![]() ![]() ![]() Left, bottom, width, height = Īx = fig.add_axes() 图的位置编号,编号从左到右,从上到下依次递增。 fig = plt.figure(figsize=(8, 5))Īxes2 = fig.add_subplot(2, 2, 1, facecolor='pink') Create a figure with separate subplot titles and a centered figure title. You also learned how to control these titles globally and how to reset values back to their default values.为了在Matplotlib图形窗口中创建多个子图,可使用subplot()函数。该函数接受三个整数作为参 You also learned how to control the style, size, and position of these titles. In this tutorial, you learned how to use Matplotlib to add titles, subtitles, and axis labels to your plots. update() method again and pass in the default values: # Restoring rcParams back to default values In order to restore values to their default values, we can use the. Matplotlib stores the default values in the rcParamsDefault attribute. Once you’ve set the rcParams in Matplotlib, you may want to reset these styles in order to ensure that the next time you run your script that default values are applied. Resetting Matplotlib Title Styles to Default Values If you’re curious about the different rcParams that are available, you can print them using the () method. Plt.ylabel('y-Axis Title', style='italic', loc='bottom') Plt.xlabel('x-Axis Label', fontweight='bold') Let’s see how we can add and style axis labels in Matplotlib: # Adding Axis Labels to a Matplotlib Plot ylabel() adds an y-axis label to your plot xlabel() adds an x-axis label to your plot We can add axis titles using the following methods: This is part of the incredible flexibility that Matplotlib offers. Matplotlib handles the styling of axis labels in the same way that you learned above. See how to plot subfigures for further details. Axis labels provide descriptive titles to your data to help your readers understand what your dad is communicating. 4 Answers Sorted by: 49 New in matplotlib 3.4.0 Row titles can now be implemented as subfigure suptitles: The new subfigure feature allows creating virtual figures within figures with localized artists (e.g., colorbars and suptitles) that only pertain to each subfigure. In this section, you’ll learn how to add axis labels to your Matplotlib plot. In the next section, you’ll learn how to add and style axis labels in a Matplotlib plot. While this is an official way to add a subtitle to a Matplotlib plot, it does provide the option to visually represent a subtitle. Y = Īdding a subtitle to your Matplotlib plot Let’s see how we can use these parameters to style our plot: # Adding style to our plot's title The ones above represent the key parameters that we can use to control the styling. There are many, many more attributes that you can learn about in the official documentation. family= controls the font family of the font.fontweight= controls the the weight of the font.loc= controls the positioning of the text.fontsize= controls the size of the font and accepts an integer or a string.title() method in order to style our text: Let’s take a look at the parameters we can pass into the. Matplotlib provides you with incredible flexibility to style your plot’s title in terms of size, style, and positioning (and many more). Changing Font Sizes and Positioning in Matplotlib Titles This is what you’ll learn in the next section. We can easily control the font styling, sizing, and positioning using Matplotlib. We can see that the title is applied with Matplotlib’s default values. ![]()
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