The strength of the geoviz package lies in its ability to create thematic maps from statistical data. To achieve this, many functions are available.
First, let’s load the packages and some data.
library(geoviz)
library(sf)
world <- st_read(
system.file("gpkg/world.gpkg", package = "geoviz"),
quiet = TRUE
)
cities <- st_read(
system.file("gpkg/cities.gpkg", package = "geoviz"),
quiet = TRUE
)Proportional symbols
With the viz_prop function, you can quickly draw a map
with proportionnal symbols. At a minimum, you need two parameters:
data (a spatial data frame) and var (the
variable to map). Note that you should use absolute quantitative data
(stocks) here.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_prop(data = world, var = "pop", fill = "#38896F") |>
viz_render()With the k attribute (and possibily
fixmax), you can change the size of the circles. With
symbol, it is possible to change the type of symbol—for
example: "circle", "square",
"spike", "halfcircle". Additionally, you can
modify all the usual graphical styles (fill,
stroke, strokeWidth…).
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_prop(data = world, var = "pop", k = 30,
fill = "#38896F", symbol = "square") |>
viz_render()The legend can be configured using the prefixes leg_.
With the prefix leg_circle_..., you can modify the
appearance of circles. With the prefix leg_line_..., you
can modify the appearance of lines. With the prefix
leg_values_..., you can modify the style of the values.
Everything is configurable. To better understand, you can refer to the
documentation of the legend functions and/or to the dedicated
vignette.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_prop(data = world, var = "pop", k = 30,
fill = "#38896F", symbol = "circle", leg_type = "separate",
leg_circle_fill = "#38896F", leg_title = "Population",
leg_subtitle = "in million inh.", leg_note = "made with geoviz",
leg_values_round = 0, leg_values_factor = 1/1000000) |>
viz_render()Choropleth
In thematic cartography, according to the rules of graphic semiology,
relative quantitative data (percentages, indices, ratios) must be
represented using visual order variables. The most classic
representation is the choropleth map. The simplest way to create a
chropleth map with the geoviz library is to use viz_choro.
As previously, you need two parameters: data (a spatial
data frame) and var (the variable to map).
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_choro(data = world, var = "gdppc") |>
viz_render()To change class boundaries, you have access to several discretization
methods from the JavaScript library statsbreaks. You can
choose them using the method parameter. The available
methods are: “quantile”, “q6”, “equal”, “jenks”, “msd”, “geometric”,
“headtail”, “pretty”, “arithmetic”, “nestedmeans”. In addition, with
nb, you can specify the number classes. For the msd method
only , you can also choose the parameters sd (number of
standard deviations to include) and middle (to define
whether the mean is at the center of a class or at a class
boundary).
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_choro(data = world, var = "gdppc", method = "jenks", nb = 4) |>
viz_render()If you prefer, you can also directly specify the class boundaries
using the breaks parameter.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_choro(data = world, var = "gdppc",
breaks = c(200, 1000, 5000, 10000, 50000, 200000)) |>
viz_render()Regarding colors, you have access to all palettes available in the JavaScript library dispocal. See here. For example, you can use:
- Sequential
"BluGrn", "BluYl", "BrwnYl",
"BurgYl", "Burg", "DarkMint",
"Emrld", "Magenta", "Mint",
"OrYel", "Peach", "PinkYl",
"PurpOr", "Purp", "RedOr",
"SunsetDark", "Sunset",
"TealGrn", "Teal", "agGrnYl",
"agSunset", "Algae", "Amp",
"Deep", "Dense", "Gray",
"Haline", "Ice", "Matter",
"Oxy", "Phase", "Solar",
"Speed", "Tempo", "Thermal",
"Turbid", "Blues", "BuGn",
"BuPu", "GnBu", "Greens",
"Greys", "OrRd", "Oranges",
"PuBuGn", "PuBu", "PuRd",
"Purples", "RdPu", "Reds",
"YlGnBu", "YlGn", "YlOrBr",
"YlOrRd", "Blues10", "Blues7",
"Inferno", "Magma", "Plasma",
"Viridis", "Cube1", "CubeYF",
"LinearL", "Acton", "Bamako",
"Batlow", "Bilbao", "Buda",
"Davos", "Devon", "GrayC",
"Hawaii", "Imola", "LaJolla",
"LaPaz", "Nuuk", "Oleron",
"Oslo", "Tokyo", "Turku",
"Carrots", "BlueFluorite",
"AridElevation", "Florida"
- Diverging
"ArmyRose", "Earth", "Fall",
"Geyser", "TealRose", "Temps",
"Tropic", "Balance", "Curl",
"Delta", "BrBG", "PRGn",
"PiYG", "PuOr", "RdBu",
"RdGy", "RdYlBu", "RdYlGn",
"Spectral", "BlueDarkOrange12",
"BlueDarkOrange18", "BlueDarkRed12",
"BlueDarkRed18", "BlueGray",
"BlueGreen", "BlueGrey",
"BlueOrange10", "BlueOrange12",
"BlueOrange8", "BlueOrangeRed",
"BrownBlue10", "BrownBlue12",
"GreenMagenta", "RedYellowBlue",
"Berlin", "Broc", "Cork",
"Lisbon", "Roma", "Tofino",
"Vik"
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_choro(data = world, var = "gdppc", colors = "BlueOrangeRed") |>
viz_render()You can also choose any colors you want by specifying a vector.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_choro(data = world, var = "gdppc",
colors = c("#ffffcc", "#c7e9b4", "#7fcdbb",
"#41b6c4", "#2c7fb8", "#253494")) |>
viz_render()Typology
To create a typology map, you can use the viz_typo
function. As before, you need at least two parameters: data
(a spatial data frame) and var (a qualitative
variable).
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_typo(data = world, var = "region") |>
viz_render()Of course, you can change the palette with the colors
parameter. For example, you can use for example:
"Antique", "Bold", "Pastel",
"Prism", "Safe", "Vivid",
"Accent", "Dark2", "Paired",
"Pastel1", "Pastel2", "Set1",
"Set2", "Set3", "BlueRed",
"GreenOrange", "PurpleGray",
"GrandBudapest3", "IsleOfDogs2",
"Moonrise5"
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_typo(data = world, var = "region", colors = "Pastel") |>
viz_render()There are other palettes in dicopal, but some are only available for a fixed number of classes. Fortunately, you can also directly choose your own colors.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_typo(data = world, var = "region",
colors = c("#e41a1c", "#377eb8", "#4daf4a",
"#984ea3", "#ff7f00", "#ffff33")) |>
viz_render()To properly determine the order of the types in the legend and which
color corresponds to which category, you can also use the
order argument.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_typo(data = world, var = "region",
order = c("Antarctica", "Oceania", "Africa",
"America", "Asia", "Europe"),
colors = c("#e41a1c", "#377eb8", "#4daf4a",
"#984ea3", "#ff7f00", "#ffff33")) |>
viz_render()Obviously, all these functions also work on point objects.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_typo(data = st_centroid(world), var = "region", r = 10,
order = c("Antarctica", "Oceania", "Africa",
"America", "Asia", "Europe"),
colors = c("#e41a1c", "#377eb8", "#4daf4a",
"#984ea3", "#ff7f00", "#ffff33")) |>
viz_render()## Warning: st_centroid assumes attributes are constant over geometriespictograms
Another way to represent qualitative data is to use pictograms. For
this, you can use the viz_picto function with the
data and var parameters.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_picto(data = world, var = "region") |>
viz_render()Some symbols are selected by default. But you can choose the ones you want from this list:
"circle", "square",
"triangle", "pentagon",
"hexagon", "roundsquare",
"pillow", "drop", "egg",
"star12", "star8", "star",
"diamond", "trapzium", "plus",
"minus", "arrow", "stop",
"vbar", "crescent", "donut",
"heart", "clover", "fist",
"check", "plane", "rocket",
"boat", "pin", "hospital",
"flower", "cloud", "human",
"tent", "beer", "boom",
"nuke", "target", "missing"
To see what they look like, you can click |here](https://observablehq.com/embed/@neocartocnrs/symbols@826?cells=symbols).
To choose the symbols you want and define their display
order, you can use the order and symbols
parameters.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_picto(data = world, var = "region",
order = c("Antarctica", "Oceania", "Africa",
"America", "Asia", "Europe"),
symbols = c("hospital", "flower", "cloud",
"beer", "nuke", "plane")) |>
viz_render()These symbols are configurable. You can change the color
(fill), the size (r), and even add a bounding
circle, which is also customizable (background). With the
dodge parameter, you can even spread the symbols apart to avoid
overlaps.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_picto(data = world, var = "region", background = TRUE,
r = 8, fill = "#38896F", dodge = TRUE) |>
viz_render()Combinaisons
With geoviz, it is of course possible to combine these representation modes by overlaying layers. You just need to pay attention to the position of the legends so that they do not overlap.
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_typo(data = world, var = "region",
colors = "Pastel", leg_pos = c(10, 100)) |>
viz_prop(data = world, var = "pop", k = 30,
leg_values_round = 0, leg_values_factor = 1/1000000,
fill = "none", stroke = "#38896F",
strokeWidth = 1.5) |>
viz_render()
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_choro(data = world, var = "gdppc",
colors = "OrRd", leg_pos = c(10, 100)) |>
viz_prop(data = world, var = "pop", k = 30,
leg_values_round = 0, leg_values_factor = 1/1000000,
fill = "none", stroke = "#38896F",
strokeWidth = 1.5) |>
viz_render()With the functions viz_propchoro and viz_proptypo, you can also
display two variables simultaneously by coloring the circles. In this
case, you must use var1 (for symbols) and var2
(for colors). The legends can be configured using the prefixes
leg1 and leg2. Then, you can use exactly the
same parameters as in the previous functions.
For example:
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_proptypo(data = world, var1 = "pop", k = 30,
leg1_values_round = 0, leg1_values_factor = 1/1000000,
var2 = "region", colors = "Pastel") |>
viz_render()Or:
viz_create(projection = "EqualEarth", zoomable = T) |>
viz_path(data = world, fill = "#CCC") |>
viz_propchoro(data = world, var1 = "pop", k = 30,
leg1_values_round = 0, leg1_values_factor = 1/1000000,
var2 = "gdppc", colors = "OrRd") |>
viz_render()That’s about it for now. To go further, go to the Symbology (advanced) section.