小编CER*_*CER的帖子

我遇到了以下可能重复但无法找到答案的问题

df <-structure(list(year = c(1980, 1980, 1983, 1983, 1986, 1986), 
name = c("aa", "bb", "aa", "bb", "aa", "bb"), value = c(1, 
2, 4, 3, 2, 5)), .Names = c("year", "name", "value"), row.names = c(NA, 
-6L), class = "data.frame")


  year name value
  1980   aa     1
  1980   bb     2
  1983   aa     4
  1983   bb     3
  1986   aa     2
  1986   bb     5

我希望用过去几年的价值填补之间缺失的年份,以获得类似的东西

  year name value
  1980   aa     1
  1980   bb     2
  1981   aa     1
  1981   bb     2
  1982   aa     1
  1982   bb …

我有一个相当简单的问题，但无法弄清楚为什么它不起作用

library(shiny)
library(leaflet)


pts <- data.frame(
  id = letters[seq(from = 1, to = 10)],
  x = rnorm(10, mean = -93.625),
  y = rnorm(10, mean = 42.0285),
  stringsAsFactors = F
)




# Define UI
ui <- fluidPage(uiOutput('Select'))

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

  output$Select <- renderUI({
    Range <- sort(unique(pts$id))
    selectInput("dataselect",
                "select",
                choices = Range,
                selected = 'a')
  })


  mydata <- reactive({
    if (input$dataselect != 'a') {
      data <- pts[pts$id == input$dataselect,]
    }
    else
    {
      data <- pts
    }


  })

  observe(print(mydata())) …

尝试使用交叉折叠重采样并拟合 Ranger 包中的随机森林。无需重新采样的拟合工作正常，但一旦我尝试重新采样拟合，它就会失败并出现以下错误。

考虑以下df

df<-structure(list(a = c(1379405931, 732812609, 18614430, 1961678341, 
2362202769, 55687714, 72044715, 236503454, 61988734, 2524712675, 
98081131, 1366513385, 48203585, 697397991, 28132854), b = structure(c(1L, 
6L, 2L, 5L, 7L, 8L, 8L, 1L, 3L, 4L, 3L, 5L, 7L, 2L, 2L), .Label = c("CA", 
"IA", "IL", "LA", "MA", "MN", "TX", "WI"), class = "factor"), 
    c = structure(c(2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
    2L, 2L, 2L, 1L), .Label = c("R", "U"), class = "factor"), 
    d = structure(c(3L, 3L, …