Add Text, Font and Grid lines in Matplotlib
Adding text annotations and grid lines in Matplotlib enhances the readability and clarity of plots. Here’s how you can incorporate text annotations and grid lines into your Matplotlib plots.
Example: Creating Grid Lines with Chart Title in Matplotlib
# Importing the library
import matplotlib.pyplot as plt
# Define X and Y data points
X = [12, 34, 23, 45, 67, 89]
Y = [1, 3, 67, 78, 7, 5]
# Plot the graph using matplotlib
plt.plot(X, Y)
# Add gridlines to the plot
plt.grid(color = 'green', linestyle = '--', linewidth = 0.5)
# `plt.grid()` also works
# displaying the title
plt.title(label='Number of Users of a particular Language',
fontweight=10,
pad='2.0')
# Function to view the plot
plt.show()
Output
Refere
- How to add a grid on a figure in Matplotlib?
- How to Change Legend Font Size in Matplotlib?
- How to Change Fonts in matplotlib?
- How to change the font size of the Title in a Matplotlib figure ?
- How to Set Tick Labels Font Size in Matplotlib?
- Add Text Inside the Plot in Matplotlib
- How to add text to Matplotlib?
Customizing Styles in Matplotlib
Here, we’ll delve into the fundamentals of Matplotlib, exploring its various classes and functionalities to help you unleash the full potential of your data visualization projects. From basic plotting techniques to advanced customization options, this guide will equip you with the knowledge needed to create stunning visualizations with Matplotlib. So, let’s dive in and discover how to effectively utilize Matplotlib for your data visualization needs.
Table of Content
- Getting Started with Matplotlib
- Exploring Different Plot Styles with Matplotlib
- Matplotlib Figure Class
- Python Pyplot Class
- Matplotlib Axes Class
- Set Colors in Matplotlib
- Add Text, Font and Grid lines in Matplotlib
- Custom Legends with Matplotlib
- Matplotlib Ticks and Tick Labels
- Style Plots using Matplotlib
- Create Multiple Subplots in Matplotlib
- Working With Images In Matplotlib
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