@data-ui/histogram

A React + d3 library for creating histograms. Vertical or horizontal, raw data or binned data, numeric or categorical bins, counts or densities, cumulative or not.

npm install --save @data-ui/histogram

Demo it live at williaster.github.io/data-ui.

Example usage

Similar to the @data-ui/xy-chart package, this @data-ui/histogram package exports a parent <Histogram /> container component that renders an svg and coordinates scales across its children. You can pass the parent container optionally-animated <BarSeries /> and/or <DensitySeries /> as well as <XAxis /> and <YAxis />.

import { Histogram, DensitySeries, BarSeries, withParentSize, XAxis, YAxis } from '@data-ui/histogram';

const ResponsiveHistogram = withParentSize(({ parentWidth, parentHeight, ...rest}) => (
  <Histogram
    width={parentWidth}
    height={parentHeight}
    {...rest}
  />
);

const rawData = Array(100).fill().map(Math.random);

...
  render () {
    return (
      <ResponsiveHistogram
        ariaLabel="My histogram of ..."
        orientation="vertical"
        cumulative={false}
        normalized={true}
        binCount={25}
        valueAccessor={datum => datum}
        binType="numeric"
        renderTooltip={({ event, datum, data, color }) => (
          <div>
            <strong style={{ color }}>{datum.bin0} to {datum.bin1}</strong>
            <div><strong>count </strong>{datum.count}</div>
            <div><strong>cumulative </strong>{datum.cumulative}</div>
            <div><strong>density </strong>{datum.density}</div>
          </div>
        )}
      >
        <BarSeries
          animated
          rawData={rawData /* or binnedData={...} */}
        />
        <XAxis />
        <YAxis />
      </ResponsiveHistogram>
    );
  }

Demo with the Histogram playground.

Components

Check out the example source code and PropTable tabs in the Storybook williaster.github.io/data-ui.

<Histogram />

Name	Type	Default	Description
ariaLabel	PropTypes.string.isRequired	-	Accessibility label
binValues	PropTypes.arrayOf(PropTypes.oneOfType([PropTypes.number, PropTypes.string]))	null	Bin thresholds, overrides binCount
binCount	PropTypes.number	10	an approximate number of bins to use (if data is not already binned)
binType	PropTypes.oneOf(['numeric', 'categorical'])	'numeric'	Specify whether to bins are categorical or numeric
children	PropTypes.node.isRequired	-	Child Series, Axis, or other
cumulative	PropTypes.bool	false	whether to show a cumulative histogram
height	PropTypes.number.isRequired	-	height of the visualization
horizontal	PropTypes.bool	false	whether the histograms is oriented vertically or horizontally
limits	PropTypes.array	null	values outside the limits are ignored
margin	PropTypes.shape({ top: PropTypes.number, right: PropTypes.number, bottom: PropTypes.number, left: PropTypes.number })	{ top: 32, right: 32, bottom: 64, left: 64 }	chart margin, leave room for axes and labels!
normalized	PropTypes.bool	false	whether the value axis is normalized as fraction of total
theme	PropTypes.object	{}	chart theme object, see theme below.
width	PropTypes.number.isRequired	-	width of the svg
valueAccessor	PropTypes.func	d => d	for raw data, how to access the bin value

<*Series />

<BarSeries /> and <DensitySeries /> components accept either rawData or binnnedData. Raw data can be in any format as long as the value of each datum can be accessed with the Histogram valueAccessor function. Binned data should have the following shapes:

export const numericBinnedDatumShape = PropTypes.shape({
  id: PropTypes.string.isRequired,
  bin0: PropTypes.number.isRequired,
  bin1: PropTypes.number.isRequired,
  count: PropTypes.number.isRequired,
});

export const categoricalBinnedDatumShape = PropTypes.shape({
  id: PropTypes.string.isRequired,
  bin: PropTypes.string.isRequired,
  count: PropTypes.number.isRequired,
});

If both rawData and binnnedData are provided, rawData is ignored.

<BarSeries />

Name	Type	Default	Description
animated	PropTypes.bool	true	whether to animate updates to the data in the series
rawData	PropTypes.array	[]	raw datum
binnedData	binnedDataShape	[]	binned data
fill	PropTypes.oneOfType([PropTypes.func, PropTypes.string])	@data-ui/theme.color.default	determines bar fill color
fillOpacity	PropTypes.oneOfType([PropTypes.func, PropTypes.number])	0.7	opacity of bar fill
stroke	PropTypes.oneOfType([PropTypes.func, PropTypes.string])	'white'	determines bar stroke color
strokeWidth	PropTypes.oneOfType([PropTypes.func, PropTypes.number])	1	determines width of bar outline
onClick	PropTypes.func	--	Called on bar click with a signature of ({ event, data, datum, color, index })

<DensitySeries />

For raw data that is numeric, the <DensitySeries /> plots an estimates of the probability density function, i.e., a kernel density estimate. If pre-aggregated and/or categorical data is passed to the Series, it plots an Area graph of values based on the data counts.

Name	Type	Default	Description
animated	PropTypes.bool	true	whether to animate updates to the data in the series
rawData	PropTypes.array	[]	raw datum
binnedData	binnedDataShape	[]	binned data
fill	PropTypes.oneOfType([PropTypes.func, PropTypes.string])	@data-ui/theme.color.default	determines bar fill color
kernel	PropTypes.oneOf(['gaussian', 'parabolic'])	'gaussian'	kernel function type, parabolic = epanechnikov kernel
showArea	PropTypes.bool	true	whether to show density area fill
showLine	PropTypes.bool	true	whether to show density line path
smoothing	PropTypes.number	1	smoothing constant for parabolic / epanechinikov kernel function
fillOpacity	PropTypes.oneOfType([PropTypes.func, PropTypes.number])	0.7	opacity of area fill if shown
stroke	PropTypes.oneOfType([PropTypes.func, PropTypes.string])	'white'	determines line color if shown
strokeWidth	PropTypes.oneOfType([PropTypes.func, PropTypes.number])	2	determines width of line path if shown
strokeDasharray	PropTypes.oneOfType([PropTypes.func, PropTypes.string])	''	determines dash pattern of line if shown
strokeLinecap	PropTypes.oneOf(['butt', 'square', 'round', 'inherit'])	'round'	style of line path stroke
useEntireScale	PropTypes.bool	false	if true, density plots will scale to fill the entire y-range of the plot. if false, the maximum value is scaled to the count of the series

<XAxis /> and <YAxis />

Name	Type	Default	Description
axisStyles	axisStylesShape	{}	config object for axis and axis label styles, see theme below
label	PropTypes.oneOfType([PropTypes.string, PropTypes.element])	<text {...axisStyles.label[orientation]} />	string or component for axis labels
numTicks	PropTypes.number	null	approximate number of ticks
orientation	XAxis PropTypes.oneOf(['bottom', 'top']) or YAxis PropTypes.oneOf(['left', 'right'])	bottom, left	orientation of axis
tickStyles	tickStylesShape	{}	config object for styling ticks and tick labels, see theme below
tickLabelComponent	PropTypes.element	<text {...tickStyles.label[orientation]} />	component to use for tick labels
tickFormat	PropTypes.func	null	(tick, tickIndex) => formatted tick
tickValues	PropTypes.arrayOf(PropTypes.oneOfType([PropTypes.number, PropTypes.string]))	null	custom tick values

Tooltips

Tooltips are supported for histogram BarSeries. The easiest way to use tooltips out of the box is by passing a renderTooltip function to <Histogram /> as shown in the above example. This function takes an object with the shape { event, datum, data, color } as input and should return the inner contents of the tooltip (not the tooltip container!) as shown above. datum corresponds to the binned data point, see the above-specified shapes which depend on whether your bins are categorical or numeric. color represents the bar fill. If this function returns a falsy value, a tooltip will not be rendered.

Under the covers this will wrap the <Histogram /> component in the exported <WithTooltip /> HOC, which wraps the svg in a <div /> and handles the positioning and rendering of an HTML-based tooltip with the contents returned by renderTooltip(). This tooltip is aware of the bounds of its container and should position itself "smartly".

If you'd like more customizability over tooltip rendering you can do either of the following:

1. Roll your own tooltip positioning logic and pass onMouseMove and onMouseLeave functions to Histogram. These functions are passed to the <BarSeries /> children and are called with the signature onMouseMove({ data, datum, event, color }) and onMouseLeave() upon appropriate trigger.

2. Wrap <Histogram /> in <WithTooltip /> yourself, which accepts props for additional customization:

Name	Type	Default	Description
children	PropTypes.func or PropTypes.object	-	Child function (to call) or element (to clone) with onMouseMove, onMouseLeave, and tooltipData props/keys
className	PropTypes.string	-	Class name to add to the <div> container wrapper
renderTooltip	PropTypes.func.isRequired	-	Renders the contents of the tooltip, signature of ({ event, data, datum, color, index }) => node. If this function returns a falsy value, a tooltip will not be rendered.
styles	PropTypes.object	{}	Styles to add to the <div> container wrapper
TooltipComponent	PropTypes.func or PropTypes.object	@vx's TooltipWithBounds	Component (not instance) to use as the tooltip container component. It is passed top and left numbers for positioning
tooltipProps	PropTypes.object	-	Props that are passed to TooltipComponent
tooltipTimeout	PropTypes.number	200	Timeout in ms for the tooltip to hide upon calling onMouseLeave

Theme

A theme object with the following shape can be passed to <Histogram /> to style the chart, axes, and series. Alternatively, keys (eg xAxisStyles) can be passed directly to the axes components.

See @data-ui/theme for an example.

export const themeShape = PropTypes.shape({
  gridStyles: PropTypes.shape({
    stroke: PropTypes.string,
    strokeWidth: PropTypes.number,
  }),
  xAxisStyles: PropTypes.shape({
    stroke: PropTypes.string,
    strokeWidth: PropTypes.number,
    label: PropTypes.shape({
      bottom: PropTypes.object,
      top: PropTypes.object,
    }),
  }),
  yAxisStyles: PropTypes.shape({
    stroke: PropTypes.string,
    strokeWidth: PropTypes.number,
    label: PropTypes.shape({
      left: PropTypes.object,
      right: PropTypes.object,
    }),
  })
  xTickStyles: PropTypes.shape({
    stroke: PropTypes.string,
    tickLength: PropTypes.number,
    label: PropTypes.shape({
      bottom: PropTypes.object,
      top: PropTypes.object,
    }),
  }),
  yTickStyles: PropTypes.shape({
    stroke: PropTypes.string,
    tickLength: PropTypes.number,
    label: PropTypes.shape({
      left: PropTypes.object,
      right: PropTypes.object,
    }),
  }),
});

Development

npm install
yarn run dev # or 'build'