Expansión de la CASEN sobre el CENSO (Región 13)

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 13.

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 13 y con la zona = 2:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 13) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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	13110072002	12	13110	42	2017
488	13115022001	12	13115	43	2017
489	13115022901	12	13115	13	2017
490	13115032002	12	13115	6	2017
491	13115032003	12	13115	8	2017
492	13115032004	12	13115	1	2017
493	13115032006	12	13115	203	2017
494	13115032007	12	13115	33	2017
495	13115032008	12	13115	7	2017
496	13115032901	12	13115	19	2017
983	13119072006	12	13119	53	2017
984	13119132006	12	13119	57	2017
985	13119132901	12	13119	2	2017
986	13119142001	12	13119	17	2017
987	13119142004	12	13119	20	2017
1474	13124062013	12	13124	9	2017
1475	13124062901	12	13124	6	2017
1476	13124072012	12	13124	5	2017
1477	13124072016	12	13124	14	2017
1478	13124072019	12	13124	128	2017
1479	13124082008	12	13124	21	2017
1480	13124082009	12	13124	2	2017
1481	13124082010	12	13124	17	2017
1482	13124082011	12	13124	10	2017
1483	13124082017	12	13124	4	2017
1484	13124082020	12	13124	16	2017
1971	13125022002	12	13125	5	2017
1972	13125022004	12	13125	3	2017
2459	13202012001	12	13202	478	2017
2460	13202012002	12	13202	272	2017
2461	13202012005	12	13202	168	2017
2462	13202012009	12	13202	170	2017
2463	13202022004	12	13202	94	2017
2464	13202022006	12	13202	82	2017
2465	13202022007	12	13202	57	2017
2466	13202022010	12	13202	101	2017
2467	13202022011	12	13202	16	2017
2468	13202022012	12	13202	197	2017
2469	13202022014	12	13202	353	2017
2470	13202032003	12	13202	472	2017
2471	13202032008	12	13202	441	2017
2472	13202032013	12	13202	338	2017
2959	13203012004	12	13203	53	2017
2960	13203012005	12	13203	102	2017
2961	13203012012	12	13203	6	2017
2962	13203012019	12	13203	56	2017
2963	13203012901	12	13203	1	2017
2964	13203022002	12	13203	7	2017
2965	13203022004	12	13203	4	2017
2966	13203022015	12	13203	101	2017
2967	13203032017	12	13203	10	2017
2968	13203032018	12	13203	104	2017
2969	13203042001	12	13203	4	2017
2970	13203042008	12	13203	8	2017
2971	13203042010	12	13203	43	2017
2972	13203042013	12	13203	2	2017
2973	13203042014	12	13203	1	2017
2974	13203042901	12	13203	12	2017
2975	13203052006	12	13203	66	2017
2976	13203052009	12	13203	16	2017
2977	13203052017	12	13203	7	2017
2978	13203062003	12	13203	83	2017
2979	13203062007	12	13203	447	2017
3466	13301012005	12	13301	207	2017
3467	13301012010	12	13301	4	2017
3468	13301012012	12	13301	517	2017
3469	13301012015	12	13301	98	2017
3470	13301012018	12	13301	281	2017
3471	13301012025	12	13301	46	2017
3472	13301012026	12	13301	47	2017
3473	13301012029	12	13301	16	2017
3474	13301022004	12	13301	1706	2017
3475	13301022006	12	13301	341	2017
3476	13301022008	12	13301	77	2017
3477	13301032001	12	13301	16	2017
3478	13301032007	12	13301	637	2017
3479	13301032013	12	13301	82	2017
3480	13301032014	12	13301	40	2017
3481	13301032018	12	13301	291	2017
3482	13301032019	12	13301	14	2017
3483	13301032020	12	13301	283	2017
3484	13301032022	12	13301	96	2017
3485	13301032024	12	13301	859	2017
3486	13301032028	12	13301	296	2017
3487	13301042021	12	13301	25	2017
3488	13301052002	12	13301	137	2017
3489	13301052009	12	13301	18	2017
3490	13301052023	12	13301	53	2017
3491	13301052901	12	13301	2	2017
3492	13301062004	12	13301	496	2017
3493	13301062005	12	13301	44	2017
3494	13301062016	12	13301	400	2017
3495	13301062027	12	13301	72	2017
3982	13302012003	12	13302	102	2017
3983	13302012006	12	13302	26	2017
3984	13302012009	12	13302	77	2017
3985	13302012014	12	13302	37	2017
3986	13302012016	12	13302	4	2017
3987	13302012017	12	13302	15	2017
3988	13302012018	12	13302	7	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	13110072002	42	2017	13110
488	13115022001	43	2017	13115
489	13115022901	13	2017	13115
490	13115032002	6	2017	13115
491	13115032003	8	2017	13115
492	13115032004	1	2017	13115
493	13115032006	203	2017	13115
494	13115032007	33	2017	13115
495	13115032008	7	2017	13115
496	13115032901	19	2017	13115
983	13119072006	53	2017	13119
984	13119132006	57	2017	13119
985	13119132901	2	2017	13119
986	13119142001	17	2017	13119
987	13119142004	20	2017	13119
1474	13124062013	9	2017	13124
1475	13124062901	6	2017	13124
1476	13124072012	5	2017	13124
1477	13124072016	14	2017	13124
1478	13124072019	128	2017	13124
1479	13124082008	21	2017	13124
1480	13124082009	2	2017	13124
1481	13124082010	17	2017	13124
1482	13124082011	10	2017	13124
1483	13124082017	4	2017	13124
1484	13124082020	16	2017	13124
1971	13125022002	5	2017	13125
1972	13125022004	3	2017	13125
2459	13202012001	478	2017	13202
2460	13202012002	272	2017	13202
2461	13202012005	168	2017	13202
2462	13202012009	170	2017	13202
2463	13202022004	94	2017	13202
2464	13202022006	82	2017	13202
2465	13202022007	57	2017	13202
2466	13202022010	101	2017	13202
2467	13202022011	16	2017	13202
2468	13202022012	197	2017	13202
2469	13202022014	353	2017	13202
2470	13202032003	472	2017	13202
2471	13202032008	441	2017	13202
2472	13202032013	338	2017	13202
2959	13203012004	53	2017	13203
2960	13203012005	102	2017	13203
2961	13203012012	6	2017	13203
2962	13203012019	56	2017	13203
2963	13203012901	1	2017	13203
2964	13203022002	7	2017	13203
2965	13203022004	4	2017	13203
2966	13203022015	101	2017	13203
2967	13203032017	10	2017	13203
2968	13203032018	104	2017	13203
2969	13203042001	4	2017	13203
2970	13203042008	8	2017	13203
2971	13203042010	43	2017	13203
2972	13203042013	2	2017	13203
2973	13203042014	1	2017	13203
2974	13203042901	12	2017	13203
2975	13203052006	66	2017	13203
2976	13203052009	16	2017	13203
2977	13203052017	7	2017	13203
2978	13203062003	83	2017	13203
2979	13203062007	447	2017	13203
3466	13301012005	207	2017	13301
3467	13301012010	4	2017	13301
3468	13301012012	517	2017	13301
3469	13301012015	98	2017	13301
3470	13301012018	281	2017	13301
3471	13301012025	46	2017	13301
3472	13301012026	47	2017	13301
3473	13301012029	16	2017	13301
3474	13301022004	1706	2017	13301
3475	13301022006	341	2017	13301
3476	13301022008	77	2017	13301
3477	13301032001	16	2017	13301
3478	13301032007	637	2017	13301
3479	13301032013	82	2017	13301
3480	13301032014	40	2017	13301
3481	13301032018	291	2017	13301
3482	13301032019	14	2017	13301
3483	13301032020	283	2017	13301
3484	13301032022	96	2017	13301
3485	13301032024	859	2017	13301
3486	13301032028	296	2017	13301
3487	13301042021	25	2017	13301
3488	13301052002	137	2017	13301
3489	13301052009	18	2017	13301
3490	13301052023	53	2017	13301
3491	13301052901	2	2017	13301
3492	13301062004	496	2017	13301
3493	13301062005	44	2017	13301
3494	13301062016	400	2017	13301
3495	13301062027	72	2017	13301
3982	13302012003	102	2017	13302
3983	13302012006	26	2017	13302
3984	13302012009	77	2017	13302
3985	13302012014	37	2017	13302
3986	13302012016	4	2017	13302
3987	13302012017	15	2017	13302
3988	13302012018	7	2017	13302

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
29	13202	13202012001	478	2017	Pirque	274675.6	2017	26521	7284672878
30	13202	13202012002	272	2017	Pirque	274675.6	2017	26521	7284672878
31	13202	13202012005	168	2017	Pirque	274675.6	2017	26521	7284672878
32	13202	13202012009	170	2017	Pirque	274675.6	2017	26521	7284672878
33	13202	13202022004	94	2017	Pirque	274675.6	2017	26521	7284672878
34	13202	13202022006	82	2017	Pirque	274675.6	2017	26521	7284672878
35	13202	13202022007	57	2017	Pirque	274675.6	2017	26521	7284672878
36	13202	13202022010	101	2017	Pirque	274675.6	2017	26521	7284672878
37	13202	13202022011	16	2017	Pirque	274675.6	2017	26521	7284672878
38	13202	13202022012	197	2017	Pirque	274675.6	2017	26521	7284672878
39	13202	13202022014	353	2017	Pirque	274675.6	2017	26521	7284672878
40	13202	13202032003	472	2017	Pirque	274675.6	2017	26521	7284672878
41	13202	13202032008	441	2017	Pirque	274675.6	2017	26521	7284672878
42	13202	13202032013	338	2017	Pirque	274675.6	2017	26521	7284672878
43	13203	13203012004	53	2017	San José de Maipo	344876.8	2017	18189	6272964115
44	13203	13203012005	102	2017	San José de Maipo	344876.8	2017	18189	6272964115
45	13203	13203012012	6	2017	San José de Maipo	344876.8	2017	18189	6272964115
46	13203	13203012019	56	2017	San José de Maipo	344876.8	2017	18189	6272964115
47	13203	13203012901	1	2017	San José de Maipo	344876.8	2017	18189	6272964115
48	13203	13203022002	7	2017	San José de Maipo	344876.8	2017	18189	6272964115
49	13203	13203022004	4	2017	San José de Maipo	344876.8	2017	18189	6272964115
50	13203	13203022015	101	2017	San José de Maipo	344876.8	2017	18189	6272964115
51	13203	13203032017	10	2017	San José de Maipo	344876.8	2017	18189	6272964115
52	13203	13203032018	104	2017	San José de Maipo	344876.8	2017	18189	6272964115
53	13203	13203042001	4	2017	San José de Maipo	344876.8	2017	18189	6272964115
54	13203	13203042008	8	2017	San José de Maipo	344876.8	2017	18189	6272964115
55	13203	13203042010	43	2017	San José de Maipo	344876.8	2017	18189	6272964115
56	13203	13203042013	2	2017	San José de Maipo	344876.8	2017	18189	6272964115
57	13203	13203042014	1	2017	San José de Maipo	344876.8	2017	18189	6272964115
58	13203	13203042901	12	2017	San José de Maipo	344876.8	2017	18189	6272964115
59	13203	13203052006	66	2017	San José de Maipo	344876.8	2017	18189	6272964115
60	13203	13203052009	16	2017	San José de Maipo	344876.8	2017	18189	6272964115
61	13203	13203052017	7	2017	San José de Maipo	344876.8	2017	18189	6272964115
62	13203	13203062003	83	2017	San José de Maipo	344876.8	2017	18189	6272964115
63	13203	13203062007	447	2017	San José de Maipo	344876.8	2017	18189	6272964115
64	13301	13301012005	207	2017	Colina	255373.7	2017	146207	37337421744
65	13301	13301012010	4	2017	Colina	255373.7	2017	146207	37337421744
66	13301	13301012012	517	2017	Colina	255373.7	2017	146207	37337421744
67	13301	13301012015	98	2017	Colina	255373.7	2017	146207	37337421744
68	13301	13301012018	281	2017	Colina	255373.7	2017	146207	37337421744
69	13301	13301012025	46	2017	Colina	255373.7	2017	146207	37337421744
70	13301	13301012026	47	2017	Colina	255373.7	2017	146207	37337421744
71	13301	13301012029	16	2017	Colina	255373.7	2017	146207	37337421744
72	13301	13301022004	1706	2017	Colina	255373.7	2017	146207	37337421744
73	13301	13301022006	341	2017	Colina	255373.7	2017	146207	37337421744
74	13301	13301022008	77	2017	Colina	255373.7	2017	146207	37337421744
75	13301	13301032001	16	2017	Colina	255373.7	2017	146207	37337421744
76	13301	13301032007	637	2017	Colina	255373.7	2017	146207	37337421744
77	13301	13301032013	82	2017	Colina	255373.7	2017	146207	37337421744
78	13301	13301032014	40	2017	Colina	255373.7	2017	146207	37337421744
79	13301	13301032018	291	2017	Colina	255373.7	2017	146207	37337421744
80	13301	13301032019	14	2017	Colina	255373.7	2017	146207	37337421744
81	13301	13301032020	283	2017	Colina	255373.7	2017	146207	37337421744
82	13301	13301032022	96	2017	Colina	255373.7	2017	146207	37337421744
83	13301	13301032024	859	2017	Colina	255373.7	2017	146207	37337421744
84	13301	13301032028	296	2017	Colina	255373.7	2017	146207	37337421744
85	13301	13301042021	25	2017	Colina	255373.7	2017	146207	37337421744
86	13301	13301052002	137	2017	Colina	255373.7	2017	146207	37337421744
87	13301	13301052009	18	2017	Colina	255373.7	2017	146207	37337421744
88	13301	13301052023	53	2017	Colina	255373.7	2017	146207	37337421744
89	13301	13301052901	2	2017	Colina	255373.7	2017	146207	37337421744
90	13301	13301062004	496	2017	Colina	255373.7	2017	146207	37337421744
91	13301	13301062005	44	2017	Colina	255373.7	2017	146207	37337421744
92	13301	13301062016	400	2017	Colina	255373.7	2017	146207	37337421744
93	13301	13301062027	72	2017	Colina	255373.7	2017	146207	37337421744
94	13302	13302012003	102	2017	Lampa	243425.7	2017	102034	24837699582
95	13302	13302012006	26	2017	Lampa	243425.7	2017	102034	24837699582
96	13302	13302012009	77	2017	Lampa	243425.7	2017	102034	24837699582
97	13302	13302012014	37	2017	Lampa	243425.7	2017	102034	24837699582
98	13302	13302012016	4	2017	Lampa	243425.7	2017	102034	24837699582
99	13302	13302012017	15	2017	Lampa	243425.7	2017	102034	24837699582
100	13302	13302012018	7	2017	Lampa	243425.7	2017	102034	24837699582
101	13302	13302012019	43	2017	Lampa	243425.7	2017	102034	24837699582
102	13302	13302012020	32	2017	Lampa	243425.7	2017	102034	24837699582
103	13302	13302012021	9	2017	Lampa	243425.7	2017	102034	24837699582
104	13302	13302012028	48	2017	Lampa	243425.7	2017	102034	24837699582
105	13302	13302012901	1	2017	Lampa	243425.7	2017	102034	24837699582
106	13302	13302022002	11	2017	Lampa	243425.7	2017	102034	24837699582
107	13302	13302022005	62	2017	Lampa	243425.7	2017	102034	24837699582
108	13302	13302022007	2	2017	Lampa	243425.7	2017	102034	24837699582
109	13302	13302022017	145	2017	Lampa	243425.7	2017	102034	24837699582
110	13302	13302032001	231	2017	Lampa	243425.7	2017	102034	24837699582
111	13302	13302032010	45	2017	Lampa	243425.7	2017	102034	24837699582
112	13302	13302032015	3	2017	Lampa	243425.7	2017	102034	24837699582
113	13302	13302032019	3	2017	Lampa	243425.7	2017	102034	24837699582
114	13302	13302032022	42	2017	Lampa	243425.7	2017	102034	24837699582
115	13302	13302032025	454	2017	Lampa	243425.7	2017	102034	24837699582
116	13302	13302032026	906	2017	Lampa	243425.7	2017	102034	24837699582
117	13302	13302032027	536	2017	Lampa	243425.7	2017	102034	24837699582
118	13302	13302042008	77	2017	Lampa	243425.7	2017	102034	24837699582
119	13302	13302042010	4	2017	Lampa	243425.7	2017	102034	24837699582
120	13302	13302042012	12	2017	Lampa	243425.7	2017	102034	24837699582
121	13302	13302042901	4	2017	Lampa	243425.7	2017	102034	24837699582
122	13302	13302052004	17	2017	Lampa	243425.7	2017	102034	24837699582
123	13302	13302052011	6	2017	Lampa	243425.7	2017	102034	24837699582
124	13302	13302052014	180	2017	Lampa	243425.7	2017	102034	24837699582
125	13302	13302052023	17	2017	Lampa	243425.7	2017	102034	24837699582
126	13303	13303012003	11	2017	Tiltil	264794.8	2017	19312	5113717064
127	13303	13303012012	39	2017	Tiltil	264794.8	2017	19312	5113717064
128	13303	13303022006	12	2017	Tiltil	264794.8	2017	19312	5113717064
129	13303	13303022007	29	2017	Tiltil	264794.8	2017	19312	5113717064
130	13303	13303022009	124	2017	Tiltil	264794.8	2017	19312	5113717064
131	13303	13303022011	28	2017	Tiltil	264794.8	2017	19312	5113717064
132	13303	13303032008	22	2017	Tiltil	264794.8	2017	19312	5113717064
133	13303	13303042010	28	2017	Tiltil	264794.8	2017	19312	5113717064
134	13303	13303052002	41	2017	Tiltil	264794.8	2017	19312	5113717064
135	13303	13303052004	38	2017	Tiltil	264794.8	2017	19312	5113717064
136	13401	13401062004	18	2017	San Bernardo	251728.3	2017	301313	75849003232
137	13401	13401062005	5	2017	San Bernardo	251728.3	2017	301313	75849003232
138	13401	13401062009	7	2017	San Bernardo	251728.3	2017	301313	75849003232
139	13401	13401062012	1	2017	San Bernardo	251728.3	2017	301313	75849003232
140	13401	13401062016	1	2017	San Bernardo	251728.3	2017	301313	75849003232
141	13401	13401062018	1	2017	San Bernardo	251728.3	2017	301313	75849003232
142	13401	13401062020	2	2017	San Bernardo	251728.3	2017	301313	75849003232
143	13401	13401082002	66	2017	San Bernardo	251728.3	2017	301313	75849003232
144	13401	13401082003	91	2017	San Bernardo	251728.3	2017	301313	75849003232
145	13401	13401082013	35	2017	San Bernardo	251728.3	2017	301313	75849003232
146	13401	13401082021	175	2017	San Bernardo	251728.3	2017	301313	75849003232
147	13401	13401112008	3	2017	San Bernardo	251728.3	2017	301313	75849003232
148	13401	13401112014	1	2017	San Bernardo	251728.3	2017	301313	75849003232
149	13401	13401112015	34	2017	San Bernardo	251728.3	2017	301313	75849003232
150	13401	13401122006	75	2017	San Bernardo	251728.3	2017	301313	75849003232
151	13401	13401122007	26	2017	San Bernardo	251728.3	2017	301313	75849003232
152	13401	13401122010	25	2017	San Bernardo	251728.3	2017	301313	75849003232
153	13401	13401122011	43	2017	San Bernardo	251728.3	2017	301313	75849003232
154	13402	13402012002	260	2017	Buin	289884.0	2017	96614	28006850165
155	13402	13402022001	151	2017	Buin	289884.0	2017	96614	28006850165
156	13402	13402022012	89	2017	Buin	289884.0	2017	96614	28006850165
157	13402	13402022013	5	2017	Buin	289884.0	2017	96614	28006850165
158	13402	13402032004	282	2017	Buin	289884.0	2017	96614	28006850165
159	13402	13402032010	385	2017	Buin	289884.0	2017	96614	28006850165
160	13402	13402042002	7	2017	Buin	289884.0	2017	96614	28006850165
161	13402	13402042004	45	2017	Buin	289884.0	2017	96614	28006850165
162	13402	13402042008	8	2017	Buin	289884.0	2017	96614	28006850165
163	13402	13402042014	2	2017	Buin	289884.0	2017	96614	28006850165
164	13402	13402042015	48	2017	Buin	289884.0	2017	96614	28006850165
165	13402	13402052003	63	2017	Buin	289884.0	2017	96614	28006850165
166	13402	13402052008	10	2017	Buin	289884.0	2017	96614	28006850165
167	13402	13402052009	6	2017	Buin	289884.0	2017	96614	28006850165
168	13402	13402052011	12	2017	Buin	289884.0	2017	96614	28006850165
169	13402	13402052016	26	2017	Buin	289884.0	2017	96614	28006850165
170	13402	13402052017	162	2017	Buin	289884.0	2017	96614	28006850165
171	13402	13402062005	79	2017	Buin	289884.0	2017	96614	28006850165
172	13402	13402062006	119	2017	Buin	289884.0	2017	96614	28006850165
173	13402	13402062007	130	2017	Buin	289884.0	2017	96614	28006850165
174	13402	13402062012	13	2017	Buin	289884.0	2017	96614	28006850165
175	13402	13402062013	18	2017	Buin	289884.0	2017	96614	28006850165
176	13403	13403012003	125	2017	Calera de Tango	298439.8	2017	25392	7577982724
177	13403	13403012004	332	2017	Calera de Tango	298439.8	2017	25392	7577982724
178	13403	13403012008	339	2017	Calera de Tango	298439.8	2017	25392	7577982724
179	13403	13403012013	38	2017	Calera de Tango	298439.8	2017	25392	7577982724
180	13403	13403022001	16	2017	Calera de Tango	298439.8	2017	25392	7577982724
181	13403	13403022008	261	2017	Calera de Tango	298439.8	2017	25392	7577982724
182	13403	13403022011	123	2017	Calera de Tango	298439.8	2017	25392	7577982724
183	13403	13403022013	191	2017	Calera de Tango	298439.8	2017	25392	7577982724
184	13403	13403022014	192	2017	Calera de Tango	298439.8	2017	25392	7577982724
185	13403	13403022018	98	2017	Calera de Tango	298439.8	2017	25392	7577982724
186	13403	13403032001	265	2017	Calera de Tango	298439.8	2017	25392	7577982724
187	13403	13403032007	26	2017	Calera de Tango	298439.8	2017	25392	7577982724
188	13403	13403032016	56	2017	Calera de Tango	298439.8	2017	25392	7577982724
189	13403	13403042002	108	2017	Calera de Tango	298439.8	2017	25392	7577982724
190	13403	13403042005	193	2017	Calera de Tango	298439.8	2017	25392	7577982724
191	13403	13403042009	206	2017	Calera de Tango	298439.8	2017	25392	7577982724
192	13403	13403042010	48	2017	Calera de Tango	298439.8	2017	25392	7577982724
193	13403	13403042012	151	2017	Calera de Tango	298439.8	2017	25392	7577982724
194	13403	13403042015	79	2017	Calera de Tango	298439.8	2017	25392	7577982724
195	13403	13403052002	118	2017	Calera de Tango	298439.8	2017	25392	7577982724
196	13403	13403052010	47	2017	Calera de Tango	298439.8	2017	25392	7577982724
197	13403	13403052017	12	2017	Calera de Tango	298439.8	2017	25392	7577982724
198	13404	13404012032	246	2017	Paine	282280.9	2017	72759	20538478428
199	13404	13404022009	20	2017	Paine	282280.9	2017	72759	20538478428
200	13404	13404022010	26	2017	Paine	282280.9	2017	72759	20538478428
201	13404	13404022026	49	2017	Paine	282280.9	2017	72759	20538478428
202	13404	13404022032	129	2017	Paine	282280.9	2017	72759	20538478428
203	13404	13404022038	2	2017	Paine	282280.9	2017	72759	20538478428
204	13404	13404032025	509	2017	Paine	282280.9	2017	72759	20538478428
205	13404	13404042002	19	2017	Paine	282280.9	2017	72759	20538478428
206	13404	13404042007	2	2017	Paine	282280.9	2017	72759	20538478428
207	13404	13404042008	23	2017	Paine	282280.9	2017	72759	20538478428
208	13404	13404042018	7	2017	Paine	282280.9	2017	72759	20538478428
209	13404	13404042034	24	2017	Paine	282280.9	2017	72759	20538478428
210	13404	13404042036	238	2017	Paine	282280.9	2017	72759	20538478428
211	13404	13404052011	63	2017	Paine	282280.9	2017	72759	20538478428
212	13404	13404052012	28	2017	Paine	282280.9	2017	72759	20538478428
213	13404	13404052016	80	2017	Paine	282280.9	2017	72759	20538478428
214	13404	13404052019	107	2017	Paine	282280.9	2017	72759	20538478428
215	13404	13404062005	5	2017	Paine	282280.9	2017	72759	20538478428
216	13404	13404062014	2	2017	Paine	282280.9	2017	72759	20538478428
217	13404	13404062022	2	2017	Paine	282280.9	2017	72759	20538478428
218	13404	13404062028	243	2017	Paine	282280.9	2017	72759	20538478428
219	13404	13404062030	68	2017	Paine	282280.9	2017	72759	20538478428
220	13404	13404062032	13	2017	Paine	282280.9	2017	72759	20538478428
221	13404	13404062037	12	2017	Paine	282280.9	2017	72759	20538478428
222	13404	13404062039	64	2017	Paine	282280.9	2017	72759	20538478428
223	13404	13404072006	172	2017	Paine	282280.9	2017	72759	20538478428
224	13404	13404072021	99	2017	Paine	282280.9	2017	72759	20538478428
225	13404	13404072023	84	2017	Paine	282280.9	2017	72759	20538478428
226	13404	13404072031	31	2017	Paine	282280.9	2017	72759	20538478428
227	13404	13404082003	52	2017	Paine	282280.9	2017	72759	20538478428
228	13404	13404082004	217	2017	Paine	282280.9	2017	72759	20538478428
229	13404	13404082013	102	2017	Paine	282280.9	2017	72759	20538478428
230	13404	13404082017	11	2017	Paine	282280.9	2017	72759	20538478428
231	13404	13404082029	262	2017	Paine	282280.9	2017	72759	20538478428
232	13404	13404092001	65	2017	Paine	282280.9	2017	72759	20538478428
233	13404	13404092002	4	2017	Paine	282280.9	2017	72759	20538478428
234	13404	13404092018	6	2017	Paine	282280.9	2017	72759	20538478428
235	13404	13404092020	42	2017	Paine	282280.9	2017	72759	20538478428
236	13404	13404092024	82	2017	Paine	282280.9	2017	72759	20538478428
237	13404	13404092027	45	2017	Paine	282280.9	2017	72759	20538478428
238	13404	13404092033	27	2017	Paine	282280.9	2017	72759	20538478428
239	13404	13404092034	7	2017	Paine	282280.9	2017	72759	20538478428
240	13501	13501012021	10	2017	Melipilla	199121.9	2017	123627	24616837833
241	13501	13501012024	60	2017	Melipilla	199121.9	2017	123627	24616837833
242	13501	13501022010	115	2017	Melipilla	199121.9	2017	123627	24616837833
243	13501	13501022029	16	2017	Melipilla	199121.9	2017	123627	24616837833
244	13501	13501032003	120	2017	Melipilla	199121.9	2017	123627	24616837833
245	13501	13501032004	10	2017	Melipilla	199121.9	2017	123627	24616837833
246	13501	13501032006	91	2017	Melipilla	199121.9	2017	123627	24616837833
247	13501	13501032018	20	2017	Melipilla	199121.9	2017	123627	24616837833
248	13501	13501032019	17	2017	Melipilla	199121.9	2017	123627	24616837833
249	13501	13501032030	31	2017	Melipilla	199121.9	2017	123627	24616837833
250	13501	13501042007	37	2017	Melipilla	199121.9	2017	123627	24616837833
251	13501	13501042027	39	2017	Melipilla	199121.9	2017	123627	24616837833
252	13501	13501042030	13	2017	Melipilla	199121.9	2017	123627	24616837833
253	13501	13501042032	5	2017	Melipilla	199121.9	2017	123627	24616837833
254	13501	13501052020	12	2017	Melipilla	199121.9	2017	123627	24616837833
255	13501	13501052034	6	2017	Melipilla	199121.9	2017	123627	24616837833
256	13501	13501052048	21	2017	Melipilla	199121.9	2017	123627	24616837833
257	13501	13501062008	15	2017	Melipilla	199121.9	2017	123627	24616837833
258	13501	13501062022	64	2017	Melipilla	199121.9	2017	123627	24616837833
259	13501	13501062034	59	2017	Melipilla	199121.9	2017	123627	24616837833
260	13501	13501062036	1	2017	Melipilla	199121.9	2017	123627	24616837833
261	13501	13501072009	285	2017	Melipilla	199121.9	2017	123627	24616837833
262	13501	13501072028	4	2017	Melipilla	199121.9	2017	123627	24616837833
263	13501	13501072034	45	2017	Melipilla	199121.9	2017	123627	24616837833
264	13501	13501082015	5	2017	Melipilla	199121.9	2017	123627	24616837833
265	13501	13501082016	7	2017	Melipilla	199121.9	2017	123627	24616837833
266	13501	13501082017	46	2017	Melipilla	199121.9	2017	123627	24616837833
267	13501	13501082035	62	2017	Melipilla	199121.9	2017	123627	24616837833
268	13501	13501092002	37	2017	Melipilla	199121.9	2017	123627	24616837833
269	13501	13501092015	124	2017	Melipilla	199121.9	2017	123627	24616837833
270	13501	13501092023	73	2017	Melipilla	199121.9	2017	123627	24616837833
271	13501	13501092035	118	2017	Melipilla	199121.9	2017	123627	24616837833
272	13501	13501092037	107	2017	Melipilla	199121.9	2017	123627	24616837833
273	13501	13501092044	220	2017	Melipilla	199121.9	2017	123627	24616837833
274	13501	13501092049	22	2017	Melipilla	199121.9	2017	123627	24616837833
275	13501	13501092901	13	2017	Melipilla	199121.9	2017	123627	24616837833
276	13501	13501102001	1	2017	Melipilla	199121.9	2017	123627	24616837833
277	13501	13501102015	31	2017	Melipilla	199121.9	2017	123627	24616837833
278	13501	13501102023	8	2017	Melipilla	199121.9	2017	123627	24616837833
279	13501	13501102037	7	2017	Melipilla	199121.9	2017	123627	24616837833
280	13501	13501102040	197	2017	Melipilla	199121.9	2017	123627	24616837833
281	13501	13501102047	20	2017	Melipilla	199121.9	2017	123627	24616837833
282	13501	13501112043	46	2017	Melipilla	199121.9	2017	123627	24616837833
283	13501	13501112045	84	2017	Melipilla	199121.9	2017	123627	24616837833
284	13501	13501112046	21	2017	Melipilla	199121.9	2017	123627	24616837833
285	13501	13501122005	79	2017	Melipilla	199121.9	2017	123627	24616837833
286	13501	13501122011	13	2017	Melipilla	199121.9	2017	123627	24616837833
287	13501	13501122012	12	2017	Melipilla	199121.9	2017	123627	24616837833
288	13501	13501122014	66	2017	Melipilla	199121.9	2017	123627	24616837833
289	13501	13501122033	2	2017	Melipilla	199121.9	2017	123627	24616837833
290	13501	13501122901	19	2017	Melipilla	199121.9	2017	123627	24616837833
291	13501	13501132035	12	2017	Melipilla	199121.9	2017	123627	24616837833
292	13501	13501132039	11	2017	Melipilla	199121.9	2017	123627	24616837833
293	13501	13501152008	122	2017	Melipilla	199121.9	2017	123627	24616837833
294	13501	13501152009	14	2017	Melipilla	199121.9	2017	123627	24616837833
295	13501	13501152028	47	2017	Melipilla	199121.9	2017	123627	24616837833
296	13501	13501152041	246	2017	Melipilla	199121.9	2017	123627	24616837833
297	13501	13501162001	31	2017	Melipilla	199121.9	2017	123627	24616837833
298	13501	13501162025	19	2017	Melipilla	199121.9	2017	123627	24616837833
299	13501	13501162026	5	2017	Melipilla	199121.9	2017	123627	24616837833
300	13501	13501172031	33	2017	Melipilla	199121.9	2017	123627	24616837833
301	13501	13501172038	31	2017	Melipilla	199121.9	2017	123627	24616837833
302	13501	13501172042	25	2017	Melipilla	199121.9	2017	123627	24616837833
303	13501	13501172046	11	2017	Melipilla	199121.9	2017	123627	24616837833
304	13502	13502022004	43	2017	Alhué	242844.2	2017	6444	1564887792
305	13502	13502022901	10	2017	Alhué	242844.2	2017	6444	1564887792
306	13502	13502032002	52	2017	Alhué	242844.2	2017	6444	1564887792
307	13502	13502032006	10	2017	Alhué	242844.2	2017	6444	1564887792
308	13502	13502032008	16	2017	Alhué	242844.2	2017	6444	1564887792
309	13502	13502042003	29	2017	Alhué	242844.2	2017	6444	1564887792
310	13502	13502042901	3	2017	Alhué	242844.2	2017	6444	1564887792
311	13502	13502052007	3	2017	Alhué	242844.2	2017	6444	1564887792
312	13502	13502052901	2	2017	Alhué	242844.2	2017	6444	1564887792
313	13503	13503012006	2	2017	Curacaví	220990.2	2017	32579	7199638514
314	13503	13503012007	107	2017	Curacaví	220990.2	2017	32579	7199638514
315	13503	13503012014	18	2017	Curacaví	220990.2	2017	32579	7199638514
316	13503	13503022022	54	2017	Curacaví	220990.2	2017	32579	7199638514
317	13503	13503022024	266	2017	Curacaví	220990.2	2017	32579	7199638514
318	13503	13503022025	172	2017	Curacaví	220990.2	2017	32579	7199638514
319	13503	13503022901	28	2017	Curacaví	220990.2	2017	32579	7199638514
320	13503	13503032008	45	2017	Curacaví	220990.2	2017	32579	7199638514
321	13503	13503032019	35	2017	Curacaví	220990.2	2017	32579	7199638514
322	13503	13503032020	12	2017	Curacaví	220990.2	2017	32579	7199638514
323	13503	13503032028	143	2017	Curacaví	220990.2	2017	32579	7199638514
324	13503	13503042001	3	2017	Curacaví	220990.2	2017	32579	7199638514
325	13503	13503042010	8	2017	Curacaví	220990.2	2017	32579	7199638514
326	13503	13503042012	6	2017	Curacaví	220990.2	2017	32579	7199638514
327	13503	13503042013	325	2017	Curacaví	220990.2	2017	32579	7199638514
328	13503	13503042015	19	2017	Curacaví	220990.2	2017	32579	7199638514
329	13503	13503042026	20	2017	Curacaví	220990.2	2017	32579	7199638514
330	13503	13503042029	30	2017	Curacaví	220990.2	2017	32579	7199638514
331	13503	13503042030	39	2017	Curacaví	220990.2	2017	32579	7199638514
332	13503	13503052003	1	2017	Curacaví	220990.2	2017	32579	7199638514
333	13503	13503052011	8	2017	Curacaví	220990.2	2017	32579	7199638514
334	13503	13503052017	2	2017	Curacaví	220990.2	2017	32579	7199638514
335	13503	13503062002	6	2017	Curacaví	220990.2	2017	32579	7199638514
336	13503	13503062005	11	2017	Curacaví	220990.2	2017	32579	7199638514
337	13503	13503062016	10	2017	Curacaví	220990.2	2017	32579	7199638514
338	13503	13503062018	165	2017	Curacaví	220990.2	2017	32579	7199638514
339	13503	13503072004	47	2017	Curacaví	220990.2	2017	32579	7199638514
340	13503	13503072021	32	2017	Curacaví	220990.2	2017	32579	7199638514
341	13503	13503072024	31	2017	Curacaví	220990.2	2017	32579	7199638514
342	13503	13503072025	44	2017	Curacaví	220990.2	2017	32579	7199638514
343	13503	13503072027	24	2017	Curacaví	220990.2	2017	32579	7199638514
344	13503	13503082001	41	2017	Curacaví	220990.2	2017	32579	7199638514
345	13503	13503082017	13	2017	Curacaví	220990.2	2017	32579	7199638514
346	13503	13503082023	72	2017	Curacaví	220990.2	2017	32579	7199638514
347	13504	13504012001	70	2017	María Pinto	198063.3	2017	13590	2691680700
348	13504	13504012003	4	2017	María Pinto	198063.3	2017	13590	2691680700
349	13504	13504012004	7	2017	María Pinto	198063.3	2017	13590	2691680700
350	13504	13504012007	20	2017	María Pinto	198063.3	2017	13590	2691680700
351	13504	13504012011	3	2017	María Pinto	198063.3	2017	13590	2691680700
352	13504	13504012012	59	2017	María Pinto	198063.3	2017	13590	2691680700
353	13504	13504012015	45	2017	María Pinto	198063.3	2017	13590	2691680700
354	13504	13504012901	2	2017	María Pinto	198063.3	2017	13590	2691680700
355	13504	13504022004	55	2017	María Pinto	198063.3	2017	13590	2691680700
356	13504	13504022006	22	2017	María Pinto	198063.3	2017	13590	2691680700
357	13504	13504022010	20	2017	María Pinto	198063.3	2017	13590	2691680700
358	13504	13504022013	24	2017	María Pinto	198063.3	2017	13590	2691680700
359	13504	13504022014	16	2017	María Pinto	198063.3	2017	13590	2691680700
360	13504	13504022016	15	2017	María Pinto	198063.3	2017	13590	2691680700
361	13504	13504022017	11	2017	María Pinto	198063.3	2017	13590	2691680700
362	13504	13504022018	20	2017	María Pinto	198063.3	2017	13590	2691680700
363	13504	13504022019	85	2017	María Pinto	198063.3	2017	13590	2691680700
364	13504	13504022020	2	2017	María Pinto	198063.3	2017	13590	2691680700
365	13504	13504032003	45	2017	María Pinto	198063.3	2017	13590	2691680700
366	13504	13504042003	7	2017	María Pinto	198063.3	2017	13590	2691680700
367	13504	13504042008	4	2017	María Pinto	198063.3	2017	13590	2691680700
368	13504	13504042011	15	2017	María Pinto	198063.3	2017	13590	2691680700
369	13504	13504052005	24	2017	María Pinto	198063.3	2017	13590	2691680700
370	13504	13504052017	29	2017	María Pinto	198063.3	2017	13590	2691680700
371	13505	13505012003	11	2017	San Pedro	231429.7	2017	9726	2250885401
372	13505	13505012004	24	2017	San Pedro	231429.7	2017	9726	2250885401
373	13505	13505012011	1	2017	San Pedro	231429.7	2017	9726	2250885401
374	13505	13505012018	2	2017	San Pedro	231429.7	2017	9726	2250885401
375	13505	13505012019	7	2017	San Pedro	231429.7	2017	9726	2250885401
376	13505	13505012020	1	2017	San Pedro	231429.7	2017	9726	2250885401
377	13505	13505012021	11	2017	San Pedro	231429.7	2017	9726	2250885401
378	13505	13505012022	19	2017	San Pedro	231429.7	2017	9726	2250885401
379	13505	13505012023	27	2017	San Pedro	231429.7	2017	9726	2250885401
380	13505	13505012027	2	2017	San Pedro	231429.7	2017	9726	2250885401
381	13505	13505012031	5	2017	San Pedro	231429.7	2017	9726	2250885401
382	13505	13505012034	22	2017	San Pedro	231429.7	2017	9726	2250885401
383	13505	13505012035	9	2017	San Pedro	231429.7	2017	9726	2250885401
384	13505	13505012036	64	2017	San Pedro	231429.7	2017	9726	2250885401
385	13505	13505022011	10	2017	San Pedro	231429.7	2017	9726	2250885401
386	13505	13505022012	32	2017	San Pedro	231429.7	2017	9726	2250885401
387	13505	13505022016	9	2017	San Pedro	231429.7	2017	9726	2250885401
388	13505	13505022026	11	2017	San Pedro	231429.7	2017	9726	2250885401
389	13505	13505022027	4	2017	San Pedro	231429.7	2017	9726	2250885401
390	13505	13505022901	8	2017	San Pedro	231429.7	2017	9726	2250885401
391	13505	13505032002	3	2017	San Pedro	231429.7	2017	9726	2250885401
392	13505	13505032008	4	2017	San Pedro	231429.7	2017	9726	2250885401
393	13505	13505032032	1	2017	San Pedro	231429.7	2017	9726	2250885401
394	13505	13505032037	1	2017	San Pedro	231429.7	2017	9726	2250885401
395	13505	13505032038	2	2017	San Pedro	231429.7	2017	9726	2250885401
396	13505	13505032040	12	2017	San Pedro	231429.7	2017	9726	2250885401
397	13505	13505032901	3	2017	San Pedro	231429.7	2017	9726	2250885401
398	13505	13505042001	5	2017	San Pedro	231429.7	2017	9726	2250885401
399	13505	13505042012	1	2017	San Pedro	231429.7	2017	9726	2250885401
400	13505	13505042015	5	2017	San Pedro	231429.7	2017	9726	2250885401
401	13505	13505042024	10	2017	San Pedro	231429.7	2017	9726	2250885401
402	13505	13505042025	28	2017	San Pedro	231429.7	2017	9726	2250885401
403	13505	13505052006	9	2017	San Pedro	231429.7	2017	9726	2250885401
404	13505	13505052014	33	2017	San Pedro	231429.7	2017	9726	2250885401
405	13505	13505062007	7	2017	San Pedro	231429.7	2017	9726	2250885401
406	13505	13505062009	20	2017	San Pedro	231429.7	2017	9726	2250885401
407	13505	13505062010	11	2017	San Pedro	231429.7	2017	9726	2250885401
408	13505	13505062012	12	2017	San Pedro	231429.7	2017	9726	2250885401
409	13505	13505062013	3	2017	San Pedro	231429.7	2017	9726	2250885401
410	13505	13505062015	1	2017	San Pedro	231429.7	2017	9726	2250885401
411	13505	13505062024	7	2017	San Pedro	231429.7	2017	9726	2250885401
412	13505	13505062028	12	2017	San Pedro	231429.7	2017	9726	2250885401
413	13505	13505062029	5	2017	San Pedro	231429.7	2017	9726	2250885401
414	13505	13505062030	2	2017	San Pedro	231429.7	2017	9726	2250885401
415	13505	13505992999	5	2017	San Pedro	231429.7	2017	9726	2250885401
416	13601	13601012006	12	2017	Talagante	230734.4	2017	74237	17129031774
417	13601	13601012014	143	2017	Talagante	230734.4	2017	74237	17129031774
418	13601	13601012017	578	2017	Talagante	230734.4	2017	74237	17129031774
419	13601	13601022005	127	2017	Talagante	230734.4	2017	74237	17129031774
420	13601	13601022006	547	2017	Talagante	230734.4	2017	74237	17129031774
421	13601	13601022008	453	2017	Talagante	230734.4	2017	74237	17129031774
422	13601	13601022009	149	2017	Talagante	230734.4	2017	74237	17129031774
423	13601	13601022013	66	2017	Talagante	230734.4	2017	74237	17129031774
424	13601	13601022019	179	2017	Talagante	230734.4	2017	74237	17129031774
425	13601	13601032001	24	2017	Talagante	230734.4	2017	74237	17129031774
426	13601	13601032003	334	2017	Talagante	230734.4	2017	74237	17129031774
427	13601	13601032004	38	2017	Talagante	230734.4	2017	74237	17129031774
428	13601	13601032006	54	2017	Talagante	230734.4	2017	74237	17129031774
429	13601	13601032010	31	2017	Talagante	230734.4	2017	74237	17129031774
430	13601	13601032016	166	2017	Talagante	230734.4	2017	74237	17129031774
431	13601	13601032017	14	2017	Talagante	230734.4	2017	74237	17129031774
432	13601	13601042001	37	2017	Talagante	230734.4	2017	74237	17129031774
433	13601	13601042002	104	2017	Talagante	230734.4	2017	74237	17129031774
434	13601	13601042004	27	2017	Talagante	230734.4	2017	74237	17129031774
435	13601	13601042007	57	2017	Talagante	230734.4	2017	74237	17129031774
436	13601	13601042011	13	2017	Talagante	230734.4	2017	74237	17129031774
437	13601	13601042012	146	2017	Talagante	230734.4	2017	74237	17129031774
438	13601	13601042015	219	2017	Talagante	230734.4	2017	74237	17129031774
439	13601	13601042018	48	2017	Talagante	230734.4	2017	74237	17129031774
440	13601	13601042021	11	2017	Talagante	230734.4	2017	74237	17129031774
441	13602	13602012002	211	2017	El Monte	201444.7	2017	35923	7236496479
442	13602	13602012901	11	2017	El Monte	201444.7	2017	35923	7236496479
443	13602	13602022001	66	2017	El Monte	201444.7	2017	35923	7236496479
444	13602	13602022003	63	2017	El Monte	201444.7	2017	35923	7236496479
445	13602	13602032001	117	2017	El Monte	201444.7	2017	35923	7236496479
446	13602	13602032004	102	2017	El Monte	201444.7	2017	35923	7236496479
447	13603	13603012001	457	2017	Isla de Maipo	232595.7	2017	36219	8424384020
448	13603	13603012003	89	2017	Isla de Maipo	232595.7	2017	36219	8424384020
449	13603	13603012004	4	2017	Isla de Maipo	232595.7	2017	36219	8424384020
450	13603	13603012007	44	2017	Isla de Maipo	232595.7	2017	36219	8424384020
451	13603	13603012009	2	2017	Isla de Maipo	232595.7	2017	36219	8424384020
452	13603	13603022003	265	2017	Isla de Maipo	232595.7	2017	36219	8424384020
453	13603	13603022004	13	2017	Isla de Maipo	232595.7	2017	36219	8424384020
454	13603	13603022005	108	2017	Isla de Maipo	232595.7	2017	36219	8424384020
455	13603	13603022006	99	2017	Isla de Maipo	232595.7	2017	36219	8424384020
456	13603	13603022009	8	2017	Isla de Maipo	232595.7	2017	36219	8424384020
457	13603	13603032002	1	2017	Isla de Maipo	232595.7	2017	36219	8424384020
458	13603	13603042008	217	2017	Isla de Maipo	232595.7	2017	36219	8424384020
459	13603	13603052010	25	2017	Isla de Maipo	232595.7	2017	36219	8424384020
460	13604	13604012002	72	2017	Padre Hurtado	231845.6	2017	63250	14664233522
461	13604	13604012004	51	2017	Padre Hurtado	231845.6	2017	63250	14664233522
462	13604	13604012009	13	2017	Padre Hurtado	231845.6	2017	63250	14664233522
463	13604	13604012011	205	2017	Padre Hurtado	231845.6	2017	63250	14664233522
464	13604	13604022003	37	2017	Padre Hurtado	231845.6	2017	63250	14664233522
465	13604	13604022006	33	2017	Padre Hurtado	231845.6	2017	63250	14664233522
466	13604	13604022008	23	2017	Padre Hurtado	231845.6	2017	63250	14664233522
467	13604	13604022010	39	2017	Padre Hurtado	231845.6	2017	63250	14664233522
468	13604	13604022012	28	2017	Padre Hurtado	231845.6	2017	63250	14664233522
469	13604	13604022014	181	2017	Padre Hurtado	231845.6	2017	63250	14664233522
470	13604	13604032011	5	2017	Padre Hurtado	231845.6	2017	63250	14664233522
471	13604	13604042001	283	2017	Padre Hurtado	231845.6	2017	63250	14664233522
472	13604	13604052005	7	2017	Padre Hurtado	231845.6	2017	63250	14664233522
473	13604	13604052006	21	2017	Padre Hurtado	231845.6	2017	63250	14664233522
474	13604	13604052007	28	2017	Padre Hurtado	231845.6	2017	63250	14664233522
475	13604	13604052013	38	2017	Padre Hurtado	231845.6	2017	63250	14664233522
476	13604	13604052014	19	2017	Padre Hurtado	231845.6	2017	63250	14664233522
477	13605	13605012001	87	2017	Peñaflor	249848.3	2017	90201	22536570306
478	13605	13605012002	313	2017	Peñaflor	249848.3	2017	90201	22536570306
479	13605	13605012006	21	2017	Peñaflor	249848.3	2017	90201	22536570306
480	13605	13605012007	155	2017	Peñaflor	249848.3	2017	90201	22536570306
481	13605	13605012009	521	2017	Peñaflor	249848.3	2017	90201	22536570306
482	13605	13605022006	380	2017	Peñaflor	249848.3	2017	90201	22536570306
483	13605	13605022901	7	2017	Peñaflor	249848.3	2017	90201	22536570306
484	13605	13605032004	101	2017	Peñaflor	249848.3	2017	90201	22536570306
485	13605	13605032006	72	2017	Peñaflor	249848.3	2017	90201	22536570306
486	13605	13605032008	28	2017	Peñaflor	249848.3	2017	90201	22536570306

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
29	13202	13202012001	478	2017	Pirque	274675.6	2017	26521	7284672878
30	13202	13202012002	272	2017	Pirque	274675.6	2017	26521	7284672878
31	13202	13202012005	168	2017	Pirque	274675.6	2017	26521	7284672878
32	13202	13202012009	170	2017	Pirque	274675.6	2017	26521	7284672878
33	13202	13202022004	94	2017	Pirque	274675.6	2017	26521	7284672878
34	13202	13202022006	82	2017	Pirque	274675.6	2017	26521	7284672878
35	13202	13202022007	57	2017	Pirque	274675.6	2017	26521	7284672878
36	13202	13202022010	101	2017	Pirque	274675.6	2017	26521	7284672878
37	13202	13202022011	16	2017	Pirque	274675.6	2017	26521	7284672878
38	13202	13202022012	197	2017	Pirque	274675.6	2017	26521	7284672878
39	13202	13202022014	353	2017	Pirque	274675.6	2017	26521	7284672878
40	13202	13202032003	472	2017	Pirque	274675.6	2017	26521	7284672878
41	13202	13202032008	441	2017	Pirque	274675.6	2017	26521	7284672878
42	13202	13202032013	338	2017	Pirque	274675.6	2017	26521	7284672878
43	13203	13203012004	53	2017	San José de Maipo	344876.8	2017	18189	6272964115
44	13203	13203012005	102	2017	San José de Maipo	344876.8	2017	18189	6272964115
45	13203	13203012012	6	2017	San José de Maipo	344876.8	2017	18189	6272964115
46	13203	13203012019	56	2017	San José de Maipo	344876.8	2017	18189	6272964115
47	13203	13203012901	1	2017	San José de Maipo	344876.8	2017	18189	6272964115
48	13203	13203022002	7	2017	San José de Maipo	344876.8	2017	18189	6272964115
49	13203	13203022004	4	2017	San José de Maipo	344876.8	2017	18189	6272964115
50	13203	13203022015	101	2017	San José de Maipo	344876.8	2017	18189	6272964115
51	13203	13203032017	10	2017	San José de Maipo	344876.8	2017	18189	6272964115
52	13203	13203032018	104	2017	San José de Maipo	344876.8	2017	18189	6272964115
53	13203	13203042001	4	2017	San José de Maipo	344876.8	2017	18189	6272964115
54	13203	13203042008	8	2017	San José de Maipo	344876.8	2017	18189	6272964115
55	13203	13203042010	43	2017	San José de Maipo	344876.8	2017	18189	6272964115
56	13203	13203042013	2	2017	San José de Maipo	344876.8	2017	18189	6272964115
57	13203	13203042014	1	2017	San José de Maipo	344876.8	2017	18189	6272964115
58	13203	13203042901	12	2017	San José de Maipo	344876.8	2017	18189	6272964115
59	13203	13203052006	66	2017	San José de Maipo	344876.8	2017	18189	6272964115
60	13203	13203052009	16	2017	San José de Maipo	344876.8	2017	18189	6272964115
61	13203	13203052017	7	2017	San José de Maipo	344876.8	2017	18189	6272964115
62	13203	13203062003	83	2017	San José de Maipo	344876.8	2017	18189	6272964115
63	13203	13203062007	447	2017	San José de Maipo	344876.8	2017	18189	6272964115
64	13301	13301012005	207	2017	Colina	255373.7	2017	146207	37337421744
65	13301	13301012010	4	2017	Colina	255373.7	2017	146207	37337421744
66	13301	13301012012	517	2017	Colina	255373.7	2017	146207	37337421744
67	13301	13301012015	98	2017	Colina	255373.7	2017	146207	37337421744
68	13301	13301012018	281	2017	Colina	255373.7	2017	146207	37337421744
69	13301	13301012025	46	2017	Colina	255373.7	2017	146207	37337421744
70	13301	13301012026	47	2017	Colina	255373.7	2017	146207	37337421744
71	13301	13301012029	16	2017	Colina	255373.7	2017	146207	37337421744
72	13301	13301022004	1706	2017	Colina	255373.7	2017	146207	37337421744
73	13301	13301022006	341	2017	Colina	255373.7	2017	146207	37337421744
74	13301	13301022008	77	2017	Colina	255373.7	2017	146207	37337421744
75	13301	13301032001	16	2017	Colina	255373.7	2017	146207	37337421744
76	13301	13301032007	637	2017	Colina	255373.7	2017	146207	37337421744
77	13301	13301032013	82	2017	Colina	255373.7	2017	146207	37337421744
78	13301	13301032014	40	2017	Colina	255373.7	2017	146207	37337421744
79	13301	13301032018	291	2017	Colina	255373.7	2017	146207	37337421744
80	13301	13301032019	14	2017	Colina	255373.7	2017	146207	37337421744
81	13301	13301032020	283	2017	Colina	255373.7	2017	146207	37337421744
82	13301	13301032022	96	2017	Colina	255373.7	2017	146207	37337421744
83	13301	13301032024	859	2017	Colina	255373.7	2017	146207	37337421744
84	13301	13301032028	296	2017	Colina	255373.7	2017	146207	37337421744
85	13301	13301042021	25	2017	Colina	255373.7	2017	146207	37337421744
86	13301	13301052002	137	2017	Colina	255373.7	2017	146207	37337421744
87	13301	13301052009	18	2017	Colina	255373.7	2017	146207	37337421744
88	13301	13301052023	53	2017	Colina	255373.7	2017	146207	37337421744
89	13301	13301052901	2	2017	Colina	255373.7	2017	146207	37337421744
90	13301	13301062004	496	2017	Colina	255373.7	2017	146207	37337421744
91	13301	13301062005	44	2017	Colina	255373.7	2017	146207	37337421744
92	13301	13301062016	400	2017	Colina	255373.7	2017	146207	37337421744
93	13301	13301062027	72	2017	Colina	255373.7	2017	146207	37337421744
94	13302	13302012003	102	2017	Lampa	243425.7	2017	102034	24837699582
95	13302	13302012006	26	2017	Lampa	243425.7	2017	102034	24837699582
96	13302	13302012009	77	2017	Lampa	243425.7	2017	102034	24837699582
97	13302	13302012014	37	2017	Lampa	243425.7	2017	102034	24837699582
98	13302	13302012016	4	2017	Lampa	243425.7	2017	102034	24837699582
99	13302	13302012017	15	2017	Lampa	243425.7	2017	102034	24837699582
100	13302	13302012018	7	2017	Lampa	243425.7	2017	102034	24837699582
101	13302	13302012019	43	2017	Lampa	243425.7	2017	102034	24837699582
102	13302	13302012020	32	2017	Lampa	243425.7	2017	102034	24837699582
103	13302	13302012021	9	2017	Lampa	243425.7	2017	102034	24837699582
104	13302	13302012028	48	2017	Lampa	243425.7	2017	102034	24837699582
105	13302	13302012901	1	2017	Lampa	243425.7	2017	102034	24837699582
106	13302	13302022002	11	2017	Lampa	243425.7	2017	102034	24837699582
107	13302	13302022005	62	2017	Lampa	243425.7	2017	102034	24837699582
108	13302	13302022007	2	2017	Lampa	243425.7	2017	102034	24837699582
109	13302	13302022017	145	2017	Lampa	243425.7	2017	102034	24837699582
110	13302	13302032001	231	2017	Lampa	243425.7	2017	102034	24837699582
111	13302	13302032010	45	2017	Lampa	243425.7	2017	102034	24837699582
112	13302	13302032015	3	2017	Lampa	243425.7	2017	102034	24837699582
113	13302	13302032019	3	2017	Lampa	243425.7	2017	102034	24837699582
114	13302	13302032022	42	2017	Lampa	243425.7	2017	102034	24837699582
115	13302	13302032025	454	2017	Lampa	243425.7	2017	102034	24837699582
116	13302	13302032026	906	2017	Lampa	243425.7	2017	102034	24837699582
117	13302	13302032027	536	2017	Lampa	243425.7	2017	102034	24837699582
118	13302	13302042008	77	2017	Lampa	243425.7	2017	102034	24837699582
119	13302	13302042010	4	2017	Lampa	243425.7	2017	102034	24837699582
120	13302	13302042012	12	2017	Lampa	243425.7	2017	102034	24837699582
121	13302	13302042901	4	2017	Lampa	243425.7	2017	102034	24837699582
122	13302	13302052004	17	2017	Lampa	243425.7	2017	102034	24837699582
123	13302	13302052011	6	2017	Lampa	243425.7	2017	102034	24837699582
124	13302	13302052014	180	2017	Lampa	243425.7	2017	102034	24837699582
125	13302	13302052023	17	2017	Lampa	243425.7	2017	102034	24837699582
126	13303	13303012003	11	2017	Tiltil	264794.8	2017	19312	5113717064
127	13303	13303012012	39	2017	Tiltil	264794.8	2017	19312	5113717064
128	13303	13303022006	12	2017	Tiltil	264794.8	2017	19312	5113717064

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
13202012001	13202	478	2017	Pirque	274675.6	2017	26521	7284672878	1610	0.0607066	13202
13202012002	13202	272	2017	Pirque	274675.6	2017	26521	7284672878	1485	0.0559934	13202
13202012005	13202	168	2017	Pirque	274675.6	2017	26521	7284672878	1482	0.0558802	13202
13202012009	13202	170	2017	Pirque	274675.6	2017	26521	7284672878	954	0.0359715	13202
13202022004	13202	94	2017	Pirque	274675.6	2017	26521	7284672878	343	0.0129331	13202
13202022006	13202	82	2017	Pirque	274675.6	2017	26521	7284672878	234	0.0088232	13202
13202022007	13202	57	2017	Pirque	274675.6	2017	26521	7284672878	168	0.0063346	13202
13202022010	13202	101	2017	Pirque	274675.6	2017	26521	7284672878	308	0.0116134	13202
13202022011	13202	16	2017	Pirque	274675.6	2017	26521	7284672878	58	0.0021869	13202
13202022012	13202	197	2017	Pirque	274675.6	2017	26521	7284672878	744	0.0280532	13202
13202022014	13202	353	2017	Pirque	274675.6	2017	26521	7284672878	1477	0.0556917	13202
13202032003	13202	472	2017	Pirque	274675.6	2017	26521	7284672878	1944	0.0733004	13202
13202032008	13202	441	2017	Pirque	274675.6	2017	26521	7284672878	2296	0.0865729	13202
13202032013	13202	338	2017	Pirque	274675.6	2017	26521	7284672878	1748	0.0659100	13202
13203012004	13203	53	2017	San José de Maipo	344876.8	2017	18189	6272964115	151	0.0083017	13203
13203012005	13203	102	2017	San José de Maipo	344876.8	2017	18189	6272964115	618	0.0339766	13203
13203012012	13203	6	2017	San José de Maipo	344876.8	2017	18189	6272964115	66	0.0036286	13203
13203012019	13203	56	2017	San José de Maipo	344876.8	2017	18189	6272964115	537	0.0295233	13203
13203012901	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	10	0.0005498	13203
13203022002	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	313	0.0172082	13203
13203022004	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	23	0.0012645	13203
13203022015	13203	101	2017	San José de Maipo	344876.8	2017	18189	6272964115	808	0.0444225	13203
13203032017	13203	10	2017	San José de Maipo	344876.8	2017	18189	6272964115	35	0.0019242	13203
13203032018	13203	104	2017	San José de Maipo	344876.8	2017	18189	6272964115	1186	0.0652042	13203
13203042001	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	40	0.0021991	13203
13203042008	13203	8	2017	San José de Maipo	344876.8	2017	18189	6272964115	62	0.0034087	13203
13203042010	13203	43	2017	San José de Maipo	344876.8	2017	18189	6272964115	358	0.0196822	13203
13203042013	13203	2	2017	San José de Maipo	344876.8	2017	18189	6272964115	39	0.0021442	13203
13203042014	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	17	0.0009346	13203
13203042901	13203	12	2017	San José de Maipo	344876.8	2017	18189	6272964115	42	0.0023091	13203
13203052006	13203	66	2017	San José de Maipo	344876.8	2017	18189	6272964115	256	0.0140744	13203
13203052009	13203	16	2017	San José de Maipo	344876.8	2017	18189	6272964115	218	0.0119853	13203
13203052017	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	32	0.0017593	13203
13203062003	13203	83	2017	San José de Maipo	344876.8	2017	18189	6272964115	306	0.0168234	13203
13203062007	13203	447	2017	San José de Maipo	344876.8	2017	18189	6272964115	1864	0.1024795	13203
13301012005	13301	207	2017	Colina	255373.7	2017	146207	37337421744	1304	0.0089189	13301
13301012010	13301	4	2017	Colina	255373.7	2017	146207	37337421744	121	0.0008276	13301
13301012012	13301	517	2017	Colina	255373.7	2017	146207	37337421744	1844	0.0126123	13301
13301012015	13301	98	2017	Colina	255373.7	2017	146207	37337421744	620	0.0042406	13301
13301012018	13301	281	2017	Colina	255373.7	2017	146207	37337421744	776	0.0053075	13301
13301012025	13301	46	2017	Colina	255373.7	2017	146207	37337421744	259	0.0017715	13301
13301012026	13301	47	2017	Colina	255373.7	2017	146207	37337421744	205	0.0014021	13301
13301012029	13301	16	2017	Colina	255373.7	2017	146207	37337421744	304	0.0020792	13301
13301022004	13301	1706	2017	Colina	255373.7	2017	146207	37337421744	5042	0.0344854	13301
13301022006	13301	341	2017	Colina	255373.7	2017	146207	37337421744	1010	0.0069080	13301
13301022008	13301	77	2017	Colina	255373.7	2017	146207	37337421744	185	0.0012653	13301
13301032001	13301	16	2017	Colina	255373.7	2017	146207	37337421744	727	0.0049724	13301
13301032007	13301	637	2017	Colina	255373.7	2017	146207	37337421744	2002	0.0136929	13301
13301032013	13301	82	2017	Colina	255373.7	2017	146207	37337421744	303	0.0020724	13301
13301032014	13301	40	2017	Colina	255373.7	2017	146207	37337421744	99	0.0006771	13301
13301032018	13301	291	2017	Colina	255373.7	2017	146207	37337421744	802	0.0054854	13301
13301032019	13301	14	2017	Colina	255373.7	2017	146207	37337421744	50	0.0003420	13301
13301032020	13301	283	2017	Colina	255373.7	2017	146207	37337421744	1068	0.0073047	13301
13301032022	13301	96	2017	Colina	255373.7	2017	146207	37337421744	321	0.0021955	13301
13301032024	13301	859	2017	Colina	255373.7	2017	146207	37337421744	4204	0.0287538	13301
13301032028	13301	296	2017	Colina	255373.7	2017	146207	37337421744	896	0.0061283	13301
13301042021	13301	25	2017	Colina	255373.7	2017	146207	37337421744	364	0.0024896	13301
13301052002	13301	137	2017	Colina	255373.7	2017	146207	37337421744	1273	0.0087068	13301
13301052009	13301	18	2017	Colina	255373.7	2017	146207	37337421744	155	0.0010601	13301
13301052023	13301	53	2017	Colina	255373.7	2017	146207	37337421744	967	0.0066139	13301
13301052901	13301	2	2017	Colina	255373.7	2017	146207	37337421744	22	0.0001505	13301
13301062004	13301	496	2017	Colina	255373.7	2017	146207	37337421744	1532	0.0104783	13301
13301062005	13301	44	2017	Colina	255373.7	2017	146207	37337421744	172	0.0011764	13301
13301062016	13301	400	2017	Colina	255373.7	2017	146207	37337421744	1331	0.0091035	13301
13301062027	13301	72	2017	Colina	255373.7	2017	146207	37337421744	231	0.0015800	13301
13302012003	13302	102	2017	Lampa	243425.7	2017	102034	24837699582	808	0.0079189	13302
13302012006	13302	26	2017	Lampa	243425.7	2017	102034	24837699582	355	0.0034792	13302
13302012009	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	968	0.0094870	13302
13302012014	13302	37	2017	Lampa	243425.7	2017	102034	24837699582	200	0.0019601	13302
13302012016	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	18	0.0001764	13302
13302012017	13302	15	2017	Lampa	243425.7	2017	102034	24837699582	344	0.0033714	13302
13302012018	13302	7	2017	Lampa	243425.7	2017	102034	24837699582	118	0.0011565	13302
13302012019	13302	43	2017	Lampa	243425.7	2017	102034	24837699582	500	0.0049003	13302
13302012020	13302	32	2017	Lampa	243425.7	2017	102034	24837699582	532	0.0052139	13302
13302012021	13302	9	2017	Lampa	243425.7	2017	102034	24837699582	206	0.0020189	13302
13302012028	13302	48	2017	Lampa	243425.7	2017	102034	24837699582	437	0.0042829	13302
13302012901	13302	1	2017	Lampa	243425.7	2017	102034	24837699582	14	0.0001372	13302
13302022002	13302	11	2017	Lampa	243425.7	2017	102034	24837699582	255	0.0024992	13302
13302022005	13302	62	2017	Lampa	243425.7	2017	102034	24837699582	1376	0.0134857	13302
13302022007	13302	2	2017	Lampa	243425.7	2017	102034	24837699582	243	0.0023816	13302
13302022017	13302	145	2017	Lampa	243425.7	2017	102034	24837699582	1012	0.0099183	13302
13302032001	13302	231	2017	Lampa	243425.7	2017	102034	24837699582	1258	0.0123292	13302
13302032010	13302	45	2017	Lampa	243425.7	2017	102034	24837699582	234	0.0022934	13302
13302032015	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	148	0.0014505	13302
13302032019	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	47	0.0004606	13302
13302032022	13302	42	2017	Lampa	243425.7	2017	102034	24837699582	215	0.0021071	13302
13302032025	13302	454	2017	Lampa	243425.7	2017	102034	24837699582	2238	0.0219339	13302
13302032026	13302	906	2017	Lampa	243425.7	2017	102034	24837699582	3031	0.0297058	13302
13302032027	13302	536	2017	Lampa	243425.7	2017	102034	24837699582	2777	0.0272164	13302
13302042008	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	807	0.0079091	13302
13302042010	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	100	0.0009801	13302
13302042012	13302	12	2017	Lampa	243425.7	2017	102034	24837699582	468	0.0045867	13302
13302042901	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	19	0.0001862	13302
13302052004	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	358	0.0035086	13302
13302052011	13302	6	2017	Lampa	243425.7	2017	102034	24837699582	158	0.0015485	13302
13302052014	13302	180	2017	Lampa	243425.7	2017	102034	24837699582	1137	0.0111433	13302
13302052023	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	842	0.0082522	13302
13303012003	13303	11	2017	Tiltil	264794.8	2017	19312	5113717064	59	0.0030551	13303
13303012012	13303	39	2017	Tiltil	264794.8	2017	19312	5113717064	705	0.0365058	13303
13303022006	13303	12	2017	Tiltil	264794.8	2017	19312	5113717064	379	0.0196251	13303

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
13202012001	13202	478	2017	Pirque	274675.6	2017	26521	7284672878	1610	0.0607066	13202	442227794
13202012002	13202	272	2017	Pirque	274675.6	2017	26521	7284672878	1485	0.0559934	13202	407893338
13202012005	13202	168	2017	Pirque	274675.6	2017	26521	7284672878	1482	0.0558802	13202	407069311
13202012009	13202	170	2017	Pirque	274675.6	2017	26521	7284672878	954	0.0359715	13202	262040569
13202022004	13202	94	2017	Pirque	274675.6	2017	26521	7284672878	343	0.0129331	13202	94213747
13202022006	13202	82	2017	Pirque	274675.6	2017	26521	7284672878	234	0.0088232	13202	64274102
13202022007	13202	57	2017	Pirque	274675.6	2017	26521	7284672878	168	0.0063346	13202	46145509
13202022010	13202	101	2017	Pirque	274675.6	2017	26521	7284672878	308	0.0116134	13202	84600100
13202022011	13202	16	2017	Pirque	274675.6	2017	26521	7284672878	58	0.0021869	13202	15931188
13202022012	13202	197	2017	Pirque	274675.6	2017	26521	7284672878	744	0.0280532	13202	204358683
13202022014	13202	353	2017	Pirque	274675.6	2017	26521	7284672878	1477	0.0556917	13202	405695933
13202032003	13202	472	2017	Pirque	274675.6	2017	26521	7284672878	1944	0.0733004	13202	533969461
13202032008	13202	441	2017	Pirque	274675.6	2017	26521	7284672878	2296	0.0865729	13202	630655289
13202032013	13202	338	2017	Pirque	274675.6	2017	26521	7284672878	1748	0.0659100	13202	480133034
13203012004	13203	53	2017	San José de Maipo	344876.8	2017	18189	6272964115	151	0.0083017	13203	52076397
13203012005	13203	102	2017	San José de Maipo	344876.8	2017	18189	6272964115	618	0.0339766	13203	213133862
13203012012	13203	6	2017	San José de Maipo	344876.8	2017	18189	6272964115	66	0.0036286	13203	22761869
13203012019	13203	56	2017	San José de Maipo	344876.8	2017	18189	6272964115	537	0.0295233	13203	185198842
13203012901	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	10	0.0005498	13203	3448768
13203022002	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	313	0.0172082	13203	107946438
13203022004	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	23	0.0012645	13203	7932166
13203022015	13203	101	2017	San José de Maipo	344876.8	2017	18189	6272964115	808	0.0444225	13203	278660454
13203032017	13203	10	2017	San José de Maipo	344876.8	2017	18189	6272964115	35	0.0019242	13203	12070688
13203032018	13203	104	2017	San José de Maipo	344876.8	2017	18189	6272964115	1186	0.0652042	13203	409023885
13203042001	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	40	0.0021991	13203	13795072
13203042008	13203	8	2017	San José de Maipo	344876.8	2017	18189	6272964115	62	0.0034087	13203	21382362
13203042010	13203	43	2017	San José de Maipo	344876.8	2017	18189	6272964115	358	0.0196822	13203	123465894
13203042013	13203	2	2017	San José de Maipo	344876.8	2017	18189	6272964115	39	0.0021442	13203	13450195
13203042014	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	17	0.0009346	13203	5862906
13203042901	13203	12	2017	San José de Maipo	344876.8	2017	18189	6272964115	42	0.0023091	13203	14484826
13203052006	13203	66	2017	San José de Maipo	344876.8	2017	18189	6272964115	256	0.0140744	13203	88288461
13203052009	13203	16	2017	San José de Maipo	344876.8	2017	18189	6272964115	218	0.0119853	13203	75183142
13203052017	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	32	0.0017593	13203	11036058
13203062003	13203	83	2017	San José de Maipo	344876.8	2017	18189	6272964115	306	0.0168234	13203	105532301
13203062007	13203	447	2017	San José de Maipo	344876.8	2017	18189	6272964115	1864	0.1024795	13203	642850355
13301012005	13301	207	2017	Colina	255373.7	2017	146207	37337421744	1304	0.0089189	13301	333007298
13301012010	13301	4	2017	Colina	255373.7	2017	146207	37337421744	121	0.0008276	13301	30900217
13301012012	13301	517	2017	Colina	255373.7	2017	146207	37337421744	1844	0.0126123	13301	470909093
13301012015	13301	98	2017	Colina	255373.7	2017	146207	37337421744	620	0.0042406	13301	158331691
13301012018	13301	281	2017	Colina	255373.7	2017	146207	37337421744	776	0.0053075	13301	198169987
13301012025	13301	46	2017	Colina	255373.7	2017	146207	37337421744	259	0.0017715	13301	66141787
13301012026	13301	47	2017	Colina	255373.7	2017	146207	37337421744	205	0.0014021	13301	52351607
13301012029	13301	16	2017	Colina	255373.7	2017	146207	37337421744	304	0.0020792	13301	77633603
13301022004	13301	1706	2017	Colina	255373.7	2017	146207	37337421744	5042	0.0344854	13301	1287594167
13301022006	13301	341	2017	Colina	255373.7	2017	146207	37337421744	1010	0.0069080	13301	257927431
13301022008	13301	77	2017	Colina	255373.7	2017	146207	37337421744	185	0.0012653	13301	47244133
13301032001	13301	16	2017	Colina	255373.7	2017	146207	37337421744	727	0.0049724	13301	185656676
13301032007	13301	637	2017	Colina	255373.7	2017	146207	37337421744	2002	0.0136929	13301	511258136
13301032013	13301	82	2017	Colina	255373.7	2017	146207	37337421744	303	0.0020724	13301	77378229
13301032014	13301	40	2017	Colina	255373.7	2017	146207	37337421744	99	0.0006771	13301	25281996
13301032018	13301	291	2017	Colina	255373.7	2017	146207	37337421744	802	0.0054854	13301	204809703
13301032019	13301	14	2017	Colina	255373.7	2017	146207	37337421744	50	0.0003420	13301	12768685
13301032020	13301	283	2017	Colina	255373.7	2017	146207	37337421744	1068	0.0073047	13301	272739106
13301032022	13301	96	2017	Colina	255373.7	2017	146207	37337421744	321	0.0021955	13301	81974956
13301032024	13301	859	2017	Colina	255373.7	2017	146207	37337421744	4204	0.0287538	13301	1073591011
13301032028	13301	296	2017	Colina	255373.7	2017	146207	37337421744	896	0.0061283	13301	228814830
13301042021	13301	25	2017	Colina	255373.7	2017	146207	37337421744	364	0.0024896	13301	92956025
13301052002	13301	137	2017	Colina	255373.7	2017	146207	37337421744	1273	0.0087068	13301	325090713
13301052009	13301	18	2017	Colina	255373.7	2017	146207	37337421744	155	0.0010601	13301	39582923
13301052023	13301	53	2017	Colina	255373.7	2017	146207	37337421744	967	0.0066139	13301	246946363
13301052901	13301	2	2017	Colina	255373.7	2017	146207	37337421744	22	0.0001505	13301	5618221
13301062004	13301	496	2017	Colina	255373.7	2017	146207	37337421744	1532	0.0104783	13301	391232500
13301062005	13301	44	2017	Colina	255373.7	2017	146207	37337421744	172	0.0011764	13301	43924275
13301062016	13301	400	2017	Colina	255373.7	2017	146207	37337421744	1331	0.0091035	13301	339902387
13301062027	13301	72	2017	Colina	255373.7	2017	146207	37337421744	231	0.0015800	13301	58991323
13302012003	13302	102	2017	Lampa	243425.7	2017	102034	24837699582	808	0.0079189	13302	196687979
13302012006	13302	26	2017	Lampa	243425.7	2017	102034	24837699582	355	0.0034792	13302	86416129
13302012009	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	968	0.0094870	13302	235636094
13302012014	13302	37	2017	Lampa	243425.7	2017	102034	24837699582	200	0.0019601	13302	48685143
13302012016	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	18	0.0001764	13302	4381663
13302012017	13302	15	2017	Lampa	243425.7	2017	102034	24837699582	344	0.0033714	13302	83738447
13302012018	13302	7	2017	Lampa	243425.7	2017	102034	24837699582	118	0.0011565	13302	28724235
13302012019	13302	43	2017	Lampa	243425.7	2017	102034	24837699582	500	0.0049003	13302	121712858
13302012020	13302	32	2017	Lampa	243425.7	2017	102034	24837699582	532	0.0052139	13302	129502481
13302012021	13302	9	2017	Lampa	243425.7	2017	102034	24837699582	206	0.0020189	13302	50145698
13302012028	13302	48	2017	Lampa	243425.7	2017	102034	24837699582	437	0.0042829	13302	106377038
13302012901	13302	1	2017	Lampa	243425.7	2017	102034	24837699582	14	0.0001372	13302	3407960
13302022002	13302	11	2017	Lampa	243425.7	2017	102034	24837699582	255	0.0024992	13302	62073558
13302022005	13302	62	2017	Lampa	243425.7	2017	102034	24837699582	1376	0.0134857	13302	334953786
13302022007	13302	2	2017	Lampa	243425.7	2017	102034	24837699582	243	0.0023816	13302	59152449
13302022017	13302	145	2017	Lampa	243425.7	2017	102034	24837699582	1012	0.0099183	13302	246346825
13302032001	13302	231	2017	Lampa	243425.7	2017	102034	24837699582	1258	0.0123292	13302	306229552
13302032010	13302	45	2017	Lampa	243425.7	2017	102034	24837699582	234	0.0022934	13302	56961618
13302032015	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	148	0.0014505	13302	36027006
13302032019	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	47	0.0004606	13302	11441009
13302032022	13302	42	2017	Lampa	243425.7	2017	102034	24837699582	215	0.0021071	13302	52336529
13302032025	13302	454	2017	Lampa	243425.7	2017	102034	24837699582	2238	0.0219339	13302	544786754
13302032026	13302	906	2017	Lampa	243425.7	2017	102034	24837699582	3031	0.0297058	13302	737823347
13302032027	13302	536	2017	Lampa	243425.7	2017	102034	24837699582	2777	0.0272164	13302	675993215
13302042008	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	807	0.0079091	13302	196444553
13302042010	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	100	0.0009801	13302	24342572
13302042012	13302	12	2017	Lampa	243425.7	2017	102034	24837699582	468	0.0045867	13302	113923235
13302042901	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	19	0.0001862	13302	4625089
13302052004	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	358	0.0035086	13302	87146407
13302052011	13302	6	2017	Lampa	243425.7	2017	102034	24837699582	158	0.0015485	13302	38461263
13302052014	13302	180	2017	Lampa	243425.7	2017	102034	24837699582	1137	0.0111433	13302	276775040
13302052023	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	842	0.0082522	13302	204964453
13303012003	13303	11	2017	Tiltil	264794.8	2017	19312	5113717064	59	0.0030551	13303	15622893
13303012012	13303	39	2017	Tiltil	264794.8	2017	19312	5113717064	705	0.0365058	13303	186680330
13303022006	13303	12	2017	Tiltil	264794.8	2017	19312	5113717064	379	0.0196251	13303	100357227

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 
## -389300400  -52240370  -26648681   29481582  616707781 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 56671901    4781582   11.85   <2e-16 ***
## Freq.x        949720      28478   33.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 88640000 on 456 degrees of freedom
## Multiple R-squared:  0.7092, Adjusted R-squared:  0.7086 
## F-statistic:  1112 on 1 and 456 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 
## -389300400  -52240370  -26648681   29481582  616707781 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 56671901    4781582   11.85   <2e-16 ***
## Freq.x        949720      28478   33.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 88640000 on 456 degrees of freedom
## Multiple R-squared:  0.7092, Adjusted R-squared:  0.7086 
## F-statistic:  1112 on 1 and 456 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 
## -389300400  -52240370  -26648681   29481582  616707781 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 56671901    4781582   11.85   <2e-16 ***
## Freq.x        949720      28478   33.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 88640000 on 456 degrees of freedom
## Multiple R-squared:  0.7092, Adjusted R-squared:  0.7086 
## F-statistic:  1112 on 1 and 456 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 
## -163834135  -69687428  -15404665   46453421  838991671 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -121951198   12295299  -9.919   <2e-16 ***
## log(Freq.x)   76667676    3306468  23.187   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 111400000 on 456 degrees of freedom
## Multiple R-squared:  0.5411, Adjusted R-squared:  0.5401 
## F-statistic: 537.6 on 1 and 456 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 
## -205149500  -44837048    -374053   27645401  637473510 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -43438921    6361072  -6.829 2.74e-11 ***
## sqrt(Freq.x)  24943574     694456  35.918  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8.4e+07 on 456 degrees of freedom
## Multiple R-squared:  0.7388, Adjusted R-squared:  0.7383 
## F-statistic:  1290 on 1 and 456 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 
## -5863.7 -2393.6  -557.9  1817.5 10250.7 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   3314.86     225.88   14.68   <2e-16 ***
## sqrt(Freq.x)   927.54      24.66   37.61   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2983 on 456 degrees of freedom
## Multiple R-squared:  0.7562, Adjusted R-squared:  0.7557 
## F-statistic:  1415 on 1 and 456 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 
## -3.2350 -0.5775  0.1081  0.6201  1.7029 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  16.722124   0.062396  268.00   <2e-16 ***
## sqrt(Freq.x)  0.181314   0.006812   26.62   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.824 on 456 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6075 
## F-statistic: 708.5 on 1 and 456 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 
## -6954.5 -2427.3  -174.3  1940.9 14749.1 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -897.74     357.40  -2.512   0.0124 *  
## log(Freq.x)  3234.73      96.11  33.655   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3237 on 456 degrees of freedom
## Multiple R-squared:  0.713,  Adjusted R-squared:  0.7123 
## F-statistic:  1133 on 1 and 456 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 
## -1.80140 -0.45182  0.00971  0.44264  1.81614 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.57452    0.07101  219.31   <2e-16 ***
## log(Freq.x)  0.72853    0.01910   38.15   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.6432 on 456 degrees of freedom
## Multiple R-squared:  0.7614, Adjusted R-squared:  0.7609 
## F-statistic:  1455 on 1 and 456 DF,  p-value: < 2.2e-16

9 Modelo elegido: log-log (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.7609).

9.1 Diagrama de dispersión sobre log-log

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

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

9.2 Modelo log-log

Observemos nuevamente el resultado sobre log-log.

linearMod <- lm(log( multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_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 
## -1.80140 -0.45182  0.00971  0.44264  1.81614 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.57452    0.07101  219.31   <2e-16 ***
## log(Freq.x)  0.72853    0.01910   38.15   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.6432 on 456 degrees of freedom
## Multiple R-squared:  0.7614, Adjusted R-squared:  0.7609 
## F-statistic:  1455 on 1 and 456 DF,  p-value: < 2.2e-16

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

9.3 Análisis de residuos

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

9.4 Ecuación del modelo

\[ \hat Y = e^{15.57452+0.72853 \cdot ln{X}} \]

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

Esta nueva variable se llamará: est_ing

h_y_m_comuna_corr_01$est_ing <- 
exp(15.57452+0.72853 * log(h_y_m_comuna_corr_01$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
13202012001	13202	478	2017	Pirque	274675.6	2017	26521	7284672878	1610	0.0607066	13202	442227794	519962113
13202012002	13202	272	2017	Pirque	274675.6	2017	26521	7284672878	1485	0.0559934	13202	407893338	344813752
13202012005	13202	168	2017	Pirque	274675.6	2017	26521	7284672878	1482	0.0558802	13202	407069311	242735147
13202012009	13202	170	2017	Pirque	274675.6	2017	26521	7284672878	954	0.0359715	13202	262040569	244836999
13202022004	13202	94	2017	Pirque	274675.6	2017	26521	7284672878	343	0.0129331	13202	94213747	159005054
13202022006	13202	82	2017	Pirque	274675.6	2017	26521	7284672878	234	0.0088232	13202	64274102	143945768
13202022007	13202	57	2017	Pirque	274675.6	2017	26521	7284672878	168	0.0063346	13202	46145509	110442341
13202022010	13202	101	2017	Pirque	274675.6	2017	26521	7284672878	308	0.0116134	13202	84600100	167546880
13202022011	13202	16	2017	Pirque	274675.6	2017	26521	7284672878	58	0.0021869	13202	15931188	43768899
13202022012	13202	197	2017	Pirque	274675.6	2017	26521	7284672878	744	0.0280532	13202	204358683	272593549
13202022014	13202	353	2017	Pirque	274675.6	2017	26521	7284672878	1477	0.0556917	13202	405695933	416925444
13202032003	13202	472	2017	Pirque	274675.6	2017	26521	7284672878	1944	0.0733004	13202	533969461	515199056
13202032008	13202	441	2017	Pirque	274675.6	2017	26521	7284672878	2296	0.0865729	13202	630655289	490321503
13202032013	13202	338	2017	Pirque	274675.6	2017	26521	7284672878	1748	0.0659100	13202	480133034	403942713
13203012004	13203	53	2017	San José de Maipo	344876.8	2017	18189	6272964115	151	0.0083017	13203	52076397	104740536
13203012005	13203	102	2017	San José de Maipo	344876.8	2017	18189	6272964115	618	0.0339766	13203	213133862	168753806
13203012012	13203	6	2017	San José de Maipo	344876.8	2017	18189	6272964115	66	0.0036286	13203	22761869	21420748
13203012019	13203	56	2017	San José de Maipo	344876.8	2017	18189	6272964115	537	0.0295233	13203	185198842	109027365
13203012901	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	10	0.0005498	13203	3448768	5806683
13203022002	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	313	0.0172082	13203	107946438	23966652
13203022004	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	23	0.0012645	13203	7932166	15942149
13203022015	13203	101	2017	San José de Maipo	344876.8	2017	18189	6272964115	808	0.0444225	13203	278660454	167546880
13203032017	13203	10	2017	San José de Maipo	344876.8	2017	18189	6272964115	35	0.0019242	13203	12070688	31078360
13203032018	13203	104	2017	San José de Maipo	344876.8	2017	18189	6272964115	1186	0.0652042	13203	409023885	171158075
13203042001	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	40	0.0021991	13203	13795072	15942149
13203042008	13203	8	2017	San José de Maipo	344876.8	2017	18189	6272964115	62	0.0034087	13203	21382362	26415342
13203042010	13203	43	2017	San José de Maipo	344876.8	2017	18189	6272964115	358	0.0196822	13203	123465894	89941239
13203042013	13203	2	2017	San José de Maipo	344876.8	2017	18189	6272964115	39	0.0021442	13203	13450195	9621382
13203042014	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	17	0.0009346	13203	5862906	5806683
13203042901	13203	12	2017	San José de Maipo	344876.8	2017	18189	6272964115	42	0.0023091	13203	14484826	35493106
13203052006	13203	66	2017	San José de Maipo	344876.8	2017	18189	6272964115	256	0.0140744	13203	88288461	122891102
13203052009	13203	16	2017	San José de Maipo	344876.8	2017	18189	6272964115	218	0.0119853	13203	75183142	43768899
13203052017	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	32	0.0017593	13203	11036058	23966652
13203062003	13203	83	2017	San José de Maipo	344876.8	2017	18189	6272964115	306	0.0168234	13203	105532301	145222550
13203062007	13203	447	2017	San José de Maipo	344876.8	2017	18189	6272964115	1864	0.1024795	13203	642850355	495172633
13301012005	13301	207	2017	Colina	255373.7	2017	146207	37337421744	1304	0.0089189	13301	333007298	282606385
13301012010	13301	4	2017	Colina	255373.7	2017	146207	37337421744	121	0.0008276	13301	30900217	15942149
13301012012	13301	517	2017	Colina	255373.7	2017	146207	37337421744	1844	0.0126123	13301	470909093	550538075
13301012015	13301	98	2017	Colina	255373.7	2017	146207	37337421744	620	0.0042406	13301	158331691	163906444
13301012018	13301	281	2017	Colina	255373.7	2017	146207	37337421744	776	0.0053075	13301	198169987	353088936
13301012025	13301	46	2017	Colina	255373.7	2017	146207	37337421744	259	0.0017715	13301	66141787	94470683
13301012026	13301	47	2017	Colina	255373.7	2017	146207	37337421744	205	0.0014021	13301	52351607	95962498
13301012029	13301	16	2017	Colina	255373.7	2017	146207	37337421744	304	0.0020792	13301	77633603	43768899
13301022004	13301	1706	2017	Colina	255373.7	2017	146207	37337421744	5042	0.0344854	13301	1287594167	1313777364
13301022006	13301	341	2017	Colina	255373.7	2017	146207	37337421744	1010	0.0069080	13301	257927431	406551570
13301022008	13301	77	2017	Colina	255373.7	2017	146207	37337421744	185	0.0012653	13301	47244133	137496987
13301032001	13301	16	2017	Colina	255373.7	2017	146207	37337421744	727	0.0049724	13301	185656676	43768899
13301032007	13301	637	2017	Colina	255373.7	2017	146207	37337421744	2002	0.0136929	13301	511258136	640955377
13301032013	13301	82	2017	Colina	255373.7	2017	146207	37337421744	303	0.0020724	13301	77378229	143945768
13301032014	13301	40	2017	Colina	255373.7	2017	146207	37337421744	99	0.0006771	13301	25281996	85325111
13301032018	13301	291	2017	Colina	255373.7	2017	146207	37337421744	802	0.0054854	13301	204809703	362199673
13301032019	13301	14	2017	Colina	255373.7	2017	146207	37337421744	50	0.0003420	13301	12768685	39711542
13301032020	13301	283	2017	Colina	255373.7	2017	146207	37337421744	1068	0.0073047	13301	272739106	354918033
13301032022	13301	96	2017	Colina	255373.7	2017	146207	37337421744	321	0.0021955	13301	81974956	161462680
13301032024	13301	859	2017	Colina	255373.7	2017	146207	37337421744	4204	0.0287538	13301	1073591011	796948273
13301032028	13301	296	2017	Colina	255373.7	2017	146207	37337421744	896	0.0061283	13301	228814830	366723081
13301042021	13301	25	2017	Colina	255373.7	2017	146207	37337421744	364	0.0024896	13301	92956025	60585588
13301052002	13301	137	2017	Colina	255373.7	2017	146207	37337421744	1273	0.0087068	13301	325090713	209215150
13301052009	13301	18	2017	Colina	255373.7	2017	146207	37337421744	155	0.0010601	13301	39582923	47690489
13301052023	13301	53	2017	Colina	255373.7	2017	146207	37337421744	967	0.0066139	13301	246946363	104740536
13301052901	13301	2	2017	Colina	255373.7	2017	146207	37337421744	22	0.0001505	13301	5618221	9621382
13301062004	13301	496	2017	Colina	255373.7	2017	146207	37337421744	1532	0.0104783	13301	391232500	534155076
13301062005	13301	44	2017	Colina	255373.7	2017	146207	37337421744	172	0.0011764	13301	43924275	91460311
13301062016	13301	400	2017	Colina	255373.7	2017	146207	37337421744	1331	0.0091035	13301	339902387	456674603
13301062027	13301	72	2017	Colina	255373.7	2017	146207	37337421744	231	0.0015800	13301	58991323	130933428
13302012003	13302	102	2017	Lampa	243425.7	2017	102034	24837699582	808	0.0079189	13302	196687979	168753806
13302012006	13302	26	2017	Lampa	243425.7	2017	102034	24837699582	355	0.0034792	13302	86416129	62341698
13302012009	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	968	0.0094870	13302	235636094	137496987
13302012014	13302	37	2017	Lampa	243425.7	2017	102034	24837699582	200	0.0019601	13302	48685143	80613930
13302012016	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	18	0.0001764	13302	4381663	15942149
13302012017	13302	15	2017	Lampa	243425.7	2017	102034	24837699582	344	0.0033714	13302	83738447	41758593
13302012018	13302	7	2017	Lampa	243425.7	2017	102034	24837699582	118	0.0011565	13302	28724235	23966652
13302012019	13302	43	2017	Lampa	243425.7	2017	102034	24837699582	500	0.0049003	13302	121712858	89941239
13302012020	13302	32	2017	Lampa	243425.7	2017	102034	24837699582	532	0.0052139	13302	129502481	72522874
13302012021	13302	9	2017	Lampa	243425.7	2017	102034	24837699582	206	0.0020189	13302	50145698	28782094
13302012028	13302	48	2017	Lampa	243425.7	2017	102034	24837699582	437	0.0042829	13302	106377038	97445721
13302012901	13302	1	2017	Lampa	243425.7	2017	102034	24837699582	14	0.0001372	13302	3407960	5806683
13302022002	13302	11	2017	Lampa	243425.7	2017	102034	24837699582	255	0.0024992	13302	62073558	33313012
13302022005	13302	62	2017	Lampa	243425.7	2017	102034	24837699582	1376	0.0134857	13302	334953786	117419226
13302022007	13302	2	2017	Lampa	243425.7	2017	102034	24837699582	243	0.0023816	13302	59152449	9621382
13302022017	13302	145	2017	Lampa	243425.7	2017	102034	24837699582	1012	0.0099183	13302	246346825	218046703
13302032001	13302	231	2017	Lampa	243425.7	2017	102034	24837699582	1258	0.0123292	13302	306229552	306119031
13302032010	13302	45	2017	Lampa	243425.7	2017	102034	24837699582	234	0.0022934	13302	56961618	92970038
13302032015	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	148	0.0014505	13302	36027006	12927818
13302032019	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	47	0.0004606	13302	11441009	12927818
13302032022	13302	42	2017	Lampa	243425.7	2017	102034	24837699582	215	0.0021071	13302	52336529	88412547
13302032025	13302	454	2017	Lampa	243425.7	2017	102034	24837699582	2238	0.0219339	13302	544786754	500810003
13302032026	13302	906	2017	Lampa	243425.7	2017	102034	24837699582	3031	0.0297058	13302	737823347	828485096
13302032027	13302	536	2017	Lampa	243425.7	2017	102034	24837699582	2777	0.0272164	13302	675993215	565205681
13302042008	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	807	0.0079091	13302	196444553	137496987
13302042010	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	100	0.0009801	13302	24342572	15942149
13302042012	13302	12	2017	Lampa	243425.7	2017	102034	24837699582	468	0.0045867	13302	113923235	35493106
13302042901	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	19	0.0001862	13302	4625089	15942149
13302052004	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	358	0.0035086	13302	87146407	45745360
13302052011	13302	6	2017	Lampa	243425.7	2017	102034	24837699582	158	0.0015485	13302	38461263	21420748
13302052014	13302	180	2017	Lampa	243425.7	2017	102034	24837699582	1137	0.0111433	13302	276775040	255247662
13302052023	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	842	0.0082522	13302	204964453	45745360
13303012003	13303	11	2017	Tiltil	264794.8	2017	19312	5113717064	59	0.0030551	13303	15622893	33313012
13303012012	13303	39	2017	Tiltil	264794.8	2017	19312	5113717064	705	0.0365058	13303	186680330	83765733
13303022006	13303	12	2017	Tiltil	264794.8	2017	19312	5113717064	379	0.0196251	13303	100357227	35493106

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
13202012001	13202	478	2017	Pirque	274675.6	2017	26521	7284672878	1610	0.0607066	13202	442227794	519962113	322957.83
13202012002	13202	272	2017	Pirque	274675.6	2017	26521	7284672878	1485	0.0559934	13202	407893338	344813752	232197.81
13202012005	13202	168	2017	Pirque	274675.6	2017	26521	7284672878	1482	0.0558802	13202	407069311	242735147	163788.90
13202012009	13202	170	2017	Pirque	274675.6	2017	26521	7284672878	954	0.0359715	13202	262040569	244836999	256642.56
13202022004	13202	94	2017	Pirque	274675.6	2017	26521	7284672878	343	0.0129331	13202	94213747	159005054	463571.59
13202022006	13202	82	2017	Pirque	274675.6	2017	26521	7284672878	234	0.0088232	13202	64274102	143945768	615152.85
13202022007	13202	57	2017	Pirque	274675.6	2017	26521	7284672878	168	0.0063346	13202	46145509	110442341	657394.89
13202022010	13202	101	2017	Pirque	274675.6	2017	26521	7284672878	308	0.0116134	13202	84600100	167546880	543983.38
13202022011	13202	16	2017	Pirque	274675.6	2017	26521	7284672878	58	0.0021869	13202	15931188	43768899	754636.20
13202022012	13202	197	2017	Pirque	274675.6	2017	26521	7284672878	744	0.0280532	13202	204358683	272593549	366389.18
13202022014	13202	353	2017	Pirque	274675.6	2017	26521	7284672878	1477	0.0556917	13202	405695933	416925444	282278.57
13202032003	13202	472	2017	Pirque	274675.6	2017	26521	7284672878	1944	0.0733004	13202	533969461	515199056	265020.09
13202032008	13202	441	2017	Pirque	274675.6	2017	26521	7284672878	2296	0.0865729	13202	630655289	490321503	213554.66
13202032013	13202	338	2017	Pirque	274675.6	2017	26521	7284672878	1748	0.0659100	13202	480133034	403942713	231088.51
13203012004	13203	53	2017	San José de Maipo	344876.8	2017	18189	6272964115	151	0.0083017	13203	52076397	104740536	693645.94
13203012005	13203	102	2017	San José de Maipo	344876.8	2017	18189	6272964115	618	0.0339766	13203	213133862	168753806	273064.41
13203012012	13203	6	2017	San José de Maipo	344876.8	2017	18189	6272964115	66	0.0036286	13203	22761869	21420748	324556.78
13203012019	13203	56	2017	San José de Maipo	344876.8	2017	18189	6272964115	537	0.0295233	13203	185198842	109027365	203030.48
13203012901	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	10	0.0005498	13203	3448768	5806683	580668.27
13203022002	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	313	0.0172082	13203	107946438	23966652	76570.77
13203022004	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	23	0.0012645	13203	7932166	15942149	693136.91
13203022015	13203	101	2017	San José de Maipo	344876.8	2017	18189	6272964115	808	0.0444225	13203	278660454	167546880	207360.00
13203032017	13203	10	2017	San José de Maipo	344876.8	2017	18189	6272964115	35	0.0019242	13203	12070688	31078360	887953.15
13203032018	13203	104	2017	San José de Maipo	344876.8	2017	18189	6272964115	1186	0.0652042	13203	409023885	171158075	144315.41
13203042001	13203	4	2017	San José de Maipo	344876.8	2017	18189	6272964115	40	0.0021991	13203	13795072	15942149	398553.72
13203042008	13203	8	2017	San José de Maipo	344876.8	2017	18189	6272964115	62	0.0034087	13203	21382362	26415342	426053.91
13203042010	13203	43	2017	San José de Maipo	344876.8	2017	18189	6272964115	358	0.0196822	13203	123465894	89941239	251232.51
13203042013	13203	2	2017	San José de Maipo	344876.8	2017	18189	6272964115	39	0.0021442	13203	13450195	9621382	246702.11
13203042014	13203	1	2017	San José de Maipo	344876.8	2017	18189	6272964115	17	0.0009346	13203	5862906	5806683	341569.57
13203042901	13203	12	2017	San José de Maipo	344876.8	2017	18189	6272964115	42	0.0023091	13203	14484826	35493106	845073.96
13203052006	13203	66	2017	San José de Maipo	344876.8	2017	18189	6272964115	256	0.0140744	13203	88288461	122891102	480043.37
13203052009	13203	16	2017	San José de Maipo	344876.8	2017	18189	6272964115	218	0.0119853	13203	75183142	43768899	200774.77
13203052017	13203	7	2017	San José de Maipo	344876.8	2017	18189	6272964115	32	0.0017593	13203	11036058	23966652	748957.87
13203062003	13203	83	2017	San José de Maipo	344876.8	2017	18189	6272964115	306	0.0168234	13203	105532301	145222550	474583.50
13203062007	13203	447	2017	San José de Maipo	344876.8	2017	18189	6272964115	1864	0.1024795	13203	642850355	495172633	265650.55
13301012005	13301	207	2017	Colina	255373.7	2017	146207	37337421744	1304	0.0089189	13301	333007298	282606385	216722.69
13301012010	13301	4	2017	Colina	255373.7	2017	146207	37337421744	121	0.0008276	13301	30900217	15942149	131753.30
13301012012	13301	517	2017	Colina	255373.7	2017	146207	37337421744	1844	0.0126123	13301	470909093	550538075	298556.44
13301012015	13301	98	2017	Colina	255373.7	2017	146207	37337421744	620	0.0042406	13301	158331691	163906444	264365.23
13301012018	13301	281	2017	Colina	255373.7	2017	146207	37337421744	776	0.0053075	13301	198169987	353088936	455011.52
13301012025	13301	46	2017	Colina	255373.7	2017	146207	37337421744	259	0.0017715	13301	66141787	94470683	364751.67
13301012026	13301	47	2017	Colina	255373.7	2017	146207	37337421744	205	0.0014021	13301	52351607	95962498	468109.75
13301012029	13301	16	2017	Colina	255373.7	2017	146207	37337421744	304	0.0020792	13301	77633603	43768899	143976.64
13301022004	13301	1706	2017	Colina	255373.7	2017	146207	37337421744	5042	0.0344854	13301	1287594167	1313777364	260566.71
13301022006	13301	341	2017	Colina	255373.7	2017	146207	37337421744	1010	0.0069080	13301	257927431	406551570	402526.31
13301022008	13301	77	2017	Colina	255373.7	2017	146207	37337421744	185	0.0012653	13301	47244133	137496987	743226.96
13301032001	13301	16	2017	Colina	255373.7	2017	146207	37337421744	727	0.0049724	13301	185656676	43768899	60204.81
13301032007	13301	637	2017	Colina	255373.7	2017	146207	37337421744	2002	0.0136929	13301	511258136	640955377	320157.53
13301032013	13301	82	2017	Colina	255373.7	2017	146207	37337421744	303	0.0020724	13301	77378229	143945768	475068.54
13301032014	13301	40	2017	Colina	255373.7	2017	146207	37337421744	99	0.0006771	13301	25281996	85325111	861869.80
13301032018	13301	291	2017	Colina	255373.7	2017	146207	37337421744	802	0.0054854	13301	204809703	362199673	451620.54
13301032019	13301	14	2017	Colina	255373.7	2017	146207	37337421744	50	0.0003420	13301	12768685	39711542	794230.84
13301032020	13301	283	2017	Colina	255373.7	2017	146207	37337421744	1068	0.0073047	13301	272739106	354918033	332320.26
13301032022	13301	96	2017	Colina	255373.7	2017	146207	37337421744	321	0.0021955	13301	81974956	161462680	502999.00
13301032024	13301	859	2017	Colina	255373.7	2017	146207	37337421744	4204	0.0287538	13301	1073591011	796948273	189569.05
13301032028	13301	296	2017	Colina	255373.7	2017	146207	37337421744	896	0.0061283	13301	228814830	366723081	409289.15
13301042021	13301	25	2017	Colina	255373.7	2017	146207	37337421744	364	0.0024896	13301	92956025	60585588	166443.92
13301052002	13301	137	2017	Colina	255373.7	2017	146207	37337421744	1273	0.0087068	13301	325090713	209215150	164348.11
13301052009	13301	18	2017	Colina	255373.7	2017	146207	37337421744	155	0.0010601	13301	39582923	47690489	307680.57
13301052023	13301	53	2017	Colina	255373.7	2017	146207	37337421744	967	0.0066139	13301	246946363	104740536	108314.93
13301052901	13301	2	2017	Colina	255373.7	2017	146207	37337421744	22	0.0001505	13301	5618221	9621382	437335.56
13301062004	13301	496	2017	Colina	255373.7	2017	146207	37337421744	1532	0.0104783	13301	391232500	534155076	348665.19
13301062005	13301	44	2017	Colina	255373.7	2017	146207	37337421744	172	0.0011764	13301	43924275	91460311	531745.99
13301062016	13301	400	2017	Colina	255373.7	2017	146207	37337421744	1331	0.0091035	13301	339902387	456674603	343106.39
13301062027	13301	72	2017	Colina	255373.7	2017	146207	37337421744	231	0.0015800	13301	58991323	130933428	566811.38
13302012003	13302	102	2017	Lampa	243425.7	2017	102034	24837699582	808	0.0079189	13302	196687979	168753806	208853.72
13302012006	13302	26	2017	Lampa	243425.7	2017	102034	24837699582	355	0.0034792	13302	86416129	62341698	175610.42
13302012009	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	968	0.0094870	13302	235636094	137496987	142042.34
13302012014	13302	37	2017	Lampa	243425.7	2017	102034	24837699582	200	0.0019601	13302	48685143	80613930	403069.65
13302012016	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	18	0.0001764	13302	4381663	15942149	885674.94
13302012017	13302	15	2017	Lampa	243425.7	2017	102034	24837699582	344	0.0033714	13302	83738447	41758593	121391.26
13302012018	13302	7	2017	Lampa	243425.7	2017	102034	24837699582	118	0.0011565	13302	28724235	23966652	203107.22
13302012019	13302	43	2017	Lampa	243425.7	2017	102034	24837699582	500	0.0049003	13302	121712858	89941239	179882.48
13302012020	13302	32	2017	Lampa	243425.7	2017	102034	24837699582	532	0.0052139	13302	129502481	72522874	136321.19
13302012021	13302	9	2017	Lampa	243425.7	2017	102034	24837699582	206	0.0020189	13302	50145698	28782094	139718.90
13302012028	13302	48	2017	Lampa	243425.7	2017	102034	24837699582	437	0.0042829	13302	106377038	97445721	222987.92
13302012901	13302	1	2017	Lampa	243425.7	2017	102034	24837699582	14	0.0001372	13302	3407960	5806683	414763.05
13302022002	13302	11	2017	Lampa	243425.7	2017	102034	24837699582	255	0.0024992	13302	62073558	33313012	130639.26
13302022005	13302	62	2017	Lampa	243425.7	2017	102034	24837699582	1376	0.0134857	13302	334953786	117419226	85333.74
13302022007	13302	2	2017	Lampa	243425.7	2017	102034	24837699582	243	0.0023816	13302	59152449	9621382	39594.17
13302022017	13302	145	2017	Lampa	243425.7	2017	102034	24837699582	1012	0.0099183	13302	246346825	218046703	215461.17
13302032001	13302	231	2017	Lampa	243425.7	2017	102034	24837699582	1258	0.0123292	13302	306229552	306119031	243337.86
13302032010	13302	45	2017	Lampa	243425.7	2017	102034	24837699582	234	0.0022934	13302	56961618	92970038	397307.85
13302032015	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	148	0.0014505	13302	36027006	12927818	87350.12
13302032019	13302	3	2017	Lampa	243425.7	2017	102034	24837699582	47	0.0004606	13302	11441009	12927818	275059.97
13302032022	13302	42	2017	Lampa	243425.7	2017	102034	24837699582	215	0.0021071	13302	52336529	88412547	411221.15
13302032025	13302	454	2017	Lampa	243425.7	2017	102034	24837699582	2238	0.0219339	13302	544786754	500810003	223775.69
13302032026	13302	906	2017	Lampa	243425.7	2017	102034	24837699582	3031	0.0297058	13302	737823347	828485096	273337.21
13302032027	13302	536	2017	Lampa	243425.7	2017	102034	24837699582	2777	0.0272164	13302	675993215	565205681	203531.03
13302042008	13302	77	2017	Lampa	243425.7	2017	102034	24837699582	807	0.0079091	13302	196444553	137496987	170380.41
13302042010	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	100	0.0009801	13302	24342572	15942149	159421.49
13302042012	13302	12	2017	Lampa	243425.7	2017	102034	24837699582	468	0.0045867	13302	113923235	35493106	75839.97
13302042901	13302	4	2017	Lampa	243425.7	2017	102034	24837699582	19	0.0001862	13302	4625089	15942149	839060.47
13302052004	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	358	0.0035086	13302	87146407	45745360	127780.33
13302052011	13302	6	2017	Lampa	243425.7	2017	102034	24837699582	158	0.0015485	13302	38461263	21420748	135574.35
13302052014	13302	180	2017	Lampa	243425.7	2017	102034	24837699582	1137	0.0111433	13302	276775040	255247662	224492.23
13302052023	13302	17	2017	Lampa	243425.7	2017	102034	24837699582	842	0.0082522	13302	204964453	45745360	54329.41
13303012003	13303	11	2017	Tiltil	264794.8	2017	19312	5113717064	59	0.0030551	13303	15622893	33313012	564627.33
13303012012	13303	39	2017	Tiltil	264794.8	2017	19312	5113717064	705	0.0365058	13303	186680330	83765733	118816.64
13303022006	13303	12	2017	Tiltil	264794.8	2017	19312	5113717064	379	0.0196251	13303	100357227	35493106	93649.36

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "P15/region_13_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