我正在尝试使用以下内容绘制seaborn群集图(它也不适用于热图),没有NaN承认：

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

def plotClusterMap():
    a = pd.DataFrame(np.matrix('1 2; 3 4'))
    print a
    fig = plt.figure()
    sns.clustermap(a)
    plt.show()

a形式良好：

   0  1
0  1  2
1  3  4

控制台输出：

Traceback (most recent call last):
  File "main.py", line 78, in <module>
    main()
  File "main.py", line 72, in main
    heatmapPlotter.plotClusterMap()
  File "/Users/username/code.py", line 12, in plotClusterMap
    sns.clustermap(a)
  File "/Library/Python/2.7/site-packages/seaborn/matrix.py", line 895, in clustermap
    **kwargs)
  File "/Library/Python/2.7/site-packages/seaborn/matrix.py", line 813, in plot
    self.plot_matrix(colorbar_kws, mask, **kws)
  File "/Library/Python/2.7/site-packages/seaborn/matrix.py", line 803, in plot_matrix
    cbar_kws=colorbar_kws, mask=mask, **kws)
  File "/Library/Python/2.7/site-packages/seaborn/matrix.py", line 292, in heatmap
    plotter.plot(ax, cbar_ax, kwargs)
  File "/Library/Python/2.7/site-packages/seaborn/matrix.py", line 177, in plot
    if axis_ticklabels_overlap(xtl):
  File "/Library/Python/2.7/site-packages/seaborn/utils.py", line 374, in axis_ticklabels_overlap
    bboxes = [l.get_window_extent() for l in labels]
  File "/usr/local/lib/python2.7/site-packages/matplotlib/text.py", line 796, in get_window_extent
    raise RuntimeError('Cannot get window extent w/o renderer')
RuntimeError: Cannot get window extent w/o renderer

> Mac OSX：10.9 10.10.3(编辑)
> Seaborn：0.5.1
> Matplotlib：1.3.1(刚刚从1.4降级)
> Numpy：1.8.0
> Python：2.7.9

解决方法:

我使用的是Mac OS X 10.9.5,python 2.7.9,matplotlib 1.4.3和seaborn 0.5.1.我能够重现错误.

默认情况下,我使用macosx后端进行matplotlib.如果我将后端更改为qt4agg(需要PyQt4),tkagg或webagg,则代码可以正常工作.这是适合我的脚本：

import numpy as np
import pandas as pd

import matplotlib
matplotlib.use('qt4agg')  # Can also use 'tkagg' or 'webagg'

import matplotlib.pyplot as plt
import seaborn as sns


def plotClusterMap():
    a = pd.DataFrame(np.matrix('1 2; 3 4'))
    print a
    # fig = plt.figure()
    sns.clustermap(a)
    plt.show()


if __name__ == "__main__":
    plotClusterMap()

请注意,我注释掉了fig = plt.figure(). clustermap似乎创建了自己的数字.