library(rtemis.draw)
Attaching package: 'rtemis.draw'The following object is masked from 'package:graphics':
Axis17 MapLibre: high-level API
Choropleth maps — regions shaded by a value — are rendered with MapLibre GL, a WebGL map renderer, rather than ECharts. As with the Sigma.js network renderer, rtemis.draw uses a high-performance JavaScript library for each plot type. The high-level draw_choropleth() and the low-level MapModel / MapLibreOption classes are the R counterparts of the choropleth renderer in rtemis.live.
Note on rendering There is no basemap: administrative boundaries are drawn on the themed page background, and the map auto-detects your system’s light/dark setting like every other draw_* function. The location-to-geometry join, the classification scale, and FIPS/ISO key normalization run in the browser and are shared with SVG export. Unmatched location keys are reported in the browser console. Regions without data remain visible in a neutral color.
17.1 Countries
The simplest input is a data frame with a location column and a value column. For world maps the location key is an ISO-A3 (or ISO-A2) country code; resolution = "country" is the default.
countries <- data.frame(
iso = c(
"USA", "CAN", "MEX", "BRA", "ARG", "GBR", "FRA", "DEU", "ESP", "ITA",
"NOR", "SWE", "POL", "RUS", "CHN", "JPN", "KOR", "IND", "IDN", "AUS",
"NZL", "ZAF", "EGY", "NGA", "KEN", "SAU", "TUR", "IRN", "CHL", "COL"
),
life_exp = c(
78.5, 82.3, 75.0, 75.9, 76.7, 81.3, 82.5, 81.0, 83.5, 82.9,
82.8, 82.8, 78.3, 73.2, 78.2, 84.6, 83.4, 70.2, 71.7, 83.4,
82.1, 64.9, 71.8, 55.7, 66.7, 75.1, 77.7, 76.7, 80.2, 77.3
)
)
draw_choropleth(
countries,
location = "iso",
value = "life_exp",
value_label = "Life expectancy"
)The renderer accepts ISO-A3, ISO-A2, or upper/lower case, so a column of two-letter codes joins just as well.
17.2 US states
Set resolution = "state" to join to US states. The location key can be a FIPS code, a postal abbreviation, or a full state name — all normalize to the same 2-digit FIPS id. Here we use the built-in state.x77 data:
states <- data.frame(
abbr = state.abb,
income = as.numeric(state.x77[, "Income"])
)
draw_choropleth(
states,
location = "abbr",
value = "income",
resolution = "state",
value_label = "Income (1974, $)",
colormap = "greens"
)17.3 Classification and color schemes
classification controls how values are binned into color classes: "quantile" (equal counts, the default), "equal" (equal-width intervals), or "jenks" (natural breaks). num_classes sets the number of classes (2–12), and colormap selects the ramp.
draw_choropleth(
states,
location = "abbr",
value = "income",
resolution = "state",
value_label = "Income",
classification = "jenks",
num_classes = 6,
colormap = "viridis"
)Sequential schemes — "blues", "viridis", "ylorrd", "greens", "magma" — suit data with a natural low-to-high order. Diverging schemes — "rdbu", "rdylgn", "spectral", "brbg" — emphasize departure from a midpoint:
state_pop <- data.frame(
abbr = state.abb,
illiteracy = as.numeric(state.x77[, "Illiteracy"])
)
draw_choropleth(
state_pop,
location = "abbr",
value = "illiteracy",
resolution = "state",
value_label = "Illiteracy (%)",
colormap = "rdylgn",
classification = "equal"
)17.4 Tooltips and styling
Pass tooltip with extra column names to surface them on hover. The remaining arguments tune appearance: opacity, show_boundaries, outline_width, and the corner anchors legend_position / tooltip_position.
states_full <- data.frame(
abbr = state.abb,
name = state.name,
income = as.numeric(state.x77[, "Income"]),
murder = as.numeric(state.x77[, "Murder"])
)
draw_choropleth(
states_full,
location = "abbr",
value = "income",
resolution = "state",
value_label = "Income",
tooltip = c("name", "murder"),
colormap = "blues",
outline_width = 0.5,
legend_position = "bottom-left",
tooltip_position = "top-right"
)The full set of appearance arguments:
opacity— fill opacity,0-1.show_boundaries,outline_width— region outlines.show_legend— hide the color legend entirely.legend_position,tooltip_position— corner anchors, each one of"top-left","top-right","bottom-left","bottom-right".
17.5 US counties
Set resolution = "county" to join on 5-digit FIPS. As an example we use the CDC PLACES county dataset — the same sample data that ships with rtemis.live — read straight from the web:
places <- read.csv(
"https://live.rtemis.org/sample/places_county.csv",
colClasses = c(fips = "character")
)One row per county, keyed by fips, with five health indicators: smoking, obesity, physical_inactivity, high_bp, and no_insurance. We color by smoking and put the rest in the tooltip. County boundaries are dense, so a thinner outline_width keeps them from swallowing the fill:
draw_choropleth(
places,
location = "fips",
value = "smoking",
resolution = "county",
value_label = "Smoking (%)",
tooltip = c(
"county", "obesity", "physical_inactivity", "high_bp", "no_insurance"
),
colormap = "magma",
opacity = 0.9,
show_boundaries = TRUE,
outline_width = 0.15,
legend_position = "bottom-right"
)The county geometry and dataset may use different boundary vintages. Keys without a matching region are reported in the browser console; regions without a value use the “No data” color.
17.6 Export a map
Save a choropleth as SVG with editable boundaries, colors, legend, and text:
state_map <- draw_choropleth(
states, "abbr", "income", resolution = "state",
value_label = "Income (1974, $)", colormap = "greens"
)
save_drawing(state_map, file.path(tempdir(), "state-income.svg"),
width = 1100, height = 700)This requires Node.js and exports the initial Mercator view. Browser panning and zooming do not change the saved R object.
17.7 Lower-level API
draw_choropleth() builds a MapModel and a MapLibreOption render spec internally. To assemble rows by hand or set the render spec directly and draw it with draw(), see the MapLibre low-level S7 API chapter.
