casen_2006 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2006_c.rds")
casen_2006 <- mutate_if(casen_2006, is.factor, as.character)
casen_2009 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2009_c.rds")
casen_2009 <- mutate_if(casen_2009, is.factor, as.character)
casen_2011 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2011_c.rds")
casen_2011 <- mutate_if(casen_2011, is.factor, as.character)
casen_2013 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2013_c.rds")
casen_2013 <- mutate_if(casen_2013, is.factor, as.character)
casen_2015 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2015_c.rds")
casen_2015 <- mutate_if(casen_2015, is.factor, as.character)
casen_2017 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2017_c.rds")
casen_2017 <- mutate_if(casen_2017, is.factor, as.character)
casen_2020 <- readRDS(file = "C:/Users/enamo/Desktop/Shiny-R/Casen_en_pandemia_2020/casen/casen_2020_c.rds")
casen_2020 <- mutate_if(casen_2020, is.factor, as.character)carrera <- read_xlsx("C:/Users/enamo/Desktop/Shiny-R/ttcc_zoho/diccionarios/1/tabla 1.3.xlsx")
carrera <- carrera[,c(1,3)]
names(carrera)[2] <- "Homologacion"
diccionario <- function(df){
variable <- switch(i,"s9","s7","s6","s6")
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
)
}
for (i in 1:4) {
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)
}0.1 Interpolación
df_tablas <- data.frame()
funcion1 <- function(n){
xx<-switch(n,"2011","2013","2015","2017")
tanio <<- xx
v1 <- switch(n,"Homologacion","Homologacion","Homologacion","Homologacion")
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
}
################ -- frecuencia
expan<-switch(n,"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] <- "categorias"
data_df1 <<- tabla_matp
################
}
for (n in 1:4){
funcion1(n)
assign(paste0("tabla_",tanio),data_df1)
}
tabla_f <- merge(tabla_2011, tabla_2013, by= "categorias", all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2015, by= "categorias", all.x = T, all.y = T)
tabla_f <- merge(tabla_f, tabla_2017, by= "categorias", all.x = T, all.y = T)
colnames(tabla_f) <- c("Variable","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", "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("categorias",paste0(seq(2011,2017,1)))
################
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'),
list(extend='pdf',
filename= 'tabla')),
text = 'Download')), scrollX = TRUE))%>%
formatRound(columns=c(paste0(seq(2011,2017,1))) ,mark = "", digits=0)