Question

我正在R中构建一个交互式闪亮应用，并希望显示两个散点图：

整个数据集（左）
Zoomed Region（右）

左图不应更改，用于为右图选择不同的区域。它类似于示例代码（http://shiny.rstudio.com/gallery/plot-interaction-zoom.html）中的 plot2 和 plot3 。

我想显示两个图的统计数据和线性回归，并根据右图中选择的区域更新缩放图的信息。我想到这样做的一种方法是使用画笔对原始数据（df_mtcars）进行子集化并将其保存为新的数据帧（df_mtcars2）。

我对R仍然有点新，并且无法找到关于此的很多信息。我发现了一种用ggvis（here）做类似事情的方法，但有没有办法用ggplot2做呢？如果有更简单的方法，我也会接受其他建议。

这是我的代码：

app.R

library(ggplot2)
library(dplyr)

df_mtcars <- mtcars %>%
  select(wt,mpg)

df_mtcars2 <- df_mtcars
#choose selection based on brushed/zoomed data

ui <- fluidPage(
  fluidRow(
    column(width = 12, class = "well",
       h4("Left plot controls right plot"),
       fluidRow(
         column(width = 6,
                h5("Entire Dataset (left)"),
                plotOutput("plot1", height = 350,
                           brush = brushOpts(
                             id = "plot1_brush",
                             resetOnNew = TRUE
                           )
                )
         ),
         column(width = 6,
                h5("Zoomed Region (right)"),
                plotOutput("plot2", height = 350)
         )
       ),
       fluidRow(
         column(width = 6,
                verbatimTextOutput("summary1")),
         column(width = 6, 
                verbatimTextOutput("summary2"))
       )    
    )
  )
)
server <- function(input, output) {

# Linked plots (left and right)
ranges <- reactiveValues(x = NULL, y = NULL)

output$plot1 <- renderPlot({
  ggplot(df_mtcars, aes(wt, mpg)) + geom_point() + 
  geom_smooth(method = "lm", color = "red")
})

output$plot2 <- renderPlot({
  #dataset should be changed to df_mtcars2
  ggplot(df_mtcars2, aes(wt, mpg)) + geom_point() + 
    geom_smooth(method = "lm", color = "blue") +
    # if using df_mtcars2, should get rid of coord_cartesian range (?)
    coord_cartesian(xlim = ranges$x, ylim = ranges$y) 
})

# When a double-click happens, check if there's a brush on the plot.
# If so, zoom to the brush bounds; if not, reset the zoom.
observe({
  brush <- input$plot1_brush
  if (!is.null(brush)) {
    ranges$x <- c(brush$xmin, brush$xmax)
    ranges$y <- c(brush$ymin, brush$ymax)
  } else {
    ranges$x <- NULL
    ranges$y <- NULL
  }
})

output$summary1 <- renderPrint({
  summary(df_mtcars)
  #how to add linear equation and R^2 (?)
})

output$summary2 <- renderPrint({
  summary(df_mtcars2) #should be df_mtcars2
  #how to add linear equation and R^2 (?)
 })
}

Answer 1

要获取刷新数据，您可以使用brushedPoint函数，它输出刷子点的行号。然后，您可以直接转到ggplot和plot2中的summary2。这是一个例子：

server <- function(input, output) {

  values <- reactiveValues(data=df_mtcars)

  output$plot1 <- renderPlot({
    ggplot(df_mtcars, aes(wt, mpg)) + geom_point() + 
      geom_smooth(method = "lm", color = "red")
  })

  output$plot2 <- renderPlot({
    ggplot(values$data, aes(wt, mpg)) + geom_point() + 
      geom_smooth(method = "lm", color = "blue") 
  })

  observe({
    if (!is.null(input$plot1_brush)) {      
      values$data <- brushedPoints(df_mtcars, input$plot1_brush)
    } else {     
      values$data <- df_mtcars
    }
  })

  output$summary1 <- renderPrint({
    summary(df_mtcars)
  })

  output$summary2 <- renderPrint({
    summary(values$data)
  })
}

要显示线性方程式，您可以在verbatimTextOutput("summary2_lm")中添加ui.R，在server.R输出中添加线性方程式和R2系数：

output$summary2_lm <- renderPrint({
    m <- lm(mpg ~ wt, values$data);
    paste("y=",format(coef(m)[1], digits = 2),"x+",format(coef(m)[2], digits = 2)," R2=",format(summary(m)$r.squared, digits = 3))
  })

将等式和R2作为字符串的函数的灵感来自docs on BodyParser

基于缩放交互的子集数据框

1 个答案: