Casen 2006:2020

Tabla 041

¿Cuántas Consultas de Medicina General recibió?

VE-CC

DataIntelligence
date:11-10-2021

1 Introduccion

direccion <- switch(2,"C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/","C:/Users/chris/OneDrive/Documentos/archivos_grandes/")

dataset_06 <<- readRDS(paste0(direccion,"casen_2006_c.rds"))
dataset_06 <- mutate_if(dataset_06, is.factor, as.character)
dataset_09 <<- readRDS(paste0(direccion,"casen_2009_c.rds"))
dataset_09 <- mutate_if(dataset_09, is.factor, as.character)
dataset_11 <<- readRDS(paste0(direccion,"casen_2011_c.rds"))
dataset_11 <- mutate_if(dataset_11, is.factor, as.character)
dataset_13 <<- readRDS(paste0(direccion,"casen_2013_c.rds"))
dataset_13 <- mutate_if(dataset_13, is.factor, as.character)
dataset_15 <<- readRDS(paste0(direccion,"casen_2015_c.rds"))
dataset_15 <- mutate_if(dataset_15, is.factor, as.character)
dataset_17 <<- readRDS(paste0(direccion,"casen_2017_c.rds"))
dataset_17 <- mutate_if(dataset_17, is.factor, as.character)
dataset_20 <<- readRDS(paste0(direccion,"casen_2020_e1.rds"))
dataset_20 <- mutate_if(dataset_20, is.factor, as.character)
casen_2006 <- dataset_06
casen_2009 <- dataset_09
casen_2011 <- dataset_11
casen_2013 <- dataset_13
casen_2015 <- dataset_15
casen_2017 <- dataset_17
casen_2020 <- dataset_20

2 Categorías de respuesta

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

## # A tibble: 54 x 2
##    Variable Homologacion_041
##    <chr>    <chr>           
##  1 1        De 1 a 5        
##  2 3        De 1 a 5        
##  3 5        De 1 a 5        
##  4 2        De 1 a 5        
##  5 4        De 1 a 5        
##  6 12       De 11 a 20      
##  7 20       De 11 a 20      
##  8 15       De 11 a 20      
##  9 11       De 11 a 20      
## 10 14       De 11 a 20      
## # ... with 44 more rows

La base de datos necesaria

diccionario <- function(df){
    
    #entre 2006 y 2020: 7
    
#                      2006  2009   2011   2013 2015   2017 2020
  variable <- switch(i,"S8A","S14A","s25a","s22a","s19a","s19a","")
  
 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","2020")
 
    tanio <<- xx

    v1 <- switch(n, "Homologacion_041","Homologacion_041", "Homologacion_041","Homologacion_041", "Homologacion_041","Homologacion_041", "Homologacion_041")

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
################ 
#print(data_df1)
}

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
##            Homologación   Freq.x   Freq.y   Freq.x   Freq.y   Freq.x   Freq.y
## 1              De 1 a 5  2546022  2170843  2845289  2814456  3055148  2540924
## 2            De 11 a 20    25544    16918    18931    17230    16992    17113
## 3            De 21 a 30      618      361     1582     5602     1583     3242
## 4            De 31 a 40      475       NA       NA      499      771     5181
## 5            De 41 a 50      177       NA       NA      162      173     1697
## 6             De 6 a 10   119549    72154    92993    83103    89267    70185
## 7             Más de 50      168       NA       NA       NA       NA       NA
## 8               Ninguna 13460188 14342589 13964837 14310178 14340595 15070502
## 9 No sabe o no responde       NA     4186      116     4067    11045    60322
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 = 'recibio_atencion'),
          list(extend='pdf',
            filename= 'recibio_atencion')),
          text = 'Download')), scrollX = TRUE))%>%
    formatRound(columns=c(paste0(seq(2006,2017,1))) ,mark = "", digits=2)

3 Análisis