[Tut] Python ? Put Legend Outside Plot ? – Easy Guide

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Python ? Put Legend Outside Plot ? – Easy Guide

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Are you tired of feeling boxed in by your Python plots and ready to break free from the constraints of traditional legend placement?

In this guide, I’ll show you how to put legends outside your plot for (click to jump):

• Matplotlib
  
  
• Seaborn
  
  
• Pandas
  
  
• Bokeh
  

Let’s start with the first!

Matplotlib Put Legend Outside Plot

Let’s start with various ways to position the legend outside for better visualization and presentation.

Matplotlib Set Legend Outside Plot (General)

First, let’s adjust the legend’s position outside the plot in general. To do this, use the

Code:

bbox_to_anchor

parameter in the legend function like this:

Code:

matplotlib.pyplot.legend(bbox_to_anchor=(x, y))

. Here, adjust the values of

Code:

x

and

Code:

y

to control the legend’s position.

Code:

import matplotlib.pyplot as plt # Sample data for plotting x = [1, 2, 3, 4, 5] y1 = [1, 4, 9, 16, 25] y2 = [1, 8, 27, 64, 125] # Create the plot plt.plot(x, y1, label='y = x^2') plt.plot(x, y2, label='y = x^3') # Set the legend's position outside the plot using bbox_to_anchor plt.legend(bbox_to_anchor=(1.05, 1)) # Add axis labels and title plt.xlabel('x') plt.ylabel('y') plt.title('Plotting with External Legend') # Display the plot plt.show()

In this example, the

Code:

bbox_to_anchor

parameter is set to

Code:

(1.05, 1)

, which moves the legend slightly to the right of the plot.

Info: The

Code:

bbox_to_anchor

parameter in

Code:

matplotlib.pyplot.legend()

uses a tuple of two values,

Code:

x

and

Code:

y

, to control the position of the legend.

Code:

x=0/1

controls the left/right and

Code:

y=0/1

controls the bottom/top legend placement.

Generally, in axes coordinates:

• Code:

  (0, 0)
  represents the left-bottom corner of the axes.
  
  
• Code:

  (0, 1)
  represents the left-top corner of the axes.
  
  
• Code:

  (1, 0)
  represents the right-bottom corner of the axes.
  
  
• Code:

  (1, 1)
  represents the right-top corner of the axes.
  

However, the values of

Code:

x

and

Code:

y

are not limited to the range

Code:

[0, 1]

. You can use values outside of this range to place the legend beyond the axes’ boundaries.

For example:

• (1.05, 1) places the legend slightly to the right of the top-right corner of the axes.
  
  
• (0, 1.1) places the legend slightly above the top-left corner of the axes.
  

Using negative values is also allowed. For example:

• (-0.3, 0) places the legend to the left of the bottom-left corner of the axes.
  
  
• (1, -0.2) places the legend below the bottom-right corner of the axes.
  

The range of

Code:

x

and

Code:

y

depends on the desired position of the legend relative to the plot. By adjusting these values, you can fine-tune the legend’s position to create the perfect visualization.

Matplotlib Set Legend Below or Above Plot

To place the legend below the plot, you can set the

Code:

loc

parameter as ‘upper center’ and use

Code:

bbox_to_anchor

like this:

Code:

plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1))

. For placing the legend above the plot, use

Code:

bbox_to_anchor=(0.5, 1.1)

instead .



Matplotlib Set Legend Left of Plot (Upper, Center, Lower Left)

For positioning the legend to the left of the plot, use the following examples:

• Upper left:
  Code:

  plt.legend(loc='center left', bbox_to_anchor=(-0.2, 0.5))
  
  
  
• Center left:
  Code:

  plt.legend(loc='center left', bbox_to_anchor=(-0.1, 0.5))
  
  
• Lower left:
  Code:

  plt.legend(loc='lower left', bbox_to_anchor=(-0.2, 0))

Matplotlib Set Legend Right of Plot (Upper, Center, Lower Right)

To position the legend to the right of the plot, you can try the following:

• Upper right:
  Code:

  plt.legend(loc='upper right', bbox_to_anchor=(1.1, 1))
  
  
  
• Center right:
  Code:

  plt.legend(loc='center right', bbox_to_anchor=(1.1, 0.5))
  
  
• Lower right:
  Code:

  plt.legend(loc='lower right', bbox_to_anchor=(1.1, 0))

Matplotlib Set Subplots Legend Outside Plot

When working with subplots, you can place a single, unified legend outside the plot by iterating over the axes and using the

Code:

legend()

method on the last axis (source) . Remember to use the

Code:

bbox_to_anchor

parameter to control the legend’s position.

Here’s an example that does two things, i.e., (1) placing the legend on the right and (2) adjusting the layout to accommodate the external legend:

Code:

import numpy as np import matplotlib.pyplot as plt # Sample data for plotting x = np.linspace(0, 10, 100) y1 = np.sin(x) y2 = np.cos(x) # Create subplots fig, axes = plt.subplots(nrows=2, ncols=1, sharex=True) # Plot data on the first subplot axes[0].plot(x, y1, label='sin(x)') axes[0].set_title('Sine Wave') # Plot data on the second subplot axes[1].plot(x, y2, label='cos(x)', color='orange') axes[1].set_title('Cosine Wave') # Set a common x-label for both subplots fig.text(0.5, 0.04, 'x', ha='center') # Set y-labels for individual subplots axes[0].set_ylabel('sin(x)') axes[1].set_ylabel('cos(x)') # Create a unified legend for both subplots handles, labels = axes[-1].get_legend_handles_labels() for ax in axes[:-1]: h, l = ax.get_legend_handles_labels() handles += h labels += l # Place the unified legend outside the plot using bbox_to_anchor fig.legend(handles, labels, loc='upper right', bbox_to_anchor=(1, 0.75)) # Adjust the layout to accommodate the external legend fig.subplots_adjust(right=0.7) # Display the subplots plt.show()

Legend Outside Plot Is Cut Off

If your legend is cut off, you can adjust the saved figure’s dimensions using

Code:

plt.savefig('filename.ext', bbox_inches='tight')

. The

Code:

bbox_inches

parameter with the value ‘tight’ will ensure that the whole legend is visible on the saved figure .

Add Legend Outside a Scatter Plot

For a scatter plot, you can use the same approach as mentioned earlier by adding the

Code:

loc

and

Code:

bbox_to_anchor

parameters to position the legend outside the plot. For instance,

Code:

plt.legend(loc='upper right', bbox_to_anchor=(1.1, 1))

will place the legend in the upper right corner outside the scatter plot .

If your legend is cut off when placing it outside the plot in Python’s Matplotlib, you can adjust the layout and save or display the entire figure, including the external legend, by following these steps:

1. Use the
   Code:

   bbox_to_anchor
   parameter in the
   Code:

   legend()
   function to control the position of the legend.
   
   
2. Adjust the layout of the figure using the
   Code:

   subplots_adjust()
   or
   Code:

   tight_layout()
   function to make room for the legend.
   
   
3. Save or display the entire figure, including the external legend.
   

Here’s an example demonstrating these steps:

Code:

import matplotlib.pyplot as plt # Sample data for plotting x = [1, 2, 3, 4, 5] y1 = [1, 4, 9, 16, 25] y2 = [1, 8, 27, 64, 125] # Create the plot plt.plot(x, y1, label='y = x^2') plt.plot(x, y2, label='y = x^3') # Set the legend's position outside the plot using bbox_to_anchor plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left') # Add axis labels and title plt.xlabel('x') plt.ylabel('y') plt.title('Plotting with External Legend') # Adjust the layout to accommodate the external legend plt.subplots_adjust(right=0.7) # Display the plot plt.show()

In this example, you use the

Code:

subplots_adjust()

function to adjust the layout of the figure and make room for the legend.

You can also use the

Code:

tight_layout()

function, which automatically adjusts the layout based on the elements in the figure:

Code:

# ... # Set the legend's position outside the plot using bbox_to_anchor plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left') # Add axis labels and title plt.xlabel('x') plt.ylabel('y') plt.title('Plotting with External Legend') # Automatically adjust the layout to accommodate the external legend plt.tight_layout(rect=[0, 0, 0.7, 1]) # Display the plot plt.show()

In this case, the

Code:

rect

parameter is a list

Code:

[left, bottom, right, top]

, which specifies the normalized figure coordinates of the new bounding box for the subplots. Adjust the values in the

Code:

rect

parameter as needed to ensure the legend is not cut off.

Additional Legend Configurations

In this section, you’ll learn about some additional ways to customize the legend for your plots in Python using Matplotlib. This will help you create more meaningful and visually appealing visualizations. However, feel free to skip ahead to the following sections on plotting the legend outside the figure in Seaborn, Pandas, and Bokeh.

Python Set Legend Position

As you already know by now, you can place the legend at a specific position in the plot by using the

Code:

bbox_to_anchor

parameter. For example, you could place the legend outside the plot to the right by passing

Code:

(1.05, 0.5)

as the argument:

Code:

import matplotlib.pyplot as plt plt.legend(bbox_to_anchor=(1.05, 0.5))

This will place the legend slightly outside the right border of the plot, with its vertical center aligned with the plot center.

Python Set Legend Location

You can easily change the location of the legend by using the

Code:

loc

parameter. Matplotlib allows you to use predefined locations like

Code:

'upper right'

,

Code:

'lower left'

, etc., or use a specific coordinate by passing a tuple:

Code:

plt.legend(loc='upper left')

This will place the legend in the upper-left corner of the plot.

Python Set Legend Font Size

To change the font size of the legend, you can use the

Code:

fontsize

parameter. You can pass a numeric value or a string like

Code:

'small'

,

Code:

'medium'

, or

Code:

'large'

to set the font size:

Code:

plt.legend(fontsize='large')

This will increase the font size of the legend text.

Python Set Legend Title

If you want to add a title to your legend, you can use the

Code:

title

parameter. Just pass a string as the argument to set the title:

Code:

plt.legend(title='My Legend Title')

This will add the title “My Legend Title” above your legend.

Python Set Legend Labels

If you’d like to customize the legend labels, you can pass the

Code:

labels

parameter. It takes a list of strings as the argument:

Code:

plt.legend(labels=['Label 1', 'Label 2'])

Your legend will now display the custom labels “Label 1” and “Label 2” for the corresponding plot elements.

Python Set Legend Color

Changing the color of the legend text and lines can be achieved by using the

Code:

labelcolor

parameter. Just pass a color string or a list of colors:

Code:

plt.legend(labelcolor='red')

This will change the color of the legend text and lines to red.

Seaborn Put Legend Outside Plot

In this section, I’ll show you how to move the legend outside the plot using Seaborn. Let’s dive into various ways of setting the legend position, like below, above, left or right of the plot.

Sns Set Legend Outside Plot (General)

First, let’s talk about the general approach:

You can use the

Code:

legend()

function and the

Code:

bbox_to_anchor

parameter from Matplotlib to move the legend. You can combine this with the

Code:

loc

parameter to fine-tune the legend’s position.

Here’s a quick example:

Code:

import seaborn as sns import matplotlib.pyplot as plt # Sample data for plotting tips = sns.load_dataset("tips") # Create a Seaborn plot with axis variable 'ax' fig, ax = plt.subplots() sns_plot = sns.scatterplot(x="total_bill", y="tip", hue="day", data=tips, ax=ax) # Set the legend's position outside the plot using bbox_to_anchor on 'ax' ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.) # Add axis labels and title ax.set_xlabel('Total Bill') ax.set_ylabel('Tip') ax.set_title('Tips by Total Bill and Day') # Display the plot plt.show()

Sns Set Legend Below or Above Plot

Now let’s move the legend below or above the plot. Simply adjust the

Code:

bbox_to_anchor

parameter accordingly. For example, to place the legend below the plot, you can use

Code:

bbox_to_anchor=(0.5, -0.1)

:

Code:

ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1))

And to place the legend above the plot, use

Code:

bbox_to_anchor=(0.5, 1.1)

:

Code:

ax.legend(loc='lower center', bbox_to_anchor=(0.5, 1.1))

Sns Set Legend Left of Plot (Upper, Center, Lower Left)

Similarly, to position the legend on the left side of the plot, you can use the following code snippets:

Upper left:

Code:

ax.legend(loc='upper right', bbox_to_anchor=(-0.15, 1))

Center left:

Code:

ax.legend(loc='center right', bbox_to_anchor=(-0.15, 0.5))

Lower left:

Code:

ax.legend(loc='lower right', bbox_to_anchor=(-0.15, 0))

Sns Set Legend Right of Plot (Upper, Center, Lower Right)

Lastly, to place the legend on the right side of the plot, adjust the

Code:

bbox_to_anchor

parameter like so:

Upper right:

Code:

ax.legend(loc='upper left', bbox_to_anchor=(1.05, 1))

Center right:

Code:

ax.legend(loc='center left', bbox_to_anchor=(1.05, 0.5))

Lower right:

Code:

ax.legend(loc='lower left', bbox_to_anchor=(1.05, 0))

With these techniques, you can easily position the legend outside the plot using Seaborn! Happy plotting!

Pandas Put Legend Outside Plot

When working with Pandas and Matplotlib, you often want to move the legend outside the plot to improve readability. No worries! You can do this by taking advantage of the fact that

Code:

.plot()

returns a Matplotlib axis, enabling you to add

Code:

.legend(bbox_to_anchor=(x, y))

to your code.

Here’s how:



First, import the necessary libraries like Pandas and Matplotlib:

Code:

import pandas as pd import matplotlib.pyplot as plt

Create your DataFrame and plot it using the

Code:

plot()

function, like this:

Code:

data = {'A': [1, 2, 3], 'B': [4, 5, 6]} df = pd.DataFrame(data) ax = df.plot()

Next, you’ll want to place the legend outside the plot. Adjust the coordinates parameter,

Code:

bbox_to_anchor

, to position it according to your preferences. For example, if you want to place the legend to the right of the plot, use:

Code:

ax.legend(bbox_to_anchor=(1.05, 1)) plt.tight_layout() plt.show()

This code will place the legend to the right of the plot, at the top .

Bokeh Put Legend Outside Plot

Placing a legend outside the plot in Bokeh can be easily done by using the

Code:

add_layout

method. You’ll need to create a

Code:

Legend

object manually and then add it to your plot using

Code:

add_layout

. This gives you the flexibility to position the legend anywhere on your plot, which is particularly helpful when you have many curves that might be obscured by an overlapping legend.

Here’s a short example to help you move the legend outside the plot in Bokeh:

Code:

from bokeh.plotting import figure, show from bokeh.models import Legend, LegendItem from bokeh.io import output_notebook output_notebook() # Example data x = list(range(10)) y1 = [i**2 for i in x] y2 = [i**0.5 for i in x] # Create a figure p = figure(title="Example Plot") # Add line glyphs and store their renderer r1 = p.line(x, y1, line_color="blue", legend_label="Line 1") r2 = p.line(x, y2, line_color="red", legend_label="Line 2") # Create Legend object legend = Legend(items=[ LegendItem(label="Line 1", renderers=[r1]), LegendItem(label="Line 2", renderers=[r2]) ], location="top_left") # Add legend to plot p.add_layout(legend, 'right') # Show plot show(p)

To ensure your plot is as clear as possible, we recommend experimenting with different legend positions and layouts. By customizing your plot, you can maintain a clean and organized display of your curves even when there’s a lot of information to convey.

With Bokeh, you have full control over your plot’s appearance, so enjoy exploring different options to find the perfect fit for your data!

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