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app.R
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app.R
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# Packages ----
library(shiny)
library(shinydashboard)
library(shinyEffects)
library(shinyWidgets)
library(bs4Dash)
library(numform)
library(tidyverse)
library(echarts4r)
library(echarts4r.maps)
library(echarts4r.assets)
library(readxl)
library(DT)
library(lubridate)
options(scipen = 999, encoding = "latin1")
# DATA ----
# * Completed database ----
db <- read_excel("db_cvd.xlsx")
code <- read_delim("CODE.txt",
delim = ";", escape_double = FALSE, trim_ws = TRUE)
db$Cause <- factor(db$Cause, levels = c(1,2,3,4,5,6,7,8,9),
labels = code$Causes)
prevalences <- data.frame()
for(i in 1:1782){
prop <- prop.test(x = db$N[i], n = db$Population[i], alternative = "two.sided",
conf.level = 0.95)
final <- round(data.frame(Rate = prop$estimate, Rate_lower = prop$conf.int[1],
Rate_upper = prop$conf.int[2])*100000,1)
prevalences <- rbind.data.frame(prevalences, final)
}
db <- cbind.data.frame(db, prevalences)
# * Mortality by sex ----
both <- db %>%
filter(Cause == "Cardiovascular diseases",
Age == "All Ages",
Sex == "Both") %>%
arrange(Year) %>%
as.data.frame()
female <- db %>%
filter(Cause == "Cardiovascular diseases",
Age == "All Ages",
Sex == "Female") %>%
arrange(Year) %>%
as.data.frame()
male <- db %>%
filter(Cause == "Cardiovascular diseases",
Age == "All Ages",
Sex == "Male") %>%
arrange(Year) %>%
as.data.frame()
# * Moratality by province ----
provincias <- read_excel("causa_provincias.xlsx")
provincias <- provincias %>%
pivot_longer(names_to = "Province", values_to = "Total", cols = 2:17) %>%
arrange(Year) %>% as.data.frame()
# * Annualized change ratio by sex ----
acr <- read.csv("acr.csv") %>% as.data.frame()
# * Annualized change ratio by province ----
acr_province <- read.csv("provinces_final.csv") %>% as.data.frame()
# * Forecast data ----
forecast <- read.csv("forecast.csv") %>% as.data.frame()
forecast <- forecast[c(1:11, 22:26), 5:6]
forecast$Serie <- c(rep("Actual", 11), rep("Estimated", 5))
forecast$Deaths <- round(forecast$Deaths)
forecast$Year <- as.Date(forecast$Year, "%Y-%m-%d") %>% year() %>% as.character()
# UI Shiny Dashboard ----
ui <- dashboardPage(
dark = NULL,
header = dashboardHeader(title = HTML("<head>
<link href='https://unpkg.com/boxicons@2.1.2/css/boxicons.min.css' rel='stylesheet'>
<style>
.logo-content .logo {
color: white;
display: flex;
height: 50px;
width: 100%;
align-items: center;
}
.logo-content .logo i {
font-size: 26px;
margin-right: 10px;
}
.logo-content .logo .logo_name {
font-size: 20px;
font-weight: 400;
overflow: hidden
}
.layout-fixed.sidebar-mini.sidebar-collapse .wrapper .main-sidebar.sidebar-dark-primary.elevation-4.shiny-bound-input .brand-link .logo-content{
width: 50px;
height: 50px;
left: 25px;
background: url('https://avatars.githubusercontent.com/u/112302277?s=400&u=cbd35fa32b91217fb520bde438550648ea09cf7c&v=4');
background-size: cover;
background-position:center;
background-repeat:no-repeat;
transition-duration: 0.5s;
transform: translateX(5%);
}
.layout-fixed.sidebar-mini.sidebar-collapse .wrapper .main-sidebar.sidebar-dark-primary.elevation-4.shiny-bound-input .brand-link .logo-content .logo_name{
display: none;
}
.layout-fixed.sidebar-mini.sidebar-collapse .wrapper .main-sidebar.sidebar-dark-primary.elevation-4.shiny-bound-input .brand-link .logo-content .bx-bar-chart-square {
display: none;
}
</style>
<title>Document</title>
</head>
<div class='logo-content'>
<div class='logo'>
<i class='bx bx-bar-chart-square'></i>
<div class='logo_name'>EpiCardio</div>
</div>
</div>"),
tags$style(".inner{font-size:200%;color:white;face:bold}"),
tags$style(".row{display:flex;place-items:center}"),
tags$style("#header_text{font-size:200%}"),
controlbarIcon = icon("th", lib = "glyphicon"),
rightUi = (dropdownMenu(type = "messages",
messageItem(from = "José A. Ávila Cabreja",
message = "Puede enviar sugerencias a mi correo"
))
)
),
sidebar = dashboardSidebar(
bs4SidebarUserPanel(name = tags$a(href = "mailto:javilacabreja@gmail.com","José A. Ávila Cabreja"), image = "https://media-exp1.licdn.com/dms/image/C4E03AQFn3EdRI1ihBw/profile-displayphoto-shrink_400_400/0/1640650841613?e=1667433600&v=beta&t=LqpqRj_jmdC_Dss8hUP1Z_zPnQqXqmsWSXWjFGfflGY"),
sidebarMenu(id = "sidebarid",
menuItem("Home", tabName = "home", icon = icon("fas fa-house")),
menuItem("General", tabName = "general", icon = icon("fas fa-rectangle-list")),
menuItem("Rate of changes", tabName = "changes", icon = icon("transfer",lib = "glyphicon")),
menuItem("Forecasts", tabName = "forecasts", icon = icon("chart-line"))
)
),
body = dashboardBody(
tabItems(
# * First Tab Information ----
tabItem("home",
includeHTML("intro.html")
),
# * Second tab with general information about the time period ----
tabItem("general",
fluidRow(id = "sexos",
column(valueBoxOutput("both_mortality_box", width = 10), width = 4),
column(valueBoxOutput("female_mortality_box", width = 10), width = 4),
column(valueBoxOutput("male_mortality_box", width = 10), width = 4)
),
box(
title = " Cardiovascular disease mortality by sex, age and causes",
solidHeader = TRUE,
status = "primary",
icon = icon("signal", lib = "glyphicon"),
width = 11.5,
fluidRow(
column(6,
selectInput("cause1", "Causes:",
choices = unique(db$Cause))),
column(6,
selectInput("medida1", "Measure:", choices = c("Total", "Rate"))),
br(),
column(12,
echarts4rOutput("plot1", height = 600))),
footer = HTML("<p style='font-size:100%'><i>Note:</i> Rate by 100 000 persons.</p>")
),
box(
title = " Trends in cardiovascular disease mortality between 2010 and 2020",
solidHeader = TRUE,
status = "warning",
icon = icon("random", lib = "glyphicon"),
width = 11.5,
fluidRow(
column(4,
selectInput("cause0", "Causes:",
choices = unique(db$Cause))),
column(4,
selectInput("age0", "Age:",
choices = unique(db$Age))),
column(4,
selectInput("medida0", "Measure:", choices = c("Total", "Rate"))),
br(),
column(12,
echarts4rOutput("plot0", height = 600))),
footer = HTML("<p style='font-size:100%'><i>Note:</i> Rate by 100 000 persons.</p>")
),
box(title = " Cardiovascular disease mortality by province",
solidHeader = TRUE,
status = "danger",
icon = icon("globe", lib = "glyphicon"),
width = 11.5,
echarts4rOutput("map", height = 600)
)
),
# * Third tab with annualized rate of change by cause, age, sex and province ----
tabItem("changes",
box(
title = "Annualised rate of change in cardiovascular disease mortality by sex 2010-2020",
solidHeader = TRUE,
status = "lightblue",
icon = icon("transfer", lib = "glyphicon"),
width = 11.5,
fluidRow(class = "rates",
column(6,
selectInput("cause2", "Causes:",
choices = unique(db$Cause))),
column(6,
selectInput("sex2", "Sex:",
choices = unique(db$Sex))),
column(12,
textOutput("header_text")),
br(),
column(4,
dataTableOutput("rate_change_table", width = 400)),
column(8,
echarts4rOutput("plot2", height = 460))),
footer = HTML("<p style='font-size:100%'><i>Note:</i> Data are reported in percentage.</p>")
),
box(
title = "Annualised rate of change in cardiovascular disease mortality by province 2010-2020",
solidHeader = TRUE,
status = "indigo",
icon = icon("transfer", lib = "glyphicon"),
width = 11.5,
footer = fluidRow(
column(12, HTML("<p style='font-size:100%'><i>Note:</i> Data are reported in percentage.</p>")),
column(12, paste(acr_province$Provinces, ": ", unique(provincias$Province), collapse = ", "))),
echarts4rOutput("plot3", height = 800)
)
),
# * Fourth tab with forecasting ----
tabItem("forecasts",
box(
title = "Cardiovascular disease mortality in both sexes in the next 5 years",
solidHeader = TRUE,
status = "navy",
icon = icon("chart-line"),
width = 11.5,
echarts4rOutput("forecast_plot")
)
))
),
controlbar = dashboardControlbar(skinSelector(), width = 250),
title = "EpiCardio"
)
# SERVER ----
server <- function(input, output, session){
# * Value boxes ----
output$both_mortality_box <- renderValueBox({
valueBox(value = f_comma(sum(both$N)), subtitle = "2010-2020", icon = icon("fas fa-heart"),
width = 6, color = "orange", footer = "Both sex")
})
output$female_mortality_box <- renderValueBox({
valueBox(value = f_comma(sum(female$N)), subtitle = paste(round(sum(female$N)/sum(both$N)*100), "%"), icon = icon("fas fa-female"),
width = 6, color = "purple", footer = "Female")
})
output$male_mortality_box <- renderValueBox({
valueBox(value = f_comma(sum(male$N)), subtitle = paste(round(sum(male$N)/sum(both$N)*100), "%"), icon = icon("fas fa-male"),
width = 6, color = "primary", footer = "Male")
})
# * PLOT1 ----
output$plot1 <- renderEcharts4r({
if(input$medida1=="Total"){
db %>%
filter(Cause == input$cause1,
Age != "All Ages") %>%
group_by(Sex) %>%
e_charts(Age) %>%
e_bar(N) %>%
e_color(color = c("#FD7E14", "#6F42C1", "#007BFF")) %>%
e_title("Cardiovascular disease mortality by cause, age and sex 2010-2020",
"Data extracted from the Statistical Yearbook on Health 2010-2020") %>%
e_tooltip(trigger = "item") %>%
e_legend(center=0, top = 570) %>%
e_show_loading()
} else {
db %>%
filter(Cause == input$cause1,
Age != "All Ages") %>%
group_by(Sex) %>%
e_charts(Age) %>%
e_bar(Rate) %>%
e_color(color = c("#FD7E14", "#6F42C1", "#007BFF")) %>%
e_title(text = "Cardiovascular disease mortality by cause, age and sex 2010-2020",
subtext = "Data extracted from the Statistical Yearbook on Health 2010-2020") %>%
e_tooltip(trigger = "item") %>%
e_legend(center=0, top = 570) %>%
e_show_loading()
}
})
# * PLOT2 ----
trends_table <- reactive({
db %>%
filter(Cause == input$cause0,
Age == input$age0) %>%
arrange(Year) %>%
mutate(Year2 = as.character(Year))
})
output$plot0 <- renderEcharts4r({
if(input$medida0=="Total"){
trends_table() %>%
group_by(Sex) %>%
e_charts(Year2) %>%
e_line(N) %>%
e_color(color = c("#FD7E14", "#6F42C1", "#007BFF")) %>%
e_title("Trends in cardiovascular diseases mortality by cause, age and sex 2010-2020",
"Data extracted from the Statistical Yearbook on Health 2010-2020") %>%
e_tooltip(trigger = "axis") %>%
e_legend(center=0, top = 570)%>%
e_show_loading()
} else {
trends_table() %>%
group_by(Sex) %>%
e_charts(Year2) %>%
e_line(Rate) %>%
e_color(color = c("#FD7E14", "#6F42C1", "#007BFF")) %>%
e_title("Trends in cardiovascular diseases mortality by cause, age and sex 2010-2020",
"Data extracted from the Statistical Yearbook on Health 2010-2020") %>%
e_tooltip(trigger = "axis") %>%
e_legend(center=0, top = 570) %>%
e_show_loading()
}
})
# * MAP PLOT3 ----
output$map <- renderEcharts4r({
provincias %>%
group_by(Year) %>%
e_charts(Province, timeline = TRUE) %>%
em_map("Cuba") %>%
e_map(Total, "Cuba") %>%
e_visual_map(Total) %>%
e_tooltip(trigger = "item", formatter = htmlwidgets::JS("
function(params){
return('<strong>' + params.name + ':' +'</strong><br /> ' + params.value + ' deaths')}")) %>%
e_timeline_opts(axis_type = "time") %>%
e_title("Cardiovascular disease mortality in Cuba by province 2010-2020",
"Data extracted from the Statistical Yearbook on Health 2010-2020") %>%
e_show_loading()
})
sex <- reactive({
if(input$sex2=="Both"){paste("both sexes")
} else {
if(input$sex2=="Female"){paste("females")
} else {
if(input$sex2=="Male"){paste("males")}
}
}
})
# * TABLE-PLOT4 ----
output$header_text <- renderText({
paste("Annualised rate of change for", tolower(input$cause2), "mortality for", sex(), "(%)")
})
rate_change_table <- reactive({
acr %>%
filter(Sex == input$sex2,
Cause == input$cause2) %>%
select(Age, ARC, Lower, Upper) %>%
mutate(color = if_else(ARC > 0, "#dc3545", "#5470C6")) %>%
as.data.frame()
})
output$rate_change_table <- renderDataTable({
datatable(rate_change_table()[,1:4], filter = "none",
options = list(paging=FALSE, searching=FALSE, info = FALSE, ordering = FALSE),
selection = "none",
rownames = FALSE,
style = "bootstrap4")
})
output$plot2 <- renderEcharts4r({
rate_change_table() %>%
e_charts(Age) %>%
e_bar(ARC, legend = FALSE) %>%
e_add_nested("itemStyle", color) %>%
e_error_bar(lower = Lower, upper = Upper,
itemStyle = list(borderWidth = 2)
) %>%
e_show_loading()
})
# * PLOT5 ----
output$plot3 <- renderEcharts4r({
acr_province %>%
e_charts(Provinces) %>%
e_line(ARC, legend = FALSE) %>%
e_error_bar(lower = Lower, upper = Upper,
itemStyle = list(borderWidth = 2)) %>%
e_x_axis(axisLabel = list(interval = 0, rotate = 45)) %>%
e_title("Annualised rate of change in cardiovascular disease mortality by province 2010-2020",
"Data extracted from the Statistical Yearbook on Health 2010-2020") %>%
e_labels() %>%
e_show_loading()
})
# * FORECAST PLOT ----
output$forecast_plot <- renderEcharts4r({
forecast %>%
group_by(Serie) %>%
e_charts(Year) %>%
e_bar(Deaths, stack = "grp") %>%
e_color(color = c("#5470C6","#dc3545")) %>%
e_tooltip(trigger = "item")
})
session$onSessionEnded(stopApp)
}
# SHINY APP ----
shinyApp(ui = ui, server = server)