Casen 2006:2020

Tabla 048

Si le ofrecieran un trabajo, ¿estaría disponible para comenzar a trabajar?

VE-CC

DataIntelligence
date:11-10-2021

1 Introducción

direccion <- 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/")

casen_2006 <<- readRDS(paste0(direccion,"casen_2006_c.rds"))
casen_2006 <- mutate_if(casen_2006, is.factor, as.character)
casen_2009 <<- readRDS(paste0(direccion,"casen_2009_c.rds"))
casen_2009 <- mutate_if(casen_2009, is.factor, as.character)
casen_2011 <<- readRDS(paste0(direccion,"casen_2011_c.rds"))
casen_2011 <- mutate_if(casen_2011, is.factor, as.character)
casen_2013 <<- readRDS(paste0(direccion,"casen_2013_c.rds"))
casen_2013 <- mutate_if(casen_2013, is.factor, as.character)
casen_2015 <<- readRDS(paste0(direccion,"casen_2015_c.rds"))
casen_2015 <- mutate_if(casen_2015, is.factor, as.character)
casen_2017 <<- readRDS(paste0(direccion,"casen_2017_c.rds"))
casen_2017 <- mutate_if(casen_2017, is.factor, as.character)
casen_2020 <<- readRDS(paste0(direccion,"casen_2020_e1.rds"))
casen_2020 <- mutate_if(casen_2020, is.factor, as.character)

2 Categorías de respuesta

Obtenemos las frecuencias de respuestas ya expandidas a la población, por categoría. , include = FALSE

## # A tibble: 8 x 2
##   Variable                  Homologacion_048         
##   <chr>                     <chr>                    
## 1 No                        No                       
## 2 <NA>                      No sabe o no responde    
## 3 NS/NR                     No sabe o no responde    
## 4 Sin dato                  No sabe o no responde    
## 5 No sabe/no responde       No sabe o no responde    
## 6 Si, ahora mismo           Sí, ahora mismo          
## 7 Sí, ahora mismo           Sí, ahora mismo          
## 8 Sí, en otra época del año Sí, en otra época del año
diccionario <- function(df){
    
    #entre 2006 y 2020: 7
    
  variable <- switch(i,"O5","O5","o5","o5","o5","o5","")
  
 names(carrera)[1] <- variable
  
  df <- merge(df, carrera, by = variable)
  
    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)
  
}
df_tablas <- data.frame()

funcion1 <- function(n){

    xx<-switch(n,"2006","2009","2011","2013" ,"2015","2017","")
 
    tanio <<- xx

    v1 <- switch(n, "Homologacion_048","Homologacion_048", "Homologacion_048","Homologacion_048", "Homologacion_048","Homologacion_048")

if(xx==2006) {
eliminated <- casen_2006 
c <- eliminated[,c(v1)]
anio <- 2006
}    
    
if(xx==2009) {
eliminated <- casen_2009 
c <- eliminated[,c(v1)]
anio <- 2009
}

if(xx==2011) {
eliminated <- casen_2011  
c <- eliminated[,c(v1)]
anio <- 2011
}
 
if(xx==2013) {
eliminated <- casen_2013  
c <- eliminated[,c(v1)]
anio <- 2013
}    
    
if(xx==2015) {
eliminated <- casen_2015 
c <- eliminated[,c(v1)]
anio <- 2015
}

if(xx==2017) {
eliminated <- casen_2017  
c <- eliminated[,c(v1)]
anio <- 2017
}
 

#if(xx==2020) {
#eliminated <- casen_2020
#c <- eliminated[,c(v1)]
#anio <- 2020
#}
     
################ -- frecuencia
expan<-switch(n, "EXPC","EXPC", "expc_full","expc", "expc_todas","expc", "expc")
tabla_matp <-xtabs(eliminated[,(expan)]~c, data = eliminated)
tabla_matp <- as.data.frame(tabla_matp) 
names(tabla_matp)[1] <- "Homologación"
data_df1 <<- tabla_matp
################ 

}

for (n in 1:6){
  
  funcion1(n) 
  assign(paste0("tabla_",tanio),data_df1)

}

tabla_f <- 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 <- merge(tabla_f, tabla_2020, by= "Homologación",  all.x = T, all.y = T)
tabla_f
##                Homologación  Freq.x   Freq.y  Freq.x   Freq.y   Freq.x   Freq.y
## 1                        No 4815877  5605177 4444459  4942248  4659822  4205448
## 2     No sabe o no responde 9979508 10037863 9713828 10094321 10342100 11245211
## 3           Sí, ahora mismo  447810   480141 1221714  1064983  1181688  1192177
## 4 Sí, en otra época del año  909546   483870 1543747  1133745  1331964  1126330
colnames(tabla_f) <- c("variable", "2006","2009","2011","2013","2015","2017")
 
tabla_f <- mutate_all(tabla_f, ~replace(., is.na(.), 0))

tabla_t <- 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$a2018 <- NA
#tabla_t$a2019 <- NA
 
tabla_t <- tabla_t[,c("variable","2006","a2007","a2008","2009","a2010","2011","a2012","2013","a2014","2015","a2016","2017")]
receptaculo <- data.frame()
for (n in 1:nrow(tabla_t)) {
  calculado <- na.approx(c(tabla_t[n,c(2:ncol(tabla_t))]))
  receptaculo <- rbind(receptaculo,calculado)
}
receptaculo <- cbind(tabla_t$variable,receptaculo)
colnames(receptaculo) <- c("Homologación",paste0(seq(2006,2017,1)))
# receptaculo$categorias<- as.character(receptaculo$categorias)
################
is.num <- sapply(receptaculo, is.numeric)
receptaculo [is.num] <- lapply(receptaculo [is.num], round, 2)
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