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This page contains example plots. Click on any image to see the full image and source code. For longer tutorials, see our tutorials page. You can also find external resources and a FAQ in our user guide. Tagging! You can also browse the example gallery by tags.
- Lines, bars and markers
Figure legend demo; Configuring the font family; Using ttf...
- Images, contours and fields
Scatter plots with a legend; Simple Plot; Shade regions...
- Subplots, axes and figures
Subplots, axes and figures - Examples — Matplotlib 3.9.2...
- Statistics
The histogram (hist) function with multiple data sets....
- Pie and polar charts
Labeling a pie and a donut. Labeling a pie and a donut. Bar...
- Text, labels and annotations
Figure legend demo; Configuring the font family; Using ttf...
- Color
Color#. For a description of the colormaps available in...
- Shapes and collections
Explore the Matplotlib documentation for shapes and...
- Lines, bars and markers
You can do this either by using the label= keyword in each of your plt.plot() calls or by assigning your labels as a tuple or list within legend, as in this working example:
Legend Demo. Note. Go to the end to download the full example code. Legend Demo #. There are many ways to create and customize legends in Matplotlib. Below we'll show a few examples for how to do so. First we'll show off how to make a legend for specific lines.
23 mar 2019 · Matplotlib Examples: Displaying and Configuring Legends. Last updated: 23 Oct 2022. Table of Contents. Add legend to plot. Add legend to multiple plots in the same axis. Add legend to axis. Change legend location. Disable legend. Change number of columns in legend.
There’re two ways to code in Matplotlib. The rst one is state-based: import matplotlib.pyplot as plt plt.figure() plt.plot([0, 1], [0, 1],'r--') plt.xlim([0.0, 1.0]) plt.ylim([0.0, 1.0]) plt.title('Test figure') plt.show() t.XXX to plot each component in t. abel(xlabel='X title', size=20) ax.set_ylabel(ylabel='Y title' , color='b', si.
This post explains how to customize the legend on a chart with matplotlib. It provides many examples covering the most common use cases like controling the legend location, adding a legend title or customizing the legend markers and labels.
Matplotlib is a versatile Python library that provides native support for creating legends in various visualizations. Understanding how to position legends, whether inside or outside a chart, can enhance data interpretation.
