1 Introducción
<- switch(3,"C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/","C:/Users/chris/OneDrive/Documentos/archivos_grandes/","C:/Users/Ian/Documents/Casen/")
direccion
<<- readRDS(paste0(direccion,"casen_2006_c.rds"))
casen_2006 <- mutate_if(casen_2006, is.factor, as.character)
casen_2006 <<- readRDS(paste0(direccion,"casen_2009_c.rds"))
casen_2009 <- mutate_if(casen_2009, is.factor, as.character)
casen_2009 <<- readRDS(paste0(direccion,"casen_2011_c.rds"))
casen_2011 <- mutate_if(casen_2011, is.factor, as.character)
casen_2011 <<- readRDS(paste0(direccion,"casen_2013_c.rds"))
casen_2013 <- mutate_if(casen_2013, is.factor, as.character)
casen_2013 <<- readRDS(paste0(direccion,"casen_2015_c.rds"))
casen_2015 <- mutate_if(casen_2015, is.factor, as.character)
casen_2015 <<- readRDS(paste0(direccion,"casen_2017_c.rds"))
casen_2017 <- mutate_if(casen_2017, is.factor, as.character)
casen_2017 <<- readRDS(paste0(direccion,"casen_2020_e1.rds"))
casen_2020 <- mutate_if(casen_2020, is.factor, as.character) casen_2020
2 Categorías de respuesta
Obtenemos las frecuencias de respuestas ya expandidas a la población, por categoría. , include = FALSE
## # A tibble: 37 x 2
## Variable Homologacion_049
## <chr> <chr>
## 1 Educación básica (preparatoria) Educación Básica (preparatoria)
## 2 Educación Básica Educación Básica (preparatoria)
## 3 Preparatoria Educación Básica (preparatoria)
## 4 Primaria o Preparatoria (S. An~ Educación Básica (preparatoria)
## 5 Primaria o Preparatoria (siste~ Educación Básica (preparatoria)
## 6 Educación media CH-TP (humanid~ Educación Media Científico-Humanista o Técni~
## 7 Educ. media científico humanis~ Educación Media Científico-Humanista o Técni~
## 8 Educ. media técnica profesional Educación Media Científico-Humanista o Técni~
## 9 Educación Media Científico-Hum~ Educación Media Científico-Humanista o Técni~
## 10 Educación Media Técnica Profes~ Educación Media Científico-Humanista o Técni~
## # ... with 27 more rows
<- function(df){
diccionario
#entre 2006 y 2020: 7
<- switch(i,"T14A","T16PT","r5pn","r4pn","r10b","r12b","")
variable
names(carrera)[1] <- variable
<- merge(df, carrera, by = variable)
df
switch(i,
case = casen_2006 <<- df,
case = casen_2009 <<- df,
case = casen_2011 <<- df,
case = casen_2013 <<- df,
case = casen_2015 <<- df,
case = casen_2017 <<- df,
#case = casen_2020 <<- df
)
}
for (i in 1:6) {
switch(i,
case = casen <- casen_2006,
case = casen <- casen_2009,
case = casen <- casen_2011,
case = casen <- casen_2013,
case = casen <- casen_2015,
case = casen <- casen_2017
#case = casen <- casen_2020
)
diccionario(casen)
}
<- data.frame()
df_tablas
<- function(n){
funcion1
<-switch(n,"2006","2009","2011","2013" ,"2015","2017","")
xx
<<- xx
tanio
<- switch(n, "Homologacion_049","Homologacion_049","Homologacion_049","Homologacion_049","Homologacion_049","Homologacion_049")
v1
if(xx==2006) {
<- casen_2006
eliminated <- eliminated[,c(v1)]
c <- 2006
anio
}
if(xx==2009) {
<- casen_2009
eliminated <- eliminated[,c(v1)]
c <- 2009
anio
}
if(xx==2011) {
<- casen_2011
eliminated <- eliminated[,c(v1)]
c <- 2011
anio
}
if(xx==2013) {
<- casen_2013
eliminated <- eliminated[,c(v1)]
c <- 2013
anio
}
if(xx==2015) {
<- casen_2015
eliminated <- eliminated[,c(v1)]
c <- 2015
anio
}
if(xx==2017) {
<- casen_2017
eliminated <- eliminated[,c(v1)]
c <- 2017
anio
}
#if(xx==2020) {
#eliminated <- casen_2020
#c <- eliminated[,c(v1)]
#anio <- 2020
#}
################ -- frecuencia
<-switch(n, "EXPC","EXPC", "expc_full","expc", "expc_todas","expc", "expc")
expan<-xtabs(eliminated[,(expan)]~c, data = eliminated)
tabla_matp <- as.data.frame(tabla_matp)
tabla_matp names(tabla_matp)[1] <- "Homologación"
<<- tabla_matp
data_df1 ################
}
for (n in 1:6){
funcion1(n)
assign(paste0("tabla_",tanio),data_df1)
}
<- merge(tabla_2006, tabla_2009, by= "Homologación", all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2011, by= "Homologación", all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2013, by= "Homologación", all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2015, by= "Homologación", all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2017, by= "Homologación", all.x = T, all.y = T)
tabla_f #tabla_f <- merge(tabla_f, tabla_2020, by= "Homologación", all.x = T, all.y = T)
tabla_f
## Homologación Freq.x
## 1 Educación Básica (preparatoria) 2669686
## 2 Educación Media Científico-Humanista o Técnico-Profesional 1346810
## 3 Ninguno 1452847
## 4 No sabe o no responde 10064799
## 5 Profesional o universitaria 375722
## 6 Técnico Nivel Superior (carrera de 1 a 3 años) 242877
## 7 Educación Parvularia NA
## 8 Humanidades (sistema antiguo) NA
## 9 Técnica, Comercial, Industrial o Normalista (sistema antiguo) NA
## 10 Postgrado NA
## Freq.y Freq.x Freq.y Freq.x Freq.y
## 1 2748399 2925222 2925377 2959953 1631926
## 2 552588 685503 777582 762765 372268
## 3 1133340 991331 968310 987444 646310
## 4 10542802 10815018 10919452 10890464 13955656
## 5 411165 371996 415930 455281 327954
## 6 52549 113040 139094 153166 88102
## 7 300 NA NA NA NA
## 8 990447 884603 877859 1025472 608396
## 9 175461 126595 197296 258298 121653
## 10 NA 10440 14397 22731 16901
colnames(tabla_f) <- c("variable", "2006","2009","2011","2013","2015","2017")
<- mutate_all(tabla_f, ~replace(., is.na(.), 0))
tabla_f
<- tabla_f
tabla_t $a2007 <- NA
tabla_t$a2008 <- NA
tabla_t$a2010 <- NA
tabla_t$a2012 <- NA
tabla_t$a2014 <- NA
tabla_t$a2016 <- NA
tabla_t#tabla_t$a2018 <- NA
#tabla_t$a2019 <- NA
<- tabla_t[,c("variable","2006","a2007","a2008","2009","a2010","2011","a2012","2013","a2014","2015","a2016","2017")]
tabla_t <- data.frame()
receptaculo for (n in 1:nrow(tabla_t)) {
<- na.approx(c(tabla_t[n,c(2:ncol(tabla_t))]))
calculado <- rbind(receptaculo,calculado)
receptaculo
}<- cbind(tabla_t$variable,receptaculo)
receptaculo colnames(receptaculo) <- c("Homologación",paste0(seq(2006,2017,1)))
# receptaculo$categorias<- as.character(receptaculo$categorias)
################
<- sapply(receptaculo, is.numeric)
is.num <- lapply(receptaculo [is.num], round, 2) receptaculo [is.num]
datatable(receptaculo, extensions = 'Buttons', escape = FALSE, rownames = TRUE,
options = list(dom = 'Bfrtip',
buttons = list('colvis', list(extend = 'collection',
buttons = list(
list(extend='copy'),
list(extend='excel',
filename = 'tabla_genero'),
list(extend='pdf',
filename= 'tabla_genero')),
text = 'Download')), scrollX = TRUE))%>%
formatRound(columns=c(paste0(seq(2006,2017,1))) ,mark = "", digits=0)
3 Análisis