r - Formatting/aligning rCharts (nvd3) in shiny app -
i developing shiny app hope picture below: 
however, try achieve this, able following form:
i looking how make output neatly collected, , appreciate help. have looked @ couple of other similar questions here, viz. this , this, don't think answer question (the first talks adding mainpanel, using fludipage , fluidrows. had thought columns , rows automatically adjust screen size, , 12 columns designed fit screen size, apparently wrong?
many help.
the server.r file copying/pasting. apologies, bit long:
# # # load libraries, scripts, data library(shiny) library(shinyapps) library(shinydashboard) library(dplyr) library(tidyr) library(lubridate) library(htmlwidgets) options(shiny.trace = true, shiny.maxrequestsize=300*1024^2) ## body of shiny server side program shinyserver(function(input, output, session) { datalist <- reactive({ if(is.null(input$uploadfile)){ return(null) } uploadfileinfo <- input$uploadfile uploaddata <- read.csv(uploadfileinfo$datapath, header = true, stringsasfactors = false) uploadeddata <- tbl_df(uploaddata) %>% mutate(yearvalue = year(datevalues), monthvalue = month(datevalues)) sumdata1 <- uploadeddata %>% select(yearvalue, earnpts, earncount, redempts, redemcount, churncount, acquiscount) %>% gather(metrics, totals, -yearvalue) %>% group_by(yearvalue, metrics) %>% summarise(yearlytotals = sum(totals)) %>% arrange(yearlytotals) sumdata2 <- uploadeddata %>% select(yearvalue, monthvalue, earnpts, earncount, redempts, redemcount, churncount, acquiscount) %>% gather(metrics, totals, -c(yearvalue, monthvalue)) %>% group_by(yearvalue, monthvalue, metrics) %>% summarise(yearmonthtotals = sum(totals)) %>% arrange(yearvalue, monthvalue) %>% group_by(yearvalue, metrics) %>% mutate(cumulatives = cumsum(yearmonthtotals)) sumdata3 <- uploadeddata %>% select(yearvalue, monthvalue, earnpts, earncount, redempts, redemcount, churncount, acquiscount) %>% group_by(yearvalue, monthvalue) %>% summarise_each(funs(mean)) %>% round() sumdata4 <- uploadeddata %>% group_by(datevalues) %>% summarise_each(funs(sum)) earndata <- sumdata4 %>% select(earnpts, earncount) row.names(earndata) <- sumdata4$datevalues redempdata <- sumdata4 %>% select(redempts, redemcount) row.names(earndata) <- sumdata4$datevalues custdata <- sumdata4 %>% select(churncount, acquiscount) row.names(earndata) <- sumdata4$datevalues sumdata5 <- uploadeddata %>% group_by(datevalues) %>% summarise_each(funs(sum)) earntsdata <- sumdata5 %>% select(earnpts, earncount) row.names(earntsdata) <- sumdata5$datevalues redemtsdata <- sumdata5 %>% select(redempts, redemcount) row.names(redemtsdata) <- sumdata5$datevalues custtsdata <- sumdata5 %>% select(acquiscount, churncount) row.names(custtsdata) <- sumdata5$datevalues dflist <- list(sumdata1 = sumdata1, sumdata2 = sumdata2, sumdata3 = sumdata3, sumdata4 = sumdata4, earndata = earndata, redempdata = redempdata, custdata = custdata, sumdata5 = sumdata5, earntsdata = earntsdata, redemtsdata = redemtsdata, custtsdata = custtsdata) return(dflist) }) ### main chart output$outlineschart <- renderchart2({ mydata <- datalist()$sumdata1 mainplot <- nplot(yearlytotals ~ metrics, group = 'yearvalue', data = mydata, type = 'multibarchart') mainplot$chart(margin=list(left=100)) rm(mydata) return(mainplot) }) ### information boxes output$infobox1 <- renderinfobox({ infobox( "progress", 10*2, icon = icon("line-chart"), color = "blue" ) }) output$infobox2 <- renderinfobox({ infobox( "progress", 10*2, icon = icon("line-chart"), color = "blue" ) }) output$infobox3 <- renderinfobox({ infobox( "progress", 10*2, icon = icon("line-chart"), color = "blue" ) }) output$infobox4 <- renderinfobox({ infobox( "progress", 10*2, icon = icon("line-chart"), color = "blue" ) }) output$infobox5 <- renderinfobox({ infobox( "progress", 10*2, icon = icon("smile-o"), color = "blue" ) }) output$infobox6 <- renderinfobox({ infobox( "progress", 10*2, icon = icon("frown-o"), color = "purple", fill = true ) }) ### cumulative chart points earned output$cearnptschart <- renderchart2({ mydata <- datalist()$sumdata2 interimdata <- mydata %>% filter( metrics == 'earnpts') myplot <- nplot(cumulatives ~ monthvalue, group = 'yearvalue', data = interimdata, type = 'linechart') rm(mydata) rm(interimdata) return(myplot) }) ### cumulative chart count of earn transactions output$cearncountchart <- renderchart2({ mydata <- datalist()$sumdata2 interimdata <- mydata %>% filter( metrics == 'earncount') myplot <- nplot(cumulatives ~ monthvalue, group = 'yearvalue', data = interimdata, type = 'linechart') rm(mydata) rm(interimdata) return(myplot) }) ### cumulative chart points redeemed output$credemptschart <- renderchart2({ mydata <- datalist()$sumdata2 interimdata <- mydata %>% filter( metrics == 'redempts') myplot <- nplot(cumulatives ~ monthvalue, group = 'yearvalue', data = interimdata, type = 'linechart') rm(mydata) rm(interimdata) return(myplot) }) ### cumulative chart count of redemption transactions output$credemcountchart <- renderchart2({ mydata <- datalist()$sumdata2 interimdata <- mydata %>% filter( metrics == 'redemcount') myplot <- nplot(cumulatives ~ monthvalue, group = 'yearvalue', data = interimdata, type = 'linechart') rm(mydata) rm(interimdata) return(myplot) }) ### cumulative chart customer acquisition output$cacquischart <- renderchart2({ mydata <- datalist()$sumdata2 interimdata <- mydata %>% filter( metrics == 'acquiscount') myplot <- nplot(cumulatives ~ monthvalue, group = 'yearvalue', data = interimdata, type = 'linechart') rm(mydata) rm(interimdata) return(myplot) }) ### cumulative chart customer acquisition output$cchurnchart <- renderchart2({ mydata <- datalist()$sumdata2 interimdata <- mydata %>% filter( metrics == 'churncount') myplot <- nplot(cumulatives ~ monthvalue, group = 'yearvalue', data = interimdata, type = 'linechart') rm(mydata) rm(interimdata) return(myplot) }) }) the ui.r file:
### load libraries library(shiny) library(shinythemes) ### body shiny ui shinyui(navbarpage("my sample dashboard", theme = shinytheme('readable'), inverse = true, tabpanel("overview section", fluidrow( column(6, ##current app supports csv, since proof of concept... fileinput(inputid = 'uploadfile', label = 'please upload file') ) ), fluidrow( column(3, h4('main chart goes here'), showoutput('outlineschart', 'nvd3') ), column(3, offset = 5, h5('info boxes go here'), infoboxoutput('infobox1'), infoboxoutput('infobox2'), infoboxoutput('infobox3'), infoboxoutput('infobox4'), infoboxoutput('infobox5'), infoboxoutput('infobox6') ) ), hr(), fluidrow( column(2, h5('earned points chart goes here'), showoutput('cearnptschart', 'nvd3') ), column(2, offset = 4, h5('earn count chart goes here'), showoutput('cearncountchart', 'nvd3') ) ), fluidrow( column(2, h5('redeemed points chart goes here'), showoutput('credemptschart', 'nvd3') ), column(2, offset = 4, h5('redemption count chart goes here'), showoutput('credemcountchart', 'nvd3') ) ), fluidrow( column(2, h5('customer acquisition chart goes here'), showoutput('cacquischart', 'nvd3') ), column(2, offset = 4, h5('customer churn chart goes here'), showoutput('cchurnchart', 'nvd3') ) ) ), tabpanel("details section"), tabpanel("experiments section")) ) edit:
following code generate csv file fed app.
earnptsrange <- 12000:18000 earncountrange <- 1000:10000 redemptsrange <- 10000:20000 redemcountrange <- 10000:20000 churnrange <- 1000:10000 acquisitionrange <- 800:15000 ### obtained dirk eddelbuettel: https://stackoverflow.com/questions/14720983/efficiently-generate-a-random-sample-of-times-and-dates-between-two-dates generatedates <- function(n, st="2014/01/01", et="2015/08/31") { st <- as.posixct(as.date(st)) et <- as.posixct(as.date(et)) dt <- as.numeric(difftime(et,st,unit="sec")) ev <- sort(runif(n, 0, dt)) rt <- st + ev rt[order(rt)] as.date(rt) } ## generate data; 10 readings each month out of 20 months datevalues <- generatedates(200) earnpts <- sample(x = earnptsrange, size = 190) earncount <- sample(x = earncountrange, size = 190) redempts <- sample(x = redemptsrange, size = 190) redemcount <- sample(x = redemcountrange, size = 190) churncount <- sample(x = churnrange, size = 190) acquiscount <- sample(x = acquisitionrange, size = 190) ## merge generated data toydata <- data.frame(datevalues = datevalues, earnpts = earnpts, earncount = earncount, redempts = redempts, redemcount = redemcount, churncount = churncount, acquiscount = acquiscount) ## write data csv file write.csv(x = toydata, file = './toydataset.csv', row.names = false) many in advance.
i have pushed think fix issue on fork of rcharts. solved issues responsiveness , auto-resizing rcharts. way use specifying width , height parameter in showoutput. default width 100% , default height 400px. example call showoutput("mygraph", "nvd3", height=555)
you can download from: https://github.com/clecocel/rcharts
and can install using: devtools::install_github("clecocel/rcharts")
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