Using a data frame and this code in Python, I was able to create a plot:
g = sns.lmplot('credibility', 'percentWatched', data=data, hue = 'millennial', markers = ["+", "."], x_jitter = True, y_jitter = True, size=5)
g.set(xlabel = 'Credibility Ranking\n ← Low High →', ylabel = 'Percent of Video Watched [%]')
However having the legend say "+ 0" and ". 1" isn't very helpful to readers. How can I edit the legend's labels? Ideally instead of saying 'millennial' it would say 'Generation' and "+ Millennial" ". Older Generations"
If legend_out
is set to True
then legend is available thought g._legend
property and it is a part of a figure. Seaborn legend is standard matplotlib legend object. Therefore you may change legend texts like:
import seaborn as sns
tips = sns.load_dataset("tips")
g = sns.lmplot(x="total_bill", y="tip", hue="smoker",
data=tips, markers=["o", "x"], 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)
sns.plt.show()
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):
import seaborn as sns
tips = sns.load_dataset("tips")
g = sns.lmplot(x="total_bill", y="tip", hue="smoker",
data=tips, markers=["o", "x"], 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)
sns.plt.show()
Moreover you may combine both situations and use this code:
import seaborn as sns
tips = sns.load_dataset("tips")
g = sns.lmplot(x="total_bill", y="tip", hue="smoker",
data=tips, markers=["o", "x"], 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)
sns.plt.show()
This code works for any seaborn plot which is based on Grid
class.