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JDR VI10 for CS725@ODU

Name: Joel D. Rodriguez-Ortiz

Usage

The bottom view is a scatterplot matrix of all the numerical values of the football data set. This view can be panned by dragging with the mouse and zoomed in and out with the mouse scroll wheel. Double-clicking on any of the scatterplots in the matrix will update the (upper) juxtaposed view with the selected scatterplot. Points in this plot can also be clicked to show player details in the corner. The details shown in the corner are filtered by the plot selected from the matrix, they will match the axes shown in the currently selected scatterplot.

Notes

The original intent of this idea was implementing juxtaposed, coordinated, side-by-side (top-to-bottom in this case) views. The views share a subset of the data in an overview/detail type fashion.

For the longest time now I've been wanting to use other attributes from the football data set other than Passing Yards vs Passing Attempts. And scatterplot matrices are a perfect example of the small multiples idiom discussed in CH12. So I thought why not just plot all the attributes of the dataset?!

The idea was that you would use the scatterplot matrix to search for trends of interest. But, by providing the ability to pan, I wouldn't have to limit the number of attributes in the matrix. In essence you were also using it as a bird's eye map, to hone in on a combination of attributes that exhibited a strong relation to each other and then shifting your attention to the detailed view (akin to the CH6 Overview First Details Later rule of thumb). Scatterplot matrices are also an example of small multiples, another idiom discussed in CH12.

The implementation worked more or less as I wanted, but ran into a problem mentioned repeatedly in the chapter: screen real estate (this may have been made worse by working with a bl.ocks.org block). I wound up making the detailed view slightly smaller than I originally wanted to and had to stack them vertically because horizontally they looked odd inside the block. I placed the scatterplot matrix below the detailed view as if they were navigation controls. In the end both views fit into the screen and exercise juxtaposed views as originally intended. The navigation flow should go from searching for trends in the scatterplot matrix, to selecting a scatterplot showing attributes of interest, to further inspecting individual values within the scatterplot.

// http://colorbrewer2.org/
function ColorMap()
{
// public
this.byConference = function(conference) // no restrictions
{
if (bigFive.indexOf(conference) >= 0)
{
return colors[0];
}
if (groupOfFive.indexOf(conference) >= 0)
{
return colors[1];
}
return colors[2];
};
this.getConferenceColors = function()
{
return [
{ category: 'Big Five', color: colors[0] },
{ category: 'Group Of Five', color: colors[1] },
{ category: 'Independent', color: colors[2] }
];
};
// private variables
var bigFive = [ 'SEC', 'ACC', 'Big 12', 'Pac-12', 'Big Ten' ];
var groupOfFive = [ 'American', 'Sun Belt', 'MWC', 'MAC', 'CUSA' ];
var colors = [ '#e41a1c', '#377eb8', '#4daf4a' ];
}
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function Detail(g, // <g></g>
gw, // group width
gh, // group height
dw, // detail width
dh, // detail height
dp, // detail padding
fs, // font size
fp) // font padding
{
this.update = function(details) {
// create text
if (text == null)
{
text = detail.selectAll('text')
.data(details)
.enter()
.append('text')
.text(function(d) { return d; })
.attr('transform', function(d, i) {
var x = 3;
var y = (fontSize + fontPadding) * i;
y += tweak;
return 'translate(' + x + ',' + y + ')';
})
.style({
'font-family': 'sans-serif',
'font-size': fontSize + 'px'
});
}
else
{
// update text
text.data(details)
.text(function (d) { return d; });
}
};
var groupWidth = gw;
var groupHeight = gh;
var width = dw;
var height = dh;
var padding = dp || 50;
var fontSize = fs || 12;
var fontPadding = fp || 3;
var tweak = 16;
var detail = g.append('g')
.attr('class', 'detail')
.attr('transform', 'translate(' + (groupWidth - width - padding) + ','
+ (groupHeight - height - padding) + ')');
detail.append('rect')
.attr('width', width)
.attr('height', height)
.attr('fill', 'none')
.attr('stroke', 'black');
var text = null;
}
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>Homework</title>
<script src="d3.min.js" type="text/javascript"></script>
<script src="color_map.js" type="text/javascript"></script>
<script src="detail.js" type="text/javascript"></script>
<script src="legend.js" type="text/javascript"></script>
<script src="scatterplot.js" type="text/javascript"></script>
<script src="setup.js" type="text/javascript"></script>
<link href="main.css" rel="stylesheet" type="text/css" />
</head>
<body style="text-align: center;">
<div id="chart1" class="chart-div">
</div>
<div id="chart0" class="chart-div">
</div>
<script src="main.js" type="text/javascript"></script>
</body>
</html>
function Legend(g, // <g></g>
mw, // mark width
mh, // mark height
mp) // mark padding
{
mw = mw || 25;
mh = mh || 25;
mp = mp || 10;
// public
this.draw = function(marks)
{
var m = group.selectAll('.legend')
.data(marks)
.enter()
.append('g')
.attr('class', 'legend');
m.append('rect')
.attr('x', 0)
.attr('y', function(d, i) {
return (markHeight + markPadding) * i;
})
.attr('width', markWidth)
.attr('height', markHeight)
.attr('fill', function(d) {
return d.color;
});
m.append('text')
.attr('transform', function(d, i) {
var x = markWidth + markPadding;
var y = (markHeight + markPadding) * i;
y += tweak;
return 'translate(' + x + ',' + y + ')';
})
.attr('class', 'legend-text')
.text(function(d) {
return d.category;
});
};
// private
var group = g;
var markWidth = mw;
var markHeight = mh;
var markPadding = mp;
var tweak = 16;
}
body
{
cursor: default;
}
.small .axis path,
.small .axis line
{
fill: none;
stroke: black;
stroke-width: 0.25px;
shape-rendering: crispEdges;
}
.small .axis text
{
font-family: sans-serif;
font-size: 2px;
}
.small .axis-title
{
font-family: sans-serif;
}
text
{
cursor: default;
}
.chart-div
{
margin: 25px 25px 25px 25px;
display: inline;
}
.small circle
{
stroke: black;
stroke-width: 0.15px;
}
.axis path,
.axis line
{
fill: none;
stroke: black;
shape-rendering: crispEdges;
}
.axis text,
.legend-text
{
font-family: sans-serif;
font-size: 10px;
}
.hover-label
{
font-family: sans-serif;
font-size: 14px;
font-weight: bold;
}
#chart1 circle
{
stroke: black;
stroke-width: 1px;
}
function createZoomableContainer(group, width, height)
{
var zoom = d3.behavior.zoom()
.scaleExtent([ 0.90, 5 ])
.on('zoom', zoomed);
group.call(zoom);
var rect = group.append('rect')
.attr('width', width)
.attr('height', height)
.style('fill', 'none')
.style('pointer-events', 'all');
var container = group.append('g');
function zoomed()
{
container.attr('transform',
'translate(' + d3.event.translate + ')scale(' +
d3.event.scale + ')');
}
group.on('dblclick.zoom', null);
return container;
}
var raw = null;
d3.csv('passing_stats.csv', function(error, data)
{
raw = data;
});
var id0 = window.setInterval(function() {
if (raw != null)
{
var columns = [
'Rk',
'Cmp',
'Passing Attempts',
'Pct',
'Passing Yards',
'Y/A',
'AY/A',
'Passing TD',
'Interceptions',
'Rate',
'Rushing Attempts',
'Rushing Yards',
'Rushing Avg',
'Rushing TD'
];
var absoluteWidth = 1000;
var plotsPerRow = columns.length;
var plotWidth = absoluteWidth / plotsPerRow;
var plotHeight = absoluteWidth / plotsPerRow;
var plotPadding = 10;
var radius = 0.75;
var viewportWidth = 800;
var viewportHeight = 400;
var svg = d3.select('#chart0')
.append('svg')
.attr('width', viewportWidth)
.attr('height', viewportHeight);
var container = createZoomableContainer(svg, viewportWidth, viewportHeight);
var groups = [];
for (var i = 0; i < columns.length * columns.length / plotsPerRow; ++i)
{
for (var j = 0; j < plotsPerRow; ++j)
{
var group = container.append('g')
.attr('transform', 'translate(' + plotWidth * j
+ ',' + plotHeight * i + ')')
.attr('class', 'small')
.on('dblclick', function() {
var axes = d3.select(this).attr('data').split(',');
drawDetailedView(axes[0], axes[1]);
});
groups.push(group);
}
}
var datasets = [];
var color = new ColorMap();
var k = 0;
for (i = 0; i < columns.length; ++i)
{
for (j = 0; j < columns.length; ++j)
{
if (i != j)
{
var dataset = [];
raw.forEach(function(v) {
dataset.push({
x: Number(v[columns[j]]),
y: Number(v[columns[i]]),
name: v['Player'],
conference: v['Conf'],
color: color.byConference(v['Conf']),
radius: radius,
layer: 0
});
});
datasets.push(dataset);
}
else
{
datasets.push(columns[i]); // diagonal title
}
groups[k].attr('data', columns[j] + ',' + columns[i]);
++k;
}
}
var fontSize = 10;
datasets.forEach(function(ds, i) {
if (typeof(ds) != 'string')
{
var scatterplot = new Scatterplot(
groups[i], datasets[i], plotWidth, plotHeight, plotPadding);
groups[i].append('rect')
.attr('width', plotWidth)
.attr('height', plotHeight)
.style('fill', 'none')
.style('pointer-events', 'all');
scatterplot.draw();
}
else
{
var words = ds.split(' ');
words.forEach(function(word, w) {
groups[i].append('text')
.attr('x', 0)
.attr('y', plotHeight / 2 + fontSize * w)
.attr('class', 'axis-title')
.text(word)
.attr('style', 'font-size: ' + fontSize + 'px');
});
}
});
window.clearInterval(id0);
drawDetailedView('Passing Attempts', 'Passing Yards');
}
}, 100);
function drawDetailedView(xaxis, yaxis)
{
d3.select('#chart1').select('svg').remove();
var width = 800;
var height = 500;
var padding = 50;
var dataset = [];
var color = new ColorMap();
var radius = 5;
raw.forEach(function(v) {
dataset.push({
x: Number(v[xaxis]),
y: Number(v[yaxis]),
name: v['Player'],
conference: v['Conf'],
color: color.byConference(v['Conf']),
radius: radius,
layer: 0
});
});
var svg = d3.select('#chart1')
.append('svg')
.attr('width', width)
.attr('height', height);
var scatterplot = new Scatterplot(svg, dataset, width, height, padding);
scatterplot.draw();
scatterplot.makeHoverLabels(function(d) { return d.name; });
scatterplot.drawAxisLabels(yaxis, xaxis);
var lg = svg.append('g')
.attr('transform', 'translate(100,50)');
var legend = new Legend(lg);
legend.draw(color.getConferenceColors());
var last = null;
var detail = new Detail(svg,
width - padding,
height - padding,
width * 0.21,
height * 0.15,
10, 9);
scatterplot.each(function() {
d3.select(this)
.on('click', function(d) {
if (last != null)
{
last.color = color.byConference(last.conference);
last.radius = radius;
last.layer = 0;
}
d.color = 'orange';
d.radius = radius * 2;
d.layer = 1;
last = d;
scatterplot.draw();
var details;
raw.forEach(function(r) {
if (d.name == r['Player'])
{
details = [
'Rank: ' + r['Rk'],
'Name: ' + r['Player'],
'School: ' + r['School'],
xaxis + ': ' + r[xaxis],
yaxis + ': ' + r[yaxis]
];
}
});
if (details)
{
detail.update(details);
}
});
});
}
Rk Player School Conf Cmp Passing Attempts Pct Passing Yards Y/A AY/A Passing TD Interceptions Rate Rushing Attempts Rushing Yards Rushing Avg Rushing TD
1 Marcus Mariota Oregon Pac-12 254 372 68.3 3773 10.1 11.9 38 2 186.1 117 669 5.7 14
2 Garrett Grayson Colorado State MWC 250 386 64.8 3779 9.8 10.7 32 6 171.3 53 -25 -0.5 0
3 Zach Terrell Western Michigan MAC 231 330 70.0 3146 9.5 9.6 23 10 167.0 67 203 3.0 3
4 Blake Sims Alabama SEC 230 355 64.8 3250 9.2 9.7 26 7 161.9 73 321 4.4 6
5 Jake Waters Kansas State Big 12 231 349 66.2 3163 9.1 9.4 20 6 157.8 139 471 3.4 8
6 Connor Cook Michigan State Big Ten 188 323 58.2 2900 9.0 9.5 22 6 152.4 45 69 1.5 2
7 J.T. Barrett Ohio State Big Ten 203 314 64.6 2834 9.0 9.8 34 10 169.8 171 938 5.5 11
8 Grant Hedrick Boise State MWC 270 381 70.9 3387 8.9 8.5 22 13 157.8 147 563 3.8 8
9 Bryce Petty Baylor Big 12 234 377 62.1 3305 8.8 9.4 26 6 155.3 77 137 1.8 5
10 Rakeem Cato Marshall CUSA 242 414 58.5 3622 8.7 9.1 37 13 155.2 84 457 5.4 6
11 Bo Wallace Mississippi SEC 219 358 61.2 3108 8.7 8.5 22 11 148.2 107 218 2.0 5
12 Dak Prescott Mississippi State SEC 210 344 61.0 2987 8.7 8.8 24 10 151.2 195 939 4.8 13
13 Gary Nova Rutgers Big Ten 178 307 58.0 2667 8.7 8.2 20 12 144.6 43 -35 -0.8 3
14 Brad Kayaa Miami (FL) ACC 202 345 58.6 2962 8.6 8.6 25 11 148.2 24 -124 -5.2 1
15 Brandon Doughty Western Kentucky CUSA 344 510 67.5 4344 8.5 9.4 44 10 163.5 37 -56 -1.5 2
16 Cody Kessler Southern California Pac-12 292 413 70.7 3505 8.5 9.8 36 4 168.8 52 -149 -2.9 2
17 Nick Marshall Auburn SEC 163 271 60.1 2315 8.5 8.7 18 7 148.7 146 780 5.3 11
18 Jameis Winston Florida State ACC 276 422 65.4 3559 8.4 7.8 24 17 147.0 50 82 1.6 3
19 Patrick Mahomes Texas Tech Big 12 105 185 56.8 1547 8.4 9.1 16 4 151.2 47 98 2.1 0
20 Gunner Kiel Cincinnati American 219 364 60.2 3010 8.3 8.6 30 11 150.8 57 136 2.4 1
21 Kenny Hill Texas A&M SEC 214 321 66.7 2649 8.3 8.6 23 8 154.6 52 156 3.0 0
22 Brett Hundley UCLA Pac-12 259 368 70.4 3019 8.2 8.7 21 5 155.4 148 548 3.7 8
23 Driphus Jackson Rice CUSA 176 307 57.3 2524 8.2 8.4 21 8 143.8 108 360 3.3 1
24 Everett Golson Notre Dame Ind 250 416 60.1 3355 8.1 7.9 29 14 144.1 113 280 2.5 8
25 Taylor Lamb Appalachian State Sun Belt 181 295 61.4 2381 8.1 7.9 17 9 142.1 78 483 6.2 4
26 Cody Clements Alabama-Birmingham CUSA 181 273 66.3 2221 8.1 7.9 13 7 145.2 91 160 1.8 4
27 Trevone Boykin Texas Christian Big 12 279 462 60.4 3714 8.0 8.7 30 7 146.3 141 659 4.7 8
28 Chad Voytik Pittsburgh ACC 158 252 62.7 2011 8.0 7.9 15 7 143.8 102 426 4.2 3
29 Dylan Thompson South Carolina SEC 248 417 59.5 3280 7.9 7.8 24 11 139.3 60 -53 -0.9 3
30 Cooper Rush Central Michigan MAC 215 337 63.8 2664 7.9 7.5 20 12 142.7 38 -77 -2.0 0
31 Tommy Armstrong Jr Nebraska Big Ten 152 294 51.7 2314 7.9 7.5 19 11 131.7 133 664 5.0 5
32 Trevor Knight Oklahoma Big 12 162 279 58.1 2197 7.9 7.4 14 9 134.3 66 340 5.2 5
33 Shane Carden East Carolina American 358 551 65.0 4302 7.8 8.2 28 8 144.4 87 94 1.1 6
34 Jared Goff California Pac-12 315 509 61.9 3964 7.8 8.5 35 7 147.2 55 -44 -0.8 0
35 Clint Trickett West Virginia Big 12 281 419 67.1 3285 7.8 7.6 18 10 142.3 42 -106 -2.5 1
36 Justin Holman Central Florida American 200 339 59.0 2661 7.8 7.3 20 13 136.7 103 162 1.6 3
37 Kevin Hogan Stanford Pac-12 218 333 65.5 2603 7.8 7.8 17 8 143.2 84 245 2.9 5
38 Logan Woodside Toledo MAC 164 269 61.0 2087 7.8 8.0 19 7 144.2 47 88 1.9 3
39 Mike Bercovici Arizona State Pac-12 115 186 61.8 1445 7.8 8.1 12 4 144.1 26 16 0.6 0
40 Blake Frohnapfel Massachusetts MAC 241 436 55.3 3345 7.7 7.7 23 10 132.5 41 -85 -2.1 0
41 Nick Arbuckle Georgia State Sun Belt 259 429 60.4 3283 7.7 6.9 23 17 134.4 73 10 0.1 2
42 Joe Licata Buffalo MAC 223 344 64.8 2642 7.7 7.9 29 11 150.8 34 -6 -0.2 2
43 Hutson Mason Georgia SEC 178 263 67.7 2019 7.7 8.5 20 4 154.2 40 14 0.4 4
44 Lucas Falk Washington State Pac-12 156 243 64.2 1883 7.7 7.5 13 7 141.2 36 -70 -1.9 1
45 Taylor Kelly Arizona State Pac-12 141 244 57.8 1874 7.7 8.4 20 5 145.3 86 232 2.7 3
46 Taylor Heinicke Old Dominion CUSA 289 455 63.5 3476 7.6 7.6 30 14 143.3 80 139 1.7 2
47 Cody Sokol Louisiana Tech CUSA 246 420 58.6 3189 7.6 7.6 29 13 138.9 50 56 1.1 2
48 Christian Stewart Brigham Young Ind 176 300 58.7 2273 7.6 8.1 22 6 142.5 71 174 2.5 4
49 Will Gardner Louisville ACC 127 221 57.5 1669 7.6 8.0 12 3 136.1 22 -106 -4.8 0
50 Mitch Leidner Minnesota Big Ten 101 206 49.0 1540 7.5 6.7 10 8 120.1 117 461 3.9 10
51 Connor Halliday Washington State Pac-12 354 526 67.3 3873 7.4 7.6 32 11 145.0 29 -131 -4.5 0
52 Paxton Lynch Memphis American 235 367 64.0 2725 7.4 7.7 18 6 139.3 100 283 2.8 10
53 Colby Kirkegaard Wyoming MWC 205 358 57.3 2654 7.4 7.0 12 9 125.6 78 -110 -1.4 0
54 Davis Webb Texas Tech Big 12 211 345 61.2 2539 7.4 7.1 24 13 138.4 17 15 0.9 1
55 Daxx Garman Oklahoma State Big 12 152 277 54.9 2041 7.4 6.3 12 12 122.4 60 -16 -0.3 1
56 Wes Lunt Illinois Big Ten 149 233 63.9 1729 7.4 8.0 14 3 143.5 16 -80 -5.0 0
57 Marquise Williams North Carolina ACC 245 391 62.7 2870 7.3 7.3 20 9 136.6 178 737 4.1 12
58 Cyler Miles Washington Pac-12 194 291 66.7 2129 7.3 8.0 16 3 144.2 109 280 2.6 4
59 Greg Ward Houston American 161 236 68.2 1720 7.3 6.9 9 6 136.9 104 491 4.7 6
60 Andrew Hendrix Miami (OH) MAC 222 458 48.5 3280 7.2 7.3 23 9 121.3 157 384 2.4 6
61 Blake Decker Nevada-Las Vegas MWC 231 401 57.6 2881 7.2 5.9 15 18 121.3 147 366 2.5 5
62 Fredi Knighten Arkansas State Sun Belt 246 401 61.3 2874 7.2 7.3 19 7 133.7 194 786 4.1 11
63 Austin Grammer Middle Tennessee State CUSA 206 321 64.2 2307 7.2 6.5 16 12 133.5 124 442 3.6 6
64 Quinn Kaehler San Diego State MWC 158 280 56.4 2016 7.2 6.2 9 10 120.4 24 -116 -4.8 0
65 Tyler Murphy Boston College ACC 120 211 56.9 1526 7.2 6.1 11 10 125.3 170 1079 6.3 10
66 Tyler Jones Texas State Sun Belt 246 376 65.4 2670 7.1 7.4 22 7 140.7 167 539 3.2 6
67 Jake Rudock Iowa Big Ten 211 337 62.6 2404 7.1 7.4 16 5 135.2 65 154 2.4 3
68 Anu Solomon Arizona Pac-12 285 491 58.0 3458 7.0 7.5 27 7 132.5 114 259 2.3 1
69 Sean Mannion Oregon State Pac-12 282 453 62.3 3164 7.0 6.9 15 8 128.3 48 -306 -6.4 1
70 Joe Gray San Jose State MWC 210 330 63.6 2305 7.0 6.4 11 9 127.9 57 108 1.9 3
71 Jaquez Johnson Florida Atlantic CUSA 182 315 57.8 2215 7.0 7.4 17 5 131.5 120 513 4.3 7
72 Drew Hare Northern Illinois MAC 179 299 59.9 2097 7.0 7.8 17 2 136.2 145 850 5.9 8
73 Travis Wilson Utah Pac-12 173 287 60.3 2012 7.0 7.6 17 4 135.9 103 218 2.1 2
74 Mike Cummings Kansas Big 12 137 244 56.1 1715 7.0 6.7 9 6 122.4 67 23 0.3 4
75 Reggie Bell Eastern Michigan MAC 105 184 57.1 1297 7.0 6.6 9 6 125.9 133 562 4.2 4
76 Patrick Towles Kentucky SEC 225 393 57.3 2718 6.9 6.6 14 9 122.5 145 303 2.1 6
77 Anthony Jennings Louisiana State SEC 104 213 48.8 1460 6.9 6.3 10 7 115.3 100 284 2.8 0
78 Nick Mullens Southern Mississippi CUSA 218 365 59.7 2470 6.8 6.3 12 9 122.5 49 39 0.8 0
79 Jacoby Brissett North Carolina State ACC 206 344 59.9 2344 6.8 7.4 22 5 135.3 110 498 4.5 3
80 Brandon Silvers Troy Sun Belt 190 270 70.4 1823 6.8 7.1 11 3 138.3 100 196 2.0 5
81 Mike White South Florida American 122 242 50.4 1639 6.8 6.1 8 7 112.4 29 -85 -2.9 0
82 Chandler Whitmer Connecticut American 124 225 55.1 1522 6.8 6.1 11 8 121.0 76 77 1.0 2
83 Dane Evans Tulsa American 256 462 55.4 3102 6.7 6.1 23 17 120.9 77 58 0.8 3
84 Brandon Allen Arkansas SEC 178 316 56.3 2125 6.7 7.2 18 5 128.4 36 -13 -0.4 2
85 Devin Gardner Michigan Big Ten 172 281 61.2 1892 6.7 5.0 10 15 118.8 98 258 2.6 4
86 Matt Linehan Idaho Sun Belt 220 378 58.2 2500 6.6 5.1 11 18 113.8 82 -74 -0.9 1
87 Tyrone Swoopes Texas Big 12 211 359 58.8 2352 6.6 6.0 13 10 120.2 103 294 2.9 3
88 Terrance Broadway Louisiana-Lafayette Sun Belt 190 311 61.1 2068 6.6 6.1 12 9 123.9 133 646 4.9 3
89 Jameill Showers Texas-El Paso CUSA 146 262 55.7 1732 6.6 6.7 12 5 122.6 83 288 3.5 4
90 Maty Mauk Missouri SEC 209 395 52.9 2551 6.5 6.4 23 11 120.8 97 335 3.5 1
91 Ozzie Mann Ball State MAC 116 197 58.9 1281 6.5 7.1 10 2 128.2 31 -2 -0.1 0
92 Sefo Liufau Colorado Pac-12 325 498 65.3 3194 6.4 6.2 28 15 131.7 70 126 1.8 0
93 C.J. Brown Maryland Big Ten 174 327 53.2 2083 6.4 5.9 13 9 114.3 148 569 3.8 7
94 Andrew McNulty North Texas CUSA 110 202 54.5 1295 6.4 5.4 6 7 111.2 42 54 1.3 2
95 Pete Thomas Louisiana-Monroe Sun Belt 301 501 60.1 3181 6.3 6.4 14 6 120.2 110 6 0.1 3
96 James Knapke Bowling Green State MAC 255 444 57.4 2805 6.3 5.7 13 12 114.8 57 126 2.2 2
97 Tyler Rogers New Mexico State Sun Belt 268 435 61.6 2739 6.3 4.9 19 22 118.8 69 200 2.9 2
98 Brian Burrell Fresno State MWC 242 412 58.7 2576 6.3 5.6 22 16 121.1 101 328 3.2 3
99 Cody Fajardo Nevada MWC 225 376 59.8 2374 6.3 6.0 18 11 122.8 164 997 6.1 13
100 Greyson Lambert Virginia ACC 154 261 59.0 1632 6.3 5.1 10 11 115.7 35 -6 -0.2 2
101 Justin Worley Tennessee SEC 157 252 62.3 1579 6.3 5.8 12 8 124.3 45 -105 -2.3 3
102 Michael Brewer Virginia Tech ACC 248 417 59.5 2598 6.2 5.5 17 14 118.5 75 -22 -0.3 2
103 Jack Milas Ball State MAC 115 209 55.0 1302 6.2 6.0 9 5 116.8 27 96 3.6 2
104 Ikaika Woolsey Hawaii MWC 208 414 50.2 2534 6.1 5.3 13 13 105.7 109 213 2.0 1
105 Colin Reardon Kent State MAC 228 401 56.9 2466 6.1 5.1 14 16 112.1 59 148 2.5 2
106 P.J. Walker Temple American 205 379 54.1 2317 6.1 5.0 13 15 108.8 106 324 3.1 3
107 Alex McGough Florida International CUSA 138 274 50.4 1680 6.1 5.5 14 10 111.4 97 92 0.9 4
108 Brandon Bridge South Alabama Sun Belt 140 270 51.9 1648 6.1 6.1 14 6 115.8 85 256 3.0 3
109 J.D. Sprague Ohio MAC 98 202 48.5 1236 6.1 5.3 3 5 99.9 65 264 4.1 3
110 Christian Hackenberg Penn State Big Ten 236 434 54.4 2606 6.0 4.8 8 15 104.0 85 -94 -1.1 0
111 Sam Richardson Iowa State Big 12 254 452 56.2 2669 5.9 5.8 18 9 115.0 125 421 3.4 3
112 Anthony Boone Duke ACC 240 422 56.9 2507 5.9 6.0 17 7 116.8 88 346 3.9 5
113 Cole Stoudt Clemson ACC 165 266 62.0 1573 5.9 4.7 6 10 111.6 61 101 1.7 0
114 Tanner Lee Tulane American 185 336 55.1 1962 5.8 4.7 12 14 107.6 35 -128 -3.7 0
115 Trevor Siemian Northwestern Big Ten 228 391 58.3 2214 5.7 4.8 7 11 106.2 68 -123 -1.8 5
116 Kyle Pohl Akron MAC 207 382 54.2 2185 5.7 5.2 9 8 105.8 46 18 0.4 1
117 John Wolford Wake Forest ACC 205 353 58.1 1965 5.6 4.5 11 13 107.8 104 -151 -1.5 0
118 Jeff Driskel Florida SEC 106 195 54.4 1092 5.6 4.2 9 10 106.4 66 173 2.6 4
119 John O'Korn Houston American 90 174 51.7 951 5.5 4.1 6 8 99.8 32 17 0.5 1
120 Austin Appleby Purdue Big Ten 144 272 52.9 1449 5.3 4.2 10 11 101.7 61 198 3.2 5
121 Garrett Krstich Southern Methodist American 99 181 54.7 855 4.7 3.2 2 7 90.3 40 81 2.0 0
function Scatterplot(g, // <g></g>
d, // object { x, y }
w, // width
h, // height
p, // padding
t, // ticks
r) // radius
{
w = w || 640;
h = h || 480;
p = p || 50;
t = t || 5;
r = r || 4;
// public
this.draw = function()
{
// create the marks
if (marks == null)
{
// create circles
marks = group.selectAll('circle')
.data(dataset)
.enter()
.append('circle')
.attr('cx', function(d) {
return xScale(d.x);
})
.attr('cy', function(d) {
return yScale(d.y);
})
.attr('r', function(d) {
return d.radius || radius;
})
.style('fill', function(d) { return d.color; });
// create x axis
group.append('g')
.attr('class', 'axis x-axis')
.attr('transform', 'translate(0,' + (height - padding) + ')')
.call(xAxis);
// create y axis
group.append('g')
.attr('class', 'axis y-axis')
.attr('transform', 'translate(' + padding + ',0)')
.call(yAxis);
}
else
{
// update the marks
marks.style('fill', function(d) { return d.color; })
.attr('r', function(d) {
return d.radius || radius;
});
marks.sort(function(a, b) {
if (a.layer != null && b.layer != null)
{
return a.layer - b.layer;
}
return 0;
});
}
};
// read: returns text after reading the data
this.makeHoverLabels = function(read)
{
if (hoverLabels == null)
{
hoverLabels = group.selectAll('.hover-label')
.data(dataset)
.enter()
.append('text')
.attr('class', 'hover-label')
.attr('transform', function(d) {
return 'translate(' + (xScale(d.x) - 55) + ',' +
(yScale(d.y) - 13) + ')';
});
marks.on('mouseover', function(d, i) {
hoverLabels.each(function(d, j) {
if (i == j)
{
d3.select(this)
.text(function(d, i) {
return read(d, i);
});
}
})
})
.on('mouseout', function(d, i) {
hoverLabels.each(function(d, j) {
if (i == j)
{
d3.select(this).text('');
}
})
});
}
};
this.drawAxisLabels = function(vertical, horizontal)
{
if (group != null)
{
group.select('.x-axis')
.append('text')
.attr('x', width * 0.80 / 2 )
.attr('y', -5)
.text(horizontal);
group.select('.y-axis')
.append('text')
.attr('transform', 'rotate(-90)')
.attr('x', -height * 1.10 / 2)
.attr('y', 10)
.text(vertical);
}
};
// Invokes callback on each mark.
this.each = function(callback)
{
if (marks != null)
{
marks.each(callback);
}
};
// private
var group = g;
var dataset = d;
var width = w;
var height = h;
var padding = p;
var radius = r;
var ticks = t;
var xScale = d3.scale.linear()
.domain([ d3.min(dataset, function(d) { return d.x }) - 50,
d3.max(dataset, function(d) { return d.x }) + 50])
.range([ padding, width - padding * 2]);
var yScale = d3.scale.linear()
.domain([ d3.min(dataset, function(d) { return d.y }) - 50,
d3.max(dataset, function(d) { return d.y }) + 50])
.range([ height - padding, padding ]);
var xAxis = d3.svg.axis()
.scale(xScale)
.orient('bottom')
.ticks(ticks);
var yAxis = d3.svg.axis()
.scale(yScale)
.orient('left')
.ticks(ticks);
var marks = null;
var hoverLabels = null;
}
// expand frame element
d3.select(self.frameElement).style('height', '1050px');
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