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 09 y con la zona = 2:

tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$REGION == 10) 
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$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 10101032002 12 10101 20 2017
2 10101032011 12 10101 50 2017
3 10101032019 12 10101 33 2017
4 10101042010 12 10101 1 2017
5 10101062003 12 10101 19 2017
6 10101062008 12 10101 144 2017
7 10101062013 12 10101 135 2017
8 10101062029 12 10101 3 2017
9 10101062039 12 10101 4 2017
10 10101072014 12 10101 74 2017
11 10101072021 12 10101 5 2017
12 10101072028 12 10101 7 2017
13 10101072029 12 10101 81 2017
14 10101072036 12 10101 5 2017
15 10101072045 12 10101 12 2017
16 10101072050 12 10101 3 2017
17 10101082016 12 10101 10 2017
18 10101082017 12 10101 1 2017
19 10101082018 12 10101 34 2017
20 10101082030 12 10101 13 2017
21 10101082034 12 10101 2 2017
22 10101082042 12 10101 51 2017
23 10101082045 12 10101 12 2017
24 10101092004 12 10101 11 2017
25 10101092008 12 10101 195 2017
26 10101092037 12 10101 18 2017
27 10101092040 12 10101 76 2017
28 10101092041 12 10101 265 2017
29 10101092044 12 10101 49 2017
30 10101102005 12 10101 2 2017
31 10101102007 12 10101 22 2017
32 10101102026 12 10101 3 2017
33 10101102035 12 10101 69 2017
34 10101102037 12 10101 15 2017
35 10101102901 12 10101 3 2017
36 10101112025 12 10101 32 2017
37 10101122024 12 10101 16 2017
38 10101132022 12 10101 29 2017
39 10101132023 12 10101 13 2017
40 10101132027 12 10101 11 2017
41 10101132049 12 10101 152 2017
42 10101142009 12 10101 1 2017
43 10101142015 12 10101 6 2017
44 10101142027 12 10101 11 2017
45 10101142038 12 10101 1 2017
46 10101142046 12 10101 9 2017
47 10101142047 12 10101 6 2017
48 10101142049 12 10101 136 2017
49 10101152002 12 10101 58 2017
50 10101152006 12 10101 14 2017
51 10101152020 12 10101 76 2017
52 10101152031 12 10101 90 2017
53 10101152033 12 10101 49 2017
54 10101152049 12 10101 7 2017
55 10101152901 12 10101 2 2017
56 10101162006 12 10101 18 2017
57 10101162010 12 10101 16 2017
58 10101162020 12 10101 31 2017
59 10101162031 12 10101 123 2017
60 10101162032 12 10101 2 2017
61 10101162033 12 10101 18 2017
62 10101172029 12 10101 198 2017
1148 10102012001 12 10102 3 2017
1149 10102012004 12 10102 2 2017
1150 10102012008 12 10102 19 2017
1151 10102012017 12 10102 3 2017
1152 10102012033 12 10102 64 2017
1153 10102022001 12 10102 4 2017
1154 10102022002 12 10102 3 2017
1155 10102022003 12 10102 8 2017
1156 10102022004 12 10102 6 2017
1157 10102022010 12 10102 16 2017
1158 10102022013 12 10102 3 2017
1159 10102032002 12 10102 1 2017
1160 10102032011 12 10102 2 2017
1161 10102032016 12 10102 3 2017
1162 10102032018 12 10102 8 2017
1163 10102032034 12 10102 16 2017
1164 10102032901 12 10102 7 2017
1165 10102042014 12 10102 3 2017
1166 10102042016 12 10102 3 2017
1167 10102042019 12 10102 12 2017
1168 10102042028 12 10102 16 2017
1169 10102042029 12 10102 5 2017
1170 10102042035 12 10102 3 2017
1171 10102042043 12 10102 2 2017
1172 10102042901 12 10102 5 2017
1173 10102052012 12 10102 4 2017
1174 10102052019 12 10102 14 2017
1175 10102052042 12 10102 18 2017
1176 10102052043 12 10102 8 2017
1177 10102062015 12 10102 41 2017
1178 10102062019 12 10102 7 2017
1179 10102062027 12 10102 1 2017
1180 10102062038 12 10102 15 2017
1181 10102062039 12 10102 12 2017
1182 10102072022 12 10102 4 2017
1183 10102082022 12 10102 19 2017
1184 10102092022 12 10102 4 2017
1185 10102102023 12 10102 9 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 10101032002 20 2017 10101
2 10101032011 50 2017 10101
3 10101032019 33 2017 10101
4 10101042010 1 2017 10101
5 10101062003 19 2017 10101
6 10101062008 144 2017 10101
7 10101062013 135 2017 10101
8 10101062029 3 2017 10101
9 10101062039 4 2017 10101
10 10101072014 74 2017 10101
11 10101072021 5 2017 10101
12 10101072028 7 2017 10101
13 10101072029 81 2017 10101
14 10101072036 5 2017 10101
15 10101072045 12 2017 10101
16 10101072050 3 2017 10101
17 10101082016 10 2017 10101
18 10101082017 1 2017 10101
19 10101082018 34 2017 10101
20 10101082030 13 2017 10101
21 10101082034 2 2017 10101
22 10101082042 51 2017 10101
23 10101082045 12 2017 10101
24 10101092004 11 2017 10101
25 10101092008 195 2017 10101
26 10101092037 18 2017 10101
27 10101092040 76 2017 10101
28 10101092041 265 2017 10101
29 10101092044 49 2017 10101
30 10101102005 2 2017 10101
31 10101102007 22 2017 10101
32 10101102026 3 2017 10101
33 10101102035 69 2017 10101
34 10101102037 15 2017 10101
35 10101102901 3 2017 10101
36 10101112025 32 2017 10101
37 10101122024 16 2017 10101
38 10101132022 29 2017 10101
39 10101132023 13 2017 10101
40 10101132027 11 2017 10101
41 10101132049 152 2017 10101
42 10101142009 1 2017 10101
43 10101142015 6 2017 10101
44 10101142027 11 2017 10101
45 10101142038 1 2017 10101
46 10101142046 9 2017 10101
47 10101142047 6 2017 10101
48 10101142049 136 2017 10101
49 10101152002 58 2017 10101
50 10101152006 14 2017 10101
51 10101152020 76 2017 10101
52 10101152031 90 2017 10101
53 10101152033 49 2017 10101
54 10101152049 7 2017 10101
55 10101152901 2 2017 10101
56 10101162006 18 2017 10101
57 10101162010 16 2017 10101
58 10101162020 31 2017 10101
59 10101162031 123 2017 10101
60 10101162032 2 2017 10101
61 10101162033 18 2017 10101
62 10101172029 198 2017 10101
1148 10102012001 3 2017 10102
1149 10102012004 2 2017 10102
1150 10102012008 19 2017 10102
1151 10102012017 3 2017 10102
1152 10102012033 64 2017 10102
1153 10102022001 4 2017 10102
1154 10102022002 3 2017 10102
1155 10102022003 8 2017 10102
1156 10102022004 6 2017 10102
1157 10102022010 16 2017 10102
1158 10102022013 3 2017 10102
1159 10102032002 1 2017 10102
1160 10102032011 2 2017 10102
1161 10102032016 3 2017 10102
1162 10102032018 8 2017 10102
1163 10102032034 16 2017 10102
1164 10102032901 7 2017 10102
1165 10102042014 3 2017 10102
1166 10102042016 3 2017 10102
1167 10102042019 12 2017 10102
1168 10102042028 16 2017 10102
1169 10102042029 5 2017 10102
1170 10102042035 3 2017 10102
1171 10102042043 2 2017 10102
1172 10102042901 5 2017 10102
1173 10102052012 4 2017 10102
1174 10102052019 14 2017 10102
1175 10102052042 18 2017 10102
1176 10102052043 8 2017 10102
1177 10102062015 41 2017 10102
1178 10102062019 7 2017 10102
1179 10102062027 1 2017 10102
1180 10102062038 15 2017 10102
1181 10102062039 12 2017 10102
1182 10102072022 4 2017 10102
1183 10102082022 19 2017 10102
1184 10102092022 4 2017 10102
1185 10102102023 9 2017 10102


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 10101 10101142038 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
2 10101 10101142009 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
3 10101 10101142015 6 2017 Puerto Montt 176237.4 2017 245902 43337141298
4 10101 10101072029 81 2017 Puerto Montt 176237.4 2017 245902 43337141298
5 10101 10101072036 5 2017 Puerto Montt 176237.4 2017 245902 43337141298
6 10101 10101072045 12 2017 Puerto Montt 176237.4 2017 245902 43337141298
7 10101 10101142027 11 2017 Puerto Montt 176237.4 2017 245902 43337141298
8 10101 10101082016 10 2017 Puerto Montt 176237.4 2017 245902 43337141298
9 10101 10101082017 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
10 10101 10101082018 34 2017 Puerto Montt 176237.4 2017 245902 43337141298
11 10101 10101072050 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
12 10101 10101082034 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
13 10101 10101082042 51 2017 Puerto Montt 176237.4 2017 245902 43337141298
14 10101 10101082045 12 2017 Puerto Montt 176237.4 2017 245902 43337141298
15 10101 10101082030 13 2017 Puerto Montt 176237.4 2017 245902 43337141298
16 10101 10101072028 7 2017 Puerto Montt 176237.4 2017 245902 43337141298
17 10101 10101092037 18 2017 Puerto Montt 176237.4 2017 245902 43337141298
18 10101 10101092040 76 2017 Puerto Montt 176237.4 2017 245902 43337141298
19 10101 10101092041 265 2017 Puerto Montt 176237.4 2017 245902 43337141298
20 10101 10101092044 49 2017 Puerto Montt 176237.4 2017 245902 43337141298
21 10101 10101102005 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
22 10101 10101102007 22 2017 Puerto Montt 176237.4 2017 245902 43337141298
23 10101 10101102026 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
24 10101 10101102035 69 2017 Puerto Montt 176237.4 2017 245902 43337141298
25 10101 10101102037 15 2017 Puerto Montt 176237.4 2017 245902 43337141298
26 10101 10101102901 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
27 10101 10101112025 32 2017 Puerto Montt 176237.4 2017 245902 43337141298
28 10101 10101092004 11 2017 Puerto Montt 176237.4 2017 245902 43337141298
29 10101 10101092008 195 2017 Puerto Montt 176237.4 2017 245902 43337141298
30 10101 10101132023 13 2017 Puerto Montt 176237.4 2017 245902 43337141298
31 10101 10101132027 11 2017 Puerto Montt 176237.4 2017 245902 43337141298
32 10101 10101132049 152 2017 Puerto Montt 176237.4 2017 245902 43337141298
33 10101 10101032002 20 2017 Puerto Montt 176237.4 2017 245902 43337141298
34 10101 10101032011 50 2017 Puerto Montt 176237.4 2017 245902 43337141298
35 10101 10101032019 33 2017 Puerto Montt 176237.4 2017 245902 43337141298
36 10101 10101042010 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
37 10101 10101062003 19 2017 Puerto Montt 176237.4 2017 245902 43337141298
38 10101 10101062008 144 2017 Puerto Montt 176237.4 2017 245902 43337141298
39 10101 10101062013 135 2017 Puerto Montt 176237.4 2017 245902 43337141298
40 10101 10101062029 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
41 10101 10101062039 4 2017 Puerto Montt 176237.4 2017 245902 43337141298
42 10101 10101072014 74 2017 Puerto Montt 176237.4 2017 245902 43337141298
43 10101 10101072021 5 2017 Puerto Montt 176237.4 2017 245902 43337141298
44 10101 10101152031 90 2017 Puerto Montt 176237.4 2017 245902 43337141298
45 10101 10101152033 49 2017 Puerto Montt 176237.4 2017 245902 43337141298
46 10101 10101152049 7 2017 Puerto Montt 176237.4 2017 245902 43337141298
47 10101 10101152901 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
48 10101 10101162006 18 2017 Puerto Montt 176237.4 2017 245902 43337141298
49 10101 10101162010 16 2017 Puerto Montt 176237.4 2017 245902 43337141298
50 10101 10101162020 31 2017 Puerto Montt 176237.4 2017 245902 43337141298
51 10101 10101162031 123 2017 Puerto Montt 176237.4 2017 245902 43337141298
52 10101 10101162032 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
53 10101 10101162033 18 2017 Puerto Montt 176237.4 2017 245902 43337141298
54 10101 10101172029 198 2017 Puerto Montt 176237.4 2017 245902 43337141298
55 10101 10101122024 16 2017 Puerto Montt 176237.4 2017 245902 43337141298
56 10101 10101132022 29 2017 Puerto Montt 176237.4 2017 245902 43337141298
57 10101 10101152020 76 2017 Puerto Montt 176237.4 2017 245902 43337141298
58 10101 10101142047 6 2017 Puerto Montt 176237.4 2017 245902 43337141298
59 10101 10101142049 136 2017 Puerto Montt 176237.4 2017 245902 43337141298
60 10101 10101152002 58 2017 Puerto Montt 176237.4 2017 245902 43337141298
61 10101 10101142046 9 2017 Puerto Montt 176237.4 2017 245902 43337141298
62 10101 10101152006 14 2017 Puerto Montt 176237.4 2017 245902 43337141298
63 10102 10102012017 3 2017 Calbuco 155443.9 2017 33985 5282762017
64 10102 10102012033 64 2017 Calbuco 155443.9 2017 33985 5282762017
65 10102 10102022001 4 2017 Calbuco 155443.9 2017 33985 5282762017
66 10102 10102022003 8 2017 Calbuco 155443.9 2017 33985 5282762017
67 10102 10102022004 6 2017 Calbuco 155443.9 2017 33985 5282762017
68 10102 10102022010 16 2017 Calbuco 155443.9 2017 33985 5282762017
69 10102 10102022002 3 2017 Calbuco 155443.9 2017 33985 5282762017
70 10102 10102012008 19 2017 Calbuco 155443.9 2017 33985 5282762017
71 10102 10102032901 7 2017 Calbuco 155443.9 2017 33985 5282762017
72 10102 10102042014 3 2017 Calbuco 155443.9 2017 33985 5282762017
73 10102 10102042016 3 2017 Calbuco 155443.9 2017 33985 5282762017
74 10102 10102042019 12 2017 Calbuco 155443.9 2017 33985 5282762017
75 10102 10102042028 16 2017 Calbuco 155443.9 2017 33985 5282762017
76 10102 10102042029 5 2017 Calbuco 155443.9 2017 33985 5282762017
77 10102 10102042035 3 2017 Calbuco 155443.9 2017 33985 5282762017
78 10102 10102022013 3 2017 Calbuco 155443.9 2017 33985 5282762017
79 10102 10102032002 1 2017 Calbuco 155443.9 2017 33985 5282762017
80 10102 10102032011 2 2017 Calbuco 155443.9 2017 33985 5282762017
81 10102 10102012001 3 2017 Calbuco 155443.9 2017 33985 5282762017
82 10102 10102012004 2 2017 Calbuco 155443.9 2017 33985 5282762017
83 10102 10102032034 16 2017 Calbuco 155443.9 2017 33985 5282762017
84 10102 10102062015 41 2017 Calbuco 155443.9 2017 33985 5282762017
85 10102 10102062019 7 2017 Calbuco 155443.9 2017 33985 5282762017
86 10102 10102062027 1 2017 Calbuco 155443.9 2017 33985 5282762017
87 10102 10102062038 15 2017 Calbuco 155443.9 2017 33985 5282762017
88 10102 10102062039 12 2017 Calbuco 155443.9 2017 33985 5282762017
89 10102 10102072022 4 2017 Calbuco 155443.9 2017 33985 5282762017
90 10102 10102082022 19 2017 Calbuco 155443.9 2017 33985 5282762017
91 10102 10102092022 4 2017 Calbuco 155443.9 2017 33985 5282762017
92 10102 10102102023 9 2017 Calbuco 155443.9 2017 33985 5282762017
93 10102 10102112023 12 2017 Calbuco 155443.9 2017 33985 5282762017
94 10102 10102122023 12 2017 Calbuco 155443.9 2017 33985 5282762017
95 10102 10102132023 26 2017 Calbuco 155443.9 2017 33985 5282762017
96 10102 10102142901 11 2017 Calbuco 155443.9 2017 33985 5282762017
97 10102 10102152006 45 2017 Calbuco 155443.9 2017 33985 5282762017
98 10102 10102162009 7 2017 Calbuco 155443.9 2017 33985 5282762017
99 10102 10102162030 8 2017 Calbuco 155443.9 2017 33985 5282762017
100 10102 10102162031 7 2017 Calbuco 155443.9 2017 33985 5282762017
101 10102 10102162036 7 2017 Calbuco 155443.9 2017 33985 5282762017
102 10102 10102162040 8 2017 Calbuco 155443.9 2017 33985 5282762017
103 10102 10102162041 9 2017 Calbuco 155443.9 2017 33985 5282762017
104 10102 10102172024 4 2017 Calbuco 155443.9 2017 33985 5282762017
105 10102 10102182021 10 2017 Calbuco 155443.9 2017 33985 5282762017
106 10102 10102192026 8 2017 Calbuco 155443.9 2017 33985 5282762017
107 10102 10102202025 2 2017 Calbuco 155443.9 2017 33985 5282762017
108 10102 10102032016 3 2017 Calbuco 155443.9 2017 33985 5282762017
109 10102 10102032018 8 2017 Calbuco 155443.9 2017 33985 5282762017
110 10102 10102052043 8 2017 Calbuco 155443.9 2017 33985 5282762017
111 10102 10102042901 5 2017 Calbuco 155443.9 2017 33985 5282762017
112 10102 10102052012 4 2017 Calbuco 155443.9 2017 33985 5282762017
113 10102 10102052019 14 2017 Calbuco 155443.9 2017 33985 5282762017
114 10102 10102042043 2 2017 Calbuco 155443.9 2017 33985 5282762017
115 10102 10102052042 18 2017 Calbuco 155443.9 2017 33985 5282762017
133 10104 10104042047 16 2017 Fresia 183977.2 2017 12261 2255743895
134 10104 10104042054 2 2017 Fresia 183977.2 2017 12261 2255743895
135 10104 10104052004 6 2017 Fresia 183977.2 2017 12261 2255743895
136 10104 10104052041 4 2017 Fresia 183977.2 2017 12261 2255743895
137 10104 10104052046 2 2017 Fresia 183977.2 2017 12261 2255743895
138 10104 10104062013 4 2017 Fresia 183977.2 2017 12261 2255743895
139 10104 10104052030 5 2017 Fresia 183977.2 2017 12261 2255743895
140 10104 10104042024 18 2017 Fresia 183977.2 2017 12261 2255743895
141 10104 10104012007 3 2017 Fresia 183977.2 2017 12261 2255743895
142 10104 10104012009 1 2017 Fresia 183977.2 2017 12261 2255743895
143 10104 10104012012 19 2017 Fresia 183977.2 2017 12261 2255743895
144 10104 10104012015 1 2017 Fresia 183977.2 2017 12261 2255743895
145 10104 10104012016 3 2017 Fresia 183977.2 2017 12261 2255743895
146 10104 10104012018 4 2017 Fresia 183977.2 2017 12261 2255743895
147 10104 10104012020 3 2017 Fresia 183977.2 2017 12261 2255743895
148 10104 10104012024 1 2017 Fresia 183977.2 2017 12261 2255743895
149 10104 10104012025 2 2017 Fresia 183977.2 2017 12261 2255743895
150 10104 10104012038 2 2017 Fresia 183977.2 2017 12261 2255743895
151 10104 10104012041 2 2017 Fresia 183977.2 2017 12261 2255743895
152 10104 10104012042 1 2017 Fresia 183977.2 2017 12261 2255743895
153 10104 10104012047 2 2017 Fresia 183977.2 2017 12261 2255743895
154 10104 10104012052 1 2017 Fresia 183977.2 2017 12261 2255743895
155 10104 10104012053 2 2017 Fresia 183977.2 2017 12261 2255743895
156 10104 10104012901 1 2017 Fresia 183977.2 2017 12261 2255743895
157 10104 10104022017 1 2017 Fresia 183977.2 2017 12261 2255743895
158 10104 10104022021 2 2017 Fresia 183977.2 2017 12261 2255743895
159 10104 10104032002 1 2017 Fresia 183977.2 2017 12261 2255743895
160 10104 10104032019 11 2017 Fresia 183977.2 2017 12261 2255743895
161 10104 10104032023 3 2017 Fresia 183977.2 2017 12261 2255743895
162 10104 10104032037 1 2017 Fresia 183977.2 2017 12261 2255743895
163 10104 10104032055 28 2017 Fresia 183977.2 2017 12261 2255743895
164 10104 10104042001 1 2017 Fresia 183977.2 2017 12261 2255743895
165 10104 10104042008 7 2017 Fresia 183977.2 2017 12261 2255743895
166 10104 10104042022 10 2017 Fresia 183977.2 2017 12261 2255743895
167 10104 10104062056 3 2017 Fresia 183977.2 2017 12261 2255743895
168 10104 10104062901 1 2017 Fresia 183977.2 2017 12261 2255743895
169 10104 10104062031 2 2017 Fresia 183977.2 2017 12261 2255743895
170 10104 10104062043 1 2017 Fresia 183977.2 2017 12261 2255743895
171 10104 10104062049 3 2017 Fresia 183977.2 2017 12261 2255743895
172 10104 10104062027 3 2017 Fresia 183977.2 2017 12261 2255743895
173 10105 10105032029 9 2017 Frutillar 174883.1 2017 18428 3222744874
174 10105 10105042008 4 2017 Frutillar 174883.1 2017 18428 3222744874
175 10105 10105042013 6 2017 Frutillar 174883.1 2017 18428 3222744874
176 10105 10105042015 20 2017 Frutillar 174883.1 2017 18428 3222744874
177 10105 10105042027 10 2017 Frutillar 174883.1 2017 18428 3222744874
178 10105 10105012024 43 2017 Frutillar 174883.1 2017 18428 3222744874
179 10105 10105012025 98 2017 Frutillar 174883.1 2017 18428 3222744874
180 10105 10105032011 17 2017 Frutillar 174883.1 2017 18428 3222744874
181 10105 10105032014 9 2017 Frutillar 174883.1 2017 18428 3222744874
182 10105 10105012009 3 2017 Frutillar 174883.1 2017 18428 3222744874
183 10105 10105012010 68 2017 Frutillar 174883.1 2017 18428 3222744874
184 10105 10105012013 6 2017 Frutillar 174883.1 2017 18428 3222744874
185 10105 10105012019 15 2017 Frutillar 174883.1 2017 18428 3222744874
186 10105 10105012023 3 2017 Frutillar 174883.1 2017 18428 3222744874
187 10105 10105022022 1 2017 Frutillar 174883.1 2017 18428 3222744874
188 10105 10105022028 8 2017 Frutillar 174883.1 2017 18428 3222744874
189 10105 10105012026 10 2017 Frutillar 174883.1 2017 18428 3222744874
190 10105 10105012030 22 2017 Frutillar 174883.1 2017 18428 3222744874
191 10105 10105022001 10 2017 Frutillar 174883.1 2017 18428 3222744874
192 10105 10105022003 5 2017 Frutillar 174883.1 2017 18428 3222744874
193 10105 10105022005 6 2017 Frutillar 174883.1 2017 18428 3222744874
194 10105 10105022012 7 2017 Frutillar 174883.1 2017 18428 3222744874
195 10105 10105022016 4 2017 Frutillar 174883.1 2017 18428 3222744874
196 10105 10105022017 3 2017 Frutillar 174883.1 2017 18428 3222744874
197 10105 10105022018 4 2017 Frutillar 174883.1 2017 18428 3222744874
198 10105 10105022020 6 2017 Frutillar 174883.1 2017 18428 3222744874
199 10105 10105022021 3 2017 Frutillar 174883.1 2017 18428 3222744874
200 10105 10105032006 20 2017 Frutillar 174883.1 2017 18428 3222744874
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514 10204 10204012003 26 2017 Curaco de Vélez 177952.2 2017 3829 681378864
515 10204 10204012007 13 2017 Curaco de Vélez 177952.2 2017 3829 681378864
516 10204 10204022013 3 2017 Curaco de Vélez 177952.2 2017 3829 681378864
517 10204 10204022014 21 2017 Curaco de Vélez 177952.2 2017 3829 681378864
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520 10204 10204032012 9 2017 Curaco de Vélez 177952.2 2017 3829 681378864
521 10204 10204012002 11 2017 Curaco de Vélez 177952.2 2017 3829 681378864
522 10204 10204012013 1 2017 Curaco de Vélez 177952.2 2017 3829 681378864
523 10204 10204012015 21 2017 Curaco de Vélez 177952.2 2017 3829 681378864
524 10204 10204012008 6 2017 Curaco de Vélez 177952.2 2017 3829 681378864
525 10204 10204012010 3 2017 Curaco de Vélez 177952.2 2017 3829 681378864
526 10204 10204022006 5 2017 Curaco de Vélez 177952.2 2017 3829 681378864
527 10204 10204022008 4 2017 Curaco de Vélez 177952.2 2017 3829 681378864
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529 10205 10205012013 29 2017 Dalcahue 207717.6 2017 13762 2858609503
530 10205 10205012027 13 2017 Dalcahue 207717.6 2017 13762 2858609503
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532 10205 10205022011 5 2017 Dalcahue 207717.6 2017 13762 2858609503
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534 10205 10205022015 6 2017 Dalcahue 207717.6 2017 13762 2858609503
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538 10205 10205032019 1 2017 Dalcahue 207717.6 2017 13762 2858609503
539 10205 10205012014 25 2017 Dalcahue 207717.6 2017 13762 2858609503
540 10205 10205012015 8 2017 Dalcahue 207717.6 2017 13762 2858609503
541 10205 10205012018 26 2017 Dalcahue 207717.6 2017 13762 2858609503
542 10205 10205012020 1 2017 Dalcahue 207717.6 2017 13762 2858609503
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552 10205 10205042004 10 2017 Dalcahue 207717.6 2017 13762 2858609503
553 10205 10205042008 2 2017 Dalcahue 207717.6 2017 13762 2858609503
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567 10206 10206022003 5 2017 Puqueldón 208274.8 2017 3921 816645370
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819 10303 10303062030 2 2017 Purranque 186719.5 2017 20369 3803288945
820 10303 10303062032 4 2017 Purranque 186719.5 2017 20369 3803288945
821 10303 10303052012 4 2017 Purranque 186719.5 2017 20369 3803288945
822 10303 10303052016 2 2017 Purranque 186719.5 2017 20369 3803288945
823 10303 10303052019 3 2017 Purranque 186719.5 2017 20369 3803288945
824 10303 10303052034 6 2017 Purranque 186719.5 2017 20369 3803288945
825 10303 10303072032 1 2017 Purranque 186719.5 2017 20369 3803288945
826 10303 10303072041 3 2017 Purranque 186719.5 2017 20369 3803288945
827 10303 10303082001 5 2017 Purranque 186719.5 2017 20369 3803288945
828 10303 10303082035 2 2017 Purranque 186719.5 2017 20369 3803288945
829 10303 10303082043 1 2017 Purranque 186719.5 2017 20369 3803288945
830 10303 10303062038 3 2017 Purranque 186719.5 2017 20369 3803288945
831 10303 10303072011 11 2017 Purranque 186719.5 2017 20369 3803288945
832 10303 10303072021 2 2017 Purranque 186719.5 2017 20369 3803288945
833 10303 10303072024 16 2017 Purranque 186719.5 2017 20369 3803288945
834 10304 10304012038 1 2017 Puyehue 176006.9 2017 11667 2053472049
835 10304 10304012901 7 2017 Puyehue 176006.9 2017 11667 2053472049
836 10304 10304022001 1 2017 Puyehue 176006.9 2017 11667 2053472049
837 10304 10304022002 3 2017 Puyehue 176006.9 2017 11667 2053472049
838 10304 10304012025 14 2017 Puyehue 176006.9 2017 11667 2053472049
839 10304 10304012030 2 2017 Puyehue 176006.9 2017 11667 2053472049
840 10304 10304012033 4 2017 Puyehue 176006.9 2017 11667 2053472049
841 10304 10304012036 26 2017 Puyehue 176006.9 2017 11667 2053472049
842 10304 10304012037 14 2017 Puyehue 176006.9 2017 11667 2053472049
843 10304 10304042016 2 2017 Puyehue 176006.9 2017 11667 2053472049
844 10304 10304042023 2 2017 Puyehue 176006.9 2017 11667 2053472049
845 10304 10304042901 3 2017 Puyehue 176006.9 2017 11667 2053472049
846 10304 10304012010 14 2017 Puyehue 176006.9 2017 11667 2053472049
847 10304 10304012011 2 2017 Puyehue 176006.9 2017 11667 2053472049
848 10304 10304012012 5 2017 Puyehue 176006.9 2017 11667 2053472049
849 10304 10304012013 1 2017 Puyehue 176006.9 2017 11667 2053472049
850 10304 10304012015 14 2017 Puyehue 176006.9 2017 11667 2053472049
851 10304 10304012016 9 2017 Puyehue 176006.9 2017 11667 2053472049
852 10304 10304012020 5 2017 Puyehue 176006.9 2017 11667 2053472049
853 10304 10304032010 10 2017 Puyehue 176006.9 2017 11667 2053472049
854 10304 10304032012 1 2017 Puyehue 176006.9 2017 11667 2053472049
855 10304 10304032018 1 2017 Puyehue 176006.9 2017 11667 2053472049
856 10304 10304032019 12 2017 Puyehue 176006.9 2017 11667 2053472049
857 10304 10304032021 5 2017 Puyehue 176006.9 2017 11667 2053472049
858 10304 10304032024 1 2017 Puyehue 176006.9 2017 11667 2053472049
859 10304 10304032026 17 2017 Puyehue 176006.9 2017 11667 2053472049
860 10304 10304032027 4 2017 Puyehue 176006.9 2017 11667 2053472049
861 10304 10304022032 1 2017 Puyehue 176006.9 2017 11667 2053472049
862 10304 10304022044 74 2017 Puyehue 176006.9 2017 11667 2053472049
863 10304 10304032006 7 2017 Puyehue 176006.9 2017 11667 2053472049
864 10304 10304032007 3 2017 Puyehue 176006.9 2017 11667 2053472049
865 10304 10304032009 5 2017 Puyehue 176006.9 2017 11667 2053472049
866 10304 10304032041 8 2017 Puyehue 176006.9 2017 11667 2053472049
867 10304 10304032042 2 2017 Puyehue 176006.9 2017 11667 2053472049
868 10304 10304032901 1 2017 Puyehue 176006.9 2017 11667 2053472049
869 10304 10304042013 6 2017 Puyehue 176006.9 2017 11667 2053472049
870 10304 10304012004 8 2017 Puyehue 176006.9 2017 11667 2053472049
871 10304 10304012005 2 2017 Puyehue 176006.9 2017 11667 2053472049
872 10304 10304012008 6 2017 Puyehue 176006.9 2017 11667 2053472049
873 10304 10304032035 3 2017 Puyehue 176006.9 2017 11667 2053472049
874 10304 10304032028 1 2017 Puyehue 176006.9 2017 11667 2053472049
875 10304 10304032029 2 2017 Puyehue 176006.9 2017 11667 2053472049
876 10304 10304032034 16 2017 Puyehue 176006.9 2017 11667 2053472049
877 10304 10304032040 13 2017 Puyehue 176006.9 2017 11667 2053472049
878 10305 10305032019 16 2017 Río Negro 156568.1 2017 14085 2205262341
879 10305 10305012025 2 2017 Río Negro 156568.1 2017 14085 2205262341
880 10305 10305012026 1 2017 Río Negro 156568.1 2017 14085 2205262341
881 10305 10305012027 9 2017 Río Negro 156568.1 2017 14085 2205262341
882 10305 10305012030 22 2017 Río Negro 156568.1 2017 14085 2205262341
883 10305 10305022008 31 2017 Río Negro 156568.1 2017 14085 2205262341
884 10305 10305022044 2 2017 Río Negro 156568.1 2017 14085 2205262341
885 10305 10305022901 3 2017 Río Negro 156568.1 2017 14085 2205262341
886 10305 10305012008 5 2017 Río Negro 156568.1 2017 14085 2205262341
887 10305 10305012010 12 2017 Río Negro 156568.1 2017 14085 2205262341
888 10305 10305012013 8 2017 Río Negro 156568.1 2017 14085 2205262341
889 10305 10305012015 6 2017 Río Negro 156568.1 2017 14085 2205262341
890 10305 10305012016 19 2017 Río Negro 156568.1 2017 14085 2205262341
891 10305 10305012021 2 2017 Río Negro 156568.1 2017 14085 2205262341
892 10305 10305012024 5 2017 Río Negro 156568.1 2017 14085 2205262341
893 10305 10305042001 36 2017 Río Negro 156568.1 2017 14085 2205262341
894 10305 10305042002 1 2017 Río Negro 156568.1 2017 14085 2205262341
895 10305 10305042005 11 2017 Río Negro 156568.1 2017 14085 2205262341
896 10305 10305042007 21 2017 Río Negro 156568.1 2017 14085 2205262341
897 10305 10305042014 5 2017 Río Negro 156568.1 2017 14085 2205262341
898 10305 10305042041 1 2017 Río Negro 156568.1 2017 14085 2205262341
899 10305 10305042043 16 2017 Río Negro 156568.1 2017 14085 2205262341
900 10305 10305052006 6 2017 Río Negro 156568.1 2017 14085 2205262341
901 10305 10305052007 1 2017 Río Negro 156568.1 2017 14085 2205262341
902 10305 10305032023 6 2017 Río Negro 156568.1 2017 14085 2205262341
903 10305 10305032031 4 2017 Río Negro 156568.1 2017 14085 2205262341
904 10305 10305032032 2 2017 Río Negro 156568.1 2017 14085 2205262341
905 10305 10305032044 5 2017 Río Negro 156568.1 2017 14085 2205262341
906 10305 10305052042 14 2017 Río Negro 156568.1 2017 14085 2205262341
907 10305 10305062003 2 2017 Río Negro 156568.1 2017 14085 2205262341
908 10305 10305062004 1 2017 Río Negro 156568.1 2017 14085 2205262341
909 10305 10305062011 2 2017 Río Negro 156568.1 2017 14085 2205262341
910 10305 10305062012 2 2017 Río Negro 156568.1 2017 14085 2205262341
911 10305 10305062018 1 2017 Río Negro 156568.1 2017 14085 2205262341
912 10305 10305062020 4 2017 Río Negro 156568.1 2017 14085 2205262341
913 10305 10305062028 3 2017 Río Negro 156568.1 2017 14085 2205262341
914 10305 10305062034 4 2017 Río Negro 156568.1 2017 14085 2205262341
915 10305 10305052010 16 2017 Río Negro 156568.1 2017 14085 2205262341
916 10305 10305052022 11 2017 Río Negro 156568.1 2017 14085 2205262341
917 10305 10305052035 3 2017 Río Negro 156568.1 2017 14085 2205262341
918 10305 10305052037 14 2017 Río Negro 156568.1 2017 14085 2205262341
919 10305 10305062036 3 2017 Río Negro 156568.1 2017 14085 2205262341
920 10305 10305062038 35 2017 Río Negro 156568.1 2017 14085 2205262341
921 10306 10306012028 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
922 10306 10306012042 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
923 10306 10306012043 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
924 10306 10306012031 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
925 10306 10306012037 4 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
926 10306 10306012060 3 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
927 10306 10306022016 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
928 10306 10306012052 4 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
929 10306 10306012054 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
930 10306 10306012003 5 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
931 10306 10306012012 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
932 10306 10306012018 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
933 10306 10306022049 3 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
934 10306 10306022051 6 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
935 10306 10306022055 3 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
936 10306 10306022068 13 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
937 10306 10306022070 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
938 10306 10306022901 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
939 10306 10306032006 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
940 10306 10306032009 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
941 10306 10306042007 3 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
942 10306 10306022024 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
943 10306 10306022027 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
944 10306 10306022032 6 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
945 10306 10306022033 8 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
946 10306 10306042063 6 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
947 10306 10306042073 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
948 10306 10306042901 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
949 10306 10306052015 6 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
950 10306 10306052048 14 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
951 10306 10306052058 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
952 10306 10306052901 1 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
953 10306 10306042036 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
954 10306 10306042047 12 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
955 10306 10306042019 2 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
956 10306 10306042035 6 2017 San Juan de la Costa 152674.0 2017 7512 1146887184
957 10307 10307032053 9 2017 San Pablo 181411.6 2017 10030 1819558805
958 10307 10307032054 5 2017 San Pablo 181411.6 2017 10030 1819558805
959 10307 10307032019 9 2017 San Pablo 181411.6 2017 10030 1819558805
960 10307 10307032025 11 2017 San Pablo 181411.6 2017 10030 1819558805
961 10307 10307032028 1 2017 San Pablo 181411.6 2017 10030 1819558805
962 10307 10307032035 10 2017 San Pablo 181411.6 2017 10030 1819558805
963 10307 10307032038 16 2017 San Pablo 181411.6 2017 10030 1819558805
964 10307 10307032041 4 2017 San Pablo 181411.6 2017 10030 1819558805
965 10307 10307032051 3 2017 San Pablo 181411.6 2017 10030 1819558805
966 10307 10307112027 1 2017 San Pablo 181411.6 2017 10030 1819558805
967 10307 10307112029 2 2017 San Pablo 181411.6 2017 10030 1819558805
968 10307 10307112032 2 2017 San Pablo 181411.6 2017 10030 1819558805
969 10307 10307112056 9 2017 San Pablo 181411.6 2017 10030 1819558805
970 10307 10307112901 2 2017 San Pablo 181411.6 2017 10030 1819558805
971 10307 10307122006 1 2017 San Pablo 181411.6 2017 10030 1819558805
972 10307 10307122008 4 2017 San Pablo 181411.6 2017 10030 1819558805
973 10307 10307122012 1 2017 San Pablo 181411.6 2017 10030 1819558805
974 10307 10307122013 3 2017 San Pablo 181411.6 2017 10030 1819558805
975 10307 10307122020 4 2017 San Pablo 181411.6 2017 10030 1819558805
976 10307 10307122023 3 2017 San Pablo 181411.6 2017 10030 1819558805
977 10307 10307122034 2 2017 San Pablo 181411.6 2017 10030 1819558805
978 10307 10307122037 4 2017 San Pablo 181411.6 2017 10030 1819558805
979 10307 10307122039 1 2017 San Pablo 181411.6 2017 10030 1819558805
980 10307 10307122043 1 2017 San Pablo 181411.6 2017 10030 1819558805
981 10307 10307122044 1 2017 San Pablo 181411.6 2017 10030 1819558805
982 10307 10307042003 5 2017 San Pablo 181411.6 2017 10030 1819558805
983 10307 10307042005 5 2017 San Pablo 181411.6 2017 10030 1819558805
984 10307 10307042030 14 2017 San Pablo 181411.6 2017 10030 1819558805
985 10307 10307042901 3 2017 San Pablo 181411.6 2017 10030 1819558805
986 10307 10307052010 3 2017 San Pablo 181411.6 2017 10030 1819558805
987 10307 10307052011 2 2017 San Pablo 181411.6 2017 10030 1819558805
988 10307 10307052036 3 2017 San Pablo 181411.6 2017 10030 1819558805
989 10307 10307052901 3 2017 San Pablo 181411.6 2017 10030 1819558805
990 10307 10307062030 3 2017 San Pablo 181411.6 2017 10030 1819558805
991 10307 10307062045 1 2017 San Pablo 181411.6 2017 10030 1819558805
992 10307 10307072042 11 2017 San Pablo 181411.6 2017 10030 1819558805
993 10307 10307072045 2 2017 San Pablo 181411.6 2017 10030 1819558805
994 10307 10307072055 6 2017 San Pablo 181411.6 2017 10030 1819558805
995 10307 10307082001 3 2017 San Pablo 181411.6 2017 10030 1819558805
996 10307 10307082014 4 2017 San Pablo 181411.6 2017 10030 1819558805
997 10307 10307082018 2 2017 San Pablo 181411.6 2017 10030 1819558805
998 10307 10307082039 18 2017 San Pablo 181411.6 2017 10030 1819558805
999 10307 10307092055 4 2017 San Pablo 181411.6 2017 10030 1819558805
1000 10307 10307092901 1 2017 San Pablo 181411.6 2017 10030 1819558805
1001 10307 10307102003 6 2017 San Pablo 181411.6 2017 10030 1819558805
1002 10307 10307102015 1 2017 San Pablo 181411.6 2017 10030 1819558805
1003 10307 10307102021 1 2017 San Pablo 181411.6 2017 10030 1819558805
1004 10307 10307102024 1 2017 San Pablo 181411.6 2017 10030 1819558805
1005 10307 10307112009 1 2017 San Pablo 181411.6 2017 10030 1819558805
1006 10307 10307012052 2 2017 San Pablo 181411.6 2017 10030 1819558805
1007 10307 10307022016 11 2017 San Pablo 181411.6 2017 10030 1819558805
1008 10307 10307022031 1 2017 San Pablo 181411.6 2017 10030 1819558805
1009 10307 10307022041 3 2017 San Pablo 181411.6 2017 10030 1819558805
1010 10307 10307022048 11 2017 San Pablo 181411.6 2017 10030 1819558805
1011 10307 10307022053 1 2017 San Pablo 181411.6 2017 10030 1819558805
1012 10307 10307032007 8 2017 San Pablo 181411.6 2017 10030 1819558805
1013 10307 10307032015 2 2017 San Pablo 181411.6 2017 10030 1819558805


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
10101 10101142038 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101142009 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101142015 6 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072029 81 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072036 5 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072045 12 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101142027 11 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082016 10 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082017 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082018 34 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072050 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082034 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082042 51 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082045 12 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101082030 13 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072028 7 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101092037 18 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101092040 76 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101092041 265 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101092044 49 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101102005 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101102007 22 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101102026 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101102035 69 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101102037 15 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101102901 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101112025 32 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101092004 11 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101092008 195 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101132023 13 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101132027 11 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101132049 152 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101032002 20 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101032011 50 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101032019 33 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101042010 1 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101062003 19 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101062008 144 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101062013 135 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101062029 3 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101062039 4 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072014 74 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101072021 5 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152031 90 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152033 49 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152049 7 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152901 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101162006 18 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101162010 16 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101162020 31 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101162031 123 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101162032 2 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101162033 18 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101172029 198 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101122024 16 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101132022 29 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152020 76 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101142047 6 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101142049 136 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152002 58 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101142046 9 2017 Puerto Montt 176237.4 2017 245902 43337141298
10101 10101152006 14 2017 Puerto Montt 176237.4 2017 245902 43337141298
10102 10102012017 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102012033 64 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102022001 4 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102022003 8 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102022004 6 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102022010 16 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102022002 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102012008 19 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102032901 7 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102042014 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102042016 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102042019 12 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102042028 16 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102042029 5 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102042035 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102022013 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102032002 1 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102032011 2 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102012001 3 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102012004 2 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102032034 16 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102062015 41 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102062019 7 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102062027 1 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102062038 15 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102062039 12 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102072022 4 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102082022 19 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102092022 4 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102102023 9 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102112023 12 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102122023 12 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102132023 26 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102142901 11 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102152006 45 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102162009 7 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102162030 8 2017 Calbuco 155443.9 2017 33985 5282762017
10102 10102162031 7 2017 Calbuco 155443.9 2017 33985 5282762017


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
10101032002 10101 20 2017 Puerto Montt 176237.4 2017 245902 43337141298 129 0.0005246 10101
10101032011 10101 50 2017 Puerto Montt 176237.4 2017 245902 43337141298 426 0.0017324 10101
10101032019 10101 33 2017 Puerto Montt 176237.4 2017 245902 43337141298 829 0.0033713 10101
10101042010 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 6 0.0000244 10101
10101062003 10101 19 2017 Puerto Montt 176237.4 2017 245902 43337141298 158 0.0006425 10101
10101062008 10101 144 2017 Puerto Montt 176237.4 2017 245902 43337141298 581 0.0023627 10101
10101062013 10101 135 2017 Puerto Montt 176237.4 2017 245902 43337141298 571 0.0023221 10101
10101062029 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 47 0.0001911 10101
10101062039 10101 4 2017 Puerto Montt 176237.4 2017 245902 43337141298 67 0.0002725 10101
10101072014 10101 74 2017 Puerto Montt 176237.4 2017 245902 43337141298 997 0.0040545 10101
10101072021 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 44 0.0001789 10101
10101072028 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 145 0.0005897 10101
10101072029 10101 81 2017 Puerto Montt 176237.4 2017 245902 43337141298 1051 0.0042741 10101
10101072036 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 118 0.0004799 10101
10101072045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 113 0.0004595 10101
10101072050 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101
10101082016 10101 10 2017 Puerto Montt 176237.4 2017 245902 43337141298 121 0.0004921 10101
10101082017 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 38 0.0001545 10101
10101082018 10101 34 2017 Puerto Montt 176237.4 2017 245902 43337141298 623 0.0025335 10101
10101082030 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 176 0.0007157 10101
10101082034 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101
10101082042 10101 51 2017 Puerto Montt 176237.4 2017 245902 43337141298 253 0.0010289 10101
10101082045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 123 0.0005002 10101
10101092004 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 97 0.0003945 10101
10101092008 10101 195 2017 Puerto Montt 176237.4 2017 245902 43337141298 752 0.0030581 10101
10101092037 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 276 0.0011224 10101
10101092040 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 509 0.0020699 10101
10101092041 10101 265 2017 Puerto Montt 176237.4 2017 245902 43337141298 1683 0.0068442 10101
10101092044 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 530 0.0021553 10101
10101102005 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 147 0.0005978 10101
10101102007 10101 22 2017 Puerto Montt 176237.4 2017 245902 43337141298 824 0.0033509 10101
10101102026 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 245 0.0009963 10101
10101102035 10101 69 2017 Puerto Montt 176237.4 2017 245902 43337141298 940 0.0038227 10101
10101102037 10101 15 2017 Puerto Montt 176237.4 2017 245902 43337141298 164 0.0006669 10101
10101102901 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 16 0.0000651 10101
10101112025 10101 32 2017 Puerto Montt 176237.4 2017 245902 43337141298 1078 0.0043839 10101
10101122024 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 952 0.0038715 10101
10101132022 10101 29 2017 Puerto Montt 176237.4 2017 245902 43337141298 703 0.0028589 10101
10101132023 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 603 0.0024522 10101
10101132027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 105 0.0004270 10101
10101132049 10101 152 2017 Puerto Montt 176237.4 2017 245902 43337141298 1883 0.0076575 10101
10101142009 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 59 0.0002399 10101
10101142015 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 124 0.0005043 10101
10101142027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 192 0.0007808 10101
10101142038 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 53 0.0002155 10101
10101142046 10101 9 2017 Puerto Montt 176237.4 2017 245902 43337141298 317 0.0012891 10101
10101142047 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 263 0.0010695 10101
10101142049 10101 136 2017 Puerto Montt 176237.4 2017 245902 43337141298 973 0.0039569 10101
10101152002 10101 58 2017 Puerto Montt 176237.4 2017 245902 43337141298 554 0.0022529 10101
10101152006 10101 14 2017 Puerto Montt 176237.4 2017 245902 43337141298 214 0.0008703 10101
10101152020 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 617 0.0025091 10101
10101152031 10101 90 2017 Puerto Montt 176237.4 2017 245902 43337141298 642 0.0026108 10101
10101152033 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 700 0.0028467 10101
10101152049 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 96 0.0003904 10101
10101152901 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 46 0.0001871 10101
10101162006 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 233 0.0009475 10101
10101162010 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 351 0.0014274 10101
10101162020 10101 31 2017 Puerto Montt 176237.4 2017 245902 43337141298 205 0.0008337 10101
10101162031 10101 123 2017 Puerto Montt 176237.4 2017 245902 43337141298 762 0.0030988 10101
10101162032 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 24 0.0000976 10101
10101162033 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 168 0.0006832 10101
10101172029 10101 198 2017 Puerto Montt 176237.4 2017 245902 43337141298 854 0.0034729 10101
10102012001 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 80 0.0023540 10102
10102012004 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 283 0.0083272 10102
10102012008 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 697 0.0205090 10102
10102012017 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 268 0.0078858 10102
10102012033 10102 64 2017 Calbuco 155443.9 2017 33985 5282762017 1490 0.0438429 10102
10102022001 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 164 0.0048257 10102
10102022002 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102
10102022003 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 184 0.0054142 10102
10102022004 10102 6 2017 Calbuco 155443.9 2017 33985 5282762017 74 0.0021774 10102
10102022010 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 294 0.0086509 10102
10102022013 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 450 0.0132411 10102
10102032002 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 54 0.0015889 10102
10102032011 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 163 0.0047962 10102
10102032016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 95 0.0027954 10102
10102032018 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 470 0.0138296 10102
10102032034 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 695 0.0204502 10102
10102032901 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 89 0.0026188 10102
10102042014 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 87 0.0025600 10102
10102042016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 48 0.0014124 10102
10102042019 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 336 0.0098867 10102
10102042028 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 171 0.0050316 10102
10102042029 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 183 0.0053847 10102
10102042035 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 271 0.0079741 10102
10102042043 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 86 0.0025305 10102
10102042901 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 127 0.0037369 10102
10102052012 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 302 0.0088863 10102
10102052019 10102 14 2017 Calbuco 155443.9 2017 33985 5282762017 332 0.0097690 10102
10102052042 10102 18 2017 Calbuco 155443.9 2017 33985 5282762017 410 0.0120641 10102
10102052043 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 273 0.0080330 10102
10102062015 10102 41 2017 Calbuco 155443.9 2017 33985 5282762017 1129 0.0332205 10102
10102062019 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 362 0.0106518 10102
10102062027 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 25 0.0007356 10102
10102062038 10102 15 2017 Calbuco 155443.9 2017 33985 5282762017 357 0.0105046 10102
10102062039 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 643 0.0189201 10102
10102072022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 148 0.0043549 10102
10102082022 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 565 0.0166250 10102
10102092022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102
10102102023 10102 9 2017 Calbuco 155443.9 2017 33985 5282762017 630 0.0185376 10102


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
10101032002 10101 20 2017 Puerto Montt 176237.4 2017 245902 43337141298 129 0.0005246 10101 22734631
10101032011 10101 50 2017 Puerto Montt 176237.4 2017 245902 43337141298 426 0.0017324 10101 75077153
10101032019 10101 33 2017 Puerto Montt 176237.4 2017 245902 43337141298 829 0.0033713 10101 146100846
10101042010 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 6 0.0000244 10101 1057425
10101062003 10101 19 2017 Puerto Montt 176237.4 2017 245902 43337141298 158 0.0006425 10101 27845517
10101062008 10101 144 2017 Puerto Montt 176237.4 2017 245902 43337141298 581 0.0023627 10101 102393958
10101062013 10101 135 2017 Puerto Montt 176237.4 2017 245902 43337141298 571 0.0023221 10101 100631584
10101062029 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 47 0.0001911 10101 8283160
10101062039 10101 4 2017 Puerto Montt 176237.4 2017 245902 43337141298 67 0.0002725 10101 11807909
10101072014 10101 74 2017 Puerto Montt 176237.4 2017 245902 43337141298 997 0.0040545 10101 175708737
10101072021 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 44 0.0001789 10101 7754448
10101072028 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 145 0.0005897 10101 25554430
10101072029 10101 81 2017 Puerto Montt 176237.4 2017 245902 43337141298 1051 0.0042741 10101 185225559
10101072036 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 118 0.0004799 10101 20796019
10101072045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 113 0.0004595 10101 19914832
10101072050 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101 11631672
10101082016 10101 10 2017 Puerto Montt 176237.4 2017 245902 43337141298 121 0.0004921 10101 21324731
10101082017 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 38 0.0001545 10101 6697023
10101082018 10101 34 2017 Puerto Montt 176237.4 2017 245902 43337141298 623 0.0025335 10101 109795931
10101082030 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 176 0.0007157 10101 31017791
10101082034 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101 11631672
10101082042 10101 51 2017 Puerto Montt 176237.4 2017 245902 43337141298 253 0.0010289 10101 44588075
10101082045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 123 0.0005002 10101 21677206
10101092004 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 97 0.0003945 10101 17095033
10101092008 10101 195 2017 Puerto Montt 176237.4 2017 245902 43337141298 752 0.0030581 10101 132530562
10101092037 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 276 0.0011224 10101 48641536
10101092040 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 509 0.0020699 10101 89704862
10101092041 10101 265 2017 Puerto Montt 176237.4 2017 245902 43337141298 1683 0.0068442 10101 296607627
10101092044 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 530 0.0021553 10101 93405848
10101102005 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 147 0.0005978 10101 25906905
10101102007 10101 22 2017 Puerto Montt 176237.4 2017 245902 43337141298 824 0.0033509 10101 145219658
10101102026 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 245 0.0009963 10101 43178175
10101102035 10101 69 2017 Puerto Montt 176237.4 2017 245902 43337141298 940 0.0038227 10101 165663202
10101102037 10101 15 2017 Puerto Montt 176237.4 2017 245902 43337141298 164 0.0006669 10101 28902942
10101102901 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 16 0.0000651 10101 2819799
10101112025 10101 32 2017 Puerto Montt 176237.4 2017 245902 43337141298 1078 0.0043839 10101 189983971
10101122024 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 952 0.0038715 10101 167778052
10101132022 10101 29 2017 Puerto Montt 176237.4 2017 245902 43337141298 703 0.0028589 10101 123894927
10101132023 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 603 0.0024522 10101 106271182
10101132027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 105 0.0004270 10101 18504932
10101132049 10101 152 2017 Puerto Montt 176237.4 2017 245902 43337141298 1883 0.0076575 10101 331855117
10101142009 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 59 0.0002399 10101 10398010
10101142015 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 124 0.0005043 10101 21853444
10101142027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 192 0.0007808 10101 33837590
10101142038 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 53 0.0002155 10101 9340585
10101142046 10101 9 2017 Puerto Montt 176237.4 2017 245902 43337141298 317 0.0012891 10101 55867271
10101142047 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 263 0.0010695 10101 46350449
10101142049 10101 136 2017 Puerto Montt 176237.4 2017 245902 43337141298 973 0.0039569 10101 171479038
10101152002 10101 58 2017 Puerto Montt 176237.4 2017 245902 43337141298 554 0.0022529 10101 97635547
10101152006 10101 14 2017 Puerto Montt 176237.4 2017 245902 43337141298 214 0.0008703 10101 37714814
10101152020 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 617 0.0025091 10101 108738506
10101152031 10101 90 2017 Puerto Montt 176237.4 2017 245902 43337141298 642 0.0026108 10101 113144443
10101152033 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 700 0.0028467 10101 123366215
10101152049 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 96 0.0003904 10101 16918795
10101152901 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 46 0.0001871 10101 8106923
10101162006 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 233 0.0009475 10101 41063326
10101162010 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 351 0.0014274 10101 61859345
10101162020 10101 31 2017 Puerto Montt 176237.4 2017 245902 43337141298 205 0.0008337 10101 36128677
10101162031 10101 123 2017 Puerto Montt 176237.4 2017 245902 43337141298 762 0.0030988 10101 134292936
10101162032 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 24 0.0000976 10101 4229699
10101162033 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 168 0.0006832 10101 29607892
10101172029 10101 198 2017 Puerto Montt 176237.4 2017 245902 43337141298 854 0.0034729 10101 150506782
10102012001 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 80 0.0023540 10102 12435515
10102012004 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 283 0.0083272 10102 43990633
10102012008 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 697 0.0205090 10102 108344420
10102012017 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 268 0.0078858 10102 41658974
10102012033 10102 64 2017 Calbuco 155443.9 2017 33985 5282762017 1490 0.0438429 10102 231611458
10102022001 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 164 0.0048257 10102 25492805
10102022002 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102 47876731
10102022003 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 184 0.0054142 10102 28601683
10102022004 10102 6 2017 Calbuco 155443.9 2017 33985 5282762017 74 0.0021774 10102 11502851
10102022010 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 294 0.0086509 10102 45700516
10102022013 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 450 0.0132411 10102 69949769
10102032002 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 54 0.0015889 10102 8393972
10102032011 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 163 0.0047962 10102 25337361
10102032016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 95 0.0027954 10102 14767174
10102032018 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 470 0.0138296 10102 73058648
10102032034 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 695 0.0204502 10102 108033533
10102032901 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 89 0.0026188 10102 13834510
10102042014 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 87 0.0025600 10102 13523622
10102042016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 48 0.0014124 10102 7461309
10102042019 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 336 0.0098867 10102 52229161
10102042028 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 171 0.0050316 10102 26580912
10102042029 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 183 0.0053847 10102 28446239
10102042035 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 271 0.0079741 10102 42125305
10102042043 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 86 0.0025305 10102 13368178
10102042901 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 127 0.0037369 10102 19741379
10102052012 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 302 0.0088863 10102 46944067
10102052019 10102 14 2017 Calbuco 155443.9 2017 33985 5282762017 332 0.0097690 10102 51607385
10102052042 10102 18 2017 Calbuco 155443.9 2017 33985 5282762017 410 0.0120641 10102 63732012
10102052043 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 273 0.0080330 10102 42436193
10102062015 10102 41 2017 Calbuco 155443.9 2017 33985 5282762017 1129 0.0332205 10102 175496199
10102062019 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 362 0.0106518 10102 56270703
10102062027 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 25 0.0007356 10102 3886098
10102062038 10102 15 2017 Calbuco 155443.9 2017 33985 5282762017 357 0.0105046 10102 55493484
10102062039 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 643 0.0189201 10102 99950448
10102072022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 148 0.0043549 10102 23005702
10102082022 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 565 0.0166250 10102 87825821
10102092022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102 47876731
10102102023 10102 9 2017 Calbuco 155443.9 2017 33985 5282762017 630 0.0185376 10102 97929677

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 
## -166088923  -15526686   -7462451    6431300  179442852 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 22489571     957602   23.48   <2e-16 ***
## Freq.x        854755      24866   34.37   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 28030000 on 994 degrees of freedom
## Multiple R-squared:  0.5431, Adjusted R-squared:  0.5426 
## F-statistic:  1182 on 1 and 994 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 
## -166088923  -15526686   -7462451    6431300  179442852 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 22489571     957602   23.48   <2e-16 ***
## Freq.x        854755      24866   34.37   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 28030000 on 994 degrees of freedom
## Multiple R-squared:  0.5431, Adjusted R-squared:  0.5426 
## F-statistic:  1182 on 1 and 994 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 
## -166088923  -15526686   -7462451    6431300  179442852 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 22489571     957602   23.48   <2e-16 ***
## Freq.x        854755      24866   34.37   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 28030000 on 994 degrees of freedom
## Multiple R-squared:  0.5431, Adjusted R-squared:  0.5426 
## F-statistic:  1182 on 1 and 994 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 
## -64119514 -17466146  -3640118  12446142 326256183 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -5706520    1636983  -3.486 0.000512 ***
## log(Freq.x) 23242661     766266  30.332  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 29880000 on 994 degrees of freedom
## Multiple R-squared:  0.4807, Adjusted R-squared:  0.4802 
## F-statistic: 920.1 on 1 and 994 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 
## -91063253 -12574909  -3460352   7938329 167341041 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6129734    1272823  -4.816 1.69e-06 ***
## sqrt(Freq.x) 13841041     335423  41.264  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 25180000 on 994 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.631 
## F-statistic:  1703 on 1 and 994 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 
## -5017.0 -1170.0  -182.4   970.2  6801.2 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2649.89      87.96   30.13   <2e-16 ***
## sqrt(Freq.x)   875.45      23.18   37.77   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1740 on 994 degrees of freedom
## Multiple R-squared:  0.5893, Adjusted R-squared:  0.5889 
## F-statistic:  1427 on 1 and 994 DF,  p-value: < 2.2e-16

8.7 Modelo log-raíz

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

linearMod <- lm( log(multi_pob)~sqrt(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = log(multi_pob) ~ sqrt(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.5148 -0.4273  0.0566  0.5133  1.7660 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  16.067071   0.037724  425.91   <2e-16 ***
## sqrt(Freq.x)  0.276271   0.009941   27.79   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7461 on 994 degrees of freedom
## Multiple R-squared:  0.4372, Adjusted R-squared:  0.4367 
## F-statistic: 772.3 on 1 and 994 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 
## -4143.4 -1237.5  -191.8  1012.4  8544.4 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2365.70      98.18   24.10   <2e-16 ***
## log(Freq.x)  1648.54      45.96   35.87   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1792 on 994 degrees of freedom
## Multiple R-squared:  0.5642, Adjusted R-squared:  0.5637 
## F-statistic:  1287 on 1 and 994 DF,  p-value: < 2.2e-16

8.9 Modelo log-log

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

linearMod <- lm( log(multi_pob)~log(Freq.x) , data=h_y_m_comuna_corr_01)
summary(linearMod) 
## 
## Call:
## lm(formula = log(multi_pob) ~ log(Freq.x), data = h_y_m_comuna_corr_01)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.84621 -0.42955  0.03607  0.48730  1.75190 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.87306    0.03773  420.68   <2e-16 ***
## log(Freq.x)  0.58011    0.01766   32.84   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.6888 on 994 degrees of freedom
## Multiple R-squared:  0.5205, Adjusted R-squared:   0.52 
## F-statistic:  1079 on 1 and 994 DF,  p-value: < 2.2e-16

9 Modelo elegido: sqrt (sqrt)

Es éste el modelo que nos entrega el mayor coeficiente de determinación de todos (0.631).

9.1 Diagrama de dispersión sobre sqrt

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

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

9.2 Modelo sqrt

Observemos nuevamente el resultado sobre sqrt.

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 
## -91063253 -12574909  -3460352   7938329 167341041 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6129734    1272823  -4.816 1.69e-06 ***
## sqrt(Freq.x) 13841041     335423  41.264  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 25180000 on 994 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.631 
## F-statistic:  1703 on 1 and 994 DF,  p-value: < 2.2e-16
ggplot(h_y_m_comuna_corr_01, aes(x = sqrt(Freq.x) , y = (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


\[ \hat Y = -6129734 + 13841041 \cdot \sqrt {X} \]

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$est_ing <- 
 -6129734 + 13841041 * sqrt (h_y_m_comuna_corr_01$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
10101032002 10101 20 2017 Puerto Montt 176237.4 2017 245902 43337141298 129 0.0005246 10101 22734631 55769283
10101032011 10101 50 2017 Puerto Montt 176237.4 2017 245902 43337141298 426 0.0017324 10101 75077153 91741205
10101032019 10101 33 2017 Puerto Montt 176237.4 2017 245902 43337141298 829 0.0033713 10101 146100846 73380993
10101042010 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 6 0.0000244 10101 1057425 7711307
10101062003 10101 19 2017 Puerto Montt 176237.4 2017 245902 43337141298 158 0.0006425 10101 27845517 54201965
10101062008 10101 144 2017 Puerto Montt 176237.4 2017 245902 43337141298 581 0.0023627 10101 102393958 159962758
10101062013 10101 135 2017 Puerto Montt 176237.4 2017 245902 43337141298 571 0.0023221 10101 100631584 154688630
10101062029 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 47 0.0001911 10101 8283160 17843652
10101062039 10101 4 2017 Puerto Montt 176237.4 2017 245902 43337141298 67 0.0002725 10101 11807909 21552348
10101072014 10101 74 2017 Puerto Montt 176237.4 2017 245902 43337141298 997 0.0040545 10101 175708737 112935403
10101072021 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 44 0.0001789 10101 7754448 24819775
10101072028 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 145 0.0005897 10101 25554430 30490218
10101072029 10101 81 2017 Puerto Montt 176237.4 2017 245902 43337141298 1051 0.0042741 10101 185225559 118439635
10101072036 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 118 0.0004799 10101 20796019 24819775
10101072045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 113 0.0004595 10101 19914832 41817038
10101072050 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101 11631672 17843652
10101082016 10101 10 2017 Puerto Montt 176237.4 2017 245902 43337141298 121 0.0004921 10101 21324731 37639481
10101082017 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 38 0.0001545 10101 6697023 7711307
10101082018 10101 34 2017 Puerto Montt 176237.4 2017 245902 43337141298 623 0.0025335 10101 109795931 74576710
10101082030 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 176 0.0007157 10101 31017791 43774849
10101082034 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101 11631672 13444454
10101082042 10101 51 2017 Puerto Montt 176237.4 2017 245902 43337141298 253 0.0010289 10101 44588075 92715070
10101082045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 123 0.0005002 10101 21677206 41817038
10101092004 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 97 0.0003945 10101 17095033 39775806
10101092008 10101 195 2017 Puerto Montt 176237.4 2017 245902 43337141298 752 0.0030581 10101 132530562 187149885
10101092037 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 276 0.0011224 10101 48641536 52592830
10101092040 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 509 0.0020699 10101 89704862 114533664
10101092041 10101 265 2017 Puerto Montt 176237.4 2017 245902 43337141298 1683 0.0068442 10101 296607627 219186089
10101092044 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 530 0.0021553 10101 93405848 90757553
10101102005 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 147 0.0005978 10101 25906905 13444454
10101102007 10101 22 2017 Puerto Montt 176237.4 2017 245902 43337141298 824 0.0033509 10101 145219658 58790503
10101102026 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 245 0.0009963 10101 43178175 17843652
10101102035 10101 69 2017 Puerto Montt 176237.4 2017 245902 43337141298 940 0.0038227 10101 165663202 108842587
10101102037 10101 15 2017 Puerto Montt 176237.4 2017 245902 43337141298 164 0.0006669 10101 28902942 47476387
10101102901 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 16 0.0000651 10101 2819799 17843652
10101112025 10101 32 2017 Puerto Montt 176237.4 2017 245902 43337141298 1078 0.0043839 10101 189983971 72167018
10101122024 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 952 0.0038715 10101 167778052 49234430
10101132022 10101 29 2017 Puerto Montt 176237.4 2017 245902 43337141298 703 0.0028589 10101 123894927 68406553
10101132023 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 603 0.0024522 10101 106271182 43774849
10101132027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 105 0.0004270 10101 18504932 39775806
10101132049 10101 152 2017 Puerto Montt 176237.4 2017 245902 43337141298 1883 0.0076575 10101 331855117 164514080
10101142009 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 59 0.0002399 10101 10398010 7711307
10101142015 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 124 0.0005043 10101 21853444 27773754
10101142027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 192 0.0007808 10101 33837590 39775806
10101142038 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 53 0.0002155 10101 9340585 7711307
10101142046 10101 9 2017 Puerto Montt 176237.4 2017 245902 43337141298 317 0.0012891 10101 55867271 35393389
10101142047 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 263 0.0010695 10101 46350449 27773754
10101142049 10101 136 2017 Puerto Montt 176237.4 2017 245902 43337141298 973 0.0039569 10101 171479038 155283154
10101152002 10101 58 2017 Puerto Montt 176237.4 2017 245902 43337141298 554 0.0022529 10101 97635547 99280494
10101152006 10101 14 2017 Puerto Montt 176237.4 2017 245902 43337141298 214 0.0008703 10101 37714814 45658699
10101152020 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 617 0.0025091 10101 108738506 114533664
10101152031 10101 90 2017 Puerto Montt 176237.4 2017 245902 43337141298 642 0.0026108 10101 113144443 125177910
10101152033 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 700 0.0028467 10101 123366215 90757553
10101152049 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 96 0.0003904 10101 16918795 30490218
10101152901 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 46 0.0001871 10101 8106923 13444454
10101162006 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 233 0.0009475 10101 41063326 52592830
10101162010 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 351 0.0014274 10101 61859345 49234430
10101162020 10101 31 2017 Puerto Montt 176237.4 2017 245902 43337141298 205 0.0008337 10101 36128677 70933921
10101162031 10101 123 2017 Puerto Montt 176237.4 2017 245902 43337141298 762 0.0030988 10101 134292936 147374836
10101162032 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 24 0.0000976 10101 4229699 13444454
10101162033 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 168 0.0006832 10101 29607892 52592830
10101172029 10101 198 2017 Puerto Montt 176237.4 2017 245902 43337141298 854 0.0034729 10101 150506782 188630977
10102012001 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 80 0.0023540 10102 12435515 17843652
10102012004 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 283 0.0083272 10102 43990633 13444454
10102012008 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 697 0.0205090 10102 108344420 54201965
10102012017 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 268 0.0078858 10102 41658974 17843652
10102012033 10102 64 2017 Calbuco 155443.9 2017 33985 5282762017 1490 0.0438429 10102 231611458 104598594
10102022001 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 164 0.0048257 10102 25492805 21552348
10102022002 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102 47876731 17843652
10102022003 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 184 0.0054142 10102 28601683 33018642
10102022004 10102 6 2017 Calbuco 155443.9 2017 33985 5282762017 74 0.0021774 10102 11502851 27773754
10102022010 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 294 0.0086509 10102 45700516 49234430
10102022013 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 450 0.0132411 10102 69949769 17843652
10102032002 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 54 0.0015889 10102 8393972 7711307
10102032011 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 163 0.0047962 10102 25337361 13444454
10102032016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 95 0.0027954 10102 14767174 17843652
10102032018 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 470 0.0138296 10102 73058648 33018642
10102032034 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 695 0.0204502 10102 108033533 49234430
10102032901 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 89 0.0026188 10102 13834510 30490218
10102042014 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 87 0.0025600 10102 13523622 17843652
10102042016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 48 0.0014124 10102 7461309 17843652
10102042019 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 336 0.0098867 10102 52229161 41817038
10102042028 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 171 0.0050316 10102 26580912 49234430
10102042029 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 183 0.0053847 10102 28446239 24819775
10102042035 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 271 0.0079741 10102 42125305 17843652
10102042043 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 86 0.0025305 10102 13368178 13444454
10102042901 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 127 0.0037369 10102 19741379 24819775
10102052012 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 302 0.0088863 10102 46944067 21552348
10102052019 10102 14 2017 Calbuco 155443.9 2017 33985 5282762017 332 0.0097690 10102 51607385 45658699
10102052042 10102 18 2017 Calbuco 155443.9 2017 33985 5282762017 410 0.0120641 10102 63732012 52592830
10102052043 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 273 0.0080330 10102 42436193 33018642
10102062015 10102 41 2017 Calbuco 155443.9 2017 33985 5282762017 1129 0.0332205 10102 175496199 82496171
10102062019 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 362 0.0106518 10102 56270703 30490218
10102062027 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 25 0.0007356 10102 3886098 7711307
10102062038 10102 15 2017 Calbuco 155443.9 2017 33985 5282762017 357 0.0105046 10102 55493484 47476387
10102062039 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 643 0.0189201 10102 99950448 41817038
10102072022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 148 0.0043549 10102 23005702 21552348
10102082022 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 565 0.0166250 10102 87825821 54201965
10102092022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102 47876731 21552348
10102102023 10102 9 2017 Calbuco 155443.9 2017 33985 5282762017 630 0.0185376 10102 97929677 35393389


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
10101032002 10101 20 2017 Puerto Montt 176237.4 2017 245902 43337141298 129 0.0005246 10101 22734631 55769283 432320.02
10101032011 10101 50 2017 Puerto Montt 176237.4 2017 245902 43337141298 426 0.0017324 10101 75077153 91741205 215354.94
10101032019 10101 33 2017 Puerto Montt 176237.4 2017 245902 43337141298 829 0.0033713 10101 146100846 73380993 88517.48
10101042010 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 6 0.0000244 10101 1057425 7711307 1285217.83
10101062003 10101 19 2017 Puerto Montt 176237.4 2017 245902 43337141298 158 0.0006425 10101 27845517 54201965 343050.41
10101062008 10101 144 2017 Puerto Montt 176237.4 2017 245902 43337141298 581 0.0023627 10101 102393958 159962758 275323.16
10101062013 10101 135 2017 Puerto Montt 176237.4 2017 245902 43337141298 571 0.0023221 10101 100631584 154688630 270908.28
10101062029 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 47 0.0001911 10101 8283160 17843652 379652.18
10101062039 10101 4 2017 Puerto Montt 176237.4 2017 245902 43337141298 67 0.0002725 10101 11807909 21552348 321676.84
10101072014 10101 74 2017 Puerto Montt 176237.4 2017 245902 43337141298 997 0.0040545 10101 175708737 112935403 113275.23
10101072021 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 44 0.0001789 10101 7754448 24819775 564085.79
10101072028 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 145 0.0005897 10101 25554430 30490218 210277.37
10101072029 10101 81 2017 Puerto Montt 176237.4 2017 245902 43337141298 1051 0.0042741 10101 185225559 118439635 112692.33
10101072036 10101 5 2017 Puerto Montt 176237.4 2017 245902 43337141298 118 0.0004799 10101 20796019 24819775 210337.07
10101072045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 113 0.0004595 10101 19914832 41817038 370062.29
10101072050 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101 11631672 17843652 270358.37
10101082016 10101 10 2017 Puerto Montt 176237.4 2017 245902 43337141298 121 0.0004921 10101 21324731 37639481 311070.09
10101082017 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 38 0.0001545 10101 6697023 7711307 202929.13
10101082018 10101 34 2017 Puerto Montt 176237.4 2017 245902 43337141298 623 0.0025335 10101 109795931 74576710 119705.79
10101082030 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 176 0.0007157 10101 31017791 43774849 248720.73
10101082034 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 66 0.0002684 10101 11631672 13444454 203703.85
10101082042 10101 51 2017 Puerto Montt 176237.4 2017 245902 43337141298 253 0.0010289 10101 44588075 92715070 366462.73
10101082045 10101 12 2017 Puerto Montt 176237.4 2017 245902 43337141298 123 0.0005002 10101 21677206 41817038 339975.92
10101092004 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 97 0.0003945 10101 17095033 39775806 410059.85
10101092008 10101 195 2017 Puerto Montt 176237.4 2017 245902 43337141298 752 0.0030581 10101 132530562 187149885 248869.53
10101092037 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 276 0.0011224 10101 48641536 52592830 190553.73
10101092040 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 509 0.0020699 10101 89704862 114533664 225017.02
10101092041 10101 265 2017 Puerto Montt 176237.4 2017 245902 43337141298 1683 0.0068442 10101 296607627 219186089 130235.35
10101092044 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 530 0.0021553 10101 93405848 90757553 171240.67
10101102005 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 147 0.0005978 10101 25906905 13444454 91458.87
10101102007 10101 22 2017 Puerto Montt 176237.4 2017 245902 43337141298 824 0.0033509 10101 145219658 58790503 71347.70
10101102026 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 245 0.0009963 10101 43178175 17843652 72831.23
10101102035 10101 69 2017 Puerto Montt 176237.4 2017 245902 43337141298 940 0.0038227 10101 165663202 108842587 115789.99
10101102037 10101 15 2017 Puerto Montt 176237.4 2017 245902 43337141298 164 0.0006669 10101 28902942 47476387 289490.17
10101102901 10101 3 2017 Puerto Montt 176237.4 2017 245902 43337141298 16 0.0000651 10101 2819799 17843652 1115228.27
10101112025 10101 32 2017 Puerto Montt 176237.4 2017 245902 43337141298 1078 0.0043839 10101 189983971 72167018 66945.29
10101122024 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 952 0.0038715 10101 167778052 49234430 51716.84
10101132022 10101 29 2017 Puerto Montt 176237.4 2017 245902 43337141298 703 0.0028589 10101 123894927 68406553 97306.62
10101132023 10101 13 2017 Puerto Montt 176237.4 2017 245902 43337141298 603 0.0024522 10101 106271182 43774849 72595.11
10101132027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 105 0.0004270 10101 18504932 39775806 378817.20
10101132049 10101 152 2017 Puerto Montt 176237.4 2017 245902 43337141298 1883 0.0076575 10101 331855117 164514080 87368.07
10101142009 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 59 0.0002399 10101 10398010 7711307 130700.12
10101142015 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 124 0.0005043 10101 21853444 27773754 223981.89
10101142027 10101 11 2017 Puerto Montt 176237.4 2017 245902 43337141298 192 0.0007808 10101 33837590 39775806 207165.65
10101142038 10101 1 2017 Puerto Montt 176237.4 2017 245902 43337141298 53 0.0002155 10101 9340585 7711307 145496.36
10101142046 10101 9 2017 Puerto Montt 176237.4 2017 245902 43337141298 317 0.0012891 10101 55867271 35393389 111651.07
10101142047 10101 6 2017 Puerto Montt 176237.4 2017 245902 43337141298 263 0.0010695 10101 46350449 27773754 105603.63
10101142049 10101 136 2017 Puerto Montt 176237.4 2017 245902 43337141298 973 0.0039569 10101 171479038 155283154 159592.14
10101152002 10101 58 2017 Puerto Montt 176237.4 2017 245902 43337141298 554 0.0022529 10101 97635547 99280494 179206.67
10101152006 10101 14 2017 Puerto Montt 176237.4 2017 245902 43337141298 214 0.0008703 10101 37714814 45658699 213358.41
10101152020 10101 76 2017 Puerto Montt 176237.4 2017 245902 43337141298 617 0.0025091 10101 108738506 114533664 185629.93
10101152031 10101 90 2017 Puerto Montt 176237.4 2017 245902 43337141298 642 0.0026108 10101 113144443 125177910 194981.17
10101152033 10101 49 2017 Puerto Montt 176237.4 2017 245902 43337141298 700 0.0028467 10101 123366215 90757553 129653.65
10101152049 10101 7 2017 Puerto Montt 176237.4 2017 245902 43337141298 96 0.0003904 10101 16918795 30490218 317606.44
10101152901 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 46 0.0001871 10101 8106923 13444454 292270.74
10101162006 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 233 0.0009475 10101 41063326 52592830 225720.30
10101162010 10101 16 2017 Puerto Montt 176237.4 2017 245902 43337141298 351 0.0014274 10101 61859345 49234430 140269.03
10101162020 10101 31 2017 Puerto Montt 176237.4 2017 245902 43337141298 205 0.0008337 10101 36128677 70933921 346019.13
10101162031 10101 123 2017 Puerto Montt 176237.4 2017 245902 43337141298 762 0.0030988 10101 134292936 147374836 193405.30
10101162032 10101 2 2017 Puerto Montt 176237.4 2017 245902 43337141298 24 0.0000976 10101 4229699 13444454 560185.58
10101162033 10101 18 2017 Puerto Montt 176237.4 2017 245902 43337141298 168 0.0006832 10101 29607892 52592830 313052.56
10101172029 10101 198 2017 Puerto Montt 176237.4 2017 245902 43337141298 854 0.0034729 10101 150506782 188630977 220879.36
10102012001 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 80 0.0023540 10102 12435515 17843652 223045.65
10102012004 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 283 0.0083272 10102 43990633 13444454 47506.90
10102012008 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 697 0.0205090 10102 108344420 54201965 77764.66
10102012017 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 268 0.0078858 10102 41658974 17843652 66580.79
10102012033 10102 64 2017 Calbuco 155443.9 2017 33985 5282762017 1490 0.0438429 10102 231611458 104598594 70200.40
10102022001 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 164 0.0048257 10102 25492805 21552348 131416.76
10102022002 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102 47876731 17843652 57933.94
10102022003 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 184 0.0054142 10102 28601683 33018642 179449.14
10102022004 10102 6 2017 Calbuco 155443.9 2017 33985 5282762017 74 0.0021774 10102 11502851 27773754 375321.00
10102022010 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 294 0.0086509 10102 45700516 49234430 167464.05
10102022013 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 450 0.0132411 10102 69949769 17843652 39652.56
10102032002 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 54 0.0015889 10102 8393972 7711307 142801.98
10102032011 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 163 0.0047962 10102 25337361 13444454 82481.31
10102032016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 95 0.0027954 10102 14767174 17843652 187827.92
10102032018 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 470 0.0138296 10102 73058648 33018642 70252.43
10102032034 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 695 0.0204502 10102 108033533 49234430 70840.91
10102032901 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 89 0.0026188 10102 13834510 30490218 342586.72
10102042014 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 87 0.0025600 10102 13523622 17843652 205099.45
10102042016 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 48 0.0014124 10102 7461309 17843652 371742.76
10102042019 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 336 0.0098867 10102 52229161 41817038 124455.47
10102042028 10102 16 2017 Calbuco 155443.9 2017 33985 5282762017 171 0.0050316 10102 26580912 49234430 287920.64
10102042029 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 183 0.0053847 10102 28446239 24819775 135627.18
10102042035 10102 3 2017 Calbuco 155443.9 2017 33985 5282762017 271 0.0079741 10102 42125305 17843652 65843.74
10102042043 10102 2 2017 Calbuco 155443.9 2017 33985 5282762017 86 0.0025305 10102 13368178 13444454 156330.86
10102042901 10102 5 2017 Calbuco 155443.9 2017 33985 5282762017 127 0.0037369 10102 19741379 24819775 195431.30
10102052012 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 302 0.0088863 10102 46944067 21552348 71365.39
10102052019 10102 14 2017 Calbuco 155443.9 2017 33985 5282762017 332 0.0097690 10102 51607385 45658699 137526.20
10102052042 10102 18 2017 Calbuco 155443.9 2017 33985 5282762017 410 0.0120641 10102 63732012 52592830 128275.19
10102052043 10102 8 2017 Calbuco 155443.9 2017 33985 5282762017 273 0.0080330 10102 42436193 33018642 120947.41
10102062015 10102 41 2017 Calbuco 155443.9 2017 33985 5282762017 1129 0.0332205 10102 175496199 82496171 73070.12
10102062019 10102 7 2017 Calbuco 155443.9 2017 33985 5282762017 362 0.0106518 10102 56270703 30490218 84227.12
10102062027 10102 1 2017 Calbuco 155443.9 2017 33985 5282762017 25 0.0007356 10102 3886098 7711307 308452.28
10102062038 10102 15 2017 Calbuco 155443.9 2017 33985 5282762017 357 0.0105046 10102 55493484 47476387 132987.08
10102062039 10102 12 2017 Calbuco 155443.9 2017 33985 5282762017 643 0.0189201 10102 99950448 41817038 65034.27
10102072022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 148 0.0043549 10102 23005702 21552348 145623.97
10102082022 10102 19 2017 Calbuco 155443.9 2017 33985 5282762017 565 0.0166250 10102 87825821 54201965 95932.68
10102092022 10102 4 2017 Calbuco 155443.9 2017 33985 5282762017 308 0.0090628 10102 47876731 21552348 69975.16
10102102023 10102 9 2017 Calbuco 155443.9 2017 33985 5282762017 630 0.0185376 10102 97929677 35393389 56179.98


Guardamos:

saveRDS(h_y_m_comuna_corr_01, "P15/region_10_P15_r.rds")