Move seaborn plot legend to a different position

Question

I'm using factorplot(kind="bar") with seaborn.

The plot is fine except the legend is misplaced: too much to the right, text goes out of the plot's shaded area.

How do I make seaborn place the legend somewhere else, such as in top-left instead of middle-right?

Answer 1

Building on @user308827's answer: you can use legend=False in factorplot and specify the legend through matplotlib:

import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")

titanic = sns.load_dataset("titanic")

g = sns.factorplot("class", "survived", "sex",
                   data=titanic, kind="bar",
                   size=6, palette="muted",
                   legend=False)
g.despine(left=True)
plt.legend(loc='upper left')
g.set_ylabels("survival probability")

• plt acts on the current axes. To get axes from a FacetGrid use fig.
  • g.fig.get_axes()[0].legend(loc='lower left')

Answer 2

• For seaborn >= 0.11.2 use seaborn.move_legend, which applies to Axes and Figure level plots, and it accepts kwargs, like title
  • See matplotlib.axes.Axes.legend and How to put the legend out of the plot for parameters and their usage.
• The original question asked about sns.factorplot, which has been renamed to seaborn.catplot, a figure-level plot.
• For g = sns.jointplot or g = sns.JointGrid, the legend is in g.ax_joint, not g.
  • sns.move_legend(g.ax_joint)
  • See How to move or remove the legend from a seaborn JointGrid or jointplot.
• .move_legend is for moving the legend, not changing the legend title, or labels. This should be done by cleaning the data.
  • In pandas, there are various ways to change column names and the string values in a column, such as .rename, and .map.
• Tested in python 3.10, pandas 1.5.0, matplotlib 3.5.2, seaborn 0.12.0
  • See How can I customize the legend with Seaborn 0.12 objects? to relocate legends using the new seaborn.object interface, which debuted in seaborn 0.12.0.

import matplotlib.pyplot as plt
import seaborn as sns

# load the data
penguins = sns.load_dataset('penguins', cache=False)

Figure Level Plot

g = sns.displot(penguins, x="bill_length_mm", hue="species", col="island", col_wrap=2, height=3)
sns.move_legend(g, "upper left", bbox_to_anchor=(.55, .45), title='Species')
plt.show()

Axes Level Plot

ax = sns.histplot(penguins, x="bill_length_mm", hue="species")
sns.move_legend(ax, "lower center", bbox_to_anchor=(.5, 1), ncol=3, title=None, frameon=False)
plt.show()

Answer 3

Check out the docs here: https://matplotlib.org/users/legend_guide.html#legend-location

adding this simply worked to bring legend out of the plot:

plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)

Answer 4

Modifying the example here:

You can use legend_out = False

import seaborn as sns
sns.set(style="whitegrid")

titanic = sns.load_dataset("titanic")

g = sns.factorplot("class", "survived", "sex",
                    data=titanic, kind="bar",
                    size=6, palette="muted",
                   legend_out=False)
g.despine(left=True)
g.set_ylabels("survival probability")

Answer 5

This is how I was able to move the legend to a particular place inside the plot and change the aspect and size of the plot:

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
import seaborn as sns
sns.set(style="ticks")

figure_name = 'rater_violinplot.png'
figure_output_path = output_path + figure_name

viol_plot = sns.factorplot(x="Rater", 
                       y="Confidence", 
                       hue="Event Type", 
                       data=combo_df, 
                       palette="colorblind",
                       kind='violin',
                       size = 10,
                       aspect = 1.5,
                       legend=False)

viol_plot.ax.legend(loc=2)
viol_plot.fig.savefig(figure_output_path)  

This worked for me to change the size and aspect of the plot as well as move the legend outside the plot area.

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
import seaborn as sns
sns.set(style="ticks")


figure_name = 'rater_violinplot.png'
figure_output_path = output_path + figure_name

viol_plot = sns.factorplot(x="Rater", 
                       y="Confidence", 
                       hue="Event Type", 
                       data=combo_df, 
                       palette="colorblind",
                       kind='violin',
                       size = 10,
                       aspect = 1.5,
                       legend_out=True)

viol_plot.fig.savefig(figure_output_path)  

I figured this out from mwaskom's answer here and Fernando Hernandez's answer here.

Answer 6

it seems you can directly call:

g = sns.factorplot("class", "survived", "sex",
                data=titanic, kind="bar",
                size=6, palette="muted",
               legend_out=False)

g._legend.set_bbox_to_anchor((.7, 1.1))

Answer 7

If you wish to customize your legend, just use the add_legend method. It takes the same parameters as matplotlib plt.legend.

import seaborn as sns
sns.set(style="whitegrid")

titanic = sns.load_dataset("titanic")

g = sns.factorplot("class", "survived", "sex",
                    data=titanic, kind="bar",
                    size=6, palette="muted",
                   legend_out=False)
g.despine(left=True)
g.set_ylabels("survival probability")
g.add_legend(bbox_to_anchor=(1.05, 0), loc=2, borderaxespad=0.)

Answer 8

Using object oriented API:

fig,ax = plt.subplots(1,1)
sns.someplot(...,ax=ax)
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles, labels,loc="upper left")

source: https://matplotlib.org/stable/tutorials/intermediate/legend_guide.html