Taking Rickshaw for a Go
Rickshaw is a simple framework for drawing charts of time series data on a web page, built on top of Mike Bostock's delightful D3 library. These charts can be powered by static historical data sets, or living data that continuously updates in real time.
Rickshaw builds on top of D3 technically, and spiritually too. Rickshaw makes every effort to provide help for common problems without obscuring anything underneath it. If you need to reach down to D3 or the SVG layers below, go right ahead -- it's all there waiting.
Let's start with a simple but complete program that paints a chart:
Breaking that down, first we pull in our dependencies and create
a div to hold our chart. Then in our
Rickshaw.Graph's constructor, and pass along an
element reference to our chart container, some layout instructions,
and a series of data objects.
series object has a couple of slots,
data array of coordinate objects, and a color to draw
them with. Finally, we call the render() method on our just instantiated
graph object, which creates paints our chart on the screen.
Let's Try with Real Data
Our previous work allowed us to paint a chart of made up values with minimal scaffolding. That was fun, but it doesn't tell us anything interesting about data. Let's use population change data from the 2010 U.S. Census to power our chart, and see what we find.
We'll begin by drawing a line representing the United States
population with a point for each decade from 1910 to 2010. We'll use
a short script we've written to massage the
Rickshaw.Graph's constructor can take as
Time on the X-Axis
A trained eye can already see some points of interest there. For instance, ending about a quarter way into the graph there is a short period where the growth rate flattens out significantly. What happened then?
First we have to answer the question of when the flattening happened.
Putting a label on our x axis should help. Rickshaw gives us a helper
for time based axes. After we modify our data transformation script
to use epoch seconds for the
x values we can pass our
graph along to
When the graph's
render() function is later called
Rickshaw examines the
x domain and determines the time
unit being used, and labels the graph accordingly. The styling we
included lines up the labels nicely across the bottom of our graph.
Our updated transform_epoch.pl uses epoch
x. Let's see how we do.
Now let's add the pieces to get a
y axis. We need a new
HTML element to put the
y axis in, as well as some
styling to position the axis absolutely in relation to the chart.
We pass along a reference to our graph to
Rickshaw.Graph.Axis.Y's constructor, as well as the
element we want to draw the axis inside. We also ask
Rickshaw.Fixtures.Number.formatKMBT to help us format the
numbers on our
y ticks in there.
Breaking Things Down
The Great Depression left a mark. We should break that data down by region. Some simple changes to our data transformation gives us the regional data for our series. Here's transform_region.pl.
Plugging that data into our series parameter leaves us wanting to
provide colors for each of those individual series. We'll use the
Rickshaw.Color.Palette plugin to pick our colors. Once
we've created our palette, calling its
returns the next color.
What Are We Looking At?
We need a legend! Following a familiar pattern, we add a container
div for the legend and style it. Then we call the constructor for the
Rickshaw.Graph.Legend plugin, which takes a reference to
our newly added DOM element, and a reference to the graph.
It's clear that the South is growing quickly, but instead of painting this chart as a stacked graph it would be nice to see how these growth patterns line up against each other. We set the renderer in a callback, and then ask the graph to update.
We're just getting started, but that's all for today. Next time we'll get into stacked bars, and different line interpolations, and smoothing, and zooming.
If you're clamoring for more, you may enjoy a poke around in the examples directory.