	2017	116262	25230952648	104	0.0008945	08102	22569877.3
8104012005	08104	2	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104	3980481.5
8104012023	08104	24	2017	Florida	147425.2	2017	10624	1566245750	163	0.0153426	08104	24030314.1
8104012029	08104	2	2017	Florida	147425.2	2017	10624	1566245750	45	0.0042357	08104	6634135.8
8104012037	08104	11	2017	Florida	147425.2	2017	10624	1566245750	162	0.0152485	08104	23882888.9
8104012043	08104	7	2017	Florida	147425.2	2017	10624	1566245750	68	0.0064006	08104	10024916.3
8104012044	08104	16	2017	Florida	147425.2	2017	10624	1566245750	214	0.0201431	08104	31549001.4
8104012052	08104	8	2017	Florida	147425.2	2017	10624	1566245750	93	0.0087538	08104	13710547.3
8104012054	08104	1	2017	Florida	147425.2	2017	10624	1566245750	43	0.0040474	08104	6339285.3
8104022001	08104	5	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104	6191860.1
8104022023	08104	3	2017	Florida	147425.2	2017	10624	1566245750	13	0.0012236	08104	1916528.1
8104022035	08104	2	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104	4275332.0
8104022036	08104	7	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104	8845514.4
8104022040	08104	4	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104	10319766.8
8104032004	08104	7	2017	Florida	147425.2	2017	10624	1566245750	175	0.0164721	08104	25799417.0
8104032007	08104	2	2017	Florida	147425.2	2017	10624	1566245750	30	0.0028238	08104	4422757.2
8104032012	08104	6	2017	Florida	147425.2	2017	10624	1566245750	26	0.0024473	08104	3833056.2
8104032028	08104	20	2017	Florida	147425.2	2017	10624	1566245750	174	0.0163780	08104	25651991.8
8104032045	08104	7	2017	Florida	147425.2	2017	10624	1566245750	244	0.0229669	08104	35971758.6
8104032050	08104	1	2017	Florida	147425.2	2017	10624	1566245750	67	0.0063065	08104	9877491.1
8104032053	08104	2	2017	Florida	147425.2	2017	10624	1566245750	58	0.0054593	08104	8550663.9
8104032901	08104	3	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104	3243355.3
8104042012	08104	40	2017	Florida	147425.2	2017	10624	1566245750	745	0.0701242	08104	109831803.8
8104042014	08104	8	2017	Florida	147425.2	2017	10624	1566245750	118	0.0111069	08104	17396178.3
8104042017	08104	3	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104	8845514.4
8104042030	08104	1	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104	6191860.1
8104042042	08104	4	2017	Florida	147425.2	2017	10624	1566245750	89	0.0083773	08104	13120846.4
8104042043	08104	3	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104	4275332.0
8104042047	08104	3	2017	Florida	147425.2	2017	10624	1566245750	59	0.0055535	08104	8698089.2
8104042062	08104	9	2017	Florida	147425.2	2017	10624	1566245750	75	0.0070595	08104	11056893.0
8104052003	08104	6	2017	Florida	147425.2	2017	10624	1566245750	34	0.0032003	08104	5012458.2
8104052010	08104	4	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104	8992939.6
8104052025	08104	1	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104	3980481.5
8104052027	08104	4	2017	Florida	147425.2	2017	10624	1566245750	15	0.0014119	08104	2211378.6
8104052029	08104	1	2017	Florida	147425.2	2017	10624	1566245750	11	0.0010354	08104	1621677.6
8104052031	08104	7	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104	8992939.6
8104052032	08104	4	2017	Florida	147425.2	2017	10624	1566245750	47	0.0044239	08104	6928986.3
8104052039	08104	20	2017	Florida	147425.2	2017	10624	1566245750	181	0.0170369	08104	26683968.4
8104052043	08104	27	2017	Florida	147425.2	2017	10624	1566245750	291	0.0273908	08104	42900744.8
8104052051	08104	1	2017	Florida	147425.2	2017	10624	1566245750	6	0.0005648	08104	884551.4
8104052054	08104	16	2017	Florida	147425.2	2017	10624	1566245750	124	0.0116717	08104	18280729.8
8104052056	08104	1	2017	Florida	147425.2	2017	10624	1566245750	24	0.0022590	08104	3538205.8
8104052059	08104	13	2017	Florida	147425.2	2017	10624	1566245750	115	0.0108245	08104	16953902.6
8104052901	08104	6	2017	Florida	147425.2	2017	10624	1566245750	87	0.0081890	08104	12825995.9
8104062002	08104	1	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104	3243355.3
8104062003	08104	4	2017	Florida	147425.2	2017	10624	1566245750	17	0.0016002	08104	2506229.1
8104062013	08104	6	2017	Florida	147425.2	2017	10624	1566245750	282	0.0265437	08104	41573917.7
8104062024	08104	2	2017	Florida	147425.2	2017	10624	1566245750	141	0.0132718	08104	20786958.8
8104062035	08104	1	2017	Florida	147425.2	2017	10624	1566245750	31	0.0029179	08104	4570182.4
8104062036	08104	1	2017	Florida	147425.2	2017	10624	1566245750	36	0.0033886	08104	5307308.6
8104062049	08104	21	2017	Florida	147425.2	2017	10624	1566245750	499	0.0469691	08104	73565194.8
8104062051	08104	3	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104	10319766.8
8104062056	08104	6	2017	Florida	147425.2	2017	10624	1566245750	122	0.0114834	08104	17985879.3
8104062060	08104	1	2017	Florida	147425.2	2017	10624	1566245750	28	0.0026355	08104	4127906.7
8104062901	08104	9	2017	Florida	147425.2	2017	10624	1566245750	123	0.0115776	08104	18133304.5
8105012014	08105	4	2017	Hualqui	202715.1	2017	24333	4932666876	25	0.0010274	08105	5067877.9
8105012028	08105	9	2017	Hualqui	202715.1	2017	24333	4932666876	137	0.0056302	08105	27771970.7
8105012034	08105	6	2017	Hualqui	202715.1	2017	24333	4932666876	50	0.0020548	08105	10135755.7
8105022024	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	10	0.0004110	08105	2027151.1
8105022025	08105	12	2017	Hualqui	202715.1	2017	24333	4932666876	64	0.0026302	08105	12973767.3
8105022034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	38	0.0015617	08105	7703174.3
8105022038	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	15	0.0006164	08105	3040726.7
8105022044	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	76	0.0031233	08105	15406348.7
8105022901	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	99	0.0040685	08105	20068796.3
8105032001	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	18	0.0007397	08105	3648872.1
8105032003	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	14	0.0005754	08105	2838011.6
8105032034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	32	0.0013151	08105	6486883.7
8105032039	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	94	0.0038631	08105	19055220.7

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 
## -387916290  -18657567  -11774971    6611126  414199097 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 20407050    1742127   11.71   <2e-16 ***
## Freq.x       1492308      54495   27.38   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 44310000 on 771 degrees of freedom
## Multiple R-squared:  0.4931, Adjusted R-squared:  0.4924 
## F-statistic: 749.9 on 1 and 771 DF,  p-value: < 2.2e-16

7.4 Gráfica de la recta de regresión lineal

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

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

8 Modelos alternativos

8.1 Modelo cuadrático

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

linearMod <- lm( multi_pob~(Freq.x^2) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^2), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -387916290  -18657567  -11774971    6611126  414199097 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 20407050    1742127   11.71   <2e-16 ***
## Freq.x       1492308      54495   27.38   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 44310000 on 771 degrees of freedom
## Multiple R-squared:  0.4931, Adjusted R-squared:  0.4924 
## F-statistic: 749.9 on 1 and 771 DF,  p-value: < 2.2e-16

8.2 Modelo cúbico

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

linearMod <- lm( multi_pob~(Freq.x^3) , data=h_y_m_comuna_corr_01)
summary(linearMod) 

## 
## Call:
## lm(formula = multi_pob ~ (Freq.x^3), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -387916290  -18657567  -11774971    6611126  414199097 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 20407050    1742127   11.71   <2e-16 ***
## Freq.x       1492308      54495   27.38   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 44310000 on 771 degrees of freedom
## Multiple R-squared:  0.4931, Adjusted R-squared:  0.4924 
## F-statistic: 749.9 on 1 and 771 DF,  p-value: < 2.2e-16

8.3 Modelo logarítmico

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

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

## 
## Call:
## lm(formula = multi_pob ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -80600448 -25739860  -4155436  20251308 503419614 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -15952324    2759196  -5.782 1.08e-08 ***
## log(Freq.x)  33871806    1343289  25.216  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 46070000 on 771 degrees of freedom
## Multiple R-squared:  0.452,  Adjusted R-squared:  0.4512 
## F-statistic: 635.8 on 1 and 771 DF,  p-value: < 2.2e-16

8.4 Modelo exponencial

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

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

8.5 Modelo con raíz cuadrada

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

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

## 
## Call:
## lm(formula = multi_pob ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -191799375  -15527058   -2724529    9719348  416552528 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -20389908    2295287  -8.883   <2e-16 ***
## sqrt(Freq.x)  21365353     638699  33.451   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 39750000 on 771 degrees of freedom
## Multiple R-squared:  0.5921, Adjusted R-squared:  0.5915 
## F-statistic:  1119 on 1 and 771 DF,  p-value: < 2.2e-16

8.6 Modelo raíz-raíz

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

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

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11516.5  -1413.1   -327.8   1158.6   9450.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1777.56     125.38   14.18   <2e-16 ***
## sqrt(Freq.x)  1229.65      34.89   35.24   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2171 on 771 degrees of freedom
## Multiple R-squared:  0.617,  Adjusted R-squared:  0.6165 
## F-statistic:  1242 on 1 and 771 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

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

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

## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.9239 -0.6029  0.0510  0.6611  2.3253 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  15.68595    0.05145  304.87   <2e-16 ***
## sqrt(Freq.x)  0.37644    0.01432   26.29   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.891 on 771 degrees of freedom
## Multiple R-squared:  0.4728, Adjusted R-squared:  0.4721 
## F-statistic: 691.3 on 1 and 771 DF,  p-value: < 2.2e-16

8.8 Modelo raíz-log

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

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

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4793.2 -1598.9  -162.6  1232.4 13148.2 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  1693.28     136.78   12.38   <2e-16 ***
## log(Freq.x)  2156.25      66.59   32.38   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2284 on 771 degrees of freedom
## Multiple R-squared:  0.5762, Adjusted R-squared:  0.5757 
## F-statistic:  1048 on 1 and 771 DF,  p-value: < 2.2e-16

8.9 Modelo log-log

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

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

## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.72914 -0.55756  0.05133  0.60672  2.24965 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.54592    0.04987  311.71   <2e-16 ***
## log(Freq.x)  0.72966    0.02428   30.05   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.8327 on 771 degrees of freedom
## Multiple R-squared:  0.5395, Adjusted R-squared:  0.5389 
## F-statistic: 903.1 on 1 and 771 DF,  p-value: < 2.2e-16

9 Modelo elegido: raiz-raiz (raiz-raiz)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.6037 ).

9.1 Diagrama de dispersión sobre raiz-raiz

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

scatter.smooth(x=sqrt(h_y_m_comuna_corr_01$Freq.x), y=sqrt(h_y_m_comuna_corr_01$multi_pob), lpars = list(col = "red", lwd = 2, lty = 1), main="multi_pob ~ Freq.x")

9.2 Modelo raiz-raiz

Observemos nuevamente el resultado sobre raiz-raiz.

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

## 
## Call:
## lm(formula = sqrt(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11516.5  -1413.1   -327.8   1158.6   9450.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1777.56     125.38   14.18   <2e-16 ***
## sqrt(Freq.x)  1229.65      34.89   35.24   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2171 on 771 degrees of freedom
## Multiple R-squared:  0.617,  Adjusted R-squared:  0.6165 
## F-statistic:  1242 on 1 and 771 DF,  p-value: < 2.2e-16

ggplot(h_y_m_comuna_corr_01, aes(x = sqrt(Freq.x) , y = sqrt(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

\[ \hat Y = (1896.07)^2 + 2 \cdot 1896.07 \cdot 1384.54 \cdot \sqrt{X}+ 1384.54^2 \cdot X \]

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

Esta nueva variable se llamará: est_ing

h_y_m_comuna_corr_01$est_ing <- 
(1896.07)^2 + 2 * 1896.07 * 1384.54 * sqrt(h_y_m_comuna_corr_01$Freq.x)+  1384.54^2 * (h_y_m_comuna_corr_01$Freq.x)

r3_100 <- h_y_m_comuna_corr_01[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing
8101252025	08101	9	2017	Concepción	197625.8	2017	223574	44183983882	60	0.0002684	08101	11857546.2	36598749
8101282901	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	31	0.0001387	08101	6126398.9	30904911
8101292012	08101	6	2017	Concepción	197625.8	2017	223574	44183983882	86	0.0003847	08101	16995816.2	27957514
8101292020	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	61	0.0002728	08101	12055172.0	39367718
8101292023	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	54	0.0002415	08101	10671791.6	30904911
8101292901	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	21	0.0000939	08101	4150141.2	14854127
8101302001	08101	24	2017	Concepción	197625.8	2017	223574	44183983882	280	0.0012524	08101	55335215.6	75323358
8101302005	08101	40	2017	Concepción	197625.8	2017	223574	44183983882	688	0.0030773	08101	135966529.7	113479374
8101302008	08101	12	2017	Concepción	197625.8	2017	223574	44183983882	98	0.0004383	08101	19367325.5	44786307
8101302011	08101	18	2017	Concepción	197625.8	2017	223574	44183983882	469	0.0020977	08101	92686486.1	60375631
8101302016	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	13	0.0000581	08101	2569135.0	21763625
8101302018	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	51	0.0002281	08101	10078914.3	21763625
8101302019	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	198	0.0008856	08101	39129902.4	39367718
8101302021	08101	19	2017	Concepción	197625.8	2017	223574	44183983882	401	0.0017936	08101	79247933.7	62902981
8101302024	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	88	0.0003936	08101	17391067.8	14854127
8101302901	08101	3	2017	Concepción	197625.8	2017	223574	44183983882	16	0.0000716	08101	3162012.3	18439841
8101312001	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	90	0.0004026	08101	17786319.3	21763625
8101312004	08101	5	2017	Concepción	197625.8	2017	223574	44183983882	63	0.0002818	08101	12450423.5	24920020
8101312013	08101	94	2017	Concepción	197625.8	2017	223574	44183983882	1045	0.0046741	08101	206518929.6	234692698
8101312014	08101	51	2017	Concepción	197625.8	2017	223574	44183983882	534	0.0023885	08101	105532161.1	138854721
8101312017	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	47	0.0002102	08101	9288411.2	30904911
8101322025	08101	31	2017	Concepción	197625.8	2017	223574	44183983882	100	0.0004473	08101	19762577.0	92253383
8102052001	08102	9	2017	Coronel	217018.1	2017	116262	25230952648	62	0.0005333	08102	13455119.2	36598749
8102062004	08102	3	2017	Coronel	217018.1	2017	116262	25230952648	29	0.0002494	08102	6293523.5	18439841
8102062005	08102	118	2017	Coronel	217018.1	2017	116262	25230952648	350	0.0030104	08102	75956317.9	286828912
8102062009	08102	134	2017	Coronel	217018.1	2017	116262	25230952648	382	0.0032857	08102	82900895.5	321243938
8102072005	08102	95	2017	Coronel	217018.1	2017	116262	25230952648	624	0.0053672	08102	135419263.8	236879699
8102082002	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	24	0.0002064	08102	5208433.2	14854127
8102092010	08102	13	2017	Coronel	217018.1	2017	116262	25230952648	298	0.0025632	08102	64671379.2	47445921
8102102007	08102	29	2017	Coronel	217018.1	2017	116262	25230952648	744	0.0063993	08102	161461430.0	87460766
8102102011	08102	16	2017	Coronel	217018.1	2017	116262	25230952648	503	0.0043264	08102	109160079.7	55267776
8102112006	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	55	0.0004731	08102	11935992.8	14854127
8102112008	08102	20	2017	Coronel	217018.1	2017	116262	25230952648	104	0.0008945	08102	22569877.3	65414468
8104012005	08104	2	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104	3980481.5	14854127
8104012023	08104	24	2017	Florida	147425.2	2017	10624	1566245750	163	0.0153426	08104	24030314.1	75323358
8104012029	08104	2	2017	Florida	147425.2	2017	10624	1566245750	45	0.0042357	08104	6634135.8	14854127
8104012037	08104	11	2017	Florida	147425.2	2017	10624	1566245750	162	0.0152485	08104	23882888.9	42095048
8104012043	08104	7	2017	Florida	147425.2	2017	10624	1566245750	68	0.0064006	08104	10024916.3	30904911
8104012044	08104	16	2017	Florida	147425.2	2017	10624	1566245750	214	0.0201431	08104	31549001.4	55267776
8104012052	08104	8	2017	Florida	147425.2	2017	10624	1566245750	93	0.0087538	08104	13710547.3	33780977
8104012054	08104	1	2017	Florida	147425.2	2017	10624	1566245750	43	0.0040474	08104	6339285.3	10762402
8104022001	08104	5	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104	6191860.1	24920020
8104022023	08104	3	2017	Florida	147425.2	2017	10624	1566245750	13	0.0012236	08104	1916528.1	18439841
8104022035	08104	2	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104	4275332.0	14854127
8104022036	08104	7	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104	8845514.4	30904911
8104022040	08104	4	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104	10319766.8	21763625
8104032004	08104	7	2017	Florida	147425.2	2017	10624	1566245750	175	0.0164721	08104	25799417.0	30904911
8104032007	08104	2	2017	Florida	147425.2	2017	10624	1566245750	30	0.0028238	08104	4422757.2	14854127
8104032012	08104	6	2017	Florida	147425.2	2017	10624	1566245750	26	0.0024473	08104	3833056.2	27957514
8104032028	08104	20	2017	Florida	147425.2	2017	10624	1566245750	174	0.0163780	08104	25651991.8	65414468
8104032045	08104	7	2017	Florida	147425.2	2017	10624	1566245750	244	0.0229669	08104	35971758.6	30904911
8104032050	08104	1	2017	Florida	147425.2	2017	10624	1566245750	67	0.0063065	08104	9877491.1	10762402
8104032053	08104	2	2017	Florida	147425.2	2017	10624	1566245750	58	0.0054593	08104	8550663.9	14854127
8104032901	08104	3	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104	3243355.3	18439841
8104042012	08104	40	2017	Florida	147425.2	2017	10624	1566245750	745	0.0701242	08104	109831803.8	113479374
8104042014	08104	8	2017	Florida	147425.2	2017	10624	1566245750	118	0.0111069	08104	17396178.3	33780977
8104042017	08104	3	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104	8845514.4	18439841
8104042030	08104	1	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104	6191860.1	10762402
8104042042	08104	4	2017	Florida	147425.2	2017	10624	1566245750	89	0.0083773	08104	13120846.4	21763625
8104042043	08104	3	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104	4275332.0	18439841
8104042047	08104	3	2017	Florida	147425.2	2017	10624	1566245750	59	0.0055535	08104	8698089.2	18439841
8104042062	08104	9	2017	Florida	147425.2	2017	10624	1566245750	75	0.0070595	08104	11056893.0	36598749
8104052003	08104	6	2017	Florida	147425.2	2017	10624	1566245750	34	0.0032003	08104	5012458.2	27957514
8104052010	08104	4	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104	8992939.6	21763625
8104052025	08104	1	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104	3980481.5	10762402
8104052027	08104	4	2017	Florida	147425.2	2017	10624	1566245750	15	0.0014119	08104	2211378.6	21763625
8104052029	08104	1	2017	Florida	147425.2	2017	10624	1566245750	11	0.0010354	08104	1621677.6	10762402
8104052031	08104	7	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104	8992939.6	30904911
8104052032	08104	4	2017	Florida	147425.2	2017	10624	1566245750	47	0.0044239	08104	6928986.3	21763625
8104052039	08104	20	2017	Florida	147425.2	2017	10624	1566245750	181	0.0170369	08104	26683968.4	65414468
8104052043	08104	27	2017	Florida	147425.2	2017	10624	1566245750	291	0.0273908	08104	42900744.8	82634479
8104052051	08104	1	2017	Florida	147425.2	2017	10624	1566245750	6	0.0005648	08104	884551.4	10762402
8104052054	08104	16	2017	Florida	147425.2	2017	10624	1566245750	124	0.0116717	08104	18280729.8	55267776
8104052056	08104	1	2017	Florida	147425.2	2017	10624	1566245750	24	0.0022590	08104	3538205.8	10762402
8104052059	08104	13	2017	Florida	147425.2	2017	10624	1566245750	115	0.0108245	08104	16953902.6	47445921
8104052901	08104	6	2017	Florida	147425.2	2017	10624	1566245750	87	0.0081890	08104	12825995.9	27957514
8104062002	08104	1	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104	3243355.3	10762402
8104062003	08104	4	2017	Florida	147425.2	2017	10624	1566245750	17	0.0016002	08104	2506229.1	21763625
8104062013	08104	6	2017	Florida	147425.2	2017	10624	1566245750	282	0.0265437	08104	41573917.7	27957514
8104062024	08104	2	2017	Florida	147425.2	2017	10624	1566245750	141	0.0132718	08104	20786958.8	14854127
8104062035	08104	1	2017	Florida	147425.2	2017	10624	1566245750	31	0.0029179	08104	4570182.4	10762402
8104062036	08104	1	2017	Florida	147425.2	2017	10624	1566245750	36	0.0033886	08104	5307308.6	10762402
8104062049	08104	21	2017	Florida	147425.2	2017	10624	1566245750	499	0.0469691	08104	73565194.8	67911268
8104062051	08104	3	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104	10319766.8	18439841
8104062056	08104	6	2017	Florida	147425.2	2017	10624	1566245750	122	0.0114834	08104	17985879.3	27957514
8104062060	08104	1	2017	Florida	147425.2	2017	10624	1566245750	28	0.0026355	08104	4127906.7	10762402
8104062901	08104	9	2017	Florida	147425.2	2017	10624	1566245750	123	0.0115776	08104	18133304.5	36598749
8105012014	08105	4	2017	Hualqui	202715.1	2017	24333	4932666876	25	0.0010274	08105	5067877.9	21763625
8105012028	08105	9	2017	Hualqui	202715.1	2017	24333	4932666876	137	0.0056302	08105	27771970.7	36598749
8105012034	08105	6	2017	Hualqui	202715.1	2017	24333	4932666876	50	0.0020548	08105	10135755.7	27957514
8105022024	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	10	0.0004110	08105	2027151.1	10762402
8105022025	08105	12	2017	Hualqui	202715.1	2017	24333	4932666876	64	0.0026302	08105	12973767.3	44786307
8105022034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	38	0.0015617	08105	7703174.3	10762402
8105022038	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	15	0.0006164	08105	3040726.7	14854127
8105022044	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	76	0.0031233	08105	15406348.7	10762402
8105022901	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	99	0.0040685	08105	20068796.3	18439841
8105032001	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	18	0.0007397	08105	3648872.1	14854127
8105032003	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	14	0.0005754	08105	2838011.6	14854127
8105032034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	32	0.0013151	08105	6486883.7	10762402
8105032039	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	94	0.0038631	08105	19055220.7	18439841

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

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

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

r3_100 <- h_y_m_comuna_corr_01[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

zona	código.x	Freq.x	anio	comuna.x	promedio_i	año	personas	Ingresos_expandidos	Freq.y	p_poblacional	código.y	multi_pob	est_ing	ing_medio_zona
8101252025	08101	9	2017	Concepción	197625.8	2017	223574	44183983882	60	0.0002684	08101	11857546.2	36598749	609979.15
8101282901	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	31	0.0001387	08101	6126398.9	30904911	996932.60
8101292012	08101	6	2017	Concepción	197625.8	2017	223574	44183983882	86	0.0003847	08101	16995816.2	27957514	325087.37
8101292020	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	61	0.0002728	08101	12055172.0	39367718	645372.42
8101292023	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	54	0.0002415	08101	10671791.6	30904911	572313.16
8101292901	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	21	0.0000939	08101	4150141.2	14854127	707339.39
8101302001	08101	24	2017	Concepción	197625.8	2017	223574	44183983882	280	0.0012524	08101	55335215.6	75323358	269011.99
8101302005	08101	40	2017	Concepción	197625.8	2017	223574	44183983882	688	0.0030773	08101	135966529.7	113479374	164940.95
8101302008	08101	12	2017	Concepción	197625.8	2017	223574	44183983882	98	0.0004383	08101	19367325.5	44786307	457003.13
8101302011	08101	18	2017	Concepción	197625.8	2017	223574	44183983882	469	0.0020977	08101	92686486.1	60375631	128732.69
8101302016	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	13	0.0000581	08101	2569135.0	21763625	1674124.96
8101302018	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	51	0.0002281	08101	10078914.3	21763625	426737.74
8101302019	08101	10	2017	Concepción	197625.8	2017	223574	44183983882	198	0.0008856	08101	39129902.4	39367718	198826.86
8101302021	08101	19	2017	Concepción	197625.8	2017	223574	44183983882	401	0.0017936	08101	79247933.7	62902981	156865.29
8101302024	08101	2	2017	Concepción	197625.8	2017	223574	44183983882	88	0.0003936	08101	17391067.8	14854127	168796.90
8101302901	08101	3	2017	Concepción	197625.8	2017	223574	44183983882	16	0.0000716	08101	3162012.3	18439841	1152490.08
8101312001	08101	4	2017	Concepción	197625.8	2017	223574	44183983882	90	0.0004026	08101	17786319.3	21763625	241818.05
8101312004	08101	5	2017	Concepción	197625.8	2017	223574	44183983882	63	0.0002818	08101	12450423.5	24920020	395555.87
8101312013	08101	94	2017	Concepción	197625.8	2017	223574	44183983882	1045	0.0046741	08101	206518929.6	234692698	224586.31
8101312014	08101	51	2017	Concepción	197625.8	2017	223574	44183983882	534	0.0023885	08101	105532161.1	138854721	260027.57
8101312017	08101	7	2017	Concepción	197625.8	2017	223574	44183983882	47	0.0002102	08101	9288411.2	30904911	657551.29
8101322025	08101	31	2017	Concepción	197625.8	2017	223574	44183983882	100	0.0004473	08101	19762577.0	92253383	922533.83
8102052001	08102	9	2017	Coronel	217018.1	2017	116262	25230952648	62	0.0005333	08102	13455119.2	36598749	590302.40
8102062004	08102	3	2017	Coronel	217018.1	2017	116262	25230952648	29	0.0002494	08102	6293523.5	18439841	635856.59
8102062005	08102	118	2017	Coronel	217018.1	2017	116262	25230952648	350	0.0030104	08102	75956317.9	286828912	819511.18
8102062009	08102	134	2017	Coronel	217018.1	2017	116262	25230952648	382	0.0032857	08102	82900895.5	321243938	840952.72
8102072005	08102	95	2017	Coronel	217018.1	2017	116262	25230952648	624	0.0053672	08102	135419263.8	236879699	379614.90
8102082002	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	24	0.0002064	08102	5208433.2	14854127	618921.97
8102092010	08102	13	2017	Coronel	217018.1	2017	116262	25230952648	298	0.0025632	08102	64671379.2	47445921	159214.50
8102102007	08102	29	2017	Coronel	217018.1	2017	116262	25230952648	744	0.0063993	08102	161461430.0	87460766	117554.79
8102102011	08102	16	2017	Coronel	217018.1	2017	116262	25230952648	503	0.0043264	08102	109160079.7	55267776	109876.29
8102112006	08102	2	2017	Coronel	217018.1	2017	116262	25230952648	55	0.0004731	08102	11935992.8	14854127	270075.04
8102112008	08102	20	2017	Coronel	217018.1	2017	116262	25230952648	104	0.0008945	08102	22569877.3	65414468	628985.27
8104012005	08104	2	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104	3980481.5	14854127	550152.86
8104012023	08104	24	2017	Florida	147425.2	2017	10624	1566245750	163	0.0153426	08104	24030314.1	75323358	462106.49
8104012029	08104	2	2017	Florida	147425.2	2017	10624	1566245750	45	0.0042357	08104	6634135.8	14854127	330091.72
8104012037	08104	11	2017	Florida	147425.2	2017	10624	1566245750	162	0.0152485	08104	23882888.9	42095048	259845.98
8104012043	08104	7	2017	Florida	147425.2	2017	10624	1566245750	68	0.0064006	08104	10024916.3	30904911	454483.98
8104012044	08104	16	2017	Florida	147425.2	2017	10624	1566245750	214	0.0201431	08104	31549001.4	55267776	258260.63
8104012052	08104	8	2017	Florida	147425.2	2017	10624	1566245750	93	0.0087538	08104	13710547.3	33780977	363236.31
8104012054	08104	1	2017	Florida	147425.2	2017	10624	1566245750	43	0.0040474	08104	6339285.3	10762402	250288.42
8104022001	08104	5	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104	6191860.1	24920020	593333.80
8104022023	08104	3	2017	Florida	147425.2	2017	10624	1566245750	13	0.0012236	08104	1916528.1	18439841	1418449.33
8104022035	08104	2	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104	4275332.0	14854127	512211.28
8104022036	08104	7	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104	8845514.4	30904911	515081.84
8104022040	08104	4	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104	10319766.8	21763625	310908.92
8104032004	08104	7	2017	Florida	147425.2	2017	10624	1566245750	175	0.0164721	08104	25799417.0	30904911	176599.49
8104032007	08104	2	2017	Florida	147425.2	2017	10624	1566245750	30	0.0028238	08104	4422757.2	14854127	495137.57
8104032012	08104	6	2017	Florida	147425.2	2017	10624	1566245750	26	0.0024473	08104	3833056.2	27957514	1075288.99
8104032028	08104	20	2017	Florida	147425.2	2017	10624	1566245750	174	0.0163780	08104	25651991.8	65414468	375945.22
8104032045	08104	7	2017	Florida	147425.2	2017	10624	1566245750	244	0.0229669	08104	35971758.6	30904911	126659.47
8104032050	08104	1	2017	Florida	147425.2	2017	10624	1566245750	67	0.0063065	08104	9877491.1	10762402	160632.87
8104032053	08104	2	2017	Florida	147425.2	2017	10624	1566245750	58	0.0054593	08104	8550663.9	14854127	256105.64
8104032901	08104	3	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104	3243355.3	18439841	838174.60
8104042012	08104	40	2017	Florida	147425.2	2017	10624	1566245750	745	0.0701242	08104	109831803.8	113479374	152321.31
8104042014	08104	8	2017	Florida	147425.2	2017	10624	1566245750	118	0.0111069	08104	17396178.3	33780977	286279.47
8104042017	08104	3	2017	Florida	147425.2	2017	10624	1566245750	60	0.0056476	08104	8845514.4	18439841	307330.69
8104042030	08104	1	2017	Florida	147425.2	2017	10624	1566245750	42	0.0039533	08104	6191860.1	10762402	256247.67
8104042042	08104	4	2017	Florida	147425.2	2017	10624	1566245750	89	0.0083773	08104	13120846.4	21763625	244535.11
8104042043	08104	3	2017	Florida	147425.2	2017	10624	1566245750	29	0.0027297	08104	4275332.0	18439841	635856.59
8104042047	08104	3	2017	Florida	147425.2	2017	10624	1566245750	59	0.0055535	08104	8698089.2	18439841	312539.68
8104042062	08104	9	2017	Florida	147425.2	2017	10624	1566245750	75	0.0070595	08104	11056893.0	36598749	487983.32
8104052003	08104	6	2017	Florida	147425.2	2017	10624	1566245750	34	0.0032003	08104	5012458.2	27957514	822279.82
8104052010	08104	4	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104	8992939.6	21763625	356780.73
8104052025	08104	1	2017	Florida	147425.2	2017	10624	1566245750	27	0.0025414	08104	3980481.5	10762402	398607.48
8104052027	08104	4	2017	Florida	147425.2	2017	10624	1566245750	15	0.0014119	08104	2211378.6	21763625	1450908.30
8104052029	08104	1	2017	Florida	147425.2	2017	10624	1566245750	11	0.0010354	08104	1621677.6	10762402	978400.18
8104052031	08104	7	2017	Florida	147425.2	2017	10624	1566245750	61	0.0057417	08104	8992939.6	30904911	506637.88
8104052032	08104	4	2017	Florida	147425.2	2017	10624	1566245750	47	0.0044239	08104	6928986.3	21763625	463055.84
8104052039	08104	20	2017	Florida	147425.2	2017	10624	1566245750	181	0.0170369	08104	26683968.4	65414468	361405.90
8104052043	08104	27	2017	Florida	147425.2	2017	10624	1566245750	291	0.0273908	08104	42900744.8	82634479	283967.28
8104052051	08104	1	2017	Florida	147425.2	2017	10624	1566245750	6	0.0005648	08104	884551.4	10762402	1793733.66
8104052054	08104	16	2017	Florida	147425.2	2017	10624	1566245750	124	0.0116717	08104	18280729.8	55267776	445707.87
8104052056	08104	1	2017	Florida	147425.2	2017	10624	1566245750	24	0.0022590	08104	3538205.8	10762402	448433.42
8104052059	08104	13	2017	Florida	147425.2	2017	10624	1566245750	115	0.0108245	08104	16953902.6	47445921	412573.23
8104052901	08104	6	2017	Florida	147425.2	2017	10624	1566245750	87	0.0081890	08104	12825995.9	27957514	321350.73
8104062002	08104	1	2017	Florida	147425.2	2017	10624	1566245750	22	0.0020708	08104	3243355.3	10762402	489200.09
8104062003	08104	4	2017	Florida	147425.2	2017	10624	1566245750	17	0.0016002	08104	2506229.1	21763625	1280213.21
8104062013	08104	6	2017	Florida	147425.2	2017	10624	1566245750	282	0.0265437	08104	41573917.7	27957514	99140.12
8104062024	08104	2	2017	Florida	147425.2	2017	10624	1566245750	141	0.0132718	08104	20786958.8	14854127	105348.42
8104062035	08104	1	2017	Florida	147425.2	2017	10624	1566245750	31	0.0029179	08104	4570182.4	10762402	347174.26
8104062036	08104	1	2017	Florida	147425.2	2017	10624	1566245750	36	0.0033886	08104	5307308.6	10762402	298955.61
8104062049	08104	21	2017	Florida	147425.2	2017	10624	1566245750	499	0.0469691	08104	73565194.8	67911268	136094.73
8104062051	08104	3	2017	Florida	147425.2	2017	10624	1566245750	70	0.0065889	08104	10319766.8	18439841	263426.30
8104062056	08104	6	2017	Florida	147425.2	2017	10624	1566245750	122	0.0114834	08104	17985879.3	27957514	229159.95
8104062060	08104	1	2017	Florida	147425.2	2017	10624	1566245750	28	0.0026355	08104	4127906.7	10762402	384371.50
8104062901	08104	9	2017	Florida	147425.2	2017	10624	1566245750	123	0.0115776	08104	18133304.5	36598749	297550.81
8105012014	08105	4	2017	Hualqui	202715.1	2017	24333	4932666876	25	0.0010274	08105	5067877.9	21763625	870544.98
8105012028	08105	9	2017	Hualqui	202715.1	2017	24333	4932666876	137	0.0056302	08105	27771970.7	36598749	267144.15
8105012034	08105	6	2017	Hualqui	202715.1	2017	24333	4932666876	50	0.0020548	08105	10135755.7	27957514	559150.28
8105022024	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	10	0.0004110	08105	2027151.1	10762402	1076240.20
8105022025	08105	12	2017	Hualqui	202715.1	2017	24333	4932666876	64	0.0026302	08105	12973767.3	44786307	699786.05
8105022034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	38	0.0015617	08105	7703174.3	10762402	283221.10
8105022038	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	15	0.0006164	08105	3040726.7	14854127	990275.15
8105022044	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	76	0.0031233	08105	15406348.7	10762402	141610.55
8105022901	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	99	0.0040685	08105	20068796.3	18439841	186261.02
8105032001	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	18	0.0007397	08105	3648872.1	14854127	825229.29
8105032003	08105	2	2017	Hualqui	202715.1	2017	24333	4932666876	14	0.0005754	08105	2838011.6	14854127	1061009.09
8105032034	08105	1	2017	Hualqui	202715.1	2017	24333	4932666876	32	0.0013151	08105	6486883.7	10762402	336325.06
8105032039	08105	3	2017	Hualqui	202715.1	2017	24333	4932666876	94	0.0038631	08105	19055220.7	18439841	196168.52

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "P15/region_08_P15_r.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