ggplot map with l
I would use different hue ranges for fill and line color:
ggplot(df, aes(map_id = id)) +
geom_map(aes(fill = growth, color = category), map =world.ggmap) +
expand_limits(x = world.ggmap$long, y = world.ggmap$lat) +
scale_fill_gradient(high = "red", low = "white", guide = "colorbar") +
scale_colour_hue(h = c(120, 240))
OR, use fill for category and transparency for growth level.
ggplot(df, aes(map_id = id)) +
geom_map(aes(alpha = growth, fill = category), map =world.ggmap) +
expand_limits(x = world.ggmap$long, y = world.ggmap$lat) +
scale_alpha(range = c(0.2, 1), na.value = 1)
It depends on what you want to show.
Just in case, here is the way to change the linesize:
ggplot(df, aes(map_id = id)) +
geom_map(aes(fill = growth, color = category, size = factor(1)), map =world.ggmap) +
expand_limits(x = world.ggmap$long, y = world.ggmap$lat) +
scale_fill_gradient(high = "red", low = "white", guide = "colorbar") +
scale_colour_hue(h = c(120, 240)) +
scale_size_manual(values = 2, guide = FALSE)
Here is HSV version:
df$hue <- ifelse(is.na(df$category), 0, as.numeric(df$category)/max(as.numeric(df$category), na.rm=T))
df$sat <- ifelse(is.na(df$growth), 0, df$growth/max(df$growth, na.rm=T))
df$fill <- ifelse(is.na(df$category), "grey50", hsv(df$hue, df$sat))
ggplot(df, aes(map_id = id)) +
geom_map(aes(fill = fill), map =world.ggmap) +
expand_limits(x = world.ggmap$long, y = world.ggmap$lat) +
scale_fill_identity(guide = "none")
Labeling center of map polygons in R ggplot
Try something like this?
Get a data frame of the centroids of your polygons from the
original map object.In the data frame you are plotting, ensure there are columns for
the ID you want to label, and the longitude and latitude of those
centroids.Use geom_text in ggplot to add the labels.
Based on this example I read a world map, extracting the ISO3 IDs to use as my polygon labels, and make a data frame of countries' ID, population, and longitude and latitude of centroids. I then plot the population data on a world map and add labels at the centroids.
library(rgdal) # used to read world map data
library(rgeos) # to fortify without needing gpclib
library(maptools)
library(ggplot2)
library(scales) # for formatting ggplot scales with commas
# Data from http://thematicmapping.org/downloads/world_borders.php.
# Direct link: http://thematicmapping.org/downloads/TM_WORLD_BORDERS_SIMPL-0.3.zip
# Unpack and put the files in a dir 'data'
worldMap <- readOGR(dsn="data", layer="TM_WORLD_BORDERS_SIMPL-0.3")
# Change "data" to your path in the above!
worldMap.fort <- fortify(world.map, region = "ISO3")
# Fortifying a map makes the data frame ggplot uses to draw the map outlines.
# "region" or "id" identifies those polygons, and links them to your data.
# Look at head(worldMap@data) to see other choices for id.
# Your data frame needs a column with matching ids to set as the map_id aesthetic in ggplot.
idList <- worldMap@data$ISO3
# "coordinates" extracts centroids of the polygons, in the order listed at worldMap@data
centroids.df <- as.data.frame(coordinates(worldMap))
names(centroids.df) <- c("Longitude", "Latitude") #more sensible column names
# This shapefile contained population data, let's plot it.
popList <- worldMap@data$POP2005
pop.df <- data.frame(id = idList, population = popList, centroids.df)
ggplot(pop.df, aes(map_id = id)) + #"id" is col in your df, not in the map object
geom_map(aes(fill = population), colour= "grey", map = worldMap.fort) +
expand_limits(x = worldMap.fort$long, y = worldMap.fort$lat) +
scale_fill_gradient(high = "red", low = "white", guide = "colorbar", labels = comma) +
geom_text(aes(label = id, x = Longitude, y = Latitude)) + #add labels at centroids
coord_equal(xlim = c(-90,-30), ylim = c(-60, 20)) + #let's view South America
labs(x = "Longitude", y = "Latitude", title = "World Population") +
theme_bw()
Minor technical note: actually coordinates
in the sp
package doesn't quite find the centroid, but it should usually give a sensible location for a label. Use gCentroid
in the rgeos
package if you want to label at the true centroid in more complex situations like non-contiguous shapes.
Ploting subregions in wordmap with ggplot2
geom_map will match the entries in data$country to map$region. Unfortunately map_data splits regions by the first colon, so you get "UK" which doesn't match "UK:Great Britain" in data$country.
A possible manual fix is to correct like this:
map$region[which(map$subregion == "Great Britain")] <- "UK:Great Britain"
map$region[which(map$subregion == "Northern Ireland")] <- "UK:Northern Ireland"
map$region[which(map$subregion == "Hong Kong")] <- "China:Hong Kong"
Map with geom_sf in ggplot2 missing axis labels
Disabling spherical geometry seems to be the solution.
# Deactivate s2
sf::sf_use_s2(FALSE)
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