How to split seaborn legend into multiple columns?
Question:
I use a relplot with different hue and style and would like to show the respective legend entries besides instead of below each other.
So currently I get a legend like this:
Instead I would like to have a single legend looking something like this:
How can this be done?
I tried setting the following but that had no effect:
plot._legend
leg._ncol = 2
leg.handleheight = 1 # restricting the height
Minimal working example to solve this problem:
import pandas as pd
import seaborn as sns
columns = ['category1', 'category2', 'category3', 'time', 'value']
data = [['content1', 'other1', 'critera1', 0, 0.1], ['content1', 'other1', 'critera1', 1, 0.4], ['content1', 'other1', 'critera1', 2, 0.7], ['content2', 'other1', 'critera1', 0, 0.2], ['content2', 'other1', 'critera1', 1, 0.6], ['content2', 'other1', 'critera1', 2, 0.8], ['content1', 'other2', 'critera1', 0, 0.0], ['content1', 'other2', 'critera1', 1, 0.2], ['content1', 'other2', 'critera1', 2, 0.8], ['content2', 'other2', 'critera1', 0, 0.3], ['content2', 'other2', 'critera1', 1, 0.6], ['content2', 'other2', 'critera1', 2, 0.5], [
'content1', 'other1', 'critera2', 0, 0.1], ['content1', 'other1', 'critera2', 1, 0.4], ['content1', 'other1', 'critera2', 2, 0.7], ['content2', 'other1', 'critera2', 0, 0.2], ['content2', 'other1', 'critera2', 1, 0.6], ['content2', 'other1', 'critera2', 2, 0.8], ['content1', 'other2', 'critera2', 0, 0.0], ['content1', 'other2', 'critera2', 1, 0.2], ['content1', 'other2', 'critera2', 2, 0.8], ['content2', 'other2', 'critera2', 0, 0.3], ['content2', 'other2', 'critera2', 1, 0.6], ['content2', 'other2', 'critera2', 2, 0.5], ]
df = pd.DataFrame(data, columns=columns)
plot = sns.relplot(x='time', y='value', col='category3', hue='category1', style='category2', kind="line", col_wrap=2, data=df)
leg = plot._legend
leg.set_bbox_to_anchor((0.5, 1.3, 0, 0))
leg._loc = 9
Answers:
Since you seem to want to place the legend above the plots, I would instruct seaborn to not reserve space on the right for the legend using legend_out=False. Then it’s just a matter of getting the handles and labels created by seaborn, and generate a new legend using ncol=2. Note that this will only work well if you have the same number of elements in both columns, otherwise things will get messy.
plot = sns.relplot(x='time', y='value', col='category3', hue='category1', style='category2', kind="line", col_wrap=2, data=df, facet_kws=dict(legend_out=False))
h,l = plot.axes[0].get_legend_handles_labels()
plot.axes[0].legend_.remove()
plot.fig.legend(h,l, ncol=2) # you can specify any location parameter you want here
Final solution thanks to @DizietAsahi
import pandas as pd
import seaborn as sns
columns = ['category1', 'category2', 'category3', 'time', 'value']
data = [['content1', 'other1', 'critera1', 0, 0.1], ['content1', 'other1', 'critera1', 1, 0.4], ['content1', 'other1', 'critera1', 2, 0.7], ['content2', 'other1', 'critera1', 0, 0.2], ['content2', 'other1', 'critera1', 1, 0.6], ['content2', 'other1', 'critera1', 2, 0.8], ['content1', 'other2', 'critera1', 0, 0.0], ['content1', 'other2', 'critera1', 1, 0.2], ['content1', 'other2', 'critera1', 2, 0.8], ['content2', 'other2', 'critera1', 0, 0.3], ['content2', 'other2', 'critera1', 1, 0.6], ['content2', 'other2', 'critera1', 2, 0.5], [
'content1', 'other1', 'critera2', 0, 0.1], ['content1', 'other1', 'critera2', 1, 0.4], ['content1', 'other1', 'critera2', 2, 0.7], ['content2', 'other1', 'critera2', 0, 0.2], ['content2', 'other1', 'critera2', 1, 0.6], ['content2', 'other1', 'critera2', 2, 0.8], ['content1', 'other2', 'critera2', 0, 0.0], ['content1', 'other2', 'critera2', 1, 0.2], ['content1', 'other2', 'critera2', 2, 0.8], ['content2', 'other2', 'critera2', 0, 0.3], ['content2', 'other2', 'critera2', 1, 0.6], ['content2', 'other2', 'critera2', 2, 0.5], ]
df = pd.DataFrame(data, columns=columns)
plot = sns.relplot(x='time', y='value', col='category3', hue='category1', style='category2', kind="line",
col_wrap=2, data=df)
handles, labels = plot.axes[0].get_legend_handles_labels()
plot._legend.remove()
plot.fig.legend(handles, labels, ncol=2, loc='upper center',
bbox_to_anchor=(0.5, 1.15), frameon=False)
Use ncol
ax = sns.barplot(x="X", y="Y", data=data)
ax.legend(loc='upper left',ncol=2, title="Title")
The answer given by @DizietAsahi was not working for my case. However, I was able to do this with the sns.move_legend() utility function, which can be used to modify the legend of a plot.
sns.move_legend(ax, "upper center", bbox_to_anchor=(0.5, 1.15),
ncol=2)
import seaborn as sns
import matplotlib.pyplot as plt
# legend and other functionalities will be controlled by matplotlib.pyplot
fig, ax = plt.subplots()
# your plot (it is generated by seaborn)
sns.relplot(...)
# position your legend
lgd = ax.legend(loc = 'upper center', bbox_to_anchor = (0.5, -0.13),
fancybox = True, shadow = True, ncol = 2)
# here bbox_extra_artists and bbox_inches = 'tight' will make sure the saved figure is not trimming the legend if it goes outside of the figure
plt.savefig("plot.jpg", bbox_extra_artists = (lgd,), bbox_inches = 'tight')
Note: You may need to adjust bbox_to_anchor if the legend overlaps the axis labels.
References:
I use a relplot with different hue and style and would like to show the respective legend entries besides instead of below each other.
So currently I get a legend like this:
Instead I would like to have a single legend looking something like this:
How can this be done?
I tried setting the following but that had no effect:
plot._legend
leg._ncol = 2
leg.handleheight = 1 # restricting the height
Minimal working example to solve this problem:
import pandas as pd
import seaborn as sns
columns = ['category1', 'category2', 'category3', 'time', 'value']
data = [['content1', 'other1', 'critera1', 0, 0.1], ['content1', 'other1', 'critera1', 1, 0.4], ['content1', 'other1', 'critera1', 2, 0.7], ['content2', 'other1', 'critera1', 0, 0.2], ['content2', 'other1', 'critera1', 1, 0.6], ['content2', 'other1', 'critera1', 2, 0.8], ['content1', 'other2', 'critera1', 0, 0.0], ['content1', 'other2', 'critera1', 1, 0.2], ['content1', 'other2', 'critera1', 2, 0.8], ['content2', 'other2', 'critera1', 0, 0.3], ['content2', 'other2', 'critera1', 1, 0.6], ['content2', 'other2', 'critera1', 2, 0.5], [
'content1', 'other1', 'critera2', 0, 0.1], ['content1', 'other1', 'critera2', 1, 0.4], ['content1', 'other1', 'critera2', 2, 0.7], ['content2', 'other1', 'critera2', 0, 0.2], ['content2', 'other1', 'critera2', 1, 0.6], ['content2', 'other1', 'critera2', 2, 0.8], ['content1', 'other2', 'critera2', 0, 0.0], ['content1', 'other2', 'critera2', 1, 0.2], ['content1', 'other2', 'critera2', 2, 0.8], ['content2', 'other2', 'critera2', 0, 0.3], ['content2', 'other2', 'critera2', 1, 0.6], ['content2', 'other2', 'critera2', 2, 0.5], ]
df = pd.DataFrame(data, columns=columns)
plot = sns.relplot(x='time', y='value', col='category3', hue='category1', style='category2', kind="line", col_wrap=2, data=df)
leg = plot._legend
leg.set_bbox_to_anchor((0.5, 1.3, 0, 0))
leg._loc = 9
Since you seem to want to place the legend above the plots, I would instruct seaborn to not reserve space on the right for the legend using legend_out=False. Then it’s just a matter of getting the handles and labels created by seaborn, and generate a new legend using ncol=2. Note that this will only work well if you have the same number of elements in both columns, otherwise things will get messy.
plot = sns.relplot(x='time', y='value', col='category3', hue='category1', style='category2', kind="line", col_wrap=2, data=df, facet_kws=dict(legend_out=False))
h,l = plot.axes[0].get_legend_handles_labels()
plot.axes[0].legend_.remove()
plot.fig.legend(h,l, ncol=2) # you can specify any location parameter you want here
Final solution thanks to @DizietAsahi
import pandas as pd
import seaborn as sns
columns = ['category1', 'category2', 'category3', 'time', 'value']
data = [['content1', 'other1', 'critera1', 0, 0.1], ['content1', 'other1', 'critera1', 1, 0.4], ['content1', 'other1', 'critera1', 2, 0.7], ['content2', 'other1', 'critera1', 0, 0.2], ['content2', 'other1', 'critera1', 1, 0.6], ['content2', 'other1', 'critera1', 2, 0.8], ['content1', 'other2', 'critera1', 0, 0.0], ['content1', 'other2', 'critera1', 1, 0.2], ['content1', 'other2', 'critera1', 2, 0.8], ['content2', 'other2', 'critera1', 0, 0.3], ['content2', 'other2', 'critera1', 1, 0.6], ['content2', 'other2', 'critera1', 2, 0.5], [
'content1', 'other1', 'critera2', 0, 0.1], ['content1', 'other1', 'critera2', 1, 0.4], ['content1', 'other1', 'critera2', 2, 0.7], ['content2', 'other1', 'critera2', 0, 0.2], ['content2', 'other1', 'critera2', 1, 0.6], ['content2', 'other1', 'critera2', 2, 0.8], ['content1', 'other2', 'critera2', 0, 0.0], ['content1', 'other2', 'critera2', 1, 0.2], ['content1', 'other2', 'critera2', 2, 0.8], ['content2', 'other2', 'critera2', 0, 0.3], ['content2', 'other2', 'critera2', 1, 0.6], ['content2', 'other2', 'critera2', 2, 0.5], ]
df = pd.DataFrame(data, columns=columns)
plot = sns.relplot(x='time', y='value', col='category3', hue='category1', style='category2', kind="line",
col_wrap=2, data=df)
handles, labels = plot.axes[0].get_legend_handles_labels()
plot._legend.remove()
plot.fig.legend(handles, labels, ncol=2, loc='upper center',
bbox_to_anchor=(0.5, 1.15), frameon=False)
Use ncol
ax = sns.barplot(x="X", y="Y", data=data)
ax.legend(loc='upper left',ncol=2, title="Title")
The answer given by @DizietAsahi was not working for my case. However, I was able to do this with the sns.move_legend() utility function, which can be used to modify the legend of a plot.
sns.move_legend(ax, "upper center", bbox_to_anchor=(0.5, 1.15),
ncol=2)
import seaborn as sns
import matplotlib.pyplot as plt
# legend and other functionalities will be controlled by matplotlib.pyplot
fig, ax = plt.subplots()
# your plot (it is generated by seaborn)
sns.relplot(...)
# position your legend
lgd = ax.legend(loc = 'upper center', bbox_to_anchor = (0.5, -0.13),
fancybox = True, shadow = True, ncol = 2)
# here bbox_extra_artists and bbox_inches = 'tight' will make sure the saved figure is not trimming the legend if it goes outside of the figure
plt.savefig("plot.jpg", bbox_extra_artists = (lgd,), bbox_inches = 'tight')
Note: You may need to adjust bbox_to_anchor if the legend overlaps the axis labels.
References: