Análisis de frecuencias en el Censo 2017 de Chile

DataIntelligence

Abstract

Construímos un código para los registros, tablas de contingencia básicas para las preguntas del Censo del 2017 y algunos ejercicios sobre comunas específicas.

Parte I: Construcción de la clave

1 Se lee el microdato Censo 2017 csv con la función import de la librería rio.

library("rio")
x <- import("Microdato_Censo2017-Personas.csv")

debemos hacer un subset para trabajar mas rápido:

x <- x[c(1:10000),]

2 Analicemos la estructura del código de Comuna:

unique(x$COMUNA)

## [1] 15202 15201 15102 15101

• Vemos que algunos códigos tienen 5 digitos y otros 4. Vamos a dejar ésto inalterado . Sin embargo, añadimos un trozo de código si en el futuro se desea agregar un cero previo a las comunas de 4 dígitos para homologar.

# recogemos el campo Comuna:
codigos <- x$COMUNA
# construimos una secuencia llamada rango del 1 al total de filas del dataset:
rango <- seq(1:nrow(x))
# Creamos un string que agrega un cero a todos los registros:
cadena<- paste("0",codigos[rango], sep = "")

# El string cadena tiene o 5 o 6 digitos, los cuales siempre deben ser siempre 5 agregandole un cero al inicio de los que tienen 4.
# Para ello extraemos un substring de la cadena sobre todas las filas (rangos) comenzando desde el primero o el segundo y llegando siempre al 6.

cadena <- substr(cadena,(nchar(cadena)[rango])-(4),6)
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
comuna_corr <- cbind(codigos,cadena)

• Lo verificamos

unique(comuna_corr$cadena)

## [1] "15202" "15201" "15102" "15101"

3 Analicemos la estructura del código de DC:

unique(x$DC)

## [1]  1  2  3  4 99  5  6  7  8

Debemos agregar un cero a la izquierda a todos los códigos DC que contengan un dígito:

# Le asignamos a la variable codigos, la variable DC del dataframe x:
codigos <- x$DC

# Creamos una secuencia llamada rango con toda la cantidad de registros del dataframe:
rango <- seq(1:nrow(x))

# Creamos un string que añade un cero a todos los codigos quedando algunos con dos dígitos y otros con tres: 
cadena <- paste("0",codigos[rango], sep = "")

# Ésta es la línea más importante del código. 
# Si el string entrante contiene tres digitos, la función substr comenzaría desde la posición 2 a la 3, y si tiene 2, comenzaría desde la posición 1 a la 3, pero como no existe posición tres, llega a la 2.

cadena <- substr(cadena,(nchar(cadena)[rango])-(1),(nchar(cadena)[rango]))

codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
dc <- cbind(codigos,cadena)

4 Lo verificamos

unique(dc$cadena)

## [1] "01" "02" "03" "04" "99" "05" "06" "07" "08"

5 Analicemos la estructura del código de zc_loc:

a002 <- unique(x$ZC_LOC)

kbl(a002) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "30%", height = "300px")

x
6
8
12
15
4
5
9
11
901
1
2
10
14
13
999
7
21
3
20
17

Deben todos los codigos poseer tres dígitos, agregándole un cero a los que tienen 2 y dos ceros a los que tienen uno.

codigos <- x$ZC_LOC
rango <- seq(1:nrow(x))
cadena<- paste("00",codigos[rango], sep = "")
cadena <- substr(cadena,(nchar(cadena)[rango])-(2),nchar(cadena)[rango])
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
cadena_c <- cbind(codigos,cadena)

6 lo verificamos

unique(cadena_c$cadena)

##  [1] "006" "008" "012" "015" "004" "005" "009" "011" "901" "001" "002" "010"
## [13] "014" "013" "999" "007" "021" "003" "020" "017"

7 Unimos nuestra nueva clave a nuestro dataframe original con el nombre de campo clave:

x$clave <- paste(x$COMUNA, dc$cadena, x$AREA,  cadena_c$cadena, sep="")

---

Parte II: Generación de las tablas de contingencia:

El Censo 2017 contempla preguntas agrupadas por el prefijo P y un número.

P07 Relación de parentesco y tabla de codificación.

tabla_P07 <- table(x$clave, x$P07, useNA = "no")
#write_xlsx(tabla_P07, "tabla_P07.xlsx")
a001 <- head(tabla_P07,5)
kbl(a001) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18
15101011001	438	125	5	43	274	14	31	14	10	8	16	47	1	66	35	7	411	0
15101011002	339	91	1	33	193	6	19	18	7	3	8	36	2	45	30	2	168	0
15101021001	830	240	9	86	548	14	46	36	7	11	14	107	3	75	62	0	662	0
15102012002	12	4	0	1	7	0	0	0	0	0	0	0	0	0	0	1	0	0
15102012003	220	54	0	9	96	0	10	3	0	1	6	22	0	37	40	2	65	0

#### P08-P12COMUNA: Geografía humana y codificación de respuestas.

P08: sexo

tabla_P08 <- table(x$clave, x$P08, useNA = "no")
#write_xlsx(tabla_P08, "tabla_P08.xlsx")

a_003 <- head(tabla_P08,50)
kbl(a_003) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	1	2
15101011001	843	702
15101011002	494	507
15101021001	1692	1058
15102012002	16	9
15102012003	300	265
15102022007	21	18
15102032005	55	57
15102032008	9	5
15102032901	17	13
15102042001	105	76
15102052004	174	85
15102052006	29	1
15201011001	1323	393
15201012901	19	18
15201022002	37	15
15201032006	22	9
15201032007	38	14
15201032901	18	17
15201042009	10	5
15201042021	41	34
15201042901	10	12
15201052001	34	29
15201052003	38	15
15201052012	12	13
15201052013	7	10
15201052020	11	7
15201052901	3	4
15201062005	4	0
15201062010	21	19
15201062017	2	0
15201062901	2	3
15201072901	25	28
15201082004	7	0
15201991999	370	66
15202012006	27	29
15202012008	6	6
15202012012	9	10
15202012015	96	73
15202022004	25	17
15202022005	8	7
15202022009	29	39
15202022011	70	17
15202022901	10	10
15202032001	14	8
15202032002	14	13
15202032010	4	11
15202032014	69	0
15202032901	8	8
15202042013	15	15
15202042901	8	8

P09: edad

tabla_P09 <- table(x$clave, x$P09, useNA = "no")
#write_xlsx(tabla_P09, "tabla_P09.xlsx")


a_004 <- head(tabla_P09,50)

kbl(a_004) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	54	55	56	57	58	59	60	61	62	63	64	65	66	67	68	69	70	71	72	73	74	75	76	77	78	79	80	81	82	83	84	85	86	87	88	89	90	91	92	93	95	96	97	98	99	100
15101011001	4	15	15	8	16	8	19	13	12	22	14	16	11	14	13	10	12	10	8	11	22	25	16	22	25	35	27	29	33	20	22	33	24	20	28	23	25	29	29	21	18	19	16	27	21	27	18	19	21	16	18	20	16	15	21	20	29	25	15	24	21	19	19	24	19	12	18	16	20	18	16	20	10	10	10	13	13	11	15	9	6	6	11	7	2	1	7	3	10	2	4	3	0	2	1	1	0	1	0	1
15101011002	9	6	7	8	9	10	7	15	3	6	3	8	11	10	4	12	13	11	7	9	16	12	11	17	14	16	12	15	13	16	15	19	13	21	15	11	16	8	13	12	13	10	15	17	10	19	16	13	10	18	15	13	13	7	17	20	17	17	19	18	11	12	6	17	10	18	9	9	19	12	13	13	7	13	8	14	12	8	3	6	6	3	0	1	3	2	2	3	2	0	4	2	0	0	0	0	1	1	0	1
15101021001	34	39	26	22	23	24	38	25	20	25	26	18	14	27	27	18	25	25	171	219	88	70	68	50	48	65	57	48	42	55	41	41	46	36	43	51	39	29	25	24	30	22	25	36	35	22	20	25	31	32	24	20	22	16	25	27	26	28	18	36	25	27	15	20	23	19	14	14	19	11	10	10	16	19	12	19	14	15	14	10	12	6	11	15	7	7	11	4	2	3	0	5	3	2	1	1	1	0	1	0
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15102042001	3	3	3	3	2	1	4	2	3	1	1	1	2	1	2	0	2	1	1	1	2	2	1	5	0	3	3	3	3	1	6	4	7	1	4	3	3	0	0	3	1	1	4	3	3	4	5	3	1	3	5	3	2	0	2	3	4	4	3	0	4	4	3	2	0	2	3	4	3	0	0	1	2	0	0	1	1	1	0	0	1	0	1	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0
15102052004	2	4	3	2	1	3	4	1	2	6	2	5	0	3	5	2	1	2	1	3	1	5	5	4	6	8	5	3	6	4	7	5	4	6	4	1	6	6	3	3	1	8	6	5	2	5	1	3	2	2	4	8	8	2	3	7	4	3	3	1	6	3	6	5	2	2	2	1	1	2	3	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0
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15201011001	1	24	10	17	12	6	10	18	15	13	12	14	8	16	7	9	8	76	252	129	69	38	51	42	45	31	40	33	31	29	32	25	27	29	33	29	29	33	19	27	18	17	16	25	14	12	10	19	16	11	12	12	12	15	8	9	8	11	11	7	3	8	9	5	4	4	2	3	5	2	4	6	1	2	5	5	3	8	3	3	1	1	2	1	5	3	2	0	0	1	1	0	0	0	0	1	0	0	0	1
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15201052012	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1	0	1	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1	1	1	0	0	0	0	1	0	1	0	0	0	0	3	0	0	1	0	0	0	0	1	0	0	1	0	1	1	1	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201052013	0	0	0	0	0	0	0	2	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201052020	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	2	0	0	0	1	1	0	1	0	1	0	0	0	1	1	0	0	0	1	0	0	1	1	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0
15201052901	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0
15201062005	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201062010	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0	0	0	1	1	2	0	2	3	2	1	2	2	2	0	0	1	1	0	1	2	1	0	0	2	1	0	0	1	0	2	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201062017	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201062901	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201072901	0	0	0	1	1	2	2	1	2	0	2	0	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	1	2	0	1	2	1	0	0	2	0	1	1	0	0	1	1	0	0	0	0	0	0	0	0	1	1	0	0	0	1	1	2	1	0	1	0	3	0	2	1	3	2	0	3	1	0	1	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201082004	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15201991999	0	1	2	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	3	3	5	4	6	4	9	5	14	8	12	9	13	18	7	10	11	19	16	8	8	12	19	16	16	20	7	9	14	9	9	13	10	7	4	10	4	4	9	8	8	3	5	2	3	3	3	3	1	1	2	1	1	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202012006	0	1	1	1	1	0	3	0	2	0	0	1	1	3	0	1	1	0	0	1	0	1	1	0	3	0	1	0	0	1	0	1	0	0	0	2	2	0	0	1	0	1	0	2	1	0	0	1	0	0	1	0	1	0	0	1	1	0	1	1	0	0	0	0	0	3	0	0	1	0	1	1	0	1	3	1	1	0	2	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0
15202012008	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	1	0	0	0	0	0	0	1	0	0	0	1	2	1	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202012012	1	0	1	0	0	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	1	2	0	1	1	0	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202012015	2	3	0	2	1	2	3	2	0	1	0	3	3	1	1	2	1	2	1	1	1	2	3	0	3	3	3	2	2	2	1	3	2	4	3	4	2	5	3	3	4	4	5	3	3	0	2	5	4	1	3	0	1	5	7	3	2	3	3	1	2	3	1	2	1	3	2	1	2	3	2	0	2	0	0	2	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022004	0	1	0	2	0	0	2	0	3	0	0	1	0	2	1	3	0	0	1	0	0	0	1	0	0	0	1	0	1	0	0	1	0	1	0	1	0	0	1	1	0	1	0	0	0	1	1	0	0	0	0	0	0	2	1	0	0	1	0	2	1	2	0	1	1	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022005	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	1	1	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022009	2	0	1	2	0	0	0	0	1	1	1	1	0	2	1	1	2	1	1	2	1	0	0	2	1	0	0	0	4	0	0	0	0	0	2	1	1	0	0	1	0	2	2	0	1	2	1	0	2	1	2	1	0	0	0	1	1	1	2	2	0	0	1	1	1	2	2	1	2	0	1	1	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0
15202022011	0	2	0	1	0	0	1	1	0	1	0	0	0	1	0	2	1	0	2	4	3	1	4	3	1	2	2	3	3	5	4	4	0	2	1	0	3	2	0	0	1	1	0	2	2	1	0	0	2	0	0	0	1	0	1	1	2	0	1	1	0	3	1	2	1	0	0	0	1	2	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022901	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0	0	2	0	1	0	0	0	0	0	0	2	0	1	1	0	1	0	0	0	0	0	1	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032001	0	1	0	2	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	3	0	1	0	0	0	0	0	1	1	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032002	1	2	0	1	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	2	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1	0	0	2	0	0	0	0	1	1	0	2	0	0	0	1	0	0	0	1	0	3	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032010	1	1	0	0	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032014	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	7	5	3	4	6	1	4	5	4	3	1	1	4	3	2	5	1	3	1	2	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032901	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	1	0	2	0	1	0	1	0	0	2	0	1	0	0	0	0	1	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202042013	0	0	0	1	1	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	1	0	1	1	1	1	0	0	0	0	0	0	1	0	1	0	0	0	1	2	1	2	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	3	0	1	0	0	0	0	0	1	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0
15202042901	1	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	3	0	0	1	1	1	0	0	0	0	0	0	0	1	0	0	1	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

P10: residencia habitual

tabla_P10 <- table(x$clave, x$P10, useNA = "no")
#write_xlsx(tabla_P10, "tabla_P10.xlsx")

a_005 <- head(tabla_P10,50)

kbl(a_005) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	1	2	3	4	99
15101011001	1087	205	156	80	17
15101011002	784	57	126	15	19
15101021001	1976	674	66	9	25
15102012002	24	1	0	0	0
15102012003	430	27	84	16	8
15102022007	32	0	7	0	0
15102032005	83	9	20	0	0
15102032008	13	0	1	0	0
15102032901	29	0	1	0	0
15102042001	147	12	17	4	1
15102052004	176	54	25	2	2
15102052006	0	4	26	0	0
15201011001	914	711	72	6	13
15201012901	25	0	3	9	0
15201022002	43	2	7	0	0
15201032006	15	2	14	0	0
15201032007	0	5	47	0	0
15201032901	35	0	0	0	0
15201042009	15	0	0	0	0
15201042021	61	1	10	2	1
15201042901	11	2	1	7	1
15201052001	46	2	4	4	7
15201052003	33	10	7	1	2
15201052012	24	1	0	0	0
15201052013	12	0	0	0	5
15201052020	17	0	1	0	0
15201052901	3	3	0	0	1
15201062005	0	0	4	0	0
15201062010	39	0	1	0	0
15201062017	0	1	1	0	0
15201062901	5	0	0	0	0
15201072901	48	3	1	0	1
15201082004	0	0	7	0	0
15201991999	5	0	34	396	1
15202012006	46	8	1	1	0
15202012008	11	0	0	0	1
15202012012	16	1	0	0	2
15202012015	130	14	19	2	4
15202022004	42	0	0	0	0
15202022005	15	0	0	0	0
15202022009	65	0	0	0	3
15202022011	74	12	1	0	0
15202022901	18	0	0	0	2
15202032001	21	0	0	0	1
15202032002	26	0	1	0	0
15202032010	15	0	0	0	0
15202032014	56	13	0	0	0
15202032901	16	0	0	0	0
15202042013	23	7	0	0	0
15202042901	13	0	2	0	1

Demografía geográfica.

P10COMUNA: Comuna de residencia habitual

tabla_P10COMUNA <- table(x$clave, x$P10COMUNA)
#write_xlsx(tabla_P10COMUNA, "tabla_P10COMUNA.xlsx")


a_006 <- head(tabla_P10COMUNA,50)

kbl(a_006) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	98	99	997	1101	1107	1401	1403	2101	2103	2201	3102	3301	4101	4102	4201	4203	4301	5000	5101	5102	5103	5105	5107	5109	5301	5401	5404	5501	5502	5504	5601	5602	5701	5702	5801	5804	6113	6115	6117	6303	7101	7102	7301	7401	7406	7408	8101	8102	8103	8111	8112	8201	8202	8301	8309	9101	9110	9116	9118	9120	9210	10101	10302	12000	12101	13000	13101	13102	13103	13104	13105	13106	13107	13108	13109	13110	13111	13113	13114	13118	13119	13120	13121	13122	13123	13124	13125	13127	13129	13130	13131	13201	13203	13301	13401	13403	13404	13601	13602	13604	13605	14101	14106	14204	15000	15101	15102	15201	15202	16101	16205
15101011001	1372	17	1	9	0	0	0	7	0	5	0	0	4	6	0	0	3	1	3	0	0	0	0	3	0	0	0	0	0	0	0	1	0	0	0	1	1	3	1	2	5	0	1	4	0	0	2	0	1	0	0	0	0	0	0	0	1	1	0	0	0	3	0	0	0	2	22	2	4	0	2	0	1	1	0	3	2	1	5	2	2	0	3	1	2	6	1	1	3	0	3	3	3	0	2	0	1	3	1	3	0	0	0	0	0	0	0	0	0	1	1
15101011002	856	19	5	3	0	0	0	5	0	0	2	4	0	2	0	0	3	0	2	0	0	2	4	2	1	0	0	2	3	0	2	0	1	0	2	0	0	0	1	0	0	1	0	0	1	0	1	0	0	0	1	2	1	1	0	3	0	0	0	2	0	0	0	2	0	0	10	2	2	1	0	2	0	0	2	5	0	2	2	2	3	7	0	0	2	3	0	1	0	6	0	9	0	0	0	0	0	1	1	1	0	1	0	0	0	0	0	0	0	0	0
15101021001	2659	25	4	2	0	0	0	0	0	3	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	1	0	0	2	0	14	1	0	0	0	0	0	0	0	1	0	0	1	0	10	2	0	0	0	1	2	1	2	0	0	0	0	1	0	0	2	0	0	0	4	1	0	0	0	0	0	0	0	2	0
15102012002	25	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15102012003	473	8	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	80	0	0	0	0	0
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15202022004	42	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022005	15	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022009	65	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202022011	86	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0
15202022901	18	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032001	21	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032002	26	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0
15202032010	15	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032014	69	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032901	16	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202042013	30	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202042901	13	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0

P11COMUNA: Comuna de residencia de hace 5 años

tabla_P11COMUNA <- table(x$clave, x$P11COMUNA, useNA = "no")
#write_xlsx(tabla_P11COMUNA, "tabla_P11COMUNA.xlsx")


a_007 <- head(tabla_P11COMUNA,50)

kbl(a_007) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	98	99	997	1000	1101	1107	1401	1402	1404	1405	2000	2101	2102	2104	2201	2202	2203	2301	2302	3101	3102	3201	3202	3301	3304	4101	4102	4106	4201	4202	4203	4204	4301	4302	4303	5101	5102	5103	5105	5107	5109	5201	5301	5304	5401	5404	5501	5502	5504	5601	5602	5603	5604	5701	5702	5801	5802	5803	5804	6101	6102	6104	6106	6107	6108	6110	6112	6113	6115	6116	6117	6203	6205	6301	6303	6307	6308	6310	7101	7102	7103	7105	7107	7109	7201	7301	7302	7304	7401	7402	7403	7404	7405	7406	7407	7408	8000	8101	8102	8103	8105	8106	8107	8108	8109	8110	8111	8112	8201	8202	8203	8205	8206	8301	8303	8304	8305	8306	8309	8311	8312	8313	9000	9101	9102	9103	9105	9106	9107	9108	9109	9110	9111	9112	9115	9116	9118	9119	9120	9121	9201	9202	9203	9204	9205	9208	9210	9211	10000	10101	10102	10104	10105	10107	10108	10109	10201	10202	10205	10301	10302	10303	10403	11101	11201	11301	12000	12101	13000	13101	13102	13103	13104	13105	13106	13107	13108	13109	13110	13111	13112	13113	13114	13115	13116	13117	13118	13119	13120	13121	13122	13123	13124	13125	13126	13127	13128	13129	13130	13131	13132	13201	13203	13301	13302	13401	13402	13404	13501	13503	13504	13505	13601	13602	13603	13604	13605	14101	14103	14105	14106	14107	14108	14201	14202	14204	15000	15101	15102	15201	15202	16101	16102	16103	16106	16107	16108	16109	16207	16301	16302	16303
15101011001	1181	36	8	0	22	0	0	0	0	0	0	10	1	0	12	0	0	1	0	2	0	0	0	1	0	11	9	0	0	0	1	0	4	0	1	16	0	0	0	0	12	0	0	0	0	0	0	0	0	2	0	1	0	0	1	3	2	0	1	1	0	0	0	0	0	0	0	1	3	0	1	0	0	2	2	0	0	0	5	0	0	0	0	1	0	1	0	0	3	0	0	0	0	2	0	0	1	6	1	1	1	1	0	0	0	3	2	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	1	1	0	0	0	0	1	0	0	0	1	1	1	0	0	1	0	0	0	1	0	0	0	0	9	0	0	0	0	1	0	1	0	0	4	0	0	0	0	0	0	0	2	1	40	2	3	1	7	4	0	0	1	3	7	1	1	6	0	0	0	2	6	3	3	3	0	8	1	1	3	1	6	0	3	0	6	2	0	2	2	0	1	0	0	0	0	3	0	0	3	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0	2	0	0	0	1	0	0	0	0	0	0
15101011002	745	47	1	0	26	3	0	0	0	1	0	6	0	0	4	0	0	0	0	1	2	1	0	4	0	2	2	0	0	0	0	0	3	0	0	4	0	1	2	3	4	0	0	0	0	0	3	2	0	3	0	0	0	1	0	3	0	0	0	1	1	0	0	0	0	0	0	0	1	0	2	0	0	0	0	0	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	1	0	1	0	0	0	0	0	4	0	1	2	1	0	0	0	1	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	2	0	2	0	0	22	2	2	1	0	2	0	0	2	5	0	0	3	3	0	0	1	2	3	7	1	0	4	0	0	0	2	1	2	6	0	0	9	0	0	0	1	0	0	0	1	0	0	1	1	0	0	1	1	0	0	0	0	0	0	0	0	0	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0
15101021001	1708	60	12	3	30	4	2	0	0	0	2	25	0	0	28	1	1	2	0	8	0	0	0	3	1	9	5	2	1	1	2	0	7	0	1	21	0	2	0	0	7	2	1	0	1	0	1	4	2	11	1	3	1	5	0	2	2	2	1	12	0	1	0	0	3	1	0	0	0	1	3	1	0	3	4	1	1	3	18	0	0	1	1	3	3	2	1	2	16	1	0	3	2	3	2	0	0	18	10	1	0	3	1	4	1	5	3	2	1	2	3	1	0	18	2	0	5	4	0	0	0	0	0	16	0	1	0	0	1	1	2	0	1	2	1	1	1	1	4	0	4	3	1	1	0	2	0	0	1	11	1	0	0	1	1	2	2	4	1	17	0	1	1	3	6	1	0	5	1	142	12	2	4	5	2	2	2	3	12	6	6	5	28	1	3	5	2	66	5	0	11	7	7	6	3	3	3	4	2	2	1	27	0	3	0	22	1	6	2	0	0	1	1	1	0	4	0	13	0	0	2	0	1	1	1	0	2	0	0	1	0	20	5	0	1	1	0	1	1	4	0	1
15102012002	17	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	4	0	0	0	0	0	0	0	0	0	0	0	0
15102012003	354	15	2	0	2	1	0	1	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	167	0	3	0	0	0	1	0	0	0	0	0	0	0	0
15102022007	30	0	0	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0
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P12COMUNA: Comuna de de nacimiento

tabla_P12COMUNA <- table(x$clave, x$P12COMUNA, useNA = "no")
#write_xlsx(tabla_P12COMUNA, "tabla_P12COMUNA.xlsx")



a_008 <- head(tabla_P12COMUNA,50)

kbl(a_008) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

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15202032010	9	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202032014	2	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	0	0	0	0	0	1	0	1	1	0	2	0	1	1	1	1	0	0	0	1	3	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	2	0	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	1	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	1	0	1	0	1	0	0	0	0	1	0	0	0	1	0	0	1	0	0	1	1	1	0	1	0	0	0	0	0	0	0	1	0	1	0	0	0	1	1	1	0	0	0	0	0	2	0	0	0	1	1	0	1	0	0	0	0	0	0	0	0	0	0	0
15202032901	16	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202042013	22	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
15202042901	15	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

La geografía demográfica.

P10PAIS País de residencia habitual

P11PAIS País de residencia hace 5 años

P12PAIS País de nacimiento

P11 Residencia hace 5 años

P12 Lugar de nacimiento

P12A_LLEGADA Año de llegada al país

P12A_TRAMO Período de llegada al País

Educacion

p13: Asiste actualmente a la educacion formal?

P14 Curso o año más alto aprobado

P15 Nivel del curso más alto aprobado

P15A Completó el nivel especificado

Etnia

P16 Se considera perteneciente a un pueblo indígena u originario

P16A Pueblo indígena u originario listado

P16A_OTRO Pueblo indígena u originario (Otro)

Trabajo

P17 Trabajó durante la semana pasada

P18 Rama de actividad económica

Demografía

P19 Total hijos/as nacidos vivos

P20 Total hijos/as actualmente vivos

P21M Mes de nacimiento del último/a hijo/a

P21A Año de nacimiento del último/a hijo/a

Migración

P10PAIS_GRUPO País de residencia habitual (grupo)

P11PAIS_GRUPO País de residencia hace 5 años (grupo)

P12PAIS_GRUPO País de nacimiento (grupo)

Escolaridad

ESCOLARIDAD Años de escolaridad

Pueblo indígena

P16A_GRUPO Pueblo indígena u originario (grupo)

Códigos territoriales

REGION_15R Códigos regiones a 15 regiones

PROVINCIA_15R Códigos provincias a 15 regiones

COMUNA_15R Códigos comunas a 15 regiones

Parte III: Análisis por comuna

i Debemos simplemente seleccionar el codigo comunal correcto. No hay cabecera para el código, sólo nombre de fila.

Obtengamos la suma para el campo P10:

variable <- filter(x, x$COMUNA == 15202)
variable <- sum(variable$P10)
variable

## [1] 2168

Despleguemos los 5 primeros registros de la comuna 15202:

variable1 <- filter(x, x$COMUNA == 15202)
a_011 <- head(variable1,5)
kbl(a_011) %>%
  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

Crucemos con la relación de parentezco:

tabla_P07_15202 <- table(variable1$clave, variable1$P07)

kbl(tabla_P07_15202) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	1	2	4	5	6	7	8	11	12	13	14	15	16	17
15202012006	17	7	4	13	0	0	0	2	4	1	2	5	1	0
15202012008	7	3	0	2	0	0	0	0	0	0	0	0	0	0
15202012012	9	3	0	5	1	0	0	0	0	0	1	0	0	0
15202012015	59	8	6	29	0	3	0	3	3	0	11	18	1	28
15202022004	16	5	2	12	0	1	0	0	1	0	4	1	0	0
15202022005	8	2	0	4	0	0	1	0	0	0	0	0	0	0
15202022009	26	11	3	18	3	2	0	0	1	0	2	2	0	0
15202022011	12	3	2	7	0	0	0	0	9	0	3	0	0	51
15202022901	9	4	1	5	0	0	0	0	0	0	0	1	0	0
15202032001	8	1	1	6	0	0	0	0	0	0	1	0	0	5
15202032002	14	4	1	6	0	0	0	0	0	0	0	2	0	0
15202032010	8	1	0	4	0	0	0	0	1	0	1	0	0	0
15202032014	0	0	0	0	0	0	0	0	0	0	0	0	0	69
15202032901	10	5	0	1	0	0	0	0	0	0	0	0	0	0
15202042013	11	3	1	5	0	2	0	0	0	0	1	0	0	7
15202042901	6	1	0	1	1	2	0	0	2	0	2	0	1	0
15202992999	1	0	0	0	0	0	0	0	0	0	0	0	0	0