Guest, 쇼핑 중독 기미.

일주일에 몇 번씩 택배가 오는 바람에, 드디어 배달원과 안면을 텄습니다. 그리고 왜인지 높은 확률로 찾아오는 사람이—— 조금 가볍고, 거리감이 이상한 꽃미남 배달원.

“이제 물건 없어도 만나고 싶은데.”

물건을 전해주러 오기만 하던 남자가, 어느새 “Guest을 만나기 위해” 현관으로 오게 되기까지. 쇼핑을 너무 많이 했더니, 배달원의 독점욕까지 배송되었습니다. (웃음)

00:00:00.000 --> 00:00:03.480 In this video, I'm going to show you how to use the Python library, Matplotlib, to plot

00:00:03.480 --> 00:00:07.440 multiple charts in a single figure using the subplots function. This is a very common task

00:00:07.440 --> 00:00:11.760 in data visualization, and it's very useful when you want to compare different datasets

00:00:11.760 --> 00:00:13.620 or different views of the same data.

00:00:13.620 --> 00:00:17.400 I'll start by showing you how to create a basic layout with multiple subplots, and then

00:00:17.400 --> 00:00:21.000 we'll look at how to customize the layout and appearance of the subplots.

00:00:21.000 --> 00:00:24.480 To get started, we'll need to import the Matplotlib library. We'll also need some data to plot.

00:00:24.480 --> 00:00:28.080 I'll use some sample data for this example. I'll start by importing the necessary libraries

00:00:28.080 --> 00:00:32.400 and creating some sample data. I'll create two sets of data, x and y1, and x and y2.

00:00:32.400 --> 00:00:36.120 Now, let's create a figure with two subplots. We can do this using the subplots function.

00:00:36.120 --> 00:00:41.280 This function returns a figure object and an array of axes objects. We can then use the

00:00:41.280 --> 00:00:45.480 axes objects to plot our data. In this case, we'll create a figure with one row and two

00:00:45.480 --> 00:00:49.080 columns of subplots. We can then plot our first set of data on the first subplot and

00:00:49.080 --> 00:00:52.440 our second set of data on the second subplot. We can also add titles and labels to each

00:00:52.440 --> 00:00:56.280 subplot. Finally, we'll use the show function to display the figure. And there you have

00:00:56.280 --> 00:00:59.880 it! You've successfully created a figure with multiple subplots using Matplotlib. You can

00:00:59.880 --> 00:01:03.480 customize the layout and appearance of the subplots in many ways, such as changing the

00:01:03.480 --> 00:01:07.320 number of rows and columns, adjusting the spacing between subplots, and adding more

00:01:07.320 --> 00:01:10.920 complex plots. I hope this video was helpful. Thanks for watching! Don't forget to like

00:01:10.920 --> 00:01:14.400 and subscribe for more data science tutorials. See you in the next one! Bye! ✌️

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