Adventures in Machine Learning

Optimizing Visualizations: Placing Legends Outside a Matplotlib Plot

Matplotlib is an incredibly useful library for creating beautiful and informative visualizations in Python. One of the most important components of any visualization is the legend, which provides critical information about what each line or marker represents.

Sometimes, the legend can become too large or crowded for the plot, making it difficult to read or even overwhelming. In these cases, you might want to place the legend outside of the plot itself.

Thankfully, Matplotlib provides a simple and flexible way to handle this situation: the bbox_to_anchor and loc parameters. By adjusting these parameters, you can position the legend wherever you like and customize its appearance to fit your needs.

In this article, we will explore three different examples of placing the legend outside of the Matplotlib plot, using specific settings for each.

Example 1: Place Legend in Top Right Corner

When you want to display a legend outside of the plot, one common location is in the top right corner.

This position allows you to preserve the existing plot layout and provides a compact display for the legend. To achieve this, we need to adjust the location and size of the legend using the bbox_to_anchor parameter.

First, let’s create a simple plot with a legend:

“` python

import matplotlib.pyplot as plt

import numpy as np

# data for plotting

x = np.linspace(0, 2*np.pi, 100)

y = np.sin(x)

# plot

plt.plot(x, y, label=’sin(x)’)

plt.legend(loc=’upper left’) # legend inside plot

plt.show()

“`

This creates a sine wave with a legend in the upper left corner of the plot. To move this legend outside of the plot and into the top right corner, we need to adjust the bbox_to_anchor and loc parameters:

“` python

import matplotlib.pyplot as plt

import numpy as np

# data for plotting

x = np.linspace(0, 2*np.pi, 100)

y = np.sin(x)

# plot

plt.plot(x, y, label=’sin(x)’)

plt.legend(bbox_to_anchor=(1.05, 1), loc=’upper left’) # legend outside plot

plt.show()

“`

Here, we set bbox_to_anchor=(1.05, 1), which moves the legend 5% to the right and 100% up from the upper left corner of the plot. We also set loc=’upper left’ to move the legend outside of the plot in the direction we desired.

Running this code produces an image with the legend now in the top right corner of the plot. Example 2: Place Legend in Bottom Right Corner

Another popular location for legends outside of the plot is in the bottom right corner.

This position provides a similar advantage to the top right corner as it preserves the layout of the plot while also keeping the legend concise. To accomplish this, we need to make a few adjustments to the previous code.

“` python

import matplotlib.pyplot as plt

import numpy as np

# data for plotting

x = np.linspace(0, 2*np.pi, 100)

y = np.cos(x)

# plot

plt.plot(x, y, label=’cos(x)’)

plt.legend(bbox_to_anchor=(1.05, 0), loc=’lower left’) # legend outside plot

plt.show()

“`

Here, we set bbox_to_anchor=(1.05, 0), which moves the legend 5% to the right and 0% down from the lower left corner of the plot. We also set loc=’lower left’, which moves the legend to the bottom right corner.

Running the code produces an image with the legend in the bottom right corner. Example 3: Place Legend Above Plot

If you have a plot with a lot of lines or data points, the legend can quickly become too large to display in a compact manner.

In these cases, placing the legend above the plot can be helpful. This technique makes the legend its own row and expands the original plot to make room for it.

To achieve this, we need to use the mode, expand and ncol parameters in addition to bbox_to_anchor and loc. “` python

import matplotlib.pyplot as plt

import numpy as np

# data for plotting

x = np.linspace(0, 2*np.pi, 100)

y_sin = np.sin(x)

y_cos = np.cos(x)

# plot

plt.plot(x, y_sin, label=’sin(x)’)

plt.plot(x, y_cos, label=’cos(x)’)

plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=’lower left’,

ncol=2, mode=”expand”, borderaxespad=0.)

plt.show()

“`

Here, we set bbox_to_anchor=(0., 1.02, 1., .102), which moves the legend to a separate row above the plot. We also set loc=’lower left’, which aligns the new row with the lower left corner of the plot.

The mode parameter is set to “expand” which adds a border across the top of the plot to make space for the legend. The ncol parameter is set to 2, which creates two columns of legend entries for more compact display.

borderaxespad is used to reduce the padding between the legend and plots x-axis. Running this code creates an image with the legend above the plot, spanning its width.

Additional Resources

If you are interested in learning more about customizing legends in Matplotlib, there are many resources available. The Matplotlib documentation provides detailed information on all of the available legend options.

There are also numerous tutorials and examples available online that demonstrate creative ways to use legend placement to make your visualizations more informative and aesthetically pleasing. Check out some more examples of using bbox_to_anchor to place the legend outside of the plot, as well as other exciting and creative ways of improving the presentation of your visualizations!

In conclusion, placing legends outside a plot in Matplotlib is a useful technique for optimizing visualizations with many data points or multiple lines.

By adjusting the location, size, and appearance of legends using bbox_to_anchor, loc, ncol, and mode parameters, you can create clear and concise representations of the data. The article presented three examples of placing legends outside a plot, including top right and bottom right corners, and above the plot.

Additional resources for customizing legends in Matplotlib include the official documentation and online tutorials. Overall, efficient design and placement of legends can significantly enhance the readability and overall effectiveness of visualizations.

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