Parcial
rm(list=ls())
library(xtable)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
ruta<-"D:/Dropbox/SantoTomas/20161/Estadística Exploratoria/CorteIII/Parcial III"
setwd(ruta)
load(file = "BDsParcialFinal.RData")
attach(Personas)
attach(Vivienda)
## The following objects are masked from Personas:
##
## AREA, DIRECTORIO, DPTO, fex_c_2011, HOGAR, MES, ORDEN, REGIS,
## SECUENCIA_P
# Punto 1
tabla1<-prop.table(table(P6050,P6100),1)*100
print.xtable(xtable(tabla1),type = "html",comment = F)
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|
Contributivo (EPS)?
|
Especial ? (Fuerzas Armadas, Ecopetrol, universidades públic
|
Subsidiado? (EPS-S)
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No sabe, no informa
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|
Jefe (a) del hogar
|
56.68
|
5.76
|
37.51
|
0.06
|
|
Pareja, esposo(a), cónyuge, compañero(a)
|
57.40
|
5.35
|
37.25
|
0.00
|
|
Hijo(a), hijastro(a)
|
48.38
|
4.04
|
47.55
|
0.04
|
|
Nieto(a)
|
41.50
|
2.99
|
55.49
|
0.02
|
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Otro pariente
|
42.44
|
2.87
|
54.48
|
0.21
|
|
Empleado(a) del servicio doméstico y sus parientes
|
28.73
|
0.00
|
71.27
|
0.00
|
|
Pensionista
|
65.08
|
3.17
|
31.75
|
0.00
|
|
Trabajador
|
42.86
|
0.00
|
57.14
|
0.00
|
|
Otro no pariente
|
40.15
|
4.13
|
55.72
|
0.00
|
# Punto 2
P6008rec<-P6008
P6008rec<-replace(P6008rec,P6008rec %in% 5:20,5)
tabla2<-prop.table(table(P6008rec,P4030S1A1),1)*100
print.xtable(xtable(tabla2),type = "html",comment = F)
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Conexión Pirata
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Bajo - Bajo
|
Bajo
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Medio - Bajo
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Medio
|
Medio - Alto
|
Alto
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No sabe o cuenta con planta eléctrica
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|
1
|
0.34
|
23.24
|
33.81
|
28.78
|
9.94
|
2.57
|
0.97
|
0.34
|
|
2
|
0.25
|
22.84
|
34.57
|
27.60
|
10.37
|
2.91
|
1.47
|
0.00
|
|
3
|
0.28
|
24.70
|
37.84
|
27.04
|
7.26
|
1.98
|
0.83
|
0.08
|
|
4
|
0.39
|
29.12
|
37.60
|
24.48
|
6.57
|
1.38
|
0.47
|
0.00
|
|
5
|
0.72
|
38.69
|
35.10
|
20.15
|
3.99
|
0.91
|
0.33
|
0.12
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# Punto 3
detach(Personas)
detach(Vivienda)
Base<-full_join(Vivienda,Personas,by=c("DIRECTORIO","SECUENCIA_P","ORDEN"))
db3<-Base[Base$P6220 %in% c("Universitario","Postgrado") & Base$P5210S16=="Sí",]
aggregate(formula = P5210S16~P6220,data = db3,FUN = "length")
## P6220 P5210S16
## 1 Universitario 1081
## 2 Postgrado 594
# Punto 4
db4<-subset(Base, subset = Base$P5090=="Propia, la están pagando")
aggregate(formula = P6040~P6020,data = db4,FUN = "mean")
## P6020 P6040
## 1 Hombre 46.35729
## 2 Mujer 48.19392