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Last active September 7, 2016 19:59
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Interview event / score scatterplot
Raw
.block
license: gpl-3.0
Raw
index.html
<!DOCTYPE html>
<meta charset="utf-8">
<style type="text/css">
body {
margin: 0;
font-family: arial, sans;
}
.label {
font-size: 15px;
}
.legend text,
.axis text {
font-size: 13px;
fill: #333;
}
.axis path,
.axis line {
fill: none;
stroke-width:1px;
stroke: #777;
}
circle {
fill-opacity: 0.65;
}
.bubble {
opacity: 1;
transition: opacity 0.3s;
}
.bubble text {
opacity: 0;
pointer-events: none;
font-size: 12px;
}
.bubble:hover text {
opacity: 1;
}
.bubble:hover circle {
fill-opacity: 1;
}
.legend rect {
fill-opacity: 0.75;
}
.legend:hover rect {
fill-opacity: 1;
}
</style>
<body>
<button onclick="toggle()">toggle</button>
</body>
<script src="//d3js.org/d3.v4.0.0-alpha.35.min.js"></script>
<script>
var margin = { top: 30, right: 50, bottom: 40, left: 40 };
var width = 960 - margin.left - margin.right;
var height = 500 - margin.top - margin.bottom;
var svg = d3.select("body")
.append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
var xscale = d3.scaleLog()
.range([0,width]);
var yscale = d3.scaleLinear()
.domain([0, 4])
.range([height,0]);
var radius = d3.scaleSqrt()
.range([1, 5]);
var xAxis = d3.axisBottom()
.scale(xscale)
.tickValues([1,10,100,1000,10000])
.tickFormat(d3.format(","));
var yAxis = d3.axisLeft()
.scale(yscale)
var color = d3.scaleLinear()
.range(["#1b9e77","#d95f02","#7570b3","#e7298a","#66a61e","#e6ab02","#a6761d"])
.domain([0, 1, 2, 3, 4]);
rawData = null;
d3.csv("phl_hec_all_confirmed.csv", function(error, gottenData) {
rawData = gottenData;
var data = rawData.map(function(d) {
return {
y: +d["Average"],
x: +d["interview events"],
r: +d["Rounded Average"]
}
});
xscale.domain(d3.extent(data, function(d) {
return d.x;
})).nice()
radius.domain(d3.extent(data, function(d) {
return d.r;
})).nice()
svg.append("g")
.attr("transform", "translate(0," + height + ")")
.attr("class", "x axis")
.call(xAxis);
svg.append("g")
.attr("transform", "translate(0,0)")
.attr("class", "y axis")
.call(yAxis);
var group = svg.selectAll("g.bubble")
.data(data)
.enter().append("g")
.attr("class", "bubble")
.attr("transform", function(d) {
return "translate(" + xscale(d.x) + "," + yscale(d.y) + ")"
});
group
.append("circle")
.attr("r", function(d) { return radius(d.r); })
.style("fill", function(d) {
return color(d.r);
})
group
.append("text")
.attr("x", function(d) { return radius(d.r); })
.attr("alignment-baseline", "middle")
.text(function(d) {
return d["ID"] + ' score ' + d.y;
});
svg.append("text")
.attr("x", 10)
.attr("y", 10)
.attr("class", "label")
.text("Average score");
svg.append("text")
.attr("x", width)
.attr("y", height-10)
.attr("text-anchor", "end")
.attr("class", "label")
.text("Interview events (count)");
var legend = svg.selectAll(".legend")
.data(color.domain())
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
legend.append("rect")
.attr("x", width)
.attr("width", 18)
.attr("height", 18)
.style("fill", color);
legend.append("text")
.attr("x", width - 6)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) { return d; });
legend.on("mouseover", function(type) {
d3.selectAll(".bubble")
.style("opacity", 0.1)
.filter(function(d) { return d.r === type; })
.style("opacity", 1);
})
.on("mouseout", function(type) {
d3.selectAll(".bubble")
.style("opacity", 1);
});
});
toggle = function(){
var data = rawData.map(function(d) {
return {
y: +d["% +"],
x: +d["interview events"],
r: (Math.round(+d["% +"] * 4) / 4),
}
});
xscale.domain(d3.extent(data, function(d) {
return d.x;
})).nice()
yscale.domain(d3.extent(data, function(d) {
return d.y;
})).nice()
yAxis
.tickFormat(function(d){return Math.round(d * 100) + '%';})
.scale(yscale)
d3.select('.y.axis').call(yAxis)
color.domain([0, 0.25, 0.5, 1]);
var group = svg.selectAll("g.bubble")
.data(data)
.transition().duration(1000)
.attr("transform", function(d) {
return "translate(" + xscale(d.x) + "," + yscale(d.y) + ")"
})
group.selectAll('circle').transition().style("fill", function(d) {
return color(d.r/4);
})
var legend = d3.selectAll(".legend")
.data(color.domain())
legend.transition()
.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
legend.selectAll('rect')
.transition()
.style("fill", color);
legend.selectAll("text").remove()
legend.append("text")
.attr("x", width - 6)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) { return d; });
legend.on("mouseover", function(type) {
d3.selectAll(".bubble")
.style("opacity", 0.1)
.filter(function(d) { return d.r === type; })
.style("opacity", 1);
})
.on("mouseout", function(type) {
d3.selectAll(".bubble")
.style("opacity", 1);
});
legend.exit().remove()
}
</script>
Raw
phl_hec_all_confirmed.csv
ID 1 2 3 4 % + % - Average interview events Rounded Average
43beb078-44eb-42f9-ab62-e93dfdc684d9 12 135 388 60 0.75 0.25 2.83 2248 3.00
e5c1deea-224e-4345-a142-040468ebfe4b 11 105 173 25 0.63 0.37 2.68 1272 3.00
ba2217e6-09d0-4282-a6e7-88f69094becc 7 55 147 40 0.75 0.25 2.88 1200 3.00
b618e419-594b-4831-8b56-fe44f188b916 1 7 4 3 0.47 0.53 2.60 1066 3.00
09753a9d-5eee-46ca-a198-e05378b6a208 12 25 45 9 0.59 0.41 2.56 1062 3.00
f83c0363-4838-45ad-b527-bec8e0374fb7 4 39 43 43 0.67 0.33 2.97 1032 3.00
e0ed2d3b-082a-4b6e-a6bb-15630b62b458 6 57 83 10 0.60 0.40 2.62 940 3.00
574e930f-c545-45eb-a932-0764403c7e0a 2 3 6 0 0.55 0.45 2.36 796 2.00
da947c4d-70a0-49bc-b653-f15784b91211 0 7 10 6 0.70 0.30 2.96 773 3.00
ed789c99-8463-470e-8f8f-63615f9d2b08 5 19 22 22 0.65 0.35 2.90 773 3.00
65a5c717-26f3-42e7-8978-ae7ef7d39283 23 157 222 85 0.63 0.37 2.76 644 3.00
657a92c0-2257-4d8d-9999-14c664d5586a 1 2 4 1 0.63 0.38 2.63 576 3.00
1b40f78e-5eef-402a-a13a-d002d7530e5d 6 41 51 14 0.58 0.42 2.65 558 3.00
e8695397-92b7-4e86-85e2-e6da915cd202 4 30 87 6 0.73 0.27 2.75 517 3.00
7552f5eb-0d71-4d9a-b3d5-51025f0d0355 0 9 184 57 0.96 0.04 3.19 473 3.00
bd571b2b-1ef0-4142-996b-ab9447067919 15 149 169 29 0.55 0.45 2.59 468 3.00
b8562e6d-dca6-4a2c-ade7-e37dbcc0cc1a 0 4 12 6 0.82 0.18 3.09 466 3.00
59d5542c-52c2-44b4-bb52-b1c1a4404640 0 7 26 0 0.79 0.21 2.79 454 3.00
dc60e36c-6b7e-4b6c-8a38-fa65d8d3b00c 6 102 127 40 0.61 0.39 2.73 437 3.00
9f8cb571-c2e6-40c6-8491-a8e49c5ba9ce 2 10 38 8 0.79 0.21 2.90 408 3.00
5dbd9d24-e18b-4ee0-9e04-70198407ec3f 0 1 85 1 0.99 0.01 3.00 388 3.00
3573223c-6c51-427d-9a49-272ab0484353 0 0 2 0 1.00 0.00 3.00 361 3.00
ef7ec1c1-a416-4fa5-84ac-6a0529334b26 9 92 139 68 0.67 0.33 2.86 352 3.00
f3b7d1a6-c931-4eb7-a725-4a22f19d23ac 16 77 121 84 0.69 0.31 2.92 344 3.00
b4cfdbda-78e7-42cc-8bf0-fbc70b56394b 34 141 221 66 0.62 0.38 2.69 341 3.00
65df42e8-a63d-4cca-b6b1-7118b5e34ebf 0 3 30 8 0.93 0.07 3.12 335 3.00
2525b9a0-3d7c-4e3a-af7a-a9a1d4226ecb 0 2 8 6 0.88 0.13 3.25 309 3.00
a51fcecd-eee4-4842-b995-32b835fdad72 1 50 72 20 0.64 0.36 2.78 293 3.00
bd66779c-ea05-4626-a79c-aa6e7d5f20c8 2 29 77 7 0.73 0.27 2.77 283 3.00
e79b0e2e-7054-4c23-8aa8-3f307ae829ee 0 4 18 1 0.83 0.17 2.87 283 3.00
ff209f68-3d67-441c-b5b3-780d302ce660 19 111 163 87 0.66 0.34 2.84 276 3.00
698edb2c-54a5-4aeb-8a93-77327e6a47ef 10 54 126 26 0.70 0.30 2.78 270 3.00
1755036a-f6fa-4fb1-adc4-6bcf39d2b874 7 64 132 69 0.74 0.26 2.97 269 3.00
10777676-d6fa-44e6-9aa7-9cf6752dcda9 11 62 57 11 0.48 0.52 2.48 267 2.00
49bf3f3f-8a55-410d-97c1-f9d878d427e1 0 0 40 0 1.00 0.00 3.00 265 3.00
1c928c70-1d06-47c9-9b8a-3361007dfd35 15 82 67 30 0.50 0.50 2.58 263 3.00
b894397c-f6a3-4cc3-bacb-9df9f40296e6 11 48 30 29 0.50 0.50 2.65 262 3.00
b0e78090-8840-406d-aeb8-b45ac16375d7 11 42 38 26 0.55 0.45 2.68 258 3.00
06434313-ae3b-4ac5-b0f2-86e6bebab43b 10 55 92 59 0.70 0.30 2.93 255 3.00
ef4ccaa2-2c94-4f7e-b89f-89b95d023383 21 83 140 39 0.63 0.37 2.70 254 3.00
1711648d-0c61-4770-94b9-5580422e28bb 4 35 132 19 0.79 0.21 2.87 251 3.00
f7a99ef8-6639-4d44-9850-8c3d8d30c252 1 23 35 13 0.67 0.33 2.83 247 3.00
e3ae052f-8ae1-4469-b508-ee5ec7147a94 29 119 90 54 0.49 0.51 2.58 241 3.00
93df8ca3-1156-4e51-baaf-df1895323b76 16 75 110 22 0.59 0.41 2.62 239 3.00
e939a6a2-ceb7-4db1-ade7-5b03b666003f 16 97 70 10 0.41 0.59 2.38 238 2.00
f249b86e-39bc-41ba-a51e-2d3d57557309 14 83 81 28 0.53 0.47 2.60 238 3.00
3120a447-6be4-48b8-a971-2318f3a52cf8 1 65 73 1 0.53 0.47 2.53 234 3.00
2656452a-7d9f-4942-a880-d46f44d7e474 0 5 4 0 0.44 0.56 2.44 228 2.00
4f5c7fff-04ea-4b9a-919f-562fec6694c0 22 125 126 29 0.51 0.49 2.54 225 3.00
4495f77b-d861-41f5-be3e-05edce6f92c4 0 24 45 15 0.71 0.29 2.89 219 3.00
0dacefe6-2e45-4475-9e3f-dadd8394e798 13 87 149 28 0.64 0.36 2.69 215 3.00
9f42199e-3e7d-42f4-a395-ed7845d580bb 1 50 101 14 0.69 0.31 2.77 214 3.00
378820fd-3503-4139-a030-23765ab389a0 6 89 125 19 0.60 0.40 2.66 212 3.00
b8d2243c-b8cc-4d05-8f75-7fb2109c0254 0 20 145 29 0.90 0.10 3.05 210 3.00
ebbc8d91-fb98-47cf-b79c-265b3d10c5e9 9 62 108 12 0.63 0.37 2.64 207 3.00
fbc9c8de-52f7-4fc8-8b93-1405f462fbdc 1 32 76 10 0.72 0.28 2.80 194 3.00
f31a9f57-0298-4baa-8c1b-e60f75a6bb13 1 72 81 8 0.55 0.45 2.59 192 3.00
834915f9-7853-4407-8d6d-f85eb9b917c0 3 34 27 1 0.43 0.57 2.40 189 2.00
3984b8f2-29a5-4383-a047-ca0f4860ab77 25 102 88 36 0.49 0.51 2.54 188 3.00
09c2370f-5d35-4501-8a12-b0be32e3d554 1 1 1 0 0.33 0.67 2.00 185 2.00
2fd0b60f-607b-4882-ae3b-2e1c51998542 1 49 84 14 0.66 0.34 2.75 184 3.00
c65fe287-a9e1-455a-a7d1-1dc7ab1b4d22 5 76 121 36 0.66 0.34 2.79 181 3.00
04709b58-a87e-4327-aea7-9e1ea3c6de19 6 39 75 12 0.66 0.34 2.70 177 3.00
cf0238e0-5681-4677-bde8-84ea26310666 2 53 89 28 0.68 0.32 2.83 176 3.00
fe317ca0-7964-4a4a-9cc9-cf1338257ea7 9 29 40 22 0.62 0.38 2.75 174 3.00
3a571acf-3776-43d7-98bb-a2134b005de6 0 0 2 1 1.00 0.00 3.33 172 3.00
6cdb288a-5572-4304-8396-4c5649e0401a 4 60 65 8 0.53 0.47 2.56 170 3.00
b0e5a006-1ada-4210-a37d-f79b19a36952 12 54 124 20 0.69 0.31 2.72 170 3.00
9f112a90-4755-4d51-92af-6616e6248083 1 37 87 18 0.73 0.27 2.85 169 3.00
63d95f2a-2a81-407d-bba3-1832e4ee0a5c 2 38 54 9 0.61 0.39 2.68 168 3.00
431d5e8a-818a-4765-ac3c-e05d71853a7e 13 57 133 19 0.68 0.32 2.71 161 3.00
9e26d60b-751f-49f6-a7c9-587c1bd67bcf 0 30 69 42 0.79 0.21 3.09 161 3.00
c9d00783-79fb-40d6-ba0e-cbe217309245 13 78 76 7 0.48 0.52 2.44 161 2.00
c7ad2be2-4d8c-48fb-8d45-203340447bac 1 18 23 14 0.66 0.34 2.89 160 3.00
dbf02835-1ed5-44bd-b12a-9d16b6ac0cf9 15 61 90 44 0.64 0.36 2.78 160 3.00
78343cff-2ffa-436e-be11-cb230ba82216 8 49 67 21 0.61 0.39 2.70 159 3.00
49c378df-2ba8-4ff7-905e-4ee9592685e8 2 41 79 10 0.67 0.33 2.73 158 3.00
d41ab64f-a88a-45f8-94d5-82d2a757ce31 1 67 45 20 0.49 0.51 2.63 158 3.00
52ba78ca-f2b7-401d-bb7c-6d6522bef460 11 41 72 32 0.67 0.33 2.80 157 3.00
0378e40a-7f98-44d0-bb57-941255572eaf 8 60 79 11 0.57 0.43 2.59 156 3.00
16358854-508a-482e-966b-12a98419ad3d 5 39 43 49 0.68 0.32 3.00 155 3.00
44536c58-2f7f-4def-b60d-1b3725abce6d 1 27 16 12 0.50 0.50 2.70 151 3.00
0e76f072-1e88-424a-9a83-d971a4b8211e 16 61 70 15 0.52 0.48 2.52 147 3.00
eace2f36-59aa-4945-99f4-8f4123d711c5 1 26 58 5 0.70 0.30 2.74 147 3.00
415b40e8-a6d2-4677-9670-b19c11639860 0 37 68 3 0.66 0.34 2.69 144 3.00
8195e9fc-cc05-47c9-ae39-c470a631f028 15 80 65 13 0.45 0.55 2.44 142 2.00
0024b1e1-f351-4d19-8340-21f3fb933cd2 20 70 109 32 0.61 0.39 2.66 139 3.00
6297f93f-d92f-4bb9-b8ae-206545844d29 10 58 43 4 0.41 0.59 2.36 139 2.00
629cb616-f1e0-4014-8232-f2f217c36974 2 20 47 20 0.75 0.25 2.96 139 3.00
4edc56d6-577c-46e7-9e40-7ecf57ea7d02 0 15 59 14 0.83 0.17 2.99 138 3.00
ddea79c2-21c3-43b1-8b3e-b664534faf1e 1 7 5 2 0.47 0.53 2.53 138 3.00
e3b6b38e-2d2e-4650-89dc-5e82d7ca2076 1 26 53 18 0.72 0.28 2.90 138 3.00
878c734f-2778-4ab3-ad00-e2a4d248c847 3 10 11 9 0.61 0.39 2.79 137 3.00
c6672bfd-8d6e-42da-9d7d-c90bc12848b0 0 1 5 1 0.86 0.14 3.00 137 3.00
233cda6b-37cd-427f-9c74-380a4cf7146b 3 19 28 9 0.63 0.37 2.73 135 3.00
5d547fd9-6af4-4e04-b742-0f07db577c35 7 37 52 24 0.63 0.37 2.78 134 3.00
f5ecee33-4206-4e4f-841e-215ebde080bf 2 34 67 7 0.67 0.33 2.72 134 3.00
860cfbdb-dfed-4d7f-8c44-8052c72a5ed6 5 43 44 45 0.65 0.35 2.94 133 3.00
6d04d66b-3a92-4534-a631-60a2c1a97b91 8 38 42 13 0.54 0.46 2.59 132 3.00
bff70a6d-0316-43b8-b62b-c4f6685e2324 13 70 56 10 0.44 0.56 2.42 132 2.00
aa50cb1c-ff86-487b-989d-2f2e4ec6da32 1 4 6 3 0.64 0.36 2.79 131 3.00
4e96c179-83e4-4ab5-992c-ee274e74b155 15 67 61 10 0.46 0.54 2.43 130 2.00
62f0942b-e79d-454c-97bf-433f86e8b910 10 23 15 16 0.48 0.52 2.58 130 3.00
9b621682-6825-4906-988d-9d24c18e6a85 3 62 145 44 0.74 0.26 2.91 130 3.00
f698a7c3-3b36-48a7-897a-39cf90b1a583 5 26 21 8 0.48 0.52 2.53 130 3.00
344fd7d8-6f23-41a2-b9b4-8a315a795c76 1 30 50 1 0.62 0.38 2.62 126 3.00
91b439c6-d29e-425c-834c-52db0f1e89b4 9 66 93 36 0.63 0.37 2.76 125 3.00
af434425-573c-435d-b925-53dd8d74e1b8 5 20 32 18 0.67 0.33 2.84 125 3.00
127f9705-ec8e-4c1d-a2d0-74b4bef6b5cb 10 42 55 18 0.58 0.42 2.65 123 3.00
9780991a-14a3-4deb-92fd-fdefd1da9b8b 2 25 42 9 0.65 0.35 2.74 123 3.00
9dc64637-d7bd-4d13-a4ed-fe477ddf0b40 4 31 78 25 0.75 0.25 2.90 123 3.00
f28e1d2b-e7c2-4ae7-ada7-47afc99c434e 6 26 19 9 0.47 0.53 2.52 123 3.00
7bebee40-5138-4513-bb67-d57fbcff0c03 0 22 67 8 0.77 0.23 2.86 122 3.00
8a90f513-aeb5-40be-a968-c408e47d7ec3 2 33 38 46 0.71 0.29 3.08 121 3.00
e53437a9-fc36-411a-90ba-7eabde133143 15 75 61 8 0.43 0.57 2.39 121 2.00
b884b784-2704-47a4-9231-5090ee55682b 0 28 74 20 0.77 0.23 2.93 119 3.00
388dc9a1-c16b-457b-85c8-693d4d3ccd1b 3 14 46 43 0.84 0.16 3.22 118 3.00
dd4ba4f4-344f-46c6-ba29-3df1113b6264 6 29 15 4 0.35 0.65 2.31 118 2.00
4570c7d6-be76-41df-b869-f11f90632337 10 21 53 37 0.74 0.26 2.97 116 3.00
567a27d6-4469-4d91-afbf-1588cd662954 0 37 44 1 0.55 0.45 2.56 116 3.00
43cc9da1-caaa-4ea3-ab19-073613274d88 5 32 49 12 0.62 0.38 2.69 115 3.00
92ce985e-3d27-4786-a59d-4736db4a5d29 1 32 50 6 0.63 0.37 2.69 115 3.00
4ba23f2e-57df-4133-ac2f-43042ed05e75 4 45 33 14 0.49 0.51 2.59 114 3.00
9548733e-8b9a-4200-b988-3690e5457bc8 5 35 30 14 0.52 0.48 2.63 114 3.00
5ef302fc-08f8-4348-a19b-8d3cc98c8d58 3 29 46 12 0.64 0.36 2.74 113 3.00
ebb66f5f-4674-472c-9450-0b814b54de9f 0 22 36 1 0.63 0.37 2.64 111 3.00
463c8323-c578-41be-a83c-9be6e0989560 0 2 6 0 0.75 0.25 2.75 110 3.00
a1205445-af4e-4434-ba20-2e09943445d3 10 34 20 7 0.38 0.62 2.34 110 2.00
74c399e9-1e59-45b6-9112-10f681d488fe 7 52 38 10 0.45 0.55 2.48 109 2.00
8e873258-e4f1-4798-96fa-d758fd94004c 5 53 70 24 0.62 0.38 2.74 109 3.00
27486d8a-1d33-4d2e-8c7c-7eb9abd85323 1 35 27 6 0.48 0.52 2.55 108 3.00
29c7a6e1-2d6a-4303-810a-b08d75860859 3 35 94 13 0.74 0.26 2.81 107 3.00
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