Best Text Placement Tools in Matplotlib to Buy in November 2025
Data Visualization with Microsoft Power BI: How to Design Savvy Dashboards
Python Data Science Handbook: Essential Tools for Working with Data
Good Charts Workbook: Tips, Tools, and Exercises for Making Better Data Visualizations
Good Charts, Updated and Expanded: The HBR Guide to Making Smarter, More Persuasive Data Visualizations
Data Visualization with Excel Dashboards and Reports
Storytelling with Data: A Data Visualization Guide for Business Professionals, 10th Anniversary Edition
To place text in matplotlib on a line, you can use the text() function provided by matplotlib. The text() function takes in the x and y coordinates where you want the text to be placed, as well as the actual text you want to display. You can also specify additional parameters such as the color, font size, and font style of the text. By providing the appropriate x and y coordinates, you can place the text directly on a line in a matplotlib plot.
How to place text in matplotlib using annotations?
To place text in Matplotlib using annotations, you can use the plt.annotate() function. Here is an example of how to use annotations to place text in a Matplotlib plot:
import matplotlib.pyplot as plt
Create a simple plot
x = [1, 2, 3, 4, 5] y = [2, 3, 5, 7, 11] plt.plot(x, y)
Add text annotations
plt.annotate('Point 1', (1, 2), textcoords='offset points', xytext=(-10, 10), ha='center') plt.annotate('Point 2', (2, 3), textcoords='offset points', xytext=(10, 10), ha='center') plt.annotate('Point 3', (3, 5), textcoords='offset points', xytext=(10, -10), ha='center') plt.annotate('Point 4', (4, 7), textcoords='offset points', xytext=(-10, -10), ha='center') plt.annotate('Point 5', (5, 11), textcoords='offset points', xytext=(0, 10), ha='center')
Show the plot
plt.show()
In this example, we use the plt.annotate() function to add text annotations to the plot at specified points. We provide the text we want to display, the point where we want to place the text, the coordinate system of the text, the offset of the text from the point, and the horizontal alignment of the text. You can customize the appearance and position of the annotations by adjusting these parameters.
How to change the font size of the legend in matplotlib?
To change the font size of the legend in matplotlib, you can use the fontsize parameter when calling the legend() function. Here's an example:
import matplotlib.pyplot as plt
Create a simple plot
plt.plot([1, 2, 3, 4], [1, 4, 9, 16], label='Data') plt.legend()
Change the font size of the legend
plt.legend(fontsize='large')
plt.show()
In this example, the fontsize parameter is set to 'large', but you can also specify a numerical value for the font size (e.g., 10, 12, 16, etc.) to adjust the font size of the legend in matplotlib.
What is the difference between text and annotations in matplotlib?
Text and annotations are both used to add text to a plot in matplotlib, but there are some key differences between the two:
- Text: Text in matplotlib refers to a simple text string that can be added anywhere on the plot using the plt.text() function. Text can be positioned using x and y coordinates, and can include additional formatting options like font size, color, and alignment. Text is typically used for adding labels or titles to a plot, or for providing additional information.
- Annotations: Annotations in matplotlib are more versatile than text and allow for more advanced customization. Annotations are added using the plt.annotate() function and can include not only text, but also arrows, lines, and shapes. Annotations are typically used to highlight specific points or features on a plot, or to provide additional context or explanation. Annotations can be positioned relative to data coordinates or figure coordinates, and can be customized in terms of appearance and style.