I am trying to figure out how to add multiple graphs to my shiny app. Below is my code for my shiny app which lands on the main page.
library(shiny)
library(markdown)
library(DT)
library(ggplot2)
library(dplyr)
library(plotly)
library(shinythemes)
happiness2015 <- read.csv("2015.csv", stringsAsFactors = TRUE)
happiness2016 <- read.csv("2016.csv", stringsAsFactors = TRUE)
happiness2017 <- read.csv("2017.csv", stringsAsFactors = TRUE)
happiness2018 <- read.csv("2018.csv", stringsAsFactors = TRUE)
happiness2019 <- read.csv("2019.csv", stringsAsFactors = TRUE)
countries_all <- read.csv("countries.csv", stringsAsFactors = TRUE)
# Define UI for application that draws a histogram
ui <- navbarPage(
theme = shinytheme("readable"),
title = "World Happiness",
tabPanel("Plot",
sidebarPanel(width = 3,
br(),
span("Data from ",
tags$a("World Happiness Report.", href = "http://worldhappiness.report")),
br(), hr(),
helpText("Select year"),
actionButton("button2015", "2015"),
actionButton("button2016", "2016"),
actionButton("button2017", "2017"),
actionButton("button2018", "2018"),
actionButton("button2019", "2019"),
br(), br(),
helpText("Choose variables"),
uiOutput("variable_1"),
uiOutput("variable_2"),
br(),
helpText("Press command to see multiple countries"),
uiOutput("country"),
br(), hr(),
span("Data source:",
tags$a("Kaggle",
href = "https://www.kaggle.com/unsdsn/world-happiness")),
br(), br(),
em(
span("Code", a(href = "https://github.com/raishamdahya/INFO281", "on GitHub"))
)),
mainPanel(
tabsetPanel(
tabPanel("Plot",
br(),
h2(textOutput("year_name_plot")),
plotlyOutput("scatterplot",
height = 800)
),
tabPanel("Table",
br(),
DT::dataTableOutput("results_table")
),
tabPanel(textOutput("tab_name_rankings"),
h1(textOutput("year_name")),
h2("Top 10"),
wellPanel(
dataTableOutput("rank_table_top")),
br(),
h2("Bottom 10"),
wellPanel(
dataTableOutput("rank_table_bottom"))
)
)
)),
tabPanel("About"))
##############################################
### SERVER STARTS HERE #######################
##############################################
server <- function(input, output, session) {
output$variable_1 <- renderUI({
selectInput("variable_1", "Y-variable:",
choices = c("Happiness.Rank", "Happiness.Score", "Economy",
"Family", "Health", "Freedom", "Government.Corruption",
"Generosity", "Dystopia.Residual"), selected = "Happiness.Score")
})
output$variable_2 <- renderUI({
selectInput("variable_2", "X-variable:",
choices = c("Happiness.Rank", "Happiness.Score", "Economy",
"Family", "Health", "Freedom", "Government.Corruption",
"Generosity", "Dystopia.Residual"), selected = "Economy")
})
data_year <- reactiveValues(data = happiness2015, year = "2015")
observeEvent(input$button2015, {
data_year$data <- happiness2015
year <- "2015"
})
observeEvent(input$button2016, {
data_year$data <- happiness2016
data_year$year <- "2016"
})
observeEvent(input$button2017, {
data_year$data <- happiness2017
data_year$year <- "2017"
})
observeEvent(input$button2018, {
data_year$data <- happiness2018
data_year$year <- "2018"
})
observeEvent(input$button2019, {
data_year$data <- happiness2019
data_year$year <- "2019"
})
filtered_data <- reactive({
data_year$data %>%
filter(Country %in% c(input$country)) %>%
arrange(Country)
})
output$year_name_plot <- renderText({
paste("Data for ", data_year$year)
})
countries <- reactive({
df_small <-
countries_all %>%
select(Country) %>%
droplevels()
c("Select All", levels(df_small$Country))
})
output$country <- renderUI ({
selectInput("country", "Countries:",
multiple = TRUE,
choices = countries(),
selected = "Select All",
selectize = FALSE,
size = 10)
})
observe({
if ("Select All" %in% input$country) {
# choose all the choices _except_ "Select All"
selected_choices <- setdiff(countries(), "Select All")
updateSelectInput(session, "country", selected = selected_choices)
}
})
output$scatterplot <- renderPlotly({
if (is.null(data_year$data)) return()
p <- ggplot(filtered_data()) +
geom_point(aes_string(x = input$variable_2, y = input$variable_1,
colour = "Region", label = "Country"), size = 3) +
ggtitle(paste0(input$variable_1, " vs. ", input$variable_2)) +
theme_bw() +
theme(legend.position = "bottom")
ggplotly(p, tooltip = c("label", "x", "y"), height = 500)
})
output$results_table <- DT::renderDataTable({
if (is.null(data_year$data)) {
return()
} else {
filtered_data()
}
},
options = list(lengthChange = FALSE,
scrollCollapse = TRUE,
scrollX = "100%"),
selection = "single"
)
output$tab_name_rankings <- renderText({
paste("Happiness Ranking: ", data_year$year)
})
output$year_name <- renderText({
paste("Happiness Ranking in ", data_year$year)
})
output$rank_table_top <- DT::renderDataTable({
if (is.null(data_year$data)) {
return()
} else {
data_year$data %>%
mutate(Rank = Happiness.Rank) %>%
arrange(Rank) %>%
top_n(10, desc(Rank))
}
},
options = list(lengthChange = FALSE,
scrollX = "100%")
)
output$rank_table_bottom <- DT::renderDataTable({
if (is.null(data_year$data)) {
return()
} else {
data_year$data %>%
mutate(Rank = Happiness.Rank) %>%
arrange(Rank) %>%
top_n(10, Rank)
}
},
options = list(lengthChange = FALSE,
scrollX = "100%")
)
}
# Run the application
shinyApp(ui = ui, server = server)
I am trying to add the following plotly plots to the page:
This is the code for the 2 graphs:
#read files
worklife<-read.csv('satisfaction-with-job-and-work-life-balance-(%)-by-usual-hours-worked,-2018.csv')
wellbeingmeasure<-read.csv('-average-rating-of-selected-wellbeing-measures-for-new-zealanders,-2018_19.csv')
colnames(worklife)
colnames(wellbeingmeasure)
ggplot(worklife, aes(x = Work.life.balance, y = Job.satisfaction)) +
geom_point(aes(color = factor(Usual.hours.worked.in.main.job)))
ggplot(wellbeingmeasure, aes(x = Average.Rating, y = Selected.wellbeing.measures)) + geom_point()
library(plotly)
p1 <- plot_ly(data = worklife, x = ~Work.life.balance, y = ~Job.satisfaction, color = ~Usual.hours.worked.in.main.job)
p1
p2 <- plot_ly(data = wellbeingmeasure, x = ~Average.Rating, y = ~Selected.wellbeing.measures)
p2
Any help on this is appreciated. How do I add the above code into my shiny app?
