25/05/2020
This app visualizes a very basic time series plots such as line graph, ACF and PACF plots
The source code for this app is available in https://github.com/MonishaDamodaran/Developing_Data_Product_RShinyApp.
My shiny app is found here https://monishadamodaran3131.shinyapps.io/try3/.
This is just a pilot version of the time series plots. I will develop this app with more features to handle both univariate and multivariate time series data.
Many more options like differenced data, stationary tests and forecasting options can be added in different tabs.
The documentation for the app is seen in the main panel of the app.
#initialize library(shiny) library(ggplot2) library(purrr) library(dplyr) library(forecast)
#DEFAULT DATA
AirPassengers <- as.data.frame(AirPassengers)
AirPassengers$index = 1:nrow(AirPassengers)
#plotting theme for ggplot2
.theme<- theme(
axis.line = element_line(colour = 'gray', size = .75),
panel.background = element_blank(),
plot.background = element_blank()
)
ui<-(fluidPage(
# title
titlePanel("Univariate Time Series Plot"),
#input
sidebarLayout(
sidebarPanel
(
# Input: Select a file ----
fileInput("file1", "Choose CSV File",
multiple = TRUE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Input: Checkbox if file has header ----
checkboxInput("header", "Header", TRUE),
# Input: Select separator ----
radioButtons("sep", "Separator",
choices = c(Semicolon = ";",
Comma = ",",
Tab = "\t"),
selected = ","),
tags$hr(),
# Input: Select what to display
selectInput("dataset","Data:",
choices =list(AirPassengers = "AirPassengers", mtcars = "mtcars",
uploaded_file = "inFile"), selected=NULL),
selectInput("variable","Variable:", choices = NULL, selected = NULL),
selectInput("group","Group:", choices = NULL,selected = NULL),
selectInput("plot.type","Plot Type:",
list(linegraph = "linegraph", none = "none")),
selectInput("acfpcf", "acfpacf", list(acf = "acf", pacf = "pacf"
)),
checkboxInput("show.points", "show points", TRUE)
),
# output
mainPanel(
h3(textOutput("caption")),
#h3(htmlOutput("caption")),
uiOutput("plot"),
uiOutput("plot1"),# depends on input
tabsetPanel(
tabPanel("Documentation",
br(),
p("The app name Univariate Time series Analysis signifies a
very simple visualization of univariate time series data"),
p("The R dataset strong(AirPassengers) is used here. The dataset
is first converted to a data frame object since it is a ts object.
The year and index column is been mutated to AirPassengers data."),
br(),
strong("LEFT PANE"),
br(),
p("1) The left pane consists of a browse box to upload files,"),
p("2) The check box to get header of the imported files,"),
p("3) The radio button to select the type of imported files,"),
p("4) The drop down list displaying the data name strong(AirPassengers)
by default and if the file has uploaded from your drive select
upload files from the list,"),
p("5) The variable and group drop down boxes are column names of
the selected data. It is used as a x axis and y axis for plots,"),
p("6) The Plot type box consists of option to get strong(Linegraph or None",),
p("7) Acf and Pacf plots are displayed in main panel by selecting
the required one from acfpacf dropdown list,"),
p("8) The final checkbox gives the option to display the points
in the plotted graph."),
br(),
strong(em("Once the app is opened, it displays the linegraph of the variable x vs
x of AirPassengers data. Choosing the group to Index shows the actual line
chart of Passengers data over time")),
br(),
p("I have provided an example time series dataset in my
github page to try visualizing the plots using my app")
))
)
)))
server<-(function(input, output, session){
#update group and
#variables based on the data
observe({
#browser()
if(!exists(input$dataset)) return() #make sure upload exists
var.opts<-colnames(get(input$dataset))
updateSelectInput(session, "variable", choices = var.opts)
updateSelectInput(session, "group", choices = var.opts)
})
output$caption<-renderText({
switch(input$plot.type,
"linegraph" = "linegraph"
)
})
output$caption1 <- renderText({
switch(input$acfpcf,
"acf" = "acf",
"pacf" = "pacf")
})
output$plot <- renderUI({
plotOutput("p")
})
output$plot1 <- renderUI({
plotOutput("q")
})
#get data object
get_data<-reactive({
if(!exists(input$dataset)) return() # if no upload
check<-function(x){is.null(x) || x==""}
if(check(input$dataset)) return()
obj<-list(data=get(input$dataset),
variable=input$variable,
group=input$group
)
#require all to be set to proceed
if(any(sapply(obj,check))) return()
#make sure choices had a chance to update
check<-function(obj){
!all(c(obj$variable,obj$group) %in% colnames(obj$data))
}
if(check(obj)) return()
obj
})
output$p <- renderPlot({
data = get(input$dataset)
data = as.data.frame(data)
var.opts<-colnames(data)
plot.obj<-get_data()
#make sure variable and group have loaded
if(plot.obj$variable == "" | plot.obj$group =="") return()
if(input$plot.type=="linegraph") {
#control for 1D or 2D graphs
# if (class(plot.obj$group == "date"){
# input$group = as.Date(plot.obj$group)
# }
p<-ggplot(plot.obj$data,
aes_string(
x = plot.obj$group,
y = plot.obj$variable
#fill = plot.obj$group # let type determine plotting
)
) + geom_line()
if(input$show.points==TRUE)
{
p<-p+ geom_point(color='black',alpha=0.5, position = 'jitter')
}
}
# else {
#
# p<-ggplot(plot.obj$data,
# aes_string(
# x = plot.obj$variable,
# fill = plot.obj$group,
# group = plot.obj$group
# #color = as.factor(plot.obj$group)
# )
# ) + plot.type
# }
#
p<-p+labs(
fill = input$group,
x = "",
y = input$variable
) +
.theme
print(p)
})
getContents <- reactive({
# input$upload_file will be NULL initially. After the user selects and uploads a file
req(input$upload_file)
uf <<- read.csv(input$dataset$datapath)
uf[is.na(uf)] <- 0
uf$date <- as.Date(uf$date, format = "%Y-%m-%d")
return(uf)
})
output$dataTable <- renderTable({
getContents()
})
output$q <- renderPlot({
data = get(input$dataset)
var.opts<-colnames(get(input$dataset))
plot.obj<-get_data()
#conditions for plotting
if(is.null(plot.obj)) return()
#make sure variable and group have loaded
if(plot.obj$variable == "" | plot.obj$group =="") return()
c = data[var.opts == plot.obj$variable]
if(input$acfpcf =="acf") {
acf(c)
}else {
pacf(c)
}
})
# set uploaded file
upload_data<-reactive({
inFile <- input$file1
if (is.null(inFile))
return(NULL)
#could also store in a reactiveValues
read.csv(inFile$datapath,
header = input$header,
sep = input$sep)
})
observeEvent(input$file1,{
inFile<<-upload_data()
})
})