I need to take the data returned from timevis, but these data are returned with one hour less than the data entered. I have tried changing the R time zone and the server too, but that has not solved the problem.
here's a simple example of what I'm trying to do:
ui<-fluidPage(
mainPanel(
timevisOutput("gantt"),
tableOutput("return"),
actionButton("btn","btn")
)
)
server <- function(input, output, session) {
data <- data.frame(
id = 1:4,
content = c("Item one" , "Item two" ,"Ranged item", "Item four"),
start = c("2016-01-10 00:00:00", "2016-01-11T00:00:00.000Z", "2016-01-20", "2016-02-14 15:00:00"),
end = c(NA , NA, "2016-02-04", NA),
group =c(1,1,2,2)
)
output$gantt<-renderTimevis({
timevis(data= data,
groups = data.frame(id = 1:4, content = c(" 1", " 2", " 3", " 4")),
options = list(editable = list(add=FALSE, remove=TRUE, updateTime= TRUE, updateGroup=TRUE, overrideItems=TRUE), align = "left"))
})
observeEvent(input$btn,{
output$return<-renderTable(
print(input$gantt_data)
)
})
}
shinyApp(ui, server)
The result of input$gantt_data returned is this:
id content start group end
1 1 Item one 2016-01-09T23:00:00.000Z 1 <NA>
2 2 Item two 2016-01-10T23:00:00.000Z 1 <NA>
3 3 Ranged item 2016-01-19T23:00:00.000Z 2 2016-02-03T23:00:00.000Z
4 4 Item four 2016-02-14T14:00:00.000Z 2 <NA>
First of all: Since you use mixed date formats, the second event is not displayed correctly. In my example below, I corrected that.
Since the timeline itself contains the dates in the correct time zone, it's just an issue of the object returned by input$gantt_data. You can manually correct that by first converting it to a POSIXct object and then displaying it in your desired timezone:
library(timevis)
ui<-fluidPage(
mainPanel(
timevisOutput("gantt"),
tableOutput("return"),
actionButton("btn","btn")
)
)
server <- function(input, output, session) {
data <- data.frame(
id = 1:4,
content = c("Item one" , "Item two" ,"Ranged item", "Item four"),
start = c("2016-01-10 00:00:00", "2016-01-11 00:00:00.00", "2016-01-20", "2016-02-14 15:00:00"),
end = c(NA , NA, "2016-02-04", NA),
group =c(1,1,2,2)
)
output$gantt<-renderTimevis({
timevis(data= data,
groups = data.frame(id = 1:4, content = c(" 1", " 2", " 3", " 4")),
options = list(editable = list(add=FALSE, remove=TRUE, updateTime= TRUE, updateGroup=TRUE, overrideItems=TRUE), align = "left"))
})
observeEvent(input$btn,{
output$return<-renderTable({
dat <- input$gantt_data
dat$start <- format(as.POSIXct(input$gantt_data$start, format = "%Y-%m-%dT%H:%M:%S", tz = "UTC"), tz="Europe/Berlin")
dat$end <- format(as.POSIXct(input$gantt_data$end, format = "%Y-%m-%dT%H:%M:%S", tz = "UTC"), tz="Europe/Berlin")
print(dat)
})
})
}
shinyApp(ui, server)
Related
I'm trying to create and render an interactive formattable table in a shiny app.
Here is a sample dataframe:
tcharts <- data.frame(pgm = c(1,2,3,4,5,6,7,8),
horse = c("Cigar", "Funny Cide", "Animal Kingdom", "Blame", "Zenyatta", "New Years Day", "Northern Dancer", "Beautiful Pleasure"),
groundloss = c(55,70,85,42,90,45,53,50),
distanceRun = c(5050,5070,5085,5045,5090,5045,5053,5050),
ttl = c(50,70,85,42,90,45,53,50),
fps = c(52.3,51.8,51.9,52.0,53.6,52.9,53.7,53.1),
finishTime = c(52.3,51.8,51.9,52.0,53.6,52.9,53.7,53.1),
finish = c(4,7,1,2,5,6,3,8),
BL = c(0,1,2,6,2,9,6,8),
rnum = c(1,1,1,1,1,1,1,1),
sixteenth = c(330,330,330,330,330,330,330)
)
Working version
This version of the code, when list() is empty (use all variables in dataframe) produces a table as expected.
library(shiny)
library(formattable)
inputPanel(
selectInput("rnum", label = "Race Number:",
choices = c(1,2,3,4,5,6,7,8,9), selected = 1),
sliderInput("poc", label = "Point of Call:",
min = 330, max = 5280, value = 330, step = 330)
)
cdat <- reactive({
tcharts %>% filter(rnum %in% input$rnum) %>%
filter(Sixteenth %in% input$poc)
})
renderFormattable({
formattable(cdat(),list(
))
})
Error Version:
With this version, I get an ERROR: object pgm not found
library(shiny)
library(formattable)
inputPanel(
selectInput("rnum", label = "Race Number:",
choices = c(1,2,3,4,5,6,7,8,9), selected = 1),
sliderInput("poc", label = "Point of Call:",
min = 330, max = 5280, value = 330, step = 330)
)
cdat <- reactive({
tcharts %>% filter(rnum %in% input$rnum) %>%
filter(Sixteenth %in% input$poc)
})
renderFormattable({
formattable(cdat(),list(
pgm,
Horse
))
})
The error message leads me to believe I'm not specifying the variable correctly, but I'm not sure how to do it. I'v looked at several formattable / shiny SO questions and responses, but have not come up with the correct sytax.
I am attempting to add the values from a checkboxgroupinput value to the data frame called surv_data in a Shiny App.
Below is the code for the check boxes:
checkboxGroupInput(inputId = "variables", label = "",
choices = c(
"Covariate 1" = "cov1",
"Covariate 2" = "cov2"
),
selected = c('cov1', 'cov2'))
Here is where I combine the variables in to one data frame:
surv_data <- reactive({
raw_surv <- raw_surv_data()
data.frame(
Time = raw_surv[[input$Time]],
Treatment = raw_surv[[input$Treatment]],
endpoint = raw_surv[[input$Endpoint]]
)
})
I need to somehow add the values cov1 and cov2 below the following line:
endpoint = raw_surv[[input$Endpoint]]
I've attempted to add variables = raw_surv[[input$variables]] but unfortunately this does not work. Any help would be appreciated.
Maybe
surv_data <- reactive({
raw_surv <- raw_surv_data()
cbind(
data.frame(
Time = raw_surv[[input$Time]],
Treatment = raw_surv[[input$Treatment]],
endpoint = raw_surv[[input$Endpoint]]
),
raw_surv[input$variables]
)
})
Here is my code - creating a dashboard that will filter by date. One tab will show our wellness survey data, the other will show post-practice loading data. I am pulling in the first 3 columns from "post.csv" which are Date, Name, Daily. Then I am looking to create and add the next 3 columns with the math.
Where I am first stuck is that I need my Daily_Load to aggregate data for a specific athlete on the given Date. Then I need to create a rolling 7-day sum for each athlete using the Daily load data from the last 7 days (including Date selected). A 28-Day Rolling Sum/4 and 7-Day/28-Rolling is the last piece.
Thanks again for all of the help!
library(shiny)
library(dplyr)
library(lubridate)
library(ggplot2)
library(DT)
library(zoo)
library(tidyr)
library(tidyverse)
library(data.table)
library(RcppRoll)
AM_Wellness <- read.csv("amwell.csv", stringsAsFactors = FALSE)
Post_Practice <- read.csv("post.csv", stringsAsFactors = FALSE)
Post_Data <- Post_Practice[, 1:3]
Daily_Load <- aggregate(Daily~ ., Post_Data, sum)
Acute_Load <- rollsum(Post_Data$Daily, 7, fill = NA, align = "right")
Chronic_Load <- rollsum(Post_Data$Daily, 28, fill = NA, align = "right")/4
Post_Data['Day Load'] <- aggregate(Daily~ ., Post_Data, sum)
Post_Data['7-Day Sum'] <- Acute_Load
Post_Data['28-Day Rolling'] <- Chronic_Load
Post_Data['Ratio'] <- Acute_Load/Chronic_Load
ui <- fluidPage(
titlePanel("Dashboard"),
sidebarLayout(
sidebarPanel(
dateInput('date',
label = "Date",
value = Sys.Date()
),
selectInput("athleteInput", "Athlete",
choices = c("All"))
),
mainPanel(tabsetPanel(type = "tabs",
tabPanel("AM Wellness", tableOutput("amwell")),
tabPanel("Post Practice", tableOutput("post"))
)
)
)
)
server <- function(input, output) {
output$amwell <- renderTable({
datefilter <- subset(AM_Wellness, AM_Wellness$Date == input$date)
}, hover = TRUE, bordered = TRUE, spacing = "xs", align = "c")
output$post <- renderTable({
datefilter <- subset(Post_Data, Post_Data$Date == input$date)
}, hover = TRUE, bordered = TRUE, spacing = "xs", align = "c")
}
shinyApp(ui = ui, server = server)
I am trying to make a Shiny app where the user selects a few options and a network and data table will display based on the inputs. I have a diet study database and would like users to be able to specify the predator species they are interested in, the diet metric (weight, volumetric, etc) and the taxonomic level they want nodes identified to. The data table works fine (so I did not include the code) and updates based on the input but the network does not change, it only shows all of the data. When I run the code for generating the plot outside of Shiny it works fine. This is my first shiny attempt so any suggestions would be greatly appreciated.
library(dplyr)
library(igraph)
library(networkD3)
Diet <-data.frame(
Predator_Scientific_Name = rep("Acanthocybium solanderi", 10),
Class_Predator = rep("Actinopterygii", 10),
Order_Predator = rep("Perciformes", 10),
Family_Predator = rep("Scombridae", 10),
Genus_Predator = rep("Acanthocybium", 10),
Species_Predator = rep("solandri", 10),
Class_Prey = rep("Actinopterygii", 10),
Order_Prey = c( "Clupeiformes" , NA , "Perciformes", "Perciformes", "Perciformes", "Perciformes", "Perciformes", "Perciformes", "Tetraodontiformes", "Tetraodontiformes"),
Family_Prey = c("Clupeidae", NA, "Coryphaenidae", "Carangidae", "Scombridae","Echeneidae","Carangidae", "Scombridae", "Balistidae","Diodontidae"),
Genus_Prey = c("Sardinella", NA, "Coryphaena", "Decapterus", "Euthynnus", NA, NA, NA, "Balistes", "Diodon"),
Species_Prey = c("aurita" , "", "hippurus", "punctatus","alletteratus", "", "", "","capriscus", "spp." ),
Lowest_Taxonomic_Identification_Prey = c("Sardinella aurita","Actinopterygii","Coryphaena hippurus","Decapterus punctatus","Euthynnus alletteratus", "Echeneidae", "Carangidae","Scombridae","Balistes capriscus","Diodon spp."),
Frequency_of_Occurrence = c(2.8, 59.1, 1.4, 7.0, 1.4, 1.4, 15.5, 21.1, 2.8, 4.2), StringAsFactors = FALSE
)
pred.name <- unique(Diet$Predator_Scientific_Name)
prey.tax <- unique(Diet$Lowest_Taxonomic_Identification_Prey)
#Progress bar function
compute_data <- function(updateProgress = NULL) {
# Create 0-row data frame which will be used to store data
dat <- data.frame(x = numeric(0), y = numeric(0))
for (i in 1:10) {
Sys.sleep(0.25)
# Compute new row of data
new_row <- data.frame(x = rnorm(1), y = rnorm(1))
# If we were passed a progress update function, call it
if (is.function(updateProgress)) {
text <- paste0("x:", round(new_row$x, 2), " y:", round(new_row$y, 2))
updateProgress(detail = text)
}
# Add the new row of data
dat <- rbind(dat, new_row)
}
dat
}
####
# Define UI for application that draws a histogram
ui <- dashboardPage(
skin = "blue",
dashboardHeader(title = "Diet Database"),
dashboardSidebar(
sidebarMenu(
menuItem("Parameters",
tabName = "paramaters",
icon = shiny::icon("bar-chart")))
),
dashboardBody(
tabItems(
tabItem(
tabName = "paramaters",
fluidRow(
shiny::column(
width = 4,
shinydashboard::box(
title = "Predator",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
shiny::helpText("Select a predator to view its connections and prey items:"),
shiny::selectInput(
"pred",
shiny::h5("Predator Scientific Name:"),
c(NA,pred.name))),
shinydashboard::box(
title = "Prey",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
shiny::helpText("Select a prey taxa to view its connections and predators:"),
shiny::selectInput(
"prey",
shiny::h5("Prey Taxa:"),
c(NA,prey.tax))),
shinydashboard::box(
title = "Diet Metric",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
shiny::helpText("Select a diet metric to use:"),
shiny::selectInput(
"dietmetric",
shiny::h5("Diet Metric:"),
c("Frequency of Occurrence" = "Frequency_of_Occurrence",
"Wet Weight" = "Weight",
"Dry Weight" = "Dry_Weight",
"Volume" = "Volume",
"Index of Relative Importance" = "IRI",
"Index of Caloric Importance" = "ICI",
"Number" = "Number"))),
shinydashboard::box(
title = "Taxonomic Level",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
shiny::helpText("Select a taxonomic level of nodes:"),
shiny::selectInput(
"nodetax",
shiny::h5("Taxonomic Level:"),
c("Order" = "Order",
"Family" = "Family",
"Genus" = "Genus",
"Species" = "Species"))),
shinydashboard::box(
title = "Generate Network",
status = "primary",
solidHeader = T,
collapsible = T,
width = NULL,
actionButton("makenet", "Generate")
)
),
#Area for network to be displayed
shiny::column(
width = 8,
shinydashboard::box(
title = "Trophic Network",
status = "primary",
solidHeader = TRUE,
collapsible = FALSE,
width = NULL,
forceNetworkOutput("netplot")
)
)
))
)))
server <- function(input, output, session) {
network.data <- eventReactive(input$makenet, {
edgelist <- Diet %>% filter(Predator_Scientific_Name == input$pred|Lowest_Taxonomic_Identification_Prey == input$prey
) %>% select(
paste(input$nodetax, "Predator", sep = "_"),
Class_Predator,
paste(input$nodetax, "Prey", sep = "_"),
Class_Prey,
input$dietmetric
)
colnames(edgelist) <- c("SourceName",
"SourceClass",
"TargetName",
"TargetClass",
"Weight")
edgelist <- edgelist[complete.cases(edgelist),]
})
output$netplot <- renderForceNetwork( {
network.data()
ig <-igraph::simplify(igraph::graph_from_data_frame(edgelist[,c(1,3,5)], directed = TRUE))
SourceID <- TargetID <- c()
for (i in 1:nrow(edgelist)) {
SourceID[i] <- which(edgelist[i,1] == V(ig)$name)-1
TargetID[i] <- which(edgelist[i,3] == V(ig)$name)-1
}
#Create edgelist that contains source and target nodes and edge weights
edgeList <- cbind(edgelist, SourceID, TargetID)
nodeList <- data.frame(ID = c(0:(igraph::vcount(ig) - 1)),
nName = igraph::V(ig)$name)
#Determine and assign groups based on class
preddf <-
data.frame(SciName = edgelist[, 1], class = edgelist[, 2])
preydf <-
data.frame(SciName = edgelist[, 3], class = edgelist[, 4])
groupsdf <- rbind(preddf, preydf)
groupsdf <- groupsdf %>% mutate(SciName = as.character(SciName),
class = as.character(class))
nodeGroup <- c()
for (i in 1:nrow(nodeList)) {
index <- which(groupsdf[, 1] == nodeList$nName[i])
nodeGroup[i] <- groupsdf[index[1], 2]
}
nodeList <-
cbind(nodeList,
nodeGroup)
progress <- shiny::Progress$new()
progress$set(message = "Generating your network...", value = 0)
# Close the progress when this reactive exits (even if there's an error)
on.exit(progress$close())
# Create a callback function to update progress.
# Each time this is called:
# - If `value` is NULL, it will move the progress bar 1/5 of the remaining
# distance. If non-NULL, it will set the progress to that value.
# - It also accepts optional detail text.
updateProgress <- function(value = NULL, detail = NULL) {
if (is.null(value)) {
value <- progress$getValue()
value <- value + (progress$getMax() - value) / 5
}
progress$set(value = value, detail = detail)
}
# Compute the new data, and pass in the updateProgress function so
# that it can update the progress indicator.
compute_data(updateProgress)
networkD3::forceNetwork(
Links = edgeList,
# data frame that contains info about edges
Nodes = nodeList,
# data frame that contains info about nodes
Source = "SourceID",
# ID of source node
Target = "TargetID",
# ID of target node
Value = "Weight",
# value from the edge list (data frame) that will be used to value/weight relationship amongst nodes
NodeID = "nName",
# value from the node list (data frame) that contains node
Group = "nodeGroup",
# value from the node list (data frame) that contains value we want to use for node color
fontSize = 25,
opacity = 0.85,
zoom = TRUE,
# ability to zoom when click on the node
opacityNoHover = 0.4 # opacity of labels when static
)
})
}
# Run the application
shinyApp(ui = ui, server = server)
I am sharing my fixed code in case it helps someone in the future. I basically just changed the top of the server code.
network.data <- eventReactive(input$makenet, {
Diet %>% filter(Predator_Scientific_Name == input$pred|Lowest_Taxonomic_Identification_Prey == input$prey
) %>% select(
paste(input$nodetax, "Predator", sep = "_"),
Class_Predator,
paste(input$nodetax, "Prey", sep = "_"),
Class_Prey,
input$dietmetric
) %>% rename("SourceName" = paste(input$nodetax, "Predator", sep = "_"),
"SourceClass" = Class_Predator,
"TargetName" = paste(input$nodetax, "Prey", sep = "_"),
"TargetClass" = Class_Prey,
"Weight" = input$dietmetric) %>% na.omit()
})
output$netplot <- renderForceNetwork( {
edgelist <- network.data()
I am working with the timevis library in R. I want a gannt diagram with one line per item. The following example will stack items after another if there is room. Is there a way to force the diagram to have as many rows as there are items?
library(timevis)
data <- data.frame(
id = 1:4,
content = c("Item one" , "Item two" ,"Ranged item", "Item four"),
start = c("2016-01-10", "2016-01-11", "2016-01-20", "2016-02-14"),
end = c(NA , NA, "2016-02-04", NA)
)
timevis(data)
This gives the following output from timevis:
But I want each of the items on a separate line
I am aware of other packages than timevis, but I would prefer using timvis as the interactivity is very usefull for what I am trying to vizualise.
From the examples, slightly modified:
timevis(data = data.frame(
start = c(Sys.Date(), Sys.Date()+1, Sys.Date() + 2, Sys.Date() + 3),
content = c("one", "two", "three", "four"),
group = c(1, 2, 3, 4)),
groups = data.frame(id = 1:4, content = c("G1", "G2", "G3", "G4"))
)
This should be a good starting point.
You need the option: stack = TRUE for this, this puts them on different lines inside a group, example final call below
tv <<- timevis(main,group, showZoom = FALSE,options = list(
editable = TRUE,stack = TRUE, showCurrentTime = FALSE,multiselect = TRUE,align = "center"))