僅針對某些州使用ggplot2繪制美國地圖

我有以下代碼：

library(ggplot2)
library(ggsn) # for scale bar `scalebar`
library(fiftystater)
library(tidyverse)

ggplot(data= data.to.work.african, aes(map_id = State_L))   
ggtitle("African American")  
geom_map(aes(fill = Suicide_Rate_By_Pop),  color= "white", map = fifty_states)   
expand_limits(x = fifty_states$long, y = fifty_states$lat)  
coord_map()  
geom_text(data = fifty_states %>%
          group_by(id) %>%
          summarise(lat = mean(c(max(lat), min(lat))),
                    long = mean(c(max(long), min(long)))) %>%
          mutate(State_L = id) %>%
          left_join(data.to.work.african, by = "State_L"),  size=2, 
          aes(x = long, y = lat, label = paste(Acronym, Suicide_Rate_By_Pop, sep = '\n'))
         )  
scale_x_continuous(breaks = NULL)   
scale_y_continuous(breaks = NULL)  
labs(x = "", y = "")   
labs(fill = "Suicides Rate by 100,000 inhabitants") 
  
scale_fill_gradientn(colours=rev(heat.colors(10)),na.value="grey90",
                     guide = guide_colourbar(barwidth = 25, barheight = 0.4,
                                             #put legend title on top of legend
                                             title.position = "top")
                                            )  
theme(legend.position = "bottom",
      legend.title=element_text(size=10), 
      legend.text=element_text(size=08))

結果是：

在我的資料集中，我沒有所有州的資訊，因為這樣，地圖上的某些州會呈現“NA”結果并且沒有圍繞它自己的區域排列。

我將如何解決這個問題？我想為我的資料集上沒有行的那個州提供州名，比如 MT。

資料

# The data extracted from dput is:
structure(list(Acronym = c("AL", "AK", "AR", "CA", "CO", "CT", 
"DE", "DC", "FL", "GA", "HI", "IL", "IN", "IA", "KS", "KY", "LA", 
"MD", "MA", "MI", "MS", "MO", "NE", "NV", "NH", "NJ", "NY", "NC", 
"OH", "OK", "OR", "PA", "RI", "SC", "TN", "TX", "VA", "WA", "WI"
), State_U = c("Alabama", "Alaska", "Arkansas", "California", 
"Colorado", "Connecticut", "Delaware", "District of Columbia", 
"Florida", "Georgia", "Hawaii", "Illinois", "Indiana", "Iowa", 
"Kansas", "Kentucky", "Louisiana", "Maryland", "Massachusetts", 
"Michigan", "Mississippi", "Missouri", "Nebraska", "Nevada", 
"New Hampshire", "New Jersey", "New York", "North Carolina", 
"Ohio", "Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", 
"South Carolina", "Tennessee", "Texas", "Virginia", "Washington", 
"Wisconsin"), State_L = c("alabama", "alaska", "arkansas", "california", 
"colorado", "connecticut", "delaware", "district of columbia", 
"florida", "georgia", "hawaii", "illinois", "indiana", "iowa", 
"kansas", "kentucky", "louisiana", "maryland", "massachusetts", 
"michigan", "mississippi", "missouri", "nebraska", "nevada", 
"new hampshire", "new jersey", "new york", "north carolina", 
"ohio", "oklahoma", "oregon", "pennsylvania", "rhode island", 
"south carolina", "tennessee", "texas", "virginia", "washington", 
"wisconsin"), Race = c("African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American", "African American", "African American", "African American", 
"African American"), Suicide_Rates = c(14L, 1L, 4L, 42L, 3L, 
4L, 1L, 1L, 26L, 33L, 2L, 20L, 6L, 1L, 2L, 6L, 21L, 20L, 6L, 
23L, 14L, 9L, 2L, 4L, 1L, 9L, 27L, 27L, 14L, 3L, 1L, 24L, 3L, 
9L, 13L, 40L, 24L, 7L, 2L), Population = c(4452173L, 627963L, 
2678588L, 33987977L, 4326921L, 3411777L, 786373L, 572046L, 16047515L, 
8227303L, 1213519L, 12434161L, 6091866L, 2929067L, 2693681L, 
4049021L, 4471885L, 5311034L, 6361104L, 9952450L, 2848353L, 5607285L, 
1713820L, 2018741L, 1239882L, 8430621L, 19001780L, 8081614L, 
11363543L, 3454365L, 3429708L, 12284173L, 1050268L, 4024223L, 
5703719L, 20944499L, 7105817L, 5910512L, 5373999L), Suicide_Rate_By_Pop = c(0, 
0, 0, 0.124, 0, 0, 0, 0, 0.162, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0.142, 0, 0, 0, 0, 0, 0, 0, 0, 0.191, 0, 
NA, 0)), row.names = c(1L, 4L, 11L, 14L, 18L, 22L, 26L, 28L, 
30L, 34L, 38L, 44L, 48L, 51L, 54L, 58L, 61L, 65L, 69L, 73L, 80L, 
84L, 88L, 92L, 96L, 99L, 106L, 110L, 116L, 119L, 123L, 127L, 
131L, 133L, 138L, 142L, 150L, 153L, 158L), class = "data.frame")

#  I read it's .csv using
data.to.work.african  <- read.csv2("dataSuicideAfrican.csv", sep = ';', 
                                stringsAsFactors=FALSE,  
                                header = TRUE)

uj5u.com熱心網友回復：

問題不在于ggplot代碼本身，而在于資料。在標簽回傳的geom_text部分中，因為您當前的資料只有 39 個狀態，而資料有 51 個。您可以通過以下方式克服這個問題：ggplotNAdata.to.work.africanfifty_states

1. 使用識別缺失狀態setdiff()
2. 將這些狀態名稱添加到資料集中的State_L列中data.to.work.african
3. state.abb()使用函式將州名轉換為首字母縮寫詞

重新運行您的代碼，一切都很好！

代碼：

# Find missing states
missing_states <- setdiff(unique(fifty_states$id), data.to.work.african$State_L)

#> missing_states
# [1] "arizona"       "idaho"         "maine"         "minnesota"     "montana"       "new mexico"   
# [7] "north dakota"  "south dakota"  "utah"          "vermont"       "west virginia" "wyoming"  

# add missing states to `data.to.work.african` dataset
currows <- nrow(data.to.work.african) # current number of rows

# add state names
data.to.work.african[(currows 1):(currows   length(missing_states)),"State_L"] <- missing_states

# add acronyms
data.to.work.african[(currows 1):(currows   length(missing_states)),"Acronym"] <- state.abb[match(missing_states,tolower(state.name))]

重新運行您的代碼：

請注意，該fiftystater包不適用于當前版本的 R，但fifty_states可以在 Github上找到資料

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