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d3.js: Stacked Bar Chart with low values

I faced with a problem when some values in a bar very small when at the same time most of the other values are big enough. As the result these chunks with low values are almost not visible. I did not find any solution hot to correctly round chunks(not manually because I now that I can round them to more higher values via scale + invert(in order to determine what values I needed to show them more or less visible)). As an example below: as you see the last bar with low values is almost not visible. So can you suggest how to fix it? It would be great to have an opportunity to be able to specify the min size of stacked bar chart chunk. Thank you in advance.
http://jsfiddle.net/vhcdt13x/
// Setup svg using Bostock's margin convention
var margin = {top: 20, right: 160, bottom: 35, left: 30};
var width = 960 - margin.left - margin.right,
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 + ")");
/* Data in strings like it would be if imported from a csv */
var data = [
{ year: "2006", redDelicious: "100", mcintosh: "150", oranges: "90", pears: "60" },
{ year: "2012", redDelicious: "1", mcintosh: "1", oranges: "1", pears: "1" }
];
var parse = d3.time.format("%Y").parse;
// Transpose the data into layers
var dataset = d3.layout.stack()(["redDelicious", "mcintosh", "oranges", "pears"].map(function(fruit) {
return data.map(function(d) {
return {x: parse(d.year), y: +d[fruit]};
});
}));
// Set x, y and colors
var x = d3.scale.ordinal()
.domain(dataset[0].map(function(d) { return d.x; }))
.rangeRoundBands([10, width-10], 0.02);
var y = d3.scale.linear()
.domain([0, d3.max(dataset, function(d) { return d3.max(d, function(d) { return d.y0 + d.y; }); })])
.range([height, 0]);
var colors = ["b33040", "#d25c4d", "#f2b447", "#d9d574"];
// Define and draw axes
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.ticks(5)
.tickSize(-width, 0, 0)
.tickFormat( function(d) { return d } );
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom")
.tickFormat(d3.time.format("%Y"));
svg.append("g")
.attr("class", "y axis")
.call(yAxis);
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
// Create groups for each series, rects for each segment
var groups = svg.selectAll("g.cost")
.data(dataset)
.enter().append("g")
.attr("class", "cost")
.style("fill", function(d, i) { return colors[i]; });
var rect = groups.selectAll("rect")
.data(function(d) { return d; })
.enter()
.append("rect")
.attr("x", function(d) { return x(d.x); })
.attr("y", function(d) { return y(d.y0 + d.y); })
.attr("height", function(d) { return y(d.y0) - y(d.y0 + d.y); })
.attr("width", x.rangeBand())
.on("mouseover", function() { tooltip.style("display", null); })
.on("mouseout", function() { tooltip.style("display", "none"); })
.on("mousemove", function(d) {
var xPosition = d3.mouse(this)[0] - 15;
var yPosition = d3.mouse(this)[1] - 25;
tooltip.attr("transform", "translate(" + xPosition + "," + yPosition + ")");
tooltip.select("text").text(d.y);
});
// Draw legend
var legend = svg.selectAll(".legend")
.data(colors)
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(30," + i * 19 + ")"; });
legend.append("rect")
.attr("x", width - 18)
.attr("width", 18)
.attr("height", 18)
.style("fill", function(d, i) {return colors.slice().reverse()[i];});
legend.append("text")
.attr("x", width + 5)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "start")
.text(function(d, i) {
switch (i) {
case 0: return "Anjou pears";
case 1: return "Naval oranges";
case 2: return "McIntosh apples";
case 3: return "Red Delicious apples";
}
});
// Prep the tooltip bits, initial display is hidden
var tooltip = svg.append("g")
.attr("class", "tooltip")
.style("display", "none");
tooltip.append("rect")
.attr("width", 30)
.attr("height", 20)
.attr("fill", "white")
.style("opacity", 0.5);
tooltip.append("text")
.attr("x", 15)
.attr("dy", "1.2em")
.style("text-anchor", "middle")
.attr("font-size", "12px")
.attr("font-weight", "bold");

Cannot properly draw a scatterplot over a grouped bar chart in D3

I have a set of nested json data:
var data = [{"time":"2016-03-01","values":[{"specimen_count":1,"trap":"S0024", "species":1},{"specimen_count":2,"trap":"S0025", "species":2},{"specimen_count":2,"trap":"S0026", "species":2}]},{"time":"2016-03-15","values":[{"specimen_count":6,"trap":"S0024", "species":6},{"specimen_count":5,"trap":"S0025", "species":4},{"specimen_count":7,"trap":"S0026", "species":6}]}];
And I want to draw a set of grouped bar charts each group representing a time interval and each group with 3 bars, each representing a trap, and the height of the bar is the specimen_count field.
Now I want to add a scatterplot, one dot for each bar and the height of the dot is the species field, using the same scales. But I am having trouble successfully placing the dots on top the the grouped bar chart. I did manage to add a line with the species data, but I can't add the dots using the same logic.
Here is my code:
var margin = {top: 100, right: 20, bottom: 30, left: 40},
width = 600 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
var x0 = d3.scale.ordinal()
.rangeRoundBands([0, width], .1);
var x1 = d3.scale.ordinal();
var y = d3.scale.linear()
.range([height, 0]);
var xAxis = d3.svg.axis()
.scale(x0)
.tickSize(0)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left");
var color = d3.scale.ordinal()
.range(["#ca0020","#f4a582","#92c5de"]);
var svg = d3.select('#chart').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 categoriesNames = data.map(function(d) { return d.time; }); // the 5 time periods
var trapNames = data[0].values.map(function(d) { return d.trap; }); // the name of the traps
console.log(trapNames);
x0.domain(categoriesNames);
x1.domain(trapNames).rangeRoundBands([0, x0.rangeBand()]);
y.domain([0, d3.max(data, function(category) { return d3.max(category.values, function(d) { return d.specimen_count; }); })]);
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
svg.append("g")
.attr("class", "y axis")
.style('opacity','0')
.call(yAxis)
.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 6)
.attr("dy", ".71em")
.style("text-anchor", "end")
.style('font-weight','bold')
.text("Value");
svg.select('.y').transition().duration(500).delay(1300).style('opacity','1');
var slice = svg.selectAll(".slice")
.data(data)
.enter().append("g")
.attr("class", "slice")
.attr("transform",function(d) { return "translate(" + x0(d.time) + ",0)"; });
slice.selectAll("rect")
.data(function(d) { return d.values; })
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) { return x1(d.trap); })
.style("fill", function(d) { return color(d.trap) })
.attr("y", function(d) { return y(0); })
.attr("height", function(d) { return height - y(0); })
.on("mouseover", function(d) {
d3.select(this).style("fill", d3.rgb(color(d.trap)).darker(2));
})
.on("mouseout", function(d) {
d3.select(this).style("fill", color(d.trap));
});
slice.selectAll("rect")
.transition()
.delay(function (d) {return Math.random()*1000;})
.duration(1000)
.attr("y", function(d) { return y(d.specimen_count); })
.attr("height", function(d) { return height - y(d.specimen_count); });
var valueline = d3.svg.line()
.x(function (d) { return x1(d.trap) + x1.rangeBand()/2; })
.y(function (d) { return y(d.species); });
slice.enter()
.append('path')
.attr('class','line')
.style('stroke', "#0571b0")
.style('stroke-width', "3px")
.attr('fill', 'none')
.attr('d', function(d) { return valueline(d.values); });
slice.selectAll('.dot').data(data,function(d){return d.time;})
.enter()
.append("circle")
.attr("class", "dot")
.attr("r",5)
.attr("cx", function(d){
return x1(d.trap) + x1.rangeBand()/2;
})
.attr("cy",function(d){
return y(d.species);
})
.attr("fill","#0571b0");
There error I'm getting from the circle-related code is: d3.min.js:1 Error: attribute cx: Expected length, "NaN".
I think the nested data and the ordinal scale for the bar chart is throwing me off a bit, so it could be that I am not understanding fulling data access in these cases.
Also here is the screenshot of the current graph

If you need the dots on every bar chart, then the data() callback must return a list of bars not a single item. Did you try replacing it with:
slice.selectAll('.dot')
.data(function(d) {
return d.values;
})
.enter()
.append("circle") //... and so on
Doing this will use the existing data object (with 5 bar groups), but render a dot for each bar.
Here it is running:
<!DOCTYPE html>
<html>
<head>
<script data-require="d3#3.5.17" data-semver="3.5.17" src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.17/d3.js"></script>
</head>
<body>
<div id="chart"></div>
<script>
var data = [{
"time": "2016-03-01",
"values": [{
"specimen_count": 1,
"trap": "S0024",
"species": 1
}, {
"specimen_count": 2,
"trap": "S0025",
"species": 2
}, {
"specimen_count": 2,
"trap": "S0026",
"species": 2
}]
}, {
"time": "2016-03-15",
"values": [{
"specimen_count": 6,
"trap": "S0024",
"species": 6
}, {
"specimen_count": 5,
"trap": "S0025",
"species": 4
}, {
"specimen_count": 7,
"trap": "S0026",
"species": 6
}]
}];
var margin = {
top: 100,
right: 20,
bottom: 30,
left: 40
},
width = 600 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
var x0 = d3.scale.ordinal()
.rangeRoundBands([0, width], .1);
var x1 = d3.scale.ordinal();
var y = d3.scale.linear()
.range([height, 0]);
var xAxis = d3.svg.axis()
.scale(x0)
.tickSize(0)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left");
var color = d3.scale.ordinal()
.range(["#ca0020", "#f4a582", "#92c5de"]);
var svg = d3.select('#chart').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 categoriesNames = data.map(function(d) {
return d.time;
}); // the 5 time periods
var trapNames = data[0].values.map(function(d) {
return d.trap;
}); // the name of the traps
console.log(trapNames);
x0.domain(categoriesNames);
x1.domain(trapNames).rangeRoundBands([0, x0.rangeBand()]);
y.domain([0, d3.max(data, function(category) {
return d3.max(category.values, function(d) {
return d.specimen_count;
});
})]);
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
svg.append("g")
.attr("class", "y axis")
.style('opacity', '0')
.call(yAxis)
.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 6)
.attr("dy", ".71em")
.style("text-anchor", "end")
.style('font-weight', 'bold')
.text("Value");
svg.select('.y').transition().duration(500).delay(1300).style('opacity', '1');
var slice = svg.selectAll(".slice")
.data(data)
.enter().append("g")
.attr("class", "slice")
.attr("transform", function(d) {
return "translate(" + x0(d.time) + ",0)";
});
slice.selectAll("rect")
.data(function(d) {
return d.values;
})
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) {
return x1(d.trap);
})
.style("fill", function(d) {
return color(d.trap)
})
.attr("y", function(d) {
return y(0);
})
.attr("height", function(d) {
return height - y(0);
})
.on("mouseover", function(d) {
d3.select(this).style("fill", d3.rgb(color(d.trap)).darker(2));
})
.on("mouseout", function(d) {
d3.select(this).style("fill", color(d.trap));
});
slice.selectAll("rect")
.transition()
.delay(function(d) {
return Math.random() * 1000;
})
.duration(1000)
.attr("y", function(d) {
return y(d.specimen_count);
})
.attr("height", function(d) {
return height - y(d.specimen_count);
});
var valueline = d3.svg.line()
.x(function(d) {
return x1(d.trap) + x1.rangeBand() / 2;
})
.y(function(d) {
return y(d.species);
});
slice
.append('path')
.attr('class', 'line')
.style('stroke', "#0571b0")
.style('stroke-width', "3px")
.attr('fill', 'none')
.attr('d', function(d) {
return valueline(d.values);
});
slice.selectAll('.dot').data(function(d) {
return d.values;
})
.enter()
.append("circle")
.attr("class", "dot")
.attr("r", 5)
.attr("cx", function(d) {
return x1(d.trap) + x1.rangeBand() / 2;
})
.attr("cy", function(d) {
return y(d.species);
})
.attr("fill", "#0571b0");
</script>
</body>
</html>

D3.js transitions between charts

I am trying to create a transition in my bar chart code, that would allow the user to click on a particular and be shown a different set of data related to that bar.
This is a sample dataset:
module_category,component_category,date_repair,actual,predicted
M1,P06,2009/01,39,63
M1,P06,2009/10,3,4
M1,P06,2009/11,4,3
M1,P06,2009/12,4,2
M1,P06,2009/02,29,45
M1,P06,2009/03,29,32
M1,P06,2009/04,10,22
M1,P06,2009/05,13,15
M1,P06,2009/06,9,16
M1,P06,2009/07,7,12
The full dataset can be found here: full dataset
So based on my current code I can create this bar chart:
but now I want to add interactivity that will allow the user after clicking on the bar for e.g "M2", they graph then updates to show the components from the "component_category" related to that module with the respective "actual" and "predicted" values shown as bar charts also.
This is my current code:
var margin = {top: 20, right: 90, bottom: 30, left: 60},
width = 980 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
var x0 = d3.scale.ordinal()
.rangeRoundBands([0, width], .1);
var x1 = d3.scale.ordinal();
var y = d3.scale.linear()
.range([height, 0]);
var color = d3.scale.category10();
var xAxis = d3.svg.axis()
.scale(x0)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.tickFormat(d3.format(".2s"));
var svg = d3.select("#maincontent").append("svg")
.attr('id','chart')
.attr('viewBox', '0 0 980 500')
.attr('perserveAspectRatio', 'xMinYMid')
.attr('width', width + margin.right + margin.left)
.attr('height', height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
var tip=d3.tip()
.attr("class","d3-tip")
.offset([-10, 0])
.html(function(d) { return "No. of repairs: " + d.value; });
d3.csv("data/Consolidated_result.csv", function(error, data) {
if (error) throw error;
data = d3.nest()
.key(function(d) { return d.module_category;}).sortKeys(d3.ascending)
.rollup(function(values){
var counts = {}, keys = ['actual', 'predicted']
keys.forEach(function(key){
counts[key] = d3.sum(values, function(d){ return d[key]})
})
return counts
})
.entries(data);
console.log(data);
x0.domain(data.map(function(d) { return d.key; }));
x1.domain(['actual','predicted']).rangeRoundBands([0, x0.rangeBand()]);
// store all the values in an array
var yval = [];
data.forEach(function(d){
yval.push(d.values.actual);
yval.push(d.values.predicted);
});
y.domain([0, d3.max(yval)]);
svg.call(tip);
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", 0 - margin.left)
.attr("x", 0 - (height / 2))
.attr("dy", "1em")
.style("text-anchor", "middle")
.text("Number of Repairs");
var module = svg.selectAll(".module")
.data(data)
.enter().append("g")
.attr("class", "g")
.attr("transform", function(d) { return "translate(" + x0(d.key) + ",0)"; });
module.selectAll("rect")
.data(function(d){
var ary = [];
ary.push({name:"actual", value:d.values.actual});
ary.push({name:'predicted', value: d.values.predicted});
return ary;
})
.enter().append("rect")
.on('mouseover', tip.show)
.on('mouseout', tip.hide)
.on("click", function(d){
d3.select("svg")
.style("opacity",0)
.remove()
tip.hide()
setTimeout(componentgroupedchart, 1000);
})
/*
.on("click", function(d){
d3.select(this)
setTimeout(updateChart(name), 500);
})*/
.attr("width", x1.rangeBand())
.attr("x", function(d) { return x1(d.name); })
.attr("y", function(d) { return y(d.value); })
.attr("height", function(d) { return height - y(d.value); })
.style("fill", function(d) { return color(d.name); });
var legend = svg.selectAll(".legend")
.data(['actual','predicted'])
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
legend.append("rect")
.attr("x", width - 18)
.attr("width", 18)
.attr("height", 18)
.style("fill", function(d){
return color(d)
});
legend.append("text")
.attr("x", width - 24)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) { return d; });
});
What I want to implement will be to create a function where i update the chart and reload the data and nest it to this:
data = d3.nest()
.key(function(d) { return d.module_category;}).sortKeys(d3.ascending)
.key(function(d) { return d.component_category;}).sortKeys(d3.ascending)
.rollup(function(values){
var counts = {}, keys = ['actual', 'predicted']
keys.forEach(function(key){
counts[key] = d3.sum(values, function(d){ return d[key]})
})
return counts
})
.entries(data);
This is so that I can access for each module:
the number of component related to that module &
the actual and predicted repair values
The resulting data then becomes:
var data = [{
key: "M1"
values: {
key: "P06"
values: {
actual: 156 ,
predicted: 228
},
key: "P09"
values: {
actual: 31,
predicted: 20
},
key: "P12"
values: {
actual: 140,
predicted: 176
},
key: "P15"
values: {
actual: 38,
predicted: 40
},
key: "P16"
values: {
actual: 112,
predicted:113
},
key: "P17"
values: {
actual: 20 ,
predicted: 7
},
key: "P20"
values: {
actual: 98,
predicted: 127
},
key: "P28"
values: {
actual: 143 ,
predicted: 149
},
key: "P30"
values: {
actual: 16,
predicted: 38
}
},
key: "M5"
values: {
key: "P06"
values: {
actual: 61 ,
predicted: 65
},
key: "P09"
values: {
actual: 83,
predicted: 82
},
key: "P12"
values: {
actual: 45,
predicted: 58
},
key: "P15"
values: {
actual: 26,
predicted: 31
},
key: "P16"
values: {
actual: 152,
predicted:174
},
key: "P21"
values: {
actual: 74 ,
predicted: 120
}
}
}]
From this new data, the chart then transitions to a new bar chart display that shows the components and their repair values based on the selected module. I hope the question is much clearer now.

This can be achieved by making one function for making module graph, another for making the drill down category graph. Define the domain with in the functions, since the y axis domain x axis domain will change with with the module/category graph.
I have added comments in the code; in case you have any issues, feel free to ask.
var margin = {
top: 20,
right: 90,
bottom: 30,
left: 60
},
width = 980 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
var x0 = d3.scale.ordinal()
.rangeRoundBands([0, width], .1);
var x1 = d3.scale.ordinal();
var y = d3.scale.linear()
.range([height, 0]);
var color = d3.scale.category10();
var xAxis = d3.svg.axis()
.scale(x0)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.tickFormat(d3.format(".2s"));
var svg = d3.select("body").append("svg")
.attr('width', width + margin.right + margin.left)
.attr('height', height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
var tip = d3.tip()
.attr("class", "d3-tip")
.offset([-10, 0])
.html(function(d) {
return "No. of repairs: " + d.value;
});
d3.csv("my.csv", function(error, data) {
if (error) throw error;
fullData = data;
data = d3.nest()
.key(function(d) {
return d.module_category;
})
.rollup(function(values) {
var counts = {},
keys = ['actual', 'predicted']
keys.forEach(function(key) {
counts[key] = d3.sum(values, function(d) {
return d[key];
})
})
return counts
})
.entries(data);
//make the x axis
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
//make the y axis
svg.append("g")
.attr("class", "y axis")
.call(yAxis)
.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 0 - margin.left)
.attr("x", 0 - (height / 2))
.attr("dy", "1em")
.style("text-anchor", "middle")
.text("Number of Repairs");
makeModuleGraph(data)
var legend = svg.selectAll(".legend")
.data(['actual', 'predicted'])
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) {
return "translate(0," + i * 20 + ")";
});
legend.append("rect")
.attr("x", width - 18)
.attr("width", 18)
.attr("height", 18)
.style("fill", function(d) {
return color(d);
});
legend.append("text")
.attr("x", width - 24)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) {
return d;
});
});
function makeModuleGraph(data) {
var yval = [];
data.forEach(function(d) {
yval.push(d.values.actual);
yval.push(d.values.predicted);
});
x0.domain(data.map(function(d) {
return d.key;
}));
x1.domain(['actual', 'predicted']).rangeRoundBands([0, x0.rangeBand()]);
y.domain([0, d3.max(yval)]);
svg.call(tip);
svg.selectAll("g .x")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
svg.selectAll("g .y")
.attr("class", "y axis")
.call(yAxis);
var module = svg.selectAll(".module")
.data(data)
.enter().append("g")
.attr("class", "module")
.attr("transform", function(d) {
return "translate(" + x0(d.key) + ",0)";
});
module.selectAll("rect")
.data(function(d) {
var ary = [];
ary.push({
name: "actual",
value: d.values.actual,
key: d.key
});
ary.push({
name: "predicted",
value: d.values.predicted,
key: d.key
});
return ary;
})
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) {
return x1(d.name);
})
.attr("y", function(d) {
return y(d.value);
})
.attr("height", function(d) {
return height - y(d.value);
})
.style("fill", function(d) {
return color(d.name);
}).on("click", function(d) {
makeComponentCategoryGraph(d);//make the graph for category
});
}
function makeComponentCategoryGraph(d){
var filtered = fullData.filter(function(k){ if(d.key == k.module_category){return true;}else {return false;}})
var data = d3.nest()
.key(function(d) {
return d.component_category;
})
.rollup(function(values) {
var counts = {},
keys = ['actual', 'predicted']
keys.forEach(function(key) {
counts[key] = d3.sum(values, function(d) {
return d[key];
})
})
return counts
})
.entries(filtered);
var yval = [];
data.forEach(function(d) {
yval.push(d.values.actual);
yval.push(d.values.predicted);
});
x0.domain(data.map(function(d) {
return d.key;
}));
x1.domain(['actual', 'predicted']).rangeRoundBands([0, x0.rangeBand()]);
y.domain([0, d3.max(yval)]);
svg.call(tip);
svg.selectAll("g .x")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
svg.selectAll("g .y")
.attr("class", "y axis")
.call(yAxis);
svg.selectAll(".module").remove();//remove alll the bar graphs
var module = svg.selectAll(".module")
.data(data)
.enter().append("g")
.attr("class", "module")
.attr("transform", function(d) {
return "translate(" + x0(d.key) + ",0)";
});
module.selectAll("rect")
.data(function(d) {
var ary = [];
ary.push({
name: "actual",
value: d.values.actual,
key: d.key
});
ary.push({
name: "predicted",
value: d.values.predicted,
key: d.key
});
return ary;
})
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) {
return x1(d.name);
})
.attr("y", function(d) {
return y(d.value);
})
.attr("height", function(d) {
return height - y(d.value);
})
.style("fill", function(d) {
return color(d.name);
})
}
Working code here.

how to align y axis label in D3

i am trying to create a stacked bar graph.
however i can't seem to get the alignment right.the graph has two axis.
because of the length of the y axis label it is partially blocked.
i tried solving this by using different CSS styles on the label and on the enclosing div,
but they did not have the desired affect.
i created a jsfidel to explain my case.
http://jsfiddle.net/2khbceut/1/
HTML
<title>Diverging Stacked Bar Chart with D3.js</title>
<body>
<div id="figure" align="center" style="margin-bottom: 50px;"></div>
</body>
javascript
$(document).ready(getTopolegy());
function getTopolegy(){
var data = null;
var links = parseTopology(data);
createChart(links);
}
function parseTopology(data){
var links=[{1:5,2:5,3:10,N:20,link_name: "Link 167772376>>167772375"}];
return links;
}
function jsonNameToId(name){
switch (allocated_priority) {
case "allocated_priority":
return 1;
case "allocated_default":
return 2;
case "spare_capacity":
return 3;
case "total":
return "N";
default:
return 999;
}
}
function createChart(data){
var margin = {top: 50, right: 20, bottom: 10, left: 65},
width = 1000 - margin.left - margin.right,
height = 1000 - margin.top - margin.bottom;
var y = d3.scale.ordinal()
.rangeRoundBands([0, height], .3);
var x = d3.scale.linear()
.rangeRound([0, width]);
var color = d3.scale.ordinal()
.range(["#cccccc", "#92c6db", "#086fad"]);
var xAxis = d3.svg.axis()
.scale(x)
.orient("top");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
var svg = d3.select("#figure").append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.attr("id", "d3-plot")
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
color.domain(["Allocated Priority %", "Allocated Default %", "Spare Capacity %"]);
// d3.csv("js/raw_data.csv", function(error, data) {
data.forEach(function(d) {
d["Allocated Priority %"] = +d[1]*100/d.N;
d["Allocated Default %"] = +d[2]*100/d.N;
d["Spare Capacity %"] = +d[3]*100/d.N;
var x0 = 0;
var idx = 0;
d.boxes = color.domain().map(function(name) { return {name: name, x0: x0, x1: x0 += +d[name], N: +d.N, n: +d[idx += 1]}; });
});
var min_val = d3.min(data, function(d) {
return d.boxes["0"].x0;
});
var max_val = d3.max(data, function(d) {
return d.boxes["2"].x1;
});
x.domain([min_val, max_val]).nice();
y.domain(data.map(function(d) { return d.link_name; }));
svg.append("g")
.attr("class", "x axis")
.call(xAxis);
svg.append("g")
.attr("class", "y axis")
.call(yAxis)
var vakken = svg.selectAll(".Link")
.data(data)
.enter().append("g")
.attr("class", "bar")
.attr("transform", function(d) { return "translate(0," + y(d.link_name) + ")"; });
var bars = vakken.selectAll("rect")
.data(function(d) { return d.boxes; })
.enter().append("g").attr("class", "subbar");
bars.append("rect")
.attr("height", y.rangeBand())
.attr("x", function(d) { return x(d.x0); })
.attr("width", function(d) { return x(d.x1) - x(d.x0); })
.style("fill", function(d) { return color(d.name); });
bars.append("text")
.attr("x", function(d) { return x(d.x0); })
.attr("y", y.rangeBand()/2)
.attr("dy", "0.5em")
.attr("dx", "0.5em")
.style("font" ,"10px sans-serif")
.style("text-anchor", "begin")
.text(function(d) { return d.n !== 0 && (d.x1-d.x0)>3 ? d.n : "" });
vakken.insert("rect",":first-child")
.attr("height", y.rangeBand())
.attr("x", "1")
.attr("width", width)
.attr("fill-opacity", "0.5")
.style("fill", "#F5F5F5")
.attr("class", function(d,index) { return index%2==0 ? "even" : "uneven"; });
svg.append("g")
.attr("class", "y axis")
.append("line")
.attr("x1", x(0))
.attr("x2", x(0))
.attr("y2", height);
var startp = svg.append("g").attr("class", "legendbox").attr("id", "mylegendbox");
// this is not nice, we should calculate the bounding box and use that
var legend_tabs = [0, 150, 300];
var legend = startp.selectAll(".legend")
.data(color.domain().slice())
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(" + legend_tabs[i] + ",-45)"; });
legend.append("rect")
.attr("x", 0)
.attr("width", 18)
.attr("height", 18)
.style("fill", color);
legend.append("text")
.attr("x", 22)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "begin")
.style("font" ,"10px sans-serif")
.text(function(d) { return d; });
d3.selectAll(".axis path")
.style("fill", "none")
.style("stroke", "#000")
.style("shape-rendering", "crispEdges")
d3.selectAll(".axis line")
.style("fill", "none")
.style("stroke", "#000")
.style("shape-rendering", "crispEdges")
var movesize = width/2 - startp.node().getBBox().width/2;
d3.selectAll(".legendbox").attr("transform", "translate(" + movesize + ",0)");
// });
}
i will appreciate any insight you have on this matter.

How do I dynamically update my grouped bar chart using d3js?

I have successfully managed to create a grouped bar chart that displays the various performance stats for soccer players over the course of one season. This data is all loaded from a csv file. I would now like to dynamically change that data whereby when a button is pressed, a new csv file is loaded with the stats corresponding to the next soccer season. I've tried to do this on my own but everytime I try reload the data, the old data as well as the old axis's remain present and the enw data loads ontop of these. It all ends up looking messy. So how do I have the old bars and axises updated in line with the new data? Here is my code:
$(document).ready(function(){
var margin = {top: 20, right: 20, bottom: 30, left: 40},
width = 960 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
var x0 = d3.scale.ordinal()
.rangeRoundBands([0, width], .1);
var x1 = d3.scale.ordinal();
var y = d3.scale.linear()
.range([height, 0]);
var color = d3.scale.ordinal()
.range(["#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]);
var xAxis = d3.svg.axis()
.scale(x0)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.tickFormat(d3.format(".2s"));
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 + ")");
d3.csv("SoccerStatsCSV.csv", function(error, data) {
console.log(data);
var playerNames = d3.keys(data[0]).filter(function(key) { return key !== "Attribute"; });
console.log(playerNames);
data.forEach(function(d) {
d.Playerstats = playerNames.map(function(name) { return {name: name, value: +d[name]}; });
console.log(d.Playerstats);
});
x0.domain(data.map(function(d) { return d.Attribute; }));
x1.domain(playerNames).rangeRoundBands([0, x0.rangeBand()]);
y.domain([0, d3.max(data, function(d) { return d3.max(d.Playerstats, function(d) { return d.value; }); })]);
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("Units");
var state = svg.selectAll(".state")
.data(data)
.enter().append("g")
.attr("class", "g")
.attr("transform", function(d) { return "translate(" + x0(d.Attribute) + ",0)"; });
state.selectAll("rect")
.data(function(d) { return d.Playerstats; })
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) { return x1(d.name); })
.attr("y", function(d) { return y(d.value); })
.attr("height", function(d) { return height - y(d.value); })
.style("fill", function(d) { return color(d.name); });
var legend = svg.selectAll(".legend")
.data(playerNames.slice())
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
legend.append("rect")
.attr("x", width - 18)
.attr("width", 18)
.attr("height", 18)
.style("fill", color);
legend.append("text")
.attr("x", width - 24)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) { return d; });
});
//The updating button
d3.select("button")
.on('click',function(){
d3.csv("SoccerStatsCSV2008.csv", function(error, data) {
console.log(data);
var playerNames = d3.keys(data[0]).filter(function(key) { return key !== "Attribute"; });
console.log(playerNames);
data.forEach(function(d) {
d.Playerstats = playerNames.map(function(name) { return {name: name, value: +d[name]}; });
console.log(d.Playerstats);
});
x0.domain(data.map(function(d) { return d.Attribute; }));
x1.domain(playerNames).rangeRoundBands([0, x0.rangeBand()]);
y.domain([0, d3.max(data, function(d) { return d3.max(d.Playerstats, function(d) { return d.value; }); })]);
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("Units");
var state = svg.selectAll(".state")
.data(data)
.enter().append("g")
.attr("class", "g")
.attr("transform", function(d) { return "translate(" + x0(d.Attribute) + ",0)"; });
state.selectAll("rect")
.data(function(d) { return d.Playerstats; })
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) { return x1(d.name); })
.attr("y", function(d) { return y(d.value); })
.attr("height", function(d) { return height - y(d.value); })
.style("fill", function(d) { return color(d.name); });
var legend = svg.selectAll(".legend")
.data(playerNames.slice())
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
legend.append("rect")
.attr("x", width - 18)
.attr("width", 18)
.attr("height", 18)
.style("fill", color);
legend.append("text")
.attr("x", width - 24)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) { return d; });
});
});
});