I'm having doubts about a filter I made. Note that I inserted in the function Test %>% filter(Filt != 0), in this case the ABC category was not supposed to appear. However, if you test the shiny code below, you will see the ABC option appear. See the image below. What am I doing wrong?
library(shiny)
library(shinythemes)
library(dplyr)
library(tidyverse)
library(lubridate)
df1<- structure(
list(date1= c("2021-06-28","2021-06-28"),
date2 = c("2021-07-01","2021-07-01"),
Category = c("FDE","ABC"),
Week= c("Friday","Monday"),
Filt= c("1","0"),
DR1 = c(14,11),
DR01 = c(14,12), DR02= c(14,12),DR03= c(19,15),
DR04 = c(15,14),DR05 = c(15,14),
DR06 = c(12,14)),
class = "data.frame", row.names = c(NA, -2L))
f1 <- function(df1, dmda, CategoryChosse, var1, var2, gnum=0) {
df1 %>% filter(Filt != 0)
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) %>%
dplyr::summarize(across(ends_with("PV"), median))
SPV<-df1%>%
inner_join(med, by = c('Category', 'Week')) %>%
mutate(across(matches("^DR0\\d $"), ~.x
get(paste0(cur_column(), '_PV')),
.names = '{col}_{col}_PV')) %>%
dplyr::select(date1:Category, DR01_DR01_PV:last_col())
SPV<-data.frame(SPV)
mat1 <- df1 %>%
filter(date2 == dmda, Category == CategoryChosse) %>%
dplyr::select(starts_with("DR0")) %>%
pivot_longer(cols = everything()) %>%
arrange(desc(row_number())) %>%
mutate(cs = cumsum(value)) %>%
dplyr::filter(cs == 0) %>%
pull(name)
(dropnames <- paste0(mat1,"_",mat1, "_PV"))
datas<-SPV %>%
filter(date2 == ymd(dmda)) %>%
group_by(Category) %>%
dplyr::summarize(across(starts_with("DR0"), sum)) %>%
pivot_longer(cols= -Category, names_pattern = "DR0(. )", values_to = "val") %>%
mutate(name = readr::parse_number(name))
colnames(datas)[-1]<-c(var1,var2)
datas$days <- datas[[as.name(var1)]]
datas$numbers <- datas[[as.name(var2)]]
if(as.Date(dmda) < min(as.Date(df1$date1))){
datas <- datas %>%
group_by(Category) %>%
slice(1:max(days) 1) %>%
ungroup
}else{
datas <- datas %>%
group_by(Category) %>%
slice((as.Date(dmda) - min(as.Date(df1$date1) [
df1$Category == first(Category)])):max(days) 1) %>%
ungroup
}
maxrange <- range(0, datas$numbers, na.rm = TRUE)
maxrange[2] <- maxrange[2] 10
if (gnum) maxrange[2] <- maxrange[2] 40
max<-max(0, datas$days, na.rm = TRUE) 1
limx = c(0,max)
limy = c(0,maxrange[2])
plot(numbers ~ days, xlim= limx, ylim= limy, xlab = var1, ylab=var2,
xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
model <- nls(numbers ~ b1*days^2 b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
new.data <- data.frame(days = with(datas, seq(min(days),max(days),len = 45)))
new.data <- rbind(0, new.data)
lines(new.data$days,predict(model,newdata = new.data),lwd=2)
coef_val<-coef(model)[2]
points(0, coef_val, col="red",pch=19,cex = 2,xpd=TRUE)
}
ui <- fluidPage(
ui <- shiny::navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
br(),
tabPanel("",
sidebarLayout(
sidebarPanel(
uiOutput("date"),
uiOutput("mycode"),
),
mainPanel(
tabsetPanel(
tabPanel("Graph1", plotOutput("graph",width = "100%", height = "600"))
)
)
))))
server <- function(input, output,session) {
data <- reactive(df1)
output$date <- renderUI({
req(data())
all_dates <- seq(as.Date('2021-01-01'), as.Date('2021-01-15'), by = "day")
disabled <- as.Date(setdiff(all_dates, as.Date(data()$date2)), origin = "1970-01-01")
dateInput(input = "date2",
label = h4("Data"),
min = min(data()$date2),
max = max(data()$date2),
value = min(data()$date2))
})
output$mycode <- renderUI({
req(input$date2)
df1 <- data()
df2 <- df1[as.Date(df1$date2) %in% input$date2,]
selectInput("code", label = h4("Category"),choices=unique(df2$Category))
})
output$graph <- renderPlot({
req(input$date2,input$code)
var1 = "Days"
var2 = "Numbers"
f1(data(),as.character(input$date2),as.character(input$code),var1,var2)
})
}
shinyApp(ui = ui, server = server)
CodePudding user response：
Based on the updated code, the 'df1' passed to get the unique values of 'Category' is the original data
output$mycode <- renderUI({
req(input$date2)
df1 <- data()
df2 <- df1[as.Date(df1$date2) %in% input$date2,]
selectInput("code", label = h4("Category"),choices=unique(df2$Category))
})
instead, it would be
output$mycode <- renderUI({
req(input$date2)
df1 <- data() %>%
filter(Filt != 0)
df2 <- df1[as.Date(df1$date2) %in% input$date2,]
selectInput("code", label = h4("Category"),choices=unique(df2$Category))
})
-full code
f1 <- function(df1, dmda, CategoryChosse, var1, var2, gnum=0) {
df1 <- df1 %>% filter(Filt != 0) # updated the 'df1'
x<-df1 %>% dplyr::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) %>%
dplyr::summarize(across(ends_with("PV"), median))
SPV<-df1%>%
inner_join(med, by = c('Category', 'Week')) %>%
mutate(across(matches("^DR0\\d $"), ~.x
get(paste0(cur_column(), '_PV')),
.names = '{col}_{col}_PV')) %>%
dplyr::select(date1:Category, DR01_DR01_PV:last_col())
SPV<-data.frame(SPV)
mat1 <- df1 %>%
filter(date2 == dmda, Category == CategoryChosse) %>%
dplyr::select(starts_with("DR0")) %>%
pivot_longer(cols = everything()) %>%
arrange(desc(row_number())) %>%
mutate(cs = cumsum(value)) %>%
dplyr::filter(cs == 0) %>%
pull(name)
(dropnames <- paste0(mat1,"_",mat1, "_PV"))
datas<-SPV %>%
filter(date2 == ymd(dmda)) %>%
group_by(Category) %>%
dplyr::summarize(across(starts_with("DR0"), sum)) %>%
pivot_longer(cols= -Category, names_pattern = "DR0(. )", values_to = "val") %>%
mutate(name = readr::parse_number(name))
colnames(datas)[-1]<-c(var1,var2)
datas$days <- datas[[as.name(var1)]]
datas$numbers <- datas[[as.name(var2)]]
if(as.Date(dmda) < min(as.Date(df1$date1))){
datas <- datas %>%
group_by(Category) %>%
slice(1:max(days) 1) %>%
ungroup
}else{
datas <- datas %>%
group_by(Category) %>%
slice((as.Date(dmda) - min(as.Date(df1$date1) [
df1$Category == first(Category)])):max(days) 1) %>%
ungroup
}
maxrange <- range(0, datas$numbers, na.rm = TRUE)
maxrange[2] <- maxrange[2] 10
if (gnum) maxrange[2] <- maxrange[2] 40
max<-max(0, datas$days, na.rm = TRUE) 1
limx = c(0,max)
limy = c(0,maxrange[2])
plot(numbers ~ days, xlim= limx, ylim= limy, xlab = var1, ylab=var2,
xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
model <- nls(numbers ~ b1*days^2 b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
new.data <- data.frame(days = with(datas, seq(min(days),max(days),len = 45)))
new.data <- rbind(0, new.data)
lines(new.data$days,predict(model,newdata = new.data),lwd=2)
coef_val<-coef(model)[2]
points(0, coef_val, col="red",pch=19,cex = 2,xpd=TRUE)
}
ui <- fluidPage(
shiny::navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
br(),
tabPanel("",
sidebarLayout(
sidebarPanel(
uiOutput("date"),
uiOutput("mycode"),
),
mainPanel(
tabsetPanel(
tabPanel("Graph1", plotOutput("graph",width = "100%", height = "600"))
)
)
))))
server <- function(input, output,session) {
data <- reactive(df1)
output$date <- renderUI({
req(data())
all_dates <- seq(as.Date('2021-01-01'), as.Date('2021-01-15'), by = "day")
disabled <- as.Date(setdiff(all_dates, as.Date(data()$date2)), origin = "1970-01-01")
dateInput(input = "date2",
label = h4("Data"),
min = min(data()$date2),
max = max(data()$date2),
value = min(data()$date2))
})
output$mycode <- renderUI({
req(input$date2)
df1 <- data() %>%
filter(Filt != 0)
df2 <- df1[as.Date(df1$date2) %in% input$date2,]
selectInput("code", label = h4("Category"),choices=unique(df2$Category))
})
output$graph <- renderPlot({
req(input$date2,input$code)
var1 = "Days"
var2 = "Numbers"
f1(data(),as.character(input$date2),as.character(input$code),var1,var2)
})
}
shinyApp(ui = ui, server = server)
-output
