Plot has a new documentation website!
👉 https://observablehq.com/plot 👈
The image mark can now generate circular images with the r channel, and rotate images with the rotate channel.
The axis mark now properly respects the margin shorthand option, changing the default for marginTop, marginRight, marginBottom, and marginLeft. The axis mark now correctly renders the axis label when the href option is used, or any other option that may be interpreted as a channel.
Facet scale domains are now imputed correctly when the sort mark option is used with a limit, or otherwise causing the facet domain to be truncated. Plot no longer generates a spurious warning when faceting and using non-array data, such as an Arquero table. The interval scale option, when expressed as a fractional number such as 0.2, now has better floating point precision.
The Plot.indexOf channel transform, used internally by some mark shorthand, is now exported.
Plot has a few improvements for server-side rendering. Plot now assumes a high pixel density display when headless. The default class name for plots is now deterministically generated (plot-d6a7b5) rather than randomly generated; this makes it easier to apply overrides to Plot’s default styles with an external stylesheet. (The default class name will change if Plot’s default styles change in a future release.) The className plot option is now inherited by a plot’s legends, if any. The density mark now respects the Plot’s document option, and the caption option now uses a duck test instead of testing against the global Node.
TypeScript! The feature you asked for most is here. 🎉 Plot now exports TypeScript type declarations (.d.ts) with precise types and documentation for all of Plot’s public API. This allows code editors such as VS Code to offer better suggestions, complete with inline documentation. For example, if you type “Plot.g”, Plot.geo is now suggested:
Function calls also have hints, showing their expected arguments.
Types are especially useful for suggesting well-known names, such as projections, scale types, and color schemes.
TypeScript also helps for reading code; hover any symbol and immediately see the relevant documentation.
Lastly, if you’re using Plot in a TypeScript project, you can now benefit from additional static type checking to find errors.
If you have suggestions or clarifications on how to improve the documentation, please open an issue or discussion, or send us a pull request.
The strokeOpacity, fillOpacity, and opacity channels now opt-out of the opacity scale by default when all values are numbers in the range [0, 1]; to opt-in to the opacity scale, specify the channel as {value, scale: true}. The raster mark now also supports scale overrides.
The scale nice option now accepts named time intervals such as day and week. The new quarter and half time intervals represent quarters (three months) and half-years (six months). The quantile scale now supports the unknown option. BigInt channels are now supported; values are coerced to numbers. Color legends now support the opacity option.
The text mark no longer crashes when a NaN tick value is specified for an axis. The className option now allows mixed-case class names. Channel-derived scale domains now correctly handle non-orderable values, duplicate values, and mark transforms. Plot.auto now renders correctly when a non-zero reduce is used in conjunction with the bar mark, and in some cases when the zero option is specified. The zero option no longer changes the default mark type, and Plot.autoSpec now materializes the zero option.
The interfaces for reduce and map implementations have changed. To better disambiguate from arrays, reduce implementations now have a reduceIndex method instead of a reduce method, and map implementations now have a mapIndex method instead of a map method. The old interfaces are still supported, but now deprecated.
The new top-level aspectRatio option changes the default plot height such that, assuming both x and y are linear scales, a scaled unit distance in x divided by a scaled unit distance in y is the given aspect ratio. For example, if x and y represent the same units (say, degrees Fahrenheit), and if the aspectRatio is one, then scaled distances in x and y will be equivalent.
Plot.plot({
aspectRatio: 1,
grid: true,
x: {label: "Daily low temperature (°F) →", tickSpacing: 40},
y: {label: "↑ Daily temperature variation (Δ°F)", tickSpacing: 40},
color: {scheme: "rainbow", nice: true, legend: true, tickFormat: "%b"},
marks: [
Plot.ruleY([0]),
Plot.dot(weather, {
x: (d) => d.temp_min,
y: (d) => d.temp_max - d.temp_min,
fill: (d) => (d = new Date(d.date), d.setUTCFullYear(2020), d)
})
]
})The new textOverflow option for the text mark allows text to be truncated when a line of text is longer than the specified lineWidth. Overflowing characters can either be clipped (clip) or replaced with an ellipsis (ellipsis), either at the start, middle, or end of each line.
When wrapping or truncating, the text mark now more accurately estimates the width of ellipses and emojis, and no longer separates combining marks or emoji character sequences such as 👨👩👧👦.
The link mark now respects the current projection, if any, given the default curve of auto. This matches the behavior of the line mark. To opt-out of the projection and draw a straight line, set the curve to linear.
The image mark now supports the imageRendering option. (Note: Safari currently ignores the SVG image-rendering attribute.)
You can now override the scale for a given mark channel by specifying the corresponding option as a {value, scale} object. For example, to force the stroke channel to be unscaled, interpreting the associated values as literal color strings:
Plot.dot(data, {stroke: {value: "foo", scale: null}})To instead force the stroke channel to be bound to the color scale regardless of the provided values, say:
Plot.dot(data, {stroke: {value: "foo", scale: "color"}})Color channels (fill and stroke) are bound to the color scale by default, unless the provided values are all valid CSS color strings or nullish, in which case the values are interpreted literally and unscaled. Likewise, if the dot mark’s symbol channel values are all symbols, symbol names, or nullish, values are interpreted literally and unscaled; otherwise, the channel is bound to the symbol scale. (If some color channels are literal values while other color channels are not, the channels with literal values will now automatically opt-out of the color scale; the same goes for symbol channels. This deviates from the previous behavior, where all channels associated with a scale were required to be literal values in order to have the scale default to an identity scale.)
The mark facetAnchor option can now be set to empty such that a mark is only rendered on empty facets. This is typically used for annotation.
The new Plot.autoSpec method takes data and options suitable for Plot.auto and returns a corresponding options object with default options realized. While intended primarily as an internal helper, Plot.autoSpec may be useful for debugging by letting you inspect which mark and reducers are chosen by Plot.auto.
Fix Plot.auto to only default to the bar mark if x or y is zeroed. Fix Plot.auto’s support for the area mark. Fix Plot.auto’s use of the bar mark with possibly ordinal reducers. Fix a bug where arrays of values could be erroneously interpreted as reducers. Fix a crash when the mark facet option is set to exclude, but the mark is not faceted; the option is now ignored. Fix a crash coercing BigInt values to numbers.
The new auto mark (Plot.auto) automatically selects a mark type that best represents the given dimensions of data according to some simple heuristics. For example,
Plot.auto(olympians, {x: "height", y: "weight"}).plot()makes a scatterplot (equivalent to dot); adding color as
Plot.auto(olympians, {x: "height", y: "weight", color: "count"}).plot()makes a heatmap (equivalent to rect and bin; chosen since height and weight are quantitative); switching to
Plot.auto(aapl, {x: "Date", y: "Close"}).plot()makes a line chart (equivalent to lineY; chosen because the selected x dimension Date is temporal and monotonic, i.e., the data is in chronological order);
Plot.auto(penguins, {x: "body_mass_g"}).plot()makes a histogram (equivalent to rectY and binX; chosen because the body_mass_g column is quantitative); and
Plot.auto(penguins, {x: "island"}).plot()makes a bar chart (equivalent to barY and groupX; chosen because the island column is categorical). The auto mark is intended to support fast exploratory analysis where the goal is to get a useful plot as quickly as possible. It’s also great if you’re new to Plot, since you can get started with a minimal API.
Plot’s new axis and grid marks allow customization and styling of axes. This has been one of our most asked-for features, closing more than a dozen feature requests (see #1197)! The new axis mark composes a vector for tick marks and a text for tick and axis labels. As such, you can use the rich capabilities of these marks, such the lineWidth option to wrap long text labels.
Plot.plot({
y: {percent: true},
marks: [
Plot.axisX({label: null, lineWidth: 8, marginBottom: 40}),
Plot.axisY({label: "↑ Responses (%)"}),
Plot.barY(responses, {x: "name", y: "value"}),
Plot.ruleY([0])
]
})And since axes and grids are now proper marks, you can interleave them with other marks, for example to produce ggplot2-style axes with a gray background and white grid lines.
Plot.plot({
inset: 10,
marks: [
Plot.frame({fill: "#eaeaea"}),
Plot.gridY({stroke: "#fff", strokeOpacity: 1}),
Plot.gridX({stroke: "#fff", strokeOpacity: 1}),
Plot.line(aapl, {x: "Date", y: "Close"})
]
})The x and y axes are now automatically repeated in empty facets, improving readability by reducing eye travel to read tick values. Below, note that the x axis for culmen depth (with ticks at 15 and 20 mm) is rendered below the Adelie/null-sex facet in the top-right.
Plot.plot({
facet: {marginRight: 80},
marks: [
Plot.dot(penguins, {x: "culmen_depth_mm", y: "culmen_length_mm", stroke: "#ddd"}),
Plot.frame(),
Plot.gridX(),
Plot.gridY(),
Plot.dot(penguins, {x: "culmen_depth_mm", y: "culmen_length_mm", fx: "sex", fy: "species"})
]
})See Plot: Axes for more examples, including the new both axis option to repeat axes on both sides of the plot, dashed grid lines via the strokeDasharray option, data-driven tick placement, and layering axes to show hierarchical time intervals (years, months, weeks).
Marks can now declare default margins via the marginTop, marginRight, marginBottom, and marginLeft options, and the margin shorthand. For each side, the maximum corresponding margin across marks becomes the plot’s default. While most marks default to zero margins (because they are drawn inside the chart area), Plot‘s axis mark provides default margins depending on their anchor. The facet margin options (e.g., facet.marginRight) now correctly affect the positioning of the x and y axis labels.
The new mark.facetAnchor mark option controls the facets in which the mark will appear when faceting. It defaults to null for all marks except for axis marks, where it defaults to top-empty if the axis anchor is top, right-empty if anchor is right, bottom-empty if anchor is bottom, and left-empty if anchor is left. This ensures the proper positioning of the axes with respect to empty facets.
The frame mark’s new anchor option allows you to draw a line on one side of the frame (as opposed to the default behavior where a rect is drawn around all four sides); this feature is now used by the scale.line option for x and y scales. The text mark now supports soft hyphens (\xad); lines are now eligible to break at soft hyphens, in which case a hyphen (-) will appear at the end of the line before the break. The raster mark no longer crashes with an identity color scale. The voronoi mark now correctly respects the target, mixBlendMode, and opacity options.
The new raster mark and contour mark generate a raster image and smooth contours, respectively, from spatial samples. For example, the plot below shows a gridded digital elevation model of Maungawhau (R’s volcano dataset) with contours every 10 meters:
Plot.plot({
color: {legend: true, label: "Height (m)"},
marks: [
Plot.raster(volcano.values, {width: volcano.width, height: volcano.height}),
Plot.contour(volcano.values, {width: volcano.width, height: volcano.height, interval: 10})
]
})For non-gridded or sparse data, the raster and contour marks implement a variety of spatial interpolation methods to populate the raster grid. The barycentric interpolation method, shown below with data from the Great Britain aeromagnetic survey, uses barycentric coordinates from a Delaunay triangulation of the samples (small black dots).
Plot.plot({
width: 640,
height: 484,
inset: 4,
x: {tickFormat: "s"},
y: {tickFormat: "s", ticks: 5},
color: {type: "diverging", legend: true},
marks: [
Plot.raster(ca55, {x: "LONGITUDE", y: "LATITUDE", fill: "MAG_IGRF90", interpolate: "barycentric"}),
Plot.dot(ca55, {x: "LONGITUDE", y: "LATITUDE", r: 0.75, fill: "currentColor"})
]
})The same data, with a smidge of blur, as filled contours in projected coordinates:
Plot.plot({
width: 640,
height: 484,
color: {type: "diverging", legend: true},
projection: {type: "reflect-y", domain: {type: "MultiPoint", coordinates: ca55.map((d) => [d.GRID_EAST, d.GRID_NORTH])}},
marks: [Plot.contour(ca55, {x: "GRID_EAST", y: "GRID_NORTH", fill: "MAG_IGRF90", stroke: "currentColor", blur: 2})]
})Naturally, the raster and contour mark are compatible with Plot’s projection system, allowing spatial samples to be shown in any geographic projection and in conjunction with other geographic data. The equirectangular projection is the natural choice for this gridded global water vapor dataset from NASA Earth Observations.
Plot.plot({
projection: "equirectangular",
color: {
scheme: "ylgnbu",
unknown: "#ccc",
legend: true,
label: "Water vapor (cm)"
},
marks: [
Plot.raster(vapor, {
x1: -180,
y1: 90,
x2: 180,
y2: -90,
width: 720,
height: 360
}),
Plot.graticule(),
Plot.frame()
]
})The raster and contour mark also support sampling continuous spatial functions f(x, y). For example, here is the famous Mandelbrot set, with color encoding the number of iterations before the point escapes:
Plot.plot({
height: 500,
marks: [
Plot.raster({
fill: (x, y) => {
for (let n = 0, zr = 0, zi = 0; n < 80; ++n) {
[zr, zi] = [zr * zr - zi * zi + x, 2 * zr * zi + y];
if (zr * zr + zi * zi > 4) return n;
}
},
x1: -2,
y1: -1.164,
x2: 1,
y2: 1.164,
pixelSize: 0.5
})
]
})The vector mark now supports the shape constant option; the built-in shapes are arrow (default) and spike. A custom shape can also be implemented, returning the corresponding SVG path data for the desired shape. The new spike convenience constructor creates a vector suitable for spike maps. The vector mark also now supports an r constant option to set the shape radius.
Plot.plot({
width: 960,
height: 600,
projection: "albers-usa",
length: {
range: [0, 200]
},
marks: [
Plot.geo(nation, {fill: "#e0e0e0"}),
Plot.geo(statemesh, {stroke: "white"}),
Plot.spike(counties.features, Plot.geoCentroid({stroke: "red", length: (d) => population.get(d.id)}))
]
});The new geoCentroid transform and centroid initializer compute the spherical and projected planar centroids of geometry, respectively. The new identity channel helper returns a source array as-is, avoiding an extra copy.
The interval option now supports named time intervals such as “sunday” and “hour”, equivalent to the corresponding d3-time interval (e.g., d3.utcSunday and d3.utcHour). The bin transform is now many times faster, especially when there are many bins and when binning temporal data.
Diverging scales now correctly handle descending domains. When the stack order option is used without a z channel, a helpful error message is now thrown. The clip option frame now correctly handles band scales. Using D3 7.8, generated SVG path data is now rounded to three decimal points to reduce output size. Fix a crash when a facet scale’s domain includes a value for which there is no corresponding facet data. The bin, group, and hexbin transforms now correctly ignore undefined outputs. Upgrade D3 to 7.8.2.
The new geo mark renders GeoJSON geometries such as polygons, lines, and points. Together with Plot’s new projection system, Plot can now produce thematic maps. For example, the choropleth map below shows unemployment rates by U.S. county.
Plot.geo(counties, {fill: (d) => d.properties.unemployment}).plot({
projection: "albers-usa",
color: {
type: "quantile",
n: 8,
scheme: "blues",
label: "Unemployment (%)",
legend: true
}
})The new top-level projection option controls how geometric coordinates are transformed to the screen and supports a variety of common geographic projections, including the composite U.S. Albers projection shown above, the Equal Earth projection, the Mercator projection, the orthographic and stereographic projections, several conic and azimuthal projections, among others. Projections can be fit to geometry using the projection.domain option, and rotated to an arbitrary aspect using the projection.rotate option.
Plot.plot({
height: 640,
inset: 1,
projection: {type: "orthographic", rotate: [100, -30]},
marks: [
Plot.graticule(),
Plot.geo(land, {fill: "currentColor"}),
Plot.sphere()
]
})The new graticule convenience mark renders meridians and parallels (lines of constant longitude and latitude), while the sphere convenience mark draws the outline of the sphere.
Plot’s projection system works automatically with most of Plot’s mark types, including dots, vectors, lines, and rects. For geographic projections, x represents longitude and y represents latitude. For example, the map below uses vectors to show county-level vote margins in the 2020 U.S. presidential election: a margin for Biden is shown as a blue left-pointing arrow, while a margin for Trump is shown as a red right-pointing arrow; the length of the arrow is proportional to the margin.
Plot.plot({
width: 975,
projection: "albers-usa",
marks: [
Plot.geo(statemesh, {strokeOpacity: 0.25}),
Plot.geo(nation),
Plot.vector(elections, {
filter: (d) => d.votes > 0,
anchor: "start",
x: (d) => centroids.get(d.fips)?.[0],
y: (d) => centroids.get(d.fips)?.[1],
sort: (d) => Math.abs(d.results_trumpd - d.results_bidenj),
stroke: (d) => (d.results_trumpd > d.results_bidenj ? "red" : "blue"),
length: (d) => Math.sqrt(Math.abs(d.margin2020 * d.votes)),
rotate: (d) => (d.results_bidenj < d.results_trumpd ? 60 : -60)
})
]
})For the line mark, the specified projection doesn’t simply project control points; the projection has full control over how geometry is transformed from its native coordinate system (often spherical) to the screen. This allows line geometry to be represented as geodesics, which are sampled and clipped during projection. For example, the map below shows the route of Charles Darwin’s voyage on the HMS Beagle; note that the line is cut when it crosses the antimeridian in the Pacific ocean. (Also note the use of the stroke channel to vary color.)
Plot.plot({
projection: "equal-earth",
marks: [
Plot.geo(land, {fill: "currentColor"}),
Plot.graticule(),
Plot.line(beagle, {stroke: (d, i) => i, z: null, strokeWidth: 2}),
Plot.sphere()
]
})Plot’s new geo mark and projection system work with Plot’s other core features, including scales, legends, faceting, and transforms. For example, here is a faceted dot map showing openings of Walmart stores over five decades.
Plot.plot({
width: 975,
projection: "albers",
fx: {tickFormat: (d) => `${d}’s`},
facet: {data: walmarts, x: (d) => Math.floor(d.date.getUTCFullYear() / 10) * 10},
marks: [
Plot.geo(statemesh, {strokeOpacity: 0.1}),
Plot.dot(walmarts, {x: "longitude", y: "latitude", r: 1, fill: "currentColor"}),
Plot.geo(nation)
]
})As another example using the same dataset, the map below uses the hexbin transform to aggregate Walmart store opening into local hexagons.
Plot.plot({
projection: "albers",
color: {
legend: true,
label: "First year opened",
scheme: "spectral"
},
marks: [
Plot.geo(statemesh, {strokeOpacity: 0.25}),
Plot.geo(nation),
Plot.dot(walmarts, Plot.hexbin({r: "count", fill: "min"}, {x: "longitude", y: "latitude", fill: "date"}))
]
})In addition to the included basic projections, Plot’s projection system can be extended using any projection implementation compatible with D3’s projection stream interface. This includes all the projections provided by the d3-geo-projection and d3-geo-polygon libraries! For example, here is a world map using Goode’s interrupted homolosine projection.
Plot.plot({
width: 975,
height: 424,
inset: 1,
projection: {
type: d3.geoInterruptedHomolosine,
domain: {type: "Sphere"}
},
marks: [
Plot.geo(land, {clip: "sphere", fill: "currentColor"}),
Plot.graticule({clip: "sphere"}),
Plot.sphere()
]
})Plot now supports mark-level faceting via the new mark.fx and mark.fy options. Mark-level faceting makes it easier to control which marks are faceted (versus repeated across facets), especially when combining multiple datasets or specifying faceted annotations.
Plot.plot({
grid: true,
height: 180,
marks: [Plot.frame(), Plot.dot(anscombe, {x: "x", y: "y", fx: "series"})]
})When mark-level faceting is used, the mark will be faceted if either the mark.fx or mark.fy channel option (or both) is specified. As before, you can set the mark.facet option to null or false option will disable faceting, or to exclude to draw the subset of the mark’s data not in the current facet.
In addition to the above new features, this release also includes a variety of bug fixes. The fx and fy scales now support the scale.transform and scale.percent options. The quantize scale now respects the scale.unknown option. Initializers (including dodge and hexbin) no longer unintentionally drop the mark.sort option when being used to sort a scale’s domain. The error message when an invalid color scheme is specified has been improved. Plot no longer warns about empty strings appearing to be numbers. The mean and median reducers now return dates if the data is temporal. The default height now adjusts automatically to preserve the inner size of the plot when margins are specified. Fix the position of the frame anchor when either the x or y scale is ordinal (band or point). Dots with a negative constant radius r are no longer rendered rather than generating invalid SVG.
Plot.plot({
marks: [
Plot.lineY(aapl, {x: "Date", y: "Close", stroke: "#ccc", strokeWidth: 1}),
Plot.lineY(aapl, Plot.windowY({k: 20, strict: false}, {x: "Date", y: "Close", stroke: "red"})),
Plot.lineY(aapl, Plot.windowY({k: 20, strict: true}, {x: "Date", y: "Close"}))
]
})[breaking] Plot.window, Plot.windowX and Plot.windowY now return an aggregate value even when the window contains undefined values, for example at the beginning or end of a series. Set the new strict option to true to instead return undefined if the window contains any undefined values.
Parts of the README have been incorporated throughout the codebase as JSDoc comments. This allows IDEs to display the documentation as tooltips.
Swatches legends are now rendered in SVG, supporting patterns and gradients. Swatches legends now require an ordinal, categorical, or threshold color scale and will throw an error if you attempt to use them with an unsupported color scale type (such as a linear or diverging scale).
The new top-level document option specifies the document used to create plot elements. It defaults to window.document, but can be changed to another document, say when using a virtual DOM library for server-side rendering in Node.
Plot now uses D3 7.6.1, using d3.blur2 for a faster blur operator supporting fractional bandwidths when computing density contours. Plot now uses a duck test to detect marks (rather than strict instanceof), allowing marks from different versions of Plot to be combined into a single plot. Plot is now partially written in TypeScript. In the future, Plot will be written entirely in TypeScript and will export TypeScript type definition files to assist Plot development.
The new density mark creates contours representing the estimated density of two-dimensional point clouds. The bandwidth and number of thresholds are configurable.
Plot.plot({
inset: 20,
marks: [
Plot.density(faithful, {x: "waiting", y: "eruptions", stroke: "steelblue", strokeWidth: 0.25}),
Plot.density(faithful, {x: "waiting", y: "eruptions", stroke: "steelblue", thresholds: 4}),
Plot.dot(faithful, {x: "waiting", y: "eruptions", fill: "currentColor", r: 1.5})
]
})By default, as shown above, the density is represented by contour lines. By setting the fill option to density, you can draw filled regions with a sequential color encoding instead.
Plot.density(diamonds, {x: "carat", y: "price", fill: "density"}).plot({
height: 500,
grid: true,
x: {type: "log"},
y: {type: "log"},
color: {scheme: "ylgnbu"}
})The new linear regression marks produce linear regressions with confidence interval bands, representing the estimated relation of a dependent variable (typically y) on an independent variable (typically x).
Plot.plot({
grid: true,
marks: [
Plot.dot(penguins, {x: "culmen_length_mm", y: "culmen_depth_mm", fill: "species"}),
Plot.linearRegressionY(penguins, {x: "culmen_length_mm", y: "culmen_depth_mm", stroke: "species"}),
Plot.linearRegressionY(penguins, {x: "culmen_length_mm", y: "culmen_depth_mm"})
]
})The new Delaunay and Voronoi marks produce Delaunay triangulations and Voronoi tesselations: Plot.delaunayLink draws links for each edge of the Delaunay triangulation of the given points, Plot.delaunayMesh draws a mesh of the Delaunay triangulation of the given points, Plot.hull draws a convex hull around the given points, Plot.voronoi draws polygons for each cell of the Voronoi tesselation of the given points, and Plot.voronoiMesh draws a mesh for the cell boundaries of the Voronoi tesselation of the given points.
Plot.plot({
marks: [
Plot.voronoi(penguins, {x: "culmen_depth_mm", y: "culmen_length_mm", fill: "species", fillOpacity: 0.2, stroke: "white"}),
Plot.dot(penguins, {x: "culmen_depth_mm", y: "culmen_length_mm", fill: "species"})
]
})For data at regular intervals, such as integer values or daily samples, the new scale.interval option can be used to enforce uniformity. The specified interval—such as d3.utcMonth—sets the default scale.transform to the given interval’s interval.floor function. In addition, for ordinal scales the default scale.domain is an array of uniformly-spaced values spanning the extent of the values associated with the scale.
All marks now support the pointerEvents option to set the pointer-events attribute. The frame decoration mark now supports the rx and ry options. The cell mark now respects the dx and dy options.
Fix a bug where arrow heads would not render correctly when the strokeWidth was exactly one. Fix the scale.zero option when the domain is negative. Fix the clip mark option when x or y is a band scale. Fix the fill color of text marks using the href option. Fix a crash in the bar and tick mark when the associated band scale is not present, as when these marks are used (erroneously) with the dodge transform. Use element.appendChild instead of element.append for the benefit of DOM implementations that do not support the full DOM standard.
Improve the error message when the facet option is used without data. Throw an error if initializers attempt to create position scales. Throw an error if an implicit ordinal position domain has more than 10,000 values.
[breaking] Plot now requires D3 ^7.5.0.
Plot now supports mark initializers via the initializer option. Initializers can transform data, channels, and indexes. Unlike data transforms which operate in abstract data space, initializers can operate in screen space such as pixel coordinates and colors. For example, initializers can modify a marks’ positions to avoid occlusion. The new hexbin and dodge transforms are implemented as mark initializers.
The new hexbin transform functions similarly to the bin transform, except it aggregates both x and y into hexagonal bins before reducing. The size of the hexagons can be specified with the binWidth option, which controls the width of the (pointy-topped) hexagons.
Plot.plot({
color: {
legend: true
},
marks: [
Plot.hexagon(
cars,
Plot.hexbin(
{r: "count", fill: "mean"},
{x: "displacement (cc)", y: "economy (mpg)", fill: "weight (lb)"}
)
)
]
})The new dodge transform can be used to produce beeswarm plots. Given an x channel representing the desired horizontal position of circles, the dodgeY transform derives a new y (vertical position) channel such that the circles do not overlap; the dodgeX transform similarly derives a new x channel given a y channel.
Plot.plot({
height: 320,
x: {
domain: [-3, 3]
},
marks: [
Plot.dotX(Array.from({length: 800}, d3.randomNormal()), Plot.dodgeY())
]
})If an r channel is specified, the circles may have varying radius. By default, the dodge transform sorts the input data by descending radius, such that the largest circles are placed first. The order of placement greatly affects the resulting layout; to change the placement order, use the standard mark sort option.
Plot.plot({
height: 400,
x: {
domain: [-100, -20],
percent: true,
label: "← Reduction in travel (%)"
},
r: {
range: [0, 20]
},
color: {
legend: true,
tickFormat: d => d ? "lockdown" : "no lockdown"
},
marks: [
Plot.dot(lockdown, Plot.dodgeY("middle", {x: "pct_change", r: "pop", fill: "in_lockdown"}))
]
})When using the dodgeY transform, you should set the height of your plot explicitly; otherwise dots may be drawn outside the canvas. You can also adjust the range of the r scale to produce denser beeswarms.
[breaking] Color scales with diverging color schemes now default to the diverging scale type instead of the linear scale type. This includes the brbg, prgn, piyg, puor, rdbu, rdgy, rdylbu, rdylgn, spectral, burd, and buylrd schemes. If you want to use a diverging color scheme with a linear color scale, set the scale type option to linear. Color scales will also default to diverging if the scale pivot option is set. (For diverging scales, the pivot defaults to zero.)
The sort transform now supports sorting on an existing channel, avoiding the need to duplicate the channel definition. For example, to sort dots by ascending radius:
Plot.dot(earthquakes, {x: "longitude", y: "latitude", r: "intensity", sort: {channel: "r"}})The dot mark now sorts by descending radius by default to reduce occlusion. The dot mark now supports the hexagon symbol type for pointy-topped hexagons. The new circle and hexagon marks are convenience shorthand for dot marks with the circle and hexagon symbol, respectively. The dotX, dotY, textX, and textY marks now support the interval option. The rule mark now correctly respects the dx and dy options. The new hexgrid decoration mark draws a hexagonal grid; it is intended to be used with the hexbin transform as an alternative to the default horizontal and vertical axis grid.
The zero scale option (like the nice and clamp scale options) may now be specified as a top-level option, applying to all quantitative scales.
Marks can now define a channel hint to set the default range of the r scale. This is used by the hexbin transform when producing an r output channel.
Improve the performance of internal array operations, including type coercion. Thanks, @yurivish!
Fix a crash when using the area mark shorthand.
[breaking] The return signature of the internal mark.initialize method has changed. It now returns a {data, facets, channels} object instead of {index, channels}, and channels is now represented as an object with named properties representing channels rather than an iterable of [name, channel].
The new tree mark and transforms can generate hierarchical node-link diagrams using D3’s “tidy” tree or cluster (dendrogram) layout. The tree transform uses d3.stratify to convert tabular data into a hierarchy by parsing a slash-separated path for each row.
Plot.plot({
axis: null,
inset: 10,
insetRight: 120,
height: 500,
marks: Plot.tree(plotsrc, {markerEnd: "arrow"})
})The line and area marks (specifically lineX, lineY, areaX, and areaY) now support an implicit bin transform with the interval option. This can be used to “regularize” time series data, say to show gaps or default to zero when data is missing, rather than interpolating across missing data. This is also useful for stacking time series data that is sampled at irregular intervals or with missing samples.
Plot.plot({
marks: [
Plot.lineY(downloads, {x: "date", y: "downloads", interval: d3.utcDay, curve: "step"}),
Plot.areaY(downloads, {x: "date", y: "downloads", interval: d3.utcDay, fill: "#eee", curve: "step"}),
Plot.ruleY([0])
]
})The default reduce is first, picking the first value in each interval. If there is no data for a given interval, the value is undefined, resulting in a visible gap in the line or area. By using sum instead, you can default to zero when data is missing (and sum values if the data contains more than one observation per time interval).
Plot.plot({
marks: [
Plot.lineY(downloads, {x: "date", y: "downloads", interval: d3.utcDay, reduce: "sum", curve: "step"}),
Plot.areaY(downloads, {x: "date", y: "downloads", interval: d3.utcDay, reduce: "sum", fill: "#eee", curve: "step"}),
Plot.ruleY([0])
]
})The stack transform now allows the offset option to be specified as a function. For example, this can be used to visualize Likert survey results with a neutral category as a diverging stacked bar chart.
function Likert(
responses = [
["Strongly Disagree", -1],
["Disagree", -1],
["Neutral", 0],
["Agree", 1],
["Strongly Agree", 1]
]
) {
const map = new Map(responses);
return {
order: Array.from(map.keys()),
offset(facetstacks, X1, X2, Z) {
for (const stacks of facetstacks) {
for (const stack of stacks) {
const k = d3.sum(stack, i => (X2[i] - X1[i]) * (1 - map.get(Z[i]))) / 2;
for (const i of stack) {
X1[i] -= k;
X2[i] -= k;
}
}
}
}
};
}The new quantize scale type transforms a continuous domain into discrete, evenly-spaced thresholds. The threshold scale type now supports domains in descending order (in addition to ascending order), such as [20, 10, 5, 0] instead of [0, 5, 10, 20].
Plot.plot({
grid: true,
color: {
type: "quantize",
legend: true
},
marks: [
Plot.ruleY([0]),
Plot.dot(simpsons, {x: "imdb_rating", y: "us_viewers_in_millions", fill: "season"})
]
})The bin transform now coerces the input channel (the quantity being binned) to numbers as necessary. In addition, the bin transform now correctly handles typed array input channels representing temporal data. The rect mark now promotes the x channel to x1 and x2 if the latter two are not specified, and likewise the y channel to y1 and y2.
Fix a crash when text or title channels contain heterogenous types; each value is now independently formatted in a type-appropriate default formatter. Fix a rendering bug with one-dimensional rects whose opposite dimension is a band scale. Fix a rendering bug with swoopy arrows. Improve error messages to give more context.
New helpers make it easier to implement custom transforms. Plot.column constructs lazily-evaluated columns for derived channels, and Plot.transform composes a custom data transform with any of Plot’s built-in basic transforms.
The new box mark generates a horizontal or vertical boxplot suitable for visualizing one-dimensional distributions. It is a convenience mark that composites a rule, bar, tick, and dot.
Plot.boxX(morley, {x: "Speed", y: "Expt"}).plot({x: {grid: true, inset: 6}})Plot’s shorthand syntax has been expanded. The bar mark now supports one-dimensional shorthand: if no options are specified, then Plot.barX and Plot.barY can be used to visualize an array of numbers. This shorthand also now applies to the rect mark and the vector mark. The area mark now supports two-dimensional shorthand: if no options are specified, then Plot.area can be used to visualize an array of xy-tuples, similar to Plot.line.
Plot.barY(d3.range(20).map(Math.random)).plot()The mark sort options now support implicit “width” and “height” channels, defined as |x2 - x1| and |y2 - y1| respectively. These channels are useful for sorting rects and bars by length. The reverse option defaults to true when sorting by these channels. When sorting by y and no y channel is available, sorting will now fallback to y2 if available; the same fallback logic applies to x and x2. (This behavior was previously supported on marks that support implicit stacking but now applies universally to all marks.)
Plot.rectY(energy, {x: "Year", interval: 1, y: "Value", fill: "Description", sort: {color: "height"}})The bin transform now supports x and y reducers which represent the midpoint of the bin: (x1 + x2) / 2 and (y1 + y2) / 2 respectively. The bin, group, and window transforms now support percentile reducers of the form pXX where XX is a number in [00, 99]; for example p25 represents the first quartile and p75 represents the third quartile.
The error message when attempting to create a standalone legend without a valid scale definition has been improved. The high cardinality warning for the implicit z channel has been relaxed; it is now only triggered if more than half of the values are distinct. When the axis ticks option is specified as null, no ticks are generated. When the axis tickFormat option is specified as null, no tick labels are generated.
The area and line marks now support varying fill, stroke, title, and other channels within series. For example, this chart of unemployment rates by metro area highlights increases in red and decreases in blue using a window transform with the difference reducer.
Plot.line(bls, Plot.map({stroke: Plot.window({k: 2, reduce: "difference"})}, {x: "date", y: "unemployment", z: "division", stroke: "unemployment"}))The new clip mark option enables clipping to the plot frame. For example, this can be used to clip overlapping areas and produce a horizon chart of hourly traffic patterns.
d3.ticks(0, max, bands).map(t => Plot.areaY(traffic, {x: "date", y: d => d.value - t, fill: t, clip: true}))Plot can now generate helpful warnings for common mistakes. Warnings
Plot.line(aapl, {x: "Date", y: "Close"}) // 🌶 Oops, Date is a string!Warning: some data associated with the x scale are strings that appear to be dates (e.g., YYYY-MM-DD). If these strings represent dates, you should parse them to Date objects. Dates are typically associated with a "utc" or "time" scale rather than a "point" scale. If you are using a bar mark, you probably want a rect mark with the interval option instead; if you are using a group transform, you probably want a bin transform instead. If you want to treat this data as ordinal, you can suppress this warning by setting the type of the x scale to "point".
We will add more warnings in the future. If Plot did something you didn’t expect, please let us know; perhaps it will inspire a new warning that will help other users.
The text mark now supports automatic wrapping for easier annotation. The new lineWidth option specifies the desired length of a line in ems. The line breaking, wrapping, and text metrics implementations are all rudimentary, but they should be acceptable for text that is mostly ASCII. (For more control, you can hard-wrap text manually.) The monospace option now provides convenient defaults for monospaced text.
Plot.text([mobydick], {dx: 6, dy: 6, fontSize: 12, lineWidth: 80, lineHeight: 1.2, frameAnchor: "top-left", monospace: true})The line and link marks now support marker options for drawing a shape such as a dot or arrowhead on each vertex. Circle and arrow markers are provided, or you can implement a custom marker function that returns an SVG marker element. Markers automatically inherit the stroke color of the associated mark.
Plot.lineY(crimea, {x: "date", y: "deaths", stroke: "cause", marker: "circle"})The fill and stroke mark options can now be expressed as patterns or gradients using funciri color definitions, e.g. “url(#pattern)”. Colors can now also be expressed as CSS variables, e.g., “var(--blue)”. All marks now support the strokeDashoffset option (for use with strokeDasharray).
Plot.barY(alphabet, {x: "letter", y: "frequency", fill: "url(#gradient)"})The bin transform now supports the interval option, allowing numeric intervals such as integer binning with a nice default domain that aligns with interval boundaries. (The bin transform already supported time intervals as the thresholds option; time intervals can now also be specified as the interval option.) For example, if you want to bin by hour of the day, use an interval of 1:
Plot.rectY(traffic, Plot.binX({y: "mean"}, {x: d => d.date.getUTCHours(), interval: 1, y: "value"}))Plot now supports ARIA attributes for improved accessibility: aria-label, aria-description, aria-hidden. The top-level ariaLabel and ariaDescription options apply to the root SVG element. The new ariaLabel and ariaDescription scale options apply to axes; the label defaults to e.g. “y-axis” and the description defaults to the scale’s label (e.g., “↑ temperature”). Marks define a group-level aria-label (e.g., “dot”). There is also an optional ariaLabel channel for labeling data (e.g., “E 12.7%”), and a group-level ariaDescription option for a human-readable description. The ariaHidden mark option allows the hiding of decorative elements from the accessibility tree.
The new paintOrder mark option controls the paint order. The text mark’s paint order now defaults to stroke, with a stroke width of 3px and a stroke linejoin of round, making it easier to create a halo for separating labels from a busy background, improving legibility.
Fix a crash in default tuple accessors for x and y when data is undefined. Fix a bug where “none” with surrounding whitespace or capital letters would not be recognized as a valid color. When a channel is specified as a boolean value (e.g., fill: true), it is now considered a constant value rather than undefined. Fix a bug where an identity color legend would be rendered as the text “undefined” instead of showing nothing. If scale options are declared, but the scale has no defined type, domain, or data, a scale is no longer constructed rather than a default linear scale. The vector mark now respects the frameAnchor option. The default boolean color schemes have been adjusted slightly so that the false value is slightly darker, improving contrast against a white background. The returned scale object now exposes bandwidth and step values for band and point scales.
The new arrow mark draws arrows between pairs of points. It is similar to the link mark, except it is suitable for directed edges (say for representing change over time) and supports a configurable arrowhead. It also supports “swoopy” arrows with the bend option, and insets for arrows to shorten the arrow’s start or end.
Plot.arrow(data, {
x1: "POP_1980",
y1: "R90_10_1980",
x2: "POP_2015",
y2: "R90_10_2015",
bend: true,
stroke: d => d.R90_10_2015 - d.R90_10_1980
})The new vector mark similarly draws arrows at the given position (x and y) with the given magnitude (length) and direction (rotate). It is intended to visualize vector fields, such as a map of wind speed and direction.
Plot.vector((T => d3.cross(T, T))(d3.ticks(0, 2 * Math.PI, 20)), {
length: ([x, y]) => (x + y) * 2 + 2,
rotate: ([x, y]) => (Math.sin(x) - Math.sin(y)) * 60
})The dot mark now supports a symbol option to control the displayed shape, which defaults to circle. The symbol channel (and associated symbol scale) can also be used as an categorical encoding. The default symbol set is based on whether symbols are stroked or filled, improving differentiability and giving uniform weight. Plot supports all of D3’s built-in symbol types: circle, cross, diamond, square, star, triangle, and wye (for fill) and circle, plus, times, triangle2, asterisk, square2, and diamond2 (for stroke, based on Heman Robinson’s research); you can also implement a custom symbol type.
Plot.dot(penguins, {x: "body_mass_g", y: "flipper_length_mm", stroke: "species", symbol: "species"})The text mark now supports multiline text! When a text value contains \r, \r\n, or \n, it will be split into multiple lines using tspan elements. The new lineAnchor and lineHeight options control how the lines are positioned relative to the given xy position. The text, dot, and image marks now also support a frameAnchor option for positioning relative to the frame rather than according to data. This is particularly useful for annotations.
Plot.plot({
height: 200,
marks: [
Plot.frame(),
Plot.text([`This Is Just To Say\nWilliam Carlos Williams, …`], {frameAnchor: "middle"})
]
})When a text mark’s text channel, or the title channel on any mark, is specified as numbers or dates, the values are now automatically formatted (in the U.S. English locale) to improve readability. For the text channel, the default fontVariant option additionally changes to tabular-nums. The text mark now also allows fontSize to be specified as a CSS length (e.g., “12pt”), keyword (e.g., “x-large”), or percentage.
All marks now support the new standard href channel and target option, turning the mark into a clickable link.
Plot.barY(alphabet, {x: "letter", y: "frequency", href: d => `https://en.wikipedia.org/wiki/${d.letter}`})The bin and group transforms now propagate the title and href channels, if present, by default. The default reducer for the title channel automatically selects the top five distinct title values by count, making it easier to inspect the contents of a given bin or group.
Plot.rectY(data, Plot.binX({y: "count"}, {x: "body_mass_g", fill: "species", title: d => `${d.species} ${d.sex}`}))The bin transform now supports shorthand reducers for the bin extent: x1, x2, y1, and y2. The window transform now supports the first and last reducers to select the first or last element of the window, respectively.
The new generalized select transform can now call a custom selector function, or the shorthand min and max, to select the points to display. The selector function is passed two arguments: the index of the current group (e.g., [0, 1, 2, …]) and the given channel’s values. For example, to select the dot with the greatest fill value:
Plot.dotX(data, Plot.select({fill: "max"}, {x: "letter", fill: "frequency", stroke: "black"})The color scale now defaults to an identity scale if all associated defined values are valid CSS colors, rather than defaulting to the tableau10 categorical color scheme. The new symbol scale similarly defaults to identity if all associated defined values are valid symbol names (or symbol type objects).
Plot.barY(alphabet, {x: "letter", y: "frequency", fill: d => /[AEIOU]/.test(d.letter) ? "red" : "black"})The color scale now has a special default range for boolean data, encoding false as light gray and true as dark gray. If you’d prefer more color, specify a sequential scheme such as reds or blues. (You can opt-out of the special boolean range by setting the scale type to categorical or by specifying an explicit range.)
Plot.barY(alphabet, {x: "letter", y: "frequency", fill: d => /[AEIOU]/.test(d.letter)})The new Plot.scale method allows you to construct a standalone scale for use independent of any chart, or across charts. The returned object has the same form as plot.scale(name), allowing you to inspect the scale options and invoke the scale programmatically with scale.apply (and scale.invert, where applicable).
const scale = Plot.scale({color: {type: "linear"}});
console.log(scale.domain); // [0, 1]
console.log(scale.apply(0.5)); // "rgb(149, 251, 81)"This release includes various minor new features and bug fixes. The new top-level clamp option applies to all scales. When margins or insets would result in a scale’s range being inverted, Plot now collapses the range instead of producing confusing output. When the buylrd color scheme is applied to a (discrete) ordinal scale, it now has the expected colors (not rdgy). Plot now ignores non-finite values when inferring the default domain for quantitative scales. The swatches legend now wraps correctly in narrow windows. When the tickFormat option is null, ticks will now be unlabeled (rather than using the default format). Plot no longer crashes when you try to display a legend on an identity color scale.
To improve compatibility with popular bundlers such as webpack and Rollup, Plot no longer uses circular ES module imports and thereby avoids the dreaded temporal dead zone. 😱 Plot now uses vite for local development instead of Snowpack.
[breaking] For consistency with other marks, the text mark now requires the dx and dy to be specified as numbers in pixels rather than typographic units such as ems; in addition, the dx and dy translation now happens prior to rotation (if any). To affect the typographic layout, use the new lineAnchor and lineHeight options.
[breaking] Plot now requires D3 ^7.3.0.
The font-variant now only defaults to tabular-nums for axis and legend tick labels on non-ordinal scales; on ordinal scales it defaults to normal.
If a scale has an implicit label (such as inferred from a channel), the legend will now inherit the label.
The normalize transform now also supports the min, max, and deviation basis methods.
The generated figure element now resets the max-width style to initial.
Update D3 to 7.2.1.
Plot can now produce legends for color and opacity scales!
Plot.plot({
color: {
legend: true
},
marks: [
Plot.dot(athletes, {x: "weight", y: "height", stroke: "sex"})
]
})The top-level plot scale.legend option generates an inline legend for the given scale (color or opacity). Alternatively, the new plot.legend(name) function returns a legend for the scale with the given name. The new standalone Plot.legend(options) function also allows you to create a legend independently of a chart. Two forms of color legend are provided: swatches for ordinal or discrete scales (e.g., threshold color scales), and ramp for continuous scales.
The new Plot.image mark centers an image on the given xy position.
Plot.plot({
x: {
label: "Date of first inauguration →"
},
y: {
grid: true,
label: `↑ Net favorability (%)`,
percent: true,
tickFormat: "+f"
},
marks: [
Plot.ruleY([0]),
Plot.image(favorability, {x: "First Inauguration Date", y: "Net favorability", src: "Portrait URL"})
]
})All marks now support a new opacity option, either as a constant or a channel bound to the opacity scale, which sets the mark’s object opacity. The strokeOpacity or fillOpacity options should be preferred for performance, but the opacity option is needed for some cases (such as images).
All quantitative scales now have a default domain (typically [0, 1]). Ordinal scales now allow a range option to be specified in conjunction with a continuous scheme; in this case, the range should be a subset of the unit interval [0, 1], and the scheme’s interpolator will be truncated accordingly. The plot.scale method now correctly represents the symmetric transform for diverging scales. The scale definition returned by plot.scale(name) now includes a scale.apply function, allowing you to apply the scale’s encoding directly on the given data value. When applicable, a scale.invert function is also returned, which can be useful for interaction.
Plot’s stylesheet is now inlined in the generated SVG element rather than injected into the document head. To avoid namespace collisions, we use a randomly-generated class name; use the top-level className option to specify a custom class name. The default style now uses font-variant: tabular-nums for a better alignment of numbers.
A new top-level margin option allows to set all of marginLeft, marginRight, marginTop, and marginBottom at once. This shorthand notation is also available as a facet option.
Update D3 to 7.2.0.
Update D3 to 7.1.1.
The map transform now supports rank and quantile map methods. These compute the 0-based ordinal rank or the p-quantile of the data, respectively.
The bin transform now allows bin options (domain, cumulative, and thresholds) to be specified on the outputs object; this avoids ambiguity when composing multiple bin transforms. To facilitate transform composition, the bin and group transforms now consume the x1 and x2 channels when x is an output, and the y1 and y2 channels when y is an output. Also, the bin, group, and stack transforms now consume their respective transform options rather than propagating them in the returned options. The bin and group transform no longer use the channel name as the default label for the count reducer. The bin transform now automatically coerces values to dates when the thresholds are specified as a time interval or an array of dates.
The new shuffle transform randomizes the order of data. It takes an optional seed for deterministic order.
Position scales (x, y, fx, and fy) now support asymmetric insets via the scale.insetLeft, scale.insetRight, scale.insetTop, and scale.insetBottom options. Threshold and quantile scales can now be used as position scales without requiring an explicit range.
The radius scale (r) now limits the maximum default radius to 30 pixels.
Text marks now default strokeLinejoin to “round” to reduce the effect of miter joins.
Implement symmetric diverging scales by extending the domain instead of slicing the interpolator.
Fix the symmetric transform for reversed diverging scales.
The new plot.scale(name) method exposes scales used by a particular plot. This method on returned plots takes the name of a scale and returns an object specifying the options that fully describe the scale’s behavior. The returned object represents the actual options in-use, including scale.domain, scale.range, scale.interpolate, etc. The scale.label, if any, is also returned; however, note that other axis options are not. The scale object is undefined if the associated plot has no scale with the given name, and throws an error if the name is invalid (i.e., not one of the known scale names: x, y, fx, fy, r, color, or opacity). For example, given a plot:
myplot = Plot.dot(gistemp, {x: "Date", y: "Anomaly", stroke: "Anomaly"}).plot()You can retrieve the color scale like so:
mycolor = myplot.scale("color")The resulting object is:
({
type: "linear",
domain: [-0.78, 1.35],
range: [0, 1],
interpolate: d3.interpolateTurbo,
clamp: false,
label: "Anomaly"
})Inspecting materialized scales is useful for debugging and for generating color legends. (For now, we recommend using the D3 color legend; in the near future Plot will have built-in support for color legends.) Scales can also now be shared between plots, ensuring consistent encoding. To reuse a scale, pass the scale from one plot into the specification for another:
Plot.plot({…, color: myplot.scale("color")})The new scale.unknown option provides more control over how unexpected, undefined, or invalid values are displayed. For quantitative and temporal scales, the unknown value is returned whenever the input value is undefined, null, or NaN. For ordinal or categorical scales, the unknown value is returned for any input value outside the domain. For band or point scales, the unknown option has no effect; it is always equal to undefined. If the unknown option is set to undefined (the default), or null or NaN, then affected input values will be considered undefined and filtered from the output. Hence, by setting scale.unknown to a defined value, you can ensure that these values are plotted.
Plot now supports piecewise (a.k.a. “polylinear”) scales. If a single-argument interpolate function is specified (such as d3.interpolateWarm, or equivalently if you specify a color scheme such as warm), and the range is undefined, and the domain has more than two elements, the range [0, 1] will be partitioned into domain.length - 1 equal-size segments. The default scale range for x and y now supports piecewise scales, as does the default axis tick count. Additionally, ordinal color schemes now return the correct number of colors when the natural scheme size is not equal to the desired scheme size; and the rainbow and sinebow cyclical color schemes, when used with an ordinal color scale, no longer duplicate the first color as the last color.
Plot now automatically detects “reversed” quantitative or temporal scales with descending domains or ranges. Reversed scales are detected by comparing the natural order of the domain and range. This improves the default axis label arrow orientation and the behavior of the zero option.
The interval option for rect and bar now works with the default identity accessor. Also, the interval option is now ignored if the necessary value channel (e.g., x) is not defined, rather than throwing an error. For example, you no longer have to define x as the identity function here:
Plot.barX(d3.utcDays(start, end), {interval: d3.utcDay, fill: d => d})Plot’s default rounding behavior for band and point scales is now slightly smarter. Previously, automatic rounding could introduce substantial empty space on tall or wide plots; now Plot disables default rounding if it would introduce more than 30px of empty space.
The percent and transform options are now supported on all scales, including diverging scales.
The center and wiggle stack offsets now center across facets, facilitating comparison.
Internal string coercion now uses object.toString instead of object.valueOf.
Update Observable Hypertext Literal to 0.3.1.
Rect, bar, and rule marks now accept an interval option that allows you to derive x1 and x2 from x, or y1 and y2 from y, where appropriate. For example, using d3.utcDay as the interval creates rects that span from UTC midnight to UTC midnight, bounding the associated time instant. The interval is typically specifed as a D3 time interval, but may be any compatible object which implements interval.floor and interval.offset: interval.floor(x) returns the start of the interval x1 for the given x, while interval.offset(x) returns the end of the interval x2 for the given interval start x. If the interval is specified as a number n, x1 and x2 are the two consecutive multiples of n that bracket x.
The new Plot.normalize and Plot.window methods return map methods for use in conjunction with Plot.map. This allows greater flexibility; for example, you can apply separate window methods to y1 and y2 to produce Bollinger bands.
Fix a crash with the scale.tickRotate option when there are no ticks to rotate.
The constant dx and dy options have been extended to all marks, allowing to shift the mark by dx pixels horizontally and dy pixels vertically. Since only text elements accept the dx and dy properties, in all the other marks these are rendered as a transform (2D transformation) property of the mark’s parent, possibly including a 0.5px offset on low-density screens.
Quantitative scales, as well as identity position scales, now coerce channel values to numbers; both null and undefined are coerced to NaN. Similarly, time scales coerce channel values to dates; numbers are assumed to be milliseconds since UNIX epoch, while strings are assumed to be in ISO 8601 format.
Bin transform reducers now receive the extent of the current bin as an argument after the data. For example, it allows to create meaningful titles:
Plot.rect(
athletes,
Plot.bin(
{
fill: "count",
title: (bin, {x1, x2, y1, y2}) => `${bin.length} athletes weighing between ${x1} and ${x2} and with a height between ${y1} and ${y2}`
},
{
x: "weight",
y: "height",
inset: 0
}
)
).plot()The x1 and x2 outputs now default to undefined if x is explicitly defined; similary, the y1 and y2 outputs now default to undefined if y is explicitly defined.
[breaking] Plot is now published as an ES module and requires Node 12 or higher. For more, please read Sindre Sorhus’s FAQ.
[breaking] Plot now depends on D3 7.0 or higher.
The marks option now accepts render functions, null, and undefined as shorthand mark definitions. Nullish marks produce no output and are useful for conditional display (equivalent to the empty array). Render functions are invoked when plotting and may return an SVG element to insert into the plot, such as a legend or annotation.
Plot.marks(
Plot.line(aapl, {x: "Date", y: "Close"}),
() => svg`<text x=20% y=20% fill=red>Hello, world!</text>`
).plot()The Plot.marks(...marks) function provides mark.plot shorthand for array marks. This is useful for composite marks, such as boxes.
All marks now support the shapeRendering option. (This is a constant; it may not vary across marks.) All marks now allow strokeWidth to be specified as a channel. (The strokeWidth channel is unscaled; values are specified in literal pixels.) Text marks now also allow stroke and strokeOpacity to be specified as channels. If its fill is not none, a line’s default stroke is now none rather than currentColor, making it consistent with dot and other marks. When a fill or fillOpacity channel is used with a link, or when a stroke or strokeOpacity channel is used with a rule, undefined values will now be filtered. The text mark now uses attributes instead of styles for font rendering properties, improving compatibility with Firefox.
Plot.dotX(d3.range(41), {strokeWidth: d => (1 + d) / 15}).plot()Marks that represent continuous intervals (rect, bar, and rule) now handle collapsed domains during rendering. A domain is considered collapsed when it contains only a single value. A collapsed domain can occur when all input values to the bin transform are equal (e.g., [1, 1, 1, …] produces a domain of [1, 1]). Previously a collapsed domain would result in an invisible zero-width mark; now the mark spans the full extent of the chart.
Plot.rectY([1, 1, 1], Plot.binX()).plot()The link mark now supports x or y shorthand for one-dimensional links, equivalent to rule. The rect mark now supports one-dimensional (and zero-dimensional) rects: the x1, x2, y1 and y2 channels are now optional.
The new sort options allow convenient control over the order of ordinal domains, including the fx and fy facet domains. The aggregation method can be controlled via the reduce option, which defaults to max. The reverse and limit options are also supported. For example, a bar chart can be sorted by descending value like so:
Plot.barY(alphabet, {x: "letter", y: "frequency", sort: {x: "y", reverse: true}})Color scales now support the threshold scale type, allowing you to specify a set of n - 1 discrete (typically numeric) thresholds to produce n discrete colors. The new quantile color scale type will automatically compute n - 1 thresholds for n quantiles based on the data.
Plot.plot({
y: {
percent: true
},
color: {
type: "threshold",
domain: [270]
},
marks: [
Plot.ruleX(data, {x: "dem_electoral_votes", y: "probability", stroke: "dem_electoral_votes", strokeWidth: 1.5}),
Plot.ruleX([270])
]
})Diverging scales now support a symmetric option, which defaults to true, to ensure that differences above and below the pivot are equally apparent. For example, the choropleth below gives equal visual weight to West Virginia’s population decline of −3% and Alaska’s gain of +3%. If symmetric is false, as before, then −3% is mapped to the darkest purple. (Diverging scales should always use balanced interpolators where the negative and positive extremes have equal weight; this is true of Plot’s built-in diverging color schemes from ColorBrewer.)
Diverging color scales now also support transformations via four new scale types: diverging-sqrt, diverging-pow, diverging-log, and diverging-symlog, corresponding to the sqrt, pow, log, and symlog quantitative scale types respectively. (The above choropleth uses a diverging-log scale to show relative change.)
The new axis line option, which defaults to false, can be used to show a continuous line along the x or y axis to denote the extent. This is most useful when the opposite axis is ordinal and thus a rule cannot annotate a meaningful value such as zero; if the opposite axis is quantitative, a rule is generally preferred. If set at the top level, applies to both x and y.
Plot.plot({
grid: true,
inset: 6,
x: {
domain: "ABCDEFGH"
},
y: {
line: true,
domain: [0, 1]
}
})The axis and label options (along with grid) can now be set as a top-level option, or a facet-level option, and inherited by x and y or fx and fy. This is most often useful for turning off all default axes or labels by setting the respective option to null.
The mark facet option can be used to control whether or not a mark is faceted. The supported values are auto, include, exclude, and null. True is an alias for include and false is an alias for null. The default is auto, which facets a mark if and only if its data is strictly equal to the facet data. The include facet mode allows a mark with different data to be faceted; however, it requires that the mark’s data be parallel with the facet data (i.e., have the same length and order). The exclude facet mode shows all data that are not present in the current facet; this can provide shared context across facets without overdrawing. The null mode disables faceting, replicating the mark across all facets.
Plot.plot({
facet: {
data: penguins,
x: "sex",
y: "species",
marginRight: 80
},
marks: [
Plot.frame(),
Plot.dot(penguins, {
facet: "exclude",
x: "culmen_depth_mm",
y: "culmen_length_mm",
r: 2,
fill: "#ddd"
}),
Plot.dot(penguins, {
x: "culmen_depth_mm",
y: "culmen_length_mm"
})
]
})Empty facets, which can occur when faceting in both x and y, or when the specified fx or fy domain includes values not present in the data, are no longer rendered. When the facet data is null, a better error message is thrown.
The bin and group transforms now support new filter, sort and reverse options on the outputs object. By setting the filter to null, the bin transform will now return all bins, even if empty; this is useful with marks such as lines and areas that require zeroes to be present, rather than interpolating across the missing bins. (The z, fill or stroke channels, when used for grouping, are propagated to empty bins.)
Plot.plot({
marks: [
Plot.areaY(cases, Plot.binX({y: "sum", filter: null}, {
x: "specimen_collection_date",
y: "case_count",
filter: d => d.case_disposition === "Death",
fill: "transmission_category",
curve: "step",
thresholds: d3.utcWeek
})),
Plot.ruleY([0])
]
})The outputs argument to the bin and group transforms is now optional; it defaults to the count reducer for y, x and fill for Plot.binX, Plot.binY, and Plot.bin respectively, and the same for the group transforms.
The bin and group transforms now support new distinct, mode, min-index, and max-index reducers. The distinct reducer counts the number of distinct values in each group, while the mode reducer returns the most frequent value in each group. The min-index and max-index reducers are similar to min and max, except they return the zero-based index of the minimum and maximum value, respectively; for example, this is useful to sort time series by the date of each series’ peak.
Plot.plot({
height: 900,
label: null,
x: {axis: "top"},
y: {axis: null},
facet: {
data: trends,
y: "search",
marginLeft: 160
},
marks: [
Plot.areaY(trends, {x: "week", y: "interest", sort: {fy: "y", reduce: "max-index"}})
]
})The default thresholds option for the bin transforms is now auto instead of scott. The auto option applies a maximum limit of 200 bins to Scott’s rule. This reduces the risk of producing vanishing rects when they are too numerous and thin to be visible. (Note, however, that it is still possible to produce invisible rects if the insets are larger than the width.)
The normalize, window, and stack transforms can now accept a transform options argument in addition to an inputs argument that specifies the input channels. This allows makes these transforms more consistent with the other transforms, reduces ambiguity, and allows for additional shorthand. For example, you can pass k as the first argument to the window transform, here for a 24-month moving average:
Plot.plot({
y: {
label: "↑ Temperature anomaly (°C)",
tickFormat: "+f",
grid: true
},
marks: [
Plot.ruleY([0]),
Plot.line(gistemp, Plot.windowY(24, {x: "Date", y: "Anomaly"}))
]
})The offset stack options have been renamed: offset = expand is now offset = normalize, and offset = silhouette is offset = center. The shift window option has been replaced with the anchor option: shift = centered is now anchor = middle, shift = leading is anchor = start, and shift = trailing is anchor = end. The old names are supported for backwards compatibility.
The basic transforms are now available as explicit option transforms: Plot.filter, Plot.sort, and Plot.reverse. These are useful when you wish to control the order of these transforms with respect to other transforms such as Plot.bin and Plot.stack.
The select transforms now throw better error messages when required input channels are missing. When mark transform option is null, it is considered equivalent to undefined and no transform is applied instead of throwing an error.