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Self-tracking dataviz with Vega
// To try this out, go to: http://bl.ocks.org/ksen0/cb625f3991e37d0f0a2236ff5961c0b7
// Alternatively: download both files and open the .html file in your browser.
// Data is based on an export from beeminder, but any timestamped data will work.
// Visualization focuses on the display of different activities over time: some are incremental
// (in minutes or hours), some are episodic. There are also phases of life in the visualization.
metadata = {
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};
datapoints = {
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function get_events(val = "timestamp", whichs = []) {
out = {data: []};
out.min = undefined;
out.max = undefined;
$.each(whichs, function(index, which){
$.each(datapoints[which], function(index, values){
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out.min = values[val];
} if (out.max == undefined || values[val] > out.max) {
out.max = values[val];
}
out.data.push({event: which, value: values[val]})
});
});
return out;
}
function get_xy(x="timestamp", y="value", x_readable="daystamp", y_accumulate="acc", y_filter = ((x) => true), y_transform = ((x) => x), which = undefined) {
if (which == undefined || datapoints[which] == undefined)
console.log("Bad get_xy call")
out = [];
acc = undefined;
datapoints[which].sort(function(a, b) {
return a[x] - b[x];
});
$.each(datapoints[which], function(index, values){
if (y_filter(values[y])) {
row = {}
row[x] = values[x]
row[y] = y_transform(values[y])
row[x_readable] = values[x_readable]
if (acc == undefined) {
acc = values[y];
} else {
acc += values[y];
}
row[y_accumulate] = y_transform(acc);
out.push(row);
}
});
return out;
}
<!DOCTYPE html>
<html>
<head>
<title>b-viz</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta http-equiv="x-ua-compatible" content="ie=edge">
<meta name="description" content="Vega - A Visualization Grammar. Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate web-based views using Canvas or SVG.">
<link rel="stylesheet" href="https://vega.github.io/vega/assets/syntax.css">
<link rel="stylesheet" href="https://vega.github.io/vega/assets/main.css">
<script src="https://vega.github.io/vega/assets/promise.min.js"></script>
<script src="https://vega.github.io/vega/vega.js"></script>
<script src="bee_data.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
</head>
<body>
<div class="embed">
<div id="falkensee-population" class="view"></div>
<a href="../falkensee-population.vg.json">View Source</a>
<a id="falkensee-population-png" href="#">Export PNG</a>
<a id="falkensee-population-svg" href="#">Export SVG</a>
</div>
<script>
events = get_events("timestamp", ["books", "bouldern", "arts", "lrn", "tech"])
stepsize = (events.max - events.min) / 500
var spec = {
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"height": 70*5,
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{ "name": "plotWidth", "value": 70 },
{ "name": "height", "update": "(plotWidth + 10) * length(fields)"},
{ "name": "bandwidth", "value": 550000,
"bind": {"input": "range", "min": 50000, "max": 1000000, "step": 10000} },
{ "name": "steps", "value": 0,
"bind": {"input": "range", "min": 0, "max": 15, "step": 1} }
],
"data": [
{
"name": "event_log",
"values": events.data
},
{
"name": "german",
"values": get_xy("timestamp", "value", "daystamp", "total", ((x) => x>0), ((x) => x*15/60), "german")
},
{
"name": "japanese",
"values": get_xy("timestamp", "value", "daystamp", "total", ((x) => x>0), ((x) => x*15/60), "japanese")
},
{
"name": "dissertation",
"values": get_xy("timestamp", "value", "daystamp", "total", ((x) => x>0), ((x) => x*15/60), "dissertation")
},
{
"name": "depra",
"values": get_xy("timestamp", "value", "daystamp", "total", ((x) => x>0), ((x) => x/60), "depra")
},
/*{
"name": "summary",
"source": "german",
"transform": [
{
"type": "aggregate",
"fields": ["timestamp", "timestamp"],
"ops": ["min", "max"]
}
]
}*/
{
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"values": [
{
"start": 1456268399,
"end": 1464450000,
"text": "PhD Final Stretch"
},
{
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},
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},
{
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"end": 1482650000,
"text": "50min Commute"
},
{
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"end": 1483516799,
"text": "Winter Break"
},
{
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"end": 1496213999,
"text": "75min Commute"
}
]
}
],
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"range": "width",
"nice": false,
"zero": false,
"domain": {"data": "german", "field": "timestamp"}
},
{
"name": "y",
"type": "linear",
"range": "height",
"nice": true,
"zero": true,
"domain": {"data": "german", "field": "total"}
},
{
"name": "annotate_color",
"type": "ordinal",
"domain": {"data": "annotation", "field": "text"},
"scheme": "purplebluegreen"
},
{
"name": "event_color",
"type": "ordinal",
"range": ["#ffed6f"]
},
{
"name": "layout",
"type": "band",
"range": "height",
"domain": {"data": "event_log", "field": "event"}
},
{
"name": "xscale",
"type": "linear",
"range": "width",
"domain": {"data": "german", "field": "timestamp"},
"zero": false, "nice": false
}
],
"axes": [
{
"orient": "left",
"scale": "y",
"title": "Hours",
"titlePadding": 10,
"grid": true
},
{"orient": "right", "scale": "layout", "tickCount": 5, "zindex": 1}
],
"marks": [
{
"type": "rect",
"from": {"data": "annotation"},
"encode": {
"enter": {
"x": {"scale": "x", "field": "start"},
"x2": {"scale": "x", "field": "end"},
"y": {"value": 0},
"y2": {"signal": "height"},
"fill": {"scale": "annotate_color", "field": "text"},
"opacity": {"value": 0.4}
}
}
},
{
"type": "group",
"from": {
"facet": {
"data": "event_log",
"name": "events",
"groupby": "event"
}
},
"encode": {
"enter": {
"yc": {"scale": "layout", "field": "event", "band": 0.5},
"height": {"signal": "plotWidth"},
"width": {"signal": "width"}
}
},
"data": [
{
"name": "density",
"transform": [
{
"type": "density",
"steps": {"signal": "steps"},
"distribution": {
"function": "kde",
"from": "events",
"field": "value",
"bandwidth": {"signal": "bandwidth"}
}
},
{
"type": "stack",
"groupby": ["value"],
"field": "density",
"offset": "center",
"as": ["y0", "y1"]
}
]
},
{
"name": "summary",
"source": "events",
"transform": [
{
"type": "aggregate",
"fields": ["value", "value", "value"],
"ops": ["q1", "median", "q3"],
"as": ["q1", "median", "q3"]
}
]
}
],
"scales": [
{
"name": "yscale",
"type": "linear",
"range": [0, {"signal": "plotWidth"}],
"domain": {"data": "density", "field": "density"}
}
],
"marks": [
{
"type": "area",
"from": {"data": "density"},
"encode": {
"enter": {
"fill": {"scale": "event_color", "field": {"parent": "event"}}
},
"update": {
"x": {"scale": "xscale", "field": "value"},
"y": {"scale": "yscale", "field": "y0"},
"y2": {"scale": "yscale", "field": "y1"}
}
}
},
{
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"enter": {
"fill": {"value": "#fb8072"},
"height": {"value": 1}
},
"update": {
"yc": {"signal": "plotWidth / 2", "offset": -0.5},
"x": {"scale": "xscale", "field": "q1"},
"x2": {"scale": "xscale", "field": "q3"}
}
}
},
{
"type": "rect",
"from": {"data": "summary"},
"encode": {
"enter": {
"fill": {"value": "#fb8072"},
"width": {"value": 2}
},
"update": {
"yc": {"signal": "plotWidth / 2"},
"height": {"value": 8},
"x": {"scale": "xscale", "field": "median"}
}
}
}
]
},
{
"type": "line",
"from": {"data": "german"},
"encode": {
"enter": {
"interpolate": {"value": "monotone"},
"x": {"scale": "x", "field": "timestamp"},
"y": {"scale": "y", "field": "total"},
"stroke": {"value": "#fb8072"},
"strokeWidth": {"value": 2}
}
}
},
/*{
"type": "line",
"from": {"data": "japanese"},
"encode": {
"enter": {
"interpolate": {"value": "monotone"},
"x": {"scale": "x", "field": "timestamp"},
"y": {"scale": "y", "field": "total"},
"stroke": {"value": "#fb8072"},
"strokeWidth": {"value": 2}
}
}
},
{
"type": "line",
"from": {"data": "depra"},
"encode": {
"enter": {
"interpolate": {"value": "monotone"},
"x": {"scale": "x", "field": "timestamp"},
"y": {"scale": "y", "field": "total"},
"stroke": {"value": "#fb8072"},
"strokeWidth": {"value": 2}
}
}
},
{
"type": "line",
"from": {"data": "meditate"},
"encode": {
"enter": {
"interpolate": {"value": "monotone"},
"x": {"scale": "x", "field": "timestamp"},
"y": {"scale": "y", "field": "total"},
"stroke": {"value": "#fb8072"},
"strokeWidth": {"value": 2}
}
}
},
{
"type": "line",
"from": {"data": "dissertation"},
"encode": {
"enter": {
"interpolate": {"value": "monotone"},
"x": {"scale": "x", "field": "timestamp"},
"y": {"scale": "y", "field": "total"},
"stroke": {"value": "#fb8072"},
"strokeWidth": {"value": 2}
}
}
}*/
],
"legends": [
{
"fill": "annotate_color",
"title": "Period",
"orient": "top-left",
"offset": 8,
"encode": {
"symbols": {
"update": {
"strokeWidth": {"value": 0},
"shape": {"value": "square"},
"opacity": {"value": 0.3}
}
}
}
}
]
};
function image(view, type) {
return function(event) {
event.preventDefault();
view.toImageURL(type).then(function(url) {
var link = document.createElement('a');
link.setAttribute('href', url);
link.setAttribute('target', '_blank');
link.setAttribute('download', 'falkensee-population.' + type);
link.dispatchEvent(new MouseEvent('click'));
}).catch(function(error) { console.error(error); });
};
}
var view = new vega.View(vega.parse(spec), {
loader: vega.loader({baseURL: 'https://vega.github.io/vega/'}),
logLevel: vega.Warn,
renderer: 'canvas'
}).initialize('#falkensee-population').hover().run();
document.querySelector('#falkensee-population-png').addEventListener('click', image(view, 'png'));
document.querySelector('#falkensee-population-svg').addEventListener('click', image(view, 'svg'));
</script>
</div>
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