对于一个海上出生的孩子来说。热图，你可以旋转这些(基于@Aman的回答)

pandas_frame = pd.DataFrame(data, index=names, columns=names)
heatmap = seaborn.heatmap(pandas_frame)
loc, labels = plt.xticks()
heatmap.set_xticklabels(labels, rotation=45)
heatmap.set_yticklabels(labels[::-1], rotation=45) # reversed order for y

如果有人想知道如何为clustermap CorrGrids(给定海运示例的一部分):

import seaborn as sns
import matplotlib.pyplot as plt
sns.set(context="paper", font="monospace")

# Load the datset of correlations between cortical brain networks
df = sns.load_dataset("brain_networks", header=[0, 1, 2], index_col=0)
corrmat = df.corr()

# Set up the matplotlib figure
f, ax = plt.subplots(figsize=(12, 9))

# Draw the heatmap using seaborn
g=sns.clustermap(corrmat, vmax=.8, square=True)
rotation = 90 
for i, ax in enumerate(g.fig.axes):   ## getting all axes of the fig object
     ax.set_xticklabels(ax.get_xticklabels(), rotation = rotation)


g.fig.show()

这仍然是一个matplotlib对象。试试这个:

# <your code here>
locs, labels = plt.xticks()
plt.setp(labels, rotation=45)

可以使用matplotlib.pyplot.xticks实现这一点

import matplotlib.pyplot as plt

plt.xticks(rotation = 'vertical')

# Or use degrees explicitly 

degrees = 70  # Adjust according to one's preferences/needs
plt.xticks(rotation=degrees)

这里有一个例子可以说明它是如何工作的。

如果标签的名字很长，可能很难正确。使用catplot对我来说很有效的解决方案是:

import matplotlib.pyplot as plt
fig = plt.gcf()
fig.autofmt_xdate()

对于一个海上出生的孩子来说。热图，你可以旋转这些(基于@Aman的回答)

pandas_frame = pd.DataFrame(data, index=names, columns=names)
heatmap = seaborn.heatmap(pandas_frame)
loc, labels = plt.xticks()
heatmap.set_xticklabels(labels, rotation=45)
heatmap.set_yticklabels(labels[::-1], rotation=45) # reversed order for y