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Networks - Intro 1

Intro Example 1 for How to Create Effective Network Data Visualization

The dataset being used for this workshop is a table of links between consultants in a firm from Tore Opsahl's excellent set of example networks.

The list consists of connections from one consultant to another with a rating of the second consultant by the first (on a scale of 1 to 5).

This first visualization of the data is one way to look at it. We see bar charts in small multiples. Each chart shows how each consultant was rated (1 on the left, 5 on the right). It provides an interesting and actionable view into the data (there are some dramatically different distributions in the ratings of some consultants) and you can imagine how this kind of chart and the analysis it visualizes could be used to determine bonuses and performance reviews.

source target weight
1 3 5
1 8 3
1 9 3
1 12 3
1 15 2
1 23 3
1 26 2
1 37 2
1 46 2
2 1 1
2 4 2
2 5 1
2 6 3
2 7 5
2 8 4
2 10 1
2 11 5
2 12 1
2 13 4
2 14 4
2 16 2
2 18 3
2 19 2
2 20 5
2 21 1
2 22 3
2 25 3
2 26 1
2 27 4
2 28 4
2 29 5
2 31 2
2 33 2
2 34 3
2 35 5
2 37 1
2 38 4
2 41 3
3 1 4
3 4 1
3 8 1
3 9 4
3 12 4
3 22 1
3 31 1
3 32 4
3 33 2
3 37 1
3 46 4
4 8 3
4 11 2
4 20 2
4 32 3
4 33 3
4 40 5
5 2 1
5 6 5
5 7 1
5 13 1
5 14 2
5 17 1
5 18 1
5 19 5
5 20 3
5 21 2
5 23 3
5 25 3
5 26 5
5 27 2
5 28 1
5 29 3
5 34 1
5 36 3
5 38 1
5 39 4
5 44 3
5 45 5
6 2 1
6 5 3
6 7 1
6 11 1
6 13 1
6 14 1
6 17 3
6 19 4
6 20 2
6 21 3
6 23 3
6 25 5
6 26 5
6 27 1
6 28 5
6 29 1
6 35 1
6 36 5
6 38 1
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6 45 4
7 2 5
7 8 3
7 11 3
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8 33 5
8 34 3
8 37 2
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8 41 3
8 42 1
8 43 1
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9 1 3
9 3 2
9 4 1
9 8 1
9 12 1
9 15 1
9 17 5
9 18 1
9 26 1
9 31 1
9 32 2
9 33 1
9 37 1
9 40 1
9 46 1
10 1 3
10 2 1
10 4 1
10 8 4
10 9 5
10 11 1
10 12 1
10 14 1
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10 33 1
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10 37 2
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10 42 1
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10 44 1
10 45 1
11 2 5
11 20 4
11 38 3
11 45 4
12 1 3
12 2 1
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12 9 2
12 10 1
12 11 1
12 13 1
12 14 1
12 15 1
12 16 1
12 17 1
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12 20 1
12 21 1
12 22 5
12 23 1
12 24 1
12 25 1
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12 27 1
12 28 1
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12 32 2
12 33 5
12 34 1
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12 37 2
12 38 1
12 39 1
12 40 1
12 41 2
12 42 1
12 43 1
12 44 1
12 45 1
12 46 5
13 2 3
13 5 1
13 6 1
13 7 2
13 11 1
13 17 1
13 18 2
13 19 2
13 20 2
13 21 1
13 23 1
13 25 1
13 26 1
13 27 2
13 28 1
13 29 3
13 34 1
13 35 1
13 38 1
13 44 1
13 45 1
14 2 4
14 5 1
14 6 1
14 7 2
14 8 1
14 11 1
14 19 1
14 20 3
14 22 1
14 23 1
14 27 1
14 28 1
14 31 1
14 33 1
14 35 1
14 38 2
14 41 1
14 45 1
16 1 1
16 2 1
16 3 1
16 4 1
16 5 1
16 6 1
16 7 1
16 8 1
16 9 1
16 10 1
16 11 1
16 12 1
16 13 1
16 14 1
16 15 1
16 17 1
16 18 1
16 19 1
16 20 1
16 21 1
16 22 1
16 23 1
16 24 1
16 25 1
16 26 1
16 27 1
16 28 1
16 29 1
16 30 1
16 31 1
16 32 1
16 33 1
16 34 1
16 35 1
16 36 1
16 37 1
16 38 1
16 39 1
16 40 1
16 41 1
16 42 1
16 43 1
16 44 1
16 45 1
16 46 1
17 5 1
17 6 2
17 10 5
17 13 1
17 19 3
17 20 1
17 21 1
17 23 4
17 25 2
17 26 3
17 28 3
17 29 3
17 36 2
17 38 1
17 39 2
17 44 3
17 45 3
18 1 1
18 2 4
18 5 2
18 7 2
18 8 2
18 9 1
18 10 1
18 11 2
18 13 5
18 15 1
18 16 1
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18 22 2
18 25 4
18 26 2
18 27 3
18 28 2
18 29 2
18 31 3
18 33 3
18 34 3
18 35 1
18 37 2
18 38 2
18 40 2
19 2 3
19 5 5
19 6 5
19 7 3
19 11 2
19 13 3
19 14 2
19 17 3
19 20 2
19 21 2
19 25 3
19 26 5
19 27 2
19 28 3
19 29 2
19 36 5
19 38 3
19 39 5
19 44 5
19 45 5
20 1 2
20 2 3
20 4 2
20 5 2
20 6 2
20 7 3
20 8 4
20 9 1
20 10 2
20 11 4
20 12 2
20 13 5
20 14 4
20 17 1
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20 19 3
20 21 1
20 22 2
20 23 3
20 25 3
20 26 2
20 27 4
20 28 4
20 29 4
20 31 3
20 34 3
20 35 2
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20 38 4
20 41 2
20 43 2
20 44 3
20 45 5
21 2 2
21 6 3
21 17 4
21 19 2
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21 23 2
21 25 2
21 26 3
21 27 2
21 28 3
21 29 4
21 36 2
21 39 2
21 44 4
21 45 4
22 1 1
22 2 2
22 3 1
22 4 2
22 5 1
22 6 1
22 7 1
22 8 3
22 9 1
22 10 1
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22 15 5
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22 18 2
22 19 1
22 20 1
22 21 1
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22 24 1
22 25 1
22 26 1
22 27 1
22 28 1
22 29 1
22 30 1
22 31 2
22 32 2
22 33 5
22 34 2
22 35 1
22 36 1
22 37 1
22 38 4
22 39 1
22 40 5
22 41 1
22 42 1
22 43 1
22 44 1
22 45 2
22 46 2
23 1 2
23 2 1
23 5 3
23 6 3
23 7 1
23 10 3
23 11 2
23 13 1
23 14 1
23 17 4
23 19 3
23 20 3
23 21 1
23 25 2
23 26 4
23 27 1
23 28 3
23 29 4
23 31 1
23 34 1
23 35 1
23 36 5
23 38 2
23 39 4
23 44 4
23 45 2
25 2 2
25 5 2
25 6 5
25 7 1
25 11 1
25 13 1
25 17 1
25 18 2
25 19 4
25 20 3
25 23 3
25 26 4
25 27 2
25 28 3
25 29 1
25 35 1
25 36 3
25 39 3
25 44 2
25 45 3
26 1 1
26 2 1
26 5 5
26 6 5
26 7 1
26 9 1
26 11 2
26 13 1
26 17 4
26 18 1
26 19 5
26 20 2
26 21 2
26 23 5
26 25 5
26 27 2
26 28 4
26 29 2
26 31 1
26 34 1
26 35 1
26 36 5
26 38 2
26 39 5
26 44 5
26 45 5
27 2 4
27 5 2
27 6 2
27 7 2
27 11 1
27 13 5
27 14 3
27 17 1
27 18 3
27 19 2
27 20 4
27 21 1
27 23 1
27 25 3
27 26 2
27 28 2
27 29 4
27 34 1
27 35 5
27 36 1
27 38 1
27 39 1
27 44 1
27 45 3
28 2 3
28 5 2
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28 7 2
28 10 2
28 11 2
28 13 2
28 17 4
28 18 3
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28 20 3
28 21 2
28 23 4
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28 27 2
28 29 3
28 36 3
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29 18 1
29 19 1
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29 21 2
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29 34 1
29 35 1
29 36 1
29 38 1
29 44 2
29 45 1
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31 1 2
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31 16 2
31 18 3
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31 22 2
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31 37 1
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32 1 2
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32 40 5
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32 46 1
33 1 2
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33 40 5
33 43 2
34 1 1
34 2 2
34 5 1
34 6 1
34 7 1
34 8 2
34 13 1
34 16 1
34 18 1
34 19 1
34 20 1
34 22 1
34 23 1
34 25 1
34 26 1
34 27 1
34 28 1
34 29 1
34 31 3
34 32 1
34 33 4
34 35 1
34 37 2
34 38 2
34 40 1
34 42 5
34 43 1
35 2 3
35 13 2
35 18 2
35 27 4
35 29 2
35 39 2
36 2 1
36 5 3
36 6 5
36 17 3
36 18 1
36 19 4
36 20 1
36 21 1
36 23 5
36 25 4
36 26 5
36 28 4
36 29 2
36 39 4
36 44 5
36 45 5
37 1 2
37 2 1
37 8 2
37 9 1
37 10 2
37 12 2
37 18 1
37 31 2
37 32 1
37 33 1
37 34 2
37 40 1
37 43 1
38 2 5
38 4 2
38 6 2
38 7 4
38 8 2
38 11 3
38 13 2
38 14 4
38 18 1
38 19 2
38 20 3
38 22 5
38 23 3
38 26 2
38 28 1
38 29 3
38 31 3
38 33 3
38 34 2
38 35 5
38 41 4
38 44 1
38 45 2
39 5 3
39 6 5
39 13 1
39 17 1
39 19 5
39 23 4
39 25 2
39 26 4
39 28 2
39 36 3
39 44 4
39 45 5
40 1 1
40 2 1
40 4 5
40 8 3
40 9 1
40 12 1
40 15 3
40 16 2
40 18 1
40 20 1
40 22 3
40 31 2
40 32 5
40 33 5
40 34 2
40 37 2
40 43 1
41 1 2
41 2 2
41 8 3
41 10 5
41 12 2
41 14 2
41 20 2
41 38 3
41 43 2
42 8 1
42 10 1
42 28 1
42 31 1
42 33 1
42 34 4
42 37 1
42 41 1
42 43 1
42 45 1
43 8 2
43 12 2
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44 1 1
44 2 1
44 5 3
44 6 5
44 7 1
44 8 1
44 11 1
44 13 1
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44 20 2
44 21 2
44 23 3
44 25 2
44 26 4
44 28 2
44 33 1
44 34 1
44 35 1
44 36 4
44 38 1
44 39 4
44 42 1
44 43 1
44 45 3
45 1 1
45 2 2
45 4 1
45 5 5
45 6 5
45 7 2
45 8 1
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45 10 1
45 11 3
45 12 2
45 13 1
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45 17 4
45 18 2
45 19 4
45 20 4
45 21 3
45 22 1
45 23 3
45 25 4
45 26 5
45 27 2
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45 29 3
45 31 3
45 33 1
45 34 1
45 35 1
45 36 5
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46 1 3
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46 8 1
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46 12 5
46 22 1
46 32 2
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46 37 1
46 43 1
<html>
<head>
<title>Showing a census of connections per person</title>
<meta charset="utf-8" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js"></script>
</head>
<style>
svg {
height: 500px;
width: 500px;
border: 1px solid gray;
}
</style>
<body>
<div id="viz">
<svg>
</svg>
</div>
</body>
<footer>
<script>
d3.csv("firm.csv",function(error,data) {dataViz(data)});
function dataViz(incData) {
var nestedData = d3.nest()
.key(function (d) {return d.target})
.key(function (d) {return d.weight})
.entries(incData);
nestedData.forEach(function (d, i) {
var x = Math.floor(i % 8);
var y = Math.floor(i / 8);
d.x = x;
d.y = y;
});
var smallBarcharts = d3.select("svg").selectAll("g.smallmultiples")
.data(nestedData)
.enter()
.append("g")
.attr("class", "smallmultiples")
.attr("transform", function (d) {return "translate(" + (d.x * 60) + "," + (d.y * 60) + ")"});
smallBarcharts.selectAll("rect")
.data(function (d) {return d.values})
.enter()
.append("rect")
.attr("height", function (d) {return Math.min(49, d.values.length * 2)})
.attr("y", function (d) {return 50 - Math.min(49, d.values.length * 2)})
.attr("width", 10)
.attr("x", function (d) {return d.key * 10})
.style("fill", "#996666")
.style("stroke", "#CC9999")
.style("stroke-width", "1px");
smallBarcharts.insert("rect", "rect")
.style("fill", "white")
.style("stroke", "black")
.style("stroke-width", "1px")
.attr("width", 54)
.attr("height", 51)
.attr("x", 8)
.attr("y", 0)
smallBarcharts.append("text")
.attr("x", 35)
.attr("y", 15)
.style("text-anchor", "middle")
.text(function (d) {return d.key});
}
</script>
</footer>
</html>
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