Customizing Matplotlib Visualizations

Introduction

This lab will guide you through the process of customizing Matplotlib using style sheets and rcParams. Matplotlib is a powerful library for creating visualizations in Python. By customizing the properties and default styles of Matplotlib, you can create unique and visually appealing plots.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Setting rcParams at runtime

You can dynamically change the default runtime configuration settings in a Python script or interactively from the Python shell. The matplotlib.rcParams variable is global to the Matplotlib package and stores all the rc settings. To customize rcParams at runtime, you can modify it directly using the mpl.rcParams dictionary. Here's an example:

import matplotlib as mpl

mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.linestyle'] = '--'

This code changes the default line width and line style for all plots created with Matplotlib.

Let's see some random data plotted with the new default settings.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from cycler import cycler
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.linestyle'] = '--'
data = np.random.randn(50)
plt.plot(data)
plt.show()

Using style sheets

Another way to change the visual appearance of plots is to set the rcParams in a style sheet and import that style sheet with matplotlib.style.use. A style sheet is a file that contains a set of rcParams related to the style of a plot. Matplotlib provides a number of pre-defined styles that you can use. For example, the "ggplot" style emulates the aesthetics of the ggplot library in R. You can apply a style sheet like this:

import matplotlib.pyplot as plt

print(plt.style.available)
plt.style.use('Solarize_Light2')

You can also define your own custom styles and use them by calling .style.use with the path or URL to the style sheet.

Changing the matplotlibrc file

The matplotlibrc file is a configuration file that allows you to customize all kinds of properties in Matplotlib. It controls the defaults for properties like figure size, line width, colors, fonts, etc. You can modify the matplotlibrc file to customize Matplotlib according to your preferences. The file can be located in different places on your system, and Matplotlib looks for it in a specific order. Once a matplotlibrc file is found, it takes precedence over other settings. You can use the matplotlib.matplotlib_fname() function to display the path of the currently active matplotlibrc file.

Summary

Matplotlib provides multiple ways to customize the properties and default styles of plots. You can set rcParams at runtime, use style sheets to change the visual appearance of plots, and modify the matplotlibrc file to customize Matplotlib globally. Experiment with different customizations to create unique and visually appealing plots with Matplotlib.