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Multi-line plot with collapsing to / dismantling from aggregate
Raw
Readme.md

The chart shows a multi-line plot that can be collapsed into a single aggregated line.

Mouse interaction is based on invisible thick lines, as the dataset changes through collapsing / dismantling and hence voronoi maps would need to be re-calculated.

You can view a rendered version of this gist at bl.ocks.org.

Raw
assembly_code.js
// define margins
var margin = {top: 20, right: 80, bottom: 30, left: 150};
// graphics size without axis
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 + ")");
// axes scales
var x = d3.time.scale()
.range([0, width]);
var y = d3.scale.log()
.range([height, 0]);
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.ticks(5);
// parse dates and remove missing values
var parseDate = d3.time.format("%Y-%m-%d").parse;
var line = d3.svg.line()
.defined(function(d) { return !isNaN(d.gdp); })
.interpolate("basis")
.x(function(d) { return x(d.idx); })
.y(function(d) { return y(d.gdp); });
var tsdata = d3.csv("gdp.csv", function (data) {
var countryNames = d3.keys(data[0]).filter(function(key) { return key !== "idx"; });
data.forEach(function(d) {
d.idx = parseDate(d.idx);
});
var tseries = countryNames.map(function(name) {
countryData = data.map(function(d) {
return {idx: d.idx, gdp: +d[name]/1000000000, country: name};
})
return {name: name,
values: countryData
};
});
x.domain(d3.extent(data, function(d) { return d.idx; }));
y.domain([
d3.min(tseries, function(c) { return d3.min(c.values, function(v) { return v.gdp; }); }),
d3.max(tseries, function(c) { return d3.max(c.values, function(v) { return v.gdp; }); })
]);
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
svg.append("g")
.attr("class", "y axis")
.call(yAxis)
.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 6)
.attr("dy", ".71em")
.style("text-anchor", "end")
.text("GDP in bn $");
var gdp = svg.selectAll(".gdp")
.data(tseries)
.enter()
.append("g")
.attr("class", "gdp")
.append("path")
.attr("class", "line")
.attr("d", function(d) { d.line = this; return line(d.values); });
// .on("mouseover", onmouseover)
// .on("mouseout", onmouseout);
// function onmouseover(d, i) {
// var currClass = d3.select(this).attr("class");
// d3.select(this).attr("class", "current");
// var blurb = '<h2>' + this.__data__.name + '</h2>';
// d3.selectAll("h2").text(this.__data__.name)
// // d3.select("#default-blurb").hide();
// d3.select("#blurb-content").html(blurb);
// }
// function onmouseout(d, i) {
// d3.select(this).attr("class", "line");
// d3.selectAll("h2").text("World")
// }
// voronoi
var voronoi = d3.geom.voronoi()
.x(function(d) { return x(d.idx); })
.y(function(d) { return y(d.gdp); })
.clipExtent([[-margin.left, -margin.top], [width + margin.right, height + margin.bottom]]);
var voronoiGroup = svg.append("g")
.attr("class", "voronoi");
voronoiGroup.selectAll("path")
.data(voronoi(d3.nest()
.key(function(d) { return x(d.idx) + "," + y(d.gdp); })
.rollup(function(v) { return v[0]; })
.entries(d3.merge(tseries.map(function(d) { return d.values; })))
.map(function(d) { return d.values; })
.filter(function(d) { return !isNaN(d.gdp) })))
.enter().append("path")
.attr("d", function(d) { return "M" + d.join("L") + "Z"; })
.datum(function(d) { return d.point; })
.on("mouseover", mouseover)
.on("mouseout", mouseout);
function mouseover(d) {
svg.selectAll("path").filter(function(c) { return c.name == d.country})
.attr("class", "city--hover")
d3.selectAll("h2").text(d.country)
// gdp[0].filter(function(c) { return c.__data__.name == d.country })
// d3.select(d.country.line).classed("city--hover", true);
// d.country.line.parentNode.appendChild(d.country.line);
// // focus.attr("transform", "translate(" + x(d.date) + "," + y(d.value) + ")");
// // focus.select("text").text(d.city.name);
}
function mouseout(d) {
svg.selectAll("path").filter(function(c) { return c.name == d.country})
.attr("class", "line")
d3.selectAll("h2").text("World")
// d3.select(d.country.line).classed("city--hover", false);
// focus.attr("transform", "translate(-100,-100)");
}
});
Raw
index.html
<!DOCTYPE html>
<meta charset="utf-8">
<style>
body {
font: 16px sans-serif;
}
.axis path,
.axis line {
fill: none;
stroke: #000;
shape-rendering: crispEdges;
}
.x.axis path {
<!-- display: none; -->
}
.line {
fill: none;
stroke: gray;
stroke-width: 1.5px;
stroke-opacity: 0.2;
}
.grid .tick {
stroke: lightgrey;
stroke-opacity: 0.7;
shape-rendering: crispEdges;
}
.grid path {
stroke-width: 0;
}
.line current {
fill: none;
stroke: red;
stroke-width: 3.5px;
stroke-opacity: 0.2;
}
.current {
fill: none;
stroke: red;
stroke-width: 3.5px;
stroke-opacity: 1;
}
.voronoi path {
fill: none;
pointer-events: all;
}
.city--hover {
fill: none;
stroke: black;
stroke-width: 3.5px;
stroke-opacity: 1;
}
</style>
<body>
<script src="http://d3js.org/d3.v3.min.js" charset="utf-8">
</script>
<div id="blurb">
<div id="default-blurb">
<h2>World</h2>
<p>GDP evolution.</p>
</div>
<div id="blurb-content"></div>
</div>
<script src="assembly_code.js">
</script>
</body>
</html>
Raw
region_gdp.bkr
{
"beaker": "2",
"evaluators": [
{
"name": "Html",
"plugin": "Html",
"view": {
"cm": {
"mode": "htmlmixed"
}
}
},
{
"name": "Latex",
"plugin": "Latex",
"view": {
"cm": {
"mode": "stex"
}
}
},
{
"name": "JavaScript",
"plugin": "JavaScript",
"jsSetting2": "",
"jsSetting1": "",
"view": {
"cm": {
"mode": "javascript",
"background": "#FFE0F0"
}
}
},
{
"name": "",
"plugin": "Julia"
},
{
"name": "",
"plugin": "R"
}
],
"cells": [
{
"id": "codemYRvOu",
"type": "code",
"evaluator": "Julia",
"input": {
"body": [
"Pkg.clone(\"https://github.com/JuliaFinMetriX/WorldBankDataTd.jl.git\")"
]
},
"output": {
"state": {},
"result": {
"type": "Results",
"outputdata": [
{
"type": "out",
"value": "INFO: Cloning WorldBankDataTd from https://github.com/JuliaFinMetriX/WorldBankDataTd.jl.git\n"
},
{
"type": "out",
"value": "INFO: Computing changes...\n"
},
{
"type": "out",
"value": "INFO: Cloning cache of HTTPClient from git://github.com/JuliaWeb/HTTPClient.jl.git\n"
},
{
"type": "out",
"value": "INFO: Cloning cache of LibCURL from git://github.com/JuliaWeb/LibCURL.jl.git\n"
},
{
"type": "out",
"value": "INFO: Cloning cache of TimeData from git://github.com/JuliaFinMetriX/TimeData.jl.git\n"
},
{
"type": "out",
"value": "INFO: Cloning cache of TimeSeries from git://github.com/JuliaStats/TimeSeries.jl.git\n"
},
{
"type": "out",
"value": "INFO: Installing HTTPClient v0.1.4\n"
},
{
"type": "out",
"value": "INFO: Installing LibCURL v0.1.4\n"
},
{
"type": "out",
"value": "INFO: Installing TimeData v0.5.1\n"
},
{
"type": "out",
"value": "INFO: Installing TimeSeries v0.4.6\n"
},
{
"type": "out",
"value": "INFO: Building LibCURL\n"
}
]
},
"selectedType": "Results",
"pluginName": "Julia",
"shellId": "99A7F9F034DB468B886BAC31E48BB037",
"elapsedTime": 13855
},
"evaluatorReader": true,
"lineCount": 1
},
{
"id": "code3phbzx",
"type": "code",
"evaluator": "Julia",
"input": {
"body": [
"using WorldBankDataTd",
"using TimeData",
"gdp = wdi([\"NY.GDP.PCAP.KD\"], \"all\")"
]
},
"output": {
"state": {},
"result": {
"type": "Results",
"outputdata": [
{
"type": "err",
"value": "download: http://api.worldbank.org/countries/AW;AF;A9;AO;AL;AD;L5;1A;AE;AR;AM;AS;AG;AU;AT;AZ;BI;BE;BJ;BF;BD;BG;BH;BS;BA;BY;BZ;BM;BO;BR;BB;BN;BT;BW;C9;CF;CA;C4;B8;C5;CH;JG;CL;CN;CI;C6;C7;CM;CD;CG;CO;KM;CV;CR;C8;S3;CU;CW;KY;CY;CZ;DE;DJ;DM;DK;DO;DZ;4E;Z4;7E;Z7;EC;EG;XC;ER;ES;EE;ET;EU;F1;FI;FJ;FR;FO;FM;GA;GB;GE;GH;GN;GM;GW;GQ;GR;GD;GL;GT;GU;GY;XD;HK;HN;XE;HR;HT;HU;ID;IM;IN;XY;IE;IR;IQ;IS;IL;IT;JM;JO;JP;KZ;KE;KG;KH;KI;KN;KR;KV;KW;XJ;LA;LB;LR;LY;LC;ZJ;L4;XL;XM;LI;LK;XN;XO;LS;LT;LU;LV;MO;MF;MA;L6;MC;MD;MG;MV;ZQ;MX;MH;XP;MK;ML;MT;MM;XQ;ME;MN;MP;MZ;MR;MU;MW;MY;XU;M2;NA;NC;NE;NG;NI;NL;XR;NO;NP;NZ;XS;OE;OM;S4;PK;PA;PE;PH;PW;PG;PL;PR;KP;PT;PY;PS;S2;PF;QA;RO;RU;RW;8S;SA;L7;SD;SN;SG;SB;SL;SV;SM;SO;RS;ZF;SS;ZG;S1;ST;SR;SK;SI;SE;SZ;SX;A4;SC;SY;TC;TD;TG;TH;TJ;TM;TL;TO;TT;TN;TR;TV;TZ;UG;UA;XT;UY;US;UZ;VC;VE;VI;VN;VU;1W;WS;A5;YE;ZA;ZM;ZW/indicators/NY.GDP.PCAP.KD?date=1800:3000&per_page=25000&format=json"
},
{
"type": "err",
"value": "\n"
}
],
"status": "RUNNING"
},
"selectedType": "Results",
"pluginName": "Julia",
"shellId": "99A7F9F034DB468B886BAC31E48BB037",
"elapsedTime": 14571
},
"evaluatorReader": true,
"lineCount": 3
},
{
"id": "code2Ui2DJ",
"type": "code",
"evaluator": "Julia",
"input": {
"body": [
"names(gdp)"
]
},
"output": {
"state": {},
"result": "<div class=\"out_prompt_overlay prompt\" title=\"click to expand output; double click to hide output\" style=\"display: none;\"></div><div class=\"output\" style=\"display: none;\"></div><div class=\"btn output_collapsed\" title=\"click to expand output\" style=\"display: none;\">. . .</div><div class=\"output_subarea output_text\"><pre>3-element Array{Symbol,1}:\n :iso2c \n :country \n symbol(\"NY.GDP.PCAP.KD\")</pre></div>",
"selectedType": "Html",
"pluginName": "Julia",
"shellId": "99A7F9F034DB468B886BAC31E48BB037",
"elapsedTime": 53
},
"evaluatorReader": true,
"lineCount": 1
},
{
"id": "code3yqnYL",
"type": "code",
"evaluator": "Julia",
"input": {
"body": [
"countryData = getWBMeta(\"countries\")",
"countryData[1:5, 1:3]"
]
},
"output": {
"state": {},
"result": {
"type": "Results",
"outputdata": [
{
"type": "err",
"value": "download: http://api.worldbank.org/countries/all?per_page=25000&format=json"
},
{
"type": "err",
"value": "\n"
}
],
"status": "RUNNING"
},
"selectedType": "Results",
"pluginName": "Julia",
"shellId": "99A7F9F034DB468B886BAC31E48BB037",
"elapsedTime": 565
},
"evaluatorReader": true,
"lineCount": 2
},
{
"id": "codeU2WyZn",
"type": "code",
"evaluator": "Julia",
"input": {
"body": [
"countryData"
]
},
"output": {
"state": {},
"result": "<div class=\"out_prompt_overlay prompt\" title=\"click to expand output; double click to hide output\" style=\"display: none;\"></div><div class=\"output\" style=\"display: none;\"></div><div class=\"btn output_collapsed\" title=\"click to expand output\" style=\"display: none;\">. . .</div><div class=\"output_subarea output_html rendered_html\"><table class=\"data-frame\"><tbody><tr><th></th><th>iso3c</th><th>iso2c</th><th>name</th><th>region</th><th>regionId</th><th>capital</th><th>longitude</th><th>latitude</th><th>income</th><th>incomeId</th><th>lending</th><th>lendingId</th></tr><tr><th>1</th><td>ABW</td><td>AW</td><td>Aruba</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>Oranjestad</td><td>-70.0167</td><td>12.5167</td><td>High income: nonOECD</td><td>NOC</td><td>Not classified</td><td>LNX</td></tr><tr><th>2</th><td>AFG</td><td>AF</td><td>Afghanistan</td><td>South Asia</td><td>SAS</td><td>Kabul</td><td>69.1761</td><td>34.5228</td><td>Low income</td><td>LIC</td><td>IDA</td><td>IDX</td></tr><tr><th>3</th><td>AFR</td><td>A9</td><td>Africa</td><td>Aggregates</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>Aggregates</td><td>NA</td><td>Aggregates</td><td>NA</td></tr><tr><th>4</th><td>AGO</td><td>AO</td><td>Angola</td><td>Sub-Saharan Africa (all income levels)</td><td>SSF</td><td>Luanda</td><td>13.242</td><td>-8.81155</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>5</th><td>ALB</td><td>AL</td><td>Albania</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Tirane</td><td>19.8172</td><td>41.3317</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>6</th><td>AND</td><td>AD</td><td>Andorra</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Andorra la Vella</td><td>1.5218</td><td>42.5075</td><td>High income: nonOECD</td><td>NOC</td><td>Not classified</td><td>LNX</td></tr><tr><th>7</th><td>ANR</td><td>L5</td><td>Andean Region</td><td>Aggregates</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>Aggregates</td><td>NA</td><td>Aggregates</td><td>NA</td></tr><tr><th>8</th><td>ARB</td><td>1A</td><td>Arab World</td><td>Aggregates</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>Aggregates</td><td>NA</td><td>Aggregates</td><td>NA</td></tr><tr><th>9</th><td>ARE</td><td>AE</td><td>United Arab Emirates</td><td>Middle East &amp; North Africa (all income levels)</td><td>MEA</td><td>Abu Dhabi</td><td>54.3705</td><td>24.4764</td><td>High income: nonOECD</td><td>NOC</td><td>Not classified</td><td>LNX</td></tr><tr><th>10</th><td>ARG</td><td>AR</td><td>Argentina</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>Buenos Aires</td><td>-58.4173</td><td>-34.6118</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>11</th><td>ARM</td><td>AM</td><td>Armenia</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Yerevan</td><td>44.509</td><td>40.1596</td><td>Lower middle income</td><td>LMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>12</th><td>ASM</td><td>AS</td><td>American Samoa</td><td>East Asia &amp; Pacific (all income levels)</td><td>EAS</td><td>Pago Pago</td><td>-170.691</td><td>-14.2846</td><td>Upper middle income</td><td>UMC</td><td>Not classified</td><td>LNX</td></tr><tr><th>13</th><td>ATG</td><td>AG</td><td>Antigua and Barbuda</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>Saint John's</td><td>-61.8456</td><td>17.1175</td><td>High income: nonOECD</td><td>NOC</td><td>IBRD</td><td>IBD</td></tr><tr><th>14</th><td>AUS</td><td>AU</td><td>Australia</td><td>East Asia &amp; Pacific (all income levels)</td><td>EAS</td><td>Canberra</td><td>149.129</td><td>-35.282</td><td>High income: OECD</td><td>OEC</td><td>Not classified</td><td>LNX</td></tr><tr><th>15</th><td>AUT</td><td>AT</td><td>Austria</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Vienna</td><td>16.3798</td><td>48.2201</td><td>High income: OECD</td><td>OEC</td><td>Not classified</td><td>LNX</td></tr><tr><th>16</th><td>AZE</td><td>AZ</td><td>Azerbaijan</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Baku</td><td>49.8932</td><td>40.3834</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>17</th><td>BDI</td><td>BI</td><td>Burundi</td><td>Sub-Saharan Africa (all income levels)</td><td>SSF</td><td>Bujumbura</td><td>29.3639</td><td>-3.3784</td><td>Low income</td><td>LIC</td><td>IDA</td><td>IDX</td></tr><tr><th>18</th><td>BEL</td><td>BE</td><td>Belgium</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Brussels</td><td>4.36761</td><td>50.8371</td><td>High income: OECD</td><td>OEC</td><td>Not classified</td><td>LNX</td></tr><tr><th>19</th><td>BEN</td><td>BJ</td><td>Benin</td><td>Sub-Saharan Africa (all income levels)</td><td>SSF</td><td>Porto-Novo</td><td>2.6323</td><td>6.4779</td><td>Low income</td><td>LIC</td><td>IDA</td><td>IDX</td></tr><tr><th>20</th><td>BFA</td><td>BF</td><td>Burkina Faso</td><td>Sub-Saharan Africa (all income levels)</td><td>SSF</td><td>Ouagadougou</td><td>-1.53395</td><td>12.3605</td><td>Low income</td><td>LIC</td><td>IDA</td><td>IDX</td></tr><tr><th>21</th><td>BGD</td><td>BD</td><td>Bangladesh</td><td>South Asia</td><td>SAS</td><td>Dhaka</td><td>90.4113</td><td>23.7055</td><td>Low income</td><td>LIC</td><td>IDA</td><td>IDX</td></tr><tr><th>22</th><td>BGR</td><td>BG</td><td>Bulgaria</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Sofia</td><td>23.3238</td><td>42.7105</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>23</th><td>BHR</td><td>BH</td><td>Bahrain</td><td>Middle East &amp; North Africa (all income levels)</td><td>MEA</td><td>Manama</td><td>50.5354</td><td>26.1921</td><td>High income: nonOECD</td><td>NOC</td><td>Not classified</td><td>LNX</td></tr><tr><th>24</th><td>BHS</td><td>BS</td><td>Bahamas, The</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>Nassau</td><td>-77.339</td><td>25.0661</td><td>High income: nonOECD</td><td>NOC</td><td>Not classified</td><td>LNX</td></tr><tr><th>25</th><td>BIH</td><td>BA</td><td>Bosnia and Herzegovina</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Sarajevo</td><td>18.4214</td><td>43.8607</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>26</th><td>BLR</td><td>BY</td><td>Belarus</td><td>Europe &amp; Central Asia (all income levels)</td><td>ECS</td><td>Minsk</td><td>27.5766</td><td>53.9678</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>27</th><td>BLZ</td><td>BZ</td><td>Belize</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>Belmopan</td><td>-88.7713</td><td>17.2534</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>28</th><td>BMU</td><td>BM</td><td>Bermuda</td><td>North America</td><td>NAC</td><td>Hamilton</td><td>-64.706</td><td>32.3293</td><td>High income: nonOECD</td><td>NOC</td><td>Not classified</td><td>LNX</td></tr><tr><th>29</th><td>BOL</td><td>BO</td><td>Bolivia</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>La Paz</td><td>-66.1936</td><td>-13.9908</td><td>Lower middle income</td><td>LMC</td><td>Blend</td><td>IDB</td></tr><tr><th>30</th><td>BRA</td><td>BR</td><td>Brazil</td><td>Latin America &amp; Caribbean (all income levels)</td><td>LCN</td><td>Brasilia</td><td>-47.9292</td><td>-15.7801</td><td>Upper middle income</td><td>UMC</td><td>IBRD</td><td>IBD</td></tr><tr><th>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr></tbody></table></div>",
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"isSSF = countryData[:regionId] .== \"SSF\"",
"",
"# replace NA with false",
"isSSF[isSSF.na] = false",
"",
"ssfCountries = countryData[isSSF, :iso2c]",
"",
"# add SSF aggregate itself",
"ssfName = countryData[countryData[:name] .== \"Sub-Saharan Africa (all income levels)\", :iso2c]",
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"ssfData = chkDates(x -> in(x[:iso2c][1], allCountries), eachrow(gdp)) |>",
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