Expansión de la CASEN sobre el CENSO (Región 05)

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 05.

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

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

1 Variable CENSO

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

1.1 Lectura y filtrado de la tabla censal de personas

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

tabla_con_clave <- readRDS("../censo_personas_con_clave_17")
r3_100 <- tabla_con_clave[c(1:100),]
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

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

Despleguemos los códigos de regiones de nuestra tabla:

regiones <- unique(tabla_con_clave$REGION)
regiones

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

Hagamos un subset con la region 02 y con la zona = 2:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 5) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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	5101212004	12	5101	4	2017
2	5101212901	12	5101	2	2017
3	5101222003	12	5101	8	2017
4	5101232002	12	5101	45	2017
5	5101242001	12	5101	1	2017
496	5102012002	12	5102	29	2017
497	5102012029	12	5102	24	2017
498	5102012038	12	5102	9	2017
499	5102022010	12	5102	1	2017
500	5102022015	12	5102	6	2017
501	5102022025	12	5102	5	2017
502	5102022031	12	5102	6	2017
503	5102022039	12	5102	13	2017
504	5102032007	12	5102	15	2017
505	5102032011	12	5102	32	2017
506	5102032027	12	5102	32	2017
507	5102042018	12	5102	7	2017
508	5102042019	12	5102	7	2017
509	5102052008	12	5102	8	2017
510	5102052012	12	5102	31	2017
511	5102052024	12	5102	46	2017
512	5102052901	12	5102	1	2017
513	5102062012	12	5102	6	2017
514	5102062042	12	5102	2	2017
515	5102072034	12	5102	2	2017
516	5102082005	12	5102	2	2017
517	5102082013	12	5102	41	2017
518	5102082030	12	5102	20	2017
519	5102082035	12	5102	1	2017
520	5102092003	12	5102	44	2017
521	5102092040	12	5102	36	2017
522	5102102003	12	5102	7	2017
523	5102102033	12	5102	79	2017
524	5102102036	12	5102	16	2017
525	5102112023	12	5102	8	2017
526	5102112026	12	5102	71	2017
527	5102112028	12	5102	13	2017
528	5102112030	12	5102	53	2017
529	5102122009	12	5102	51	2017
530	5102122017	12	5102	70	2017
531	5102122021	12	5102	50	2017
532	5102122037	12	5102	8	2017
533	5102132002	12	5102	4	2017
534	5102132004	12	5102	31	2017
535	5102132020	12	5102	36	2017
536	5102132032	12	5102	1	2017
537	5102132901	12	5102	7	2017
1028	5103022001	12	5103	286	2017
1029	5103022002	12	5103	32	2017
1520	5104012001	12	5104	12	2017
1521	5104012002	12	5104	121	2017
1522	5104012901	12	5104	1	2017
1523	5104992999	12	5104	3	2017
2014	5105012004	12	5105	28	2017
2015	5105012012	12	5105	2	2017
2016	5105012015	12	5105	2	2017
2017	5105022012	12	5105	2	2017
2018	5105022901	12	5105	2	2017
2019	5105032005	12	5105	3	2017
2020	5105032008	12	5105	3	2017
2021	5105042002	12	5105	7	2017
2022	5105042003	12	5105	10	2017
2023	5105042013	12	5105	3	2017
2024	5105042015	12	5105	4	2017
2025	5105042016	12	5105	12	2017
2026	5105052014	12	5105	62	2017
2027	5105072011	12	5105	10	2017
2028	5105082001	12	5105	65	2017
2519	5107012010	12	5107	25	2017
2520	5107022004	12	5107	102	2017
2521	5107022009	12	5107	2	2017
2522	5107022013	12	5107	133	2017
2523	5107022016	12	5107	112	2017
2524	5107022901	12	5107	10	2017
2525	5107032002	12	5107	62	2017
2526	5107032003	12	5107	157	2017
2527	5107032006	12	5107	176	2017
2528	5107032007	12	5107	29	2017
2529	5107032011	12	5107	29	2017
2530	5107032012	12	5107	254	2017
2531	5107032014	12	5107	12	2017
2532	5107032015	12	5107	3	2017
3023	5201012002	12	5201	31	2017
3024	5201022004	12	5201	10	2017
3025	5201022005	12	5201	5	2017
3026	5201022901	12	5201	3	2017
3517	5301012009	12	5301	20	2017
3518	5301022009	12	5301	30	2017
3519	5301022014	12	5301	13	2017
3520	5301022901	12	5301	5	2017
3521	5301032003	12	5301	1	2017
3522	5301042003	12	5301	57	2017
3523	5301042005	12	5301	30	2017
3524	5301042007	12	5301	7	2017
3525	5301042015	12	5301	4	2017
3526	5301052001	12	5301	105	2017
3527	5301052002	12	5301	1	2017
3528	5301052010	12	5301	3	2017
3529	5301052011	12	5301	50	2017
3530	5301052013	12	5301	270	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	5101212004	4	2017	05101
2	5101212901	2	2017	05101
3	5101222003	8	2017	05101
4	5101232002	45	2017	05101
5	5101242001	1	2017	05101
496	5102012002	29	2017	05102
497	5102012029	24	2017	05102
498	5102012038	9	2017	05102
499	5102022010	1	2017	05102
500	5102022015	6	2017	05102
501	5102022025	5	2017	05102
502	5102022031	6	2017	05102
503	5102022039	13	2017	05102
504	5102032007	15	2017	05102
505	5102032011	32	2017	05102
506	5102032027	32	2017	05102
507	5102042018	7	2017	05102
508	5102042019	7	2017	05102
509	5102052008	8	2017	05102
510	5102052012	31	2017	05102
511	5102052024	46	2017	05102
512	5102052901	1	2017	05102
513	5102062012	6	2017	05102
514	5102062042	2	2017	05102
515	5102072034	2	2017	05102
516	5102082005	2	2017	05102
517	5102082013	41	2017	05102
518	5102082030	20	2017	05102
519	5102082035	1	2017	05102
520	5102092003	44	2017	05102
521	5102092040	36	2017	05102
522	5102102003	7	2017	05102
523	5102102033	79	2017	05102
524	5102102036	16	2017	05102
525	5102112023	8	2017	05102
526	5102112026	71	2017	05102
527	5102112028	13	2017	05102
528	5102112030	53	2017	05102
529	5102122009	51	2017	05102
530	5102122017	70	2017	05102
531	5102122021	50	2017	05102
532	5102122037	8	2017	05102
533	5102132002	4	2017	05102
534	5102132004	31	2017	05102
535	5102132020	36	2017	05102
536	5102132032	1	2017	05102
537	5102132901	7	2017	05102
1028	5103022001	286	2017	05103
1029	5103022002	32	2017	05103
1520	5104012001	12	2017	05104
1521	5104012002	121	2017	05104
1522	5104012901	1	2017	05104
1523	5104992999	3	2017	05104
2014	5105012004	28	2017	05105
2015	5105012012	2	2017	05105
2016	5105012015	2	2017	05105
2017	5105022012	2	2017	05105
2018	5105022901	2	2017	05105
2019	5105032005	3	2017	05105
2020	5105032008	3	2017	05105
2021	5105042002	7	2017	05105
2022	5105042003	10	2017	05105
2023	5105042013	3	2017	05105
2024	5105042015	4	2017	05105
2025	5105042016	12	2017	05105
2026	5105052014	62	2017	05105
2027	5105072011	10	2017	05105
2028	5105082001	65	2017	05105
2519	5107012010	25	2017	05107
2520	5107022004	102	2017	05107
2521	5107022009	2	2017	05107
2522	5107022013	133	2017	05107
2523	5107022016	112	2017	05107
2524	5107022901	10	2017	05107
2525	5107032002	62	2017	05107
2526	5107032003	157	2017	05107
2527	5107032006	176	2017	05107
2528	5107032007	29	2017	05107
2529	5107032011	29	2017	05107
2530	5107032012	254	2017	05107
2531	5107032014	12	2017	05107
2532	5107032015	3	2017	05107
3023	5201012002	31	2017	05201
3024	5201022004	10	2017	05201
3025	5201022005	5	2017	05201
3026	5201022901	3	2017	05201
3517	5301012009	20	2017	05301
3518	5301022009	30	2017	05301
3519	5301022014	13	2017	05301
3520	5301022901	5	2017	05301
3521	5301032003	1	2017	05301
3522	5301042003	57	2017	05301
3523	5301042005	30	2017	05301
3524	5301042007	7	2017	05301
3525	5301042015	4	2017	05301
3526	5301052001	105	2017	05301
3527	5301052002	1	2017	05301
3528	5301052010	3	2017	05301
3529	5301052011	50	2017	05301
3530	5301052013	270	2017	05301

2 Variable CASEN

2.1 Tabla de ingresos expandidos

Hemos calculado ya éste valor como conclusión del punto 1.1 de aquí

h_y_m_2017_censo <- readRDS("../corre_ing_exp-censo_casen/Ingresos_expandidos_rural_17.rds")
tablamadre <- head(h_y_m_2017_censo,50)
kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

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

3 Unión Censo-Casen

Integramos a la tabla censal de frecuencias la tabla de ingresos expandidos de la Casen.

comunas_con_ing_exp = merge( x = comuna_corr, y = h_y_m_2017_censo, by = "código", all.x = TRUE)

comunas_con_ing_exp <-comunas_con_ing_exp[!(is.na(comunas_con_ing_exp$Ingresos_expandidos)),]

r3_100 <- comunas_con_ing_exp
kbl(r3_100) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	código	zona	Freq	anio	comuna.x	promedio_i	año	personas	Ingresos_expandidos
1	05101	5101212004	4	2017	Valparaíso	251998.5	2017	296655	74756602991
2	05101	5101212901	2	2017	Valparaíso	251998.5	2017	296655	74756602991
3	05101	5101222003	8	2017	Valparaíso	251998.5	2017	296655	74756602991
4	05101	5101242001	1	2017	Valparaíso	251998.5	2017	296655	74756602991
5	05101	5101232002	45	2017	Valparaíso	251998.5	2017	296655	74756602991
6	05102	5102052012	31	2017	Casablanca	252317.7	2017	26867	6779018483
7	05102	5102032027	32	2017	Casablanca	252317.7	2017	26867	6779018483
8	05102	5102012029	24	2017	Casablanca	252317.7	2017	26867	6779018483
9	05102	5102052008	8	2017	Casablanca	252317.7	2017	26867	6779018483
10	05102	5102102033	79	2017	Casablanca	252317.7	2017	26867	6779018483
11	05102	5102042018	7	2017	Casablanca	252317.7	2017	26867	6779018483
12	05102	5102042019	7	2017	Casablanca	252317.7	2017	26867	6779018483
13	05102	5102062012	6	2017	Casablanca	252317.7	2017	26867	6779018483
14	05102	5102062042	2	2017	Casablanca	252317.7	2017	26867	6779018483
15	05102	5102052024	46	2017	Casablanca	252317.7	2017	26867	6779018483
16	05102	5102052901	1	2017	Casablanca	252317.7	2017	26867	6779018483
17	05102	5102032007	15	2017	Casablanca	252317.7	2017	26867	6779018483
18	05102	5102032011	32	2017	Casablanca	252317.7	2017	26867	6779018483
19	05102	5102082035	1	2017	Casablanca	252317.7	2017	26867	6779018483
20	05102	5102092003	44	2017	Casablanca	252317.7	2017	26867	6779018483
21	05102	5102092040	36	2017	Casablanca	252317.7	2017	26867	6779018483
22	05102	5102102003	7	2017	Casablanca	252317.7	2017	26867	6779018483
23	05102	5102012002	29	2017	Casablanca	252317.7	2017	26867	6779018483
24	05102	5102132901	7	2017	Casablanca	252317.7	2017	26867	6779018483
25	05102	5102012038	9	2017	Casablanca	252317.7	2017	26867	6779018483
26	05102	5102022010	1	2017	Casablanca	252317.7	2017	26867	6779018483
27	05102	5102022015	6	2017	Casablanca	252317.7	2017	26867	6779018483
28	05102	5102072034	2	2017	Casablanca	252317.7	2017	26867	6779018483
29	05102	5102082005	2	2017	Casablanca	252317.7	2017	26867	6779018483
30	05102	5102082013	41	2017	Casablanca	252317.7	2017	26867	6779018483
31	05102	5102082030	20	2017	Casablanca	252317.7	2017	26867	6779018483
32	05102	5102122037	8	2017	Casablanca	252317.7	2017	26867	6779018483
33	05102	5102122021	50	2017	Casablanca	252317.7	2017	26867	6779018483
34	05102	5102132002	4	2017	Casablanca	252317.7	2017	26867	6779018483
35	05102	5102132004	31	2017	Casablanca	252317.7	2017	26867	6779018483
36	05102	5102132020	36	2017	Casablanca	252317.7	2017	26867	6779018483
37	05102	5102132032	1	2017	Casablanca	252317.7	2017	26867	6779018483
38	05102	5102102036	16	2017	Casablanca	252317.7	2017	26867	6779018483
39	05102	5102112023	8	2017	Casablanca	252317.7	2017	26867	6779018483
40	05102	5102112026	71	2017	Casablanca	252317.7	2017	26867	6779018483
41	05102	5102022025	5	2017	Casablanca	252317.7	2017	26867	6779018483
42	05102	5102022031	6	2017	Casablanca	252317.7	2017	26867	6779018483
43	05102	5102022039	13	2017	Casablanca	252317.7	2017	26867	6779018483
44	05102	5102122009	51	2017	Casablanca	252317.7	2017	26867	6779018483
45	05102	5102122017	70	2017	Casablanca	252317.7	2017	26867	6779018483
46	05102	5102112028	13	2017	Casablanca	252317.7	2017	26867	6779018483
47	05102	5102112030	53	2017	Casablanca	252317.7	2017	26867	6779018483
54	05105	5105012015	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
55	05105	5105032005	3	2017	Puchuncaví	231606.0	2017	18546	4295363979
56	05105	5105032008	3	2017	Puchuncaví	231606.0	2017	18546	4295363979
57	05105	5105022012	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
58	05105	5105022901	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
59	05105	5105042013	3	2017	Puchuncaví	231606.0	2017	18546	4295363979
60	05105	5105042015	4	2017	Puchuncaví	231606.0	2017	18546	4295363979
61	05105	5105042002	7	2017	Puchuncaví	231606.0	2017	18546	4295363979
62	05105	5105042003	10	2017	Puchuncaví	231606.0	2017	18546	4295363979
63	05105	5105012004	28	2017	Puchuncaví	231606.0	2017	18546	4295363979
64	05105	5105012012	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
65	05105	5105082001	65	2017	Puchuncaví	231606.0	2017	18546	4295363979
66	05105	5105042016	12	2017	Puchuncaví	231606.0	2017	18546	4295363979
67	05105	5105052014	62	2017	Puchuncaví	231606.0	2017	18546	4295363979
68	05105	5105072011	10	2017	Puchuncaví	231606.0	2017	18546	4295363979
69	05107	5107012010	25	2017	Quintero	285125.8	2017	31923	9102071069
70	05107	5107022004	102	2017	Quintero	285125.8	2017	31923	9102071069
71	05107	5107022009	2	2017	Quintero	285125.8	2017	31923	9102071069
72	05107	5107022013	133	2017	Quintero	285125.8	2017	31923	9102071069
73	05107	5107022016	112	2017	Quintero	285125.8	2017	31923	9102071069
74	05107	5107032015	3	2017	Quintero	285125.8	2017	31923	9102071069
75	05107	5107032014	12	2017	Quintero	285125.8	2017	31923	9102071069
76	05107	5107022901	10	2017	Quintero	285125.8	2017	31923	9102071069
77	05107	5107032002	62	2017	Quintero	285125.8	2017	31923	9102071069
78	05107	5107032006	176	2017	Quintero	285125.8	2017	31923	9102071069
79	05107	5107032007	29	2017	Quintero	285125.8	2017	31923	9102071069
80	05107	5107032012	254	2017	Quintero	285125.8	2017	31923	9102071069
81	05107	5107032003	157	2017	Quintero	285125.8	2017	31923	9102071069
82	05107	5107032011	29	2017	Quintero	285125.8	2017	31923	9102071069
87	05301	5301012009	20	2017	Los Andes	280548.0	2017	66708	18714795984
88	05301	5301022009	30	2017	Los Andes	280548.0	2017	66708	18714795984
89	05301	5301052010	3	2017	Los Andes	280548.0	2017	66708	18714795984
90	05301	5301052011	50	2017	Los Andes	280548.0	2017	66708	18714795984
91	05301	5301052013	270	2017	Los Andes	280548.0	2017	66708	18714795984
92	05301	5301042003	57	2017	Los Andes	280548.0	2017	66708	18714795984
93	05301	5301022014	13	2017	Los Andes	280548.0	2017	66708	18714795984
94	05301	5301022901	5	2017	Los Andes	280548.0	2017	66708	18714795984
95	05301	5301032003	1	2017	Los Andes	280548.0	2017	66708	18714795984
96	05301	5301042015	4	2017	Los Andes	280548.0	2017	66708	18714795984
97	05301	5301052002	1	2017	Los Andes	280548.0	2017	66708	18714795984
98	05301	5301042005	30	2017	Los Andes	280548.0	2017	66708	18714795984
99	05301	5301042007	7	2017	Los Andes	280548.0	2017	66708	18714795984
100	05301	5301052001	105	2017	Los Andes	280548.0	2017	66708	18714795984
101	05302	5302012008	77	2017	Calle Larga	234044.6	2017	14832	3471349123
102	05302	5302042901	3	2017	Calle Larga	234044.6	2017	14832	3471349123
103	05302	5302052002	2	2017	Calle Larga	234044.6	2017	14832	3471349123
104	05302	5302052013	24	2017	Calle Larga	234044.6	2017	14832	3471349123
105	05302	5302022006	4	2017	Calle Larga	234044.6	2017	14832	3471349123
106	05302	5302012009	22	2017	Calle Larga	234044.6	2017	14832	3471349123
107	05302	5302012012	105	2017	Calle Larga	234044.6	2017	14832	3471349123
108	05302	5302012013	11	2017	Calle Larga	234044.6	2017	14832	3471349123
109	05302	5302032011	82	2017	Calle Larga	234044.6	2017	14832	3471349123
110	05302	5302042005	5	2017	Calle Larga	234044.6	2017	14832	3471349123
111	05302	5302022010	2	2017	Calle Larga	234044.6	2017	14832	3471349123
112	05302	5302022011	14	2017	Calle Larga	234044.6	2017	14832	3471349123
113	05302	5302042004	37	2017	Calle Larga	234044.6	2017	14832	3471349123
114	05303	5303012004	136	2017	Rinconada	246136.9	2017	10207	2512319225
115	05303	5303042005	3	2017	Rinconada	246136.9	2017	10207	2512319225
116	05303	5303042901	6	2017	Rinconada	246136.9	2017	10207	2512319225
117	05303	5303012013	3	2017	Rinconada	246136.9	2017	10207	2512319225
118	05303	5303022008	6	2017	Rinconada	246136.9	2017	10207	2512319225
119	05303	5303042003	27	2017	Rinconada	246136.9	2017	10207	2512319225
120	05303	5303012006	4	2017	Rinconada	246136.9	2017	10207	2512319225
121	05303	5303022009	74	2017	Rinconada	246136.9	2017	10207	2512319225
122	05303	5303022010	7	2017	Rinconada	246136.9	2017	10207	2512319225
123	05303	5303032001	4	2017	Rinconada	246136.9	2017	10207	2512319225
124	05303	5303042001	23	2017	Rinconada	246136.9	2017	10207	2512319225
125	05303	5303032014	12	2017	Rinconada	246136.9	2017	10207	2512319225
126	05304	5304012003	4	2017	San Esteban	211907.3	2017	18855	3995512770
127	05304	5304012008	17	2017	San Esteban	211907.3	2017	18855	3995512770
128	05304	5304012009	8	2017	San Esteban	211907.3	2017	18855	3995512770
129	05304	5304062005	7	2017	San Esteban	211907.3	2017	18855	3995512770
130	05304	5304062014	2	2017	San Esteban	211907.3	2017	18855	3995512770
131	05304	5304062016	14	2017	San Esteban	211907.3	2017	18855	3995512770
132	05304	5304062019	12	2017	San Esteban	211907.3	2017	18855	3995512770
133	05304	5304012024	9	2017	San Esteban	211907.3	2017	18855	3995512770
134	05304	5304022008	8	2017	San Esteban	211907.3	2017	18855	3995512770
135	05304	5304022012	51	2017	San Esteban	211907.3	2017	18855	3995512770
136	05304	5304022015	38	2017	San Esteban	211907.3	2017	18855	3995512770
137	05304	5304052022	8	2017	San Esteban	211907.3	2017	18855	3995512770
138	05304	5304092025	52	2017	San Esteban	211907.3	2017	18855	3995512770
139	05304	5304072003	84	2017	San Esteban	211907.3	2017	18855	3995512770
140	05304	5304072006	10	2017	San Esteban	211907.3	2017	18855	3995512770
141	05304	5304072007	8	2017	San Esteban	211907.3	2017	18855	3995512770
142	05304	5304062020	23	2017	San Esteban	211907.3	2017	18855	3995512770
143	05304	5304042002	1	2017	San Esteban	211907.3	2017	18855	3995512770
144	05304	5304042004	17	2017	San Esteban	211907.3	2017	18855	3995512770
145	05304	5304052018	24	2017	San Esteban	211907.3	2017	18855	3995512770
146	05304	5304032015	14	2017	San Esteban	211907.3	2017	18855	3995512770
147	05304	5304072010	2	2017	San Esteban	211907.3	2017	18855	3995512770
148	05304	5304072023	11	2017	San Esteban	211907.3	2017	18855	3995512770
149	05304	5304082010	26	2017	San Esteban	211907.3	2017	18855	3995512770
150	05304	5304092013	42	2017	San Esteban	211907.3	2017	18855	3995512770
151	05304	5304092011	25	2017	San Esteban	211907.3	2017	18855	3995512770
152	05401	5401012003	10	2017	La Ligua	172675.9	2017	35390	6111000517
153	05401	5401012009	2	2017	La Ligua	172675.9	2017	35390	6111000517
154	05401	5401012011	4	2017	La Ligua	172675.9	2017	35390	6111000517
155	05401	5401072012	40	2017	La Ligua	172675.9	2017	35390	6111000517
156	05401	5401082007	10	2017	La Ligua	172675.9	2017	35390	6111000517
157	05401	5401082015	42	2017	La Ligua	172675.9	2017	35390	6111000517
158	05401	5401082016	21	2017	La Ligua	172675.9	2017	35390	6111000517
159	05401	5401092014	96	2017	La Ligua	172675.9	2017	35390	6111000517
160	05401	5401102013	8	2017	La Ligua	172675.9	2017	35390	6111000517
161	05401	5401112012	15	2017	La Ligua	172675.9	2017	35390	6111000517
162	05401	5401122012	50	2017	La Ligua	172675.9	2017	35390	6111000517
163	05401	5401062020	13	2017	La Ligua	172675.9	2017	35390	6111000517
164	05401	5401062001	66	2017	La Ligua	172675.9	2017	35390	6111000517
165	05401	5401022003	21	2017	La Ligua	172675.9	2017	35390	6111000517
166	05401	5401032018	33	2017	La Ligua	172675.9	2017	35390	6111000517
167	05401	5401042005	10	2017	La Ligua	172675.9	2017	35390	6111000517
168	05401	5401132001	3	2017	La Ligua	172675.9	2017	35390	6111000517
169	05401	5401132002	5	2017	La Ligua	172675.9	2017	35390	6111000517
170	05401	5401052011	6	2017	La Ligua	172675.9	2017	35390	6111000517
171	05401	5401052019	7	2017	La Ligua	172675.9	2017	35390	6111000517
172	05401	5401052901	5	2017	La Ligua	172675.9	2017	35390	6111000517
173	05401	5401042010	4	2017	La Ligua	172675.9	2017	35390	6111000517
174	05402	5402032018	9	2017	Cabildo	212985.0	2017	19388	4129354103
175	05402	5402042007	4	2017	Cabildo	212985.0	2017	19388	4129354103
176	05402	5402052014	2	2017	Cabildo	212985.0	2017	19388	4129354103
177	05402	5402032016	22	2017	Cabildo	212985.0	2017	19388	4129354103
178	05402	5402042001	2	2017	Cabildo	212985.0	2017	19388	4129354103
179	05402	5402102017	20	2017	Cabildo	212985.0	2017	19388	4129354103
180	05402	5402102019	18	2017	Cabildo	212985.0	2017	19388	4129354103
181	05402	5402112002	7	2017	Cabildo	212985.0	2017	19388	4129354103
182	05402	5402102012	6	2017	Cabildo	212985.0	2017	19388	4129354103
183	05402	5402052901	5	2017	Cabildo	212985.0	2017	19388	4129354103
184	05402	5402062014	17	2017	Cabildo	212985.0	2017	19388	4129354103
185	05402	5402072011	18	2017	Cabildo	212985.0	2017	19388	4129354103
186	05402	5402052022	23	2017	Cabildo	212985.0	2017	19388	4129354103
187	05402	5402012003	14	2017	Cabildo	212985.0	2017	19388	4129354103
188	05402	5402022006	5	2017	Cabildo	212985.0	2017	19388	4129354103
189	05402	5402022018	1	2017	Cabildo	212985.0	2017	19388	4129354103
190	05402	5402092012	31	2017	Cabildo	212985.0	2017	19388	4129354103
191	05402	5402072023	37	2017	Cabildo	212985.0	2017	19388	4129354103
192	05402	5402082009	7	2017	Cabildo	212985.0	2017	19388	4129354103
193	05402	5402122015	2	2017	Cabildo	212985.0	2017	19388	4129354103
194	05402	5402142009	1	2017	Cabildo	212985.0	2017	19388	4129354103
195	05402	5402082013	3	2017	Cabildo	212985.0	2017	19388	4129354103
196	05402	5402092011	18	2017	Cabildo	212985.0	2017	19388	4129354103
202	05404	5404022012	25	2017	Petorca	270139.8	2017	9826	2654393853
203	05404	5404032011	13	2017	Petorca	270139.8	2017	9826	2654393853
204	05404	5404052025	1	2017	Petorca	270139.8	2017	9826	2654393853
205	05404	5404062001	2	2017	Petorca	270139.8	2017	9826	2654393853
206	05404	5404042004	40	2017	Petorca	270139.8	2017	9826	2654393853
207	05404	5404042017	2	2017	Petorca	270139.8	2017	9826	2654393853
208	05404	5404022003	8	2017	Petorca	270139.8	2017	9826	2654393853
209	05404	5404082027	7	2017	Petorca	270139.8	2017	9826	2654393853
210	05404	5404092019	7	2017	Petorca	270139.8	2017	9826	2654393853
211	05404	5404092023	3	2017	Petorca	270139.8	2017	9826	2654393853
212	05404	5404092029	11	2017	Petorca	270139.8	2017	9826	2654393853
213	05404	5404072015	29	2017	Petorca	270139.8	2017	9826	2654393853
214	05404	5404072021	2	2017	Petorca	270139.8	2017	9826	2654393853
215	05404	5404062005	1	2017	Petorca	270139.8	2017	9826	2654393853
216	05404	5404062016	9	2017	Petorca	270139.8	2017	9826	2654393853
217	05404	5404082024	45	2017	Petorca	270139.8	2017	9826	2654393853
218	05404	5404012008	1	2017	Petorca	270139.8	2017	9826	2654393853
219	05404	5404072901	2	2017	Petorca	270139.8	2017	9826	2654393853
220	05404	5404082022	12	2017	Petorca	270139.8	2017	9826	2654393853
221	05405	5405012009	6	2017	Zapallar	235661.4	2017	7339	1729518700
222	05405	5405022009	13	2017	Zapallar	235661.4	2017	7339	1729518700
223	05405	5405042002	161	2017	Zapallar	235661.4	2017	7339	1729518700
224	05405	5405032004	10	2017	Zapallar	235661.4	2017	7339	1729518700
225	05405	5405032007	39	2017	Zapallar	235661.4	2017	7339	1729518700
226	05405	5405032008	4	2017	Zapallar	235661.4	2017	7339	1729518700
227	05405	5405052003	15	2017	Zapallar	235661.4	2017	7339	1729518700
228	05501	5501062004	32	2017	Quillota	212067.6	2017	90517	19195726144
229	05501	5501062010	67	2017	Quillota	212067.6	2017	90517	19195726144
230	05501	5501072009	84	2017	Quillota	212067.6	2017	90517	19195726144
231	05501	5501082008	103	2017	Quillota	212067.6	2017	90517	19195726144
232	05501	5501062008	212	2017	Quillota	212067.6	2017	90517	19195726144
233	05501	5501052002	228	2017	Quillota	212067.6	2017	90517	19195726144
234	05501	5501052008	51	2017	Quillota	212067.6	2017	90517	19195726144
235	05501	5501062002	141	2017	Quillota	212067.6	2017	90517	19195726144
236	05501	5501092011	36	2017	Quillota	212067.6	2017	90517	19195726144
237	05501	5501102007	131	2017	Quillota	212067.6	2017	90517	19195726144
238	05501	5501082009	112	2017	Quillota	212067.6	2017	90517	19195726144
239	05501	5501092005	47	2017	Quillota	212067.6	2017	90517	19195726144
240	05501	5501112001	124	2017	Quillota	212067.6	2017	90517	19195726144
241	05501	5501132003	32	2017	Quillota	212067.6	2017	90517	19195726144
242	05502	5502042005	41	2017	Calera	226906.2	2017	50554	11471016698
243	05502	5502042901	3	2017	Calera	226906.2	2017	50554	11471016698
244	05502	5502032002	41	2017	Calera	226906.2	2017	50554	11471016698
245	05502	5502042004	20	2017	Calera	226906.2	2017	50554	11471016698
246	05503	5503012003	2	2017	Hijuelas	215402.0	2017	17988	3874650405
247	05503	5503012004	4	2017	Hijuelas	215402.0	2017	17988	3874650405
248	05503	5503012006	16	2017	Hijuelas	215402.0	2017	17988	3874650405
249	05503	5503022003	11	2017	Hijuelas	215402.0	2017	17988	3874650405
250	05503	5503052010	36	2017	Hijuelas	215402.0	2017	17988	3874650405
251	05503	5503052012	95	2017	Hijuelas	215402.0	2017	17988	3874650405
252	05503	5503032001	5	2017	Hijuelas	215402.0	2017	17988	3874650405
253	05503	5503032002	1	2017	Hijuelas	215402.0	2017	17988	3874650405
254	05503	5503032013	7	2017	Hijuelas	215402.0	2017	17988	3874650405
255	05503	5503022005	16	2017	Hijuelas	215402.0	2017	17988	3874650405
256	05503	5503042007	56	2017	Hijuelas	215402.0	2017	17988	3874650405
257	05503	5503042009	46	2017	Hijuelas	215402.0	2017	17988	3874650405
258	05503	5503042011	14	2017	Hijuelas	215402.0	2017	17988	3874650405
259	05503	5503032901	4	2017	Hijuelas	215402.0	2017	17988	3874650405
260	05504	5504022003	15	2017	La Cruz	243333.4	2017	22098	5377180726
261	05504	5504032002	49	2017	La Cruz	243333.4	2017	22098	5377180726
262	05504	5504042004	240	2017	La Cruz	243333.4	2017	22098	5377180726
263	05506	5506032002	28	2017	Nogales	219800.7	2017	22120	4861992055
264	05506	5506012005	7	2017	Nogales	219800.7	2017	22120	4861992055
265	05506	5506012008	14	2017	Nogales	219800.7	2017	22120	4861992055
266	05506	5506022007	71	2017	Nogales	219800.7	2017	22120	4861992055
267	05506	5506032003	45	2017	Nogales	219800.7	2017	22120	4861992055
268	05506	5506052004	76	2017	Nogales	219800.7	2017	22120	4861992055
269	05601	5601012017	2	2017	San Antonio	230261.5	2017	91350	21034388728
270	05601	5601022013	4	2017	San Antonio	230261.5	2017	91350	21034388728
271	05601	5601022014	1	2017	San Antonio	230261.5	2017	91350	21034388728
272	05601	5601022005	13	2017	San Antonio	230261.5	2017	91350	21034388728
273	05601	5601022009	42	2017	San Antonio	230261.5	2017	91350	21034388728
274	05601	5601012001	26	2017	San Antonio	230261.5	2017	91350	21034388728
275	05601	5601012005	2	2017	San Antonio	230261.5	2017	91350	21034388728
276	05601	5601032020	3	2017	San Antonio	230261.5	2017	91350	21034388728
277	05601	5601032901	7	2017	San Antonio	230261.5	2017	91350	21034388728
278	05601	5601062018	17	2017	San Antonio	230261.5	2017	91350	21034388728
279	05601	5601062019	32	2017	San Antonio	230261.5	2017	91350	21034388728
280	05601	5601062901	7	2017	San Antonio	230261.5	2017	91350	21034388728
281	05601	5601032007	1	2017	San Antonio	230261.5	2017	91350	21034388728
282	05601	5601022015	1	2017	San Antonio	230261.5	2017	91350	21034388728
283	05601	5601032002	31	2017	San Antonio	230261.5	2017	91350	21034388728
284	05601	5601032003	5	2017	San Antonio	230261.5	2017	91350	21034388728
285	05601	5601032019	90	2017	San Antonio	230261.5	2017	91350	21034388728
286	05601	5601032008	6	2017	San Antonio	230261.5	2017	91350	21034388728
287	05601	5601032011	1	2017	San Antonio	230261.5	2017	91350	21034388728
288	05601	5601032018	87	2017	San Antonio	230261.5	2017	91350	21034388728
289	05602	5602012002	27	2017	Algarrobo	218057.0	2017	13817	3012893845
290	05602	5602022012	53	2017	Algarrobo	218057.0	2017	13817	3012893845
291	05602	5602032010	9	2017	Algarrobo	218057.0	2017	13817	3012893845
292	05602	5602012005	44	2017	Algarrobo	218057.0	2017	13817	3012893845
293	05602	5602012006	56	2017	Algarrobo	218057.0	2017	13817	3012893845
294	05602	5602012007	35	2017	Algarrobo	218057.0	2017	13817	3012893845
295	05602	5602012003	2	2017	Algarrobo	218057.0	2017	13817	3012893845
296	05602	5602012009	77	2017	Algarrobo	218057.0	2017	13817	3012893845
297	05602	5602022004	12	2017	Algarrobo	218057.0	2017	13817	3012893845
298	05602	5602022011	160	2017	Algarrobo	218057.0	2017	13817	3012893845
299	05602	5602012008	14	2017	Algarrobo	218057.0	2017	13817	3012893845
300	05603	5603012001	2	2017	Cartagena	246517.9	2017	22738	5605324190
301	05603	5603012002	4	2017	Cartagena	246517.9	2017	22738	5605324190
302	05603	5603012004	6	2017	Cartagena	246517.9	2017	22738	5605324190
303	05603	5603022013	4	2017	Cartagena	246517.9	2017	22738	5605324190
304	05603	5603022014	3	2017	Cartagena	246517.9	2017	22738	5605324190
305	05603	5603032003	2	2017	Cartagena	246517.9	2017	22738	5605324190
306	05603	5603032010	2	2017	Cartagena	246517.9	2017	22738	5605324190
307	05603	5603032017	1	2017	Cartagena	246517.9	2017	22738	5605324190
308	05603	5603012007	4	2017	Cartagena	246517.9	2017	22738	5605324190
309	05603	5603012012	45	2017	Cartagena	246517.9	2017	22738	5605324190
310	05603	5603012013	15	2017	Cartagena	246517.9	2017	22738	5605324190
311	05603	5603012016	11	2017	Cartagena	246517.9	2017	22738	5605324190
312	05603	5603012901	7	2017	Cartagena	246517.9	2017	22738	5605324190
313	05603	5603022008	3	2017	Cartagena	246517.9	2017	22738	5605324190
314	05603	5603022009	4	2017	Cartagena	246517.9	2017	22738	5605324190
315	05603	5603022011	14	2017	Cartagena	246517.9	2017	22738	5605324190
324	05606	5606012003	1	2017	Santo Domingo	250404.5	2017	10900	2729409577
325	05606	5606012004	34	2017	Santo Domingo	250404.5	2017	10900	2729409577
326	05606	5606012007	5	2017	Santo Domingo	250404.5	2017	10900	2729409577
327	05606	5606012008	2	2017	Santo Domingo	250404.5	2017	10900	2729409577
328	05606	5606012010	80	2017	Santo Domingo	250404.5	2017	10900	2729409577
329	05606	5606012011	33	2017	Santo Domingo	250404.5	2017	10900	2729409577
330	05606	5606012013	2	2017	Santo Domingo	250404.5	2017	10900	2729409577
331	05606	5606012019	9	2017	Santo Domingo	250404.5	2017	10900	2729409577
332	05606	5606012020	189	2017	Santo Domingo	250404.5	2017	10900	2729409577
333	05606	5606012901	2	2017	Santo Domingo	250404.5	2017	10900	2729409577
334	05606	5606022006	91	2017	Santo Domingo	250404.5	2017	10900	2729409577
335	05606	5606022018	4	2017	Santo Domingo	250404.5	2017	10900	2729409577
336	05606	5606022901	1	2017	Santo Domingo	250404.5	2017	10900	2729409577
337	05606	5606032001	6	2017	Santo Domingo	250404.5	2017	10900	2729409577
338	05606	5606032002	23	2017	Santo Domingo	250404.5	2017	10900	2729409577
339	05606	5606032015	2	2017	Santo Domingo	250404.5	2017	10900	2729409577
340	05606	5606032016	9	2017	Santo Domingo	250404.5	2017	10900	2729409577
341	05606	5606032017	4	2017	Santo Domingo	250404.5	2017	10900	2729409577
342	05701	5701012010	15	2017	San Felipe	240842.4	2017	76844	18507290899
343	05701	5701032011	19	2017	San Felipe	240842.4	2017	76844	18507290899
344	05701	5701042001	61	2017	San Felipe	240842.4	2017	76844	18507290899
345	05701	5701052017	5	2017	San Felipe	240842.4	2017	76844	18507290899
346	05701	5701052020	8	2017	San Felipe	240842.4	2017	76844	18507290899
347	05701	5701062005	42	2017	San Felipe	240842.4	2017	76844	18507290899
348	05701	5701062007	5	2017	San Felipe	240842.4	2017	76844	18507290899
349	05701	5701062013	17	2017	San Felipe	240842.4	2017	76844	18507290899
350	05701	5701062018	31	2017	San Felipe	240842.4	2017	76844	18507290899
351	05701	5701072005	16	2017	San Felipe	240842.4	2017	76844	18507290899
352	05701	5701072007	3	2017	San Felipe	240842.4	2017	76844	18507290899
353	05701	5701072009	2	2017	San Felipe	240842.4	2017	76844	18507290899
354	05701	5701072012	32	2017	San Felipe	240842.4	2017	76844	18507290899
355	05701	5701082007	11	2017	San Felipe	240842.4	2017	76844	18507290899
356	05701	5701082009	51	2017	San Felipe	240842.4	2017	76844	18507290899
357	05701	5701082014	10	2017	San Felipe	240842.4	2017	76844	18507290899
358	05701	5701082019	20	2017	San Felipe	240842.4	2017	76844	18507290899
359	05701	5701082021	8	2017	San Felipe	240842.4	2017	76844	18507290899
360	05701	5701092004	32	2017	San Felipe	240842.4	2017	76844	18507290899
361	05701	5701102003	27	2017	San Felipe	240842.4	2017	76844	18507290899
362	05701	5701102008	52	2017	San Felipe	240842.4	2017	76844	18507290899
363	05701	5701102016	46	2017	San Felipe	240842.4	2017	76844	18507290899
364	05701	5701102022	72	2017	San Felipe	240842.4	2017	76844	18507290899
365	05702	5702012001	6	2017	Catemu	204903.4	2017	13998	2868237147
366	05702	5702012002	8	2017	Catemu	204903.4	2017	13998	2868237147
367	05702	5702012012	3	2017	Catemu	204903.4	2017	13998	2868237147
368	05702	5702012018	11	2017	Catemu	204903.4	2017	13998	2868237147
369	05702	5702022003	19	2017	Catemu	204903.4	2017	13998	2868237147
370	05702	5702022005	14	2017	Catemu	204903.4	2017	13998	2868237147
371	05702	5702022006	34	2017	Catemu	204903.4	2017	13998	2868237147
372	05702	5702022009	14	2017	Catemu	204903.4	2017	13998	2868237147
373	05702	5702032011	22	2017	Catemu	204903.4	2017	13998	2868237147
374	05702	5702042004	11	2017	Catemu	204903.4	2017	13998	2868237147
375	05702	5702042008	2	2017	Catemu	204903.4	2017	13998	2868237147
376	05702	5702042010	9	2017	Catemu	204903.4	2017	13998	2868237147
377	05702	5702042901	1	2017	Catemu	204903.4	2017	13998	2868237147
378	05702	5702052014	10	2017	Catemu	204903.4	2017	13998	2868237147
379	05702	5702052015	20	2017	Catemu	204903.4	2017	13998	2868237147
380	05702	5702052016	7	2017	Catemu	204903.4	2017	13998	2868237147
381	05702	5702052017	19	2017	Catemu	204903.4	2017	13998	2868237147
382	05702	5702062001	3	2017	Catemu	204903.4	2017	13998	2868237147
383	05703	5703022003	12	2017	Llaillay	257020.9	2017	24608	6324771348
384	05703	5703022004	48	2017	Llaillay	257020.9	2017	24608	6324771348
385	05703	5703022006	21	2017	Llaillay	257020.9	2017	24608	6324771348
386	05703	5703032001	134	2017	Llaillay	257020.9	2017	24608	6324771348
387	05703	5703032005	23	2017	Llaillay	257020.9	2017	24608	6324771348
388	05703	5703032008	21	2017	Llaillay	257020.9	2017	24608	6324771348
389	05703	5703032010	5	2017	Llaillay	257020.9	2017	24608	6324771348
390	05703	5703042002	23	2017	Llaillay	257020.9	2017	24608	6324771348
391	05703	5703042010	19	2017	Llaillay	257020.9	2017	24608	6324771348
392	05704	5704012006	77	2017	Panquehue	210643.4	2017	7273	1532009468
393	05704	5704022002	22	2017	Panquehue	210643.4	2017	7273	1532009468
394	05704	5704022005	2	2017	Panquehue	210643.4	2017	7273	1532009468
395	05704	5704022009	12	2017	Panquehue	210643.4	2017	7273	1532009468
396	05704	5704032004	22	2017	Panquehue	210643.4	2017	7273	1532009468
397	05704	5704032008	9	2017	Panquehue	210643.4	2017	7273	1532009468
398	05704	5704032010	4	2017	Panquehue	210643.4	2017	7273	1532009468
399	05704	5704042001	30	2017	Panquehue	210643.4	2017	7273	1532009468
400	05704	5704042003	12	2017	Panquehue	210643.4	2017	7273	1532009468
401	05704	5704042007	49	2017	Panquehue	210643.4	2017	7273	1532009468
402	05705	5705012011	54	2017	Putaendo	207222.5	2017	16754	3471806107
403	05705	5705022013	218	2017	Putaendo	207222.5	2017	16754	3471806107
404	05705	5705032006	89	2017	Putaendo	207222.5	2017	16754	3471806107
405	05705	5705042004	68	2017	Putaendo	207222.5	2017	16754	3471806107
406	05705	5705042009	2	2017	Putaendo	207222.5	2017	16754	3471806107
407	05705	5705042012	120	2017	Putaendo	207222.5	2017	16754	3471806107
408	05705	5705052002	1	2017	Putaendo	207222.5	2017	16754	3471806107
409	05705	5705062010	30	2017	Putaendo	207222.5	2017	16754	3471806107
410	05705	5705072001	4	2017	Putaendo	207222.5	2017	16754	3471806107
411	05705	5705072003	6	2017	Putaendo	207222.5	2017	16754	3471806107
412	05705	5705072004	4	2017	Putaendo	207222.5	2017	16754	3471806107
413	05705	5705072005	45	2017	Putaendo	207222.5	2017	16754	3471806107
414	05705	5705072007	26	2017	Putaendo	207222.5	2017	16754	3471806107
415	05705	5705072008	2	2017	Putaendo	207222.5	2017	16754	3471806107
416	05706	5706012017	23	2017	Santa María	254903.6	2017	15241	3884985562
417	05706	5706022010	116	2017	Santa María	254903.6	2017	15241	3884985562
418	05706	5706032003	14	2017	Santa María	254903.6	2017	15241	3884985562
419	05706	5706032004	9	2017	Santa María	254903.6	2017	15241	3884985562
420	05706	5706032005	5	2017	Santa María	254903.6	2017	15241	3884985562
421	05706	5706032011	19	2017	Santa María	254903.6	2017	15241	3884985562
422	05706	5706032015	7	2017	Santa María	254903.6	2017	15241	3884985562
423	05706	5706042002	6	2017	Santa María	254903.6	2017	15241	3884985562
424	05706	5706042012	6	2017	Santa María	254903.6	2017	15241	3884985562
425	05706	5706042014	5	2017	Santa María	254903.6	2017	15241	3884985562
426	05706	5706042901	12	2017	Santa María	254903.6	2017	15241	3884985562
427	05706	5706052001	3	2017	Santa María	254903.6	2017	15241	3884985562
428	05706	5706052002	5	2017	Santa María	254903.6	2017	15241	3884985562
429	05706	5706052006	4	2017	Santa María	254903.6	2017	15241	3884985562
430	05706	5706052007	3	2017	Santa María	254903.6	2017	15241	3884985562
431	05706	5706052008	4	2017	Santa María	254903.6	2017	15241	3884985562
432	05706	5706052009	56	2017	Santa María	254903.6	2017	15241	3884985562
433	05706	5706052014	6	2017	Santa María	254903.6	2017	15241	3884985562
434	05706	5706062009	31	2017	Santa María	254903.6	2017	15241	3884985562
435	05706	5706062013	3	2017	Santa María	254903.6	2017	15241	3884985562
436	05706	5706062017	21	2017	Santa María	254903.6	2017	15241	3884985562
437	05801	5801032005	2	2017	Quilpué	296519.4	2017	151708	44984360344
438	05801	5801032008	41	2017	Quilpué	296519.4	2017	151708	44984360344
439	05801	5801032012	22	2017	Quilpué	296519.4	2017	151708	44984360344
440	05801	5801032013	81	2017	Quilpué	296519.4	2017	151708	44984360344
441	05801	5801032014	19	2017	Quilpué	296519.4	2017	151708	44984360344
442	05801	5801042002	27	2017	Quilpué	296519.4	2017	151708	44984360344
443	05801	5801052002	19	2017	Quilpué	296519.4	2017	151708	44984360344
444	05801	5801062010	11	2017	Quilpué	296519.4	2017	151708	44984360344
445	05801	5801062016	77	2017	Quilpué	296519.4	2017	151708	44984360344
446	05801	5801062901	6	2017	Quilpué	296519.4	2017	151708	44984360344
447	05801	5801072901	1	2017	Quilpué	296519.4	2017	151708	44984360344
448	05801	5801102003	1	2017	Quilpué	296519.4	2017	151708	44984360344
449	05801	5801102018	4	2017	Quilpué	296519.4	2017	151708	44984360344
450	05802	5802012004	2	2017	Limache	251682.2	2017	46121	11607834893
451	05802	5802012016	47	2017	Limache	251682.2	2017	46121	11607834893
452	05802	5802022003	28	2017	Limache	251682.2	2017	46121	11607834893
453	05802	5802022009	102	2017	Limache	251682.2	2017	46121	11607834893
454	05802	5802022013	146	2017	Limache	251682.2	2017	46121	11607834893
455	05802	5802022017	34	2017	Limache	251682.2	2017	46121	11607834893
456	05802	5802022019	57	2017	Limache	251682.2	2017	46121	11607834893
457	05802	5802032006	7	2017	Limache	251682.2	2017	46121	11607834893
458	05802	5802032010	20	2017	Limache	251682.2	2017	46121	11607834893
459	05802	5802032011	39	2017	Limache	251682.2	2017	46121	11607834893
460	05802	5802042014	6	2017	Limache	251682.2	2017	46121	11607834893
461	05802	5802052002	14	2017	Limache	251682.2	2017	46121	11607834893
462	05802	5802062001	147	2017	Limache	251682.2	2017	46121	11607834893
463	05802	5802062012	186	2017	Limache	251682.2	2017	46121	11607834893
464	05802	5802062015	6	2017	Limache	251682.2	2017	46121	11607834893
465	05802	5802072008	3	2017	Limache	251682.2	2017	46121	11607834893
466	05802	5802082005	54	2017	Limache	251682.2	2017	46121	11607834893
467	05802	5802082018	83	2017	Limache	251682.2	2017	46121	11607834893
468	05803	5803012002	4	2017	Olmué	198292.3	2017	17516	3473287749
469	05803	5803012010	8	2017	Olmué	198292.3	2017	17516	3473287749
470	05803	5803012011	57	2017	Olmué	198292.3	2017	17516	3473287749
471	05803	5803022004	71	2017	Olmué	198292.3	2017	17516	3473287749
472	05803	5803022009	27	2017	Olmué	198292.3	2017	17516	3473287749
473	05803	5803032006	20	2017	Olmué	198292.3	2017	17516	3473287749
474	05803	5803032008	62	2017	Olmué	198292.3	2017	17516	3473287749
475	05803	5803032013	77	2017	Olmué	198292.3	2017	17516	3473287749
476	05803	5803042007	68	2017	Olmué	198292.3	2017	17516	3473287749
477	05803	5803042012	42	2017	Olmué	198292.3	2017	17516	3473287749
478	05803	5803052005	32	2017	Olmué	198292.3	2017	17516	3473287749
479	05803	5803052013	96	2017	Olmué	198292.3	2017	17516	3473287749
480	05803	5803052901	7	2017	Olmué	198292.3	2017	17516	3473287749
481	05804	5804032001	4	2017	Villa Alemana	249779.9	2017	126548	31609146219
482	05804	5804032006	51	2017	Villa Alemana	249779.9	2017	126548	31609146219
483	05804	5804032009	3	2017	Villa Alemana	249779.9	2017	126548	31609146219
484	05804	5804032010	9	2017	Villa Alemana	249779.9	2017	126548	31609146219
485	05804	5804032901	3	2017	Villa Alemana	249779.9	2017	126548	31609146219
486	05804	5804062004	37	2017	Villa Alemana	249779.9	2017	126548	31609146219
487	05804	5804062007	27	2017	Villa Alemana	249779.9	2017	126548	31609146219
488	05804	5804062014	80	2017	Villa Alemana	249779.9	2017	126548	31609146219
489	05804	5804072008	2	2017	Villa Alemana	249779.9	2017	126548	31609146219
490	05804	5804082901	1	2017	Villa Alemana	249779.9	2017	126548	31609146219

4 Proporción poblacional zonal respecto a la comunal

Del censo obtenemos la cantidad de población a nivel de zona y estimamos su proporción a nivel comunal. Ya hemos calculado ésta proporción aquí.

prop_pob <- readRDS("../tabla_de_prop_pob.rds")
names(prop_pob)[1] <- "zona"
names(prop_pob)[3] <- "p_poblacional" 

Veamos los 100 primeros registros:

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

zona	Freq	p_poblacional	código
1101011001	2491	0.0130100	01101
1101011002	1475	0.0077036	01101
1101021001	1003	0.0052385	01101
1101021002	54	0.0002820	01101
1101021003	2895	0.0151200	01101
1101021004	2398	0.0125243	01101
1101021005	4525	0.0236332	01101
1101031001	2725	0.0142321	01101
1101031002	3554	0.0185618	01101
1101031003	5246	0.0273988	01101
1101031004	3389	0.0177001	01101
1101041001	1800	0.0094010	01101
1101041002	2538	0.0132555	01101
1101041003	3855	0.0201339	01101
1101041004	5663	0.0295767	01101
1101041005	4162	0.0217373	01101
1101041006	2689	0.0140441	01101
1101051001	3296	0.0172144	01101
1101051002	4465	0.0233198	01101
1101051003	4656	0.0243174	01101
1101051004	2097	0.0109522	01101
1101051005	3569	0.0186402	01101
1101051006	2741	0.0143157	01101
1101061001	1625	0.0084871	01101
1101061002	4767	0.0248971	01101
1101061003	4826	0.0252053	01101
1101061004	4077	0.0212934	01101
1101061005	2166	0.0113126	01101
1101071001	2324	0.0121378	01101
1101071002	2801	0.0146291	01101
1101071003	3829	0.0199981	01101
1101071004	1987	0.0103777	01101
1101081001	5133	0.0268087	01101
1101081002	3233	0.0168853	01101
1101081003	2122	0.0110828	01101
1101081004	2392	0.0124929	01101
1101092001	57	0.0002977	01101
1101092004	247	0.0012900	01101
1101092005	76	0.0003969	01101
1101092006	603	0.0031494	01101
1101092007	84	0.0004387	01101
1101092010	398	0.0020787	01101
1101092012	58	0.0003029	01101
1101092014	23	0.0001201	01101
1101092016	20	0.0001045	01101
1101092017	8	0.0000418	01101
1101092018	74	0.0003865	01101
1101092019	25	0.0001306	01101
1101092021	177	0.0009244	01101
1101092022	23	0.0001201	01101
1101092023	288	0.0015042	01101
1101092024	14	0.0000731	01101
1101092901	30	0.0001567	01101
1101101001	2672	0.0139553	01101
1101101002	4398	0.0229699	01101
1101101003	4524	0.0236280	01101
1101101004	3544	0.0185096	01101
1101101005	4911	0.0256492	01101
1101101006	3688	0.0192617	01101
1101111001	3886	0.0202958	01101
1101111002	2312	0.0120751	01101
1101111003	4874	0.0254560	01101
1101111004	4543	0.0237272	01101
1101111005	4331	0.0226200	01101
1101111006	3253	0.0169898	01101
1101111007	4639	0.0242286	01101
1101111008	4881	0.0254925	01101
1101111009	5006	0.0261454	01101
1101111010	366	0.0019115	01101
1101111011	4351	0.0227244	01101
1101111012	2926	0.0152819	01101
1101111013	3390	0.0177053	01101
1101111014	2940	0.0153550	01101
1101112003	33	0.0001724	01101
1101112013	104	0.0005432	01101
1101112019	34	0.0001776	01101
1101112025	21	0.0001097	01101
1101112901	6	0.0000313	01101
1101991999	1062	0.0055466	01101
1107011001	4104	0.0378685	01107
1107011002	4360	0.0402307	01107
1107011003	8549	0.0788835	01107
1107012003	3	0.0000277	01107
1107012901	17	0.0001569	01107
1107021001	6701	0.0618316	01107
1107021002	3971	0.0366413	01107
1107021003	6349	0.0585836	01107
1107021004	5125	0.0472895	01107
1107021005	4451	0.0410704	01107
1107021006	3864	0.0356540	01107
1107021007	5235	0.0483045	01107
1107021008	4566	0.0421315	01107
1107031001	4195	0.0387082	01107
1107031002	7099	0.0655040	01107
1107031003	4720	0.0435525	01107
1107032005	38	0.0003506	01107
1107032006	2399	0.0221361	01107
1107032008	4	0.0000369	01107
1107041001	3630	0.0334948	01107
1107041002	5358	0.0494394	01107

5 Ingreso medio

Deseamos el valor del ingreso promedio a nivel comunal, pero expandido a nivel zonal. Ésta información está contenida en el campo promedio_i de la tabla obtenida en el punto 3.

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

	código	zona	Freq	anio	comuna.x	promedio_i	año	personas	Ingresos_expandidos
1	05101	5101212004	4	2017	Valparaíso	251998.5	2017	296655	74756602991
2	05101	5101212901	2	2017	Valparaíso	251998.5	2017	296655	74756602991
3	05101	5101222003	8	2017	Valparaíso	251998.5	2017	296655	74756602991
4	05101	5101242001	1	2017	Valparaíso	251998.5	2017	296655	74756602991
5	05101	5101232002	45	2017	Valparaíso	251998.5	2017	296655	74756602991
6	05102	5102052012	31	2017	Casablanca	252317.7	2017	26867	6779018483
7	05102	5102032027	32	2017	Casablanca	252317.7	2017	26867	6779018483
8	05102	5102012029	24	2017	Casablanca	252317.7	2017	26867	6779018483
9	05102	5102052008	8	2017	Casablanca	252317.7	2017	26867	6779018483
10	05102	5102102033	79	2017	Casablanca	252317.7	2017	26867	6779018483
11	05102	5102042018	7	2017	Casablanca	252317.7	2017	26867	6779018483
12	05102	5102042019	7	2017	Casablanca	252317.7	2017	26867	6779018483
13	05102	5102062012	6	2017	Casablanca	252317.7	2017	26867	6779018483
14	05102	5102062042	2	2017	Casablanca	252317.7	2017	26867	6779018483
15	05102	5102052024	46	2017	Casablanca	252317.7	2017	26867	6779018483
16	05102	5102052901	1	2017	Casablanca	252317.7	2017	26867	6779018483
17	05102	5102032007	15	2017	Casablanca	252317.7	2017	26867	6779018483
18	05102	5102032011	32	2017	Casablanca	252317.7	2017	26867	6779018483
19	05102	5102082035	1	2017	Casablanca	252317.7	2017	26867	6779018483
20	05102	5102092003	44	2017	Casablanca	252317.7	2017	26867	6779018483
21	05102	5102092040	36	2017	Casablanca	252317.7	2017	26867	6779018483
22	05102	5102102003	7	2017	Casablanca	252317.7	2017	26867	6779018483
23	05102	5102012002	29	2017	Casablanca	252317.7	2017	26867	6779018483
24	05102	5102132901	7	2017	Casablanca	252317.7	2017	26867	6779018483
25	05102	5102012038	9	2017	Casablanca	252317.7	2017	26867	6779018483
26	05102	5102022010	1	2017	Casablanca	252317.7	2017	26867	6779018483
27	05102	5102022015	6	2017	Casablanca	252317.7	2017	26867	6779018483
28	05102	5102072034	2	2017	Casablanca	252317.7	2017	26867	6779018483
29	05102	5102082005	2	2017	Casablanca	252317.7	2017	26867	6779018483
30	05102	5102082013	41	2017	Casablanca	252317.7	2017	26867	6779018483
31	05102	5102082030	20	2017	Casablanca	252317.7	2017	26867	6779018483
32	05102	5102122037	8	2017	Casablanca	252317.7	2017	26867	6779018483
33	05102	5102122021	50	2017	Casablanca	252317.7	2017	26867	6779018483
34	05102	5102132002	4	2017	Casablanca	252317.7	2017	26867	6779018483
35	05102	5102132004	31	2017	Casablanca	252317.7	2017	26867	6779018483
36	05102	5102132020	36	2017	Casablanca	252317.7	2017	26867	6779018483
37	05102	5102132032	1	2017	Casablanca	252317.7	2017	26867	6779018483
38	05102	5102102036	16	2017	Casablanca	252317.7	2017	26867	6779018483
39	05102	5102112023	8	2017	Casablanca	252317.7	2017	26867	6779018483
40	05102	5102112026	71	2017	Casablanca	252317.7	2017	26867	6779018483
41	05102	5102022025	5	2017	Casablanca	252317.7	2017	26867	6779018483
42	05102	5102022031	6	2017	Casablanca	252317.7	2017	26867	6779018483
43	05102	5102022039	13	2017	Casablanca	252317.7	2017	26867	6779018483
44	05102	5102122009	51	2017	Casablanca	252317.7	2017	26867	6779018483
45	05102	5102122017	70	2017	Casablanca	252317.7	2017	26867	6779018483
46	05102	5102112028	13	2017	Casablanca	252317.7	2017	26867	6779018483
47	05102	5102112030	53	2017	Casablanca	252317.7	2017	26867	6779018483
54	05105	5105012015	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
55	05105	5105032005	3	2017	Puchuncaví	231606.0	2017	18546	4295363979
56	05105	5105032008	3	2017	Puchuncaví	231606.0	2017	18546	4295363979
57	05105	5105022012	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
58	05105	5105022901	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
59	05105	5105042013	3	2017	Puchuncaví	231606.0	2017	18546	4295363979
60	05105	5105042015	4	2017	Puchuncaví	231606.0	2017	18546	4295363979
61	05105	5105042002	7	2017	Puchuncaví	231606.0	2017	18546	4295363979
62	05105	5105042003	10	2017	Puchuncaví	231606.0	2017	18546	4295363979
63	05105	5105012004	28	2017	Puchuncaví	231606.0	2017	18546	4295363979
64	05105	5105012012	2	2017	Puchuncaví	231606.0	2017	18546	4295363979
65	05105	5105082001	65	2017	Puchuncaví	231606.0	2017	18546	4295363979
66	05105	5105042016	12	2017	Puchuncaví	231606.0	2017	18546	4295363979
67	05105	5105052014	62	2017	Puchuncaví	231606.0	2017	18546	4295363979
68	05105	5105072011	10	2017	Puchuncaví	231606.0	2017	18546	4295363979
69	05107	5107012010	25	2017	Quintero	285125.8	2017	31923	9102071069
70	05107	5107022004	102	2017	Quintero	285125.8	2017	31923	9102071069
71	05107	5107022009	2	2017	Quintero	285125.8	2017	31923	9102071069
72	05107	5107022013	133	2017	Quintero	285125.8	2017	31923	9102071069
73	05107	5107022016	112	2017	Quintero	285125.8	2017	31923	9102071069
74	05107	5107032015	3	2017	Quintero	285125.8	2017	31923	9102071069
75	05107	5107032014	12	2017	Quintero	285125.8	2017	31923	9102071069
76	05107	5107022901	10	2017	Quintero	285125.8	2017	31923	9102071069
77	05107	5107032002	62	2017	Quintero	285125.8	2017	31923	9102071069
78	05107	5107032006	176	2017	Quintero	285125.8	2017	31923	9102071069
79	05107	5107032007	29	2017	Quintero	285125.8	2017	31923	9102071069
80	05107	5107032012	254	2017	Quintero	285125.8	2017	31923	9102071069
81	05107	5107032003	157	2017	Quintero	285125.8	2017	31923	9102071069
82	05107	5107032011	29	2017	Quintero	285125.8	2017	31923	9102071069
87	05301	5301012009	20	2017	Los Andes	280548.0	2017	66708	18714795984
88	05301	5301022009	30	2017	Los Andes	280548.0	2017	66708	18714795984
89	05301	5301052010	3	2017	Los Andes	280548.0	2017	66708	18714795984
90	05301	5301052011	50	2017	Los Andes	280548.0	2017	66708	18714795984
91	05301	5301052013	270	2017	Los Andes	280548.0	2017	66708	18714795984
92	05301	5301042003	57	2017	Los Andes	280548.0	2017	66708	18714795984
93	05301	5301022014	13	2017	Los Andes	280548.0	2017	66708	18714795984
94	05301	5301022901	5	2017	Los Andes	280548.0	2017	66708	18714795984
95	05301	5301032003	1	2017	Los Andes	280548.0	2017	66708	18714795984
96	05301	5301042015	4	2017	Los Andes	280548.0	2017	66708	18714795984
97	05301	5301052002	1	2017	Los Andes	280548.0	2017	66708	18714795984
98	05301	5301042005	30	2017	Los Andes	280548.0	2017	66708	18714795984
99	05301	5301042007	7	2017	Los Andes	280548.0	2017	66708	18714795984
100	05301	5301052001	105	2017	Los Andes	280548.0	2017	66708	18714795984
101	05302	5302012008	77	2017	Calle Larga	234044.6	2017	14832	3471349123
102	05302	5302042901	3	2017	Calle Larga	234044.6	2017	14832	3471349123
103	05302	5302052002	2	2017	Calle Larga	234044.6	2017	14832	3471349123
104	05302	5302052013	24	2017	Calle Larga	234044.6	2017	14832	3471349123
105	05302	5302022006	4	2017	Calle Larga	234044.6	2017	14832	3471349123
106	05302	5302012009	22	2017	Calle Larga	234044.6	2017	14832	3471349123
107	05302	5302012012	105	2017	Calle Larga	234044.6	2017	14832	3471349123
108	05302	5302012013	11	2017	Calle Larga	234044.6	2017	14832	3471349123
109	05302	5302032011	82	2017	Calle Larga	234044.6	2017	14832	3471349123
110	05302	5302042005	5	2017	Calle Larga	234044.6	2017	14832	3471349123

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
5101212004	05101	4	2017	Valparaíso	251998.5	2017	296655	74756602991	40	0.0001348	05101
5101212901	05101	2	2017	Valparaíso	251998.5	2017	296655	74756602991	25	0.0000843	05101
5101222003	05101	8	2017	Valparaíso	251998.5	2017	296655	74756602991	87	0.0002933	05101
5101232002	05101	45	2017	Valparaíso	251998.5	2017	296655	74756602991	558	0.0018810	05101
5101242001	05101	1	2017	Valparaíso	251998.5	2017	296655	74756602991	27	0.0000910	05101
5102012002	05102	29	2017	Casablanca	252317.7	2017	26867	6779018483	145	0.0053970	05102
5102012029	05102	24	2017	Casablanca	252317.7	2017	26867	6779018483	115	0.0042803	05102
5102012038	05102	9	2017	Casablanca	252317.7	2017	26867	6779018483	81	0.0030149	05102
5102022010	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	31	0.0011538	05102
5102022015	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102
5102022025	05102	5	2017	Casablanca	252317.7	2017	26867	6779018483	49	0.0018238	05102
5102022031	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	202	0.0075185	05102
5102022039	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	327	0.0121711	05102
5102032007	05102	15	2017	Casablanca	252317.7	2017	26867	6779018483	55	0.0020471	05102
5102032011	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	913	0.0339822	05102
5102032027	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	403	0.0149998	05102
5102042018	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102
5102042019	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	62	0.0023077	05102
5102052008	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	129	0.0048014	05102
5102052012	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	465	0.0173075	05102
5102052024	05102	46	2017	Casablanca	252317.7	2017	26867	6779018483	259	0.0096401	05102
5102052901	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	38	0.0014144	05102
5102062012	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	131	0.0048759	05102
5102062042	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	25	0.0009305	05102
5102072034	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102
5102082005	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	13	0.0004839	05102
5102082013	05102	41	2017	Casablanca	252317.7	2017	26867	6779018483	426	0.0158559	05102
5102082030	05102	20	2017	Casablanca	252317.7	2017	26867	6779018483	52	0.0019355	05102
5102082035	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	19	0.0007072	05102
5102092003	05102	44	2017	Casablanca	252317.7	2017	26867	6779018483	165	0.0061414	05102
5102092040	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	138	0.0051364	05102
5102102003	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102
5102102033	05102	79	2017	Casablanca	252317.7	2017	26867	6779018483	835	0.0310790	05102
5102102036	05102	16	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102
5102112023	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	45	0.0016749	05102
5102112026	05102	71	2017	Casablanca	252317.7	2017	26867	6779018483	334	0.0124316	05102
5102112028	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	324	0.0120594	05102
5102112030	05102	53	2017	Casablanca	252317.7	2017	26867	6779018483	222	0.0082629	05102
5102122009	05102	51	2017	Casablanca	252317.7	2017	26867	6779018483	760	0.0282875	05102
5102122017	05102	70	2017	Casablanca	252317.7	2017	26867	6779018483	501	0.0186474	05102
5102122021	05102	50	2017	Casablanca	252317.7	2017	26867	6779018483	422	0.0157070	05102
5102122037	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	44	0.0016377	05102
5102132002	05102	4	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102
5102132004	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	188	0.0069974	05102
5102132020	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	468	0.0174191	05102
5102132032	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	23	0.0008561	05102
5102132901	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102
5105012004	05105	28	2017	Puchuncaví	231606.0	2017	18546	4295363979	145	0.0078184	05105
5105012012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	18	0.0009706	05105
5105012015	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105
5105022012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	14	0.0007549	05105
5105022901	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	28	0.0015098	05105
5105032005	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	64	0.0034509	05105
5105032008	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	54	0.0029117	05105
5105042002	05105	7	2017	Puchuncaví	231606.0	2017	18546	4295363979	61	0.0032891	05105
5105042003	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	216	0.0116467	05105
5105042013	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	23	0.0012402	05105
5105042015	05105	4	2017	Puchuncaví	231606.0	2017	18546	4295363979	47	0.0025342	05105
5105042016	05105	12	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105
5105052014	05105	62	2017	Puchuncaví	231606.0	2017	18546	4295363979	772	0.0416262	05105
5105072011	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	169	0.0091125	05105
5105082001	05105	65	2017	Puchuncaví	231606.0	2017	18546	4295363979	932	0.0502534	05105
5107012010	05107	25	2017	Quintero	285125.8	2017	31923	9102071069	121	0.0037904	05107
5107022004	05107	102	2017	Quintero	285125.8	2017	31923	9102071069	287	0.0089904	05107
5107022009	05107	2	2017	Quintero	285125.8	2017	31923	9102071069	14	0.0004386	05107
5107022013	05107	133	2017	Quintero	285125.8	2017	31923	9102071069	559	0.0175109	05107
5107022016	05107	112	2017	Quintero	285125.8	2017	31923	9102071069	639	0.0200169	05107
5107022901	05107	10	2017	Quintero	285125.8	2017	31923	9102071069	30	0.0009398	05107
5107032002	05107	62	2017	Quintero	285125.8	2017	31923	9102071069	635	0.0198916	05107
5107032003	05107	157	2017	Quintero	285125.8	2017	31923	9102071069	665	0.0208314	05107
5107032006	05107	176	2017	Quintero	285125.8	2017	31923	9102071069	796	0.0249350	05107
5107032007	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	66	0.0020675	05107
5107032011	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	162	0.0050747	05107
5107032012	05107	254	2017	Quintero	285125.8	2017	31923	9102071069	879	0.0275350	05107
5107032014	05107	12	2017	Quintero	285125.8	2017	31923	9102071069	77	0.0024121	05107
5107032015	05107	3	2017	Quintero	285125.8	2017	31923	9102071069	109	0.0034145	05107
5301012009	05301	20	2017	Los Andes	280548.0	2017	66708	18714795984	74	0.0011093	05301
5301022009	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	318	0.0047670	05301
5301022014	05301	13	2017	Los Andes	280548.0	2017	66708	18714795984	101	0.0015141	05301
5301022901	05301	5	2017	Los Andes	280548.0	2017	66708	18714795984	116	0.0017389	05301
5301032003	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	24	0.0003598	05301
5301042003	05301	57	2017	Los Andes	280548.0	2017	66708	18714795984	945	0.0141662	05301
5301042005	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	988	0.0148108	05301
5301042007	05301	7	2017	Los Andes	280548.0	2017	66708	18714795984	301	0.0045122	05301
5301042015	05301	4	2017	Los Andes	280548.0	2017	66708	18714795984	42	0.0006296	05301
5301052001	05301	105	2017	Los Andes	280548.0	2017	66708	18714795984	358	0.0053667	05301
5301052002	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	56	0.0008395	05301
5301052010	05301	3	2017	Los Andes	280548.0	2017	66708	18714795984	103	0.0015440	05301
5301052011	05301	50	2017	Los Andes	280548.0	2017	66708	18714795984	694	0.0104035	05301
5301052013	05301	270	2017	Los Andes	280548.0	2017	66708	18714795984	1439	0.0215716	05301
5302012008	05302	77	2017	Calle Larga	234044.6	2017	14832	3471349123	230	0.0155070	05302
5302012009	05302	22	2017	Calle Larga	234044.6	2017	14832	3471349123	440	0.0296656	05302
5302012012	05302	105	2017	Calle Larga	234044.6	2017	14832	3471349123	506	0.0341154	05302
5302012013	05302	11	2017	Calle Larga	234044.6	2017	14832	3471349123	185	0.0124730	05302
5302022006	05302	4	2017	Calle Larga	234044.6	2017	14832	3471349123	488	0.0329018	05302
5302022010	05302	2	2017	Calle Larga	234044.6	2017	14832	3471349123	34	0.0022923	05302
5302022011	05302	14	2017	Calle Larga	234044.6	2017	14832	3471349123	152	0.0102481	05302
5302032011	05302	82	2017	Calle Larga	234044.6	2017	14832	3471349123	1163	0.0784115	05302
5302042004	05302	37	2017	Calle Larga	234044.6	2017	14832	3471349123	202	0.0136192	05302
5302042005	05302	5	2017	Calle Larga	234044.6	2017	14832	3471349123	49	0.0033037	05302

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
5101212004	05101	4	2017	Valparaíso	251998.5	2017	296655	74756602991	40	0.0001348	05101	10079938
5101212901	05101	2	2017	Valparaíso	251998.5	2017	296655	74756602991	25	0.0000843	05101	6299961
5101222003	05101	8	2017	Valparaíso	251998.5	2017	296655	74756602991	87	0.0002933	05101	21923866
5101232002	05101	45	2017	Valparaíso	251998.5	2017	296655	74756602991	558	0.0018810	05101	140615140
5101242001	05101	1	2017	Valparaíso	251998.5	2017	296655	74756602991	27	0.0000910	05101	6803958
5102012002	05102	29	2017	Casablanca	252317.7	2017	26867	6779018483	145	0.0053970	05102	36586060
5102012029	05102	24	2017	Casablanca	252317.7	2017	26867	6779018483	115	0.0042803	05102	29016531
5102012038	05102	9	2017	Casablanca	252317.7	2017	26867	6779018483	81	0.0030149	05102	20437730
5102022010	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	31	0.0011538	05102	7821847
5102022015	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102	18923824
5102022025	05102	5	2017	Casablanca	252317.7	2017	26867	6779018483	49	0.0018238	05102	12363565
5102022031	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	202	0.0075185	05102	50968167
5102022039	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	327	0.0121711	05102	82507874
5102032007	05102	15	2017	Casablanca	252317.7	2017	26867	6779018483	55	0.0020471	05102	13877471
5102032011	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	913	0.0339822	05102	230366021
5102032027	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	403	0.0149998	05102	101684016
5102042018	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102	18923824
5102042019	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	62	0.0023077	05102	15643695
5102052008	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	129	0.0048014	05102	32548978
5102052012	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	465	0.0173075	05102	117327710
5102052024	05102	46	2017	Casablanca	252317.7	2017	26867	6779018483	259	0.0096401	05102	65350273
5102052901	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	38	0.0014144	05102	9588071
5102062012	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	131	0.0048759	05102	33053613
5102062042	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	25	0.0009305	05102	6307941
5102072034	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436
5102082005	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	13	0.0004839	05102	3280130
5102082013	05102	41	2017	Casablanca	252317.7	2017	26867	6779018483	426	0.0158559	05102	107487322
5102082030	05102	20	2017	Casablanca	252317.7	2017	26867	6779018483	52	0.0019355	05102	13120518
5102082035	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	19	0.0007072	05102	4794035
5102092003	05102	44	2017	Casablanca	252317.7	2017	26867	6779018483	165	0.0061414	05102	41632413
5102092040	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	138	0.0051364	05102	34819837
5102102003	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102	13372836
5102102033	05102	79	2017	Casablanca	252317.7	2017	26867	6779018483	835	0.0310790	05102	210685243
5102102036	05102	16	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436
5102112023	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	45	0.0016749	05102	11354295
5102112026	05102	71	2017	Casablanca	252317.7	2017	26867	6779018483	334	0.0124316	05102	84274097
5102112028	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	324	0.0120594	05102	81750921
5102112030	05102	53	2017	Casablanca	252317.7	2017	26867	6779018483	222	0.0082629	05102	56014520
5102122009	05102	51	2017	Casablanca	252317.7	2017	26867	6779018483	760	0.0282875	05102	191761419
5102122017	05102	70	2017	Casablanca	252317.7	2017	26867	6779018483	501	0.0186474	05102	126411146
5102122021	05102	50	2017	Casablanca	252317.7	2017	26867	6779018483	422	0.0157070	05102	106478051
5102122037	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	44	0.0016377	05102	11101977
5102132002	05102	4	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102	13372836
5102132004	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	188	0.0069974	05102	47435719
5102132020	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	468	0.0174191	05102	118084663
5102132032	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	23	0.0008561	05102	5803306
5102132901	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436
5105012004	05105	28	2017	Puchuncaví	231606.0	2017	18546	4295363979	145	0.0078184	05105	33582863
5105012012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	18	0.0009706	05105	4168907
5105012015	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105	12043509
5105022012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	14	0.0007549	05105	3242483
5105022901	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	28	0.0015098	05105	6484967
5105032005	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	64	0.0034509	05105	14822781
5105032008	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	54	0.0029117	05105	12506721
5105042002	05105	7	2017	Puchuncaví	231606.0	2017	18546	4295363979	61	0.0032891	05105	14127963
5105042003	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	216	0.0116467	05105	50026886
5105042013	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	23	0.0012402	05105	5326937
5105042015	05105	4	2017	Puchuncaví	231606.0	2017	18546	4295363979	47	0.0025342	05105	10885480
5105042016	05105	12	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105	12043509
5105052014	05105	62	2017	Puchuncaví	231606.0	2017	18546	4295363979	772	0.0416262	05105	178799795
5105072011	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	169	0.0091125	05105	39141406
5105082001	05105	65	2017	Puchuncaví	231606.0	2017	18546	4295363979	932	0.0502534	05105	215856747
5107012010	05107	25	2017	Quintero	285125.8	2017	31923	9102071069	121	0.0037904	05107	34500222
5107022004	05107	102	2017	Quintero	285125.8	2017	31923	9102071069	287	0.0089904	05107	81831106
5107022009	05107	2	2017	Quintero	285125.8	2017	31923	9102071069	14	0.0004386	05107	3991761
5107022013	05107	133	2017	Quintero	285125.8	2017	31923	9102071069	559	0.0175109	05107	159385325
5107022016	05107	112	2017	Quintero	285125.8	2017	31923	9102071069	639	0.0200169	05107	182195389
5107022901	05107	10	2017	Quintero	285125.8	2017	31923	9102071069	30	0.0009398	05107	8553774
5107032002	05107	62	2017	Quintero	285125.8	2017	31923	9102071069	635	0.0198916	05107	181054886
5107032003	05107	157	2017	Quintero	285125.8	2017	31923	9102071069	665	0.0208314	05107	189608660
5107032006	05107	176	2017	Quintero	285125.8	2017	31923	9102071069	796	0.0249350	05107	226960141
5107032007	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	66	0.0020675	05107	18818303
5107032011	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	162	0.0050747	05107	46190380
5107032012	05107	254	2017	Quintero	285125.8	2017	31923	9102071069	879	0.0275350	05107	250625582
5107032014	05107	12	2017	Quintero	285125.8	2017	31923	9102071069	77	0.0024121	05107	21954687
5107032015	05107	3	2017	Quintero	285125.8	2017	31923	9102071069	109	0.0034145	05107	31078713
5301012009	05301	20	2017	Los Andes	280548.0	2017	66708	18714795984	74	0.0011093	05301	20760552
5301022009	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	318	0.0047670	05301	89214264
5301022014	05301	13	2017	Los Andes	280548.0	2017	66708	18714795984	101	0.0015141	05301	28335348
5301022901	05301	5	2017	Los Andes	280548.0	2017	66708	18714795984	116	0.0017389	05301	32543568
5301032003	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	24	0.0003598	05301	6733152
5301042003	05301	57	2017	Los Andes	280548.0	2017	66708	18714795984	945	0.0141662	05301	265117860
5301042005	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	988	0.0148108	05301	277181424
5301042007	05301	7	2017	Los Andes	280548.0	2017	66708	18714795984	301	0.0045122	05301	84444948
5301042015	05301	4	2017	Los Andes	280548.0	2017	66708	18714795984	42	0.0006296	05301	11783016
5301052001	05301	105	2017	Los Andes	280548.0	2017	66708	18714795984	358	0.0053667	05301	100436184
5301052002	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	56	0.0008395	05301	15710688
5301052010	05301	3	2017	Los Andes	280548.0	2017	66708	18714795984	103	0.0015440	05301	28896444
5301052011	05301	50	2017	Los Andes	280548.0	2017	66708	18714795984	694	0.0104035	05301	194700312
5301052013	05301	270	2017	Los Andes	280548.0	2017	66708	18714795984	1439	0.0215716	05301	403708572
5302012008	05302	77	2017	Calle Larga	234044.6	2017	14832	3471349123	230	0.0155070	05302	53830252
5302012009	05302	22	2017	Calle Larga	234044.6	2017	14832	3471349123	440	0.0296656	05302	102979613
5302012012	05302	105	2017	Calle Larga	234044.6	2017	14832	3471349123	506	0.0341154	05302	118426554
5302012013	05302	11	2017	Calle Larga	234044.6	2017	14832	3471349123	185	0.0124730	05302	43298246
5302022006	05302	4	2017	Calle Larga	234044.6	2017	14832	3471349123	488	0.0329018	05302	114213752
5302022010	05302	2	2017	Calle Larga	234044.6	2017	14832	3471349123	34	0.0022923	05302	7957516
5302022011	05302	14	2017	Calle Larga	234044.6	2017	14832	3471349123	152	0.0102481	05302	35574775
5302032011	05302	82	2017	Calle Larga	234044.6	2017	14832	3471349123	1163	0.0784115	05302	272193840
5302042004	05302	37	2017	Calle Larga	234044.6	2017	14832	3471349123	202	0.0136192	05302	47277004
5302042005	05302	5	2017	Calle Larga	234044.6	2017	14832	3471349123	49	0.0033037	05302	11468184

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 
## -208890486  -27289321  -17715457   22355709  426329030 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 27533409    3518782   7.825 3.46e-14 ***
## Freq.x       1686482      69960  24.106  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 61920000 on 465 degrees of freedom
## Multiple R-squared:  0.5555, Adjusted R-squared:  0.5545 
## F-statistic: 581.1 on 1 and 465 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 
## -208890486  -27289321  -17715457   22355709  426329030 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 27533409    3518782   7.825 3.46e-14 ***
## Freq.x       1686482      69960  24.106  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 61920000 on 465 degrees of freedom
## Multiple R-squared:  0.5555, Adjusted R-squared:  0.5545 
## F-statistic: 581.1 on 1 and 465 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 
## -208890486  -27289321  -17715457   22355709  426329030 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 27533409    3518782   7.825 3.46e-14 ***
## Freq.x       1686482      69960  24.106  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 61920000 on 465 degrees of freedom
## Multiple R-squared:  0.5555, Adjusted R-squared:  0.5545 
## F-statistic: 581.1 on 1 and 465 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 
## -115162488  -36752933   -7783231   26137109  467220651 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -45154975    6524691  -6.921  1.5e-11 ***
## log(Freq.x)  47843557    2259894  21.171  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 66280000 on 465 degrees of freedom
## Multiple R-squared:  0.4908, Adjusted R-squared:  0.4897 
## F-statistic: 448.2 on 1 and 465 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 
## -140095801  -26548882   -2318296   20133878  424835517 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -28043690    4879742  -5.747 1.65e-08 ***
## sqrt(Freq.x)  23462839     903149  25.979  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 59320000 on 465 degrees of freedom
## Multiple R-squared:  0.5921, Adjusted R-squared:  0.5912 
## F-statistic: 674.9 on 1 and 465 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 
## -6132.7 -1739.4  -543.4  1665.4 10685.6 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2062.93     220.55   9.353   <2e-16 ***
## sqrt(Freq.x)  1213.49      40.82  29.727   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2681 on 465 degrees of freedom
## Multiple R-squared:  0.6552, Adjusted R-squared:  0.6545 
## F-statistic: 883.7 on 1 and 465 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

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

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

## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.00818 -0.56341 -0.02882  0.62605  1.91681 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  16.03734    0.06621  242.23   <2e-16 ***
## sqrt(Freq.x)  0.31926    0.01225   26.05   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.8048 on 465 degrees of freedom
## Multiple R-squared:  0.5935, Adjusted R-squared:  0.5926 
## F-statistic: 678.8 on 1 and 465 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 
## -5942.8 -1880.7   -97.6  1759.6 12113.0 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   679.08     272.52   2.492   0.0131 *  
## log(Freq.x)  2670.20      94.39  28.289   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2768 on 465 degrees of freedom
## Multiple R-squared:  0.6325, Adjusted R-squared:  0.6317 
## F-statistic: 800.3 on 1 and 465 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 
## -1.82667 -0.49523  0.01905  0.54635  1.97811 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.51609    0.07053  219.99   <2e-16 ***
## log(Freq.x)  0.76419    0.02443   31.28   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7164 on 465 degrees of freedom
## Multiple R-squared:  0.6779, Adjusted R-squared:  0.6772 
## F-statistic: 978.6 on 1 and 465 DF,  p-value: < 2.2e-16

9 Modelo raiz-raiz (log-log)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.6772).

9.1 Diagrama de dispersión sobre log-log

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

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

9.2 Modelo 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 
## -1.82667 -0.49523  0.01905  0.54635  1.97811 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.51609    0.07053  219.99   <2e-16 ***
## log(Freq.x)  0.76419    0.02443   31.28   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7164 on 465 degrees of freedom
## Multiple R-squared:  0.6779, Adjusted R-squared:  0.6772 
## F-statistic: 978.6 on 1 and 465 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

\[ \hat Y = e^{15.51609+0.76419 ln{X}} \]

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$est_ing <- exp(15.51609+0.76419 *log(h_y_m_comuna_corr_01$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
5101212004	05101	4	2017	Valparaíso	251998.5	2017	296655	74756602991	40	0.0001348	05101	10079938	15799396
5101212901	05101	2	2017	Valparaíso	251998.5	2017	296655	74756602991	25	0.0000843	05101	6299961	9302429
5101222003	05101	8	2017	Valparaíso	251998.5	2017	296655	74756602991	87	0.0002933	05101	21923866	26833950
5101232002	05101	45	2017	Valparaíso	251998.5	2017	296655	74756602991	558	0.0018810	05101	140615140	100443246
5101242001	05101	1	2017	Valparaíso	251998.5	2017	296655	74756602991	27	0.0000910	05101	6803958	5477120
5102012002	05102	29	2017	Casablanca	252317.7	2017	26867	6779018483	145	0.0053970	05102	36586060	71796322
5102012029	05102	24	2017	Casablanca	252317.7	2017	26867	6779018483	115	0.0042803	05102	29016531	62129219
5102012038	05102	9	2017	Casablanca	252317.7	2017	26867	6779018483	81	0.0030149	05102	20437730	29361271
5102022010	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	31	0.0011538	05102	7821847	5477120
5102022015	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102	18923824	21538114
5102022025	05102	5	2017	Casablanca	252317.7	2017	26867	6779018483	49	0.0018238	05102	12363565	18736918
5102022031	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	202	0.0075185	05102	50968167	21538114
5102022039	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	327	0.0121711	05102	82507874	38888092
5102032007	05102	15	2017	Casablanca	252317.7	2017	26867	6779018483	55	0.0020471	05102	13877471	43381988
5102032011	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	913	0.0339822	05102	230366021	77405680
5102032027	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	403	0.0149998	05102	101684016	77405680
5102042018	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102	18923824	24230799
5102042019	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	62	0.0023077	05102	15643695	24230799
5102052008	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	129	0.0048014	05102	32548978	26833950
5102052012	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	465	0.0173075	05102	117327710	75550260
5102052024	05102	46	2017	Casablanca	252317.7	2017	26867	6779018483	259	0.0096401	05102	65350273	102144544
5102052901	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	38	0.0014144	05102	9588071	5477120
5102062012	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	131	0.0048759	05102	33053613	21538114
5102062042	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	25	0.0009305	05102	6307941	9302429
5102072034	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436	9302429
5102082005	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	13	0.0004839	05102	3280130	9302429
5102082013	05102	41	2017	Casablanca	252317.7	2017	26867	6779018483	426	0.0158559	05102	107487322	93546074
5102082030	05102	20	2017	Casablanca	252317.7	2017	26867	6779018483	52	0.0019355	05102	13120518	54048840
5102082035	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	19	0.0007072	05102	4794035	5477120
5102092003	05102	44	2017	Casablanca	252317.7	2017	26867	6779018483	165	0.0061414	05102	41632413	98733008
5102092040	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	138	0.0051364	05102	34819837	84696034
5102102003	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102	13372836	24230799
5102102033	05102	79	2017	Casablanca	252317.7	2017	26867	6779018483	835	0.0310790	05102	210685243	154418708
5102102036	05102	16	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436	45575214
5102112023	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	45	0.0016749	05102	11354295	26833950
5102112026	05102	71	2017	Casablanca	252317.7	2017	26867	6779018483	334	0.0124316	05102	84274097	142319820
5102112028	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	324	0.0120594	05102	81750921	38888092
5102112030	05102	53	2017	Casablanca	252317.7	2017	26867	6779018483	222	0.0082629	05102	56014520	113822113
5102122009	05102	51	2017	Casablanca	252317.7	2017	26867	6779018483	760	0.0282875	05102	191761419	110524948
5102122017	05102	70	2017	Casablanca	252317.7	2017	26867	6779018483	501	0.0186474	05102	126411146	140785439
5102122021	05102	50	2017	Casablanca	252317.7	2017	26867	6779018483	422	0.0157070	05102	106478051	108864970
5102122037	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	44	0.0016377	05102	11101977	26833950
5102132002	05102	4	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102	13372836	15799396
5102132004	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	188	0.0069974	05102	47435719	75550260
5102132020	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	468	0.0174191	05102	118084663	84696034
5102132032	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	23	0.0008561	05102	5803306	5477120
5102132901	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436	24230799
5105012004	05105	28	2017	Puchuncaví	231606.0	2017	18546	4295363979	145	0.0078184	05105	33582863	69896586
5105012012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	18	0.0009706	05105	4168907	9302429
5105012015	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105	12043509	9302429
5105022012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	14	0.0007549	05105	3242483	9302429
5105022901	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	28	0.0015098	05105	6484967	9302429
5105032005	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	64	0.0034509	05105	14822781	12681294
5105032008	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	54	0.0029117	05105	12506721	12681294
5105042002	05105	7	2017	Puchuncaví	231606.0	2017	18546	4295363979	61	0.0032891	05105	14127963	24230799
5105042003	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	216	0.0116467	05105	50026886	31823084
5105042013	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	23	0.0012402	05105	5326937	12681294
5105042015	05105	4	2017	Puchuncaví	231606.0	2017	18546	4295363979	47	0.0025342	05105	10885480	15799396
5105042016	05105	12	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105	12043509	36580681
5105052014	05105	62	2017	Puchuncaví	231606.0	2017	18546	4295363979	772	0.0416262	05105	178799795	128315781
5105072011	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	169	0.0091125	05105	39141406	31823084
5105082001	05105	65	2017	Puchuncaví	231606.0	2017	18546	4295363979	932	0.0502534	05105	215856747	133033962
5107012010	05107	25	2017	Quintero	285125.8	2017	31923	9102071069	121	0.0037904	05107	34500222	64097936
5107022004	05107	102	2017	Quintero	285125.8	2017	31923	9102071069	287	0.0089904	05107	81831106	187717358
5107022009	05107	2	2017	Quintero	285125.8	2017	31923	9102071069	14	0.0004386	05107	3991761	9302429
5107022013	05107	133	2017	Quintero	285125.8	2017	31923	9102071069	559	0.0175109	05107	159385325	229920901
5107022016	05107	112	2017	Quintero	285125.8	2017	31923	9102071069	639	0.0200169	05107	182195389	201624911
5107022901	05107	10	2017	Quintero	285125.8	2017	31923	9102071069	30	0.0009398	05107	8553774	31823084
5107032002	05107	62	2017	Quintero	285125.8	2017	31923	9102071069	635	0.0198916	05107	181054886	128315781
5107032003	05107	157	2017	Quintero	285125.8	2017	31923	9102071069	665	0.0208314	05107	189608660	260997786
5107032006	05107	176	2017	Quintero	285125.8	2017	31923	9102071069	796	0.0249350	05107	226960141	284806957
5107032007	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	66	0.0020675	05107	18818303	71796322
5107032011	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	162	0.0050747	05107	46190380	71796322
5107032012	05107	254	2017	Quintero	285125.8	2017	31923	9102071069	879	0.0275350	05107	250625582	376965969
5107032014	05107	12	2017	Quintero	285125.8	2017	31923	9102071069	77	0.0024121	05107	21954687	36580681
5107032015	05107	3	2017	Quintero	285125.8	2017	31923	9102071069	109	0.0034145	05107	31078713	12681294
5301012009	05301	20	2017	Los Andes	280548.0	2017	66708	18714795984	74	0.0011093	05301	20760552	54048840
5301022009	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	318	0.0047670	05301	89214264	73680669
5301022014	05301	13	2017	Los Andes	280548.0	2017	66708	18714795984	101	0.0015141	05301	28335348	38888092
5301022901	05301	5	2017	Los Andes	280548.0	2017	66708	18714795984	116	0.0017389	05301	32543568	18736918
5301032003	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	24	0.0003598	05301	6733152	5477120
5301042003	05301	57	2017	Los Andes	280548.0	2017	66708	18714795984	945	0.0141662	05301	265117860	120330099
5301042005	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	988	0.0148108	05301	277181424	73680669
5301042007	05301	7	2017	Los Andes	280548.0	2017	66708	18714795984	301	0.0045122	05301	84444948	24230799
5301042015	05301	4	2017	Los Andes	280548.0	2017	66708	18714795984	42	0.0006296	05301	11783016	15799396
5301052001	05301	105	2017	Los Andes	280548.0	2017	66708	18714795984	358	0.0053667	05301	100436184	191922070
5301052002	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	56	0.0008395	05301	15710688	5477120
5301052010	05301	3	2017	Los Andes	280548.0	2017	66708	18714795984	103	0.0015440	05301	28896444	12681294
5301052011	05301	50	2017	Los Andes	280548.0	2017	66708	18714795984	694	0.0104035	05301	194700312	108864970
5301052013	05301	270	2017	Los Andes	280548.0	2017	66708	18714795984	1439	0.0215716	05301	403708572	394980943
5302012008	05302	77	2017	Calle Larga	234044.6	2017	14832	3471349123	230	0.0155070	05302	53830252	151422222
5302012009	05302	22	2017	Calle Larga	234044.6	2017	14832	3471349123	440	0.0296656	05302	102979613	58132400
5302012012	05302	105	2017	Calle Larga	234044.6	2017	14832	3471349123	506	0.0341154	05302	118426554	191922070
5302012013	05302	11	2017	Calle Larga	234044.6	2017	14832	3471349123	185	0.0124730	05302	43298246	34227418
5302022006	05302	4	2017	Calle Larga	234044.6	2017	14832	3471349123	488	0.0329018	05302	114213752	15799396
5302022010	05302	2	2017	Calle Larga	234044.6	2017	14832	3471349123	34	0.0022923	05302	7957516	9302429
5302022011	05302	14	2017	Calle Larga	234044.6	2017	14832	3471349123	152	0.0102481	05302	35574775	41153981
5302032011	05302	82	2017	Calle Larga	234044.6	2017	14832	3471349123	1163	0.0784115	05302	272193840	158880163
5302042004	05302	37	2017	Calle Larga	234044.6	2017	14832	3471349123	202	0.0136192	05302	47277004	86488097
5302042005	05302	5	2017	Calle Larga	234044.6	2017	14832	3471349123	49	0.0033037	05302	11468184	18736918

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
5101212004	05101	4	2017	Valparaíso	251998.5	2017	296655	74756602991	40	0.0001348	05101	10079938	15799396	394984.91
5101212901	05101	2	2017	Valparaíso	251998.5	2017	296655	74756602991	25	0.0000843	05101	6299961	9302429	372097.17
5101222003	05101	8	2017	Valparaíso	251998.5	2017	296655	74756602991	87	0.0002933	05101	21923866	26833950	308436.21
5101232002	05101	45	2017	Valparaíso	251998.5	2017	296655	74756602991	558	0.0018810	05101	140615140	100443246	180005.82
5101242001	05101	1	2017	Valparaíso	251998.5	2017	296655	74756602991	27	0.0000910	05101	6803958	5477120	202856.30
5102012002	05102	29	2017	Casablanca	252317.7	2017	26867	6779018483	145	0.0053970	05102	36586060	71796322	495147.04
5102012029	05102	24	2017	Casablanca	252317.7	2017	26867	6779018483	115	0.0042803	05102	29016531	62129219	540254.08
5102012038	05102	9	2017	Casablanca	252317.7	2017	26867	6779018483	81	0.0030149	05102	20437730	29361271	362484.83
5102022010	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	31	0.0011538	05102	7821847	5477120	176681.30
5102022015	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102	18923824	21538114	287174.85
5102022025	05102	5	2017	Casablanca	252317.7	2017	26867	6779018483	49	0.0018238	05102	12363565	18736918	382386.08
5102022031	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	202	0.0075185	05102	50968167	21538114	106624.33
5102022039	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	327	0.0121711	05102	82507874	38888092	118923.83
5102032007	05102	15	2017	Casablanca	252317.7	2017	26867	6779018483	55	0.0020471	05102	13877471	43381988	788763.41
5102032011	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	913	0.0339822	05102	230366021	77405680	84781.69
5102032027	05102	32	2017	Casablanca	252317.7	2017	26867	6779018483	403	0.0149998	05102	101684016	77405680	192073.65
5102042018	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	75	0.0027915	05102	18923824	24230799	323077.32
5102042019	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	62	0.0023077	05102	15643695	24230799	390819.34
5102052008	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	129	0.0048014	05102	32548978	26833950	208015.12
5102052012	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	465	0.0173075	05102	117327710	75550260	162473.68
5102052024	05102	46	2017	Casablanca	252317.7	2017	26867	6779018483	259	0.0096401	05102	65350273	102144544	394380.48
5102052901	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	38	0.0014144	05102	9588071	5477120	144134.74
5102062012	05102	6	2017	Casablanca	252317.7	2017	26867	6779018483	131	0.0048759	05102	33053613	21538114	164413.08
5102062042	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	25	0.0009305	05102	6307941	9302429	372097.17
5102072034	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436	9302429	258400.82
5102082005	05102	2	2017	Casablanca	252317.7	2017	26867	6779018483	13	0.0004839	05102	3280130	9302429	715571.49
5102082013	05102	41	2017	Casablanca	252317.7	2017	26867	6779018483	426	0.0158559	05102	107487322	93546074	219591.72
5102082030	05102	20	2017	Casablanca	252317.7	2017	26867	6779018483	52	0.0019355	05102	13120518	54048840	1039400.78
5102082035	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	19	0.0007072	05102	4794035	5477120	288269.48
5102092003	05102	44	2017	Casablanca	252317.7	2017	26867	6779018483	165	0.0061414	05102	41632413	98733008	598381.87
5102092040	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	138	0.0051364	05102	34819837	84696034	613739.38
5102102003	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102	13372836	24230799	457184.89
5102102033	05102	79	2017	Casablanca	252317.7	2017	26867	6779018483	835	0.0310790	05102	210685243	154418708	184932.58
5102102036	05102	16	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436	45575214	1265978.17
5102112023	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	45	0.0016749	05102	11354295	26833950	596310.00
5102112026	05102	71	2017	Casablanca	252317.7	2017	26867	6779018483	334	0.0124316	05102	84274097	142319820	426107.24
5102112028	05102	13	2017	Casablanca	252317.7	2017	26867	6779018483	324	0.0120594	05102	81750921	38888092	120024.98
5102112030	05102	53	2017	Casablanca	252317.7	2017	26867	6779018483	222	0.0082629	05102	56014520	113822113	512712.22
5102122009	05102	51	2017	Casablanca	252317.7	2017	26867	6779018483	760	0.0282875	05102	191761419	110524948	145427.56
5102122017	05102	70	2017	Casablanca	252317.7	2017	26867	6779018483	501	0.0186474	05102	126411146	140785439	281008.86
5102122021	05102	50	2017	Casablanca	252317.7	2017	26867	6779018483	422	0.0157070	05102	106478051	108864970	257973.86
5102122037	05102	8	2017	Casablanca	252317.7	2017	26867	6779018483	44	0.0016377	05102	11101977	26833950	609862.50
5102132002	05102	4	2017	Casablanca	252317.7	2017	26867	6779018483	53	0.0019727	05102	13372836	15799396	298101.82
5102132004	05102	31	2017	Casablanca	252317.7	2017	26867	6779018483	188	0.0069974	05102	47435719	75550260	401863.08
5102132020	05102	36	2017	Casablanca	252317.7	2017	26867	6779018483	468	0.0174191	05102	118084663	84696034	180974.43
5102132032	05102	1	2017	Casablanca	252317.7	2017	26867	6779018483	23	0.0008561	05102	5803306	5477120	238135.66
5102132901	05102	7	2017	Casablanca	252317.7	2017	26867	6779018483	36	0.0013399	05102	9083436	24230799	673077.76
5105012004	05105	28	2017	Puchuncaví	231606.0	2017	18546	4295363979	145	0.0078184	05105	33582863	69896586	482045.42
5105012012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	18	0.0009706	05105	4168907	9302429	516801.63
5105012015	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105	12043509	9302429	178892.87
5105022012	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	14	0.0007549	05105	3242483	9302429	664459.24
5105022901	05105	2	2017	Puchuncaví	231606.0	2017	18546	4295363979	28	0.0015098	05105	6484967	9302429	332229.62
5105032005	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	64	0.0034509	05105	14822781	12681294	198145.21
5105032008	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	54	0.0029117	05105	12506721	12681294	234838.77
5105042002	05105	7	2017	Puchuncaví	231606.0	2017	18546	4295363979	61	0.0032891	05105	14127963	24230799	397226.22
5105042003	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	216	0.0116467	05105	50026886	31823084	147329.09
5105042013	05105	3	2017	Puchuncaví	231606.0	2017	18546	4295363979	23	0.0012402	05105	5326937	12681294	551360.59
5105042015	05105	4	2017	Puchuncaví	231606.0	2017	18546	4295363979	47	0.0025342	05105	10885480	15799396	336157.37
5105042016	05105	12	2017	Puchuncaví	231606.0	2017	18546	4295363979	52	0.0028038	05105	12043509	36580681	703474.63
5105052014	05105	62	2017	Puchuncaví	231606.0	2017	18546	4295363979	772	0.0416262	05105	178799795	128315781	166212.15
5105072011	05105	10	2017	Puchuncaví	231606.0	2017	18546	4295363979	169	0.0091125	05105	39141406	31823084	188302.27
5105082001	05105	65	2017	Puchuncaví	231606.0	2017	18546	4295363979	932	0.0502534	05105	215856747	133033962	142740.30
5107012010	05107	25	2017	Quintero	285125.8	2017	31923	9102071069	121	0.0037904	05107	34500222	64097936	529735.01
5107022004	05107	102	2017	Quintero	285125.8	2017	31923	9102071069	287	0.0089904	05107	81831106	187717358	654067.45
5107022009	05107	2	2017	Quintero	285125.8	2017	31923	9102071069	14	0.0004386	05107	3991761	9302429	664459.24
5107022013	05107	133	2017	Quintero	285125.8	2017	31923	9102071069	559	0.0175109	05107	159385325	229920901	411307.52
5107022016	05107	112	2017	Quintero	285125.8	2017	31923	9102071069	639	0.0200169	05107	182195389	201624911	315531.94
5107022901	05107	10	2017	Quintero	285125.8	2017	31923	9102071069	30	0.0009398	05107	8553774	31823084	1060769.47
5107032002	05107	62	2017	Quintero	285125.8	2017	31923	9102071069	635	0.0198916	05107	181054886	128315781	202072.10
5107032003	05107	157	2017	Quintero	285125.8	2017	31923	9102071069	665	0.0208314	05107	189608660	260997786	392477.87
5107032006	05107	176	2017	Quintero	285125.8	2017	31923	9102071069	796	0.0249350	05107	226960141	284806957	357797.68
5107032007	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	66	0.0020675	05107	18818303	71796322	1087823.05
5107032011	05107	29	2017	Quintero	285125.8	2017	31923	9102071069	162	0.0050747	05107	46190380	71796322	443187.17
5107032012	05107	254	2017	Quintero	285125.8	2017	31923	9102071069	879	0.0275350	05107	250625582	376965969	428857.76
5107032014	05107	12	2017	Quintero	285125.8	2017	31923	9102071069	77	0.0024121	05107	21954687	36580681	475073.78
5107032015	05107	3	2017	Quintero	285125.8	2017	31923	9102071069	109	0.0034145	05107	31078713	12681294	116342.14
5301012009	05301	20	2017	Los Andes	280548.0	2017	66708	18714795984	74	0.0011093	05301	20760552	54048840	730389.73
5301022009	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	318	0.0047670	05301	89214264	73680669	231700.22
5301022014	05301	13	2017	Los Andes	280548.0	2017	66708	18714795984	101	0.0015141	05301	28335348	38888092	385030.62
5301022901	05301	5	2017	Los Andes	280548.0	2017	66708	18714795984	116	0.0017389	05301	32543568	18736918	161525.15
5301032003	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	24	0.0003598	05301	6733152	5477120	228213.34
5301042003	05301	57	2017	Los Andes	280548.0	2017	66708	18714795984	945	0.0141662	05301	265117860	120330099	127333.44
5301042005	05301	30	2017	Los Andes	280548.0	2017	66708	18714795984	988	0.0148108	05301	277181424	73680669	74575.58
5301042007	05301	7	2017	Los Andes	280548.0	2017	66708	18714795984	301	0.0045122	05301	84444948	24230799	80500.99
5301042015	05301	4	2017	Los Andes	280548.0	2017	66708	18714795984	42	0.0006296	05301	11783016	15799396	376176.10
5301052001	05301	105	2017	Los Andes	280548.0	2017	66708	18714795984	358	0.0053667	05301	100436184	191922070	536095.17
5301052002	05301	1	2017	Los Andes	280548.0	2017	66708	18714795984	56	0.0008395	05301	15710688	5477120	97805.72
5301052010	05301	3	2017	Los Andes	280548.0	2017	66708	18714795984	103	0.0015440	05301	28896444	12681294	123119.36
5301052011	05301	50	2017	Los Andes	280548.0	2017	66708	18714795984	694	0.0104035	05301	194700312	108864970	156865.95
5301052013	05301	270	2017	Los Andes	280548.0	2017	66708	18714795984	1439	0.0215716	05301	403708572	394980943	274482.93
5302012008	05302	77	2017	Calle Larga	234044.6	2017	14832	3471349123	230	0.0155070	05302	53830252	151422222	658357.49
5302012009	05302	22	2017	Calle Larga	234044.6	2017	14832	3471349123	440	0.0296656	05302	102979613	58132400	132119.09
5302012012	05302	105	2017	Calle Larga	234044.6	2017	14832	3471349123	506	0.0341154	05302	118426554	191922070	379292.63
5302012013	05302	11	2017	Calle Larga	234044.6	2017	14832	3471349123	185	0.0124730	05302	43298246	34227418	185013.07
5302022006	05302	4	2017	Calle Larga	234044.6	2017	14832	3471349123	488	0.0329018	05302	114213752	15799396	32375.81
5302022010	05302	2	2017	Calle Larga	234044.6	2017	14832	3471349123	34	0.0022923	05302	7957516	9302429	273600.86
5302022011	05302	14	2017	Calle Larga	234044.6	2017	14832	3471349123	152	0.0102481	05302	35574775	41153981	270749.87
5302032011	05302	82	2017	Calle Larga	234044.6	2017	14832	3471349123	1163	0.0784115	05302	272193840	158880163	136612.35
5302042004	05302	37	2017	Calle Larga	234044.6	2017	14832	3471349123	202	0.0136192	05302	47277004	86488097	428158.90
5302042005	05302	5	2017	Calle Larga	234044.6	2017	14832	3471349123	49	0.0033037	05302	11468184	18736918	382386.08

Guardamos:

saveRDS(h_y_m_comuna_corr_01, "P15/region_05_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