Построение ежемесячных процентов в блестящих R - PullRequest
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Построение ежемесячных процентов в блестящих R

0 голосов
/ 23 октября 2018

У меня блестящее приложение с четырьмя различными графиками на Shinydashboard.Я хочу, чтобы все графики были реагирующими на основе данных слайдера за год.Я получил это, чтобы работать отлично ... Однако я хочу, чтобы один из графиков имел месяцы по оси X вместо лет, как другие, но все же реагировал на год sliderInput и соответственно фильтровал фрейм данных.У меня это тоже работает, но я не могу понять, как изменить месяцы с числа на фактическое название месяца на оси х.

Это то, что я хочу (не так, как на прямоугольном графике просто нужна ось X):

enter image description here

Пример данных: 

    df1<-structure(list(stdate = structure(c(16611, 16611, 16611, 16615, 
16615, 16615, 14004, 14004, 14004, 16616, 16616, 16616, 16616, 
16616, 16616, 17485, 17483, 16678, 14000, 14000, 14000, 17211, 
17210, 16615, 16611, 16756, 14098, 16674, 16674, 14096), class = "Date"), 
    sttime = structure(c(37800, 37800, 37800, 35100, 35100, 35100, 
    42600, 42600, 42600, 38700, 38700, 38700, 32400, 32400, 32400, 
    35400, 33000, 49800, 34200, 34200, 34200, 37800, 30600, 35100, 
    37800, 37800, 35400, 37800, 32400, 37200), class = c("hms", 
    "difftime"), units = "secs"), locid = c("USGS-01388500", 
    "USGS-01388500", "USGS-01388500", "USGS-01464585", "USGS-01464585", 
    "USGS-01464585", "USGS-01464515", "USGS-01464515", "USGS-01464515", 
    "USGS-01407330", "USGS-01407330", "USGS-01407330", "USGS-01466500", 
    "USGS-01466500", "USGS-01466500", "USGS-01387500", "USGS-01395000", 
    "USGS-01400860", "USGS-01377000", "USGS-01377000", "USGS-01377000", 
    "USGS-01367625", "USGS-01398000", "USGS-01464585", "USGS-01388500", 
    "USGS-01390630", "USGS-01396090", "USGS-01407810", "USGS-01407821", 
    "USGS-01391540"), charnam = c("Chloride", "Total dissolved solids", 
    "Specific conductance", "Chloride", "Total dissolved solids", 
    "Specific conductance", "Specific conductance", "Total dissolved solids", 
    "Chloride", "Chloride", "Total dissolved solids", "Specific conductance", 
    "Chloride", "Total dissolved solids", "Specific conductance", 
    "Specific conductance", "Specific conductance", "Specific conductance", 
    "Specific conductance", "Total dissolved solids", "Chloride", 
    "Specific conductance", "Specific conductance", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Specific conductance", 
    "Specific conductance", "Specific conductance", "Specific conductance"
    ), val = c(109, 294, 525, 31.9, 119, 184, 226, 155, 33, 36.4, 
    155, 203, 3.38, 43, 41, 674, 466, 312, 540, 328, 105, 844, 
    683, 100, 275, 432, 342, 200, 237, 805), valunit = c("mg/l", 
    "mg/l", "uS/cm @25C", "mg/l", "mg/l", "uS/cm @25C", "uS/cm @25C", 
    "mg/l", "mg/l", "mg/l", "mg/l", "uS/cm @25C", "mg/l", "mg/l", 
    "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", 
    "mg/l", "mg/l", "uS/cm @25C", "uS/cm @25C", "mg/l", "mg/l", 
    "mg/l", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C", "uS/cm @25C"
    ), LatDeg = c(40.969722, 40.969722, 40.969722, 40.041667, 
    40.041667, 40.041667, 40.176944, 40.176944, 40.176944, 40.319167, 
    40.319167, 40.319167, 39.885, 39.885, 39.885, 41.098056, 
    40.618889, 40.418333, 40.999167, 40.999167, 40.999167, 41.040278, 
    40.473333, 40.041667, 40.969722, NA, 40.860556, 40.2075, 
    40.211667, 40.867778), LongDeg = c(-74.281944, -74.281944, 
    -74.281944, -74.766944, -74.766944, -74.766944, -74.598889, 
    -74.598889, -74.598889, -74.160556, -74.160556, -74.160556, 
    -74.505278, -74.505278, -74.505278, -74.162778, -74.283333, 
    -74.787222, -73.989167, -73.989167, -73.989167, -74.629722, 
    -74.827778, -74.766944, -74.281944, NA, -74.76, -74.328889, 
    -74.295833, -74.094722), HUC14 = c("HUC02030103110020", "HUC02030103110020", 
    "HUC02030103110020", "HUC02040201100030", "HUC02040201100030", 
    "HUC02040201100030", "HUC02040201060020", "HUC02040201060020", 
    "HUC02040201060020", "HUC02030104070070", "HUC02030104070070", 
    "HUC02030104070070", "HUC02040202030070", "HUC02040202030070", 
    "HUC02040202030070", "HUC02030103100030", "HUC02030104050060", 
    "HUC02030105090020", "HUC02030103170060", "HUC02030103170060", 
    "HUC02030103170060", "HUC02020007010010", "HUC02030105030060", 
    "HUC02040201100030", "HUC02030103110020", NA, "HUC02030105010040", 
    "HUC02030104100010", "HUC02030104100010", "HUC02030103140070"
    ), WMA = c(3L, 3L, 3L, 20L, 20L, 20L, 20L, 20L, 20L, 12L, 
    12L, 12L, 19L, 19L, 19L, 3L, 7L, 10L, 5L, 5L, 5L, 2L, 8L, 
    20L, 3L, NA, 8L, 12L, 12L, 4L), year = c(2015, 2015, 2015, 
    2015, 2015, 2015, 2008, 2008, 2008, 2015, 2015, 2015, 2015, 
    2015, 2015, 2017, 2017, 2015, 2008, 2008, 2008, 2017, 2017, 
    2015, 2015, 2015, 2008, 2015, 2015, 2008), month = c(6, 6, 
    6, 6, 6, 6, 5, 5, 5, 6, 6, 6, 6, 6, 6, 11, 11, 8, 5, 5, 5, 
    2, 2, 6, 6, 11, 8, 8, 8, 8)), .Names = c("stdate", "sttime", 
"locid", "charnam", "val", "valunit", "LatDeg", "LongDeg", "HUC14", 
"WMA", "year", "month"), row.names = c(NA, -30L), class = c("tbl_df", 
"tbl", "data.frame"))

Что я пробовал: 

parameters<-unique(df1$charnam)


sidebar<-dashboardSidebar(
  selectInput("parameter_input","Select Parameter",
              parameters,selected = "Chloride"),
  sliderInput("date","Select Year Range",
              min = min(df1$year),
              max = max(df1$year),
              value = c(min,max),
              sep = "",
              step = 1)
)
header<-dashboardHeader()
body<- dashboardBody(
          box(plotOutput("plot1")))

ui<-dashboardPage(header=header,
                  sidebar = sidebar,
                  body = body)



server<- function(input,output,session){

  month_percent_over<-reactive({
      df1%>%
        filter(charnam == input$parameter_input)%>%
        mutate(val = as.numeric(val),greater = val >230) %>%
        group_by(month,year) %>%
        summarize(n_greater = sum(greater),percentage=mean(greater)*100)%>%
        filter(year >= input$date[1])%>%
        filter(year <= input$date[2])

  }) 




### Creates % > Standard month plots ###
output$plot1<- renderPlot({
    ggplot(data = month_percent_over(),aes(x=month,y = percentage))+
      geom_point(aes(colour="blue"),size=3,stat = "identity")+
      geom_smooth(method = "lm", se=FALSE,linetype = "dashed",aes(y=percentage,colour="red"))+
      scale_color_manual("",
                         #breaks= c("per"),
                         values = c("blue","red"),
                         labels=c("% Samples > Standard","Trendline"),
                         guide=guide_legend(override.aes=list(linetype=c(0,2), lwd=c(3,0.5))))+
      scale_x_discrete(labels=c("1" = "January", "2" = "Feburary",
                                "3" = "March","4"="April","5"="May",
                                "6"="June","7"="July",
                                "8"="August","9"="September","10"="October",
                                "11"="November","12"="December"))


})
}
shinyApp(ui,server)
...