Correlaciones entre variables del Censo de Viviendas, Hogares y Personas e ingresos promedios comunales de la CASEN 2017.
VE-CC-AJ
DataIntelligenceLunes 05-07-2021
Abstract
Calculamos correlaciones entre el ingreso promedio comunal multiplicado por la población comunal que llamaremos ipcmp extraído de la Casen 2017 y las frecuencias de categorías de respuesta para todas las variables del Censo de viviendas, hogares y personas al 2017, también extraídas a nivel comunal.
Importante es aplicar la libreria dplyr para evitar que en los filtros se desplieguen series de tiempo.
Area: urbano = 1 rural = 2
URBANO
1 Pregunta P07: Relación de parentesco
1 Jefe/a de hogar
2 Esposo/a o cónyuge
3 Conviviente por unión civil
4 Conviviente de hecho o pareja
5 Hijo/a
6 Hijo/a del cónyuge, conviviente o pareja
7 Hermano/a
8 Padre/madre
9 Cuñado/a
10 Suegro/a
11 Yerno/nuera
12 Nieto/a
13 Abuelo/a30
14 Otro pariente
15 No pariente
16 Servicio doméstico puertas adentro
17 Persona en vivienda colectiva
18 Persona en tránsito
19 Persona en operativo calle
98 No aplica
99 Missing
1.1 Cálculo de frecuencias
Leemos las respuestas a la pregunta P07 del censo de viviendas 2017 y obtenemos la tabla de frecuencias por categoría de respuesta:
tabla_con_clave <- readRDS("../censo_personas_con_clave_17")
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$AREA == 1)
b <- tabla_con_clave$COMUNA
c <- tabla_con_clave$P07
cross_tab = xtabs( ~ unlist(b) + unlist(c))
tabla <- as.data.frame(cross_tab)
d <-tabla[!(tabla$Freq == 0),]
d$anio <- "2017"
d_t <- filter(d,d$unlist.c. == 1)
for(i in 2:19){
d_i <- filter(d,d$unlist.c. == i)
d_t = merge( x = d_t, y = d_i, by = "unlist.b.", all.x = TRUE)
}
codigos <- d_t$
unlist.b.
rango <- seq(1:nrow(d_t))
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_t,cadena)
comuna_corr <- comuna_corr[,-c(1),drop=FALSE]
names(comuna_corr)[58] <- "código"
ingresos_expandidos_2017 <- readRDS("ingresos_expandidos_17_urbano_nacional.rds")
df_2017_2 = merge( x = comuna_corr, y = ingresos_expandidos_2017, by = "código", all.x = TRUE)
tablamadre <- head(df_2017_2,50)
kbl(tablamadre) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
kable_paper() %>%
scroll_box(width = "100%", height = "300px")| código | unlist.c..x | Freq.x | anio.x | unlist.c..y | Freq.y | anio.y | unlist.c..x.1 | Freq.x.1 | anio.x.1 | unlist.c..y.1 | Freq.y.1 | anio.y.1 | unlist.c..x.2 | Freq.x.2 | anio.x.2 | unlist.c..y.2 | Freq.y.2 | anio.y.2 | unlist.c..x.3 | Freq.x.3 | anio.x.3 | unlist.c..y.3 | Freq.y.3 | anio.y.3 | unlist.c..x.4 | Freq.x.4 | anio.x.4 | unlist.c..y.4 | Freq.y.4 | anio.y.4 | unlist.c..x.5 | Freq.x.5 | anio.x.5 | unlist.c..y.5 | Freq.y.5 | anio.y.5 | unlist.c..x.6 | Freq.x.6 | anio.x.6 | unlist.c..y.6 | Freq.y.6 | anio.y.6 | unlist.c..x.7 | Freq.x.7 | anio.x.7 | unlist.c..y.7 | Freq.y.7 | anio.y.7 | unlist.c..x.8 | Freq.x.8 | anio.x.8 | unlist.c..y.8 | Freq.y.8 | anio.y.8 | unlist.c. | Freq | anio | comuna.x | promedio_i | año | comuna.y | personas | Ingresos_expandidos | tipo |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01101 | 1 | 59435 | 2017 | 2 | 23062 | 2017 | 3 | 560 | 2017 | 4 | 7805 | 2017 | 5 | 55928 | 2017 | 6 | 2593 | 2017 | 7 | 2819 | 2017 | 8 | 2557 | 2017 | 9 | 1288 | 2017 | 10 | 1252 | 2017 | 11 | 3105 | 2017 | 12 | 11801 | 2017 | 13 | 157 | 2017 | 14 | 7394 | 2017 | 15 | 4738 | 2017 | 16 | 299 | 2017 | 17 | 3790 | 2017 | 18 | 142 | 2017 | 19 | 340 | 2017 | Iquique | 356487.6 | 2017 | 1101 | 191468 | 68255976664 | Urbano |
| 01107 | 1 | 29652 | 2017 | 2 | 11053 | 2017 | 3 | 490 | 2017 | 4 | 5182 | 2017 | 5 | 38458 | 2017 | 6 | 1996 | 2017 | 7 | 1453 | 2017 | 8 | 1251 | 2017 | 9 | 805 | 2017 | 10 | 580 | 2017 | 11 | 1975 | 2017 | 12 | 6177 | 2017 | 13 | 75 | 2017 | 14 | 4615 | 2017 | 15 | 1889 | 2017 | 16 | 49 | 2017 | 17 | 183 | 2017 | NA | NA | NA | 19 | 1 | 2017 | Alto Hospicio | 301933.4 | 2017 | 1107 | 108375 | 32722034397 | Urbano |
| 01401 | 1 | 2829 | 2017 | 2 | 974 | 2017 | 3 | 38 | 2017 | 4 | 451 | 2017 | 5 | 3400 | 2017 | 6 | 104 | 2017 | 7 | 122 | 2017 | 8 | 96 | 2017 | 9 | 52 | 2017 | 10 | 39 | 2017 | 11 | 104 | 2017 | 12 | 438 | 2017 | 13 | 10 | 2017 | 14 | 330 | 2017 | 15 | 170 | 2017 | 16 | 9 | 2017 | 17 | 916 | 2017 | 18 | 13 | 2017 | NA | NA | NA | Pozo Almonte | 299998.6 | 2017 | 1401 | 15711 | 4713278189 | Urbano |
| 01404 | 1 | 358 | 2017 | 2 | 116 | 2017 | 3 | 8 | 2017 | 4 | 46 | 2017 | 5 | 352 | 2017 | 6 | 11 | 2017 | 7 | 14 | 2017 | 8 | 12 | 2017 | 9 | 8 | 2017 | 10 | 5 | 2017 | 11 | 14 | 2017 | 12 | 50 | 2017 | NA | NA | NA | 14 | 43 | 2017 | 15 | 25 | 2017 | 16 | 3 | 2017 | 17 | 44 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 01405 | 1 | 1313 | 2017 | 2 | 470 | 2017 | 3 | 19 | 2017 | 4 | 163 | 2017 | 5 | 1193 | 2017 | 6 | 29 | 2017 | 7 | 55 | 2017 | 8 | 45 | 2017 | 9 | 34 | 2017 | 10 | 13 | 2017 | 11 | 48 | 2017 | 12 | 211 | 2017 | 13 | 3 | 2017 | 14 | 160 | 2017 | 15 | 89 | 2017 | 16 | 8 | 2017 | 17 | 59 | 2017 | NA | NA | NA | NA | NA | NA | Pica | 330061.1 | 2017 | 1405 | 9296 | 3068247619 | Urbano |
| 02101 | 1 | 105521 | 2017 | 2 | 42264 | 2017 | 3 | 1112 | 2017 | 4 | 13826 | 2017 | 5 | 110439 | 2017 | 6 | 5037 | 2017 | 7 | 5942 | 2017 | 8 | 4862 | 2017 | 9 | 2605 | 2017 | 10 | 2269 | 2017 | 11 | 5984 | 2017 | 12 | 22306 | 2017 | 13 | 301 | 2017 | 14 | 16588 | 2017 | 15 | 9654 | 2017 | 16 | 379 | 2017 | 17 | 4350 | 2017 | 18 | 329 | 2017 | 19 | 336 | 2017 | Antofagasta | 347580.2 | 2017 | 2101 | 361873 | 125779893517 | Urbano |
| 02102 | 1 | 3292 | 2017 | 2 | 1132 | 2017 | 3 | 22 | 2017 | 4 | 564 | 2017 | 5 | 3238 | 2017 | 6 | 215 | 2017 | 7 | 193 | 2017 | 8 | 97 | 2017 | 9 | 99 | 2017 | 10 | 62 | 2017 | 11 | 201 | 2017 | 12 | 693 | 2017 | 13 | 3 | 2017 | 14 | 482 | 2017 | 15 | 496 | 2017 | 16 | 4 | 2017 | 17 | 2080 | 2017 | 18 | 81 | 2017 | NA | NA | NA | Mejillones | 369770.7 | 2017 | 2102 | 13467 | 4979702302 | Urbano |
| 02104 | 1 | 3317 | 2017 | 2 | 1230 | 2017 | 3 | 38 | 2017 | 4 | 413 | 2017 | 5 | 3339 | 2017 | 6 | 138 | 2017 | 7 | 165 | 2017 | 8 | 124 | 2017 | 9 | 60 | 2017 | 10 | 46 | 2017 | 11 | 196 | 2017 | 12 | 892 | 2017 | 13 | 2 | 2017 | 14 | 554 | 2017 | 15 | 281 | 2017 | 16 | 8 | 2017 | 17 | 294 | 2017 | 18 | 15 | 2017 | 19 | 11 | 2017 | Taltal | 376328.9 | 2017 | 2104 | 13317 | 5011572025 | Urbano |
| 02201 | 1 | 47501 | 2017 | 2 | 18926 | 2017 | 3 | 593 | 2017 | 4 | 5590 | 2017 | 5 | 49133 | 2017 | 6 | 2052 | 2017 | 7 | 2310 | 2017 | 8 | 1717 | 2017 | 9 | 1010 | 2017 | 10 | 750 | 2017 | 11 | 2318 | 2017 | 12 | 9611 | 2017 | 13 | 124 | 2017 | 14 | 6910 | 2017 | 15 | 3260 | 2017 | 16 | 257 | 2017 | 17 | 5975 | 2017 | 18 | 310 | 2017 | 19 | 140 | 2017 | Calama | 416281.1 | 2017 | 2201 | 165731 | 68990679686 | Urbano |
| 02203 | 1 | 1624 | 2017 | 2 | 374 | 2017 | 3 | 12 | 2017 | 4 | 249 | 2017 | 5 | 1227 | 2017 | 6 | 61 | 2017 | 7 | 71 | 2017 | 8 | 41 | 2017 | 9 | 25 | 2017 | 10 | 9 | 2017 | 11 | 41 | 2017 | 12 | 172 | 2017 | NA | NA | NA | 14 | 202 | 2017 | 15 | 182 | 2017 | 16 | 3 | 2017 | 17 | 1111 | 2017 | 18 | 119 | 2017 | 19 | 1 | 2017 | San Pedro de Atacama | 437934.7 | 2017 | 2203 | 10996 | 4815529626 | Urbano |
| 02301 | 1 | 7780 | 2017 | 2 | 2718 | 2017 | 3 | 136 | 2017 | 4 | 1038 | 2017 | 5 | 7453 | 2017 | 6 | 346 | 2017 | 7 | 291 | 2017 | 8 | 255 | 2017 | 9 | 134 | 2017 | 10 | 119 | 2017 | 11 | 387 | 2017 | 12 | 1787 | 2017 | 13 | 21 | 2017 | 14 | 1008 | 2017 | 15 | 446 | 2017 | 16 | 7 | 2017 | 17 | 633 | 2017 | 18 | 41 | 2017 | 19 | 31 | 2017 | Tocopilla | 271720.8 | 2017 | 2301 | 25186 | 6843559467 | Urbano |
| 02302 | 1 | 1395 | 2017 | 2 | 563 | 2017 | 3 | 4 | 2017 | 4 | 160 | 2017 | 5 | 1302 | 2017 | 6 | 72 | 2017 | 7 | 49 | 2017 | 8 | 45 | 2017 | 9 | 22 | 2017 | 10 | 25 | 2017 | 11 | 40 | 2017 | 12 | 213 | 2017 | 13 | 4 | 2017 | 14 | 126 | 2017 | 15 | 70 | 2017 | NA | NA | NA | 17 | 835 | 2017 | NA | NA | NA | NA | NA | NA | María Elena | 466266.9 | 2017 | 2302 | 6457 | 3010685220 | Urbano |
| 03101 | 1 | 45919 | 2017 | 2 | 18422 | 2017 | 3 | 391 | 2017 | 4 | 7546 | 2017 | 5 | 50823 | 2017 | 6 | 1937 | 2017 | 7 | 1869 | 2017 | 8 | 1684 | 2017 | 9 | 603 | 2017 | 10 | 759 | 2017 | 11 | 2273 | 2017 | 12 | 9743 | 2017 | 13 | 90 | 2017 | 14 | 4633 | 2017 | 15 | 2199 | 2017 | 16 | 39 | 2017 | 17 | 1917 | 2017 | NA | NA | NA | 19 | 115 | 2017 | Copiapó | 330574.6 | 2017 | 3101 | 153937 | 50887663717 | Urbano |
| 03102 | 1 | 5007 | 2017 | 2 | 1635 | 2017 | 3 | 59 | 2017 | 4 | 840 | 2017 | 5 | 4956 | 2017 | 6 | 236 | 2017 | 7 | 176 | 2017 | 8 | 174 | 2017 | 9 | 77 | 2017 | 10 | 85 | 2017 | 11 | 234 | 2017 | 12 | 1096 | 2017 | 13 | 16 | 2017 | 14 | 581 | 2017 | 15 | 336 | 2017 | 16 | 2 | 2017 | 17 | 219 | 2017 | NA | NA | NA | 19 | 46 | 2017 | Caldera | 299314.8 | 2017 | 3102 | 17662 | 5286498241 | Urbano |
| 03103 | 1 | 2955 | 2017 | 2 | 1142 | 2017 | 3 | 22 | 2017 | 4 | 559 | 2017 | 5 | 3521 | 2017 | 6 | 125 | 2017 | 7 | 116 | 2017 | 8 | 113 | 2017 | 9 | 33 | 2017 | 10 | 33 | 2017 | 11 | 150 | 2017 | 12 | 713 | 2017 | 13 | 3 | 2017 | 14 | 271 | 2017 | 15 | 100 | 2017 | 16 | 1 | 2017 | 17 | 74 | 2017 | NA | NA | NA | 19 | 4 | 2017 | Tierra Amarilla | 315860.6 | 2017 | 3103 | 14019 | 4428049932 | Urbano |
| 03201 | 1 | 3337 | 2017 | 2 | 1215 | 2017 | 3 | 48 | 2017 | 4 | 543 | 2017 | 5 | 3517 | 2017 | 6 | 95 | 2017 | 7 | 168 | 2017 | 8 | 123 | 2017 | 9 | 31 | 2017 | 10 | 46 | 2017 | 11 | 170 | 2017 | 12 | 915 | 2017 | 13 | 13 | 2017 | 14 | 343 | 2017 | 15 | 117 | 2017 | 16 | 1 | 2017 | 17 | 401 | 2017 | NA | NA | NA | NA | NA | NA | Chañaral | 286389.3 | 2017 | 3201 | 12219 | 3499391196 | Urbano |
| 03202 | 1 | 4345 | 2017 | 2 | 1700 | 2017 | 3 | 71 | 2017 | 4 | 584 | 2017 | 5 | 4089 | 2017 | 6 | 150 | 2017 | 7 | 159 | 2017 | 8 | 187 | 2017 | 9 | 41 | 2017 | 10 | 44 | 2017 | 11 | 88 | 2017 | 12 | 469 | 2017 | 13 | 8 | 2017 | 14 | 352 | 2017 | 15 | 144 | 2017 | 16 | 2 | 2017 | 17 | 822 | 2017 | NA | NA | NA | NA | NA | NA | Diego de Almagro | 325861.5 | 2017 | 3202 | 13925 | 4537621312 | Urbano |
| 03301 | 1 | 14292 | 2017 | 2 | 5082 | 2017 | 3 | 186 | 2017 | 4 | 1699 | 2017 | 5 | 14421 | 2017 | 6 | 442 | 2017 | 7 | 742 | 2017 | 8 | 589 | 2017 | 9 | 214 | 2017 | 10 | 208 | 2017 | 11 | 815 | 2017 | 12 | 3910 | 2017 | 13 | 41 | 2017 | 14 | 1690 | 2017 | 15 | 841 | 2017 | 16 | 11 | 2017 | 17 | 809 | 2017 | 18 | 16 | 2017 | 19 | 11 | 2017 | Vallenar | 311577.0 | 2017 | 3301 | 51917 | 16176145007 | Urbano |
| 03303 | 1 | 1432 | 2017 | 2 | 429 | 2017 | 3 | 12 | 2017 | 4 | 221 | 2017 | 5 | 1447 | 2017 | 6 | 63 | 2017 | 7 | 71 | 2017 | 8 | 50 | 2017 | 9 | 17 | 2017 | 10 | 12 | 2017 | 11 | 87 | 2017 | 12 | 438 | 2017 | 13 | 2 | 2017 | 14 | 163 | 2017 | 15 | 52 | 2017 | NA | NA | NA | 17 | 93 | 2017 | NA | NA | NA | NA | NA | NA | Freirina | 289049.9 | 2017 | 3303 | 7041 | 2035200054 | Urbano |
| 03304 | 1 | 2893 | 2017 | 2 | 1003 | 2017 | 3 | 38 | 2017 | 4 | 412 | 2017 | 5 | 2669 | 2017 | 6 | 130 | 2017 | 7 | 106 | 2017 | 8 | 83 | 2017 | 9 | 54 | 2017 | 10 | 32 | 2017 | 11 | 130 | 2017 | 12 | 659 | 2017 | 13 | 4 | 2017 | 14 | 278 | 2017 | 15 | 155 | 2017 | 16 | 1 | 2017 | 17 | 220 | 2017 | 18 | 34 | 2017 | 19 | 1 | 2017 | Huasco | 337414.8 | 2017 | 3304 | 10149 | 3424422750 | Urbano |
| 04101 | 1 | 63584 | 2017 | 2 | 23476 | 2017 | 3 | 503 | 2017 | 4 | 8142 | 2017 | 5 | 65033 | 2017 | 6 | 2381 | 2017 | 7 | 3121 | 2017 | 8 | 2660 | 2017 | 9 | 821 | 2017 | 10 | 1036 | 2017 | 11 | 2749 | 2017 | 12 | 12672 | 2017 | 13 | 172 | 2017 | 14 | 6844 | 2017 | 15 | 4873 | 2017 | 16 | 179 | 2017 | 17 | 2279 | 2017 | NA | NA | NA | 19 | 115 | 2017 | La Serena | 272136.8 | 2017 | 4101 | 221054 | 60156924947 | Urbano |
| 04102 | 1 | 65051 | 2017 | 2 | 25203 | 2017 | 3 | 705 | 2017 | 4 | 9238 | 2017 | 5 | 70613 | 2017 | 6 | 3056 | 2017 | 7 | 2920 | 2017 | 8 | 2651 | 2017 | 9 | 953 | 2017 | 10 | 1044 | 2017 | 11 | 3574 | 2017 | 12 | 15595 | 2017 | 13 | 167 | 2017 | 14 | 7469 | 2017 | 15 | 4165 | 2017 | 16 | 115 | 2017 | 17 | 1761 | 2017 | 18 | 130 | 2017 | 19 | 140 | 2017 | Coquimbo | 264340.0 | 2017 | 4102 | 227730 | 60198159091 | Urbano |
| 04103 | 1 | 3133 | 2017 | 2 | 1144 | 2017 | 3 | 46 | 2017 | 4 | 422 | 2017 | 5 | 3409 | 2017 | 6 | 106 | 2017 | 7 | 133 | 2017 | 8 | 79 | 2017 | 9 | 33 | 2017 | 10 | 32 | 2017 | 11 | 151 | 2017 | 12 | 913 | 2017 | 13 | 4 | 2017 | 14 | 243 | 2017 | 15 | 106 | 2017 | NA | NA | NA | 17 | 54 | 2017 | NA | NA | NA | NA | NA | NA | Andacollo | 251267.7 | 2017 | 4103 | 11044 | 2775000288 | Urbano |
| 04104 | 1 | 396 | 2017 | 2 | 134 | 2017 | 3 | 4 | 2017 | 4 | 72 | 2017 | 5 | 458 | 2017 | 6 | 10 | 2017 | 7 | 13 | 2017 | 8 | 4 | 2017 | 9 | 5 | 2017 | 10 | 2 | 2017 | 11 | 21 | 2017 | 12 | 115 | 2017 | NA | NA | NA | 14 | 35 | 2017 | 15 | 18 | 2017 | NA | NA | NA | 17 | 6 | 2017 | NA | NA | NA | NA | NA | NA | La Higuera | 214257.0 | 2017 | 4104 | 4241 | 908664019 | Urbano |
| 04106 | 1 | 5471 | 2017 | 2 | 1835 | 2017 | 3 | 77 | 2017 | 4 | 832 | 2017 | 5 | 5677 | 2017 | 6 | 210 | 2017 | 7 | 219 | 2017 | 8 | 176 | 2017 | 9 | 41 | 2017 | 10 | 38 | 2017 | 11 | 253 | 2017 | 12 | 1217 | 2017 | 13 | 10 | 2017 | 14 | 496 | 2017 | 15 | 292 | 2017 | 16 | 21 | 2017 | 17 | 128 | 2017 | NA | NA | NA | NA | NA | NA | Vicuña | 245957.4 | 2017 | 4106 | 27771 | 6830481918 | Urbano |
| 04201 | 1 | 6862 | 2017 | 2 | 2395 | 2017 | 3 | 64 | 2017 | 4 | 870 | 2017 | 5 | 6628 | 2017 | 6 | 215 | 2017 | 7 | 295 | 2017 | 8 | 204 | 2017 | 9 | 93 | 2017 | 10 | 79 | 2017 | 11 | 297 | 2017 | 12 | 1582 | 2017 | 13 | 8 | 2017 | 14 | 667 | 2017 | 15 | 392 | 2017 | 16 | 6 | 2017 | 17 | 395 | 2017 | NA | NA | NA | NA | NA | NA | Illapel | 270316.5 | 2017 | 4201 | 30848 | 8338722128 | Urbano |
| 04202 | 1 | 711 | 2017 | 2 | 249 | 2017 | 3 | 9 | 2017 | 4 | 82 | 2017 | 5 | 568 | 2017 | 6 | 8 | 2017 | 7 | 29 | 2017 | 8 | 21 | 2017 | 9 | 9 | 2017 | 10 | 4 | 2017 | 11 | 18 | 2017 | 12 | 111 | 2017 | 13 | 1 | 2017 | 14 | 62 | 2017 | 15 | 48 | 2017 | 16 | 3 | 2017 | 17 | 27 | 2017 | NA | NA | NA | NA | NA | NA | Canela | 233397.3 | 2017 | 4202 | 9093 | 2122281844 | Urbano |
| 04203 | 1 | 5835 | 2017 | 2 | 1842 | 2017 | 3 | 66 | 2017 | 4 | 882 | 2017 | 5 | 4943 | 2017 | 6 | 178 | 2017 | 7 | 204 | 2017 | 8 | 168 | 2017 | 9 | 61 | 2017 | 10 | 41 | 2017 | 11 | 212 | 2017 | 12 | 1148 | 2017 | 13 | 6 | 2017 | 14 | 551 | 2017 | 15 | 368 | 2017 | 16 | 10 | 2017 | 17 | 578 | 2017 | NA | NA | NA | 19 | 1 | 2017 | Los Vilos | 282415.6 | 2017 | 4203 | 21382 | 6038609501 | Urbano |
| 04204 | 1 | 5166 | 2017 | 2 | 1929 | 2017 | 3 | 45 | 2017 | 4 | 629 | 2017 | 5 | 5070 | 2017 | 6 | 157 | 2017 | 7 | 214 | 2017 | 8 | 135 | 2017 | 9 | 80 | 2017 | 10 | 56 | 2017 | 11 | 233 | 2017 | 12 | 1093 | 2017 | 13 | 17 | 2017 | 14 | 554 | 2017 | 15 | 313 | 2017 | 16 | 8 | 2017 | 17 | 1098 | 2017 | NA | NA | NA | 19 | 6 | 2017 | Salamanca | 262056.9 | 2017 | 4204 | 29347 | 7690585032 | Urbano |
| 04301 | 1 | 27402 | 2017 | 2 | 9345 | 2017 | 3 | 260 | 2017 | 4 | 3630 | 2017 | 5 | 28610 | 2017 | 6 | 879 | 2017 | 7 | 1305 | 2017 | 8 | 948 | 2017 | 9 | 390 | 2017 | 10 | 331 | 2017 | 11 | 1378 | 2017 | 12 | 6909 | 2017 | 13 | 69 | 2017 | 14 | 3204 | 2017 | 15 | 1408 | 2017 | 16 | 46 | 2017 | 17 | 1185 | 2017 | 18 | 160 | 2017 | 19 | 80 | 2017 | Ovalle | 274771.4 | 2017 | 4301 | 111272 | 30574361012 | Urbano |
| 04302 | 1 | 2132 | 2017 | 2 | 586 | 2017 | 3 | 25 | 2017 | 4 | 289 | 2017 | 5 | 1795 | 2017 | 6 | 44 | 2017 | 7 | 80 | 2017 | 8 | 66 | 2017 | 9 | 27 | 2017 | 10 | 20 | 2017 | 11 | 69 | 2017 | 12 | 443 | 2017 | 13 | 6 | 2017 | 14 | 183 | 2017 | 15 | 89 | 2017 | 16 | 4 | 2017 | 17 | 140 | 2017 | NA | NA | NA | NA | NA | NA | Combarbalá | 228990.4 | 2017 | 4302 | 13322 | 3050610572 | Urbano |
| 04303 | 1 | 4923 | 2017 | 2 | 1690 | 2017 | 3 | 60 | 2017 | 4 | 666 | 2017 | 5 | 5260 | 2017 | 6 | 171 | 2017 | 7 | 161 | 2017 | 8 | 108 | 2017 | 9 | 33 | 2017 | 10 | 33 | 2017 | 11 | 235 | 2017 | 12 | 1226 | 2017 | 13 | 3 | 2017 | 14 | 475 | 2017 | 15 | 246 | 2017 | NA | NA | NA | 17 | 48 | 2017 | NA | NA | NA | NA | NA | NA | Monte Patria | 225369.1 | 2017 | 4303 | 30751 | 6930326684 | Urbano |
| 04304 | 1 | 1937 | 2017 | 2 | 617 | 2017 | 3 | 31 | 2017 | 4 | 294 | 2017 | 5 | 2044 | 2017 | 6 | 72 | 2017 | 7 | 63 | 2017 | 8 | 42 | 2017 | 9 | 19 | 2017 | 10 | 15 | 2017 | 11 | 62 | 2017 | 12 | 389 | 2017 | 13 | 5 | 2017 | 14 | 154 | 2017 | 15 | 64 | 2017 | 16 | 1 | 2017 | 17 | 37 | 2017 | NA | NA | NA | 19 | 2 | 2017 | Punitaqui | 212496.1 | 2017 | 4304 | 10956 | 2328107498 | Urbano |
| 05101 | 1 | 100951 | 2017 | 2 | 35010 | 2017 | 3 | 740 | 2017 | 4 | 13847 | 2017 | 5 | 84935 | 2017 | 6 | 3483 | 2017 | 7 | 4535 | 2017 | 8 | 3806 | 2017 | 9 | 1213 | 2017 | 10 | 1413 | 2017 | 11 | 4054 | 2017 | 12 | 15810 | 2017 | 13 | 215 | 2017 | 14 | 9854 | 2017 | 15 | 8275 | 2017 | 16 | 102 | 2017 | 17 | 6696 | 2017 | 18 | 747 | 2017 | 19 | 232 | 2017 | Valparaíso | 297929.0 | 2017 | 5101 | 296655 | 88382118059 | Urbano |
| 05102 | 1 | 5802 | 2017 | 2 | 2335 | 2017 | 3 | 56 | 2017 | 4 | 817 | 2017 | 5 | 6043 | 2017 | 6 | 244 | 2017 | 7 | 204 | 2017 | 8 | 141 | 2017 | 9 | 70 | 2017 | 10 | 78 | 2017 | 11 | 266 | 2017 | 12 | 1108 | 2017 | 13 | 12 | 2017 | 14 | 475 | 2017 | 15 | 234 | 2017 | 16 | 7 | 2017 | 17 | 105 | 2017 | NA | NA | NA | 19 | 5 | 2017 | Casablanca | 341641.8 | 2017 | 5102 | 26867 | 9178890241 | Urbano |
| 05103 | 1 | 13146 | 2017 | 2 | 5777 | 2017 | 3 | 86 | 2017 | 4 | 1484 | 2017 | 5 | 13129 | 2017 | 6 | 441 | 2017 | 7 | 372 | 2017 | 8 | 449 | 2017 | 9 | 103 | 2017 | 10 | 207 | 2017 | 11 | 400 | 2017 | 12 | 1735 | 2017 | 13 | 32 | 2017 | 14 | 978 | 2017 | 15 | 761 | 2017 | 16 | 129 | 2017 | 17 | 180 | 2017 | NA | NA | NA | NA | NA | NA | Concón | 318496.3 | 2017 | 5103 | 42152 | 13425257057 | Urbano |
| 05105 | 1 | 5458 | 2017 | 2 | 2119 | 2017 | 3 | 51 | 2017 | 4 | 812 | 2017 | 5 | 4693 | 2017 | 6 | 208 | 2017 | 7 | 134 | 2017 | 8 | 156 | 2017 | 9 | 62 | 2017 | 10 | 72 | 2017 | 11 | 227 | 2017 | 12 | 904 | 2017 | 13 | 6 | 2017 | 14 | 458 | 2017 | 15 | 380 | 2017 | 16 | 9 | 2017 | 17 | 106 | 2017 | NA | NA | NA | 19 | 4 | 2017 | Puchuncaví | 296035.5 | 2017 | 5105 | 18546 | 5490274928 | Urbano |
| 05107 | 1 | 8975 | 2017 | 2 | 3401 | 2017 | 3 | 93 | 2017 | 4 | 1226 | 2017 | 5 | 7972 | 2017 | 6 | 426 | 2017 | 7 | 247 | 2017 | 8 | 246 | 2017 | 9 | 110 | 2017 | 10 | 109 | 2017 | 11 | 324 | 2017 | 12 | 1563 | 2017 | 13 | 25 | 2017 | 14 | 903 | 2017 | 15 | 655 | 2017 | 16 | 12 | 2017 | 17 | 420 | 2017 | 18 | 134 | 2017 | 19 | 43 | 2017 | Quintero | 308224.7 | 2017 | 5107 | 31923 | 9839456903 | Urbano |
| 05109 | 1 | 119381 | 2017 | 2 | 43762 | 2017 | 3 | 808 | 2017 | 4 | 14060 | 2017 | 5 | 96190 | 2017 | 6 | 3632 | 2017 | 7 | 5056 | 2017 | 8 | 4167 | 2017 | 9 | 1123 | 2017 | 10 | 1638 | 2017 | 11 | 3719 | 2017 | 12 | 15361 | 2017 | 13 | 230 | 2017 | 14 | 10429 | 2017 | 15 | 8916 | 2017 | 16 | 450 | 2017 | 17 | 4944 | 2017 | 18 | 263 | 2017 | 19 | 119 | 2017 | Viña del Mar | 337006.1 | 2017 | 5109 | 334248 | 112643604611 | Urbano |
| 05201 | 1 | 2358 | 2017 | 2 | 653 | 2017 | 3 | 24 | 2017 | 4 | 427 | 2017 | 5 | 1704 | 2017 | 6 | 95 | 2017 | 7 | 78 | 2017 | 8 | 72 | 2017 | 9 | 38 | 2017 | 10 | 39 | 2017 | 11 | 49 | 2017 | 12 | 223 | 2017 | NA | NA | NA | 14 | 321 | 2017 | 15 | 384 | 2017 | 16 | 4 | 2017 | 17 | 853 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 05301 | 1 | 19637 | 2017 | 2 | 8324 | 2017 | 3 | 209 | 2017 | 4 | 2303 | 2017 | 5 | 18545 | 2017 | 6 | 739 | 2017 | 7 | 589 | 2017 | 8 | 633 | 2017 | 9 | 225 | 2017 | 10 | 292 | 2017 | 11 | 696 | 2017 | 12 | 3377 | 2017 | 13 | 39 | 2017 | 14 | 1855 | 2017 | 15 | 876 | 2017 | 16 | 20 | 2017 | 17 | 1771 | 2017 | 18 | 828 | 2017 | 19 | 59 | 2017 | Los Andes | 339720.2 | 2017 | 5301 | 66708 | 22662055502 | Urbano |
| 05302 | 1 | 3375 | 2017 | 2 | 1505 | 2017 | 3 | 63 | 2017 | 4 | 470 | 2017 | 5 | 3627 | 2017 | 6 | 166 | 2017 | 7 | 109 | 2017 | 8 | 106 | 2017 | 9 | 32 | 2017 | 10 | 52 | 2017 | 11 | 161 | 2017 | 12 | 574 | 2017 | 13 | 8 | 2017 | 14 | 302 | 2017 | 15 | 116 | 2017 | 16 | 7 | 2017 | 17 | 18 | 2017 | NA | NA | NA | NA | NA | NA | Calle Larga | 246387.3 | 2017 | 5302 | 14832 | 3654416747 | Urbano |
| 05303 | 1 | 2524 | 2017 | 2 | 1058 | 2017 | 3 | 37 | 2017 | 4 | 407 | 2017 | 5 | 2751 | 2017 | 6 | 102 | 2017 | 7 | 88 | 2017 | 8 | 74 | 2017 | 9 | 27 | 2017 | 10 | 44 | 2017 | 11 | 146 | 2017 | 12 | 508 | 2017 | 13 | 6 | 2017 | 14 | 179 | 2017 | 15 | 88 | 2017 | 16 | 4 | 2017 | 17 | 22 | 2017 | NA | NA | NA | NA | NA | NA | Rinconada | 273904.7 | 2017 | 5303 | 10207 | 2795744821 | Urbano |
| 05304 | 1 | 3686 | 2017 | 2 | 1688 | 2017 | 3 | 59 | 2017 | 4 | 493 | 2017 | 5 | 3895 | 2017 | 6 | 145 | 2017 | 7 | 107 | 2017 | 8 | 111 | 2017 | 9 | 27 | 2017 | 10 | 53 | 2017 | 11 | 124 | 2017 | 12 | 575 | 2017 | 13 | 5 | 2017 | 14 | 247 | 2017 | 15 | 103 | 2017 | 16 | 6 | 2017 | 17 | 48 | 2017 | NA | NA | NA | NA | NA | NA | San Esteban | 219571.6 | 2017 | 5304 | 18855 | 4140022481 | Urbano |
| 05401 | 1 | 8777 | 2017 | 2 | 3387 | 2017 | 3 | 93 | 2017 | 4 | 1121 | 2017 | 5 | 8231 | 2017 | 6 | 270 | 2017 | 7 | 277 | 2017 | 8 | 244 | 2017 | 9 | 76 | 2017 | 10 | 101 | 2017 | 11 | 401 | 2017 | 12 | 1691 | 2017 | 13 | 15 | 2017 | 14 | 781 | 2017 | 15 | 417 | 2017 | 16 | 10 | 2017 | 17 | 98 | 2017 | 18 | 5 | 2017 | 19 | 14 | 2017 | La Ligua | 250134.4 | 2017 | 5401 | 35390 | 8852256241 | Urbano |
| 05402 | 1 | 3903 | 2017 | 2 | 1594 | 2017 | 3 | 46 | 2017 | 4 | 411 | 2017 | 5 | 4015 | 2017 | 6 | 113 | 2017 | 7 | 143 | 2017 | 8 | 76 | 2017 | 9 | 38 | 2017 | 10 | 33 | 2017 | 11 | 183 | 2017 | 12 | 1033 | 2017 | 13 | 9 | 2017 | 14 | 332 | 2017 | 15 | 168 | 2017 | 16 | 3 | 2017 | 17 | 73 | 2017 | NA | NA | NA | NA | NA | NA | Cabildo | 262745.9 | 2017 | 5402 | 19388 | 5094117762 | Urbano |
| 05403 | 1 | 1793 | 2017 | 2 | 812 | 2017 | 3 | 14 | 2017 | 4 | 236 | 2017 | 5 | 1569 | 2017 | 6 | 70 | 2017 | 7 | 83 | 2017 | 8 | 44 | 2017 | 9 | 23 | 2017 | 10 | 23 | 2017 | 11 | 90 | 2017 | 12 | 295 | 2017 | 13 | 6 | 2017 | 14 | 178 | 2017 | 15 | 144 | 2017 | 16 | 8 | 2017 | 17 | 26 | 2017 | NA | NA | NA | NA | NA | NA | Papudo | 294355.2 | 2017 | 5403 | 6356 | 1870921373 | Urbano |
| 05404 | 1 | 1449 | 2017 | 2 | 486 | 2017 | 3 | 21 | 2017 | 4 | 174 | 2017 | 5 | 1219 | 2017 | 6 | 34 | 2017 | 7 | 44 | 2017 | 8 | 29 | 2017 | 9 | 9 | 2017 | 10 | 14 | 2017 | 11 | 44 | 2017 | 12 | 229 | 2017 | NA | NA | NA | 14 | 83 | 2017 | 15 | 100 | 2017 | 16 | 3 | 2017 | 17 | 165 | 2017 | NA | NA | NA | NA | NA | NA | Petorca | 237510.8 | 2017 | 5404 | 9826 | 2333781007 | Urbano |
| 05405 | 1 | 1686 | 2017 | 2 | 750 | 2017 | 3 | 8 | 2017 | 4 | 212 | 2017 | 5 | 1466 | 2017 | 6 | 80 | 2017 | 7 | 56 | 2017 | 8 | 43 | 2017 | 9 | 21 | 2017 | 10 | 26 | 2017 | 11 | 83 | 2017 | 12 | 288 | 2017 | 13 | 7 | 2017 | 14 | 107 | 2017 | 15 | 138 | 2017 | 16 | 13 | 2017 | 17 | 29 | 2017 | NA | NA | NA | NA | NA | NA | Zapallar | 294389.2 | 2017 | 5405 | 7339 | 2160521991 | Urbano |
| 05501 | 1 | 25631 | 2017 | 2 | 9910 | 2017 | 3 | 222 | 2017 | 4 | 3536 | 2017 | 5 | 25284 | 2017 | 6 | 987 | 2017 | 7 | 1048 | 2017 | 8 | 939 | 2017 | 9 | 271 | 2017 | 10 | 322 | 2017 | 11 | 1035 | 2017 | 12 | 4381 | 2017 | 13 | 59 | 2017 | 14 | 2025 | 2017 | 15 | 1284 | 2017 | 16 | 36 | 2017 | 17 | 1314 | 2017 | NA | NA | NA | 19 | 47 | 2017 | Quillota | 286029.5 | 2017 | 5501 | 90517 | 25890529852 | Urbano |
names(df_2017_2)[3] <- "Jefe/a de hogar"
names(df_2017_2)[6] <- "Esposo/a o cónyuge"
names(df_2017_2)[9] <- "Conviviente por unión civil"
names(df_2017_2)[12] <- "Conviviente de hecho o pareja"
names(df_2017_2)[15] <- "Hijo/a"
names(df_2017_2)[18] <- "Hijo/a del cónyuge, conviviente o pareja"
names(df_2017_2)[21] <- "Hermano/a"
names(df_2017_2)[24] <- "Padre/madre"
names(df_2017_2)[27] <- "Cuñado/a"
names(df_2017_2)[30] <- "Suegro/a"
names(df_2017_2)[33] <- "Yerno/nuera"
names(df_2017_2)[36] <- "Nieto/a"
names(df_2017_2)[39] <- "Abuelo/a30"
names(df_2017_2)[42] <- "Otro pariente"
names(df_2017_2)[45] <- "No pariente"
names(df_2017_2)[48] <- "Servicio doméstico puertas adentro"
names(df_2017_2)[51] <- "Persona en vivienda colectiva"
names(df_2017_2)[54] <- "Persona en tránsito"
names(df_2017_2)[57] <- "Persona en operativo calle"1.2 Correlaciones
1.2.1Pearson
El coeficiente de correlación de Pearson es probablemente la medida más utilizada para las relaciones lineales entre dos variables distribuidas normales y, por lo tanto, a menudo se denomina simplemente “coeficiente de correlación”. Por lo general, el coeficiente de Pearson se obtiene mediante un ajuste de mínimos cuadrados y un valor de 1 representa una relación positiva perfecta, -1 una relación negativa perfecta y 0 indica la ausencia de una relación entre las variables.
\[ \rho = \frac{\text{cov}(X,Y)}{\sigma_x \sigma_y} codigos <- d_t \] \[ r = \frac{{}\sum_{i=1}^{n} (x_i - \overline{x})(y_i - \overline{y})} {\sqrt{\sum_{i=1}^{n} (x_i - \overline{x})^2(y_i - \overline{y})^2}} \]
Jefe/a de hogar - Cuñado/a
III <- seq(3,27,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "pearson"), pch=20)
Suegro/a - Persona en operativo calle
III <- seq(30,57,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "pearson"), pch=20)
1.2.2 Spearman
Relacionado con el coeficiente de correlación de Pearson, el coeficiente de correlación de Spearman (rho) mide la relación entre dos variables. La rho de Spearman puede entenderse como una versión basada en rangos del coeficiente de correlación de Pearson, que se puede utilizar para variables que no tienen una distribución normal y tienen una relación no lineal. Además, su uso no solo está restringido a datos continuos, sino que también puede usarse en análisis de atributos ordinales.
\[ \rho = 1- {\frac {6 \sum d_i^2}{n(n^2 - 1)}} \]
Jefe/a de hogar - Cuñado/a
III <- seq(3,27,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "spearman"), pch=20)
Suegro/a - Persona en operativo calle
III <- seq(30,57,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "spearman"), pch=20)
1.2.3 Kendall
Similar al coeficiente de correlación de Pearson, la tau de Kendall mide el grado de una relación monótona entre variables y, como la rho de Spearman, calcula la dependencia entre variables clasificadas, lo que hace que sea factible para datos distribuidos no normales. Kendall tau se puede calcular tanto para datos continuos como ordinales. En términos generales, la tau de Kendall se distingue de la rho de Spearman por una penalización más fuerte de las dislocaciones no secuenciales (en el contexto de las variables clasificadas).
\[ \tau = \frac{c-d}{c+d} = \frac{S}{ \left( \begin{matrix} n \\ 2 \end{matrix} \right)} = \frac{2S}{n(n-1)} \]
\[\tau = \frac{S}{\sqrt{n(n-1)/2-T}\sqrt{n(n-1)/2-U}} \\ \\ T = \sum_t t(t-1)/2 \\ \\ U = \sum_u u(u-1)/2 \\\]
Jefe/a de hogar - Cuñado/a
III <- seq(3,27,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "kendall"), pch=20)
Suegro/a - Persona en operativo calle
III <- seq(30,57,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "kendall"), pch=20)
RURAL
2 Pregunta P07: Relación de parentesco
1 Jefe/a de hogar
2 Esposo/a o cónyuge
3 Conviviente por unión civil
4 Conviviente de hecho o pareja
5 Hijo/a
6 Hijo/a del cónyuge, conviviente o pareja
7 Hermano/a
8 Padre/madre
9 Cuñado/a
10 Suegro/a
11 Yerno/nuera
12 Nieto/a
13 Abuelo/a30
14 Otro pariente
15 No pariente
16 Servicio doméstico puertas adentro
17 Persona en vivienda colectiva
18 Persona en tránsito
19 Persona en operativo calle
98 No aplica
99 Missing
98 No aplica
99 Missing
2.1 Cálculo de frecuencias
Leemos las respuestas a la pregunta P07 del censo de viviendas 2017 y obtenemos la tabla de frecuencias por categoría de respuesta:
tabla_con_clave <- readRDS("../censo_personas_con_clave_17")
tabla_con_clave <- filter(tabla_con_clave, tabla_con_clave$AREA == 2)
b <- tabla_con_clave$COMUNA
c <- tabla_con_clave$P07
cross_tab = xtabs( ~ unlist(b) + unlist(c))
tabla <- as.data.frame(cross_tab)
d <-tabla[!(tabla$Freq == 0),]
d$anio <- "2017"
d_t <- filter(d,d$unlist.c. == 1)
for(i in 2:19){
d_i <- filter(d,d$unlist.c. == i)
d_t = merge( x = d_t, y = d_i, by = "unlist.b.", all.x = TRUE)
}
codigos <- d_t$
unlist.b.
rango <- seq(1:nrow(d_t))
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_t,cadena)
comuna_corr <- comuna_corr[,-c(1),drop=FALSE]
names(comuna_corr)[58] <- "código"
ingresos_expandidos_2017 <- readRDS("ingresos_expandidos_17_rural_nacional.rds")
df_2017_2 = merge( x = comuna_corr, y = ingresos_expandidos_2017, by = "código", all.x = TRUE)
tablamadre <- head(df_2017_2,50)
kbl(tablamadre) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
kable_paper() %>%
scroll_box(width = "100%", height = "300px")| código | unlist.c..x | Freq.x | anio.x | unlist.c..y | Freq.y | anio.y | unlist.c..x.1 | Freq.x.1 | anio.x.1 | unlist.c..y.1 | Freq.y.1 | anio.y.1 | unlist.c..x.2 | Freq.x.2 | anio.x.2 | unlist.c..y.2 | Freq.y.2 | anio.y.2 | unlist.c..x.3 | Freq.x.3 | anio.x.3 | unlist.c..y.3 | Freq.y.3 | anio.y.3 | unlist.c..x.4 | Freq.x.4 | anio.x.4 | unlist.c..y.4 | Freq.y.4 | anio.y.4 | unlist.c..x.5 | Freq.x.5 | anio.x.5 | unlist.c..y.5 | Freq.y.5 | anio.y.5 | unlist.c..x.6 | Freq.x.6 | anio.x.6 | unlist.c..y.6 | Freq.y.6 | anio.y.6 | unlist.c..x.7 | Freq.x.7 | anio.x.7 | unlist.c..y.7 | Freq.y.7 | anio.y.7 | unlist.c..x.8 | Freq.x.8 | anio.x.8 | unlist.c..y.8 | Freq.y.8 | anio.y.8 | unlist.c. | Freq | anio | comuna.x | promedio_i | año | comuna.y | personas | Ingresos_expandidos | tipo |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01101 | 1 | 791 | 2017 | 2 | 260 | 2017 | 3 | 7 | 2017 | 4 | 121 | 2017 | 5 | 539 | 2017 | 6 | 27 | 2017 | 7 | 24 | 2017 | 8 | 21 | 2017 | 9 | 10 | 2017 | 10 | 8 | 2017 | 11 | 37 | 2017 | 12 | 121 | 2017 | 13 | 1 | 2017 | 14 | 107 | 2017 | 15 | 95 | 2017 | 16 | 8 | 2017 | 17 | 226 | 2017 | NA | NA | NA | NA | NA | NA | Iquique | 289375.3 | 2017 | 1101 | 191468 | 55406102543 | Rural |
| 01107 | 1 | 47 | 2017 | 2 | 7 | 2017 | 3 | 1 | 2017 | 4 | 8 | 2017 | 5 | 22 | 2017 | 6 | 3 | 2017 | 7 | 1 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | 11 | 2 | 2017 | 12 | 4 | 2017 | NA | NA | NA | NA | NA | NA | 15 | 6 | 2017 | 16 | 1 | 2017 | 17 | 2389 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 01401 | 1 | 1359 | 2017 | 2 | 510 | 2017 | 3 | 10 | 2017 | 4 | 113 | 2017 | 5 | 990 | 2017 | 6 | 39 | 2017 | 7 | 58 | 2017 | 8 | 46 | 2017 | 9 | 32 | 2017 | 10 | 23 | 2017 | 11 | 37 | 2017 | 12 | 148 | 2017 | 13 | 1 | 2017 | 14 | 159 | 2017 | 15 | 146 | 2017 | 16 | 17 | 2017 | 17 | 1928 | 2017 | NA | NA | NA | NA | NA | NA | Pozo Almonte | 263069.6 | 2017 | 1401 | 15711 | 4133086727 | Rural |
| 01402 | 1 | 484 | 2017 | 2 | 167 | 2017 | 3 | 12 | 2017 | 4 | 32 | 2017 | 5 | 371 | 2017 | 6 | 11 | 2017 | 7 | 8 | 2017 | 8 | 14 | 2017 | 9 | 3 | 2017 | 10 | 2 | 2017 | 11 | 14 | 2017 | 12 | 46 | 2017 | NA | NA | NA | 14 | 45 | 2017 | 15 | 22 | 2017 | NA | NA | NA | 17 | 19 | 2017 | NA | NA | NA | NA | NA | NA | Camiña | 262850.3 | 2017 | 1402 | 1250 | 328562901 | Rural |
| 01403 | 1 | 488 | 2017 | 2 | 196 | 2017 | 3 | 2 | 2017 | 4 | 19 | 2017 | 5 | 349 | 2017 | 6 | 9 | 2017 | 7 | 14 | 2017 | 8 | 9 | 2017 | 9 | 6 | 2017 | NA | NA | NA | 11 | 12 | 2017 | 12 | 48 | 2017 | 13 | 3 | 2017 | 14 | 58 | 2017 | 15 | 48 | 2017 | 16 | 8 | 2017 | 17 | 116 | 2017 | 18 | 343 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 01404 | 1 | 607 | 2017 | 2 | 184 | 2017 | 3 | 5 | 2017 | 4 | 52 | 2017 | 5 | 387 | 2017 | 6 | 12 | 2017 | 7 | 38 | 2017 | 8 | 22 | 2017 | 9 | 19 | 2017 | 10 | 8 | 2017 | 11 | 11 | 2017 | 12 | 51 | 2017 | NA | NA | NA | 14 | 84 | 2017 | 15 | 55 | 2017 | 16 | 7 | 2017 | 17 | 79 | 2017 | NA | NA | NA | NA | NA | NA | Huara | 253968.5 | 2017 | 1404 | 2730 | 693334131 | Rural |
| 01405 | 1 | 330 | 2017 | 2 | 129 | 2017 | 3 | 6 | 2017 | 4 | 34 | 2017 | 5 | 256 | 2017 | 6 | 27 | 2017 | 7 | 16 | 2017 | 8 | 10 | 2017 | 9 | 8 | 2017 | 10 | 6 | 2017 | 11 | 4 | 2017 | 12 | 31 | 2017 | NA | NA | NA | 14 | 39 | 2017 | 15 | 25 | 2017 | 16 | 4 | 2017 | 17 | 4459 | 2017 | NA | NA | NA | NA | NA | NA | Pica | 290496.7 | 2017 | 1405 | 9296 | 2700457509 | Rural |
| 02101 | 1 | 342 | 2017 | 2 | 70 | 2017 | 3 | 6 | 2017 | 4 | 66 | 2017 | 5 | 244 | 2017 | 6 | 23 | 2017 | 7 | 13 | 2017 | 8 | 5 | 2017 | 9 | 6 | 2017 | 10 | 3 | 2017 | 11 | 15 | 2017 | 12 | 39 | 2017 | NA | NA | NA | 14 | 52 | 2017 | 15 | 80 | 2017 | 16 | 1 | 2017 | 17 | 6804 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 02102 | 1 | 138 | 2017 | 2 | 36 | 2017 | 3 | 2 | 2017 | 4 | 20 | 2017 | 5 | 79 | 2017 | 6 | 6 | 2017 | 7 | 5 | 2017 | 8 | 2 | 2017 | 9 | 3 | 2017 | 10 | 3 | 2017 | 11 | 6 | 2017 | 12 | 29 | 2017 | NA | NA | NA | 14 | 24 | 2017 | 15 | 18 | 2017 | NA | NA | NA | 17 | 142 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 02103 | 1 | 358 | 2017 | 2 | 85 | 2017 | 3 | 4 | 2017 | 4 | 69 | 2017 | 5 | 363 | 2017 | 6 | 23 | 2017 | 7 | 12 | 2017 | 8 | 12 | 2017 | 9 | 12 | 2017 | 10 | 4 | 2017 | 11 | 24 | 2017 | 12 | 87 | 2017 | NA | NA | NA | 14 | 51 | 2017 | 15 | 42 | 2017 | 16 | 2 | 2017 | 17 | 9038 | 2017 | NA | NA | NA | NA | NA | NA | Sierra Gorda | 403458.5 | 2017 | 2103 | 10186 | 4109628188 | Rural |
| 02104 | 1 | 310 | 2017 | 2 | 69 | 2017 | 3 | 2 | 2017 | 4 | 39 | 2017 | 5 | 166 | 2017 | 6 | 16 | 2017 | 7 | 8 | 2017 | 8 | 5 | 2017 | 9 | 4 | 2017 | 10 | 3 | 2017 | 11 | 14 | 2017 | 12 | 42 | 2017 | NA | NA | NA | 14 | 37 | 2017 | 15 | 78 | 2017 | 16 | 2 | 2017 | 17 | 1399 | 2017 | NA | NA | NA | NA | NA | NA | Taltal | 345494.0 | 2017 | 2104 | 13317 | 4600943086 | Rural |
| 02201 | 1 | 980 | 2017 | 2 | 321 | 2017 | 3 | 14 | 2017 | 4 | 90 | 2017 | 5 | 805 | 2017 | 6 | 33 | 2017 | 7 | 42 | 2017 | 8 | 29 | 2017 | 9 | 17 | 2017 | 10 | 7 | 2017 | 11 | 21 | 2017 | 12 | 103 | 2017 | NA | NA | NA | 14 | 226 | 2017 | 15 | 84 | 2017 | 16 | 10 | 2017 | 17 | 4462 | 2017 | NA | NA | NA | NA | NA | NA | Calama | 310025.0 | 2017 | 2201 | 165731 | 51380756402 | Rural |
| 02202 | 1 | 102 | 2017 | 2 | 8 | 2017 | NA | NA | NA | 4 | 8 | 2017 | 5 | 59 | 2017 | 6 | 3 | 2017 | 7 | 1 | 2017 | 8 | 3 | 2017 | 9 | 1 | 2017 | 10 | 1 | 2017 | 11 | 3 | 2017 | 12 | 12 | 2017 | 13 | 1 | 2017 | 14 | 13 | 2017 | 15 | 5 | 2017 | NA | NA | NA | 17 | 101 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 02203 | 1 | 1382 | 2017 | 2 | 316 | 2017 | 3 | 17 | 2017 | 4 | 168 | 2017 | 5 | 929 | 2017 | 6 | 23 | 2017 | 7 | 56 | 2017 | 8 | 38 | 2017 | 9 | 15 | 2017 | 10 | 12 | 2017 | 11 | 40 | 2017 | 12 | 187 | 2017 | NA | NA | NA | 14 | 110 | 2017 | 15 | 228 | 2017 | 16 | 13 | 2017 | 17 | 1938 | 2017 | NA | NA | NA | NA | NA | NA | San Pedro de Atacama | 356147.9 | 2017 | 2203 | 10996 | 3916202829 | Rural |
| 02301 | 1 | 214 | 2017 | 2 | 51 | 2017 | 3 | 3 | 2017 | 4 | 25 | 2017 | 5 | 67 | 2017 | 6 | 9 | 2017 | 7 | 7 | 2017 | 8 | 3 | 2017 | 9 | 11 | 2017 | 10 | 4 | 2017 | 11 | 7 | 2017 | 12 | 21 | 2017 | NA | NA | NA | 14 | 55 | 2017 | 15 | 44 | 2017 | NA | NA | NA | 17 | 34 | 2017 | NA | NA | NA | NA | NA | NA | Tocopilla | 180218.1 | 2017 | 2301 | 25186 | 4538972205 | Rural |
| 02302 | 1 | 58 | 2017 | 2 | 20 | 2017 | NA | NA | NA | 4 | 9 | 2017 | 5 | 36 | 2017 | 6 | 3 | 2017 | 7 | 4 | 2017 | 8 | 1 | 2017 | 9 | 1 | 2017 | NA | NA | NA | 11 | 1 | 2017 | 12 | 13 | 2017 | NA | NA | NA | 14 | 12 | 2017 | 15 | 16 | 2017 | 16 | 8 | 2017 | 17 | 1350 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 03101 | 1 | 976 | 2017 | 2 | 382 | 2017 | 3 | 22 | 2017 | 4 | 155 | 2017 | 5 | 840 | 2017 | 6 | 36 | 2017 | 7 | 35 | 2017 | 8 | 29 | 2017 | 9 | 16 | 2017 | 10 | 23 | 2017 | 11 | 37 | 2017 | 12 | 133 | 2017 | NA | NA | NA | 14 | 91 | 2017 | 15 | 62 | 2017 | 16 | 4 | 2017 | 17 | 134 | 2017 | NA | NA | NA | NA | NA | NA | Copiapó | 308502.8 | 2017 | 3101 | 153937 | 47489990283 | Rural |
| 03102 | 1 | 814 | 2017 | 2 | 194 | 2017 | 3 | 16 | 2017 | 4 | 105 | 2017 | 5 | 319 | 2017 | 6 | 19 | 2017 | 7 | 16 | 2017 | 8 | 18 | 2017 | 9 | 11 | 2017 | 10 | 7 | 2017 | 11 | 18 | 2017 | 12 | 68 | 2017 | NA | NA | NA | 14 | 96 | 2017 | 15 | 152 | 2017 | 16 | 7 | 2017 | 17 | 27 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 03103 | 1 | 948 | 2017 | 2 | 251 | 2017 | 3 | 8 | 2017 | 4 | 242 | 2017 | 5 | 815 | 2017 | 6 | 27 | 2017 | 7 | 29 | 2017 | 8 | 16 | 2017 | 9 | 11 | 2017 | 10 | 6 | 2017 | 11 | 22 | 2017 | 12 | 110 | 2017 | NA | NA | NA | 14 | 75 | 2017 | 15 | 72 | 2017 | 16 | 2 | 2017 | 17 | 1450 | 2017 | NA | NA | NA | NA | NA | NA | Tierra Amarilla | 312457.3 | 2017 | 3103 | 14019 | 4380339153 | Rural |
| 03201 | 1 | 415 | 2017 | 2 | 129 | 2017 | 3 | 3 | 2017 | 4 | 68 | 2017 | 5 | 321 | 2017 | 6 | 11 | 2017 | 7 | 15 | 2017 | 8 | 16 | 2017 | 9 | 3 | 2017 | 10 | 5 | 2017 | 11 | 15 | 2017 | 12 | 61 | 2017 | NA | NA | NA | 14 | 33 | 2017 | 15 | 22 | 2017 | NA | NA | NA | 17 | 19 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 03202 | 1 | 250 | 2017 | 2 | 73 | 2017 | 3 | 4 | 2017 | 4 | 33 | 2017 | 5 | 176 | 2017 | 6 | 7 | 2017 | 7 | 11 | 2017 | 8 | 10 | 2017 | 9 | 7 | 2017 | 10 | 1 | 2017 | 11 | 8 | 2017 | 12 | 27 | 2017 | 13 | 1 | 2017 | 14 | 25 | 2017 | 15 | 12 | 2017 | NA | NA | NA | 17 | 25 | 2017 | NA | NA | NA | NA | NA | NA | Diego de Almagro | 374511.6 | 2017 | 3202 | 13925 | 5215073473 | Rural |
| 03301 | 1 | 1951 | 2017 | 2 | 712 | 2017 | 3 | 20 | 2017 | 4 | 279 | 2017 | 5 | 1748 | 2017 | 6 | 66 | 2017 | 7 | 109 | 2017 | 8 | 62 | 2017 | 9 | 34 | 2017 | 10 | 29 | 2017 | 11 | 93 | 2017 | 12 | 368 | 2017 | 13 | 4 | 2017 | 14 | 221 | 2017 | 15 | 126 | 2017 | 16 | 7 | 2017 | 17 | 69 | 2017 | NA | NA | NA | NA | NA | NA | Vallenar | 254290.6 | 2017 | 3301 | 51917 | 13202005308 | Rural |
| 03302 | 1 | 1772 | 2017 | 2 | 496 | 2017 | 3 | 25 | 2017 | 4 | 257 | 2017 | 5 | 1300 | 2017 | 6 | 73 | 2017 | 7 | 100 | 2017 | 8 | 47 | 2017 | 9 | 26 | 2017 | 10 | 22 | 2017 | 11 | 93 | 2017 | 12 | 314 | 2017 | 13 | 2 | 2017 | 14 | 223 | 2017 | 15 | 117 | 2017 | 16 | 5 | 2017 | 17 | 427 | 2017 | NA | NA | NA | NA | NA | NA | Alto del Carmen | 227130.4 | 2017 | 3302 | 5299 | 1203563833 | Rural |
| 03303 | 1 | 894 | 2017 | 2 | 268 | 2017 | 3 | 9 | 2017 | 4 | 129 | 2017 | 5 | 642 | 2017 | 6 | 39 | 2017 | 7 | 39 | 2017 | 8 | 28 | 2017 | 9 | 15 | 2017 | 10 | 5 | 2017 | 11 | 42 | 2017 | 12 | 146 | 2017 | 13 | 2 | 2017 | 14 | 91 | 2017 | 15 | 85 | 2017 | 16 | 2 | 2017 | 17 | 16 | 2017 | NA | NA | NA | NA | NA | NA | Freirina | 214803.3 | 2017 | 3303 | 7041 | 1512429891 | Rural |
| 03304 | 1 | 506 | 2017 | 2 | 170 | 2017 | NA | NA | NA | 4 | 57 | 2017 | 5 | 254 | 2017 | 6 | 11 | 2017 | 7 | 23 | 2017 | 8 | 11 | 2017 | 9 | 14 | 2017 | 10 | 4 | 2017 | 11 | 20 | 2017 | 12 | 86 | 2017 | 13 | 1 | 2017 | 14 | 56 | 2017 | 15 | 28 | 2017 | 16 | 1 | 2017 | 17 | 5 | 2017 | NA | NA | NA | NA | NA | NA | Huasco | 227560.7 | 2017 | 3304 | 10149 | 2309513927 | Rural |
| 04101 | 1 | 5847 | 2017 | 2 | 2495 | 2017 | 3 | 67 | 2017 | 4 | 1004 | 2017 | 5 | 5980 | 2017 | 6 | 244 | 2017 | 7 | 188 | 2017 | 8 | 180 | 2017 | 9 | 96 | 2017 | 10 | 111 | 2017 | 11 | 305 | 2017 | 12 | 1078 | 2017 | 13 | 11 | 2017 | 14 | 587 | 2017 | 15 | 325 | 2017 | 16 | 35 | 2017 | 17 | 1861 | 2017 | NA | NA | NA | NA | NA | NA | La Serena | 233184.2 | 2017 | 4101 | 221054 | 51546306303 | Rural |
| 04102 | 1 | 4144 | 2017 | 2 | 1796 | 2017 | 3 | 57 | 2017 | 4 | 691 | 2017 | 5 | 4030 | 2017 | 6 | 199 | 2017 | 7 | 170 | 2017 | 8 | 116 | 2017 | 9 | 53 | 2017 | 10 | 79 | 2017 | 11 | 214 | 2017 | 12 | 941 | 2017 | 13 | 5 | 2017 | 14 | 452 | 2017 | 15 | 207 | 2017 | 16 | 8 | 2017 | 17 | 18 | 2017 | NA | NA | NA | NA | NA | NA | Coquimbo | 231810.7 | 2017 | 4102 | 227730 | 52790242466 | Rural |
| 04103 | 1 | 417 | 2017 | 2 | 148 | 2017 | 3 | 4 | 2017 | 4 | 48 | 2017 | 5 | 275 | 2017 | 6 | 14 | 2017 | 7 | 18 | 2017 | 8 | 12 | 2017 | 9 | 4 | 2017 | 10 | 1 | 2017 | 11 | 7 | 2017 | 12 | 43 | 2017 | 13 | 2 | 2017 | 14 | 26 | 2017 | 15 | 17 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | Andacollo | 242908.2 | 2017 | 4103 | 11044 | 2682678345 | Rural |
| 04104 | 1 | 1086 | 2017 | 2 | 329 | 2017 | 3 | 18 | 2017 | 4 | 149 | 2017 | 5 | 754 | 2017 | 6 | 32 | 2017 | 7 | 27 | 2017 | 8 | 19 | 2017 | 9 | 18 | 2017 | 10 | 4 | 2017 | 11 | 53 | 2017 | 12 | 184 | 2017 | 13 | 1 | 2017 | 14 | 120 | 2017 | 15 | 59 | 2017 | 16 | 2 | 2017 | 17 | 93 | 2017 | NA | NA | NA | NA | NA | NA | La Higuera | 250699.6 | 2017 | 4104 | 4241 | 1063217069 | Rural |
| 04105 | 1 | 1612 | 2017 | 2 | 532 | 2017 | 3 | 16 | 2017 | 4 | 233 | 2017 | 5 | 1235 | 2017 | 6 | 48 | 2017 | 7 | 47 | 2017 | 8 | 49 | 2017 | 9 | 16 | 2017 | 10 | 18 | 2017 | 11 | 81 | 2017 | 12 | 265 | 2017 | 13 | 1 | 2017 | 14 | 124 | 2017 | 15 | 96 | 2017 | NA | NA | NA | 17 | 124 | 2017 | NA | NA | NA | NA | NA | NA | Paiguano | 205942.1 | 2017 | 4105 | 4497 | 926121774 | Rural |
| 04106 | 1 | 3451 | 2017 | 2 | 1223 | 2017 | 3 | 49 | 2017 | 4 | 534 | 2017 | 5 | 3099 | 2017 | 6 | 136 | 2017 | 7 | 150 | 2017 | 8 | 83 | 2017 | 9 | 60 | 2017 | 10 | 41 | 2017 | 11 | 201 | 2017 | 12 | 835 | 2017 | 13 | 4 | 2017 | 14 | 284 | 2017 | 15 | 231 | 2017 | 16 | 8 | 2017 | 17 | 389 | 2017 | NA | NA | NA | NA | NA | NA | Vicuña | 176130.6 | 2017 | 4106 | 27771 | 4891322768 | Rural |
| 04201 | 1 | 3404 | 2017 | 2 | 1324 | 2017 | 3 | 25 | 2017 | 4 | 465 | 2017 | 5 | 2883 | 2017 | 6 | 94 | 2017 | 7 | 163 | 2017 | 8 | 65 | 2017 | 9 | 50 | 2017 | 10 | 42 | 2017 | 11 | 143 | 2017 | 12 | 610 | 2017 | 13 | 5 | 2017 | 14 | 302 | 2017 | 15 | 169 | 2017 | 16 | 6 | 2017 | 17 | 46 | 2017 | NA | NA | NA | NA | NA | NA | Illapel | 191976.8 | 2017 | 4201 | 30848 | 5922099530 | Rural |
| 04202 | 1 | 2713 | 2017 | 2 | 934 | 2017 | 3 | 18 | 2017 | 4 | 297 | 2017 | 5 | 1980 | 2017 | 6 | 52 | 2017 | 7 | 161 | 2017 | 8 | 49 | 2017 | 9 | 25 | 2017 | 10 | 31 | 2017 | 11 | 89 | 2017 | 12 | 441 | 2017 | 13 | 2 | 2017 | 14 | 222 | 2017 | 15 | 105 | 2017 | 16 | 2 | 2017 | 17 | 12 | 2017 | NA | NA | NA | NA | NA | NA | Canela | 171370.3 | 2017 | 4202 | 9093 | 1558270441 | Rural |
| 04203 | 1 | 1453 | 2017 | 2 | 533 | 2017 | 3 | 30 | 2017 | 4 | 216 | 2017 | 5 | 1182 | 2017 | 6 | 61 | 2017 | 7 | 73 | 2017 | 8 | 23 | 2017 | 9 | 28 | 2017 | 10 | 15 | 2017 | 11 | 59 | 2017 | 12 | 228 | 2017 | 13 | 2 | 2017 | 14 | 121 | 2017 | 15 | 99 | 2017 | 16 | 3 | 2017 | 17 | 162 | 2017 | NA | NA | NA | NA | NA | NA | Los Vilos | 173238.5 | 2017 | 4203 | 21382 | 3704185607 | Rural |
| 04204 | 1 | 3729 | 2017 | 2 | 1411 | 2017 | 3 | 37 | 2017 | 4 | 452 | 2017 | 5 | 3171 | 2017 | 6 | 117 | 2017 | 7 | 184 | 2017 | 8 | 58 | 2017 | 9 | 52 | 2017 | 10 | 22 | 2017 | 11 | 166 | 2017 | 12 | 783 | 2017 | 13 | 4 | 2017 | 14 | 405 | 2017 | 15 | 191 | 2017 | 16 | 2 | 2017 | 17 | 1760 | 2017 | NA | NA | NA | NA | NA | NA | Salamanca | 223234.2 | 2017 | 4204 | 29347 | 6551254640 | Rural |
| 04301 | 1 | 7975 | 2017 | 2 | 2872 | 2017 | 3 | 96 | 2017 | 4 | 1249 | 2017 | 5 | 7212 | 2017 | 6 | 324 | 2017 | 7 | 360 | 2017 | 8 | 167 | 2017 | 9 | 88 | 2017 | 10 | 63 | 2017 | 11 | 342 | 2017 | 12 | 1636 | 2017 | 13 | 13 | 2017 | 14 | 788 | 2017 | 15 | 389 | 2017 | 16 | 15 | 2017 | 17 | 144 | 2017 | NA | NA | NA | NA | NA | NA | Ovalle | 241393.7 | 2017 | 4301 | 111272 | 26860360045 | Rural |
| 04302 | 1 | 2830 | 2017 | 2 | 821 | 2017 | 3 | 30 | 2017 | 4 | 318 | 2017 | 5 | 1847 | 2017 | 6 | 65 | 2017 | 7 | 148 | 2017 | 8 | 55 | 2017 | 9 | 24 | 2017 | 10 | 9 | 2017 | 11 | 88 | 2017 | 12 | 485 | 2017 | 13 | 3 | 2017 | 14 | 266 | 2017 | 15 | 89 | 2017 | 16 | 2 | 2017 | 17 | 244 | 2017 | NA | NA | NA | NA | NA | NA | Combarbalá | 179139.6 | 2017 | 4302 | 13322 | 2386498044 | Rural |
| 04303 | 1 | 5489 | 2017 | 2 | 1783 | 2017 | 3 | 86 | 2017 | 4 | 764 | 2017 | 5 | 4530 | 2017 | 6 | 201 | 2017 | 7 | 198 | 2017 | 8 | 127 | 2017 | 9 | 47 | 2017 | 10 | 38 | 2017 | 11 | 209 | 2017 | 12 | 1039 | 2017 | 13 | 10 | 2017 | 14 | 431 | 2017 | 15 | 184 | 2017 | 16 | 5 | 2017 | 17 | 272 | 2017 | NA | NA | NA | NA | NA | NA | Monte Patria | 201205.8 | 2017 | 4303 | 30751 | 6187280931 | Rural |
| 04304 | 1 | 1865 | 2017 | 2 | 619 | 2017 | 3 | 12 | 2017 | 4 | 259 | 2017 | 5 | 1494 | 2017 | 6 | 58 | 2017 | 7 | 96 | 2017 | 8 | 36 | 2017 | 9 | 14 | 2017 | 10 | 10 | 2017 | 11 | 66 | 2017 | 12 | 327 | 2017 | 13 | 4 | 2017 | 14 | 162 | 2017 | 15 | 63 | 2017 | 16 | 3 | 2017 | 17 | 20 | 2017 | NA | NA | NA | NA | NA | NA | Punitaqui | 171931.7 | 2017 | 4304 | 10956 | 1883683880 | Rural |
| 04305 | 1 | 1699 | 2017 | 2 | 429 | 2017 | 3 | 10 | 2017 | 4 | 232 | 2017 | 5 | 1079 | 2017 | 6 | 53 | 2017 | 7 | 71 | 2017 | 8 | 42 | 2017 | 9 | 14 | 2017 | 10 | 11 | 2017 | 11 | 56 | 2017 | 12 | 305 | 2017 | 13 | 1 | 2017 | 14 | 125 | 2017 | 15 | 85 | 2017 | 16 | 1 | 2017 | 17 | 65 | 2017 | NA | NA | NA | NA | NA | NA | Río Hurtado | 182027.2 | 2017 | 4305 | 4278 | 778712384 | Rural |
| 05101 | 1 | 285 | 2017 | 2 | 104 | 2017 | 3 | 3 | 2017 | 4 | 39 | 2017 | 5 | 163 | 2017 | 6 | 13 | 2017 | 7 | 5 | 2017 | 8 | 7 | 2017 | 9 | 1 | 2017 | 10 | 2 | 2017 | 11 | 6 | 2017 | 12 | 26 | 2017 | NA | NA | NA | 14 | 23 | 2017 | 15 | 31 | 2017 | NA | NA | NA | 17 | 29 | 2017 | NA | NA | NA | NA | NA | NA | Valparaíso | 331716.1 | 2017 | 5101 | 296655 | 98405237576 | Rural |
| 05102 | 1 | 2984 | 2017 | 2 | 1433 | 2017 | 3 | 23 | 2017 | 4 | 397 | 2017 | 5 | 2554 | 2017 | 6 | 128 | 2017 | 7 | 99 | 2017 | 8 | 71 | 2017 | 9 | 35 | 2017 | 10 | 45 | 2017 | 11 | 117 | 2017 | 12 | 427 | 2017 | 13 | 3 | 2017 | 14 | 250 | 2017 | 15 | 202 | 2017 | 16 | 23 | 2017 | 17 | 74 | 2017 | NA | NA | NA | NA | NA | NA | Casablanca | 268917.1 | 2017 | 5102 | 26867 | 7224996933 | Rural |
| 05103 | 1 | 786 | 2017 | 2 | 373 | 2017 | 3 | 3 | 2017 | 4 | 106 | 2017 | 5 | 828 | 2017 | 6 | 36 | 2017 | 7 | 18 | 2017 | 8 | 22 | 2017 | 9 | 14 | 2017 | 10 | 12 | 2017 | 11 | 51 | 2017 | 12 | 126 | 2017 | 13 | 2 | 2017 | 14 | 86 | 2017 | 15 | 32 | 2017 | 16 | 2 | 2017 | 17 | 246 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 05104 | 1 | 353 | 2017 | 2 | 108 | 2017 | 3 | 9 | 2017 | 4 | 58 | 2017 | 5 | 224 | 2017 | 6 | 12 | 2017 | 7 | 5 | 2017 | 8 | 10 | 2017 | 9 | 3 | 2017 | 10 | 2 | 2017 | 11 | 5 | 2017 | 12 | 37 | 2017 | 13 | 2 | 2017 | 14 | 24 | 2017 | 15 | 38 | 2017 | NA | NA | NA | 17 | 27 | 2017 | 18 | 9 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 05105 | 1 | 976 | 2017 | 2 | 402 | 2017 | 3 | 9 | 2017 | 4 | 129 | 2017 | 5 | 799 | 2017 | 6 | 25 | 2017 | 7 | 27 | 2017 | 8 | 21 | 2017 | 9 | 6 | 2017 | 10 | 12 | 2017 | 11 | 34 | 2017 | 12 | 140 | 2017 | 13 | 1 | 2017 | 14 | 54 | 2017 | 15 | 51 | 2017 | 16 | 1 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | Puchuncaví | 279614.4 | 2017 | 5105 | 18546 | 5185728335 | Rural |
| 05107 | 1 | 1627 | 2017 | 2 | 868 | 2017 | 3 | 7 | 2017 | 4 | 203 | 2017 | 5 | 1623 | 2017 | 6 | 64 | 2017 | 7 | 37 | 2017 | 8 | 49 | 2017 | 9 | 15 | 2017 | 10 | 42 | 2017 | 11 | 54 | 2017 | 12 | 179 | 2017 | 13 | 2 | 2017 | 14 | 145 | 2017 | 15 | 78 | 2017 | 16 | 19 | 2017 | 17 | 27 | 2017 | NA | NA | NA | NA | NA | NA | Quintero | 334628.2 | 2017 | 5107 | 31923 | 10682335196 | Rural |
| 05201 | 1 | 151 | 2017 | 2 | 38 | 2017 | 3 | 3 | 2017 | 4 | 41 | 2017 | 5 | 128 | 2017 | 6 | 6 | 2017 | 7 | 2 | 2017 | 8 | 3 | 2017 | 9 | 4 | 2017 | 10 | 3 | 2017 | 11 | 1 | 2017 | 12 | 4 | 2017 | 13 | 1 | 2017 | 14 | 16 | 2017 | 15 | 8 | 2017 | 16 | 3 | 2017 | 17 | 16 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 05301 | 1 | 1243 | 2017 | 2 | 570 | 2017 | 3 | 9 | 2017 | 4 | 153 | 2017 | 5 | 1212 | 2017 | 6 | 54 | 2017 | 7 | 44 | 2017 | 8 | 29 | 2017 | 9 | 9 | 2017 | 10 | 8 | 2017 | 11 | 68 | 2017 | 12 | 252 | 2017 | 13 | 2 | 2017 | 14 | 102 | 2017 | 15 | 58 | 2017 | 16 | 3 | 2017 | 17 | 1875 | 2017 | NA | NA | NA | NA | NA | NA | Los Andes | 324402.1 | 2017 | 5301 | 66708 | 21640215030 | Rural |
| 05302 | 1 | 1329 | 2017 | 2 | 637 | 2017 | 3 | 29 | 2017 | 4 | 156 | 2017 | 5 | 1282 | 2017 | 6 | 49 | 2017 | 7 | 34 | 2017 | 8 | 34 | 2017 | 9 | 27 | 2017 | 10 | 27 | 2017 | 11 | 77 | 2017 | 12 | 260 | 2017 | 13 | 1 | 2017 | 14 | 154 | 2017 | 15 | 40 | 2017 | 16 | 5 | 2017 | NA | NA | NA | NA | NA | NA | NA | NA | NA | Calle Larga | 242743.8 | 2017 | 5302 | 14832 | 3600375502 | Rural |
| 05303 | 1 | 668 | 2017 | 2 | 303 | 2017 | 3 | 6 | 2017 | 4 | 100 | 2017 | 5 | 660 | 2017 | 6 | 17 | 2017 | 7 | 15 | 2017 | 8 | 18 | 2017 | 9 | 6 | 2017 | 10 | 10 | 2017 | 11 | 44 | 2017 | 12 | 121 | 2017 | 13 | 1 | 2017 | 14 | 53 | 2017 | 15 | 19 | 2017 | 16 | 6 | 2017 | 17 | 95 | 2017 | NA | NA | NA | NA | NA | NA | Rinconada | 326532.5 | 2017 | 5303 | 10207 | 3332917471 | Rural |
names(df_2017_2)[3] <- "Jefe/a de hogar"
names(df_2017_2)[6] <- "Esposo/a o cónyuge"
names(df_2017_2)[9] <- "Conviviente por unión civil"
names(df_2017_2)[12] <- "Conviviente de hecho o pareja"
names(df_2017_2)[15] <- "Hijo/a"
names(df_2017_2)[18] <- "Hijo/a del cónyuge, conviviente o pareja"
names(df_2017_2)[21] <- "Hermano/a"
names(df_2017_2)[24] <- "Padre/madre"
names(df_2017_2)[27] <- "Cuñado/a"
names(df_2017_2)[30] <- "Suegro/a"
names(df_2017_2)[33] <- "Yerno/nuera"
names(df_2017_2)[36] <- "Nieto/a"
names(df_2017_2)[39] <- "Abuelo/a30"
names(df_2017_2)[42] <- "Otro pariente"
names(df_2017_2)[45] <- "No pariente"
names(df_2017_2)[48] <- "Servicio doméstico puertas adentro"
names(df_2017_2)[51] <- "Persona en vivienda colectiva"
names(df_2017_2)[54] <- "Persona en tránsito"
names(df_2017_2)[57] <- "Persona en operativo calle"2.2 Correlaciones
1.2.1Pearson
El coeficiente de correlación de Pearson es probablemente la medida más utilizada para las relaciones lineales entre dos variables distribuidas normales y, por lo tanto, a menudo se denomina simplemente “coeficiente de correlación”. Por lo general, el coeficiente de Pearson se obtiene mediante un ajuste de mínimos cuadrados y un valor de 1 representa una relación positiva perfecta, -1 una relación negativa perfecta y 0 indica la ausencia de una relación entre las variables.
\[ \rho = \frac{\text{cov}(X,Y)}{\sigma_x \sigma_y} codigos <- d_t \] \[ r = \frac{{}\sum_{i=1}^{n} (x_i - \overline{x})(y_i - \overline{y})} {\sqrt{\sum_{i=1}^{n} (x_i - \overline{x})^2(y_i - \overline{y})^2}} \]
Jefe/a de hogar - Cuñado/a
III <- seq(3,27,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "pearson"), pch=20)
Suegro/a - Persona en operativo calle
III <- seq(30,51,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "pearson"), pch=20)
2.2.2 Spearman
Relacionado con el coeficiente de correlación de Pearson, el coeficiente de correlación de Spearman (rho) mide la relación entre dos variables. La rho de Spearman puede entenderse como una versión basada en rangos del coeficiente de correlación de Pearson, que se puede utilizar para variables que no tienen una distribución normal y tienen una relación no lineal. Además, su uso no solo está restringido a datos continuos, sino que también puede usarse en análisis de atributos ordinales.
\[ \rho = 1- {\frac {6 \sum d_i^2}{n(n^2 - 1)}} \]
Jefe/a de hogar - Cuñado/a
III <- seq(3,27,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "spearman"), pch=20)
Suegro/a - Persona en operativo calle
III <- seq(30,51,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "spearman"), pch=20)
1.2.3 Kendall
Similar al coeficiente de correlación de Pearson, la tau de Kendall mide el grado de una relación monótona entre variables y, como la rho de Spearman, calcula la dependencia entre variables clasificadas, lo que hace que sea factible para datos distribuidos no normales. Kendall tau se puede calcular tanto para datos continuos como ordinales. En términos generales, la tau de Kendall se distingue de la rho de Spearman por una penalización más fuerte de las dislocaciones no secuenciales (en el contexto de las variables clasificadas).
\[ \tau = \frac{c-d}{c+d} = \frac{S}{ \left( \begin{matrix} n \\ 2 \end{matrix} \right)} = \frac{2S}{n(n-1)} \]
\[\tau = \frac{S}{\sqrt{n(n-1)/2-T}\sqrt{n(n-1)/2-U}} \\ \\ T = \sum_t t(t-1)/2 \\ \\ U = \sum_u u(u-1)/2 \\\]
Jefe/a de hogar - Cuñado/a
III <- seq(3,27,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "kendall"), pch=20)
Suegro/a - Persona en operativo calle
III <- seq(30,51,3)
my_data <- df_2017_2[, c(III,64)]
chart.Correlation(my_data, histogram=TRUE, method = c( "kendall"), pch=20)