The code below generates a table containing date2
, category
and coefficient
. Besides, it has a daterange
that shows the period that a person want to see the generated table. The code works, but the problem I'm having is the following. If the viewing period is until 04/07, the coefficient values are correct, however if I want to see until 03/07, the coefficient value changes, but it couldn't change. Could you help me tweak this in the code?
library(shiny)
library(shinythemes)
library(dplyr)
library(writexl)
library(tidyverse)
library(lubridate)
function.test<-function(){
df1 <- structure(
list(date1= c("2021-06-28","2021-06-28","2021-06-28"),
date2 = c("2021-07-01","2021-07-02","2021-07-04"),
Category = c("ABC","ABC","ABC"),
Week= c("Wednesday","Wednesday","Wednesday"),
DR1 = c(4,1,0),
DR01 = c(4,1,0), DR02= c(4,2,0),DR03= c(9,5,0),
DR04 = c(5,4,0),DR05 = c(5,4,0),DR06 = c(5,4,0),DR07 = c(5,4,0),DR08 = c(5,4,0)),
class = "data.frame", row.names = c(NA, -3L))
return(df1)
}
return_coef <- function(df1, dmda, CategoryChosse) {
x<-df1 %>% select(starts_with("DR0"))
x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
med<-PV %>%
group_by(Category,Week) %>%
summarize(across(ends_with("PV"), median))
SPV<-df1%>%
inner_join(med, by = c('Category', 'Week')) %>%
mutate(across(matches("^DR0\\d $"), ~.x
get(paste0(cur_column(), '_PV')),
.names = '{col}_{col}_PV')) %>%
select(date1:Category, DR01_DR01_PV:last_col())
SPV<-data.frame(SPV)
mat1 <- df1 %>%
filter(date2 == dmda, Category == CategoryChosse) %>%
select(starts_with("DR0")) %>%
pivot_longer(cols = everything()) %>%
arrange(desc(row_number())) %>%
mutate(cs = cumsum(value)) %>%
filter(cs == 0) %>%
pull(name)
(dropnames <- paste0(mat1,"_",mat1, "_PV"))
SPV <- SPV %>%
filter(date2 == dmda, Category == CategoryChosse) %>%
select(-any_of(dropnames))
if(length(grep("DR0", names(SPV))) == 0) {
SPV[head(mat1,10)] <- NA_real_
}
datas <-SPV %>%
filter(date2 == ymd(dmda)) %>%
group_by(Category) %>%
summarize(across(starts_with("DR0"), sum)) %>%
pivot_longer(cols= -Category, names_pattern = "DR0(. )", values_to = "val") %>%
mutate(name = readr::parse_number(name))
colnames(datas)[-1]<-c("Days","Numbers")
datas <- datas %>%
group_by(Category) %>%
slice((as.Date(dmda) - min(as.Date(df1$date1) [
df1$Category == first(Category)])):max(Days) 1) %>%
ungroup
m<-df1 %>%
group_by(Category,Week) %>%
summarize(across(starts_with("DR1"), mean))
m<-subset(m, Week == df1$Week[match(ymd(dmda), ymd(df1$date2))] & Category == CategoryChosse)$DR1
if (nrow(datas)<=2){
return (as.numeric(m))
}
else if(any(table(datas$Numbers) >= 3) & length(unique(datas$Numbers)) == 1){
yz <- unique(datas$Numbers)
return(as.numeric(yz))
}
else{
mod <- nls(Numbers ~ b1*Days^2 b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
return(as.numeric(coef(mod)[2]))
}
}
ui <- fluidPage(
shiny::navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
br(),
tabPanel("",
sidebarLayout(
sidebarPanel(
uiOutput('daterange'),
br()
),
mainPanel(
dataTableOutput('table'),
br(), br(),
downloadButton("dl", "Download")
),
))
))
server <- function(input, output,session) {
data <- reactive(function.test())
data_subset <- reactive({
req(input$daterange1)
days <- seq(input$daterange1[1], input$daterange1[2], by = 'day')
df1 <- subset(data(), as.Date(date2) %in% days)
df2 <- df1 %>% select(date2,Category)
Test <- cbind(df2, coef = apply(df2, 1, function(x) {return_coef(df1,x[1],x[2])}))
Test
})
output$daterange <- renderUI({
dateRangeInput("daterange1", "Period you want to see:",
start = min(data()$date2),
end = max(data()$date2))
})
output$table <- renderDataTable({
data_subset()
})
output$dl <- downloadHandler(
filename = function() { "data.xlsx"},
content = function(file) {
writexl::write_xlsx(data_subset(), path = file)
}
)
}
shinyApp(ui = ui, server = server)
These values are correct if I view the table until 04/07.
If I change to 03/07, notice that the coefficients changed to 01/07 and 02/07
CodePudding user response:
Change this line
Test <- cbind(df2, coef = apply(df2, 1, function(x) {return_coef(df1,x[1],x[2])}))
to
Test <- cbind(df2, coef = apply(df2, 1, function(x) {return_coef(data(),x[1],x[2])}))