This cartography project was completed as an assignment for my Master’s program course, Environmental Data Science 233: Spatial Analysis. It was collaboration with G. Kumaishi.
Project Goal
Create a map of life expectancy for South America and Africa.
Step One
Create two separate maps for life expectancy data of South America and Africa using spData and tmap.
Life Expectancy in Africa:
Show code
### Africa ###
world_africa <- world[world[["continent"]] == "Africa", ] # create a subset of the world dataset of just the African continent
lifeexp_africa <- tm_shape(world_africa) + # store map in order to combine
tm_polygons(col = "lifeExp", # select life expectancy data
palette = "YlOrBr", # Yellow Orange Brown color palette from RColorBrewer
style = "pretty", # familiar GIS discrete options available such as quantile, equal, jenks, etc.
title = "Life Expectancy (years)*", # legend title lives within tm_polygons
textNA = "No Data") + # converted "Missing" legend default to "No Data"
tm_layout(inner.margins = c(0.1, 0.1, 0.1, 0.1), # margins between 0-1 (bottom, left, top, right)
legend.title.size = 1,
legend.text.size = .8,
bg.color = "lightblue", # background color
title = "Africa") + # map title lives under tm_layouts
tm_compass(type = "4star", # other compass styles available
show.labels = 1, # specifies compass label options
size = 3,
position = c("right", "top")) +
tm_credits("Life expectancy data for the\nAfrican continent uses 5-year\nclassification breaks.\nSource: SpData \n \n*Note that the color scale differs\nbetween continents.", # credit data source including github link; \n creates text break
size = .5, # can't figure out how to make size bigger...
position = c("right", "bottom"),
align = "right", # only applicable if using multiple lines
width = NA) # 1 is the whole map width, NA is determined by width of text
lifeexp_africa
Figure 1: Life Expectancy in Africa
Life Expectancy in South America:
Show code
### South America ###
world_sa <- world[world[["continent"]] == "South America", ] # create a subset of the world dataset of just the South American continent
lifeexp_sa <- tm_shape(world_sa) + # store map in order to combine
tm_polygons(col = "lifeExp", # select life expectancy data
palette = "YlOrBr", # Yellow Orange Brown color palette from RColorBrewer
n = 5, # specify number of breaks
style = "pretty", # familiar GIS discrete options available such as quantile, equal, jenks, etc.
title = "Life Expectancy (years)*", # legend title lives within tm_polygons
textNA = "No Data") + # converted "Missing" legend default to "No Data"
tm_layout(inner.margins = c(0.1, 0.25, 0.1, 0.25), # margins between 0-1 (bottom, left, top, right)
legend.position = c("right", "bottom"),
legend.title.size = 1,
legend.text.size = .8,
bg.color = "lightblue", # background color
title = "South America") + # map title lives under tm_layouts
tm_compass(type = "4star", # other compass styles available
show.labels = 1, # specifies compass label options
size = 3,
position = c("right", "top")) +
tm_credits("Life expectancy data\nfor the South American continent uses\n2-year classification breaks.\nSource: SpData \n \n*Note that the color scale differs\nbetween continents.", # credit data source including github link; \n creates text break
position = c("left", "bottom"),
align = "left",
size = .5) +
tm_credits("", # explain varying color scales b/w two continents; \n creates text break
position = c("right", "bottom"),
align = "right",
size = .3)
lifeexp_sa
Figure 2: Life Expectancy in South America
Step Two
Combine the two maps using tmap_arrange to compare and contrast life expectancy rates.
Life Expectancy in South America and Africa:*
Show code
combined_lifeexp <- tmap_arrange(lifeexp_sa,lifeexp_africa) # combine the two life expectancy maps using tmap_arrange
combined_lifeexp
Figure 3: Fig 3: A Comparision of Life Expectancy between South America and Africa
Conclusion
This project was to practice creating maps in R using sf, tmap, and spData packages.