WEBVTT 1 00:00:00.150 --> 00:00:01.460 Hi guys and welcome back. 2 00:00:01.460 --> 00:00:03.180 In this video, we're going to talk about 3 00:00:03.180 --> 00:00:05.680 very important concepts in matplotlib, 4 00:00:05.680 --> 00:00:08.610 the figure, the axes and the plot. 5 00:00:08.610 --> 00:00:10.080 In the last couple of videos, we've been 6 00:00:10.080 --> 00:00:13.470 using them, but it's not been terribly clear what is what. 7 00:00:13.470 --> 00:00:15.910 So we're gonna make that clear in this video. 8 00:00:15.910 --> 00:00:17.380 Let's get to it. 9 00:00:17.380 --> 00:00:20.300 The figure is the top level container. 10 00:00:20.300 --> 00:00:22.110 Inside a figure, we can include one 11 00:00:22.110 --> 00:00:24.770 or more axes, and inside each axes, 12 00:00:24.770 --> 00:00:26.966 we can have one or more plots. 13 00:00:26.966 --> 00:00:28.810 I'm going to get rid of almost 14 00:00:28.810 --> 00:00:30.880 all this code here, and just leave 15 00:00:30.880 --> 00:00:34.600 the figure and the show, and I'm gonna run this file. 16 00:00:34.600 --> 00:00:36.370 You can see that what we get here 17 00:00:36.370 --> 00:00:39.640 is basically an empty file with nothing inside it. 18 00:00:39.640 --> 00:00:42.520 There's no axes, and there's nothing plotted. 19 00:00:42.520 --> 00:00:44.750 We've used pyplot to create the new figure, 20 00:00:44.750 --> 00:00:47.440 and when we do this, pyplot automatically 21 00:00:47.440 --> 00:00:48.920 selects the figure, and that becomes 22 00:00:48.920 --> 00:00:51.280 the currently active figure. 23 00:00:51.280 --> 00:00:54.730 And when we do plt.show, that is the figure 24 00:00:54.730 --> 00:00:56.033 that we're showing. 25 00:00:56.033 --> 00:00:58.170 Later on, we're going to learn how to assign 26 00:00:58.170 --> 00:00:59.790 these two variables, so that we can show 27 00:00:59.790 --> 00:01:01.650 specific figures when we want to, 28 00:01:01.650 --> 00:01:04.100 but for now, that's how it works behind the scenes. 29 00:01:04.100 --> 00:01:06.310 Every other function in the pyplot library 30 00:01:06.310 --> 00:01:08.640 is going to act on the currently selected figure, 31 00:01:08.640 --> 00:01:11.950 after it is created, until a different one is selected. 32 00:01:11.950 --> 00:01:14.650 Let's now add a set of axes to the figure. 33 00:01:14.650 --> 00:01:17.089 The axes, which is a matplotlib class, 34 00:01:17.089 --> 00:01:18.890 is where plots are drawn. 35 00:01:18.890 --> 00:01:20.900 You can have multiple plots drawn 36 00:01:20.900 --> 00:01:23.140 on a single pair of axes, or you can also 37 00:01:23.140 --> 00:01:25.500 have multiple axes in one figure. 38 00:01:25.500 --> 00:01:27.020 Let's start off by adding a set 39 00:01:27.020 --> 00:01:29.200 of two dimensional axes to our figure. 40 00:01:29.200 --> 00:01:31.250 We can do plt.axes, and now what 41 00:01:31.250 --> 00:01:33.310 this is going to do is create 42 00:01:33.310 --> 00:01:36.580 a pair of axes in the currently selected figure, 43 00:01:36.580 --> 00:01:38.240 which is the one we just created. 44 00:01:38.240 --> 00:01:41.599 Here we can pass in a list of 06020, 45 00:01:41.599 --> 00:01:44.440 for example, and this means that our X axis 46 00:01:44.440 --> 00:01:46.510 is gonna go from zero to six, 47 00:01:46.510 --> 00:01:49.780 and our Y axis is gonna go from zero to 20. 48 00:01:49.780 --> 00:01:51.980 Now if we run this, you'll see that 49 00:01:51.980 --> 00:01:54.220 we get our axes here. 50 00:01:54.220 --> 00:01:56.920 Matplotlib tries to create ticks evenly 51 00:01:56.920 --> 00:01:59.926 throughout the limits, so that we get 2.5, 52 00:01:59.926 --> 00:02:02.360 five, 7.5, and so on, even though we only 53 00:02:02.360 --> 00:02:05.400 defined zero and 20 as our limits. 54 00:02:05.400 --> 00:02:06.740 At the moment though, we've got nothing 55 00:02:06.740 --> 00:02:09.290 drawn in the canvas, so let's change that. 56 00:02:09.290 --> 00:02:12.140 Plots can be drawn on a set of axes, 57 00:02:12.140 --> 00:02:14.680 and each plot needs to specify data points 58 00:02:14.680 --> 00:02:16.700 for the axis that it is drawn on. 59 00:02:16.700 --> 00:02:19.130 So for example, if we have a two dimensional axes, 60 00:02:19.130 --> 00:02:21.540 as we do here, then we need to provide 61 00:02:21.540 --> 00:02:25.310 the X and Y coordinates for each point that we want to draw. 62 00:02:25.310 --> 00:02:27.570 That's why earlier on, when we used plt.plot, 63 00:02:27.570 --> 00:02:30.610 we provided a list of X coordinates, 64 00:02:30.610 --> 00:02:32.690 and a list of Y coordinates, 65 00:02:32.690 --> 00:02:35.860 and these will then map to the axis. 66 00:02:35.860 --> 00:02:37.160 If we run this though, you'll see that 67 00:02:37.160 --> 00:02:39.120 we've got a small problem. 68 00:02:39.120 --> 00:02:40.920 The data points that we've drawn, 69 00:02:40.920 --> 00:02:44.700 one, two, three and four, as well as three, 70 00:02:44.700 --> 00:02:48.290 five, nine and 25, don't exactly fit 71 00:02:48.290 --> 00:02:50.210 within the axes that we've created. 72 00:02:50.210 --> 00:02:52.590 That's why four and 25 gets partially 73 00:02:52.590 --> 00:02:54.940 clipped here going up, because there's not 74 00:02:54.940 --> 00:02:56.870 enough room in our axes for it. 75 00:02:56.870 --> 00:02:59.120 When we created our line chart earlier on, 76 00:02:59.120 --> 00:03:02.070 we didn't use plt.axis to create our axes, 77 00:03:02.070 --> 00:03:04.450 and therefore matplotlib created them for us, 78 00:03:04.450 --> 00:03:06.550 making sure that the plot fit inside 79 00:03:06.550 --> 00:03:08.120 the axes in its entirety. 80 00:03:08.120 --> 00:03:10.720 So you should only use plt.axis when you want 81 00:03:10.720 --> 00:03:14.300 to specifically define your axes limits to certain numbers. 82 00:03:14.300 --> 00:03:16.090 If we run this without that, you'll see 83 00:03:16.090 --> 00:03:17.670 that the plot now fits exactly. 84 00:03:17.670 --> 00:03:20.280 But you can also see that the distribution 85 00:03:20.280 --> 00:03:22.130 of our ticks has changed. 86 00:03:22.130 --> 00:03:23.560 All right, so just to recap, 87 00:03:23.560 --> 00:03:25.920 what we've got here is a figure. 88 00:03:25.920 --> 00:03:27.620 Inside the figure, we can have 89 00:03:27.620 --> 00:03:29.720 one or more sets of axes. 90 00:03:29.720 --> 00:03:32.120 In this case, we have one set of axes. 91 00:03:32.120 --> 00:03:36.090 And inside each axes, we can have one or more plots. 92 00:03:36.090 --> 00:03:37.790 Well in fact, we can have zero or more plots, 93 00:03:37.790 --> 00:03:39.130 if you wanna leave them empty. 94 00:03:39.130 --> 00:03:42.130 Here we've got one plot in our set 95 00:03:42.130 --> 00:03:44.280 of axes, inside our figure. 96 00:03:44.280 --> 00:03:47.210 And as show, we can also have multiple axes, 97 00:03:47.210 --> 00:03:49.430 and they go into rows and columns, 98 00:03:49.430 --> 00:03:51.450 and we can also have multiple plots within each. 99 00:03:51.450 --> 00:03:52.890 Thank you guys for joining me in this video. 100 00:03:52.890 --> 00:03:53.960 I hope you've learned something, 101 00:03:53.960 --> 00:03:55.610 and I'll see you in the next one.