Expansión de la CASEN sobre el CENSO (Región 16)

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 16.

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 16 y con la zona = 2:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 16) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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	16101042032	12	16101	4	2017
2	16101052010	12	16101	19	2017
3	16101052026	12	16101	21	2017
4	16101052027	12	16101	26	2017
5	16101052028	12	16101	86	2017
6	16101062003	12	16101	65	2017
7	16101062014	12	16101	50	2017
8	16101062024	12	16101	38	2017
9	16101062027	12	16101	49	2017
10	16101062901	12	16101	21	2017
11	16101072001	12	16101	97	2017
12	16101072901	12	16101	59	2017
13	16101082007	12	16101	12	2017
14	16101082008	12	16101	11	2017
15	16101082011	12	16101	13	2017
16	16101082012	12	16101	7	2017
17	16101082015	12	16101	30	2017
18	16101082031	12	16101	4	2017
19	16101082037	12	16101	13	2017
20	16101092901	12	16101	5	2017
21	16101102004	12	16101	258	2017
22	16101112030	12	16101	1	2017
23	16101122002	12	16101	22	2017
24	16101122017	12	16101	98	2017
25	16101122020	12	16101	16	2017
26	16101122034	12	16101	29	2017
27	16101122035	12	16101	68	2017
28	16101142009	12	16101	171	2017
29	16101142018	12	16101	157	2017
30	16101142036	12	16101	67	2017
31	16101152016	12	16101	52	2017
32	16101152025	12	16101	356	2017
33	16101152033	12	16101	23	2017
789	16102012006	12	16102	9	2017
790	16102012029	12	16102	1	2017
791	16102012044	12	16102	4	2017
792	16102012901	12	16102	3	2017
793	16102022005	12	16102	7	2017
794	16102022015	12	16102	7	2017
795	16102022019	12	16102	4	2017
796	16102022020	12	16102	17	2017
797	16102022034	12	16102	3	2017
798	16102022035	12	16102	1	2017
799	16102022050	12	16102	32	2017
800	16102032014	12	16102	20	2017
801	16102032017	12	16102	3	2017
802	16102032019	12	16102	16	2017
803	16102032026	12	16102	2	2017
804	16102032037	12	16102	4	2017
805	16102032038	12	16102	22	2017
806	16102032901	12	16102	1	2017
807	16102042016	12	16102	1	2017
808	16102042023	12	16102	1	2017
809	16102042031	12	16102	16	2017
810	16102042049	12	16102	3	2017
811	16102052010	12	16102	1	2017
812	16102052011	12	16102	8	2017
813	16102052021	12	16102	4	2017
814	16102052043	12	16102	2	2017
815	16102052047	12	16102	13	2017
816	16102052049	12	16102	15	2017
817	16102052901	12	16102	2	2017
818	16102062008	12	16102	7	2017
819	16102062013	12	16102	1	2017
820	16102062030	12	16102	2	2017
821	16102062033	12	16102	1	2017
822	16102062040	12	16102	7	2017
823	16102062048	12	16102	1	2017
824	16102062051	12	16102	8	2017
825	16102072003	12	16102	3	2017
826	16102072008	12	16102	3	2017
827	16102072018	12	16102	2	2017
828	16102072025	12	16102	1	2017
829	16102072028	12	16102	7	2017
830	16102072039	12	16102	5	2017
831	16102072041	12	16102	12	2017
832	16102072045	12	16102	5	2017
833	16102072046	12	16102	3	2017
834	16102072051	12	16102	8	2017
835	16102082009	12	16102	14	2017
836	16102082027	12	16102	3	2017
837	16102082042	12	16102	3	2017
838	16102082045	12	16102	6	2017
1594	16103012003	12	16103	10	2017
1595	16103012012	12	16103	26	2017
1596	16103022001	12	16103	1	2017
1597	16103022005	12	16103	1	2017
1598	16103022010	12	16103	4	2017
1599	16103022013	12	16103	1	2017
1600	16103022014	12	16103	3	2017
1601	16103022015	12	16103	9	2017
1602	16103022016	12	16103	1	2017
1603	16103022028	12	16103	34	2017
1604	16103022030	12	16103	2	2017
1605	16103022031	12	16103	2	2017
1606	16103022901	12	16103	2	2017
1607	16103032007	12	16103	3	2017
1608	16103032011	12	16103	1	2017
1609	16103032020	12	16103	12	2017
1610	16103032032	12	16103	8	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	16101042032	4	2017	16101
2	16101052010	19	2017	16101
3	16101052026	21	2017	16101
4	16101052027	26	2017	16101
5	16101052028	86	2017	16101
6	16101062003	65	2017	16101
7	16101062014	50	2017	16101
8	16101062024	38	2017	16101
9	16101062027	49	2017	16101
10	16101062901	21	2017	16101
11	16101072001	97	2017	16101
12	16101072901	59	2017	16101
13	16101082007	12	2017	16101
14	16101082008	11	2017	16101
15	16101082011	13	2017	16101
16	16101082012	7	2017	16101
17	16101082015	30	2017	16101
18	16101082031	4	2017	16101
19	16101082037	13	2017	16101
20	16101092901	5	2017	16101
21	16101102004	258	2017	16101
22	16101112030	1	2017	16101
23	16101122002	22	2017	16101
24	16101122017	98	2017	16101
25	16101122020	16	2017	16101
26	16101122034	29	2017	16101
27	16101122035	68	2017	16101
28	16101142009	171	2017	16101
29	16101142018	157	2017	16101
30	16101142036	67	2017	16101
31	16101152016	52	2017	16101
32	16101152025	356	2017	16101
33	16101152033	23	2017	16101
789	16102012006	9	2017	16102
790	16102012029	1	2017	16102
791	16102012044	4	2017	16102
792	16102012901	3	2017	16102
793	16102022005	7	2017	16102
794	16102022015	7	2017	16102
795	16102022019	4	2017	16102
796	16102022020	17	2017	16102
797	16102022034	3	2017	16102
798	16102022035	1	2017	16102
799	16102022050	32	2017	16102
800	16102032014	20	2017	16102
801	16102032017	3	2017	16102
802	16102032019	16	2017	16102
803	16102032026	2	2017	16102
804	16102032037	4	2017	16102
805	16102032038	22	2017	16102
806	16102032901	1	2017	16102
807	16102042016	1	2017	16102
808	16102042023	1	2017	16102
809	16102042031	16	2017	16102
810	16102042049	3	2017	16102
811	16102052010	1	2017	16102
812	16102052011	8	2017	16102
813	16102052021	4	2017	16102
814	16102052043	2	2017	16102
815	16102052047	13	2017	16102
816	16102052049	15	2017	16102
817	16102052901	2	2017	16102
818	16102062008	7	2017	16102
819	16102062013	1	2017	16102
820	16102062030	2	2017	16102
821	16102062033	1	2017	16102
822	16102062040	7	2017	16102
823	16102062048	1	2017	16102
824	16102062051	8	2017	16102
825	16102072003	3	2017	16102
826	16102072008	3	2017	16102
827	16102072018	2	2017	16102
828	16102072025	1	2017	16102
829	16102072028	7	2017	16102
830	16102072039	5	2017	16102
831	16102072041	12	2017	16102
832	16102072045	5	2017	16102
833	16102072046	3	2017	16102
834	16102072051	8	2017	16102
835	16102082009	14	2017	16102
836	16102082027	3	2017	16102
837	16102082042	3	2017	16102
838	16102082045	6	2017	16102
1594	16103012003	10	2017	16103
1595	16103012012	26	2017	16103
1596	16103022001	1	2017	16103
1597	16103022005	1	2017	16103
1598	16103022010	4	2017	16103
1599	16103022013	1	2017	16103
1600	16103022014	3	2017	16103
1601	16103022015	9	2017	16103
1602	16103022016	1	2017	16103
1603	16103022028	34	2017	16103
1604	16103022030	2	2017	16103
1605	16103022031	2	2017	16103
1606	16103022901	2	2017	16103
1607	16103032007	3	2017	16103
1608	16103032011	1	2017	16103
1609	16103032020	12	2017	16103
1610	16103032032	8	2017	16103

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
16101	16101042032	4	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052010	19	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052026	21	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052027	26	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052028	86	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062003	65	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062014	50	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062024	38	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062027	49	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062901	21	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101072001	97	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101072901	59	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082007	12	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082008	11	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082011	13	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082012	7	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082015	30	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082031	4	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082037	13	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101092901	5	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101102004	258	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101112030	1	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122002	22	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122017	98	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122020	16	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122034	29	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122035	68	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101142009	171	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101142018	157	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101142036	67	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101152016	52	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101152025	356	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101152033	23	2017	Chillán	232041.6	2017	184739	42867130063
16102	16102012006	9	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102012029	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102012044	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102012901	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022005	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022015	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022019	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022020	17	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022034	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022035	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022050	32	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032014	20	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032017	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032019	16	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032026	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032037	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032038	22	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032901	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042016	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042023	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042031	16	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042049	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052010	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052011	8	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052021	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052043	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052047	13	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052049	15	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052901	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062008	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062013	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062030	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062033	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062040	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062048	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062051	8	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072003	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072008	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072018	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072025	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072028	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072039	5	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072041	12	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072045	5	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072046	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072051	8	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082009	14	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082027	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082042	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082045	6	2017	Bulnes	167693.2	2017	21493	3604229178
16103	16103012003	10	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103012012	26	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022001	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022005	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022010	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022013	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022014	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022015	9	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022016	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022028	34	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022030	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022031	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022901	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032007	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032011	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032020	12	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032032	8	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032901	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103042003	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103042027	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103052006	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103052021	31	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103052022	5	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103052034	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103052901	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16104	16104012005	3	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104012007	27	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104012017	2	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104012018	2	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104022019	13	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104032004	10	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104032014	10	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104032015	31	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042004	1	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042005	1	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042006	5	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042010	4	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042012	10	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042021	6	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104042022	3	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052001	8	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052003	2	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052010	2	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052018	8	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052025	2	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052026	21	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104052901	13	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104062002	6	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104062008	1	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104062011	5	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104062013	2	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104062017	14	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104072009	1	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104072024	7	2017	El Carmen	151144.7	2017	12044	1820386198
16104	16104072027	1	2017	El Carmen	151144.7	2017	12044	1820386198
16105	16105012019	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105022024	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105022028	3	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105032004	5	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105032016	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105042008	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105042021	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105052001	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105052010	4	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105052013	3	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105052031	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105052901	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105062007	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105062013	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105062015	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105062901	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105072006	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105072026	7	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105072030	3	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105082009	4	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105082011	13	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105082025	40	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105092006	1	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105092009	2	2017	Pemuco	151889.4	2017	8448	1283161238
16105	16105092030	6	2017	Pemuco	151889.4	2017	8448	1283161238
16106	16106012004	2	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106012008	80	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106012012	2	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106012013	8	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106012017	3	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106012018	3	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106022019	1	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106022020	3	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106022021	5	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106022022	5	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106022026	31	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106032004	2	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106032015	2	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106032027	2	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106032028	2	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106032029	5	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042004	3	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042005	4	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042006	17	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042007	11	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042012	9	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042014	11	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106042016	1	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106052003	5	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106052005	14	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106052009	20	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106052010	17	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106052011	84	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106052024	13	2017	Pinto	153289.2	2017	10827	1659661870
16106	16106062001	3	2017	Pinto	153289.2	2017	10827	1659661870
16107	16107012003	1	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107012008	39	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107012013	7	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107012014	7	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107012030	5	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107012036	41	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107012901	6	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022004	13	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022005	25	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022011	5	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022012	42	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022016	6	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022017	23	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022018	4	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022020	13	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022021	7	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107022028	3	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107032006	3	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107032007	4	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107032901	1	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107042033	1	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107042035	1	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107042901	7	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107052002	9	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107052010	9	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107052014	6	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107052901	3	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107062010	49	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107062024	10	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107062027	3	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107062031	24	2017	Quillón	133479.9	2017	17485	2333895558
16107	16107062032	15	2017	Quillón	133479.9	2017	17485	2333895558
16108	16108012003	12	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108012011	13	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108012025	3	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108012026	6	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108012031	31	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108022012	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108022014	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108022025	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032013	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032015	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032020	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032024	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032025	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032027	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032032	32	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108032033	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042003	4	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042006	5	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042024	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042026	5	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042034	6	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042037	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042038	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108042901	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052001	19	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052011	8	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052016	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052017	23	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052022	22	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052026	3	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052029	14	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052030	7	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108052037	3	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062002	7	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062003	17	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062005	8	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062009	2	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062010	3	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062019	10	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062021	16	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062028	1	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062029	9	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062035	11	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062036	10	2017	San Ignacio	174538.8	2017	16079	2806409365
16108	16108062901	3	2017	San Ignacio	174538.8	2017	16079	2806409365
16109	16109012012	4	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109012026	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109012045	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109012901	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109022004	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109022007	18	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109022029	4	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109022036	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109022040	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109022901	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109032012	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109032028	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109032042	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109032901	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109042013	6	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109042024	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109042028	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109042042	4	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109042043	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109052010	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109062050	8	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109062901	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109072001	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109072015	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109072033	4	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109072901	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109082008	12	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109082011	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109082014	7	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109082046	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109082901	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109092002	4	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109092005	66	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109092038	9	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109092047	16	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102002	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102005	9	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102016	11	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102019	2	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102021	3	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102051	1	2017	Yungay	194006.8	2017	17787	3450799686
16109	16109102901	9	2017	Yungay	194006.8	2017	17787	3450799686
16201	16201012014	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201012018	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201012901	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022002	5	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022020	6	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022026	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022032	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022036	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022045	3	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022059	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022067	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022070	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022080	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022083	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201022901	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201032004	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201032006	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201032033	3	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201032053	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201032083	6	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201042021	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201042048	5	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201042077	3	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201042084	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201042901	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052001	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052003	4	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052012	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052013	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052019	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052025	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201052030	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201062015	2	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201062027	1	2017	Quirihue	155446.9	2017	11594	1802251665
16201	16201062901	4	2017	Quirihue	155446.9	2017	11594	1802251665
16202	16202012002	48	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202012044	13	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202012055	6	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022002	19	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022003	6	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022010	6	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022022	4	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022032	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022034	5	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022038	5	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022041	7	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022045	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022052	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202022901	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202032031	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202032038	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202032053	2	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202042011	6	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202042021	7	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202042039	5	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202042049	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202042053	2	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202042054	4	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202052008	1	2017	Cobquecura	122513.3	2017	5012	614036495
16202	16202052048	1	2017	Cobquecura	122513.3	2017	5012	614036495
16203	16203012003	13	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012004	8	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012005	9	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012019	9	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012024	3	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012039	6	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012040	1	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203012901	17	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022002	2	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022019	67	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022020	4	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022021	3	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022022	6	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022030	4	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022031	1	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022033	12	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203022037	16	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032001	5	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032011	1	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032014	2	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032016	3	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032032	1	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032034	3	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203032036	2	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203042010	2	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203042025	2	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203042028	9	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203042042	8	2017	Coelemu	174050.2	2017	15995	2783932983
16203	16203042901	2	2017	Coelemu	174050.2	2017	15995	2783932983
16204	16204012002	1	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012007	5	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012008	11	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012015	7	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012017	14	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012019	2	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012021	1	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012023	8	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204012024	8	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022001	4	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022002	1	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022004	1	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022007	15	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022016	1	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022018	4	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022021	13	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022024	2	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204022901	3	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204032006	4	2017	Ninhue	161577.8	2017	5213	842304828
16204	16204032020	3	2017	Ninhue	161577.8	2017	5213	842304828
16205	16205012001	1	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012002	16	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012003	1	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012007	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012008	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012013	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012016	6	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012018	4	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012021	7	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012023	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205012901	1	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205022005	3	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205022006	7	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205022011	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205022020	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205022901	1	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032004	9	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032012	13	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032013	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032014	8	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032015	2	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032017	3	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032018	4	2017	Portezuelo	168595.2	2017	4862	819710106
16205	16205032901	3	2017	Portezuelo	168595.2	2017	4862	819710106
16206	16206012005	1	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012006	6	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012009	5	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012013	17	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012018	6	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012022	5	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012023	2	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012024	18	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012026	20	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012029	4	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012031	6	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012032	7	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012033	2	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012036	3	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012037	8	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206012038	10	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206022004	5	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206022014	3	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206022016	1	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206022034	14	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206022036	1	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032001	3	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032003	1	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032007	4	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032008	2	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032012	7	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032017	5	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032021	3	2017	Ránquil	221951.3	2017	5755	1277329463
16206	16206032036	11	2017	Ránquil	221951.3	2017	5755	1277329463
16207	16207012002	5	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207012012	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207012026	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207012029	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207012033	4	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022001	2	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022010	2	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022013	3	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022014	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022015	60	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022021	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022025	20	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022030	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022031	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022034	5	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022038	2	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207022039	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207032005	3	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207032022	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207032027	6	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207032032	1	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207032040	3	2017	Treguaco	178763.9	2017	5401	965503625
16207	16207032901	5	2017	Treguaco	178763.9	2017	5401	965503625
16301	16301012004	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012019	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012026	14	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012029	8	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012032	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012034	22	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012036	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012053	10	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012054	3	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012074	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301012075	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301032025	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301032046	19	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301032063	14	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301032901	35	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042017	5	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042030	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042036	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042048	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042060	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042063	3	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301042901	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301052011	15	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301052021	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301052041	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301052065	14	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301052067	18	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301052069	25	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062011	33	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062013	8	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062041	32	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062043	8	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062046	33	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062052	11	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062057	12	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062066	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301062067	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301072024	8	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301072033	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301072039	3	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301072043	12	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301072044	14	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301072901	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301082003	51	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301082018	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301082047	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301082051	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301082055	26	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301082073	8	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092022	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092023	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092025	9	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092031	25	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092038	16	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092044	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092045	12	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092049	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092056	28	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092062	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092073	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301092901	9	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102001	22	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102002	7	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102005	51	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102020	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102023	11	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102026	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102038	44	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102045	24	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102049	14	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102059	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301102060	3	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301112002	27	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301112042	4	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301112064	7	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301112075	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301112901	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301122007	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301122042	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301122075	6	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301122901	5	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301132035	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301132037	2	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301132070	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301132071	1	2017	San Carlos	175203.6	2017	53024	9289995173
16301	16301142027	1	2017	San Carlos	175203.6	2017	53024	9289995173
16302	16302012018	16	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302012025	8	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302012029	14	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302012037	18	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302012039	13	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302012041	13	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022015	9	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022017	9	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022020	17	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022021	28	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022027	5	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022035	6	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022038	77	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022042	4	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022044	30	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302022049	78	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032005	11	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032010	8	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032015	12	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032017	11	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032021	22	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032022	12	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032032	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032038	87	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302032049	31	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042012	6	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042013	3	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042015	8	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042022	25	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042027	4	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042034	44	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042045	13	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042049	5	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042050	39	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302042901	4	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302052013	8	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302052031	12	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302052043	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302062006	8	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302062028	3	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302062051	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302072009	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302082019	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302082030	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302082053	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302092026	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302092033	10	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302092037	4	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302092901	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302102002	1	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302102003	37	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112001	20	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112002	2	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112014	18	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112016	24	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112036	7	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112048	9	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302112052	7	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302122008	5	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302122036	7	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302122046	18	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302122048	5	2017	Coihueco	174853.6	2017	26881	4700239750
16302	16302122052	18	2017	Coihueco	174853.6	2017	26881	4700239750
16303	16303012003	12	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303012006	4	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303012007	6	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303012014	4	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303012015	10	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303012022	9	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303012029	8	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022006	8	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022007	2	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022018	8	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022032	7	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022037	13	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022038	20	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303022042	25	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032004	10	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032006	18	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032010	9	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032011	3	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032012	1	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032017	21	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032021	6	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032022	5	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032023	2	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032034	6	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032035	3	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032037	4	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032039	2	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032040	11	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303032041	34	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303042016	4	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303042023	1	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303042026	9	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303042027	5	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303042029	16	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303042036	1	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303062001	2	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303062002	4	2017	Ñiquén	188830.1	2017	11152	2105832760
16303	16303062028	2	2017	Ñiquén	188830.1	2017	11152	2105832760
16304	16304012005	2	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304012015	15	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304022019	6	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032003	28	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032004	8	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032009	5	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032010	19	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032011	3	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032016	27	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304032018	3	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304042001	3	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304042013	10	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304042014	4	2017	San Fabián	158019.3	2017	4308	680747063
16304	16304052017	1	2017	San Fabián	158019.3	2017	4308	680747063
16305	16305012002	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305012006	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305012026	8	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305012028	5	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305012030	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305012032	4	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305012046	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022010	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022025	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022030	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022032	10	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022046	4	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022047	8	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022056	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022062	8	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305022901	4	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305032008	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305032013	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305032019	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305032043	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305042014	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305042035	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305042039	5	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305042045	5	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305042049	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305042901	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052015	13	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052016	4	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052020	5	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052023	4	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052027	1	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052031	18	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052033	25	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052036	18	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052044	13	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052050	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305052053	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062001	10	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062004	6	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062009	8	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062012	40	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062015	9	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062023	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062029	12	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062037	19	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062044	7	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062054	4	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305062057	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072006	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072007	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072011	7	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072017	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072018	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072034	2	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072040	3	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072041	5	2017	San Nicolás	180675.3	2017	11603	2096375354
16305	16305072901	2	2017	San Nicolás	180675.3	2017	11603	2096375354

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
16101	16101042032	4	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052010	19	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052026	21	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052027	26	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101052028	86	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062003	65	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062014	50	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062024	38	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062027	49	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101062901	21	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101072001	97	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101072901	59	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082007	12	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082008	11	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082011	13	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082012	7	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082015	30	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082031	4	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101082037	13	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101092901	5	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101102004	258	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101112030	1	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122002	22	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122017	98	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122020	16	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122034	29	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101122035	68	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101142009	171	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101142018	157	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101142036	67	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101152016	52	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101152025	356	2017	Chillán	232041.6	2017	184739	42867130063
16101	16101152033	23	2017	Chillán	232041.6	2017	184739	42867130063
16102	16102012006	9	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102012029	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102012044	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102012901	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022005	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022015	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022019	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022020	17	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022034	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022035	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102022050	32	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032014	20	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032017	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032019	16	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032026	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032037	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032038	22	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102032901	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042016	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042023	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042031	16	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102042049	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052010	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052011	8	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052021	4	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052043	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052047	13	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052049	15	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102052901	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062008	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062013	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062030	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062033	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062040	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062048	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102062051	8	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072003	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072008	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072018	2	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072025	1	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072028	7	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072039	5	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072041	12	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072045	5	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072046	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102072051	8	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082009	14	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082027	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082042	3	2017	Bulnes	167693.2	2017	21493	3604229178
16102	16102082045	6	2017	Bulnes	167693.2	2017	21493	3604229178
16103	16103012003	10	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103012012	26	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022001	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022005	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022010	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022013	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022014	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022015	9	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022016	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022028	34	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022030	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022031	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103022901	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032007	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032011	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032020	12	2017	Chillán Viejo	179855.8	2017	30907	5558803478
16103	16103032032	8	2017	Chillán Viejo	179855.8	2017	30907	5558803478

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
16101042032	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	30	0.0001624	16101
16101052010	16101	19	2017	Chillán	232041.6	2017	184739	42867130063	112	0.0006063	16101
16101052026	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	355	0.0019216	16101
16101052027	16101	26	2017	Chillán	232041.6	2017	184739	42867130063	362	0.0019595	16101
16101052028	16101	86	2017	Chillán	232041.6	2017	184739	42867130063	345	0.0018675	16101
16101062003	16101	65	2017	Chillán	232041.6	2017	184739	42867130063	638	0.0034535	16101
16101062014	16101	50	2017	Chillán	232041.6	2017	184739	42867130063	348	0.0018837	16101
16101062024	16101	38	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101
16101062027	16101	49	2017	Chillán	232041.6	2017	184739	42867130063	620	0.0033561	16101
16101062901	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	373	0.0020191	16101
16101072001	16101	97	2017	Chillán	232041.6	2017	184739	42867130063	593	0.0032099	16101
16101072901	16101	59	2017	Chillán	232041.6	2017	184739	42867130063	491	0.0026578	16101
16101082007	16101	12	2017	Chillán	232041.6	2017	184739	42867130063	184	0.0009960	16101
16101082008	16101	11	2017	Chillán	232041.6	2017	184739	42867130063	147	0.0007957	16101
16101082011	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	408	0.0022085	16101
16101082012	16101	7	2017	Chillán	232041.6	2017	184739	42867130063	139	0.0007524	16101
16101082015	16101	30	2017	Chillán	232041.6	2017	184739	42867130063	313	0.0016943	16101
16101082031	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	104	0.0005630	16101
16101082037	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101
16101092901	16101	5	2017	Chillán	232041.6	2017	184739	42867130063	87	0.0004709	16101
16101102004	16101	258	2017	Chillán	232041.6	2017	184739	42867130063	3591	0.0194382	16101
16101112030	16101	1	2017	Chillán	232041.6	2017	184739	42867130063	37	0.0002003	16101
16101122002	16101	22	2017	Chillán	232041.6	2017	184739	42867130063	280	0.0015157	16101
16101122017	16101	98	2017	Chillán	232041.6	2017	184739	42867130063	682	0.0036917	16101
16101122020	16101	16	2017	Chillán	232041.6	2017	184739	42867130063	102	0.0005521	16101
16101122034	16101	29	2017	Chillán	232041.6	2017	184739	42867130063	171	0.0009256	16101
16101122035	16101	68	2017	Chillán	232041.6	2017	184739	42867130063	534	0.0028906	16101
16101142009	16101	171	2017	Chillán	232041.6	2017	184739	42867130063	607	0.0032857	16101
16101142018	16101	157	2017	Chillán	232041.6	2017	184739	42867130063	625	0.0033832	16101
16101142036	16101	67	2017	Chillán	232041.6	2017	184739	42867130063	443	0.0023980	16101
16101152016	16101	52	2017	Chillán	232041.6	2017	184739	42867130063	521	0.0028202	16101
16101152025	16101	356	2017	Chillán	232041.6	2017	184739	42867130063	1780	0.0096352	16101
16101152033	16101	23	2017	Chillán	232041.6	2017	184739	42867130063	122	0.0006604	16101
16102012006	16102	9	2017	Bulnes	167693.2	2017	21493	3604229178	183	0.0085144	16102
16102012029	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	18	0.0008375	16102
16102012044	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	32	0.0014889	16102
16102012901	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	58	0.0026986	16102
16102022005	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102
16102022015	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	160	0.0074443	16102
16102022019	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	59	0.0027451	16102
16102022020	16102	17	2017	Bulnes	167693.2	2017	21493	3604229178	359	0.0167031	16102
16102022034	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102
16102022035	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	46	0.0021402	16102
16102022050	16102	32	2017	Bulnes	167693.2	2017	21493	3604229178	422	0.0196343	16102
16102032014	16102	20	2017	Bulnes	167693.2	2017	21493	3604229178	372	0.0173080	16102
16102032017	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	31	0.0014423	16102
16102032019	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	197	0.0091658	16102
16102032026	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	36	0.0016750	16102
16102032037	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	93	0.0043270	16102
16102032038	16102	22	2017	Bulnes	167693.2	2017	21493	3604229178	358	0.0166566	16102
16102032901	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	24	0.0011166	16102
16102042016	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	219	0.0101894	16102
16102042023	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	68	0.0031638	16102
16102042031	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102
16102042049	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	41	0.0019076	16102
16102052010	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	215	0.0100033	16102
16102052011	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	141	0.0065603	16102
16102052021	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	92	0.0042805	16102
16102052043	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	63	0.0029312	16102
16102052047	16102	13	2017	Bulnes	167693.2	2017	21493	3604229178	428	0.0199135	16102
16102052049	16102	15	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102
16102052901	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	105	0.0048853	16102
16102062008	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	81	0.0037687	16102
16102062013	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	76	0.0035360	16102
16102062030	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	133	0.0061881	16102
16102062033	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	97	0.0045131	16102
16102062040	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	274	0.0127483	16102
16102062048	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	70	0.0032569	16102
16102062051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	481	0.0223794	16102
16102072003	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	66	0.0030708	16102
16102072008	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	200	0.0093054	16102
16102072018	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	116	0.0053971	16102
16102072025	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	20	0.0009305	16102
16102072028	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	109	0.0050714	16102
16102072039	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102
16102072041	16102	12	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102
16102072045	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	50	0.0023263	16102
16102072046	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102
16102072051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	502	0.0233564	16102
16102082009	16102	14	2017	Bulnes	167693.2	2017	21493	3604229178	456	0.0212162	16102
16102082027	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	72	0.0033499	16102
16102082042	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102
16102082045	16102	6	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102
16103012003	16103	10	2017	Chillán Viejo	179855.8	2017	30907	5558803478	78	0.0025237	16103
16103012012	16103	26	2017	Chillán Viejo	179855.8	2017	30907	5558803478	542	0.0175365	16103
16103022001	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103
16103022005	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	11	0.0003559	16103
16103022010	16103	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478	35	0.0011324	16103
16103022013	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	10	0.0003236	16103
16103022014	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	90	0.0029120	16103
16103022015	16103	9	2017	Chillán Viejo	179855.8	2017	30907	5558803478	171	0.0055327	16103
16103022016	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	43	0.0013913	16103
16103022028	16103	34	2017	Chillán Viejo	179855.8	2017	30907	5558803478	838	0.0271136	16103
16103022030	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	23	0.0007442	16103
16103022031	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	48	0.0015530	16103
16103022901	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	31	0.0010030	16103
16103032007	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103
16103032011	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	125	0.0040444	16103
16103032020	16103	12	2017	Chillán Viejo	179855.8	2017	30907	5558803478	386	0.0124891	16103
16103032032	16103	8	2017	Chillán Viejo	179855.8	2017	30907	5558803478	151	0.0048856	16103

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
16101042032	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	30	0.0001624	16101	6961248
16101052010	16101	19	2017	Chillán	232041.6	2017	184739	42867130063	112	0.0006063	16101	25988657
16101052026	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	355	0.0019216	16101	82374762
16101052027	16101	26	2017	Chillán	232041.6	2017	184739	42867130063	362	0.0019595	16101	83999053
16101052028	16101	86	2017	Chillán	232041.6	2017	184739	42867130063	345	0.0018675	16101	80054346
16101062003	16101	65	2017	Chillán	232041.6	2017	184739	42867130063	638	0.0034535	16101	148042530
16101062014	16101	50	2017	Chillán	232041.6	2017	184739	42867130063	348	0.0018837	16101	80750471
16101062024	16101	38	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101	104650754
16101062027	16101	49	2017	Chillán	232041.6	2017	184739	42867130063	620	0.0033561	16101	143865782
16101062901	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	373	0.0020191	16101	86551511
16101072001	16101	97	2017	Chillán	232041.6	2017	184739	42867130063	593	0.0032099	16101	137600659
16101072901	16101	59	2017	Chillán	232041.6	2017	184739	42867130063	491	0.0026578	16101	113932417
16101082007	16101	12	2017	Chillán	232041.6	2017	184739	42867130063	184	0.0009960	16101	42695651
16101082008	16101	11	2017	Chillán	232041.6	2017	184739	42867130063	147	0.0007957	16101	34110113
16101082011	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	408	0.0022085	16101	94672966
16101082012	16101	7	2017	Chillán	232041.6	2017	184739	42867130063	139	0.0007524	16101	32253780
16101082015	16101	30	2017	Chillán	232041.6	2017	184739	42867130063	313	0.0016943	16101	72629016
16101082031	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	104	0.0005630	16101	24132325
16101082037	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101	104650754
16101092901	16101	5	2017	Chillán	232041.6	2017	184739	42867130063	87	0.0004709	16101	20187618
16101102004	16101	258	2017	Chillán	232041.6	2017	184739	42867130063	3591	0.0194382	16101	833261326
16101112030	16101	1	2017	Chillán	232041.6	2017	184739	42867130063	37	0.0002003	16101	8585539
16101122002	16101	22	2017	Chillán	232041.6	2017	184739	42867130063	280	0.0015157	16101	64971643
16101122017	16101	98	2017	Chillán	232041.6	2017	184739	42867130063	682	0.0036917	16101	158252360
16101122020	16101	16	2017	Chillán	232041.6	2017	184739	42867130063	102	0.0005521	16101	23668242
16101122034	16101	29	2017	Chillán	232041.6	2017	184739	42867130063	171	0.0009256	16101	39679111
16101122035	16101	68	2017	Chillán	232041.6	2017	184739	42867130063	534	0.0028906	16101	123910206
16101142009	16101	171	2017	Chillán	232041.6	2017	184739	42867130063	607	0.0032857	16101	140849241
16101142018	16101	157	2017	Chillán	232041.6	2017	184739	42867130063	625	0.0033832	16101	145025990
16101142036	16101	67	2017	Chillán	232041.6	2017	184739	42867130063	443	0.0023980	16101	102794421
16101152016	16101	52	2017	Chillán	232041.6	2017	184739	42867130063	521	0.0028202	16101	120893665
16101152025	16101	356	2017	Chillán	232041.6	2017	184739	42867130063	1780	0.0096352	16101	413034018
16101152033	16101	23	2017	Chillán	232041.6	2017	184739	42867130063	122	0.0006604	16101	28309073
16102012006	16102	9	2017	Bulnes	167693.2	2017	21493	3604229178	183	0.0085144	16102	30687849
16102012029	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	18	0.0008375	16102	3018477
16102012044	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	32	0.0014889	16102	5366181
16102012901	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	58	0.0026986	16102	9726204
16102022005	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703
16102022015	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	160	0.0074443	16102	26830906
16102022019	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	59	0.0027451	16102	9893897
16102022020	16102	17	2017	Bulnes	167693.2	2017	21493	3604229178	359	0.0167031	16102	60201846
16102022034	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102	16937010
16102022035	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	46	0.0021402	16102	7713886
16102022050	16102	32	2017	Bulnes	167693.2	2017	21493	3604229178	422	0.0196343	16102	70766515
16102032014	16102	20	2017	Bulnes	167693.2	2017	21493	3604229178	372	0.0173080	16102	62381857
16102032017	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	31	0.0014423	16102	5198488
16102032019	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	197	0.0091658	16102	33035553
16102032026	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	36	0.0016750	16102	6036954
16102032037	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	93	0.0043270	16102	15595464
16102032038	16102	22	2017	Bulnes	167693.2	2017	21493	3604229178	358	0.0166566	16102	60034153
16102032901	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	24	0.0011166	16102	4024636
16102042016	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	219	0.0101894	16102	36724803
16102042023	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	68	0.0031638	16102	11403135
16102042031	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102	25489361
16102042049	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	41	0.0019076	16102	6875420
16102052010	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	215	0.0100033	16102	36054030
16102052011	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	141	0.0065603	16102	23644736
16102052021	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	92	0.0042805	16102	15427771
16102052043	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	63	0.0029312	16102	10564669
16102052047	16102	13	2017	Bulnes	167693.2	2017	21493	3604229178	428	0.0199135	16102	71772674
16102052049	16102	15	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703
16102052901	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	105	0.0048853	16102	17607782
16102062008	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	81	0.0037687	16102	13583146
16102062013	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	76	0.0035360	16102	12744680
16102062030	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	133	0.0061881	16102	22303191
16102062033	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	97	0.0045131	16102	16266237
16102062040	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	274	0.0127483	16102	45947927
16102062048	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	70	0.0032569	16102	11738521
16102062051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	481	0.0223794	16102	80660412
16102072003	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	66	0.0030708	16102	11067749
16102072008	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	200	0.0093054	16102	33538633
16102072018	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	116	0.0053971	16102	19452407
16102072025	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	20	0.0009305	16102	3353863
16102072028	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	109	0.0050714	16102	18278555
16102072039	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102	16937010
16102072041	16102	12	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102	14086226
16102072045	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	50	0.0023263	16102	8384658
16102072046	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102	25489361
16102072051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	502	0.0233564	16102	84181968
16102082009	16102	14	2017	Bulnes	167693.2	2017	21493	3604229178	456	0.0212162	16102	76468083
16102082027	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	72	0.0033499	16102	12073908
16102082042	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703
16102082045	16102	6	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102	14086226
16103012003	16103	10	2017	Chillán Viejo	179855.8	2017	30907	5558803478	78	0.0025237	16103	14028753
16103012012	16103	26	2017	Chillán Viejo	179855.8	2017	30907	5558803478	542	0.0175365	16103	97481848
16103022001	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103	4856107
16103022005	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	11	0.0003559	16103	1978414
16103022010	16103	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478	35	0.0011324	16103	6294953
16103022013	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	10	0.0003236	16103	1798558
16103022014	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	90	0.0029120	16103	16187023
16103022015	16103	9	2017	Chillán Viejo	179855.8	2017	30907	5558803478	171	0.0055327	16103	30755343
16103022016	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	43	0.0013913	16103	7733800
16103022028	16103	34	2017	Chillán Viejo	179855.8	2017	30907	5558803478	838	0.0271136	16103	150719168
16103022030	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	23	0.0007442	16103	4136684
16103022031	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	48	0.0015530	16103	8633079
16103022901	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	31	0.0010030	16103	5575530
16103032007	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103	4856107
16103032011	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	125	0.0040444	16103	22481976
16103032020	16103	12	2017	Chillán Viejo	179855.8	2017	30907	5558803478	386	0.0124891	16103	69424342
16103032032	16103	8	2017	Chillán Viejo	179855.8	2017	30907	5558803478	151	0.0048856	16103	27158227

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 
## -204704116  -13392802   -5676271    6833794  381251409 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15705016    1222014   12.85   <2e-16 ***
## Freq.x       1691104      50700   33.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 30430000 on 753 degrees of freedom
## Multiple R-squared:  0.5964, Adjusted R-squared:  0.5958 
## F-statistic:  1113 on 1 and 753 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 
## -204704116  -13392802   -5676271    6833794  381251409 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15705016    1222014   12.85   <2e-16 ***
## Freq.x       1691104      50700   33.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 30430000 on 753 degrees of freedom
## Multiple R-squared:  0.5964, Adjusted R-squared:  0.5958 
## F-statistic:  1113 on 1 and 753 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 
## -204704116  -13392802   -5676271    6833794  381251409 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15705016    1222014   12.85   <2e-16 ***
## Freq.x       1691104      50700   33.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 30430000 on 753 degrees of freedom
## Multiple R-squared:  0.5964, Adjusted R-squared:  0.5958 
## F-statistic:  1113 on 1 and 753 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 
## -66319781 -17078994  -3915716  12220118 695600623 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -7521661    2259283  -3.329 0.000913 ***
## log(Freq.x) 26145043    1169997  22.346  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 37140000 on 753 degrees of freedom
## Multiple R-squared:  0.3987, Adjusted R-squared:  0.3979 
## F-statistic: 499.4 on 1 and 753 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 
## -112211517  -11432811    -215376    8324271  535939625 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -18103713    1949704  -9.285   <2e-16 ***
## sqrt(Freq.x)  19637529     610873  32.147   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 31100000 on 753 degrees of freedom
## Multiple R-squared:  0.5785, Adjusted R-squared:  0.5779 
## F-statistic:  1033 on 1 and 753 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 
## -5932.9 -1172.6  -146.2   956.0  7945.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1812.16     109.54   16.54   <2e-16 ***
## sqrt(Freq.x)  1218.55      34.32   35.51   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1747 on 753 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6256 
## F-statistic:  1261 on 1 and 753 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

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

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

## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.5631 -0.5076  0.1385  0.5757  1.9725 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  15.66025    0.05054  309.86   <2e-16 ***
## sqrt(Freq.x)  0.41032    0.01584   25.91   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.8061 on 753 degrees of freedom
## Multiple R-squared:  0.4714, Adjusted R-squared:  0.4707 
## F-statistic: 671.4 on 1 and 753 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 
## -4498.8 -1190.1   -84.2   947.9 16318.8 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2055.55     111.92   18.37   <2e-16 ***
## log(Freq.x)  1889.43      57.96   32.60   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1840 on 753 degrees of freedom
## Multiple R-squared:  0.5853, Adjusted R-squared:  0.5847 
## F-statistic:  1063 on 1 and 753 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 
## -2.97565 -0.47043  0.07868  0.49989  1.79829 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.62067    0.04493  347.67   <2e-16 ***
## log(Freq.x)  0.71478    0.02327   30.72   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7386 on 753 degrees of freedom
## Multiple R-squared:  0.5562, Adjusted R-squared:  0.5556 
## F-statistic: 943.8 on 1 and 753 DF,  p-value: < 2.2e-16

9 Modelo elegido: raíz-raíz (sqrt-sqrt)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.6256).

9.1 Diagrama de dispersión sobre sqrt-sqrt

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 sqrt-sqrt

Observemos nuevamente el resultado sobre sqrt-sqrt.

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 
## -5932.9 -1172.6  -146.2   956.0  7945.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1812.16     109.54   16.54   <2e-16 ***
## sqrt(Freq.x)  1218.55      34.32   35.51   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1747 on 753 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6256 
## F-statistic:  1261 on 1 and 753 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

\[ \hat Y = {1812.16}^2 + 2 \cdot 1812.16 \cdot 1218.55 \cdot \sqrt{X}+ 1218.55 ^2 \cdot X \]

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

Esta nueva variable se llamará: est_ing

h_y_m_comuna_corr_01$est_ing <- 
(1812.16)^2 + 2 * 1812.16 * 1218.55 * sqrt(h_y_m_comuna_corr_01$Freq.x)+  1218.55 ^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
16101042032	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	30	0.0001624	16101	6961248	18056211
16101052010	16101	19	2017	Chillán	232041.6	2017	184739	42867130063	112	0.0006063	16101	25988657	50747049
16101052026	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	355	0.0019216	16101	82374762	54704627
16101052027	16101	26	2017	Chillán	232041.6	2017	184739	42867130063	362	0.0019595	16101	83999053	64409777
16101052028	16101	86	2017	Chillán	232041.6	2017	184739	42867130063	345	0.0018675	16101	80054346	171938386
16101062003	16101	65	2017	Chillán	232041.6	2017	184739	42867130063	638	0.0034535	16101	148042530	135406368
16101062014	16101	50	2017	Chillán	232041.6	2017	184739	42867130063	348	0.0018837	16101	80750471	108755900
16101062024	16101	38	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101	104650754	86933371
16101062027	16101	49	2017	Chillán	232041.6	2017	184739	42867130063	620	0.0033561	16101	143865782	106957171
16101062901	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	373	0.0020191	16101	86551511	54704627
16101072001	16101	97	2017	Chillán	232041.6	2017	184739	42867130063	593	0.0032099	16101	137600659	190812386
16101072901	16101	59	2017	Chillán	232041.6	2017	184739	42867130063	491	0.0026578	16101	113932417	124814034
16101082007	16101	12	2017	Chillán	232041.6	2017	184739	42867130063	184	0.0009960	16101	42695651	36401204
16101082008	16101	11	2017	Chillán	232041.6	2017	184739	42867130063	147	0.0007957	16101	34110113	34265021
16101082011	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	408	0.0022085	16101	94672966	38510768
16101082012	16101	7	2017	Chillán	232041.6	2017	184739	42867130063	139	0.0007524	16101	32253780	25362709
16101082015	16101	30	2017	Chillán	232041.6	2017	184739	42867130063	313	0.0016943	16101	72629016	72019549
16101082031	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	104	0.0005630	16101	24132325	18056211
16101082037	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101	104650754	38510768
16101092901	16101	5	2017	Chillán	232041.6	2017	184739	42867130063	87	0.0004709	16101	20187618	20583649
16101102004	16101	258	2017	Chillán	232041.6	2017	184739	42867130063	3591	0.0194382	16101	833261326	457316993
16101112030	16101	1	2017	Chillán	232041.6	2017	184739	42867130063	37	0.0002003	16101	8585539	9185203
16101122002	16101	22	2017	Chillán	232041.6	2017	184739	42867130063	280	0.0015157	16101	64971643	56665757
16101122017	16101	98	2017	Chillán	232041.6	2017	184739	42867130063	682	0.0036917	16101	158252360	192520885
16101122020	16101	16	2017	Chillán	232041.6	2017	184739	42867130063	102	0.0005521	16101	23668242	44707410
16101122034	16101	29	2017	Chillán	232041.6	2017	184739	42867130063	171	0.0009256	16101	39679111	70128106
16101122035	16101	68	2017	Chillán	232041.6	2017	184739	42867130063	534	0.0028906	16101	123910206	140673375
16101142009	16101	171	2017	Chillán	232041.6	2017	184739	42867130063	607	0.0032857	16101	140849241	314947807
16101142018	16101	157	2017	Chillán	232041.6	2017	184739	42867130063	625	0.0033832	16101	145025990	291745111
16101142036	16101	67	2017	Chillán	232041.6	2017	184739	42867130063	443	0.0023980	16101	102794421	138919735
16101152016	16101	52	2017	Chillán	232041.6	2017	184739	42867130063	521	0.0028202	16101	120893665	112344080
16101152025	16101	356	2017	Chillán	232041.6	2017	184739	42867130063	1780	0.0096352	16101	413034018	615224298
16101152033	16101	23	2017	Chillán	232041.6	2017	184739	42867130063	122	0.0006604	16101	28309073	58616181
16102012006	16102	9	2017	Bulnes	167693.2	2017	21493	3604229178	183	0.0085144	16102	30687849	29896946
16102012029	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	18	0.0008375	16102	3018477	9185203
16102012044	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	32	0.0014889	16102	5366181	18056211
16102012901	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	58	0.0026986	16102	9726204	15387972
16102022005	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703	25362709
16102022015	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	160	0.0074443	16102	26830906	25362709
16102022019	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	59	0.0027451	16102	9893897	18056211
16102022020	16102	17	2017	Bulnes	167693.2	2017	21493	3604229178	359	0.0167031	16102	60201846	46735960
16102022034	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102	16937010	15387972
16102022035	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	46	0.0021402	16102	7713886	9185203
16102022050	16102	32	2017	Bulnes	167693.2	2017	21493	3604229178	422	0.0196343	16102	70766515	75782592
16102032014	16102	20	2017	Bulnes	167693.2	2017	21493	3604229178	372	0.0173080	16102	62381857	52732015
16102032017	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	31	0.0014423	16102	5198488	15387972
16102032019	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	197	0.0091658	16102	33035553	44707410
16102032026	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	36	0.0016750	16102	6036954	12499406
16102032037	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	93	0.0043270	16102	15595464	18056211
16102032038	16102	22	2017	Bulnes	167693.2	2017	21493	3604229178	358	0.0166566	16102	60034153	56665757
16102032901	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	24	0.0011166	16102	4024636	9185203
16102042016	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	219	0.0101894	16102	36724803	9185203
16102042023	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	68	0.0031638	16102	11403135	9185203
16102042031	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102	25489361	44707410
16102042049	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	41	0.0019076	16102	6875420	15387972
16102052010	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	215	0.0100033	16102	36054030	9185203
16102052011	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	141	0.0065603	16102	23644736	27654345
16102052021	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	92	0.0042805	16102	15427771	18056211
16102052043	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	63	0.0029312	16102	10564669	12499406
16102052047	16102	13	2017	Bulnes	167693.2	2017	21493	3604229178	428	0.0199135	16102	71772674	38510768
16102052049	16102	15	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703	42661588
16102052901	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	105	0.0048853	16102	17607782	12499406
16102062008	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	81	0.0037687	16102	13583146	25362709
16102062013	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	76	0.0035360	16102	12744680	9185203
16102062030	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	133	0.0061881	16102	22303191	12499406
16102062033	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	97	0.0045131	16102	16266237	9185203
16102062040	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	274	0.0127483	16102	45947927	25362709
16102062048	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	70	0.0032569	16102	11738521	9185203
16102062051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	481	0.0223794	16102	80660412	27654345
16102072003	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	66	0.0030708	16102	11067749	15387972
16102072008	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	200	0.0093054	16102	33538633	15387972
16102072018	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	116	0.0053971	16102	19452407	12499406
16102072025	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	20	0.0009305	16102	3353863	9185203
16102072028	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	109	0.0050714	16102	18278555	25362709
16102072039	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102	16937010	20583649
16102072041	16102	12	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102	14086226	36401204
16102072045	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	50	0.0023263	16102	8384658	20583649
16102072046	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102	25489361	15387972
16102072051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	502	0.0233564	16102	84181968	27654345
16102082009	16102	14	2017	Bulnes	167693.2	2017	21493	3604229178	456	0.0212162	16102	76468083	40596734
16102082027	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	72	0.0033499	16102	12073908	15387972
16102082042	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703	15387972
16102082045	16102	6	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102	14086226	23011072
16103012003	16103	10	2017	Chillán Viejo	179855.8	2017	30907	5558803478	78	0.0025237	16103	14028753	32098496
16103012012	16103	26	2017	Chillán Viejo	179855.8	2017	30907	5558803478	542	0.0175365	16103	97481848	64409777
16103022001	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103	4856107	9185203
16103022005	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	11	0.0003559	16103	1978414	9185203
16103022010	16103	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478	35	0.0011324	16103	6294953	18056211
16103022013	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	10	0.0003236	16103	1798558	9185203
16103022014	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	90	0.0029120	16103	16187023	15387972
16103022015	16103	9	2017	Chillán Viejo	179855.8	2017	30907	5558803478	171	0.0055327	16103	30755343	29896946
16103022016	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	43	0.0013913	16103	7733800	9185203
16103022028	16103	34	2017	Chillán Viejo	179855.8	2017	30907	5558803478	838	0.0271136	16103	150719168	79521208
16103022030	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	23	0.0007442	16103	4136684	12499406
16103022031	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	48	0.0015530	16103	8633079	12499406
16103022901	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	31	0.0010030	16103	5575530	12499406
16103032007	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103	4856107	15387972
16103032011	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	125	0.0040444	16103	22481976	9185203
16103032020	16103	12	2017	Chillán Viejo	179855.8	2017	30907	5558803478	386	0.0124891	16103	69424342	36401204
16103032032	16103	8	2017	Chillán Viejo	179855.8	2017	30907	5558803478	151	0.0048856	16103	27158227	27654345

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
16101042032	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	30	0.0001624	16101	6961248	18056211	601873.68
16101052010	16101	19	2017	Chillán	232041.6	2017	184739	42867130063	112	0.0006063	16101	25988657	50747049	453098.65
16101052026	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	355	0.0019216	16101	82374762	54704627	154097.54
16101052027	16101	26	2017	Chillán	232041.6	2017	184739	42867130063	362	0.0019595	16101	83999053	64409777	177927.56
16101052028	16101	86	2017	Chillán	232041.6	2017	184739	42867130063	345	0.0018675	16101	80054346	171938386	498372.13
16101062003	16101	65	2017	Chillán	232041.6	2017	184739	42867130063	638	0.0034535	16101	148042530	135406368	212235.69
16101062014	16101	50	2017	Chillán	232041.6	2017	184739	42867130063	348	0.0018837	16101	80750471	108755900	312516.95
16101062024	16101	38	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101	104650754	86933371	192756.92
16101062027	16101	49	2017	Chillán	232041.6	2017	184739	42867130063	620	0.0033561	16101	143865782	106957171	172511.57
16101062901	16101	21	2017	Chillán	232041.6	2017	184739	42867130063	373	0.0020191	16101	86551511	54704627	146661.20
16101072001	16101	97	2017	Chillán	232041.6	2017	184739	42867130063	593	0.0032099	16101	137600659	190812386	321774.68
16101072901	16101	59	2017	Chillán	232041.6	2017	184739	42867130063	491	0.0026578	16101	113932417	124814034	254203.74
16101082007	16101	12	2017	Chillán	232041.6	2017	184739	42867130063	184	0.0009960	16101	42695651	36401204	197832.63
16101082008	16101	11	2017	Chillán	232041.6	2017	184739	42867130063	147	0.0007957	16101	34110113	34265021	233095.38
16101082011	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	408	0.0022085	16101	94672966	38510768	94389.14
16101082012	16101	7	2017	Chillán	232041.6	2017	184739	42867130063	139	0.0007524	16101	32253780	25362709	182465.53
16101082015	16101	30	2017	Chillán	232041.6	2017	184739	42867130063	313	0.0016943	16101	72629016	72019549	230094.41
16101082031	16101	4	2017	Chillán	232041.6	2017	184739	42867130063	104	0.0005630	16101	24132325	18056211	173617.41
16101082037	16101	13	2017	Chillán	232041.6	2017	184739	42867130063	451	0.0024413	16101	104650754	38510768	85389.73
16101092901	16101	5	2017	Chillán	232041.6	2017	184739	42867130063	87	0.0004709	16101	20187618	20583649	236593.66
16101102004	16101	258	2017	Chillán	232041.6	2017	184739	42867130063	3591	0.0194382	16101	833261326	457316993	127350.88
16101112030	16101	1	2017	Chillán	232041.6	2017	184739	42867130063	37	0.0002003	16101	8585539	9185203	248248.73
16101122002	16101	22	2017	Chillán	232041.6	2017	184739	42867130063	280	0.0015157	16101	64971643	56665757	202377.70
16101122017	16101	98	2017	Chillán	232041.6	2017	184739	42867130063	682	0.0036917	16101	158252360	192520885	282288.69
16101122020	16101	16	2017	Chillán	232041.6	2017	184739	42867130063	102	0.0005521	16101	23668242	44707410	438307.94
16101122034	16101	29	2017	Chillán	232041.6	2017	184739	42867130063	171	0.0009256	16101	39679111	70128106	410105.88
16101122035	16101	68	2017	Chillán	232041.6	2017	184739	42867130063	534	0.0028906	16101	123910206	140673375	263433.29
16101142009	16101	171	2017	Chillán	232041.6	2017	184739	42867130063	607	0.0032857	16101	140849241	314947807	518859.65
16101142018	16101	157	2017	Chillán	232041.6	2017	184739	42867130063	625	0.0033832	16101	145025990	291745111	466792.18
16101142036	16101	67	2017	Chillán	232041.6	2017	184739	42867130063	443	0.0023980	16101	102794421	138919735	313588.57
16101152016	16101	52	2017	Chillán	232041.6	2017	184739	42867130063	521	0.0028202	16101	120893665	112344080	215631.63
16101152025	16101	356	2017	Chillán	232041.6	2017	184739	42867130063	1780	0.0096352	16101	413034018	615224298	345631.63
16101152033	16101	23	2017	Chillán	232041.6	2017	184739	42867130063	122	0.0006604	16101	28309073	58616181	480460.50
16102012006	16102	9	2017	Bulnes	167693.2	2017	21493	3604229178	183	0.0085144	16102	30687849	29896946	163371.29
16102012029	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	18	0.0008375	16102	3018477	9185203	510289.06
16102012044	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	32	0.0014889	16102	5366181	18056211	564256.58
16102012901	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	58	0.0026986	16102	9726204	15387972	265309.85
16102022005	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703	25362709	248654.01
16102022015	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	160	0.0074443	16102	26830906	25362709	158516.93
16102022019	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	59	0.0027451	16102	9893897	18056211	306037.47
16102022020	16102	17	2017	Bulnes	167693.2	2017	21493	3604229178	359	0.0167031	16102	60201846	46735960	130183.73
16102022034	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102	16937010	15387972	152356.15
16102022035	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	46	0.0021402	16102	7713886	9185203	199678.33
16102022050	16102	32	2017	Bulnes	167693.2	2017	21493	3604229178	422	0.0196343	16102	70766515	75782592	179579.60
16102032014	16102	20	2017	Bulnes	167693.2	2017	21493	3604229178	372	0.0173080	16102	62381857	52732015	141752.73
16102032017	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	31	0.0014423	16102	5198488	15387972	496386.18
16102032019	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	197	0.0091658	16102	33035553	44707410	226941.17
16102032026	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	36	0.0016750	16102	6036954	12499406	347205.73
16102032037	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	93	0.0043270	16102	15595464	18056211	194152.80
16102032038	16102	22	2017	Bulnes	167693.2	2017	21493	3604229178	358	0.0166566	16102	60034153	56665757	158284.24
16102032901	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	24	0.0011166	16102	4024636	9185203	382716.80
16102042016	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	219	0.0101894	16102	36724803	9185203	41941.57
16102042023	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	68	0.0031638	16102	11403135	9185203	135076.52
16102042031	16102	16	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102	25489361	44707410	294127.70
16102042049	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	41	0.0019076	16102	6875420	15387972	375316.38
16102052010	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	215	0.0100033	16102	36054030	9185203	42721.87
16102052011	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	141	0.0065603	16102	23644736	27654345	196130.11
16102052021	16102	4	2017	Bulnes	167693.2	2017	21493	3604229178	92	0.0042805	16102	15427771	18056211	196263.16
16102052043	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	63	0.0029312	16102	10564669	12499406	198403.27
16102052047	16102	13	2017	Bulnes	167693.2	2017	21493	3604229178	428	0.0199135	16102	71772674	38510768	89978.43
16102052049	16102	15	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703	42661588	418250.86
16102052901	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	105	0.0048853	16102	17607782	12499406	119041.96
16102062008	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	81	0.0037687	16102	13583146	25362709	313119.86
16102062013	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	76	0.0035360	16102	12744680	9185203	120857.94
16102062030	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	133	0.0061881	16102	22303191	12499406	93980.50
16102062033	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	97	0.0045131	16102	16266237	9185203	94692.82
16102062040	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	274	0.0127483	16102	45947927	25362709	92564.63
16102062048	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	70	0.0032569	16102	11738521	9185203	131217.19
16102062051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	481	0.0223794	16102	80660412	27654345	57493.44
16102072003	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	66	0.0030708	16102	11067749	15387972	233151.08
16102072008	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	200	0.0093054	16102	33538633	15387972	76939.86
16102072018	16102	2	2017	Bulnes	167693.2	2017	21493	3604229178	116	0.0053971	16102	19452407	12499406	107753.50
16102072025	16102	1	2017	Bulnes	167693.2	2017	21493	3604229178	20	0.0009305	16102	3353863	9185203	459260.16
16102072028	16102	7	2017	Bulnes	167693.2	2017	21493	3604229178	109	0.0050714	16102	18278555	25362709	232685.40
16102072039	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	101	0.0046992	16102	16937010	20583649	203798.50
16102072041	16102	12	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102	14086226	36401204	433347.67
16102072045	16102	5	2017	Bulnes	167693.2	2017	21493	3604229178	50	0.0023263	16102	8384658	20583649	411672.98
16102072046	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	152	0.0070721	16102	25489361	15387972	101236.66
16102072051	16102	8	2017	Bulnes	167693.2	2017	21493	3604229178	502	0.0233564	16102	84181968	27654345	55088.34
16102082009	16102	14	2017	Bulnes	167693.2	2017	21493	3604229178	456	0.0212162	16102	76468083	40596734	89027.92
16102082027	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	72	0.0033499	16102	12073908	15387972	213721.83
16102082042	16102	3	2017	Bulnes	167693.2	2017	21493	3604229178	102	0.0047457	16102	17104703	15387972	150862.47
16102082045	16102	6	2017	Bulnes	167693.2	2017	21493	3604229178	84	0.0039082	16102	14086226	23011072	273941.33
16103012003	16103	10	2017	Chillán Viejo	179855.8	2017	30907	5558803478	78	0.0025237	16103	14028753	32098496	411519.18
16103012012	16103	26	2017	Chillán Viejo	179855.8	2017	30907	5558803478	542	0.0175365	16103	97481848	64409777	118837.23
16103022001	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103	4856107	9185203	340192.71
16103022005	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	11	0.0003559	16103	1978414	9185203	835018.46
16103022010	16103	4	2017	Chillán Viejo	179855.8	2017	30907	5558803478	35	0.0011324	16103	6294953	18056211	515891.73
16103022013	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	10	0.0003236	16103	1798558	9185203	918520.31
16103022014	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	90	0.0029120	16103	16187023	15387972	170977.46
16103022015	16103	9	2017	Chillán Viejo	179855.8	2017	30907	5558803478	171	0.0055327	16103	30755343	29896946	174835.94
16103022016	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	43	0.0013913	16103	7733800	9185203	213609.37
16103022028	16103	34	2017	Chillán Viejo	179855.8	2017	30907	5558803478	838	0.0271136	16103	150719168	79521208	94894.04
16103022030	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	23	0.0007442	16103	4136684	12499406	543452.45
16103022031	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	48	0.0015530	16103	8633079	12499406	260404.30
16103022901	16103	2	2017	Chillán Viejo	179855.8	2017	30907	5558803478	31	0.0010030	16103	5575530	12499406	403206.65
16103032007	16103	3	2017	Chillán Viejo	179855.8	2017	30907	5558803478	27	0.0008736	16103	4856107	15387972	569924.87
16103032011	16103	1	2017	Chillán Viejo	179855.8	2017	30907	5558803478	125	0.0040444	16103	22481976	9185203	73481.62
16103032020	16103	12	2017	Chillán Viejo	179855.8	2017	30907	5558803478	386	0.0124891	16103	69424342	36401204	94303.64
16103032032	16103	8	2017	Chillán Viejo	179855.8	2017	30907	5558803478	151	0.0048856	16103	27158227	27654345	183141.36

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "P15/region_16_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