Baltimore race

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		<meta charset="utf-8">
		<title>Line Chart</title>
		<script type="text/javascript" src="https://d3js.org/d3.v3.js"></script>
		<style type="text/css">
			
			body {
				background-color: white;
				font-family: Helvetica, Arial, sans-serif;
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h1 {
				font-size: 24px;
				margin: 0;
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p {
				font-size: 14px;
				margin: 10px 0 0 0;
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svg {
				background-color: white;
			}

circle:hover {
				fill: orange;
			}
			path {
				stroke: gray;
				stroke-width: 2;
			}

g.black path {
				stroke: steelblue;
				stroke-width: 2;
			}

g.white path {
				stroke: red;
				stroke-width: 2;
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			.axis path,
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			.axis text {
				font-family: sans-serif;
				font-size: 11px;
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<h1>Baltimore's Racial Composition</h1>

<p>Populuation of <strong style="color: steelblue;">blacks,</strong> <strong style="color: red;">whites</strong> and <strong style="color: gray;">others</strong>, 1970-2013; in thousands. Source: <a href="https://www.census.gov/popest/data/historical/index.html">U.S. Census Bureau</a></p>

var w = 700;
			var h = 600;
			var padding = [ 20, 10, 50, 100 ];  //Top, right, bottom, left

//Set up date formatting and years
			var dateFormat = d3.time.format("%Y");

var xScale = d3.time.scale()
								.range([ padding[3], w - padding[1] - padding[3] ]);
			
			var yScale = d3.scale.linear()
								.range([ padding[0], h - padding[2] ]);

var xAxis = d3.svg.axis()
							.scale(xScale)
							.orient("bottom")
							.ticks(15)
							.tickFormat(function(d) {
								return dateFormat(d);
							});

var yAxis = d3.svg.axis()
							.scale(yScale)
							.orient("left");

var line = d3.svg.line()
				.x(function(d) {
					return xScale(dateFormat.parse(d.year));
				})
				.y(function(d) {
					return yScale(d.amount);
				});

var svg = d3.select("body")
						.append("svg")
						.attr("width", w)
						.attr("height", h);

//Load data
			d3.csv("BaltimoreRace2.csv", function(data) {

//Data is loaded in, but we need to restructure it.
				//Remember, each line requires an array of x/y pairs;
				//that is, an array of arrays, like so:
				//
				//	[ [x: 1, y: 1], [x: 2, y: 2], [x: 3, y: 3] ]
				//
				//We, however, are using 'year' as x and 'amount' as y.
				//We also need to know which race belongs to each
				//line, so we will build an array of objects that is
				//structured like this:
				/*

[
						{
							race: "Australia",
							population: [
										{ year: 1961, amount: 90589.568 },
										{ year: 1962, amount: 94912.961 },
										{ year: 1963, amount: 101029.517 },
										…
									   ]
						},
						{
							race: "Bermuda",
							population: [
										{ year: 1961, amount: 176.016 },
										{ year: 1962, amount: 157.681 },
										{ year: 1963, amount: 150.347 },
										…
									   ]
						},
						…
					 ]

*/
				//Note that this is an array of objects. Each object
				//contains two values, 'race' and 'population'.
				//The 'population' value is itself an array, containing
				//more objects, each one holding 'year' and 'amount' values.

//New array with all the years, for referencing later
				var years = ["1970", "1971", "1972", "1973", "1974", "1975", "1976", "1977", "1978", "1979", "1980", "1981", "1982", "1983", "1984", "1985", "1986", "1987", "1988", "1989", "1990", "1991", "1992", "1993", "1994", "1995", "1996", "1997", "1998", "1999", "2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013"];

//Create a new, empty array to hold our restructured dataset
				var dataset = [];

//Loop once for each row in data
				for (var i = 0; i < data.length; i++) {

//Create new object with this race's name and empty array
					dataset[i] = {
						race: data[i].raceCat,
						population: []
					};

//Loop through all the years
					for (var j = 0; j < years.length; j++) {

// If value is not empty
						if (data[i][years[j]]) {
							//Add a new object to the population data array
							//for this race
							dataset[i].population.push({
								year: years[j],
								amount: data[i][years[j]]
							});
						}

}

}
				
				//Uncomment to log the original data to the console
				// console.log(data);

//Uncomment to log the newly restructured dataset to the console
				// console.log(dataset);

//Set scale domains
				xScale.domain([ 
					d3.min(years, function(d) {
						return dateFormat.parse(d);
					}),
					d3.max(years, function(d) {
						return dateFormat.parse(d);
					})
				]);

yScale.domain([ 
					d3.max(dataset, function(d) {
						return d3.max(d.population, function(d) {
							return +d.amount;
						});
					}),
					0
				]);

//Make a group for each race
				var groups = svg.selectAll("g")
					.data(dataset)
					.enter()
					.append("g")
					.classed("black", function(d) {

if (d.race == "Black") {
							return true;
						} else {
							return false;
						}

})
					.classed("white", function(d) {

if (d.race == "White") {
							return true;
						} else {
							return false;
						}

});

//Append a title with the race name (so we get easy tooltips)
				groups.append("title")
					.text(function(d) {
						return d.race;
					});

//Within each group, create a new line/path,
				//binding just the population data to each one
				groups.selectAll("path")
					.data(function(d) {
						return [ d.population ];
					})
					.enter()
					.append("path")
					.attr("class", "line")
					.attr("d", line)
					.attr("fill", "none")
					.attr("stroke", "steelblue")
					.attr("stroke-width", 2);

//Axes
				svg.append("g")
					.attr("class", "x axis")
					.attr("transform", "translate(0," + (h - padding[2]) + ")")
					.call(xAxis);

svg.append("g")
					.attr("class", "y axis")
					.attr("transform", "translate(" + (padding[3]) + ",0)")
					.call(yAxis);

});
			//End USA data load function

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