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	<title>Flot Examples: Percentiles</title>
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	$(function() {

		var males = {"15%": [[2, 88.0], [3, 93.3], [4, 102.0], [5, 108.5], [6, 115.7], [7, 115.6], [8, 124.6], [9, 130.3], [10, 134.3], [11, 141.4], [12, 146.5], [13, 151.7], [14, 159.9], [15, 165.4], [16, 167.8], [17, 168.7], [18, 169.5], [19, 168.0]], "90%": [[2, 96.8], [3, 105.2], [4, 113.9], [5, 120.8], [6, 127.0], [7, 133.1], [8, 139.1], [9, 143.9], [10, 151.3], [11, 161.1], [12, 164.8], [13, 173.5], [14, 179.0], [15, 182.0], [16, 186.9], [17, 185.2], [18, 186.3], [19, 186.6]], "25%": [[2, 89.2], [3, 94.9], [4, 104.4], [5, 111.4], [6, 117.5], [7, 120.2], [8, 127.1], [9, 132.9], [10, 136.8], [11, 144.4], [12, 149.5], [13, 154.1], [14, 163.1], [15, 169.2], [16, 170.4], [17, 171.2], [18, 172.4], [19, 170.8]], "10%": [[2, 86.9], [3, 92.6], [4, 99.9], [5, 107.0], [6, 114.0], [7, 113.5], [8, 123.6], [9, 129.2], [10, 133.0], [11, 140.6], [12, 145.2], [13, 149.7], [14, 158.4], [15, 163.5], [16, 166.9], [17, 167.5], [18, 167.1], [19, 165.3]], "mean": [[2, 91.9], [3, 98.5], [4, 107.1], [5, 114.4], [6, 120.6], [7, 124.7], [8, 131.1], [9, 136.8], [10, 142.3], [11, 150.0], [12, 154.7], [13, 161.9], [14, 168.7], [15, 173.6], [16, 175.9], [17, 176.6], [18, 176.8], [19, 176.7]], "75%": [[2, 94.5], [3, 102.1], [4, 110.8], [5, 117.9], [6, 124.0], [7, 129.3], [8, 134.6], [9, 141.4], [10, 147.0], [11, 156.1], [12, 160.3], [13, 168.3], [14, 174.7], [15, 178.0], [16, 180.2], [17, 181.7], [18, 181.3], [19, 182.5]], "85%": [[2, 96.2], [3, 103.8], [4, 111.8], [5, 119.6], [6, 125.6], [7, 131.5], [8, 138.0], [9, 143.3], [10, 149.3], [11, 159.8], [12, 162.5], [13, 171.3], [14, 177.5], [15, 180.2], [16, 183.8], [17, 183.4], [18, 183.5], [19, 185.5]], "50%": [[2, 91.9], [3, 98.2], [4, 106.8], [5, 114.6], [6, 120.8], [7, 125.2], [8, 130.3], [9, 137.1], [10, 141.5], [11, 149.4], [12, 153.9], [13, 162.2], [14, 169.0], [15, 174.8], [16, 176.0], [17, 176.8], [18, 176.4], [19, 177.4]]};

		var females = {"15%": [[2, 84.8], [3, 93.7], [4, 100.6], [5, 105.8], [6, 113.3], [7, 119.3], [8, 124.3], [9, 131.4], [10, 136.9], [11, 143.8], [12, 149.4], [13, 151.2], [14, 152.3], [15, 155.9], [16, 154.7], [17, 157.0], [18, 156.1], [19, 155.4]], "90%": [[2, 95.6], [3, 104.1], [4, 111.9], [5, 119.6], [6, 127.6], [7, 133.1], [8, 138.7], [9, 147.1], [10, 152.8], [11, 161.3], [12, 166.6], [13, 167.9], [14, 169.3], [15, 170.1], [16, 172.4], [17, 169.2], [18, 171.1], [19, 172.4]], "25%": [[2, 87.2], [3, 95.9], [4, 101.9], [5, 107.4], [6, 114.8], [7, 121.4], [8, 126.8], [9, 133.4], [10, 138.6], [11, 146.2], [12, 152.0], [13, 153.8], [14, 155.7], [15, 158.4], [16, 157.0], [17, 158.5], [18, 158.4], [19, 158.1]], "10%": [[2, 84.0], [3, 91.9], [4, 99.2], [5, 105.2], [6, 112.7], [7, 118.0], [8, 123.3], [9, 130.2], [10, 135.0], [11, 141.1], [12, 148.3], [13, 150.0], [14, 150.7], [15, 154.3], [16, 153.6], [17, 155.6], [18, 154.7], [19, 153.1]], "mean": [[2, 90.2], [3, 98.3], [4, 105.2], [5, 112.2], [6, 119.0], [7, 125.8], [8, 131.3], [9, 138.6], [10, 144.2], [11, 151.3], [12, 156.7], [13, 158.6], [14, 160.5], [15, 162.1], [16, 162.9], [17, 162.2], [18, 163.0], [19, 163.1]], "75%": [[2, 93.2], [3, 101.5], [4, 107.9], [5, 116.6], [6, 122.8], [7, 129.3], [8, 135.2], [9, 143.7], [10, 148.7], [11, 156.9], [12, 160.8], [13, 163.0], [14, 165.0], [15, 165.8], [16, 168.7], [17, 166.2], [18, 167.6], [19, 168.0]], "85%": [[2, 94.5], [3, 102.8], [4, 110.4], [5, 119.0], [6, 125.7], [7, 131.5], [8, 137.9], [9, 146.0], [10, 151.3], [11, 159.9], [12, 164.0], [13, 166.5], [14, 167.5], [15, 168.5], [16, 171.5], [17, 168.0], [18, 169.8], [19, 170.3]], "50%": [[2, 90.2], [3, 98.1], [4, 105.2], [5, 111.7], [6, 118.2], [7, 125.6], [8, 130.5], [9, 138.3], [10, 143.7], [11, 151.4], [12, 156.7], [13, 157.7], [14, 161.0], [15, 162.0], [16, 162.8], [17, 162.2], [18, 162.8], [19, 163.3]]};

		var dataset = [
			{ label: "Female mean", data: females["mean"], lines: { show: true }, color: "rgb(255,50,50)" },
			{ id: "f15%", data: females["15%"], lines: { show: true, lineWidth: 0, fill: false }, color: "rgb(255,50,50)" },
			{ id: "f25%", data: females["25%"], lines: { show: true, lineWidth: 0, fill: 0.2 }, color: "rgb(255,50,50)", fillBetween: "f15%" },
			{ id: "f50%", data: females["50%"], lines: { show: true, lineWidth: 0.5, fill: 0.4, shadowSize: 0 }, color: "rgb(255,50,50)", fillBetween: "f25%" },
			{ id: "f75%", data: females["75%"], lines: { show: true, lineWidth: 0, fill: 0.4 }, color: "rgb(255,50,50)", fillBetween: "f50%" },
			{ id: "f85%", data: females["85%"], lines: { show: true, lineWidth: 0, fill: 0.2 }, color: "rgb(255,50,50)", fillBetween: "f75%" },

			{ label: "Male mean", data: males["mean"], lines: { show: true }, color: "rgb(50,50,255)" },
			{ id: "m15%", data: males["15%"], lines: { show: true, lineWidth: 0, fill: false }, color: "rgb(50,50,255)" },
			{ id: "m25%", data: males["25%"], lines: { show: true, lineWidth: 0, fill: 0.2 }, color: "rgb(50,50,255)", fillBetween: "m15%" },
			{ id: "m50%", data: males["50%"], lines: { show: true, lineWidth: 0.5, fill: 0.4, shadowSize: 0 }, color: "rgb(50,50,255)", fillBetween: "m25%" },
			{ id: "m75%", data: males["75%"], lines: { show: true, lineWidth: 0, fill: 0.4 }, color: "rgb(50,50,255)", fillBetween: "m50%" },
			{ id: "m85%", data: males["85%"], lines: { show: true, lineWidth: 0, fill: 0.2 }, color: "rgb(50,50,255)", fillBetween: "m75%" }
		];

		$.plot($("#placeholder"), dataset, {
			xaxis: {
				tickDecimals: 0
			},
			yaxis: {
				tickFormatter: function (v) {
					return v + " cm";
				}
			},
			legend: {
				position: "se"
			}
		});

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	});

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		<h2>Percentiles</h2>
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		<p>Height in centimeters of individuals from the US (2003-2006) as function of age in years (source: <a href="http://www.cdc.gov/nchs/data/nhsr/nhsr010.pdf">CDC</a>). The 15%-85%, 25%-75% and 50% percentiles are indicated.</p>

		<p>For each point of a filled curve, you can specify an arbitrary bottom. As this example illustrates, this can be useful for plotting percentiles. If you have the data sets available without appropriate fill bottoms, you can use the fillbetween plugin to compute the data point bottoms automatically.</p>

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