d3 selectAll().data() just returns data in first element. why - d3.js

I am trying to get the data in all the matching element using d3. I have following code
d3.selectAll('svg').selectAll('.line').data()
what i expect is that it should return data in all the matching element. but it just return data in first matching element.
if i just do
d3.selectAll('svg').selectAll('.line')
this shows that it has 2 group element and its data property contains the data.
if i just do var line = d3.selectAll('svg').selectAll('.line'); line[0].data()it gives me error. as line[0] become a DOM element without any property
how to get data in all matching selection or am i not clear on how to use it.


This is the expected behaviour as the spec on selection.data(values) reads:
If values is not specified, then this method returns the array of data
for the first group in the selection.
That explains why you only get the data bound to the first group.
To access data bound to all groups returned by your selection you could use:
d3.selectAll('svg').selectAll('.line').each(function(d) {
// Within this function d is this group's data.
// Iterate, accumulate, do whatever you like at this point.
});


I can not see your code, therefore I will show you a working one:
// scene setup
// we generate 3 SVG tags inside the page <body>
var $svg;
for (var svg = 0; svg < 3; svg++) {
$svg = d3.select("body").append("svg:svg").attr({
width: 200,
height: 200,
id: "svg_" + svg
});
}
// multiple selection + data
// consider the array of colors as data
var array_of_colors = ["red", "yellow", "blue", "khaki", "gray", "green"];
d3.selectAll("svg").selectAll("line.dash").data(array_of_colors).enter()
.append("svg:line").attr({
x1: function(d){return(50 + Math.random() * 50);},// random coordinates
y1: function(d){return(50 + Math.random() * 50);},// random coordinates
x2: 150,
y2: 140,
"stroke-width": 2,
stroke: function(d) {
console.log(d);
return (d);
}
}).classed({
"dash": true
});
The code produces 6 lines (as size of data array) in each SVG element:
Looks like:

Related

Showing the percentage value in pie chart

console.log(group1.top(Infinity));
gives me:
0:
key: "M"
value: {Recovered: 122, Hospitalized: 38922, Deceased: 641, Migrated_Other: 1}
__proto__: Object
1:
key: "F"
value: {Recovered: 82, Hospitalized: 19215, Deceased:.....
In this code:
.label(function(d) {
return d.key+": " + (d.value[type]/<?> * 100).toFixed(2) + "%";
})
if the type is Recovered then I want the sum of recovered values (122+82) in place of <?> i.e d.value["Recovered"]/(122+82)
I am just stuck at the syntax how to take the sum of values of the matched type in place of <?>.
I can only think of
group1.all()[0].value['Recovered']+group1.all()[1].value['Recovered']
Is there any better way?
Working Code:
https://blockbuilder.org/ninjakx/61d405cb0aaeda3be960e836f803cdd5

There are a couple of ways to do this. One is to compute the sum, manually as you show above, or by using a groupAll object.
The other way, which the pie chart example uses, is to use the angle data saved in the pie slices:
// workaround for #703: not enough data is accessible through .label() to display percentages
.on('pretransition', function(chart) {
chart.selectAll('text.pie-slice').text(function(d) {
return d.data.key + ' ' + dc.utils.printSingleValue((d.endAngle - d.startAngle) / (2*Math.PI) * 100) + '%';
})
});
As noted, there is not enough data supplied to .label() to use this approach, so this is applied after drawing, using the full data objects.

Draw/update circles in rect - nested selections confusion

I am trying to get a layout that would, for each object in the data array:
append a rect or a g element that will serve as container
inside or on top of this, append a circle for each of the coordinates.
Below is a mock-up of how the data is massaged before I'm trying to append to the DOM (at the top of the update() function in the block below):
[{
label: 'foo',
circles: [
{ x: 0, y: 10 },
{ x: 10, y: 10 }
]
},{
...
}]
The drawing and updating of the rect elements seems to be working fine, but I am getting the selection and joins confused for the circles.
Here's the block: http://blockbuilder.org/basilesimon/91f75ab5209a62981f11d30a81f618b5
With
var dots = rects.selectAll('.dots')
I can select the right data below but can't draw it.
Could you help me getting the selections right so I can draw and update both the rect and the circle, please?
Thank you Gerard for your help. This is my current state, but I've pitted myself into a hole by running a for loop instead of d3 selections.
I wonder if I couldn't nest the circles in g elements after building a new data object like so:
var data = dataset.map(function(d) {
var circles = d3.range(d.amount).map(function(i) {
return {
x: (i % 5)*20,
y: (i / 5 >> 0)*20
}
});
return {
label: d.label,
dots: circles
};
});
From each object in data, we'll append a g, and inside each g we'll append the circles. Any help appreciated, since this will affect the dots + i used by the update pattern...
New question here

Here is the problem:
var dots = svg.selectAll('dots')
You're selecting something that doesn't exist. Because of that, your "enter" selection will always contain all the data, and your "exit" selection will always be empty.
The solution is changing it for something like this:
var dots = svg.selectAll(".dots" + i)
And, in the enter selection, setting the classes:
.attr("class", "dots" + i)
Here is your updated bl.ocks (with some other minor changes): https://bl.ocks.org/anonymous/4c2e1d66f1ab890da983465a4f84ca9b

dc.js Incorporate regression chart into existing scatterplot with crossfilter

I am using dc.js and crossfilter.js to create a d3 dashboard, and am wondering how to implement a regression line into a scatterplot chart that responds to filtering.
I have been playing with a few examples re adding a regression line, but I have been unsuccessful extracting and incorporating the code.
I don't have a problem with the math, but rather with how to access the filtered data from the dimension, and then how to add the regression line to to the filtered scatterplot chart (so that the regression line also responds to future filtering).
jsFiddle Demo
var data = [
{"record":"record","date":"date","cars":"cars","bikes":"bikes"},
{"record":"1","date":"01/05/2012","cars":"1488.1","bikes":"49.73"},
{"record":"2","date":"02/05/2012","cars":"1374.29","bikes":"52.44"},
{"record":"3","date":"03/05/2012","cars":"1353.01","bikes":"47.92"},
{"record":"4","date":"04/05/2012","cars":"1420.33","bikes":"50.69"},
{"record":"5","date":"05/05/2012","cars":"1544.11","bikes":"47.47"},
{"record":"6","date":"06/05/2012","cars":"1292.84","bikes":"47.75"},
{"record":"7","date":"07/05/2012","cars":"1318.9","bikes":"48.64"},
{"record":"8","date":"08/05/2012","cars":"1686.3","bikes":"50.9"},
{"record":"9","date":"09/05/2012","cars":"1603.99","bikes":"53.44"},
{"record":"10","date":"10/05/2012","cars":"1420.1","bikes":"53.29"},
{"record":"11","date":"11/05/2012","cars":"1410.8","bikes":"54.06"},
{"record":"12","date":"12/05/2012","cars":"1374.62","bikes":"51.24"},
{"record":"13","date":"13/05/2012","cars":"1279.53","bikes":"53.96"},
{"record":"14","date":"14/05/2012","cars":"1330.47","bikes":"49.5"},
{"record":"15","date":"15/05/2012","cars":"1377.61","bikes":"52.32"},
{"record":"16","date":"16/05/2012","cars":"1302.12","bikes":"51.96"},
{"record":"17","date":"17/05/2012","cars":"1326.9","bikes":"49.86"},
{"record":"18","date":"18/05/2012","cars":"1181.55","bikes":"50.25"},
{"record":"19","date":"19/05/2012","cars":"1493.75","bikes":"51.24"},
{"record":"20","date":"20/05/2012","cars":"1463.9","bikes":"50.88"},
{"record":"21","date":"21/05/2012","cars":"1370.16","bikes":"51.09"},
{"record":"22","date":"22/05/2012","cars":"1403.3","bikes":"51.67"},
{"record":"23","date":"23/05/2012","cars":"1277.65","bikes":"49.3"},
{"record":"24","date":"24/05/2012","cars":"1361.94","bikes":"50.47"},
{"record":"25","date":"25/05/2012","cars":"1400.8","bikes":"51.55"},
{"record":"26","date":"26/05/2012","cars":"1289.09","bikes":"47.17"},
{"record":"27","date":"27/05/2012","cars":"1258.39","bikes":"52.12"},
{"record":"28","date":"28/05/2012","cars":"1288.71","bikes":"49.28"},
{"record":"29","date":"29/05/2012","cars":"1511.86","bikes":"50.73"},
{"record":"30","date":"30/05/2012","cars":"1300.38","bikes":"52.39"},
{"record":"31","date":"31/05/2012","cars":"1455.19","bikes":"49.53"},
{"record":"32","date":"01/06/2012","cars":"1311.89","bikes":"50.37"},
{"record":"33","date":"02/06/2012","cars":"1368.64","bikes":"50.87"},
{"record":"34","date":"03/06/2012","cars":"1360.05","bikes":"50.51"},
{"record":"35","date":"04/06/2012","cars":"1382.56","bikes":"49.67"},
{"record":"36","date":"05/06/2012","cars":"1304.15","bikes":"47.6"},
{"record":"37","date":"06/06/2012","cars":"1271.57","bikes":"50.22"},
{"record":"38","date":"07/06/2012","cars":"1442.38","bikes":"50.8"},
{"record":"39","date":"08/06/2012","cars":"1406.38","bikes":"53.14"},
{"record":"40","date":"09/06/2012","cars":"1724.16","bikes":"49.66"},
{"record":"41","date":"10/06/2012","cars":"1931.05","bikes":"53"},
{"record":"42","date":"11/06/2012","cars":"1669.47","bikes":"53.71"},
{"record":"43","date":"12/06/2012","cars":"1794.06","bikes":"51.78"},
{"record":"44","date":"13/06/2012","cars":"1625.98","bikes":"51.58"},
{"record":"45","date":"14/06/2012","cars":"1371.51","bikes":"52.36"},
{"record":"46","date":"15/06/2012","cars":"1418.05","bikes":"47.64"},
{"record":"47","date":"16/06/2012","cars":"1431","bikes":"53.14"},
{"record":"48","date":"17/06/2012","cars":"1527.21","bikes":"48.63"},
{"record":"49","date":"18/06/2012","cars":"1320.95","bikes":"51.7"},
{"record":"50","date":"19/06/2012","cars":"1396.93","bikes":"52.92"}
];
tSel1 = "cars";
tSel2 = "bikes";
data.forEach(function (d) {
d[tSel1] = +d[tSel1];
d[tSel2] = +d[tSel2];
});
var facts = crossfilter(data);
var allDimension = facts.groupAll();
var scatterDimension = facts.dimension(function(d) {return [+d[tSel1], +d[tSel2]];});
var scatterGroup = scatterDimension.group().reduceSum(function(d) { return d[tSel1]; });
var maxY1 = d3.max(data, function(d) {return d[tSel1]});
var maxY2 = d3.max(data, function(d) {return d[tSel2]});
var maxY1Plus = maxY1 + (maxY1 * 0.1);
var maxY2Plus = maxY2 + (maxY2 * 0.1);
var minY1 = d3.min(data, function(d) {return d[tSel1]});
var minY1Minus = minY1 * 0.9;
var minY2 = d3.min(data, function(d) {return d[tSel2]});
var minY2Minus = minY2 * 0.9;
xyScatterChart = dc.scatterPlot("#scatterPlot");
xyScatterChart
.width(600)
.height(400)
.margins({top: 20, right: 20, bottom: 20, left: 60})
.dimension(scatterDimension)
.group(scatterGroup)
.symbolSize(6)
.highlightedSize(15)
.brushOn(false)
.excludedOpacity(0.5)
.excludedSize(5)
.renderHorizontalGridLines(true)
.renderVerticalGridLines(true)
.x(d3.scale.linear().domain([minY1Minus,maxY1Plus]))
.y(d3.scale.linear().domain([minY2Minus,maxY2Plus]));
dc.renderAll();
dc.redrawAll();
<link href="http://dc-js.github.io/dc.js/css/dc.css" rel="stylesheet"/>
<script src="http://dc-js.github.io/dc.js/js/d3.js"></script>
<script src="http://dc-js.github.io/dc.js/js/crossfilter.js"></script>
<script src="http://dc-js.github.io/dc.js/js/dc.js"></script>
<div id="scatterPlot"></div>
References:
https://groups.google.com/forum/#!topic/dc-js-user-group/HaQMegKa_U0
https://bl.ocks.org/ctufts/298bfe4b11989960eeeecc9394e9f118

It would be awesome to include an example in dc.js, since this is something lots of people can use.
Maybe we can work together on that? I don't know the math but here's a simple way to use a composite chart to display a line on data calculated from an aggregated group.
First off, here's the composite chart with the old scatter plot embedded in it:
var composite = dc.compositeChart("#composite");
composite
.width(600)
.height(400)
.margins({top: 20, right: 20, bottom: 20, left: 60})
.dimension(scatterDimension)
.group(scatterGroup)
.compose([
dc.scatterPlot(composite)
.symbolSize(6)
.highlightedSize(15)
.brushOn(false)
.excludedOpacity(0.5)
.excludedSize(5)
.renderHorizontalGridLines(true)
.renderVerticalGridLines(true),
dc.lineChart(composite)
.group(regressionGroup(scatterGroup))
])
.x(d3.scale.linear().domain([minY1Minus,maxY1Plus]))
.y(d3.scale.linear().domain([minY2Minus,maxY2Plus]));
Note that we're supplying the scatter group to both the composite and the scatter plot. That's just because the composite chart requires a group even though it doesn't actually use it.
We've moved the parameters that have to do with coordinates to the main (composite) chart, but everything that is specific to the scatter plot stays on it. We've also added a line chart to the composite, which uses a "fake group" based on the scatter group.
This fake group is particularly fake, but it should be enough to get you started. Since I don't have time to learn the math today, I'll just pretend that the first and last points are the regression:
function regressionGroup(group) {
return {
all: function() {
var _all = group.all();
var first, last;
for(var i=0; i < _all.length; ++i) {
var key = _all[i].key;
if(!isNaN(key[0]) && !isNaN(key[1])) {
var kv = {key: key[0], value: key[1]};
if(!first)
first = kv;
last = kv;
}
}
return [first, last];
}
};
}
As with all fake groups, the idea is to calculate some group-like data when the chart asks for it (and no sooner), based on another group. Here the calculation is not very interesting, because you know how to calculate a regression and I don't. You'll want to replace first and last and the for loop with a real calculation; all this is doing is checking for valid points and keeping the first and last ones that it finds.
Interestingly, the scatter plot takes data where the key contains both x and y coordinates, but the line chart takes data where the key is x and the value is y. That's why we have the transformation kv = {key: key[0], value: key[1]}
Postscript
Note that you'll run into a dc.js bug if you put the regression guide points outside of the domain - the stack mixin is too aggressive about clipping points to the domain. There is an easy, ugly workaround that seems to work in this case: tell the line chart it has an ordinal x scale even though it doesn't:
var composite = dc.compositeChart("#composite"),
lineChart;
composite
.width(600)
// ...
.compose([
// ...
lineChart = dc.lineChart(composite)
.group(regressionGroup(scatterGroup))
])
lineChart.isOrdinal = d3.functor(true);
Yuck! But it works! This hack probably only works inside a composite!
https://jsfiddle.net/gordonwoodhull/5tpcxov1/12/

I have a fully functional example of regression. I was precisely doing it when I came here for help and I found your question. It requires regression.js (here).
This follows Gordon's excellent suggestion of a "fake group", which should really be called an inline group, or immediate group, or even group on-the-fly. Here is mine:
function myRegressionGroup(group, min, max, filter = false) {
return {
all: function() {
var _all = group.all();
var first, last;
if(filter) reg = regression.linear(_all.filter(function(k,v) {if(k.key[0]) return k.key}).map((k,v) => k.key));
else reg = regression.linear(_all.map((k,v) => k.key));
first = reg.predict(min);
last = reg.predict(max)
return [{key:first[0], value: first[1]}, {key: last[0], value: last[1]}]
}
};
}
Please notice that this function requires a crossfilter group and also the min and max from the x-scale. Since you typically have these values calculated for your xScale, all it takes is reusing them here. This is because the function uses the extremes with the predict method to calculate the two points of the regression line.
The optional filter data wrangler is for you to decide whether to remove empty values on x or not.
#Gordon, how should I do in order to include my regression example in the Examples of using dc.js?

d3 selectAll: count results

How do I count how many nodes were matched by a selectAll? (without joined data)
Or if there's data, how to count the data from the selection? (suppose I've set it with "data(function...)" so I don't know the length in advance)

Just use d3.selectAll(data).size().Hope this example help you:
var matrix = [
[11975, 5871, 8916, 2868],
[ 1951, 10048, 2060, 6171],
[ 8010, 16145, 8090, 8045],
[ 1013, 990, 940, 6907]
];
var tr = d3.select("body").append("table").selectAll("tr")
.data(matrix)
.enter().append("tr");
var td = tr.selectAll("td")
.data(function(d) { return d; })
.enter().append("td")
.text(function(d) { return d; });
var tdSize=tr.selectAll("td").size();
Complete jsfiddle here.

If you want the length conveniently from a callback function, such as setting an element attribute, it seems that you can get it from the third argument, like so:
node
.attr('some-property', function(datum, index, array) {
// d/datum = the individual data point
// index = the index of the data point (0, 1, 2, 3, etc)
// array = full array of data points
// array.length = the size/length of the data points / dataset
// some calculation involving array.length or whatever
return someValue;
});
Similar to the call signature of the JavaScript forEach/filter/etc. array functions.
Seems like most of the d3 functions support this:
https://github.com/d3/d3-selection
...current datum (d), the current index (i), and the current group (nodes), with this as the current DOM element (nodes[i])
...is a repeated phrase throughout the docs. So if you see a d3 function where you'd use d, you can probably also get index and array.

One way I have done this previously is to pass that information into the data function by making a new object.
.data(function(d) {
return d.Objects.map(function(obj) {
return {
Object: obj,
TotalObjects: d.Objects.length
}
});
Then in your update portions you use Object and still have the count available.
.attr("x", function(d) {
return d.Object.X;
})
.attr("y", function(d) {
return d.TotalObjects;
})

To get the data count, then after .selectAll() and .data(), it appears that .enter() is needed before .size():
legend_count = legendBoxG.selectAll("legend.box")
.data(curNodesData, (d) -> d.id)
.enter()
.size()
Without the .enter(), the result is 0. The .enter() makes it return the data count. (Code above is shown in Coffee dialect.)
I need to get the count before adding attributes to my svg objects (in order to scale them properly), and none of the preceding examples did that. However I can't seem to add more attributes after stripping out the count into a variable as above. So while the above approach demonstrates the operation of data() and enter() it isn't really a practical solution. What I do instead is to get the length of the data array itself before doing the selectAll(). I can do that most simply with the length property (not a function) on the data array itself:
legend_count = curNodesData.length

For NVD3 lineChart Remove Missing Values (to be able to interpolate)

I am using NVD3 to visualise data on economic inequality. The chart for the US is here: http://www.chartbookofeconomicinequality.com/inequality-by-country/USA/
These are two lineCharts on top of each other. The problem I have is that there are quite a lot of missing values and this causes two problems:
If I would not make sure that the missing values are not visualised the line Chart would connect all shown values with the missing values. Therefore I used the following to not have the missing values included in the line chart:
chart = nv.models.lineChart()
.x(function(d) { return d[0] })
.y(function(d) { return d[1]== 0 ? null : d[1]; })
But still if you hover over the x-axis you see that the missing values are shown in the tooltip on mouseover. Can I get rid of them altogether? Possibly using remove in NVD3?
The second problem is directly related to that. Now the line only connects values of the same series when there is no missing values in between. That means there are many gaps in the lines. Is it possible to connect the dots of one series even if there are missing values in between?
Thank you for your help!

As Lars showed, getting the graph to look the way you want is just a matter of removing the missing values from your data arrays.
However, you wouldn't normally want to do that by hand, deleting all the rows with missing values. You need to use an array filter function to remove the missing values from your data arrays.
Once you have the complete data array as an array of series objects, each with an array of values, this code should work:
//to remove the missing values, so that the graph
//will just connect the valid points,
//filter each data array:
data.forEach(function(series) {
series.values = series.values.filter(
function(d){return d.y||(d.y === 0);}
);
//the filter function returns true if the
//data has a valid y value
//(either a "true" value or the number zero,
// but not null or NaN)
});
Updated fiddle here: http://jsfiddle.net/xammamax/8Kk8v/
Of course, when you are constructing the data array from a csv where each series is a separate column, you can do the filtering at the same time as you create the array:
var chartdata = [];//initialize as empty array
d3.csv("top_1_L-shaped.csv", function(error, csv) {
if (error)
return console.log("there was an error loading the csv: " + error);
var columndata = ["Germany", "Switzerland", "Portugal",
"Japan", "Italy", "Spain", "France",
"Finland", "Sweden", "Denmark", "Netherlands"];
for (var i = 0; i < columndata.length; i++) {
chartdata[i].key = columndata[i];
chartdata[i].values = csv.map(function(d) {
return [+d["year"], +d[ columndata[i] ] ];
})
.filter(function(d){
return d[1]||(d[1] === 0);
});
//the filter is applied to the mapped array,
//and the results are assigned to the values array.
}
});

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