发光：自定义NearPoints的输出

问题描述 投票：0回答：1

我包括一个相当冗长的示例，但至少它是完全独立的。我的问题是：我可以以某种方式自定义近点的输出吗？它已经非常接近我的想法，但是我的问题是是否可以自定义近点的输出（这很丑陋）。我不需要关于小标题的所有内容，例如[

2017年价值2097亿欧元

到目前为止，我的谷歌搜索工作无济于事，因此任何建议都值得赞赏。谢谢！



library(shiny)
library(Cairo)   # For nicer ggplot2 output when deployed on Linux
library(tidyverse)
library(scales)

my_ggplot_theme2 <- function(legend_coord){
    theme_bw()+

    theme(legend.title = element_text(vjust=1,lineheight=1, size=14 ),
          panel.grid.minor = element_blank(),
          plot.title = element_text(lineheight=.8, size=24, face="bold",
          vjust=1),legend.text = element_text(vjust=.4,lineheight=1,size = 14 ),
          axis.title.x = element_text(size = 20, vjust=1),
                axis.title.y = element_text(size = 20, angle=90, vjust=1),
                axis.text.x = element_text(size=15, colour="black", vjust=1),
          axis.text.y = element_text(size=15, colour="black", hjust=1),
                          legend.position = legend_coord,
           strip.background = element_rect(colour = 'blue',
                           fill = 'white', size = 1, linetype=1),
                strip.text.x = element_text(colour = 'red', angle = 0,
                                     size = 12, hjust = 0.5,
                    vjust = 0.5, face = 'bold'),
                   strip.text.y = element_text(colour = 'red', angle = 0,
                    size = 12, hjust = 0.5,
                    vjust = 0.5, face = 'bold'),

          )
}




df_ini <- structure(list(reporterlabel = c("USA", "USA", "USA", "USA", 
"USA", "USA", "USA", "USA", "China", "China", "USA", "USA", "USA", 
"USA", "USA", "USA", "China", "China", "USA", "USA", "USA", "USA", 
"China", "China", "China", "China", "China", "China", "China", 
"China", "China", "China", "China", "China", "China", "China", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "China", "China", "China", 
"China", "China", "China", "China", "China", "China", "China", 
"China", "China", "China", "China", "EU28", "EU28", "China", 
"China", "China", "China", "USA", "USA", "USA", "USA", "USA", 
"USA", "USA", "USA", "USA", "USA", "EU28", "EU28", "EU28", "EU28", 
"EU28", "EU28", "USA", "USA", "EU28", "EU28", "USA", "USA", "EU28", 
"EU28", "EU28", "EU28", "EU28", "EU28", "USA", "USA", "USA", 
"USA", "EU28", "EU28", "EU28", "EU28", "EU28", "EU28", "EU28", 
"EU28", "EU28", "EU28", "EU28", "EU28", "EU28", "EU28", "EU28", 
"EU28", "EU28", "EU28", "EU28", "EU28", "China", "China", "China", 
"China", "USA", "USA", "USA", "USA", "China", "China", "USA", 
"USA", "China", "China", "USA", "USA", "China", "China", "USA", 
"USA", "USA", "USA", "USA", "USA", "China", "China", "China", 
"China", "USA", "USA", "USA", "USA", "China", "China", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "China", "China", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan"), partnerlabel = c("World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "World", "World", "World", 
"World", "World", "World", "World", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Switzerland", "Switzerland", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Japan", "Japan", "Switzerland", "Switzerland", 
"Japan", "Japan", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Japan", "Japan", 
"Japan", "Japan", "Switzerland", "Switzerland", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Japan", "Japan", "Japan", "Japan", "Japan", 
"Japan", "Japan", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland", "Switzerland", "Switzerland", "Switzerland", "Switzerland", 
"Switzerland"), year = c(2018L, 2018L, 2017L, 2017L, 2015L, 2015L, 
2016L, 2016L, 2018L, 2018L, 2012L, 2012L, 2014L, 2014L, 2013L, 
2013L, 2017L, 2017L, 2011L, 2011L, 2010L, 2010L, 2014L, 2014L, 
2013L, 2013L, 2015L, 2015L, 2016L, 2016L, 2012L, 2012L, 2011L, 
2011L, 2010L, 2010L, 2012L, 2012L, 2018L, 2018L, 2013L, 2013L, 
2011L, 2011L, 2014L, 2014L, 2017L, 2017L, 2015L, 2015L, 2016L, 
2016L, 2010L, 2010L, 2018L, 2018L, 2017L, 2017L, 2011L, 2011L, 
2012L, 2012L, 2010L, 2010L, 2016L, 2016L, 2015L, 2015L, 2016L, 
2016L, 2014L, 2014L, 2013L, 2013L, 2017L, 2017L, 2018L, 2018L, 
2016L, 2016L, 2015L, 2015L, 2012L, 2012L, 2017L, 2017L, 2018L, 
2018L, 2012L, 2012L, 2013L, 2013L, 2015L, 2015L, 2014L, 2014L, 
2014L, 2014L, 2013L, 2013L, 2011L, 2011L, 2010L, 2010L, 2011L, 
2011L, 2010L, 2010L, 2011L, 2011L, 2018L, 2018L, 2017L, 2017L, 
2010L, 2010L, 2016L, 2016L, 2012L, 2012L, 2015L, 2015L, 2013L, 
2013L, 2014L, 2014L, 2013L, 2013L, 2016L, 2016L, 2018L, 2018L, 
2016L, 2016L, 2018L, 2018L, 2017L, 2017L, 2014L, 2014L, 2015L, 
2015L, 2017L, 2017L, 2014L, 2014L, 2013L, 2013L, 2012L, 2012L, 
2011L, 2011L, 2012L, 2012L, 2011L, 2011L, 2010L, 2010L, 2015L, 
2015L, 2017L, 2017L, 2016L, 2016L, 2015L, 2015L, 2018L, 2018L, 
2012L, 2012L, 2010L, 2010L, 2011L, 2011L, 2013L, 2013L, 2014L, 
2014L, 2010L, 2010L), trade = c("i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value", "i_value", "e_value", "i_value", 
"e_value", "i_value", "e_value"), value = c(2153.033680273, 1409.176796262, 
2073.705710368, 1368.155269117, 2020.426481323, 1356.080871475, 
1977.755888676, 1313.306256844, 1806.965668188, 2117.979322303, 
1771.689509717, 1203.146360193, 1767.169505028, 1219.784616324, 
1707.981350627, 1188.487972287, 1621.780725645, 2018.318404554, 
1586.173935964, 1065.002559117, 1484.588368409, 963.634985291, 
1477.685507736, 1763.810407469, 1467.7361096, 1664.529933147, 
1443.678047307, 2055.46740743, 1435.956424248, 1930.251015449, 
1414.495661466, 1595.650735082, 1251.027163365, 1364.425779918, 
1051.451510212, 1190.649622597, 689.629865699, 621.590442779, 
657.302694949, 624.931817975, 626.716997393, 538.071974436, 614.222575221, 
590.922220402, 611.382793901, 519.543999785, 594.12699826, 617.937009274, 
584.037763765, 563.136061217, 548.257633382, 582.645761187, 523.535979271, 
580.653879852, 152.818513692, 124.948863726, 146.740834246, 121.739056586, 
139.662191575, 105.81182183, 138.330347187, 117.924386484, 132.989383588, 
90.716169952, 131.469896106, 117.099527509, 128.630611328, 122.484952311, 
122.561022748, 143.220309136, 122.458137067, 112.496590186, 122.143972732, 
112.877296035, 120.86712417, 59.923778223, 120.741954319, 63.477320952, 
119.434301319, 57.154447135, 118.179134496, 56.306292279, 113.972363801, 
54.464342198, 111.836134513, 150.967565896, 110.1018017, 157.478369565, 
106.902278992, 134.948590308, 104.34034559, 49.104801983, 103.301313019, 
151.66367911, 100.868435476, 50.302896129, 97.515304235, 141.598887161, 
95.480368544, 170.052458043, 94.586903966, 143.012571618, 93.200648714, 
45.670513691, 92.620610256, 47.2699258, 86.349819222, 111.557347675, 
70.428774448, 49.020854681, 69.930994346, 64.720814854, 68.356634924, 
60.559417639, 67.049850532, 43.980181628, 65.864669524, 57.993483823, 
65.049885678, 55.650487632, 59.650510137, 56.492788279, 56.595873541, 
54.029698964, 56.48397519, 53.296964381, 42.259609603, 2.657949611, 
36.22046978, 2.938986358, 35.091273848, 18.865400225, 33.121737046, 
20.531060435, 32.763819035, 3.488139441, 32.062628223, 19.218557122, 
30.573392992, 2.339371756, 28.420871049, 20.120244253, 24.915989434, 
2.854051193, 23.69832177, 16.71585985, 21.513645993, 20.014475478, 
20.223146701, 20.56983734, 19.609108427, 2.667828353, 17.80879672, 
2.730342186, 17.681697192, 17.635480366, 14.762842272, 15.63045938, 
8.244246492, 2.880406036, 6.919343595, 4.506222441, 6.910251482, 
2.843246229, 6.658258726, 2.432435039, 6.573509392, 3.210703583, 
6.401458799, 3.405673417, 6.366489807, 2.292004086, 5.629922682, 
6.624220767, 5.486891886, 2.501314565, 5.438397721, 2.28086752, 
5.12168412, 5.882474702)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -180L))


reporters <- df_ini$reporterlabel %>% unique
partners <- df_ini$partnerlabel %>% unique


year_range <- seq(min(df_ini$year), max(df_ini$year))

impexp <- df_ini$trade %>% unique


ui <- fluidPage(    
    sidebarLayout(
  sidebarPanel(       
    selectInput("reporterlabel",
            "Reporter:",
            reporters ## , multiple=T
            ),
selectInput("partnerlabel",
            "Partner:",
            partners),

selectInput("tradetype",
            "Import/Export:",
            impexp) ,

selectizeInput("years",
            "Years:",
            year_range, multiple=T, selected=year_range) 

)
,

mainPanel(
    plotOutput("tradeplot" ,
                hover = "plot_hover"
               ## click = "plot_click"
               ) ,
    verbatimTextOutput("info")
)
)
)



server <- function(input, output) {

  filtered_data <- reactive({
      df_ini %>% filter(reporterlabel %in% input$reporterlabel,
                        partnerlabel %in% input$partnerlabel,
                        trade %in% input$tradetype,
                        year %in% input$years )
  })


    output$tradeplot <- renderPlot({
  filtered_data() %>%
    ggplot(aes(x = year, y = value)) +
      geom_point(size=3) +
      geom_line(size=1) +
      my_ggplot_theme2("right")+
      scale_y_continuous(breaks=pretty_breaks(n=5))+
      scale_x_continuous(breaks = function(x) unique(floor(pretty(x))))+
      xlab("Year")+
      ylab("b \u20ac")+
    labs(title = "Trade Value")
})



  output$info <- renderPrint({
    # With ggplot2, no need to tell it what the x and y variables are.
    # threshold: set max distance, in pixels
    # maxpoints: maximum number of rows to return
    # addDist: add column with distance, in pixels
    nearPoints(filtered_data(), input$plot_hover, threshold = 10, maxpoints = 1,
               addDist = F)
  }) 


}




shinyApp(ui = ui, server = server)
r shiny interactive
1个回答
0
投票

DT程序包可以使表格（小方块？）看起来更有光泽。尽管您可能希望舍入value列，但您的应用程序仅进行了几处更改，看起来效果会好一些。

有关DT和闪亮的更多信息：https://rstudio.github.io/DT/shiny.html

DT shiny

library(DT)      ####### <- ADDED THIS PACKAGE


ui <- fluidPage(    
    sidebarLayout(
        sidebarPanel(       
            selectInput("reporterlabel",
                        "Reporter:",
                        reporters ## , multiple=T
            ),
            selectInput("partnerlabel",
                        "Partner:",
                        partners),

            selectInput("tradetype",
                        "Import/Export:",
                        impexp) ,

            selectizeInput("years",
                           "Years:",
                           year_range, multiple=T, selected=year_range) 

        )
        ,

        mainPanel(
            plotOutput("tradeplot" ,
                       hover = "plot_hover"
                       ## click = "plot_click"
            ) ,
            DTOutput("info")   #### <- CHANGED THIS ####
        )
    )
)





    output$info <- renderDT({  ##### <- CHANGED THIS #########

        # With ggplot2, no need to tell it what the x and y variables are.
        # threshold: set max distance, in pixels
        # maxpoints: maximum number of rows to return
        # addDist: add column with distance, in pixels
        nearPoints(filtered_data(), input$plot_hover, threshold = 10, maxpoints = 1,
                   addDist = F)
    }) 


}




shinyApp(ui = ui, server = server)
最新问题
© www.soinside.com 2019 - 2024. All rights reserved.