Section 1.1: Setting Up Your Environment

To begin, we need to install several essential packages. Use the following command to set everything up:

npm install @visx/gradient @visx/group @visx/mock-data @visx/pattern @visx/responsive @visx/scale @visx/stats @visx/tooltip

Section 1.2: Implementing Box Plots

Now that the packages are installed, we can proceed to implement box plots. Below is an example of how to do this:

import React from "react";

import { Group } from "@visx/group";

import { ViolinPlot, BoxPlot } from "@visx/stats";

import { LinearGradient } from "@visx/gradient";

import { scaleBand, scaleLinear } from "@visx/scale";

import genStats from "@visx/mock-data/lib/generators/genStats";

import {

Tooltip,

defaultStyles as defaultTooltipStyles,

useTooltip

} from "@visx/tooltip";

import { PatternLines } from "@visx/pattern";

const data = genStats(5);

// Define your accessor functions

const x = (d) => d.boxPlot.x;

const min = (d) => d.boxPlot.min;

const max = (d) => d.boxPlot.max;

const median = (d) => d.boxPlot.median;

const firstQuartile = (d) => d.boxPlot.firstQuartile;

const thirdQuartile = (d) => d.boxPlot.thirdQuartile;

const outliers = (d) => d.boxPlot.outliers;

const Example = ({ width, height }) => {

const {

tooltipOpen,

tooltipLeft,

tooltipTop,

tooltipData,

hideTooltip,

showTooltip

} = useTooltip();

const xMax = width;

const yMax = height - 120;

const xScale = scaleBand({

range: [0, xMax],

round: true,

domain: data.map(x),

padding: 0.4

});

const values = data.reduce((allValues, { boxPlot }) => {

allValues.push(boxPlot.min, boxPlot.max);

return allValues;

}, []);

const minYValue = Math.min(...values);

const maxYValue = Math.max(...values);

const yScale = scaleLinear({

range: [yMax, 0],

round: true,

domain: [minYValue, maxYValue]

});

const boxWidth = xScale.bandwidth();

const constrainedWidth = Math.min(40, boxWidth);

return width < 10 ? null : (

<Group top={20}>

{data.map((d, i) => (

<BoxPlot

key={boxplot-${i}}

data={d.boxPlot}

x={xScale(x(d))}

width={constrainedWidth}

yScale={yScale}

{...{

minProps: {

onMouseOver: () => {

showTooltip({

tooltipTop: yScale(min(d)) + 40,

tooltipLeft: xScale(x(d)) + constrainedWidth + 5,

tooltipData: { min: min(d), name: x(d) }

});

},

onMouseLeave: hideTooltip

},

maxProps: {

onMouseOver: () => {

showTooltip({

tooltipTop: yScale(max(d)) + 40,

tooltipLeft: xScale(x(d)) + constrainedWidth + 5,

tooltipData: { max: max(d), name: x(d) }

});

},

onMouseLeave: hideTooltip

},

boxProps: {

onMouseOver: () => {

showTooltip({

tooltipTop: yScale(median(d)) + 40,

tooltipLeft: xScale(x(d)) + constrainedWidth + 5,

tooltipData: { ...d.boxPlot, name: x(d) }

});

},

onMouseLeave: hideTooltip

},

medianProps: {

style: { stroke: "white" },

onMouseOver: () => {

showTooltip({

tooltipTop: yScale(median(d)) + 40,

tooltipLeft: xScale(x(d)) + constrainedWidth + 5,

tooltipData: { median: median(d), name: x(d) }

});

},

onMouseLeave: hideTooltip

}

}}

/>

))}

{tooltipOpen && tooltipData && (

<Tooltip

top={tooltipTop}

left={tooltipLeft}

style={defaultTooltipStyles}

>

{tooltipData.name}

{tooltipData.max && Max: ${tooltipData.max}}

{tooltipData.thirdQuartile && Third Quartile: ${tooltipData.thirdQuartile}}

{tooltipData.median && Median: ${tooltipData.median}}

{tooltipData.firstQuartile && First Quartile: ${tooltipData.firstQuartile}}

{tooltipData.min && Min: ${tooltipData.min}}

</Tooltip>

)}

</Group>

);

};

export default function App() {

return (

<svg width={800} height={500}>

<Example width={800} height={500} />

</svg>

);

}

The data variable contains the information for the box plot, while the functions that follow serve as accessors for various statistical values. In the Example component, we utilize the useTooltip hook to display tooltips when hovering over the box plots.

We collect the necessary values for the box plots and establish a scale for the y-axis. The box plots are rendered using data.map, which creates box plot components for each data point. The ViolinPlot component is used to display the surrounding violin plot, while the BoxPlot component creates the box plot itself.

Tooltips are displayed upon hovering over different parts of the box plot, providing detailed information about the data.