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05_click_transition.html
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05_click_transition.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>D3: Click to transition</title>
<script type="text/javascript" src="../d3.js"></script>
<style type="text/css">
h1 {
font-family: Helvetica, sans-serif;
font-size: 14px;
font-weight: bold;
}
.area {
stroke: none;
}
.area:hover {
fill: yellow;
}
</style>
</head>
<body>
<h1>Monthly Number of Electric-Drive Vehicles Sold in the U.S. (by Type): January 2005–Feburary 2017</h1>
<script type="text/javascript">
//Width and height
var w = 1400;
var h = 300;
var padding = 20;
var dataset, xScale, yScale, xAxis, yAxis, area; //Empty, for now
//For converting strings to Dates
var parseTime = d3.timeParse("%Y-%m");
//For converting Dates to strings
var formatTime = d3.timeFormat("%b %Y");
//Define key function, to be used when binding data
var key = function(d) {
return d.key;
};
//Set up stack methods
var vehicleStack = d3.stack();
var typeStack = d3.stack();
//Load in data
d3.request("vehicle_sales_data.csv")
.mimeType("text/csv")
.get(function(response) {
//
// DATA PARSING
//
//Parse each row of the CSV into an array of string values
var rows = d3.csvParseRows(response.responseText);
// console.log(rows);
//Make dataset an empty array, so we can start adding values
dataset = [];
//Loop once for each row of the CSV, starting at row 3,
//since rows 0-2 contain only vehicle info, not sales values.
for (var i = 3; i < rows.length; i++) {
//Create a new object
dataset[i - 3] = {
date: parseTime(rows[i][0]) //Make a new Date object for each year + month
};
//Loop once for each vehicle in this row (i.e., for this date)
for (var j = 1; j < rows[i].length; j++) {
var make = rows[0][j]; //'Make' from 1st row in CSV
var model = rows[1][j]; //'Model' from 2nd row in CSV
var makeModel = rows[0][j] + " " + rows[1][j]; //'Make' + 'Model' will serve as our key
var type = rows[2][j]; //'Type' from 3rd row in CSV
var sales = rows[i][j]; //Sales value for this vehicle and month
//If sales value exists…
if (sales) {
sales = parseInt(sales); //Convert from string to int
} else { //Otherwise…
sales = 0; //Set to zero
}
//Append a new object with data for this vehicle and month
dataset[i - 3][makeModel] = {
"make": make,
"model": model,
"type": type,
"sales": sales
};
}
}
//Log out the final state of dataset
// console.log(dataset);
//
// STACKING
//
//Now that we know the column names in the data,
//get all the keys (make + model), but toss out 'date'
var keys = Object.keys(dataset[0]).slice(1);
// console.log(keys);
//Tell stack function where to find the keys
vehicleStack.keys(keys)
.value(function value(d, key) {
return d[key].sales;
});
//Stack the data and log it out
var vehicleSeries = vehicleStack(dataset);
// console.log(vehicleSeries);
//
// TYPE DATA SERIES
//
//The goal here is to make a totally separate data set that
//includes just monthly totals for each `type` (HEV, PHEV, BEV, FCEV).
//Make typeDataset an empty array, so we can start adding values
typeDataset = [];
//Loop once for each row of the CSV, starting at row 3,
//since rows 0-2 contain only vehicle info, not sales values.
for (var i = 3; i < rows.length; i++) {
//Create a new object
typeDataset[i - 3] = {
date: parseTime(rows[i][0]), //Make a new Date object for each year + month
"HEV": 0,
"PHEV": 0,
"BEV": 0,
"FCEV": 0
};
//Loop once for each vehicle in this row (i.e., for this date)
for (var j = 1; j < rows[i].length; j++) {
var type = rows[2][j]; //'Type' from 3rd row in CSV
var sales = rows[i][j]; //Sales value for this vehicle and month
//If sales value exists…
if (sales) {
sales = parseInt(sales); //Convert from string to int
} else { //Otherwise…
sales = 0; //Set to zero
}
//Add sales value to existing sum
typeDataset[i - 3][type] += sales;
}
}
//Log out the final state of dataset
// console.log(typeDataset);
//
// STACKING
//
//Tell stack function where to find the keys
typeStack.keys([ "HEV", "PHEV", "BEV", "FCEV" ]);
//Stack the data and log it out
var typeSeries = typeStack(typeDataset);
// console.log(typeSeries);
//
// MAKE THE CHART
//
//Create scale functions
xScale = d3.scaleTime()
.domain([
d3.min(dataset, function(d) { return d.date; }),
d3.max(dataset, function(d) { return d.date; })
])
.range([padding, w - padding * 2]);
yScale = d3.scaleLinear()
.domain([
0,
d3.max(dataset, function(d) {
var sum = 0;
//Loops once for each row, to calculate
//the total (sum) of sales of all vehicles
for (var i = 0; i < keys.length; i++) {
sum += d[keys[i]].sales;
};
return sum;
})
])
.range([h - padding, padding / 2])
.nice();
//Define axes
xAxis = d3.axisBottom()
.scale(xScale)
.ticks(10)
.tickFormat(formatTime);
//Define Y axis
yAxis = d3.axisRight()
.scale(yScale)
.ticks(5);
//Define area generator
area = d3.area()
.x(function(d) { return xScale(d.data.date); })
.y0(function(d) { return yScale(d[0]); })
.y1(function(d) { return yScale(d[1]); });
//Create SVG element
var svg = d3.select("body")
.append("svg")
.attr("width", w)
.attr("height", h);
//Create areas for individual VEHICLES
svg.append("g")
.attr("id", "vehicles")
.selectAll("path")
.data(vehicleSeries, key)
.enter()
.append("path")
.attr("class", "area")
.attr("d", area)
.attr("fill", function(d) {
//Which vehicle is this?
var thisKey = d.key;
//What 'type' is this vehicle?
var thisType = d[0].data[thisKey].type;
// console.log(thisType);
//New color var
var color;
switch (thisType) {
case "HEV":
color = d3.schemeCategory20[0];
break;
case "PHEV":
color = d3.schemeCategory20[1];
break;
case "BEV":
color = d3.schemeCategory20[2];
break;
case "FCEV":
color = d3.schemeCategory20[3];
break;
}
return color;
})
.append("title") //Make tooltip
.text(function(d) {
return d.key;
});
//Create areas for TYPES
svg.append("g")
.attr("id", "types")
.selectAll("path")
.data(typeSeries, key)
.enter()
.append("path")
.attr("class", "area")
.attr("d", area)
.attr("fill", function(d) {
//Which type is this?
var thisType = d.key;
//New color var
var color;
switch (thisType) {
case "HEV":
color = "rgb(110, 64, 170)";
break;
case "PHEV":
color = "rgb(76, 110, 219)";
break;
case "BEV":
color = "rgb(35, 171, 216)";
break;
case "FCEV":
color = "rgb(29, 223, 163)";
break;
}
return color;
})
.on("click", function(d) {
//Which type was clicked?
var thisType = d.key;
//Generate a new data set with all-zero values,
//except for this type's data
var thisTypeDataset = [];
for (var i = 0; i < typeDataset.length; i++) {
thisTypeDataset[i] = {
date: typeDataset[i].date,
HEV: 0,
PHEV: 0,
BEV: 0,
FCEV: 0,
[thisType]: typeDataset[i][thisType] //Overwrites the appropriate zero value above
}
}
// console.log(thisTypeDataset);
//Stack the data (even though there's now just one "layer") and log it out
var thisTypeSeries = typeStack(thisTypeDataset);
// console.log(thisTypeSeries);
//Bind the new data set to paths, overwriting old bound data.
var paths = d3.selectAll("#types path")
.data(thisTypeSeries, key);
//Transition areas into new positions (i.e., thisType's area
//will go to a zero baseline; all others will flatten out).
//
//Store this transition in a new variable for later reference.
var areaTransitions = paths.transition()
.duration(1000)
.attr("d", area);
//Update scale
yScale.domain([
0,
d3.max(thisTypeDataset, function(d) {
var sum = 0;
//Calculate the total (sum) of sales of this type,
//ignoring the others (for now)
sum += d[thisType];
return sum;
})
]);
//Append this transition to the one already in progress
//(from above). Transition areas to newly updated scale.
areaTransitions.transition()
.delay(200)
.duration(1000)
.attr("d", area);
})
.append("title") //Make tooltip
.text(function(d) {
return d.key;
});
//Create axes
svg.append("g")
.attr("class", "axis x")
.attr("transform", "translate(0," + (h - padding) + ")")
.call(xAxis);
svg.append("g")
.attr("class", "axis y")
.attr("transform", "translate(" + (w - padding * 2) + ",0)")
.call(yAxis);
});
</script>
</body>
</html>