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Customize Matplotlib Axis Tick and Grid

PythonPythonBeginner
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This tutorial is from open-source community. Access the source code

Introduction

In this lab, you will learn how to customize the axis tick and grid properties in a Matplotlib plot using Python. Matplotlib is a data visualization library in Python that allows you to create a variety of charts and graphs. In this lab, we will focus on customizing the axis tick and grid properties of a line plot.

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.

Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlottingDataGroup(["`Plotting Data`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlotCustomizationGroup(["`Plot Customization`"]) python(("`Python`")) -.-> python/BasicConceptsGroup(["`Basic Concepts`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) matplotlib/BasicConceptsGroup -.-> matplotlib/importing_matplotlib("`Importing Matplotlib`") matplotlib/BasicConceptsGroup -.-> matplotlib/figures_axes("`Understanding Figures and Axes`") matplotlib/PlottingDataGroup -.-> matplotlib/line_plots("`Line Plots`") matplotlib/PlotCustomizationGroup -.-> matplotlib/line_styles_colors("`Customizing Line Styles and Colors`") matplotlib/PlotCustomizationGroup -.-> matplotlib/grid_config("`Grid Configuration`") python/BasicConceptsGroup -.-> python/booleans("`Booleans`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/DataScienceandMachineLearningGroup -.-> python/numerical_computing("`Numerical Computing`") python/DataScienceandMachineLearningGroup -.-> python/data_visualization("`Data Visualization`") subgraph Lab Skills matplotlib/importing_matplotlib -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} matplotlib/figures_axes -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} matplotlib/line_plots -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} matplotlib/line_styles_colors -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} matplotlib/grid_config -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} python/booleans -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} python/tuples -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} python/importing_modules -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} python/numerical_computing -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} python/data_visualization -.-> lab-48564{{"`Customize Matplotlib Axis Tick and Grid`"}} end

Import Libraries

The first step is to import the necessary libraries. We will be using Matplotlib and NumPy in this lab. NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

import matplotlib.pyplot as plt
import numpy as np

Create Data

Next, we will create some data to plot. In this example, we will be using the sine function to generate a wave.

t = np.arange(0.0, 2.0, 0.01)
s = np.sin(2 * np.pi * t)

Create a Plot

Now, we will create a plot using the data we just created.

fig, ax = plt.subplots()
ax.plot(t, s)

Customize Axis Tick and Grid Properties

We can customize the axis tick and grid properties using the grid() and tick_params() functions. In this example, we will change the color and size of the tick labels and the width and style of the grid lines.

ax.grid(True, linestyle='-.', linewidth=0.5, color='gray')
ax.tick_params(axis='both', which='both', labelsize=8, width=1, color='red')

Display the Plot

Finally, we will display the plot.

plt.show()

Summary

In this lab, you learned how to customize the axis tick and grid properties in a Matplotlib plot using Python. You can use the grid() function to control the visibility and style of the grid lines, and the tick_params() function to control the appearance of the tick labels. By customizing these properties, you can create more visually appealing and informative plots.

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