How to edit a seaborn legend title and labels for figure-level functions

Question

I've created this plot using Seaborn and a pandas dataframe (data):

My code:

import seaborn as sns

g = sns.lmplot('credibility', 'percentWatched', data=data, hue='millennial', markers=["+", "."])

You may notice the plot's legend title is simply the variable name ('millennial') and the legend items are its values (0, 1). How can I edit the legend's title and labels? Ideally, the legend title would be 'Generation' and the labels would be "Millennial" and "Older Generations".

Answer 1

For the customization of the legend, you need to manipulate the legend object directly. The legend in Seaborn is stored within the plot object. Through this legend object, you can select the title and fix the label's details for your type of data.

Here's how you can do this:

g = sns.lmplot('credibility', 'percentWatched', data=data, hue='millennial', markers=["+", "."])

g.set(title='Generation', xlabel='Credibility', ylabel='Percent Watched')
g._legend.set(title='Generation', labels=["Millennial", "Older Generations"])

plt.show()

Answer 2

Here are some other ways to edit the legend of a seaborn figure (as of seaborn 0.13.2).

1. Since the legend here comes from the column passed to hue, the easiest method (and one that requires the least work imo), as mentioned in comments, is to add a column to the dataframe and use it as the hue variable.

   import seaborn as sns
   df = sns.load_dataset("tips")
   
   g = sns.lmplot(
       x='total_bill', y='tip', 
       data=df.assign(Gender=df['sex'].map({'Male': 'man', 'Female': 'woman'})),   # add a new column
       hue='Gender',               # <--- use the new column as hue
       markers=["+", "."]
   )
   

2. Yet another method is to hide the default legend and add a legend with the new labels and title using add_legend().

   g = sns.lmplot(x='total_bill', y='tip', data=df, hue='sex', markers=["+", "."])
   g.legend.set_visible(False)   # hide the original legend (can also pass `legend=False` to the plot call above)
   
   # create new legend data using the old data
   mapping = {'Male': 'man', 'Female': 'woman'}
   leg_data = {mapping[k]: v for k,v in g._legend_data.items()}
   # add the new legend data to the figure
   g.add_legend(legend_data=leg_data, title='Gender', label_order=list(leg_data))
   

3. @Serenity's answer works well but it doesn't check if a label is replaced by the correct new label. You can do so using an if-else block and make sure to replace a label with the correct label. Also, you can use legend instead of _legend.

   g = sns.lmplot(x='total_bill', y='tip', data=df, hue='sex', markers=["+", "."])
   g.legend.set_title("Gender")
   for label in g.legend.texts:
       if label.get_text() == "Male":
           label.set_text("man")
       else:
           label.set_text("woman")
   

All of the above options perform the following transformation where the legend is edited.

Answer 3

• If legend_out is set to True then legend is available through the g._legend property and it is a part of a figure. Seaborn legend is standard matplotlib legend object. Therefore you may change legend texts.
• Tested in python 3.8.11, matplotlib 3.4.3, seaborn 0.11.2

import seaborn as sns

# load the tips dataset
tips = sns.load_dataset("tips")

# plot
g = sns.lmplot(x="total_bill", y="tip", hue="smoker", data=tips, markers=["o", "x"], facet_kws={'legend_out': True})

# title
new_title = 'My title'
g._legend.set_title(new_title)
# replace labels
new_labels = ['label 1', 'label 2']
for t, l in zip(g._legend.texts, new_labels):
    t.set_text(l)

Another situation if legend_out is set to False. You have to define which axes has a legend (in below example this is axis number 0):

g = sns.lmplot(x="total_bill", y="tip", hue="smoker", data=tips, markers=["o", "x"], facet_kws={'legend_out': False})

# check axes and find which is have legend
leg = g.axes.flat[0].get_legend()
new_title = 'My title'
leg.set_title(new_title)
new_labels = ['label 1', 'label 2']
for t, l in zip(leg.texts, new_labels):
    t.set_text(l)

Moreover you may combine both situations and use this code:

g = sns.lmplot(x="total_bill", y="tip", hue="smoker", data=tips, markers=["o", "x"], facet_kws={'legend_out': True})

# check axes and find which is have legend
for ax in g.axes.flat:
    leg = g.axes.flat[0].get_legend()
    if not leg is None: break
# or legend may be on a figure
if leg is None: leg = g._legend

# change legend texts
new_title = 'My title'
leg.set_title(new_title)
new_labels = ['label 1', 'label 2']
for t, l in zip(leg.texts, new_labels):
    t.set_text(l)

This code works for any seaborn plot which is based on Grid class.

Answer 4

Took me a while to read through the above. This was the answer for me:

import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")

g = sns.lmplot(
    x="total_bill", 
    y="tip", 
    hue="smoker", 
    data=tips,  
    legend=False
)

plt.legend(title='Smoker', loc='upper left', labels=['Hell Yeh', 'Nah Bruh'])
plt.show(g)

Reference this for more arguments: matplotlib.pyplot.legend