Seaborn ValueError：零大小数组到没有标识的缩减操作最小值

Posted 2023-03-12

【中文标题】Seaborn ValueError：零大小数组到没有标识的缩减操作最小值

【英文标题】：Seaborn ValueError: zero-size array to reduction operation minimum which has no identity

【发布时间】：2020-12-06 03:51:21

【问题描述】：

我从他们自己的website 运行了这个散点图 seaborn 示例，

import seaborn as sns; sns.set()
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")

# this works:
ax = sns.scatterplot(x="total_bill", y="tip", data=tips)

# But adding 'hue' gives the error below:
ax = sns.scatterplot(x="total_bill", y="tip", hue="time", data=tips)

这个错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
e:\Anaconda3\lib\site-packages\IPython\core\formatters.py in __call__(self, obj)
    339                 pass
    340             else:
--> 341                 return printer(obj)
    342             # Finally look for special method names
    343             method = get_real_method(obj, self.print_method)

e:\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in <lambda>(fig)
    246 
    247     if 'png' in formats:
--> 248         png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
    249     if 'retina' in formats or 'png2x' in formats:
    250         png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))

e:\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in print_figure(fig, fmt, bbox_inches, **kwargs)
    130         FigureCanvasBase(fig)
    131 
--> 132     fig.canvas.print_figure(bytes_io, **kw)
    133     data = bytes_io.getvalue()
    134     if fmt == 'svg':

e:\Anaconda3\lib\site-packages\matplotlib\backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2191                            else suppress())
   2192                     with ctx:
-> 2193                         self.figure.draw(renderer)
   2194 
   2195                     bbox_inches = self.figure.get_tightbbox(

e:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
     39                 renderer.start_filter()
     40 
---> 41             return draw(artist, renderer, *args, **kwargs)
     42         finally:
     43             if artist.get_agg_filter() is not None:

e:\Anaconda3\lib\site-packages\matplotlib\figure.py in draw(self, renderer)
   1861 
   1862             self.patch.draw(renderer)
-> 1863             mimage._draw_list_compositing_images(
   1864                 renderer, self, artists, self.suppressComposite)
   1865 

e:\Anaconda3\lib\site-packages\matplotlib\image.py in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    129     if not_composite or not has_images:
    130         for a in artists:
--> 131             a.draw(renderer)
    132     else:
    133         # Composite any adjacent images together

e:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
     39                 renderer.start_filter()
     40 
---> 41             return draw(artist, renderer, *args, **kwargs)
     42         finally:
     43             if artist.get_agg_filter() is not None:

e:\Anaconda3\lib\site-packages\matplotlib\cbook\deprecation.py in wrapper(*inner_args, **inner_kwargs)
    409                          else deprecation_addendum,
    410                 **kwargs)
--> 411         return func(*inner_args, **inner_kwargs)
    412 
    413     return wrapper

e:\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in draw(self, renderer, inframe)
   2746             renderer.stop_rasterizing()
   2747 
-> 2748         mimage._draw_list_compositing_images(renderer, self, artists)
   2749 
   2750         renderer.close_group('axes')

e:\Anaconda3\lib\site-packages\matplotlib\image.py in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    129     if not_composite or not has_images:
    130         for a in artists:
--> 131             a.draw(renderer)
    132     else:
    133         # Composite any adjacent images together

e:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
     39                 renderer.start_filter()
     40 
---> 41             return draw(artist, renderer, *args, **kwargs)
     42         finally:
     43             if artist.get_agg_filter() is not None:

e:\Anaconda3\lib\site-packages\matplotlib\collections.py in draw(self, renderer)
    929     def draw(self, renderer):
    930         self.set_sizes(self._sizes, self.figure.dpi)
--> 931         Collection.draw(self, renderer)
    932 
    933 

e:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
     39                 renderer.start_filter()
     40 
---> 41             return draw(artist, renderer, *args, **kwargs)
     42         finally:
     43             if artist.get_agg_filter() is not None:

e:\Anaconda3\lib\site-packages\matplotlib\collections.py in draw(self, renderer)
    383             else:
    384                 combined_transform = transform
--> 385             extents = paths[0].get_extents(combined_transform)
    386             if (extents.width < self.figure.bbox.width
    387                     and extents.height < self.figure.bbox.height):

e:\Anaconda3\lib\site-packages\matplotlib\path.py in get_extents(self, transform, **kwargs)
    601                 xys.append(curve([0, *dzeros, 1]))
    602             xys = np.concatenate(xys)
--> 603         return Bbox([xys.min(axis=0), xys.max(axis=0)])
    604 
    605     def intersects_path(self, other, filled=True):

e:\Anaconda3\lib\site-packages\numpy\core\_methods.py in _amin(a, axis, out, keepdims, initial, where)
     41 def _amin(a, axis=None, out=None, keepdims=False,
     42           initial=_NoValue, where=True):
---> 43     return umr_minimum(a, axis, None, out, keepdims, initial, where)
     44 
     45 def _sum(a, axis=None, dtype=None, out=None, keepdims=False,

ValueError: zero-size array to reduction operation minimum which has no identity

昨天确实有效。但是，我运行了使用 conda update --all 的更新。有什么变化吗？

发生了什么事？

我在 Linux 机器上运行 python。

Pandas:  1.1.0.
Numpy:   1.19.1.
Seaborn api:  0.10.1.

【参考方案1】：

matplotlib==3.3.2 似乎已解决此问题。 seaborn: Scatterplot fails with matplotlib==3.3.1 #2194 带matplotlib版本3.3.1 一种解决方法是使用.tolist() 将list 发送到hue 使用hue=tips.time.tolist()。 正常行为会向图例添加title，但向hue 发送list 不会添加图例标题。 可以手动添加图例标题。

import seaborn as sns

# load data
tips = sns.load_dataset("tips")

# But adding 'hue' gives the error below:
ax = sns.scatterplot(x="total_bill", y="tip", hue=tips.time.tolist(), data=tips)
ax.legend(title='time')  # add a title to the legend

【参考方案2】：

鉴于 3.3.1 中的已知错误，我运行了 conda install -c conda-forge matplotlib==3.3.0。

一个正确的答案，但不是一个很好的解决方案。