Expansión de la CASEN sobre el CENSO (Región 06)

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 06.

Ensayaremos diferentes modelos dentro del análisis de regresión cuya variable independiente será: “frecuencia de población que posee la variable Censal respecto a la zona” y la dependiente: “ingreso expandido 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 02 y con la zona = 2:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 6) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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	6101092004	12	6101	4	2017
2	6101102003	12	6101	2	2017
3	6101102007	12	6101	33	2017
4	6101102009	12	6101	9	2017
5	6101102015	12	6101	16	2017
6	6101112015	12	6101	21	2017
7	6101122008	12	6101	3	2017
8	6101122901	12	6101	5	2017
9	6101132005	12	6101	11	2017
10	6101132008	12	6101	2	2017
11	6101132013	12	6101	39	2017
12	6101132014	12	6101	94	2017
13	6101142010	12	6101	2	2017
14	6101142011	12	6101	15	2017
15	6101142013	12	6101	11	2017
16	6101182001	12	6101	47	2017
17	6101182002	12	6101	17	2017
18	6101182005	12	6101	42	2017
19	6101182006	12	6101	4	2017
20	6101182015	12	6101	30	2017
755	6102012001	12	6102	34	2017
756	6102012002	12	6102	9	2017
757	6102012004	12	6102	17	2017
758	6102012006	12	6102	60	2017
759	6102012009	12	6102	5	2017
760	6102012014	12	6102	8	2017
761	6102012015	12	6102	3	2017
762	6102012018	12	6102	8	2017
763	6102022002	12	6102	3	2017
764	6102022003	12	6102	62	2017
765	6102022005	12	6102	17	2017
766	6102022007	12	6102	30	2017
767	6102022012	12	6102	15	2017
768	6102022013	12	6102	18	2017
769	6102022016	12	6102	11	2017
770	6102022017	12	6102	45	2017
771	6102022019	12	6102	40	2017
772	6102022020	12	6102	7	2017
773	6102022901	12	6102	9	2017
774	6102032011	12	6102	17	2017
1509	6103012003	12	6103	128	2017
1510	6103012004	12	6103	62	2017
1511	6103022002	12	6103	42	2017
1512	6103032001	12	6103	21	2017
1513	6103042005	12	6103	36	2017
2248	6104012002	12	6104	40	2017
2249	6104012006	12	6104	21	2017
2250	6104022006	12	6104	61	2017
2251	6104032006	12	6104	71	2017
2252	6104032008	12	6104	30	2017
2253	6104042013	12	6104	25	2017
2254	6104042015	12	6104	3	2017
2255	6104052004	12	6104	6	2017
2256	6104052005	12	6104	38	2017
2257	6104052007	12	6104	33	2017
2258	6104052010	12	6104	12	2017
2259	6104052014	12	6104	3	2017
2260	6104052016	12	6104	6	2017
2261	6104062011	12	6104	31	2017
2262	6104062016	12	6104	4	2017
2263	6104062901	12	6104	17	2017
2264	6104072011	12	6104	5	2017
2265	6104082001	12	6104	11	2017
2266	6104082009	12	6104	4	2017
2267	6104082901	12	6104	3	2017
3002	6105012001	12	6105	7	2017
3003	6105012002	12	6105	11	2017
3004	6105012003	12	6105	24	2017
3005	6105022003	12	6105	105	2017
3006	6105022005	12	6105	64	2017
3007	6105032004	12	6105	91	2017
3008	6105042004	12	6105	78	2017
3743	6106012004	12	6106	8	2017
3744	6106012012	12	6106	4	2017
3745	6106022003	12	6106	33	2017
3746	6106022004	12	6106	28	2017
3747	6106022006	12	6106	5	2017
3748	6106022010	12	6106	85	2017
3749	6106032005	12	6106	3	2017
3750	6106032007	12	6106	13	2017
3751	6106032009	12	6106	24	2017
3752	6106032011	12	6106	17	2017
3753	6106042001	12	6106	48	2017
3754	6106042002	12	6106	24	2017
3755	6106042008	12	6106	7	2017
3756	6106042011	12	6106	8	2017
3757	6106042012	12	6106	24	2017
4492	6107012001	12	6107	9	2017
4493	6107012008	12	6107	6	2017
4494	6107012021	12	6107	7	2017
4495	6107022003	12	6107	41	2017
4496	6107022007	12	6107	35	2017
4497	6107022009	12	6107	74	2017
4498	6107032005	12	6107	65	2017
4499	6107032006	12	6107	23	2017
4500	6107042002	12	6107	19	2017
4501	6107042016	12	6107	26	2017
4502	6107042019	12	6107	20	2017
4503	6107042023	12	6107	3	2017
4504	6107042024	12	6107	3	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	6101092004	4	2017	06101
2	6101102003	2	2017	06101
3	6101102007	33	2017	06101
4	6101102009	9	2017	06101
5	6101102015	16	2017	06101
6	6101112015	21	2017	06101
7	6101122008	3	2017	06101
8	6101122901	5	2017	06101
9	6101132005	11	2017	06101
10	6101132008	2	2017	06101
11	6101132013	39	2017	06101
12	6101132014	94	2017	06101
13	6101142010	2	2017	06101
14	6101142011	15	2017	06101
15	6101142013	11	2017	06101
16	6101182001	47	2017	06101
17	6101182002	17	2017	06101
18	6101182005	42	2017	06101
19	6101182006	4	2017	06101
20	6101182015	30	2017	06101
755	6102012001	34	2017	06102
756	6102012002	9	2017	06102
757	6102012004	17	2017	06102
758	6102012006	60	2017	06102
759	6102012009	5	2017	06102
760	6102012014	8	2017	06102
761	6102012015	3	2017	06102
762	6102012018	8	2017	06102
763	6102022002	3	2017	06102
764	6102022003	62	2017	06102
765	6102022005	17	2017	06102
766	6102022007	30	2017	06102
767	6102022012	15	2017	06102
768	6102022013	18	2017	06102
769	6102022016	11	2017	06102
770	6102022017	45	2017	06102
771	6102022019	40	2017	06102
772	6102022020	7	2017	06102
773	6102022901	9	2017	06102
774	6102032011	17	2017	06102
1509	6103012003	128	2017	06103
1510	6103012004	62	2017	06103
1511	6103022002	42	2017	06103
1512	6103032001	21	2017	06103
1513	6103042005	36	2017	06103
2248	6104012002	40	2017	06104
2249	6104012006	21	2017	06104
2250	6104022006	61	2017	06104
2251	6104032006	71	2017	06104
2252	6104032008	30	2017	06104
2253	6104042013	25	2017	06104
2254	6104042015	3	2017	06104
2255	6104052004	6	2017	06104
2256	6104052005	38	2017	06104
2257	6104052007	33	2017	06104
2258	6104052010	12	2017	06104
2259	6104052014	3	2017	06104
2260	6104052016	6	2017	06104
2261	6104062011	31	2017	06104
2262	6104062016	4	2017	06104
2263	6104062901	17	2017	06104
2264	6104072011	5	2017	06104
2265	6104082001	11	2017	06104
2266	6104082009	4	2017	06104
2267	6104082901	3	2017	06104
3002	6105012001	7	2017	06105
3003	6105012002	11	2017	06105
3004	6105012003	24	2017	06105
3005	6105022003	105	2017	06105
3006	6105022005	64	2017	06105
3007	6105032004	91	2017	06105
3008	6105042004	78	2017	06105
3743	6106012004	8	2017	06106
3744	6106012012	4	2017	06106
3745	6106022003	33	2017	06106
3746	6106022004	28	2017	06106
3747	6106022006	5	2017	06106
3748	6106022010	85	2017	06106
3749	6106032005	3	2017	06106
3750	6106032007	13	2017	06106
3751	6106032009	24	2017	06106
3752	6106032011	17	2017	06106
3753	6106042001	48	2017	06106
3754	6106042002	24	2017	06106
3755	6106042008	7	2017	06106
3756	6106042011	8	2017	06106
3757	6106042012	24	2017	06106
4492	6107012001	9	2017	06107
4493	6107012008	6	2017	06107
4494	6107012021	7	2017	06107
4495	6107022003	41	2017	06107
4496	6107022007	35	2017	06107
4497	6107022009	74	2017	06107
4498	6107032005	65	2017	06107
4499	6107032006	23	2017	06107
4500	6107042002	19	2017	06107
4501	6107042016	26	2017	06107
4502	6107042019	20	2017	06107
4503	6107042023	3	2017	06107
4504	6107042024	3	2017	06107

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
06101	6101092004	4	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102003	2	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102007	33	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102009	9	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102015	16	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101112015	21	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101122008	3	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101122901	5	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132005	11	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132008	2	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132013	39	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132014	94	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101142010	2	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101142011	15	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101142013	11	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182001	47	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182002	17	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182005	42	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182006	4	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182015	30	2017	Rancagua	243717.4	2017	241774	58924531866
06102	6102012001	34	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012002	9	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012004	17	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012006	60	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012009	5	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012014	8	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012015	3	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012018	8	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022002	3	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022003	62	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022005	17	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022007	30	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022012	15	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022013	18	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022016	11	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022017	45	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022019	40	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022020	7	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022901	9	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102032011	17	2017	Codegua	264737.7	2017	12988	3438412620
06103	6103012003	128	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103012004	62	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103022002	42	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103032001	21	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103042005	36	2017	Coinco	175814.1	2017	7359	1293816308
06104	6104012002	40	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104012006	21	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104022006	61	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104032006	71	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104032008	30	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104042013	25	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104042015	3	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052004	6	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052005	38	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052007	33	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052010	12	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052014	3	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052016	6	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104062011	31	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104062016	4	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104062901	17	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104072011	5	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104082001	11	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104082009	4	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104082901	3	2017	Coltauco	254006.7	2017	19597	4977769953
06105	6105012001	7	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105012002	11	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105012003	24	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105022003	105	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105022005	64	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105032004	91	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105042004	78	2017	Doñihue	198486.5	2017	20887	4145787348
06106	6106012004	8	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106012012	4	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022003	33	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022004	28	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022006	5	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022010	85	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032005	3	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032007	13	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032009	24	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032011	17	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042001	48	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042002	24	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042008	7	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042011	8	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042012	24	2017	Graneros	248394.9	2017	33437	8305580885
06107	6107012001	9	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107012008	6	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107012021	7	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107022003	41	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107022007	35	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107022009	74	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107032005	65	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107032006	23	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042002	19	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042016	26	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042019	20	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042023	3	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042024	3	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107052018	17	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107052020	59	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107052022	1	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107062015	8	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107062025	20	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107072013	16	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107082003	17	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107082017	7	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107082021	21	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107092004	3	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107092006	12	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107092010	19	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107092011	9	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107092012	31	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107102002	5	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107102014	1	2017	Las Cabras	201772.1	2017	24640	4971665251
06108	6108012006	12	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108012009	43	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108022005	2	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108042002	8	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108062901	2	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108072011	9	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108072901	14	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108092003	1	2017	Machalí	252049.6	2017	52505	13233865906
06108	6108092011	9	2017	Machalí	252049.6	2017	52505	13233865906
06109	6109012016	12	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109022010	1	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109022012	9	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109022015	15	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109032008	36	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109032013	20	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109032901	3	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109042002	39	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109042009	53	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109042017	9	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109052003	20	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109052017	8	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109062001	18	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109062003	14	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109072004	21	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109072007	33	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109072014	11	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109082005	25	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109082006	67	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109082011	19	2017	Malloa	250691.2	2017	13407	3361017589
06109	6109082012	7	2017	Malloa	250691.2	2017	13407	3361017589
06110	6110012007	32	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110012015	4	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110022001	96	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110022003	28	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110022005	10	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110022012	10	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110022013	44	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110022014	1	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110032002	5	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110032006	12	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110032008	30	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110032009	28	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110032010	28	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110032016	11	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110042004	56	2017	Mostazal	264277.9	2017	25343	6697593734
06110	6110042006	19	2017	Mostazal	264277.9	2017	25343	6697593734
06111	6111012001	8	2017	Olivar	256304.8	2017	13608	3487795575
06111	6111012002	62	2017	Olivar	256304.8	2017	13608	3487795575
06111	6111022002	259	2017	Olivar	256304.8	2017	13608	3487795575
06111	6111022003	21	2017	Olivar	256304.8	2017	13608	3487795575
06111	6111032003	53	2017	Olivar	256304.8	2017	13608	3487795575
06112	6112012005	17	2017	Peumo	230938.1	2017	14313	3305417128
06112	6112022005	8	2017	Peumo	230938.1	2017	14313	3305417128
06112	6112032001	17	2017	Peumo	230938.1	2017	14313	3305417128
06112	6112032007	37	2017	Peumo	230938.1	2017	14313	3305417128
06112	6112032008	9	2017	Peumo	230938.1	2017	14313	3305417128
06112	6112042002	15	2017	Peumo	230938.1	2017	14313	3305417128
06112	6112042004	2	2017	Peumo	230938.1	2017	14313	3305417128
06113	6113012007	32	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113012010	10	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113012011	7	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113012901	2	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113022008	15	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113022009	29	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113022011	16	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113022015	50	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113032001	4	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113032003	6	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113032004	30	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113032019	41	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113042005	57	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113042017	19	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113052006	5	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113052010	9	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113052012	7	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113052013	3	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113062016	26	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113072001	2	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113072003	17	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113072017	11	2017	Pichidegua	217210.9	2017	19714	4282095940
06113	6113072018	38	2017	Pichidegua	217210.9	2017	19714	4282095940
06114	6114012003	6	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114012005	18	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114012009	47	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114012010	6	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114012011	36	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114022004	23	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114022006	101	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114022007	1	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114022012	17	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114032001	15	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114032010	9	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114042001	8	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114042002	24	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114042004	1	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114042007	12	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06114	6114042008	1	2017	Quinta de Tilcoco	203672.8	2017	13002	2648154389
06115	6115012007	70	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115012024	9	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115012025	26	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115012034	12	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115012045	33	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115022003	9	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115022006	12	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115022901	2	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115032031	36	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115032901	2	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115042013	2	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115042020	20	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115042028	12	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115042031	25	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115052009	3	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115052022	1	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115052036	28	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115062004	42	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115062005	39	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115062017	14	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115062901	9	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115072011	7	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115072016	22	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115072019	11	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115072026	87	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115072044	9	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115082026	6	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115082032	34	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115082040	12	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115082901	5	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115092001	9	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115092010	4	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115092033	10	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115092042	10	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115102015	18	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115102029	45	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115102030	25	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115102037	20	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115102901	14	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115112002	15	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115112018	21	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115112023	7	2017	Rengo	250531.0	2017	58825	14737488444
06115	6115112035	5	2017	Rengo	250531.0	2017	58825	14737488444
06116	6116012014	183	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116012015	21	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116012016	11	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116012020	19	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116012024	20	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116012026	23	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116022005	70	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116022009	63	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116022016	9	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116032004	2	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116032006	17	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116032011	120	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116032012	2	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116032019	53	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116042001	11	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116042021	4	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116042901	5	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116052022	27	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116052027	43	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062002	32	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062003	11	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062008	11	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062010	14	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062013	25	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062017	18	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062018	41	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062023	32	2017	Requínoa	244836.0	2017	27968	6847572657
06116	6116062025	8	2017	Requínoa	244836.0	2017	27968	6847572657
06117	6117012001	11	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117012014	11	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117012030	70	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117012037	20	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117012039	10	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117022025	46	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117032003	20	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117032006	43	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117032009	146	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117032024	30	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117032030	22	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117042002	4	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117042008	1	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117042016	11	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117042026	59	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117042029	27	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117052003	19	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117052004	7	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117052015	24	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117052023	6	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117052028	19	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117052031	22	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117062007	9	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117062010	20	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117062012	20	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117062017	24	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117072007	14	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117072013	13	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117072020	38	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117072021	2	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117072901	11	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117082001	53	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117082021	88	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117092020	9	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117092035	15	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117092037	83	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117092901	31	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117102035	56	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117102036	29	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117102038	33	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117102039	15	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117112018	11	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117112019	4	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117112032	62	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117112033	10	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117112034	8	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117122005	18	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117122011	33	2017	San Vicente	242866.0	2017	46766	11357872282
06117	6117122027	31	2017	San Vicente	242866.0	2017	46766	11357872282
06201	6201012003	10	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012004	7	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012005	116	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012007	13	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012017	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012018	5	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012022	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012024	6	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012025	112	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012026	9	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201012901	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201022028	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201022901	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201032001	4	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201032006	6	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201032008	5	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201032029	4	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201032901	3	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201062002	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201062011	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201062012	2	2017	Pichilemu	230362.3	2017	16394	3776560181
06201	6201062027	1	2017	Pichilemu	230362.3	2017	16394	3776560181
06202	6202012004	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012007	9	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012008	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012009	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012019	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012022	4	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012025	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012027	2	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012029	3	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202012901	2	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022001	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022006	2	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022011	5	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022016	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022018	2	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022026	2	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022031	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022034	3	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202022901	1	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202032008	3	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202032021	3	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202032031	2	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202032033	3	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202042003	4	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202042019	9	2017	La Estrella	211425.0	2017	3041	642943494
06202	6202042901	6	2017	La Estrella	211425.0	2017	3041	642943494
06203	6203012010	4	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203012019	6	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203012020	12	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203012901	1	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203022017	2	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203022022	1	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203022901	14	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203032004	1	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203032014	15	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203032023	2	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203032901	10	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203042007	1	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203042019	7	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203052006	1	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203062006	1	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203062012	2	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203062013	5	2017	Litueche	237979.9	2017	6294	1497845780
06203	6203072016	18	2017	Litueche	237979.9	2017	6294	1497845780
06204	6204012002	2	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204012003	2	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204012005	25	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204012006	4	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204012007	31	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204012011	11	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204012012	13	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204022006	8	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204022007	2	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204022008	37	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204022009	21	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204022010	3	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204032001	2	2017	Marchihue	237849.2	2017	7308	1738201845
06204	6204032004	17	2017	Marchihue	237849.2	2017	7308	1738201845
06205	6205012007	1	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205012013	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205012025	85	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205012028	6	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205012901	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022004	2	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022010	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022016	13	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022021	1	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022027	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022032	4	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205022901	6	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205032005	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205032008	50	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205032009	1	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205032018	55	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205032019	141	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042003	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042009	4	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042012	46	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042014	36	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042017	2	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042018	11	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042023	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042031	2	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205042901	23	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205052002	1	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205052003	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205052006	7	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205052011	3	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205052022	15	2017	Navidad	165555.2	2017	6641	1099452202
06205	6205052029	28	2017	Navidad	165555.2	2017	6641	1099452202
06206	6206012017	7	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206012019	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206012027	4	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022002	44	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022007	3	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022009	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022010	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022015	7	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022024	6	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022026	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022032	3	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022033	2	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206022901	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206032004	6	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206032016	2	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206042011	6	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206042012	3	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206042030	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206042901	2	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052005	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052006	7	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052010	2	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052022	1	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052029	5	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052031	2	2017	Paredones	194146.1	2017	6188	1201375821
06206	6206052035	16	2017	Paredones	194146.1	2017	6188	1201375821
06301	6301012016	4	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301022004	44	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301022005	21	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301022015	2	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301022018	26	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301022026	2	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301022901	4	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301032013	22	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301032015	2	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301032018	1	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301032022	105	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301042008	18	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301042009	34	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301042012	90	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301042021	59	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301042901	19	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301052017	157	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301062025	33	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301062901	2	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301072001	3	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301082001	6	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301082011	3	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301092007	11	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301092019	62	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301102003	14	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301102010	8	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301102024	11	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301112023	33	2017	San Fernando	239724.5	2017	73973	17733143348
06301	6301122023	20	2017	San Fernando	239724.5	2017	73973	17733143348
06302	6302012006	14	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012011	5	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012013	10	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012016	40	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012019	6	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012020	3	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012023	9	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302012034	30	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302022001	1	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302022020	7	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302022028	33	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302022031	4	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302032004	4	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302032007	2	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302032010	3	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302032014	6	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302032015	18	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302042017	6	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302042024	1	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302042901	1	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052005	6	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052006	1	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052008	2	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052022	39	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052029	4	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052030	5	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052032	5	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052033	2	2017	Chépica	207192.9	2017	15037	3115559148
06302	6302052901	3	2017	Chépica	207192.9	2017	15037	3115559148
06303	6303012003	3	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303012021	8	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303022001	4	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303022002	6	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303022007	4	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303022029	10	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303022033	6	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303022901	3	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303032004	1	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303032010	12	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303032026	2	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303032029	25	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303032034	15	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303032035	11	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303042004	31	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303042011	7	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303042025	5	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303052023	56	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303062005	22	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303062009	4	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303062018	17	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303062023	2	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303062901	1	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303072022	2	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303072028	13	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303072032	1	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303072901	2	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303082029	28	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303082036	36	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303092019	3	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303092024	18	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303092029	19	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303092037	27	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303102003	2	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303102026	38	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303102029	8	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303102034	10	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303102901	2	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112003	11	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112008	1	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112011	3	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112014	19	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112023	4	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112025	6	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303112026	65	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303122015	10	2017	Chimbarongo	227716.7	2017	35399	8060942027
06303	6303122016	22	2017	Chimbarongo	227716.7	2017	35399	8060942027
06304	6304012004	3	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304012006	5	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304012014	9	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304012015	11	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304012018	4	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304012022	5	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304012901	3	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304022001	3	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304022003	33	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304022008	2	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304022013	9	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304022015	8	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304022019	7	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304032002	8	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304032011	2	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304042009	6	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304042016	10	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304042017	8	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304042020	11	2017	Lolol	210117.9	2017	6811	1431112941
06304	6304042021	1	2017	Lolol	210117.9	2017	6811	1431112941
06305	6305012004	4	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305012011	9	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305012014	20	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305012015	18	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305012016	1	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305022007	7	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305022024	12	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305032001	8	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305032010	8	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305032014	30	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305032016	2	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305032017	5	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042004	2	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042009	3	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042013	11	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042016	2	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042017	49	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042018	47	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305042901	10	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305052002	10	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305052019	33	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305052020	17	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305052021	8	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305052901	7	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305062022	6	2017	Nancagua	213675.0	2017	17833	3810465416
06305	6305062023	12	2017	Nancagua	213675.0	2017	17833	3810465416
06306	6306012012	18	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306012015	42	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022002	1	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022003	24	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022004	4	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022007	6	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022011	1	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022014	19	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022016	6	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022018	9	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306022022	25	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306032001	29	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306032005	5	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306032006	7	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306032021	2	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306032027	13	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306042008	4	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306042009	23	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306042010	9	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306042011	22	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306042016	10	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306042017	19	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052006	1	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052013	10	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052019	18	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052021	2	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052023	4	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052024	31	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052026	8	2017	Palmilla	230550.0	2017	12482	2877725100
06306	6306052901	1	2017	Palmilla	230550.0	2017	12482	2877725100
06307	6307012001	13	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307012004	4	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307012005	4	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307012008	5	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307012009	23	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307012015	3	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307022003	5	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307022010	8	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307022011	20	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307022016	20	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307032001	20	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307032002	16	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307032005	5	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307032017	44	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307042006	6	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307042007	1	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307042013	3	2017	Peralillo	231695.3	2017	11007	2550270534
06307	6307042014	14	2017	Peralillo	231695.3	2017	11007	2550270534
06308	6308012001	1	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308012002	13	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308012008	6	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308012012	9	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308012013	10	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308022003	1	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308022006	2	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308022007	16	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308032005	9	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308032009	44	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308032010	36	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308032011	23	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308032013	2	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308042004	65	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308042005	37	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308042011	8	2017	Placilla	221358.7	2017	8738	1934232402
06308	6308042012	2	2017	Placilla	221358.7	2017	8738	1934232402
06309	6309012004	13	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309012006	7	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309012009	2	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309012017	93	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309022001	6	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309022003	8	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309022015	2	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309022018	3	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309022019	7	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309032007	1	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309032012	1	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309032014	46	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309042013	5	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309042022	2	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309042901	1	2017	Pumanque	239369.8	2017	3421	818883984
06309	6309052016	9	2017	Pumanque	239369.8	2017	3421	818883984
06310	6310012005	135	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310012011	6	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310012015	1	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310012020	55	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310022004	9	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310022007	11	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310022009	26	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310022011	7	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310022021	18	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310022901	2	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310032010	46	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310032012	36	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310032013	20	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310042003	2	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310042010	39	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310042014	1	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310042016	20	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310042017	16	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310052022	5	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310052024	25	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310062008	84	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310062015	8	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310062019	14	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310072002	41	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310072015	45	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310072019	3	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310082001	3	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310082006	23	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310082018	9	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310092001	69	2017	Santa Cruz	224421.9	2017	37855	8495489945
06310	6310102007	23	2017	Santa Cruz	224421.9	2017	37855	8495489945

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
06101	6101092004	4	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102003	2	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102007	33	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102009	9	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101102015	16	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101112015	21	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101122008	3	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101122901	5	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132005	11	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132008	2	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132013	39	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101132014	94	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101142010	2	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101142011	15	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101142013	11	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182001	47	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182002	17	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182005	42	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182006	4	2017	Rancagua	243717.4	2017	241774	58924531866
06101	6101182015	30	2017	Rancagua	243717.4	2017	241774	58924531866
06102	6102012001	34	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012002	9	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012004	17	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012006	60	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012009	5	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012014	8	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012015	3	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102012018	8	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022002	3	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022003	62	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022005	17	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022007	30	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022012	15	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022013	18	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022016	11	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022017	45	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022019	40	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022020	7	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102022901	9	2017	Codegua	264737.7	2017	12988	3438412620
06102	6102032011	17	2017	Codegua	264737.7	2017	12988	3438412620
06103	6103012003	128	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103012004	62	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103022002	42	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103032001	21	2017	Coinco	175814.1	2017	7359	1293816308
06103	6103042005	36	2017	Coinco	175814.1	2017	7359	1293816308
06104	6104012002	40	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104012006	21	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104022006	61	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104032006	71	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104032008	30	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104042013	25	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104042015	3	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052004	6	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052005	38	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052007	33	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052010	12	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052014	3	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104052016	6	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104062011	31	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104062016	4	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104062901	17	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104072011	5	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104082001	11	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104082009	4	2017	Coltauco	254006.7	2017	19597	4977769953
06104	6104082901	3	2017	Coltauco	254006.7	2017	19597	4977769953
06105	6105012001	7	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105012002	11	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105012003	24	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105022003	105	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105022005	64	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105032004	91	2017	Doñihue	198486.5	2017	20887	4145787348
06105	6105042004	78	2017	Doñihue	198486.5	2017	20887	4145787348
06106	6106012004	8	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106012012	4	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022003	33	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022004	28	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022006	5	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106022010	85	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032005	3	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032007	13	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032009	24	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106032011	17	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042001	48	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042002	24	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042008	7	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042011	8	2017	Graneros	248394.9	2017	33437	8305580885
06106	6106042012	24	2017	Graneros	248394.9	2017	33437	8305580885
06107	6107012001	9	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107012008	6	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107012021	7	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107022003	41	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107022007	35	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107022009	74	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107032005	65	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107032006	23	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042002	19	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042016	26	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042019	20	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042023	3	2017	Las Cabras	201772.1	2017	24640	4971665251
06107	6107042024	3	2017	Las Cabras	201772.1	2017	24640	4971665251

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
6101092004	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	128	0.0005294	06101
6101102003	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	37	0.0001530	06101
6101102007	06101	33	2017	Rancagua	243717.4	2017	241774	58924531866	481	0.0019895	06101
6101102009	06101	9	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101
6101102015	06101	16	2017	Rancagua	243717.4	2017	241774	58924531866	271	0.0011209	06101
6101112015	06101	21	2017	Rancagua	243717.4	2017	241774	58924531866	74	0.0003061	06101
6101122008	06101	3	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101
6101122901	06101	5	2017	Rancagua	243717.4	2017	241774	58924531866	45	0.0001861	06101
6101132005	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	345	0.0014270	06101
6101132008	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	13	0.0000538	06101
6101132013	06101	39	2017	Rancagua	243717.4	2017	241774	58924531866	432	0.0017868	06101
6101132014	06101	94	2017	Rancagua	243717.4	2017	241774	58924531866	825	0.0034123	06101
6101142010	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	43	0.0001779	06101
6101142011	06101	15	2017	Rancagua	243717.4	2017	241774	58924531866	253	0.0010464	06101
6101142013	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	189	0.0007817	06101
6101182001	06101	47	2017	Rancagua	243717.4	2017	241774	58924531866	1112	0.0045993	06101
6101182002	06101	17	2017	Rancagua	243717.4	2017	241774	58924531866	397	0.0016420	06101
6101182005	06101	42	2017	Rancagua	243717.4	2017	241774	58924531866	2002	0.0082805	06101
6101182006	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	115	0.0004757	06101
6101182015	06101	30	2017	Rancagua	243717.4	2017	241774	58924531866	569	0.0023534	06101
6102012001	06102	34	2017	Codegua	264737.7	2017	12988	3438412620	575	0.0442716	06102
6102012002	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	157	0.0120881	06102
6102012004	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	183	0.0140899	06102
6102012006	06102	60	2017	Codegua	264737.7	2017	12988	3438412620	631	0.0485833	06102
6102012009	06102	5	2017	Codegua	264737.7	2017	12988	3438412620	99	0.0076224	06102
6102012014	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	83	0.0063905	06102
6102012015	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	87	0.0066985	06102
6102012018	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	90	0.0069295	06102
6102022002	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	32	0.0024638	06102
6102022003	06102	62	2017	Codegua	264737.7	2017	12988	3438412620	811	0.0624423	06102
6102022005	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	388	0.0298737	06102
6102022007	06102	30	2017	Codegua	264737.7	2017	12988	3438412620	606	0.0466585	06102
6102022012	06102	15	2017	Codegua	264737.7	2017	12988	3438412620	462	0.0355713	06102
6102022013	06102	18	2017	Codegua	264737.7	2017	12988	3438412620	219	0.0168617	06102
6102022016	06102	11	2017	Codegua	264737.7	2017	12988	3438412620	265	0.0204034	06102
6102022017	06102	45	2017	Codegua	264737.7	2017	12988	3438412620	600	0.0461965	06102
6102022019	06102	40	2017	Codegua	264737.7	2017	12988	3438412620	269	0.0207114	06102
6102022020	06102	7	2017	Codegua	264737.7	2017	12988	3438412620	91	0.0070065	06102
6102022901	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	37	0.0028488	06102
6102032011	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	284	0.0218663	06102
6103012003	06103	128	2017	Coinco	175814.1	2017	7359	1293816308	1211	0.1645604	06103
6103012004	06103	62	2017	Coinco	175814.1	2017	7359	1293816308	970	0.1318114	06103
6103022002	06103	42	2017	Coinco	175814.1	2017	7359	1293816308	276	0.0375051	06103
6103032001	06103	21	2017	Coinco	175814.1	2017	7359	1293816308	666	0.0905014	06103
6103042005	06103	36	2017	Coinco	175814.1	2017	7359	1293816308	812	0.1103411	06103
6104012002	06104	40	2017	Coltauco	254006.7	2017	19597	4977769953	721	0.0367913	06104
6104012006	06104	21	2017	Coltauco	254006.7	2017	19597	4977769953	221	0.0112772	06104
6104022006	06104	61	2017	Coltauco	254006.7	2017	19597	4977769953	1313	0.0670001	06104
6104032006	06104	71	2017	Coltauco	254006.7	2017	19597	4977769953	1279	0.0652651	06104
6104032008	06104	30	2017	Coltauco	254006.7	2017	19597	4977769953	803	0.0409757	06104
6104042013	06104	25	2017	Coltauco	254006.7	2017	19597	4977769953	620	0.0316375	06104
6104042015	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	84	0.0042864	06104
6104052004	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	69	0.0035209	06104
6104052005	06104	38	2017	Coltauco	254006.7	2017	19597	4977769953	672	0.0342910	06104
6104052007	06104	33	2017	Coltauco	254006.7	2017	19597	4977769953	907	0.0462826	06104
6104052010	06104	12	2017	Coltauco	254006.7	2017	19597	4977769953	294	0.0150023	06104
6104052014	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	77	0.0039292	06104
6104052016	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	64	0.0032658	06104
6104062011	06104	31	2017	Coltauco	254006.7	2017	19597	4977769953	653	0.0333214	06104
6104062016	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	18	0.0009185	06104
6104062901	06104	17	2017	Coltauco	254006.7	2017	19597	4977769953	171	0.0087258	06104
6104072011	06104	5	2017	Coltauco	254006.7	2017	19597	4977769953	278	0.0141858	06104
6104082001	06104	11	2017	Coltauco	254006.7	2017	19597	4977769953	109	0.0055621	06104
6104082009	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	19	0.0009695	06104
6104082901	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	14	0.0007144	06104
6105012001	06105	7	2017	Doñihue	198486.5	2017	20887	4145787348	335	0.0160387	06105
6105012002	06105	11	2017	Doñihue	198486.5	2017	20887	4145787348	52	0.0024896	06105
6105012003	06105	24	2017	Doñihue	198486.5	2017	20887	4145787348	210	0.0100541	06105
6105022003	06105	105	2017	Doñihue	198486.5	2017	20887	4145787348	1037	0.0496481	06105
6105022005	06105	64	2017	Doñihue	198486.5	2017	20887	4145787348	757	0.0362426	06105
6105032004	06105	91	2017	Doñihue	198486.5	2017	20887	4145787348	1254	0.0600373	06105
6105042004	06105	78	2017	Doñihue	198486.5	2017	20887	4145787348	818	0.0391631	06105
6106012004	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	265	0.0079254	06106
6106012012	06106	4	2017	Graneros	248394.9	2017	33437	8305580885	50	0.0014953	06106
6106022003	06106	33	2017	Graneros	248394.9	2017	33437	8305580885	411	0.0122918	06106
6106022004	06106	28	2017	Graneros	248394.9	2017	33437	8305580885	221	0.0066094	06106
6106022006	06106	5	2017	Graneros	248394.9	2017	33437	8305580885	71	0.0021234	06106
6106022010	06106	85	2017	Graneros	248394.9	2017	33437	8305580885	592	0.0177049	06106
6106032005	06106	3	2017	Graneros	248394.9	2017	33437	8305580885	25	0.0007477	06106
6106032007	06106	13	2017	Graneros	248394.9	2017	33437	8305580885	279	0.0083441	06106
6106032009	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	241	0.0072076	06106
6106032011	06106	17	2017	Graneros	248394.9	2017	33437	8305580885	128	0.0038281	06106
6106042001	06106	48	2017	Graneros	248394.9	2017	33437	8305580885	324	0.0096899	06106
6106042002	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	258	0.0077160	06106
6106042008	06106	7	2017	Graneros	248394.9	2017	33437	8305580885	282	0.0084338	06106
6106042011	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	64	0.0019140	06106
6106042012	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	384	0.0114843	06106
6107012001	06107	9	2017	Las Cabras	201772.1	2017	24640	4971665251	253	0.0102679	06107
6107012008	06107	6	2017	Las Cabras	201772.1	2017	24640	4971665251	66	0.0026786	06107
6107012021	06107	7	2017	Las Cabras	201772.1	2017	24640	4971665251	152	0.0061688	06107
6107022003	06107	41	2017	Las Cabras	201772.1	2017	24640	4971665251	735	0.0298295	06107
6107022007	06107	35	2017	Las Cabras	201772.1	2017	24640	4971665251	525	0.0213068	06107
6107022009	06107	74	2017	Las Cabras	201772.1	2017	24640	4971665251	1472	0.0597403	06107
6107032005	06107	65	2017	Las Cabras	201772.1	2017	24640	4971665251	1243	0.0504464	06107
6107032006	06107	23	2017	Las Cabras	201772.1	2017	24640	4971665251	309	0.0125406	06107
6107042002	06107	19	2017	Las Cabras	201772.1	2017	24640	4971665251	862	0.0349838	06107
6107042016	06107	26	2017	Las Cabras	201772.1	2017	24640	4971665251	570	0.0231331	06107
6107042019	06107	20	2017	Las Cabras	201772.1	2017	24640	4971665251	426	0.0172890	06107
6107042023	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	57	0.0023133	06107
6107042024	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	274	0.0111201	06107

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
6101092004	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	128	0.0005294	06101	31195828
6101102003	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	37	0.0001530	06101	9017544
6101102007	06101	33	2017	Rancagua	243717.4	2017	241774	58924531866	481	0.0019895	06101	117228072
6101102009	06101	9	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101	21447132
6101102015	06101	16	2017	Rancagua	243717.4	2017	241774	58924531866	271	0.0011209	06101	66047417
6101112015	06101	21	2017	Rancagua	243717.4	2017	241774	58924531866	74	0.0003061	06101	18035088
6101122008	06101	3	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101	21447132
6101122901	06101	5	2017	Rancagua	243717.4	2017	241774	58924531866	45	0.0001861	06101	10967283
6101132005	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	345	0.0014270	06101	84082505
6101132008	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	13	0.0000538	06101	3168326
6101132013	06101	39	2017	Rancagua	243717.4	2017	241774	58924531866	432	0.0017868	06101	105285919
6101132014	06101	94	2017	Rancagua	243717.4	2017	241774	58924531866	825	0.0034123	06101	201066859
6101142010	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	43	0.0001779	06101	10479848
6101142011	06101	15	2017	Rancagua	243717.4	2017	241774	58924531866	253	0.0010464	06101	61660503
6101142013	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	189	0.0007817	06101	46062590
6101182001	06101	47	2017	Rancagua	243717.4	2017	241774	58924531866	1112	0.0045993	06101	271013754
6101182002	06101	17	2017	Rancagua	243717.4	2017	241774	58924531866	397	0.0016420	06101	96755810
6101182005	06101	42	2017	Rancagua	243717.4	2017	241774	58924531866	2002	0.0082805	06101	487922245
6101182006	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	115	0.0004757	06101	28027502
6101182015	06101	30	2017	Rancagua	243717.4	2017	241774	58924531866	569	0.0023534	06101	138675203
6102012001	06102	34	2017	Codegua	264737.7	2017	12988	3438412620	575	0.0442716	06102	152224150
6102012002	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	157	0.0120881	06102	41563811
6102012004	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	183	0.0140899	06102	48446990
6102012006	06102	60	2017	Codegua	264737.7	2017	12988	3438412620	631	0.0485833	06102	167049458
6102012009	06102	5	2017	Codegua	264737.7	2017	12988	3438412620	99	0.0076224	06102	26209028
6102012014	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	83	0.0063905	06102	21973225
6102012015	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	87	0.0066985	06102	23032176
6102012018	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	90	0.0069295	06102	23826389
6102022002	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	32	0.0024638	06102	8471605
6102022003	06102	62	2017	Codegua	264737.7	2017	12988	3438412620	811	0.0624423	06102	214702236
6102022005	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	388	0.0298737	06102	102718209
6102022007	06102	30	2017	Codegua	264737.7	2017	12988	3438412620	606	0.0466585	06102	160431017
6102022012	06102	15	2017	Codegua	264737.7	2017	12988	3438412620	462	0.0355713	06102	122308795
6102022013	06102	18	2017	Codegua	264737.7	2017	12988	3438412620	219	0.0168617	06102	57977546
6102022016	06102	11	2017	Codegua	264737.7	2017	12988	3438412620	265	0.0204034	06102	70155478
6102022017	06102	45	2017	Codegua	264737.7	2017	12988	3438412620	600	0.0461965	06102	158842591
6102022019	06102	40	2017	Codegua	264737.7	2017	12988	3438412620	269	0.0207114	06102	71214428
6102022020	06102	7	2017	Codegua	264737.7	2017	12988	3438412620	91	0.0070065	06102	24091126
6102022901	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	37	0.0028488	06102	9795293
6102032011	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	284	0.0218663	06102	75185493
6103012003	06103	128	2017	Coinco	175814.1	2017	7359	1293816308	1211	0.1645604	06103	212910932
6103012004	06103	62	2017	Coinco	175814.1	2017	7359	1293816308	970	0.1318114	06103	170539723
6103022002	06103	42	2017	Coinco	175814.1	2017	7359	1293816308	276	0.0375051	06103	48524705
6103032001	06103	21	2017	Coinco	175814.1	2017	7359	1293816308	666	0.0905014	06103	117092222
6103042005	06103	36	2017	Coinco	175814.1	2017	7359	1293816308	812	0.1103411	06103	142761087
6104012002	06104	40	2017	Coltauco	254006.7	2017	19597	4977769953	721	0.0367913	06104	183138855
6104012006	06104	21	2017	Coltauco	254006.7	2017	19597	4977769953	221	0.0112772	06104	56135488
6104022006	06104	61	2017	Coltauco	254006.7	2017	19597	4977769953	1313	0.0670001	06104	333510841
6104032006	06104	71	2017	Coltauco	254006.7	2017	19597	4977769953	1279	0.0652651	06104	324874612
6104032008	06104	30	2017	Coltauco	254006.7	2017	19597	4977769953	803	0.0409757	06104	203967407
6104042013	06104	25	2017	Coltauco	254006.7	2017	19597	4977769953	620	0.0316375	06104	157484175
6104042015	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	84	0.0042864	06104	21336566
6104052004	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	69	0.0035209	06104	17526465
6104052005	06104	38	2017	Coltauco	254006.7	2017	19597	4977769953	672	0.0342910	06104	170692525
6104052007	06104	33	2017	Coltauco	254006.7	2017	19597	4977769953	907	0.0462826	06104	230384107
6104052010	06104	12	2017	Coltauco	254006.7	2017	19597	4977769953	294	0.0150023	06104	74677980
6104052014	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	77	0.0039292	06104	19558518
6104052016	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	64	0.0032658	06104	16256431
6104062011	06104	31	2017	Coltauco	254006.7	2017	19597	4977769953	653	0.0333214	06104	165866397
6104062016	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	18	0.0009185	06104	4572121
6104062901	06104	17	2017	Coltauco	254006.7	2017	19597	4977769953	171	0.0087258	06104	43435151
6104072011	06104	5	2017	Coltauco	254006.7	2017	19597	4977769953	278	0.0141858	06104	70613872
6104082001	06104	11	2017	Coltauco	254006.7	2017	19597	4977769953	109	0.0055621	06104	27686734
6104082009	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	19	0.0009695	06104	4826128
6104082901	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	14	0.0007144	06104	3556094
6105012001	06105	7	2017	Doñihue	198486.5	2017	20887	4145787348	335	0.0160387	06105	66492975
6105012002	06105	11	2017	Doñihue	198486.5	2017	20887	4145787348	52	0.0024896	06105	10321298
6105012003	06105	24	2017	Doñihue	198486.5	2017	20887	4145787348	210	0.0100541	06105	41682163
6105022003	06105	105	2017	Doñihue	198486.5	2017	20887	4145787348	1037	0.0496481	06105	205830492
6105022005	06105	64	2017	Doñihue	198486.5	2017	20887	4145787348	757	0.0362426	06105	150254274
6105032004	06105	91	2017	Doñihue	198486.5	2017	20887	4145787348	1254	0.0600373	06105	248902060
6105042004	06105	78	2017	Doñihue	198486.5	2017	20887	4145787348	818	0.0391631	06105	162361950
6106012004	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	265	0.0079254	06106	65824653
6106012012	06106	4	2017	Graneros	248394.9	2017	33437	8305580885	50	0.0014953	06106	12419746
6106022003	06106	33	2017	Graneros	248394.9	2017	33437	8305580885	411	0.0122918	06106	102090311
6106022004	06106	28	2017	Graneros	248394.9	2017	33437	8305580885	221	0.0066094	06106	54895277
6106022006	06106	5	2017	Graneros	248394.9	2017	33437	8305580885	71	0.0021234	06106	17636039
6106022010	06106	85	2017	Graneros	248394.9	2017	33437	8305580885	592	0.0177049	06106	147049792
6106032005	06106	3	2017	Graneros	248394.9	2017	33437	8305580885	25	0.0007477	06106	6209873
6106032007	06106	13	2017	Graneros	248394.9	2017	33437	8305580885	279	0.0083441	06106	69302182
6106032009	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	241	0.0072076	06106	59863175
6106032011	06106	17	2017	Graneros	248394.9	2017	33437	8305580885	128	0.0038281	06106	31794550
6106042001	06106	48	2017	Graneros	248394.9	2017	33437	8305580885	324	0.0096899	06106	80479954
6106042002	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	258	0.0077160	06106	64085889
6106042008	06106	7	2017	Graneros	248394.9	2017	33437	8305580885	282	0.0084338	06106	70047367
6106042011	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	64	0.0019140	06106	15897275
6106042012	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	384	0.0114843	06106	95383649
6107012001	06107	9	2017	Las Cabras	201772.1	2017	24640	4971665251	253	0.0102679	06107	51048349
6107012008	06107	6	2017	Las Cabras	201772.1	2017	24640	4971665251	66	0.0026786	06107	13316960
6107012021	06107	7	2017	Las Cabras	201772.1	2017	24640	4971665251	152	0.0061688	06107	30669364
6107022003	06107	41	2017	Las Cabras	201772.1	2017	24640	4971665251	735	0.0298295	06107	148302515
6107022007	06107	35	2017	Las Cabras	201772.1	2017	24640	4971665251	525	0.0213068	06107	105930368
6107022009	06107	74	2017	Las Cabras	201772.1	2017	24640	4971665251	1472	0.0597403	06107	297008573
6107032005	06107	65	2017	Las Cabras	201772.1	2017	24640	4971665251	1243	0.0504464	06107	250802756
6107032006	06107	23	2017	Las Cabras	201772.1	2017	24640	4971665251	309	0.0125406	06107	62347588
6107042002	06107	19	2017	Las Cabras	201772.1	2017	24640	4971665251	862	0.0349838	06107	173927575
6107042016	06107	26	2017	Las Cabras	201772.1	2017	24640	4971665251	570	0.0231331	06107	115010113
6107042019	06107	20	2017	Las Cabras	201772.1	2017	24640	4971665251	426	0.0172890	06107	85954927
6107042023	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	57	0.0023133	06107	11501011
6107042024	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	274	0.0111201	06107	55285563

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 
## -227270557  -24366240  -11649272   15585447  355806173 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 25403332    2239041   11.35   <2e-16 ***
## Freq.x       2540780      72553   35.02   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 48630000 on 732 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6257 
## F-statistic:  1226 on 1 and 732 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 
## -227270557  -24366240  -11649272   15585447  355806173 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 25403332    2239041   11.35   <2e-16 ***
## Freq.x       2540780      72553   35.02   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 48630000 on 732 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6257 
## F-statistic:  1226 on 1 and 732 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 
## -227270557  -24366240  -11649272   15585447  355806173 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 25403332    2239041   11.35   <2e-16 ***
## Freq.x       2540780      72553   35.02   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 48630000 on 732 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6257 
## F-statistic:  1226 on 1 and 732 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 
## -110527026  -33348098   -7377560   27316215  415989862 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -33692742    3986430  -8.452   <2e-16 ***
## log(Freq.x)  47804500    1568761  30.473   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 52810000 on 732 degrees of freedom
## Multiple R-squared:  0.5592, Adjusted R-squared:  0.5586 
## F-statistic: 928.6 on 1 and 732 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 
## -190133968  -23537726   -1868005   17295196  333731784 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -33242191    3143806  -10.57   <2e-16 ***
## sqrt(Freq.x)  28921486     731999   39.51   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 44940000 on 732 degrees of freedom
## Multiple R-squared:  0.6808, Adjusted R-squared:  0.6803 
## F-statistic:  1561 on 1 and 732 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 
## -9097.5 -1464.8  -110.2  1457.0 10274.3 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    1740.6      155.5   11.20   <2e-16 ***
## sqrt(Freq.x)   1554.5       36.2   42.94   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2223 on 732 degrees of freedom
## Multiple R-squared:  0.7158, Adjusted R-squared:  0.7154 
## F-statistic:  1844 on 1 and 732 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

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

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

## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.3772 -0.4698  0.1172  0.5322  1.7563 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  15.96952    0.05175  308.58   <2e-16 ***
## sqrt(Freq.x)  0.41613    0.01205   34.53   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7398 on 732 degrees of freedom
## Multiple R-squared:  0.6197, Adjusted R-squared:  0.6191 
## F-statistic:  1193 on 1 and 732 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 
## -5720.9 -1581.6   -77.5  1528.5 10463.8 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  1271.58     177.08   7.181  1.7e-12 ***
## log(Freq.x)  2770.05      69.68  39.752  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2346 on 732 degrees of freedom
## Multiple R-squared:  0.6834, Adjusted R-squared:  0.683 
## F-statistic:  1580 on 1 and 732 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 
## -2.38772 -0.39322  0.06034  0.43543  2.00348 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.70597    0.05000  314.12   <2e-16 ***
## log(Freq.x)  0.80380    0.01968   40.85   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.6624 on 732 degrees of freedom
## Multiple R-squared:  0.6951, Adjusted R-squared:  0.6947 
## F-statistic:  1669 on 1 and 732 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 (0.7154).

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 
## -9097.5 -1464.8  -110.2  1457.0 10274.3 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    1740.6      155.5   11.20   <2e-16 ***
## sqrt(Freq.x)   1554.5       36.2   42.94   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2223 on 732 degrees of freedom
## Multiple R-squared:  0.7158, Adjusted R-squared:  0.7154 
## F-statistic:  1844 on 1 and 732 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

\[ \hat Y = {1740.6}^2 + 2 \cdot 1740.6 \cdot 1554.5 \sqrt{X}+ 1554.5^2 X \]

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$est_ing <- 
(1740.6)^2 + 2 * 1740.6 * 1554.5 * sqrt(h_y_m_comuna_corr_01$Freq.x)+  1554.5^2 * (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
6101092004	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	128	0.0005294	06101	31195828	23518620
6101102003	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	37	0.0001530	06101	9017544	15515681
6101102007	06101	33	2017	Rancagua	243717.4	2017	241774	58924531866	481	0.0019895	06101	117228072	113860053
6101102009	06101	9	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101	21447132	41012497
6101102015	06101	16	2017	Rancagua	243717.4	2017	241774	58924531866	271	0.0011209	06101	66047417	63339314
6101112015	06101	21	2017	Rancagua	243717.4	2017	241774	58924531866	74	0.0003061	06101	18035088	78574288
6101122008	06101	3	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101	21447132	19652136
6101122901	06101	5	2017	Rancagua	243717.4	2017	241774	58924531866	45	0.0001861	06101	10967283	27212578
6101132005	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	345	0.0014270	06101	84082505	47558860
6101132008	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	13	0.0000538	06101	3168326	15515681
6101132013	06101	39	2017	Rancagua	243717.4	2017	241774	58924531866	432	0.0017868	06101	105285919	131066993
6101132014	06101	94	2017	Rancagua	243717.4	2017	241774	58924531866	825	0.0034123	06101	201066859	282644577
6101142010	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	43	0.0001779	06101	10479848	15515681
6101142011	06101	15	2017	Rancagua	243717.4	2017	241774	58924531866	253	0.0010464	06101	61660503	60235490
6101142013	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	189	0.0007817	06101	46062590	47558860
6101182001	06101	47	2017	Rancagua	243717.4	2017	241774	58924531866	1112	0.0045993	06101	271013754	153703339
6101182002	06101	17	2017	Rancagua	243717.4	2017	241774	58924531866	397	0.0016420	06101	96755810	66421973
6101182005	06101	42	2017	Rancagua	243717.4	2017	241774	58924531866	2002	0.0082805	06101	487922245	139592132
6101182006	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	115	0.0004757	06101	28027502	23518620
6101182015	06101	30	2017	Rancagua	243717.4	2017	241774	58924531866	569	0.0023534	06101	138675203	105163941
6102012001	06102	34	2017	Codegua	264737.7	2017	12988	3438412620	575	0.0442716	06102	152224150	116744021
6102012002	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	157	0.0120881	06102	41563811	41012497
6102012004	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	183	0.0140899	06102	48446990	66421973
6102012006	06102	60	2017	Codegua	264737.7	2017	12988	3438412620	631	0.0485833	06102	167049458	189935399
6102012009	06102	5	2017	Codegua	264737.7	2017	12988	3438412620	99	0.0076224	06102	26209028	27212578
6102012014	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	83	0.0063905	06102	21973225	37667556
6102012015	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	87	0.0066985	06102	23032176	19652136
6102012018	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	90	0.0069295	06102	23826389	37667556
6102022002	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	32	0.0024638	06102	8471605	19652136
6102022003	06102	62	2017	Codegua	264737.7	2017	12988	3438412620	811	0.0624423	06102	214702236	195461237
6102022005	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	388	0.0298737	06102	102718209	66421973
6102022007	06102	30	2017	Codegua	264737.7	2017	12988	3438412620	606	0.0466585	06102	160431017	105163941
6102022012	06102	15	2017	Codegua	264737.7	2017	12988	3438412620	462	0.0355713	06102	122308795	60235490
6102022013	06102	18	2017	Codegua	264737.7	2017	12988	3438412620	219	0.0168617	06102	57977546	69485311
6102022016	06102	11	2017	Codegua	264737.7	2017	12988	3438412620	265	0.0204034	06102	70155478	47558860
6102022017	06102	45	2017	Codegua	264737.7	2017	12988	3438412620	600	0.0461965	06102	158842591	148072466
6102022019	06102	40	2017	Codegua	264737.7	2017	12988	3438412620	269	0.0207114	06102	71214428	133913990
6102022020	06102	7	2017	Codegua	264737.7	2017	12988	3438412620	91	0.0070065	06102	24091126	34262531
6102022901	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	37	0.0028488	06102	9795293	41012497
6102032011	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	284	0.0218663	06102	75185493	66421973
6103012003	06103	128	2017	Coinco	175814.1	2017	7359	1293816308	1211	0.1645604	06103	212910932	373562301
6103012004	06103	62	2017	Coinco	175814.1	2017	7359	1293816308	970	0.1318114	06103	170539723	195461237
6103022002	06103	42	2017	Coinco	175814.1	2017	7359	1293816308	276	0.0375051	06103	48524705	139592132
6103032001	06103	21	2017	Coinco	175814.1	2017	7359	1293816308	666	0.0905014	06103	117092222	78574288
6103042005	06103	36	2017	Coinco	175814.1	2017	7359	1293816308	812	0.1103411	06103	142761087	122491770
6104012002	06104	40	2017	Coltauco	254006.7	2017	19597	4977769953	721	0.0367913	06104	183138855	133913990
6104012006	06104	21	2017	Coltauco	254006.7	2017	19597	4977769953	221	0.0112772	06104	56135488	78574288
6104022006	06104	61	2017	Coltauco	254006.7	2017	19597	4977769953	1313	0.0670001	06104	333510841	192699738
6104032006	06104	71	2017	Coltauco	254006.7	2017	19597	4977769953	1279	0.0652651	06104	324874612	220197400
6104032008	06104	30	2017	Coltauco	254006.7	2017	19597	4977769953	803	0.0409757	06104	203967407	105163941
6104042013	06104	25	2017	Coltauco	254006.7	2017	19597	4977769953	620	0.0316375	06104	157484175	90499072
6104042015	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	84	0.0042864	06104	21336566	19652136
6104052004	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	69	0.0035209	06104	17526465	30783986
6104052005	06104	38	2017	Coltauco	254006.7	2017	19597	4977769953	672	0.0342910	06104	170692525	128214441
6104052007	06104	33	2017	Coltauco	254006.7	2017	19597	4977769953	907	0.0462826	06104	230384107	113860053
6104052010	06104	12	2017	Coltauco	254006.7	2017	19597	4977769953	294	0.0150023	06104	74677980	50773405
6104052014	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	77	0.0039292	06104	19558518	19652136
6104052016	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	64	0.0032658	06104	16256431	30783986
6104062011	06104	31	2017	Coltauco	254006.7	2017	19597	4977769953	653	0.0333214	06104	165866397	108070364
6104062016	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	18	0.0009185	06104	4572121	23518620
6104062901	06104	17	2017	Coltauco	254006.7	2017	19597	4977769953	171	0.0087258	06104	43435151	66421973
6104072011	06104	5	2017	Coltauco	254006.7	2017	19597	4977769953	278	0.0141858	06104	70613872	27212578
6104082001	06104	11	2017	Coltauco	254006.7	2017	19597	4977769953	109	0.0055621	06104	27686734	47558860
6104082009	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	19	0.0009695	06104	4826128	23518620
6104082901	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	14	0.0007144	06104	3556094	19652136
6105012001	06105	7	2017	Doñihue	198486.5	2017	20887	4145787348	335	0.0160387	06105	66492975	34262531
6105012002	06105	11	2017	Doñihue	198486.5	2017	20887	4145787348	52	0.0024896	06105	10321298	47558860
6105012003	06105	24	2017	Doñihue	198486.5	2017	20887	4145787348	210	0.0100541	06105	41682163	87535926
6105022003	06105	105	2017	Doñihue	198486.5	2017	20887	4145787348	1037	0.0496481	06105	205830492	312210699
6105022005	06105	64	2017	Doñihue	198486.5	2017	20887	4145787348	757	0.0362426	06105	150254274	200975988
6105032004	06105	91	2017	Doñihue	198486.5	2017	20887	4145787348	1254	0.0600373	06105	248902060	274551143
6105042004	06105	78	2017	Doñihue	198486.5	2017	20887	4145787348	818	0.0391631	06105	162361950	239307666
6106012004	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	265	0.0079254	06106	65824653	37667556
6106012012	06106	4	2017	Graneros	248394.9	2017	33437	8305580885	50	0.0014953	06106	12419746	23518620
6106022003	06106	33	2017	Graneros	248394.9	2017	33437	8305580885	411	0.0122918	06106	102090311	113860053
6106022004	06106	28	2017	Graneros	248394.9	2017	33437	8305580885	221	0.0066094	06106	54895277	99325956
6106022006	06106	5	2017	Graneros	248394.9	2017	33437	8305580885	71	0.0021234	06106	17636039	27212578
6106022010	06106	85	2017	Graneros	248394.9	2017	33437	8305580885	592	0.0177049	06106	147049792	258321459
6106032005	06106	3	2017	Graneros	248394.9	2017	33437	8305580885	25	0.0007477	06106	6209873	19652136
6106032007	06106	13	2017	Graneros	248394.9	2017	33437	8305580885	279	0.0083441	06106	69302182	53955334
6106032009	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	241	0.0072076	06106	59863175	87535926
6106032011	06106	17	2017	Graneros	248394.9	2017	33437	8305580885	128	0.0038281	06106	31794550	66421973
6106042001	06106	48	2017	Graneros	248394.9	2017	33437	8305580885	324	0.0096899	06106	80479954	156512408
6106042002	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	258	0.0077160	06106	64085889	87535926
6106042008	06106	7	2017	Graneros	248394.9	2017	33437	8305580885	282	0.0084338	06106	70047367	34262531
6106042011	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	64	0.0019140	06106	15897275	37667556
6106042012	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	384	0.0114843	06106	95383649	87535926
6107012001	06107	9	2017	Las Cabras	201772.1	2017	24640	4971665251	253	0.0102679	06107	51048349	41012497
6107012008	06107	6	2017	Las Cabras	201772.1	2017	24640	4971665251	66	0.0026786	06107	13316960	30783986
6107012021	06107	7	2017	Las Cabras	201772.1	2017	24640	4971665251	152	0.0061688	06107	30669364	34262531
6107022003	06107	41	2017	Las Cabras	201772.1	2017	24640	4971665251	735	0.0298295	06107	148302515	136755638
6107022007	06107	35	2017	Las Cabras	201772.1	2017	24640	4971665251	525	0.0213068	06107	105930368	119621163
6107022009	06107	74	2017	Las Cabras	201772.1	2017	24640	4971665251	1472	0.0597403	06107	297008573	228400189
6107032005	06107	65	2017	Las Cabras	201772.1	2017	24640	4971665251	1243	0.0504464	06107	250802756	203729367
6107032006	06107	23	2017	Las Cabras	201772.1	2017	24640	4971665251	309	0.0125406	06107	62347588	84561268
6107042002	06107	19	2017	Las Cabras	201772.1	2017	24640	4971665251	862	0.0349838	06107	173927575	72530915
6107042016	06107	26	2017	Las Cabras	201772.1	2017	24640	4971665251	570	0.0231331	06107	115010113	93451388
6107042019	06107	20	2017	Las Cabras	201772.1	2017	24640	4971665251	426	0.0172890	06107	85954927	75560171
6107042023	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	57	0.0023133	06107	11501011	19652136
6107042024	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	274	0.0111201	06107	55285563	19652136

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
6101092004	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	128	0.0005294	06101	31195828	23518620	183739.22
6101102003	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	37	0.0001530	06101	9017544	15515681	419342.74
6101102007	06101	33	2017	Rancagua	243717.4	2017	241774	58924531866	481	0.0019895	06101	117228072	113860053	236715.29
6101102009	06101	9	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101	21447132	41012497	466051.10
6101102015	06101	16	2017	Rancagua	243717.4	2017	241774	58924531866	271	0.0011209	06101	66047417	63339314	233724.41
6101112015	06101	21	2017	Rancagua	243717.4	2017	241774	58924531866	74	0.0003061	06101	18035088	78574288	1061814.71
6101122008	06101	3	2017	Rancagua	243717.4	2017	241774	58924531866	88	0.0003640	06101	21447132	19652136	223319.73
6101122901	06101	5	2017	Rancagua	243717.4	2017	241774	58924531866	45	0.0001861	06101	10967283	27212578	604723.96
6101132005	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	345	0.0014270	06101	84082505	47558860	137851.77
6101132008	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	13	0.0000538	06101	3168326	15515681	1193513.96
6101132013	06101	39	2017	Rancagua	243717.4	2017	241774	58924531866	432	0.0017868	06101	105285919	131066993	303395.82
6101132014	06101	94	2017	Rancagua	243717.4	2017	241774	58924531866	825	0.0034123	06101	201066859	282644577	342599.49
6101142010	06101	2	2017	Rancagua	243717.4	2017	241774	58924531866	43	0.0001779	06101	10479848	15515681	360829.80
6101142011	06101	15	2017	Rancagua	243717.4	2017	241774	58924531866	253	0.0010464	06101	61660503	60235490	238084.94
6101142013	06101	11	2017	Rancagua	243717.4	2017	241774	58924531866	189	0.0007817	06101	46062590	47558860	251634.18
6101182001	06101	47	2017	Rancagua	243717.4	2017	241774	58924531866	1112	0.0045993	06101	271013754	153703339	138222.43
6101182002	06101	17	2017	Rancagua	243717.4	2017	241774	58924531866	397	0.0016420	06101	96755810	66421973	167309.76
6101182005	06101	42	2017	Rancagua	243717.4	2017	241774	58924531866	2002	0.0082805	06101	487922245	139592132	69726.34
6101182006	06101	4	2017	Rancagua	243717.4	2017	241774	58924531866	115	0.0004757	06101	28027502	23518620	204509.74
6101182015	06101	30	2017	Rancagua	243717.4	2017	241774	58924531866	569	0.0023534	06101	138675203	105163941	184822.39
6102012001	06102	34	2017	Codegua	264737.7	2017	12988	3438412620	575	0.0442716	06102	152224150	116744021	203033.08
6102012002	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	157	0.0120881	06102	41563811	41012497	261226.09
6102012004	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	183	0.0140899	06102	48446990	66421973	362961.60
6102012006	06102	60	2017	Codegua	264737.7	2017	12988	3438412620	631	0.0485833	06102	167049458	189935399	301006.97
6102012009	06102	5	2017	Codegua	264737.7	2017	12988	3438412620	99	0.0076224	06102	26209028	27212578	274874.53
6102012014	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	83	0.0063905	06102	21973225	37667556	453825.97
6102012015	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	87	0.0066985	06102	23032176	19652136	225886.62
6102012018	06102	8	2017	Codegua	264737.7	2017	12988	3438412620	90	0.0069295	06102	23826389	37667556	418528.40
6102022002	06102	3	2017	Codegua	264737.7	2017	12988	3438412620	32	0.0024638	06102	8471605	19652136	614129.25
6102022003	06102	62	2017	Codegua	264737.7	2017	12988	3438412620	811	0.0624423	06102	214702236	195461237	241012.62
6102022005	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	388	0.0298737	06102	102718209	66421973	171190.65
6102022007	06102	30	2017	Codegua	264737.7	2017	12988	3438412620	606	0.0466585	06102	160431017	105163941	173537.86
6102022012	06102	15	2017	Codegua	264737.7	2017	12988	3438412620	462	0.0355713	06102	122308795	60235490	130379.85
6102022013	06102	18	2017	Codegua	264737.7	2017	12988	3438412620	219	0.0168617	06102	57977546	69485311	317284.52
6102022016	06102	11	2017	Codegua	264737.7	2017	12988	3438412620	265	0.0204034	06102	70155478	47558860	179467.40
6102022017	06102	45	2017	Codegua	264737.7	2017	12988	3438412620	600	0.0461965	06102	158842591	148072466	246787.44
6102022019	06102	40	2017	Codegua	264737.7	2017	12988	3438412620	269	0.0207114	06102	71214428	133913990	497821.52
6102022020	06102	7	2017	Codegua	264737.7	2017	12988	3438412620	91	0.0070065	06102	24091126	34262531	376511.32
6102022901	06102	9	2017	Codegua	264737.7	2017	12988	3438412620	37	0.0028488	06102	9795293	41012497	1108445.86
6102032011	06102	17	2017	Codegua	264737.7	2017	12988	3438412620	284	0.0218663	06102	75185493	66421973	233880.19
6103012003	06103	128	2017	Coinco	175814.1	2017	7359	1293816308	1211	0.1645604	06103	212910932	373562301	308474.24
6103012004	06103	62	2017	Coinco	175814.1	2017	7359	1293816308	970	0.1318114	06103	170539723	195461237	201506.43
6103022002	06103	42	2017	Coinco	175814.1	2017	7359	1293816308	276	0.0375051	06103	48524705	139592132	505768.59
6103032001	06103	21	2017	Coinco	175814.1	2017	7359	1293816308	666	0.0905014	06103	117092222	78574288	117979.41
6103042005	06103	36	2017	Coinco	175814.1	2017	7359	1293816308	812	0.1103411	06103	142761087	122491770	150851.93
6104012002	06104	40	2017	Coltauco	254006.7	2017	19597	4977769953	721	0.0367913	06104	183138855	133913990	185733.69
6104012006	06104	21	2017	Coltauco	254006.7	2017	19597	4977769953	221	0.0112772	06104	56135488	78574288	355539.77
6104022006	06104	61	2017	Coltauco	254006.7	2017	19597	4977769953	1313	0.0670001	06104	333510841	192699738	146762.94
6104032006	06104	71	2017	Coltauco	254006.7	2017	19597	4977769953	1279	0.0652651	06104	324874612	220197400	172163.72
6104032008	06104	30	2017	Coltauco	254006.7	2017	19597	4977769953	803	0.0409757	06104	203967407	105163941	130963.81
6104042013	06104	25	2017	Coltauco	254006.7	2017	19597	4977769953	620	0.0316375	06104	157484175	90499072	145966.24
6104042015	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	84	0.0042864	06104	21336566	19652136	233954.00
6104052004	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	69	0.0035209	06104	17526465	30783986	446144.72
6104052005	06104	38	2017	Coltauco	254006.7	2017	19597	4977769953	672	0.0342910	06104	170692525	128214441	190795.30
6104052007	06104	33	2017	Coltauco	254006.7	2017	19597	4977769953	907	0.0462826	06104	230384107	113860053	125534.79
6104052010	06104	12	2017	Coltauco	254006.7	2017	19597	4977769953	294	0.0150023	06104	74677980	50773405	172698.66
6104052014	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	77	0.0039292	06104	19558518	19652136	255222.55
6104052016	06104	6	2017	Coltauco	254006.7	2017	19597	4977769953	64	0.0032658	06104	16256431	30783986	480999.78
6104062011	06104	31	2017	Coltauco	254006.7	2017	19597	4977769953	653	0.0333214	06104	165866397	108070364	165498.26
6104062016	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	18	0.0009185	06104	4572121	23518620	1306590.01
6104062901	06104	17	2017	Coltauco	254006.7	2017	19597	4977769953	171	0.0087258	06104	43435151	66421973	388432.59
6104072011	06104	5	2017	Coltauco	254006.7	2017	19597	4977769953	278	0.0141858	06104	70613872	27212578	97886.97
6104082001	06104	11	2017	Coltauco	254006.7	2017	19597	4977769953	109	0.0055621	06104	27686734	47558860	436319.82
6104082009	06104	4	2017	Coltauco	254006.7	2017	19597	4977769953	19	0.0009695	06104	4826128	23518620	1237822.11
6104082901	06104	3	2017	Coltauco	254006.7	2017	19597	4977769953	14	0.0007144	06104	3556094	19652136	1403724.00
6105012001	06105	7	2017	Doñihue	198486.5	2017	20887	4145787348	335	0.0160387	06105	66492975	34262531	102276.21
6105012002	06105	11	2017	Doñihue	198486.5	2017	20887	4145787348	52	0.0024896	06105	10321298	47558860	914593.47
6105012003	06105	24	2017	Doñihue	198486.5	2017	20887	4145787348	210	0.0100541	06105	41682163	87535926	416837.74
6105022003	06105	105	2017	Doñihue	198486.5	2017	20887	4145787348	1037	0.0496481	06105	205830492	312210699	301071.07
6105022005	06105	64	2017	Doñihue	198486.5	2017	20887	4145787348	757	0.0362426	06105	150254274	200975988	265490.08
6105032004	06105	91	2017	Doñihue	198486.5	2017	20887	4145787348	1254	0.0600373	06105	248902060	274551143	218940.31
6105042004	06105	78	2017	Doñihue	198486.5	2017	20887	4145787348	818	0.0391631	06105	162361950	239307666	292552.16
6106012004	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	265	0.0079254	06106	65824653	37667556	142141.72
6106012012	06106	4	2017	Graneros	248394.9	2017	33437	8305580885	50	0.0014953	06106	12419746	23518620	470372.40
6106022003	06106	33	2017	Graneros	248394.9	2017	33437	8305580885	411	0.0122918	06106	102090311	113860053	277031.76
6106022004	06106	28	2017	Graneros	248394.9	2017	33437	8305580885	221	0.0066094	06106	54895277	99325956	449438.72
6106022006	06106	5	2017	Graneros	248394.9	2017	33437	8305580885	71	0.0021234	06106	17636039	27212578	383275.75
6106022010	06106	85	2017	Graneros	248394.9	2017	33437	8305580885	592	0.0177049	06106	147049792	258321459	436353.82
6106032005	06106	3	2017	Graneros	248394.9	2017	33437	8305580885	25	0.0007477	06106	6209873	19652136	786085.44
6106032007	06106	13	2017	Graneros	248394.9	2017	33437	8305580885	279	0.0083441	06106	69302182	53955334	193388.29
6106032009	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	241	0.0072076	06106	59863175	87535926	363219.61
6106032011	06106	17	2017	Graneros	248394.9	2017	33437	8305580885	128	0.0038281	06106	31794550	66421973	518921.67
6106042001	06106	48	2017	Graneros	248394.9	2017	33437	8305580885	324	0.0096899	06106	80479954	156512408	483062.99
6106042002	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	258	0.0077160	06106	64085889	87535926	339286.54
6106042008	06106	7	2017	Graneros	248394.9	2017	33437	8305580885	282	0.0084338	06106	70047367	34262531	121498.34
6106042011	06106	8	2017	Graneros	248394.9	2017	33437	8305580885	64	0.0019140	06106	15897275	37667556	588555.56
6106042012	06106	24	2017	Graneros	248394.9	2017	33437	8305580885	384	0.0114843	06106	95383649	87535926	227958.14
6107012001	06107	9	2017	Las Cabras	201772.1	2017	24640	4971665251	253	0.0102679	06107	51048349	41012497	162104.73
6107012008	06107	6	2017	Las Cabras	201772.1	2017	24640	4971665251	66	0.0026786	06107	13316960	30783986	466424.03
6107012021	06107	7	2017	Las Cabras	201772.1	2017	24640	4971665251	152	0.0061688	06107	30669364	34262531	225411.39
6107022003	06107	41	2017	Las Cabras	201772.1	2017	24640	4971665251	735	0.0298295	06107	148302515	136755638	186062.09
6107022007	06107	35	2017	Las Cabras	201772.1	2017	24640	4971665251	525	0.0213068	06107	105930368	119621163	227849.83
6107022009	06107	74	2017	Las Cabras	201772.1	2017	24640	4971665251	1472	0.0597403	06107	297008573	228400189	155163.17
6107032005	06107	65	2017	Las Cabras	201772.1	2017	24640	4971665251	1243	0.0504464	06107	250802756	203729367	163901.34
6107032006	06107	23	2017	Las Cabras	201772.1	2017	24640	4971665251	309	0.0125406	06107	62347588	84561268	273661.06
6107042002	06107	19	2017	Las Cabras	201772.1	2017	24640	4971665251	862	0.0349838	06107	173927575	72530915	84142.59
6107042016	06107	26	2017	Las Cabras	201772.1	2017	24640	4971665251	570	0.0231331	06107	115010113	93451388	163949.80
6107042019	06107	20	2017	Las Cabras	201772.1	2017	24640	4971665251	426	0.0172890	06107	85954927	75560171	177371.29
6107042023	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	57	0.0023133	06107	11501011	19652136	344774.32
6107042024	06107	3	2017	Las Cabras	201772.1	2017	24640	4971665251	274	0.0111201	06107	55285563	19652136	71723.12

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "P15/region_06_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