问题
Let's say I want to make a bar plot where the hue of the bars represents some continuous quantity. e.g.
import seaborn as sns
titanic = sns.load_dataset("titanic")
g = titanic.groupby('pclass')
survival_rates = g['survived'].mean()
n = g.size()
ax = sns.barplot(x=n.index, y=n,
hue=survival_rates, palette='Reds',
dodge=False,
)
ax.set_ylabel('n passengers')
The legend here is kind of silly, and gets even worse the more bars I plot. What would make most sense is a colorbar (such as are used when calling sns.heatmap). Is there a way to make seaborn do this?
回答1:
The other answer is a bit hacky. So a more stringent solution, without producing plots that are deleted afterwards, would involve the manual creation of a ScalarMappable as input for the colorbar.
import matplotlib.pyplot as plt
import seaborn as sns
titanic = sns.load_dataset("titanic")
g = titanic.groupby('pclass')
survival_rates = g['survived'].mean()
n = g.size()
norm = plt.Normalize(survival_rates.min(), survival_rates.max())
sm = plt.cm.ScalarMappable(cmap="Reds", norm=norm)
sm.set_array([])
ax = sns.barplot(x=n.index, y=n, hue=survival_rates, palette='Reds',
dodge=False)
ax.set_ylabel('n passengers')
ax.get_legend().remove()
ax.figure.colorbar(sm)
plt.show()
回答2:
You can try this:
import matplotlib.pyplot as plt
import seaborn as sns
titanic = sns.load_dataset("titanic")
g = titanic.groupby('pclass')
survival_rates = g['survived'].mean()
n = g.size()
plot = plt.scatter(n.index, n, c=survival_rates, cmap='Reds')
plt.clf()
plt.colorbar(plot)
ax = sns.barplot(x=n.index, y=n, hue=survival_rates, palette='Reds', dodge=False)
ax.set_ylabel('n passengers')
ax.legend_.remove()
Output:
来源:https://stackoverflow.com/questions/49761221/make-seaborn-show-a-colorbar-instead-of-a-legend-when-using-hue-in-a-bar-plot