Plotting US Map with ggplot2 for some states only

Question

I have the following code:

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))

and the result is:

In my data set I did not have information for all states, because this, some states on map present the 'NA' result and has not line around it's own area.

How I would fix this problem? I would like to present the name of state for that one that has no line on my data set, like MT.

Data

# 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)

Answer 1

The problem is not in the ggplot code per se, rather the data. In the geom_text part of the ggplot the labels return NA because your current data.to.work.african data have only 39 states, and the fifty_states data has 51. You can overcome this by:

1. Identifying the missing states using setdiff()
2. Adding these state names to your State_L column in data.to.work.african dataset
3. Converting state names to acronyms using state.abb() function

The rerun your code and all good!

Code:

# 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))]

Rerunning your code:

Note that the fiftystater package is not available for current versions of R, but the fifty_states data can be found here on Github