Why does the Shiny-app not react to user input - r

Question

I am trying to build a web app in shiny that would allow for different user input and then plot graphs/output data tables accordingly. I am using WHO's data about suicide rates and there are two possible types of graphs: bar plot and line graph.
The user is given a choice between plotting the graph in which the x axis is either the age group (barplot) or year (line graph). They are also given the choice of plotting the graph separately for males and females and different countries as well.
The code below works fine for everything except when the user chooses x axis = year with gender = 'gender neutral'. The error says that the object rate is not found. However, the block of code which includes the object rate works perfectly fine in other places.
library(shiny)
library(dplyr)
library(ggplot2)
setwd("C:\\Users\\Lenovoi7\\Shrewsbury School\\IT\\Coursework")
who<-data.frame(read.csv("who.csv", stringsAsFactors = TRUE))
dput(head(who))
countries<-sort(unique(who$country))
countries<-union(countries, c("World"))
ui<-fluidPage(
titlePanel("Suicide statistics"),
sidebarLayout(
sidebarPanel(
selectInput(
inputId="x",
label="Please choose the x variable",
choices=c("",
"Age group"="age",
"Year"="year")),
conditionalPanel(
condition = "input.x == 'age' || input.x == 'year'",
selectInput(
inputId = "gender",
label = "Please specify the gender characteristics",
choices = c("", "Gender neutral" = "gender_neutral",
"Gender specific" = "gender_specific"),
selected = NULL),
#nested conditional panel
#only show this panel if the input is gender_specific
conditionalPanel(
condition = "input.gender == 'gender_specific'",
selectInput(
inputId = "country",
label = "Select a country:",
choices = countries,
selected = "Bosnia and Herzegovina")),
conditionalPanel(
condition = "input.gender == 'gender_neutral'",
selectInput(
inputId = "country",
label = "Select a country:",
choices = countries,
selected = "Bosnia and Herzegovina")))),
mainPanel(
plotOutput("graph")
)))
server <- function(input, output) {
x<-reactive({input$x})
gender<-reactive({input$gender})
country<-reactive({input$country})
output$graph <- renderPlot(
#x axis = age group
if (x()=="age"){
if (gender()=="gender_neutral"){
if (country()=="World"){
ggplot(data=who, aes(x=age)) + geom_bar(aes(weights=suicides_no), position="dodge")}
else {
#create a new subset of data that will be used??
who_subset<-subset(who, country == input$country)
ggplot(data=who_subset, aes(x=age)) + geom_bar(aes(weights=suicides_no))}}
else if (gender()=="gender_specific"){
if (country()=="World"){
ggplot(data=who, aes(x=age)) + geom_bar(aes(weights=suicides_no, fill=sex), position="dodge")}
else {
#create a new subset of data that will be used??
who_subset<-subset(who, country==input$country)
ggplot(data=who_subset, aes(x=age)) + geom_bar(aes(weights=suicides_no, fill=sex), position="dodge")}}}
else if (x()=="year"){
if (gender()=="gender_neutral"){
if (country()=="World"){
who_all <- who %>%
group_by(year) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no/population)
ggplot() +
geom_line(data = who_all, aes(year, rate))
}
else {
who_subset<-subset(who, country==input$country)
who_sub_sex <- who_subset %>%
group_by(year) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no/population)
ggplot() +
geom_line(data = who_subset, aes(year, rate))
}}
else if (gender()=="gender_specific"){
if (country()=="World"){
who_all <- who %>%
group_by(year) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no/population)
ggplot() +
geom_line(data = who_all, aes(year, rate))
}
else {
#create a new subset of data that will be used??
who_subset<-subset(who, country==input$country)
who_sub_sex <- who_subset %>%
group_by(year, sex) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no / population)
ggplot() +
geom_line(data = who_sub_sex, aes(year, rate, color = sex))}
}
}
)}
# Create a Shiny app object
shinyApp(ui = ui, server = server)
dput(head(who))
structure(list(country = structure(c(1L, 1L, 1L, 1L, 1L, 1L),
.Label = c("Albania",
"Anguilla", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba",
"Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Barbados",
"Belarus", "Belgium", "Belize", "Bermuda", "Bolivia",
"Bosnia and Herzegovina",
"Brazil", "British Virgin Islands", "Brunei Darussalam", "Bulgaria",
"Cabo Verde", "Canada", "Cayman Islands", "Chile", "Colombia",
"Costa Rica", "Croatia", "Cuba", "Cyprus", "Czech Republic",
"Denmark", "Dominica", "Dominican Republic", "Ecuador", "Egypt",
"El Salvador", "Estonia", "Falkland Islands (Malvinas)", "Fiji",
"Finland", "France", "French Guiana", "Georgia", "Germany", "Greece",
"Grenada", "Guadeloupe", "Guatemala", "Guyana", "Haiti", "Honduras",
"Hong Kong SAR", "Hungary", "Iceland", "Iran (Islamic Rep of)",
"Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan",
"Kazakhstan", "Kiribati", "Kuwait", "Kyrgyzstan", "Latvia", "Lithuania",
"Luxembourg", "Macau", "Malaysia", "Maldives", "Malta", "Martinique",
"Mauritius", "Mayotte", "Mexico", "Monaco", "Mongolia", "Montenegro",
"Montserrat", "Morocco", "Netherlands", "Netherlands Antilles",
"New Zealand", "Nicaragua", "Norway", "Occupied Palestinian Territory",
"Oman", "Panama", "Paraguay", "Peru", "Philippines", "Poland",
"Portugal", "Puerto Rico", "Qatar", "Republic of Korea",
"Republic of Moldova",
"Reunion", "Rodrigues", "Romania", "Russian Federation",
"Saint Kitts and Nevis",
"Saint Lucia", "Saint Pierre and Miquelon",
"Saint Vincent and Grenadines",
"San Marino", "Sao Tome and Principe", "Saudi Arabia", "Serbia",
"Seychelles", "Singapore", "Slovakia", "Slovenia", "South Africa",
"Spain", "Sri Lanka", "Suriname", "Sweden", "Switzerland",
"Syrian Arab Republic",
"Tajikistan", "TFYR Macedonia", "Thailand", "Trinidad and Tobago",
"Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands",
"Ukraine", "United Arab Emirates", "United Kingdom",
"United States of America",
"Uruguay", "Uzbekistan", "Venezuela (Bolivarian Republic of)",
"Virgin Islands (USA)", "Zimbabwe"), class = "factor"),
year = c(1985L, 1985L, 1985L, 1985L, 1985L, 1985L),
sex = structure(c(1L, 1L, 1L, 1L, 1L, 1L),.
Label = c("female", "male"), class = "factor"),
age = structure(1:6, .Label = c("15-24 years", "25-34 years",
"35-54 years", "5-14 years", "55-74 years", "75+ years"),
class = "factor"),
suicides_no = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_,
NA_integer_, NA_integer_), population = c(277900L, 246800L,
267500L, 298300L, 138700L, 34200L)),
row.names = c(NA, 6L), class = "data.frame")
Is there any chance somebody knows a way out of this problem? Again I want the web app to output line graph when the user chooses x axis = year and gender = gender_neutral.

Answer 1

Try out with this server code.
The changes are already described in my comments. Since I dont have the who data.frame I could not test it.
server <- function(input, output) {
output$graph <- renderPlot({
if (input$x == "age") {
if (input$gender=="gender_neutral"){
if (input$country=="World"){
ggplot(data = who, aes(x = age)) + geom_bar(aes(weights = suicides_no), position="dodge")}
else {
#create a new subset of data that will be used??
who_subset <- subset(who, country == input$country)
ggplot(data=who_subset, aes(x=age)) + geom_bar(aes(weights=suicides_no))
}
} else if (input$gender=="gender_specific") {
if (input$country=="World"){
ggplot(data=who, aes(x=age)) + geom_bar(aes(weights=suicides_no, fill=sex), position="dodge")}
else {
#create a new subset of data that will be used??
who_subset <- subset(who, country==input$country)
ggplot(data = who_subset, aes(x=age)) + geom_bar(aes(weights=suicides_no, fill=sex), position="dodge")
}
}
} else if (input$x=="year"){
if (input$gender=="gender_neutral"){
if (input$country=="World"){
who_all <- who %>%
group_by(year) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no/population)
ggplot() +
geom_line(data = who_all, aes(year, rate))
} else {
who_subset <- subset(who, country==input$country)
who_sub_sex <- who_subset %>%
group_by(year) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no/population)
ggplot() +
geom_line(data = who_sub_sex, aes(year, rate))
}
} else if (input$gender=="gender_specific"){
if (input$country=="World"){
who_all <- who %>%
group_by(year) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no/population)
ggplot() +
geom_line(data = who_all, aes(year, rate))
} else {
#create a new subset of data that will be used??
who_subset <- subset(who, country==input$country)
who_sub_sex <- who_subset %>%
group_by(year, sex) %>%
summarize(suicides_no = sum(suicides_no),
population = sum(population)) %>%
mutate(rate = 100000 * suicides_no / population)
ggplot() +
geom_line(data = who_sub_sex, aes(year, rate, color = sex))}
}
}
})
}