为循环添加条件,以使用R中的ClassInt为n个类较少的区域生成类间隔

我在使用R中的classInt库将类分配给不符合循环函数中标准的区间时遇到了问题。如果数据帧子集中的行数小于为类区间定义的类数(n),如何包含自动类的条件?在我的例子中,n=3。下面是一个示例,其中包含一个可以在R中创建的示例数据帧

library(classInt)
library(rlist)
library(dplyr)

##Create dataframe 
Country <- c('Australia', 'Italy', 'Peru', 'China','Australia', 'Italy', 'Peru', 
'China','Australia', 'Italy', 'Peru', 'China','Nigeria','Australia', 'Italy', 'Peru', 
'China')
Time <- c(21, 18, 17, 10,10,15,27,0,2,4,5,7,4,8,9,10,5)
Area <- c("A","A","A","A","B","B","B","B","C","C","C","C","D","D","D","D","D")
DF  <- data.frame(Country, Time, Area)

This should produce this dataframe:


      Country Time Area
 1  Australia   21    A
 2      Italy   18    A
 3       Peru   17    A
 4      China   10    A
 5  Australia   10    B
 6      Italy   15    B
 7       Peru   27    B
 8      China    0    B
 9  Australia    2    C
 10     Italy    4    C
 11      Peru    5    C
 12     China    7    C
 13   Nigeria    4    D
 14 Australia    8    D
 15     Italy    9    D
 16      Peru   10    D
 17     China    5    D


## Split by Country
NewXL <- split(DF,DF$Country)

## Generate the ranges and category/classes for each country
NewXL2 <- list()
for (i in 1:length(NewXL)) { AB <- NewXL[[i]]
#Create condition:
skip_to_next <- FALSE
tryCatch(Classes <- classIntervals(AB$Time, n=3, 
cutlabels=F,style='fisher',factor=F,warnSmallN=F,warnLargeN=F), error = function(e) { 
skip_to_next <<- TRUE})
if(skip_to_next) { next } 
## Classify
# Range and Class for each Absolute population exposed
AB$Range_Abs <- classify_intervals(AB$Time, 3, "fisher", factor = T)
AB$Class_Abs <- classify_intervals(AB$Time,3, "fisher", factor = FALSE)

NewXL2[[i]] <-AB }

此结果是尼日利亚为空的5个国家的列表,因为它只有一行(至少有3个可能是创建间隔的理想选择)。有没有办法为循环编写代码,这样我就可以定义一个类和范围最小值,以便为循环中只有一行的任何数据帧添加?在这种情况下,尼日利亚应该只有一行,所以我可以将3类(最大值)自动分配给单行,范围为[0,4)。下面是循环输出的样子。

  NewXL2
  [[1]]
       Country Time Area Range_Abs Class_Abs
  1  Australia   21    A [15.5,21]         3
  5  Australia   10    B  [5,15.5)         2
  9  Australia    2    C     [2,5)         1
  14 Australia    8    D  [5,15.5)         2

  [[2]]
     Country Time Area Range_Abs Class_Abs
  4    China   10    A  [8.5,10]         3
  8    China    0    B   [0,2.5)         1
  12   China    7    C [2.5,8.5)         2
  17   China    5    D [2.5,8.5)         2

  [[3]]
     Country Time Area Range_Abs Class_Abs
  2    Italy   18    A   [12,18]         3
  6    Italy   15    B   [12,18]         3
  10   Italy    4    C   [4,6.5)         1
  15   Italy    9    D  [6.5,12)         2

  [[4]]
  NULL

  [[5]]
     Country Time Area Range_Abs Class_Abs
  3     Peru   17    A [13.5,22)         2
  7     Peru   27    B   [22,27]         3
  11    Peru    5    C  [5,13.5)         1
  16    Peru   10    D  [5,13.5)         1

这是尼日利亚数据帧在循环后的样子:

[[4]]
    Country Time Area Range_Abs Class_Abs
 13 Nigeria   10    D     [0,4)         3  

 #Merge all lists into long dataframe with class intervals
 NewXL2b <- list.rbind(NewXL2)