R世界地图仅显示单个国家/地区群集

Question

我有一个国家和群集数字矩阵如下所示：

这是我一直在使用的R代码

#ChinaHPI
#ByYear

#packages
library(rgdal)
library(ggplot2)
library(ggmap)
library(readxl)
library(dplyr)
library(showtext) 
library(rworldmap)

fathomcolours_extended <- palette(c("#002b49", "#00af41", "#009fe3", "#8547ad", "#f7323f", "#ffb819", "#007298", "#ff7f3f", "#e6007e", "#b28978", "#ffe500", "#00a891", "#ffa891", "#bbff91"))

f2 <- palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B"))



#f1
#f2
#f3
#f4
#f5
#f6
#f7
#f8
#f9
#f10
#f11
#f12


#chart format
ditch_the_axes <- theme(
  axis.text = element_blank(),
  axis.line = element_blank(),
  axis.ticks = element_blank(),
  panel.border = element_blank(),
  panel.grid = element_blank(),
  axis.title = element_blank()
)

library(readxl)
Data <- read_excel("Data for Map.xlsx")
#subset data by year
Data_2006 <- Data[c(1,2,3)]
Data_2007 <- Data[c(1,2,4)]
Data_2008 <- Data[c(1,2,5)]
Data_2009 <- Data[c(1,2,6)]
Data_2010 <- Data[c(1,2,7)]
Data_2011 <- Data[c(1,2,8)]
Data_2012 <- Data[c(1,2,9)]
Data_2013 <- Data[c(1,2,10)]
Data_2014 <- Data[c(1,2,11)]
Data_2015 <- Data[c(1,2,12)]
Data_2016 <- Data[c(1,2,13)]
Data_2017 <- Data[c(1,2,14)]

#rworldmap
#2006
map2006 <- joinCountryData2Map(Data_2006, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2006, nameColumnToPlot = "2006", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2007
map2007 <- joinCountryData2Map(Data_2007, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2007, nameColumnToPlot = "2007", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2008
map2008 <- joinCountryData2Map(Data_2008, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2008, nameColumnToPlot = "2008", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2009
map2009 <- joinCountryData2Map(Data_2009, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2009, nameColumnToPlot = "2009", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2010
map2010 <- joinCountryData2Map(Data_2010, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2010, nameColumnToPlot = "2010", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2011
map2011 <- joinCountryData2Map(Data_2011, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2011, nameColumnToPlot = "2011", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2012
map2012 <- joinCountryData2Map(Data_2012, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2012, nameColumnToPlot = "2012", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2013
map2013 <- joinCountryData2Map(Data_2013, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2013, nameColumnToPlot = "2013", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2014
map2014 <- joinCountryData2Map(Data_2014, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2014, nameColumnToPlot = "2014", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2015
map2015 <- joinCountryData2Map(Data_2015, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2015, nameColumnToPlot = "2015", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2016
map2016 <- joinCountryData2Map(Data_2016, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2016, nameColumnToPlot = "2016", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

#2017
map2017 <- joinCountryData2Map(Data_2017, joinCode = "ISO3" , nameJoinColumn = "X__2")
mapCountryData(map2017, nameColumnToPlot = "2017", catMethod = c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14), colourPalette = palette(c("#7D5647", "#B28978", "#FFE500", "#FFBB19", "#009FE3", "#007298", "#002B49", "#FF7F3F", "#F7323F", "#E6007E", "#8547AD", "#00A891", "#00AF41", "#00763B")), missingCountryCol = "#efefef") + ditch_the_axes

基本上我想以美国为例，以及美国多年来的集群。例如，如果美国在2006年的第7组中，我希望世界地图只能在2006年为美国和第7组中的其他国家着色。我一直在尝试一种解决方法，但可能有一种更简单的方法，任何帮助非常感谢