SMILE - Declarative Data Visualization

In previous section, we show how to visualize data in imperative way. SMILE also support data visualization in declarative approach. With smile.plot.vega package, we can create a specification that describes visualizations as mappings from data to properties of graphical marks (e.g., points or bars). The specification is based on Vega-Lite. The Vega-Lite compiler automatically produces visualization components including axes, legends, and scales. It then determines properties of these components based on a set of carefully designed rules.

This approach allows specifications to be succinct and expressive, but also provide user control. As Vega-Lite is designed for analysis, it supports data transformations such as aggregation, binning, filtering, sorting, and visual transformations including stacking and faceting. Moreover, Vega-Lite specifications can be composed into layered and multi-view displays, and made interactive with selections.

Vega-Lite website provides detailed documentation on the specification. In the below, we will show how to create a variety of charts through examples.

Bar Charts

Simple Bar Chart


var bar = new View("Simple Bar Plot")
        .description("A simple bar chart with embedded data.")
        .widthStep(30);

bar.data().values("""
        [
          {"a": "A", "b": 28}, {"a": "B", "b": 55}, {"a": "C", "b": 43},
          {"a": "D", "b": 91}, {"a": "E", "b": 81}, {"a": "F", "b": 53},
          {"a": "G", "b": 19}, {"a": "H", "b": 87}, {"a": "I", "b": 52}
        ]""");

bar.mark("bar");
Field x = bar.encode("x", "a").type("ordinal");
x.axis().labelAngle(0);
bar.encode("y", "b").type("quantitative");
bar.show();

Aggregate Bar Chart


var bar = new View("Aggregate Bar Plot")
        .description("A bar chart showing the US population distribution of age groups in 2000.")
        .heightStep(20);

bar.mark("bar");
bar.data().url("https://vega.github.io/vega-lite/examples/data/population.json");
bar.transform().filter("datum.year == 2000");
bar.encode("x", "people").type("quantitative").aggregate("sum").title("population");
bar.encode("y", "age").type("ordinal");

Aggregate Bar Chart (Sorted)


var bar = new View("Sorted Aggregate Bar Plot")
        .description("A bar chart that sorts the y-values by the x-values.")
        .heightStep(20);

bar.mark("bar");
bar.data().url("https://vega.github.io/vega-lite/examples/data/population.json");
bar.transform().filter("datum.year == 2000");
bar.encode("x", "people").type("quantitative").aggregate("sum").title("population");
bar.encode("y", "age").type("ordinal").sort("-x");

Grouped Bar Chart


var bar = new View("Group Bar Plot").widthStep(12);

bar.mark("bar");
bar.viewConfig().stroke("transparent").axis().domainWidth(1);
bar.data().url("https://vega.github.io/vega-lite/examples/data/population.json");
bar.transform()
        .filter("datum.year == 2000")
        .calculate("datum.sex == 2 ? 'Female' : 'Male'", "gender");

bar.encode("x", "gender").type("nominal").title(null);
bar.encode("y", "people").type("quantitative").aggregate("sum").axis().title("population").grid(false);
bar.encode("color", "gender").type("nominal").range("#675193", "#ca8861");
bar.encode("column", "age").type("ordinal").spacing(10);

Stacked Bar Chart


var bar = new View("Stacked Bar Plot");
bar.mark("bar");
bar.data().url("https://vega.github.io/vega-lite/examples/data/seattle-weather.csv");
bar.encode("x", "date").type("ordinal").timeUnit("month").title("Month of the year");
bar.encode("y", null).type("quantitative").aggregate("count");
bar.encode("color", "weather").type("nominal")
        .domain("sun", "fog", "drizzle", "rain", "snow")
        .range("#e7ba52", "#c7c7c7", "#aec7e8", "#1f77b4", "#9467bd")
        .legend().title("Weather type");

Stacked Bar Chart with Rounded Corners


var bar = new View("Stacked Bar with Rounded Corner");
bar.mark("bar").cornerRadiusTopLeft(3).cornerRadiusTopRight(3);
bar.data().url("https://vega.github.io/vega-lite/examples/data/seattle-weather.csv");
bar.encode("x", "date").type("ordinal").timeUnit("month").title("Month of the year");
bar.encode("y", null).type("quantitative").aggregate("count");
bar.encode("color", "weather").type("nominal");

Horizontal Stacked Bar Chart


var bar = new View("Horizontal Stacked Bar");
bar.mark("bar");
bar.data().url("https://vega.github.io/vega-lite/examples/data/barley.json");
bar.encode("x", "yield").type("quantitative").aggregate("sum");
bar.encode("y", "variety").type("nominal");
bar.encode("color", "site").type("nominal");

Layered Bar Chart


var bar = new View("Layered Bar").widthStep(17);

bar.mark("bar");
bar.background().opacity(0.7);
bar.data().url("https://vega.github.io/vega-lite/examples/data/population.json");
bar.transform()
        .filter("datum.year == 2000")
        .calculate("datum.sex == 2 ? 'Female' : 'Male'", "gender");

bar.encode("x", "age").type("ordinal");
bar.encode("y", "people").type("quantitative").aggregate("sum").title("population").stack(null);
bar.encode("color", "gender").type("nominal").range("#675193", "#ca8861");

Normalized (Percentage) Stacked Bar Chart


var bar = new View("Normalized (Percentage) Stacked Bar").widthStep(17);

bar.mark("bar");
bar.background().opacity(0.7);
bar.data().url("https://vega.github.io/vega-lite/examples/data/population.json");
bar.transform()
        .filter("datum.year == 2000")
        .calculate("datum.sex == 2 ? 'Female' : 'Male'", "gender");

bar.encode("x", "age").type("ordinal");
bar.encode("y", "people").type("quantitative").aggregate("sum").title("population").stack("normalize");
bar.encode("color", "gender").type("nominal").range("#675193", "#ca8861");

Gantt Chart


var gantt = new View("Gantt Chart");
gantt.data().values("""
        [
          {"task": "A", "start": 1, "end": 3},
          {"task": "B", "start": 3, "end": 8},
          {"task": "C", "start": 8, "end": 10}
        ]""");

gantt.mark("bar");
gantt.encode("x", "start").type("quantitative");
gantt.encode("x2", "end").type("quantitative");
gantt.encode("y", "task").type("ordinal");

A Bar Chart Encoding Color Names in the Data


var bar = new View("Bar Chart Encoding Color Names in the Data");
bar.data().values("""
        [
          {"color": "red", "b": 28},
          {"color": "green", "b": 55},
          {"color": "blue", "b": 43}
        ]""");

bar.mark("bar");
bar.encode("x", "color").type("nominal");
bar.encode("y", "b").type("quantitative");
bar.encode("color", "color").type("nominal").scale(null);

Histograms and Density Plots

Histogram


var bar = new View("Histogram");
bar.mark("bar");
bar.data().url("https://vega.github.io/vega-lite/examples/data/movies.json");
bar.encode("x", "IMDB Rating").type("quantitative").bin(true);
bar.encode("y", null).type("quantitative").aggregate("count");
bar.encode("color", "gender").type("nominal").range("#675193", "#ca8861");

Relative Frequency Histogram


var bar = new View("Relative Frequency Histogram");

bar.mark("bar").tooltip(true);
bar.data().url("https://vega.github.io/vega-lite/examples/data/cars.json");
bar.encode("x", "bin_Horsepwoer").type("quantitative").bin("binned").title("Horsepower");
bar.encode("x2", "bin_Horsepwoer_end").type("quantitative");
bar.encode("y", "PercentOfTotal").type("quantitative").title("Relative Frequency").axis().format(".1~%");

bar.transform()
        .bin("Horsepower", "bin_Horsepwoer")
        .aggregate("count", null, "Count", "bin_Horsepwoer", "bin_Horsepwoer_end")
        .joinAggregate("sum", "Count", "TotalCount")
        .calculate("datum.Count/datum.TotalCount", "PercentOfTotal");

2D Histogram Heatmap


var bar = new View("2D Histogram Heatmap").width(300).height(200);
bar.mark("rect");
bar.viewConfig().stroke("transparent");
bar.data().url("https://vega.github.io/vega-lite/examples/data/movies.json");
bar.encode("x", "IMDB Rating").type("quantitative").title("IMDB Rating").bin(new BinParams().maxBins(60));
bar.encode("y", "Rotten Tomatoes Rating").type("quantitative").bin(new BinParams().maxBins(40));
bar.encode("color", null).type("quantitative").aggregate("count");
bar.transform().filter(and(valid("IMDB Rating"), valid("Rotten Tomatoes Rating")));

Density Plot


var plot = new View("Density Plot").width(400).height(100);
plot.mark("area");
plot.data().url("https://vega.github.io/vega-lite/examples/data/movies.json");
plot.encode("x", "value").type("quantitative").title("IMDB Rating");
plot.encode("y", "density").type("quantitative");
plot.transform().density("IMDB Rating").bandwidth(0.3);

Cumulative Frequency Distribution


var plot = new View("Cumulative Frequency Distribution");
plot.mark("area");
plot.data().url("https://vega.github.io/vega-lite/examples/data/movies.json");
plot.encode("x", "IMDB Rating").type("quantitative");
plot.encode("y", "Cumulative Count").type("quantitative");
plot.transform().aggregate("count", "*", "count", "IMDB Rating")
    .window(new WindowTransformField("sum", "count", 0, "Cumulative Count"))
    .sort("IMDB Rating").frame(null, 0);

Scatterplots

Scatterplot


var bar = new View("Scatter Plot");
bar.mark("point");
bar.data().url("https://vega.github.io/vega-lite/examples/data/cars.json");
bar.encode("x", "Horsepower").type("quantitative");
bar.encode("y", "Miles_per_Gallon").type("quantitative");
bar.encode("color", "Origin").type("nominal");
bar.encode("shape", "Origin").type("nominal");

Bubble Plot


var bar = new View("Bubble Plot");
bar.mark("point");
bar.data().url("https://vega.github.io/vega-lite/examples/data/cars.json");
bar.encode("x", "Horsepower").type("quantitative");
bar.encode("y", "Miles_per_Gallon").type("quantitative");
bar.encode("size", "Acceleration").type("quantitative");

Natural Disasters


var bar = new View("Natural Disasters").width(600).height(400);
bar.mark("circle").opacity(0.8).stroke("black").strokeWidth(1);
bar.data().url("https://vega.github.io/vega-lite/examples/data/disasters.csv");
bar.transform().filter("datum.Entity !== 'All natural disasters'");
bar.encode("x", "Year").type("ordinal").axis().labelOverlap("greedy");
bar.encode("y", "Entity").type("nominal").title(null);
bar.encode("color", "Entity").type("nominal").removeLegend();
bar.encode("size", "Deaths").type("quantitative")
        .range(0, 5000)
        .legend().title("Annual Global Deaths").clipHeight(30);

Text Plot


var bar = new View("Text Plot");
bar.mark("text");
bar.data().url("https://vega.github.io/vega-lite/examples/data/cars.json");
bar.transform().calculate("split(datum.Name, ' ')[0]", "Brand");
bar.encode("x", "Horsepower").type("quantitative");
bar.encode("y", "Miles_per_Gallon").type("quantitative");
bar.encode("color", "Brand").type("nominal");
bar.encode("text", "Brand").type("nominal");

Line & Area Charts

Line Chart


var line = new View("Line Chart");
line.mark("line");
line.data().url("https://vega.github.io/vega-lite/examples/data/stocks.csv");
line.transform().filter("datum.symbol==='GOOG'");
line.encode("x", "date").type("temporal");
line.encode("y", "price").type("quantitative");

Line Chart with Point Markers


var line = new View("Line Chart with Point Mark");
line.mark("line").point(true);
line.data().url("https://vega.github.io/vega-lite/examples/data/stocks.csv");
line.encode("x", "date").type("temporal").timeUnit("year");
line.encode("y", "price").type("quantitative").aggregate("mean");
line.encode("color", "symbol").type("nominal");

Line Chart with Confidence Interval Band


var line = new View();
line.mark("line");
line.encode("x", "Year").type("temporal").timeUnit("year");
line.encode("y", "Miles_per_Gallon").type("quantitative").aggregate("mean");

var band = new View();
band.mark("errorband").extent("ci");
band.encode("x", "Year").type("temporal").timeUnit("year");
band.encode("y", "Miles_per_Gallon").type("quantitative").title("Mean of Miles per Gallon (95% CIs)");

var layer = new Layer(line, band).title("Line Chart with Confidence Interval Band");
layer.data().url("https://vega.github.io/vega-lite/examples/data/cars.json");

Rolling Averages over Raw Values


var line = new View();
line.mark("line").color("red").size(3);
line.encode("x", "date").type("temporal");
line.encode("y", "rolling_mean").type("quantitative");

var point = new View();
point.mark("point").opacity(0.3);
point.encode("x", "date").type("temporal").title("Date");
point.encode("y", "temp_max").type("quantitative").title("Max Temperature");

var layer = new Layer(line, point).title("Rolling Averages over Raw Values").width(400).height(300);
layer.data().format("csv").url("https://vega.github.io/vega-lite/examples/data/seattle-weather.csv");
layer.transform().window(new WindowTransformField("mean", "temp_max", 0, "rolling_mean")).frame(-15, 15);

Area Chart with Overlaying Lines and Point Markers


var area = new View("Area Chart with Overlaying Lines and Point Markers");
area.data().url("https://vega.github.io/vega-lite/examples/data/stocks.csv");
area.transform().filter("datum.symbol==='GOOG'");
area.mark("area").line(true).point(true);
area.encode("x", "date").type("temporal");
area.encode("y", "price").type("quantitative");

Advanced Charts

Annual Weather Heatmap


var heatmap = new View("2010 Daily Max Temperature (F) in Seattle, WA");

heatmap.mark("rect");
heatmap.data().url("https://vega.github.io/vega-lite/examples/data/seattle-weather.csv");
heatmap.encode("x", "date").type("ordinal").timeUnit("date").title("Day").axis().labelAngle(0).format("%e");
heatmap.encode("y", "date").type("ordinal").timeUnit("month");
heatmap.encode("color", "temp_max").type("quantitative").aggregate("max").legend().title(null);

heatmap.config().axis().domain(false);
heatmap.viewConfig().strokeWidth(0).step(13);

Donut Chart


var donut = new View("Donut Chart");
donut.data().values("""
        [
          {"category": 1, "value": 4},
          {"category": 2, "value": 6},
          {"category": 3, "value": 10},
          {"category": 4, "value": 3},
          {"category": 5, "value": 7},
          {"category": 6, "value": 8}
        ]""");

donut.mark("arc").innerRadius(50);
donut.encode("theta", "value").type("quantitative");
donut.encode("color", "category").type("nominal");
donut.viewConfig().stroke(null);

Radial Chart


var arc = new View();
arc.mark("arc").innerRadius(20).stroke("#fff");

var text = new View();
text.mark("text").radiusOffset(10);
text.encode("text", "data").type("quantitative");

var layer = new Layer(arc, text).title("Radial Chart");
layer.background().stroke(null);
layer.data().values("[12, 23, 47, 6, 52, 19]");
layer.encode("theta", "data").type("quantitative").stack("zero");
layer.encode("radius", "data").type("quantitative").scale("sqrt").zero(true).range(20, 100);
layer.encode("color", "data").type("nominal").removeLegend();

Box Plot


var boxplot = new View("Box Plot");
boxplot.background().stroke(null);
boxplot.mark("boxplot").extent("min-max");
boxplot.viewConfig().stroke(null);
boxplot.data().url("https://vega.github.io/vega-lite/examples/data/population.json");
boxplot.encode("x", "age").type("ordinal");
boxplot.encode("y", "people").type("quantitative").title("population");

Vertical Concatenation


Concat.vconcat(bar, aggregateBar, groupedBar).show()

Scatterplot Matrix (SPLOM)


var plot = new View().width(150).height(150);
plot.mark("point");
plot.encode("x", "repeat:column").type("quantitative").zero(false);
plot.encode("y", "repeat:row").type("quantitative").zero(false);
plot.encode("color", "species").type("nominal");

String[] row = {"petalWidth", "petalLength", "sepalWidth", "sepalLength"};
String[] column = {"sepalLength", "sepalWidth", "petalLength", "petalWidth"};
var splom = new Repeat(plot, row, column).title("Scatter Plot Matrix");
splom.data().url("https://raw.githubusercontent.com/domoritz/maps/master/data/iris.json");
splom.show();

Choropleth of Unemployment Rate per County


var geo = new View("Choropleth of Unemployment Rate per County").width(500).height(300);
geo.mark("geoshape").extent("min-max");
geo.data().topojson("https://vega.github.io/vega-lite/examples/data/us-10m.json", "feature", "counties");
geo.encode("color", "rate").type("quantitative");
geo.projection("albersUsa");

var transform = geo.transform();
var lookupData = transform.lookupData("id").fields("rate");
lookupData.data().url("https://vega.github.io/vega-lite/examples/data/unemployment.tsv");
geo.transform().lookup("id", lookupData);