00:00 For this example, we're going to be plotting stock data. We have a data.json file where we've got an array of objects where each object has a ticker property and a values array. That values array has objects in it with a close property and a date property. The date that the stock closed at whatever price.
00:20 We've got Amazon here, and we also have Google. Our data runs from September 30th of 2016 to July 1st of 2016. If we come over here to our app code, we can see that we've got the shell set up here. We've got to call it a D3.json to load that file.
00:39 Now we can go ahead and just get into the business of creating our chart from that data. The first thing we're going to do is create a function that will parse the date strings that we have. We're dealing with four-digit year/two-digit month/two-digit day. We can create a parsing function for that using the D3.time parse method.
01:01 Capital Y/M/D is the format that maps to the data that we have in our JSON file. Now we have a function called parse time that we'll be able to use to parse our data. Now that we have that set up, we can iterate over our data and make sure that everything is converted to the right format that we need. First, we'll iterate over the base array and get each company object out.
01:28 We'll iterate over each of the value objects for the company. We'll use our parse time function to parse the date. Then we're just going to make sure that close is actually a number. We'll do that here as well.
01:41 Now that our data's parsed, we can go ahead and create our scales. Since we're going to be plotting the dates along the X axis, we're going to create a time scale with D3.scaletime.
01:51 For our domain, we need to do a little bit of work here to dig in and get these values from the second level down. We're going to call D3.min and then pass in the data array, but once we get each of those company objects out, we need to do an additional call to D3.min and pass in that array of values and tell it to look at the date property on each of these objects.
02:16 The second number in our domain is going to be the same exact logic, but we're going to find the max value instead of the min. There's our domain. We'll set our range to be from zero to the width of our chart.
02:28 Now that our X scale is created, we can go ahead and call SVG.appendg. You always want to have a fresh graphics container for your axes. We'll call the attribute method to set the transform attribute and give that a call to translate, to move it down by the height of our chart so that our X axis is at the bottom. Finally, we'll do .call and pass in D3.axisbutton and then pass in our X scale to that.
02:57 We're creating a bottom oriented X axis using our X scale and setting it at the bottom of the chart.
03:04 If we save this, we see that we do in fact have a X axis that runs roughly from the beginning of July, it looks like July 3rd is the first date there, to September 25th. You can see we have a little bit of overlap. Maybe we want to add some directives here on how many ticks that the scale should have. Let's try doing let's say 10 ticks. That's still too many.
03:30 Maybe five? OK. Not a lot of precision in our X axis, but that's OK for now. We're not really going to be worried about specific date things lining up.
03:42 We can move on to our Y scale. Our Y scale is just going to be a linear scale. We'll just say Y scale equals D3.scalelinear. We need to do the same work that we did for our X scale in order to find the minimum, the maximum values. I'm just going to grab this code from up here, paste it down here.
04:01 This time the difference is instead of looking at the date property on these, we're going to be looking at the close property. We'll just update these. Then the rest of that code can actually stay the same.
04:13 For our range, we're again going to set our height as the beginning value and zero as the second so that we have that inverted relationship so that on our chart, larger values are shown closer to the top of the page which actually maps to smaller Y values in an SVG context.
04:33 With the scale created, we can again do essentially the same thing we did before where we call SVG.append, create a fresh graphics container. This time we don't even need to translate it since it's going to at the top left. We'll just say .call. Then we'll call D3 axis left to create a left oriented axis. We'll pass in our Y scale.
04:56 If we save that, we can see that now we have our Y axis in place which runs from a little bit less than 700 to say maybe 850, 860, something like that.
05:08 Now that we have parsed our data and pulled the values out that we need to create our axes, let's look at how we actually create the lines for our line chart. We're going to come down here. We're going to create a variable named line. We're going to set that by calling D3.line. Then the line generator function that we're creating here, we have to tell it how to get its X and Y properties.
05:35 The first thing we're going to do is call the .X method. In this case, it's going to of course pass in our datums. We're just going to return the X scale's translated value for the date property. You can probably guess how the Y's going to work. That's going to be the exact same way except we're going to call our Y scale and use the close property.
06:01 We have our line generator created, but we need to see how we actually add that visually to the chart. We're first going to say SVG.selectall. We're going to use a CSS class selector here so everything with the class of line, we're going to do our data join and give it the whole data array.
06:21 Again tell it what to do with our inter-selection which is we want it to append a path element. We're going to give those path elements that line class that we used before.
06:32 Now that the objects are being created, we need to tell it how to actually draw the line. To do that, we use the D attribute. For the D attribute, we're going to have a callback function here. We're going to use that line function that we created above, and we're going to pass it our values array.
06:52 We created the line up here, told it which property to use for its X property and which to use for Y, and so here, we're just passing in that values array which is filled with these objects that have the date and closed properties on them.
07:09 The code that we have so far tells D3 how to draw these lines and which values to use. Now we just need to add a couple of styles so that everything shows up properly. The first style that we're going to set is the stroke style. I'm actually going to paste in some code here which has a couple of colors already defined in it.
07:28 This is essentially Amazon orange, and this is Google blue. We're telling it when you plot the first set, use this color. When you plot the second line, use this color because we're just using that index property there of I.
07:45 We're also going to set the stroke width because by default it's one which is kind of thin and can get a little bit anti-aliased and look a little bit bad. That's it. If we save this now, we should get a line chart.
07:57 In fact, we do, but it looks a little bit crazy because these path objects are actually being filled. What we need to do is come back here and set the fill to none. Once we do that, we have our actual line chart here.
08:13 We can see that Amazon has jumped ahead of Google and is much higher now. But we can see how everything worked out from the beginning of July to the end of September.
08:24 Things are a little bit jagged here. If we wanted to add a little bit of a curve to the lines just to make it look a little bit better, we can call a .curve method here. There's essentially just a bunch of curves built into D3 that you can use in various ways.
08:40 This time, we're going to use a catmull rom curve which I will not claim to understand exactly how it works or what that means. But we're just going to set it to 05 alpha. That's going to give us a nice rounded curve between all these different points.
08:57 There we essentially have a working multi-series line chart. Like pretty much every other chart we've created, we loaded in some data. We did some basic parsing to make sure that values that get loaded from JSON are generally just going to be strings, so we convert things to numbers where we need to. We convert dates where we need to.
09:18 We run through that data and create our scales and our axes. To actually create a line chart, it really just comes down to these couple of lines here. We used D3.line, tell it how to get all of its properties, and when it comes time to create the elements, we just create a path for each one of our lines and then set its D attribute using that line function that we defined up above.