R: scatter points using longitude/latitude

Question

I want to fill the colour on a map. However, the plot doesn't come out as aspected.

How can I visualize the data with longitude and latitude?

install.packages("WDI")
install.packages("tidyverse")

library(WDI)
library(tidyverse)

literacy_globe <- WDI(country = "all", indicator = "SE.ADT.LITR.ZS", start = 2015, end = 2018, extra = TRUE)

literacy_globe <- na.omit(literacy_globe)

ggplot(literacy_globe, aes(x = longitude, y = latitude, group = iso3c)) +
    geom_point(aes(fill = income), colour = "white")

I'd like the result similar to:

Answer 1

I found another way to draw the hierarchy scatter on world map, but i were not so sure if it has some drawbakcs.

literacy_globe <- WDI(country = "all", indicator = "SE.ADT.LITR.ZS", start = 
2015, end = 2018, extra = TRUE)
literacy_globe <- na.omit(literacy_globe)

lit.long <- literacy_globe$longitude
lit.lat <- literacy_globe$latitude
income <- literacy_globe$income

# prepare a NULL map
mp<-NULL 
mapworld<-borders("world",colour = "gray50",fill="white")
#mp = empty map

#plot a map
mp <- ggplot() + mapworld + ylim(-60,90)

#geom_point plot the data on it 
mp2 <- mp + geom_point(aes(x = lit.long, y = lit.lat), color = "darkblue",
fill = income) + 
scale_size(range = c(1,1))

Answer 2

You can use the following code

#Loading the required packges
library(WDI)
library(tidyverse)
library(maptools)
library("ggplot2")
library("sf")

#Downloading the data
literacy_globe <- WDI(country = "all", indicator = "SE.ADT.LITR.ZS", start = 2015, end = 2018, extra = TRUE)

#Removing the NAs
literacy_globe_1 <- na.omit(literacy_globe)

#Saving the data as .csv file as your data contains blank cells which are not NAs
write.csv(literacy_globe_1, "literacy_globe_1.csv")

#Reading the data from .csv file
data <- read.csv("literacy_globe_1.csv")

#Removing the NAs
literacy_globe <- na.omit(data)
summary(literacy_globe)
head(literacy_globe,2)

#Mapping using ggplot2 package
data(wrld_simpl)

#sp to sf conversion
world <- st_as_sf(wrld_simpl)

# now create the map
ggplot(world) +
  geom_sf(colour = "black", fill = NA) + coord_sf(expand = FALSE) + 
  theme_bw() + geom_point(aes(longitude, latitude),data= literacy_globe, colour=alpha("red",0.7))

For white fill of polygon and grey outside area, you can use

ggplot(world) +
  geom_sf(colour = "black", fill = "white") + coord_sf(expand = FALSE) + 
  geom_point(aes(longitude, latitude),data= literacy_globe, colour=alpha("red",0.7)) 

Update

choropleth map

literacy_globe <- WDI(country = "all", indicator = "SE.ADT.LITR.ZS", start = 2015, end = 2018, extra = TRUE)

literacy_globe <- na.omit(literacy_globe)
summary(literacy_globe)
head(literacy_globe,2)

#Using ggplot2 package
data(wrld_simpl)

#fortify shape file to get into dataframe 
wrld_simpl.f <- fortify(wrld_simpl, region = "NAME")
class(wrld_simpl.f)

head(wrld_simpl.f)

#merge with coefficients and reorder
merge.shp<-merge(wrld_simpl.f,literacy_globe, by.x = "id", by.y = "country", all.x=TRUE)
final.plot<-merge.shp[order(merge.shp$order), ] 

head(final.plot, 2)
#basic plot
ggplot() +
  geom_polygon(data = final.plot, 
               aes(x = long, y = lat, group = group, fill = income), 
               color = "black", size = 0.25)