Plotting Scatter Plots

Quick reference

• 00:05 Okay, in the last video, we looked at line plots.
• 00:07 In this video, we want to look at scatter plots.
• 00:10 So scatter plots are a little bit more complicated, but not too bad.
• 00:12 So let's go, my_df.plot, and the kind, we want to set this equal to scatter.
• 00:19 Now if we just run this we're going to get an error,
• 00:22 because with a scatter plot we have to designate an x and y-axis.
• 00:26 So let's designate the x-axis to be Mon, and
• 00:30 let's designate the y-axis to be Tues.
• 00:34 And when we run this, we get this scatter plot.
• 00:37 So there's not a whole lot of points in our data here.
• 00:40 So let's go back up to the top and let's add 500 points instead of just 50, just
• 00:45 to make this a little more interesting, so Shift+Enter to run both of those.
• 00:50 And then let's come back down here and do this, and we get a bigger scatter plot.
• 00:54 Now we can also sort of analyze these against
• 00:58 a third column, we can go, c='wed'.
• 01:03 And when we do that, we have them each sort of played against Wednesday.
• 01:06 And we get this different color scale to help us differentiate the different
• 01:11 points.
• 01:11 Now this is still kind of hard to see, so we can actually change this color using
• 01:15 a cmap, and we can set this equal to any kind of different cmap that's available.
• 01:21 I'm going to go seismic, and we'll talk about this in a second, and boom,
• 01:24 now we get these different colors.
• 01:26 So if we head over to this website here, and if you scroll down you can see all
• 01:30 kinds of different color maps you can choose from.
• 01:33 So, for instance, if we grab copper, I'm not even sure exactly what that is, but we
• 01:38 can run it here and, boom, we get copper, that's kind of cool looking, right?
• 01:42 So I'll play around with this, this is kind of fun.
• 01:44 Cool, I wonder what cool looks like, I bet it's cool.
• 01:48 Light blue, maybe, blues and pinks.
• 01:52 But there's all kinds of neat ones.
• 01:54 We got winter, we can do cool, warm, spectral, autumn, summer, spring.
• 02:01 Spring is lovely, let's see what spring looks like.
• 02:05 Right, that's not really that springy to me, Wistia.
• 02:12 Now, you can also, instead of reducing by color,
• 02:15 we can do it by size against that third column.
• 02:18 So we can call s=, and instead of just passing Wednesday like that,
• 02:23 we have to actually pass the whole data frame.
• 02:25 So let's go my_df, and then pass in Wednesday inside like that.
• 02:32 And when we do that we get this thing.
• 02:33 Now this is not very easy to read, so we can actually multiply all these
• 02:37 numbers by, for instance 100, to make these bigger.
• 02:41 And now you can see some of them are bigger, some of them are smaller.
• 02:44 It's kind of interesting, it's still kind of hard to read.
• 02:46 So we can call alpha=, I don't know, 0.4, for instance, like we've done in the past.
• 02:53 And now we can sort of see through these, maybe you want 0.2, 0.3.
• 02:57 You can play around with this.
• 02:59 Whatever makes more sense for you to sort of understand what's going on and
• 03:03 to see all of these things.
• 03:04 So what we're doing basically is pulling each column and
• 03:07 then sort of analyzing it against Wednesday,
• 03:10 relative to the size it is against Wednesday, and it's kind of neat.
• 03:14 So play around with these color maps, these are actually kind of fun.
• 03:18 So we can call these cmaps on other things as well, on our other plots as well.
• 03:23 So we could go cmap=, let's see, what was one, autumn.
• 03:29 That is, let's grab winter and see how winter looks.
• 03:36 Okay, whatever, maybe that's not as easy to read.
• 03:41 We changed our data up here to 500, let's change this back to 30.
• 03:54 There we go.
• 03:57 There we go, easy to read.
• 03:59 So play with the cmaps, have fun with those, and those are scatter plots.
• 04:03 In the next video, we'll look at box plots.

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