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我有一个pandas框架

的数据
我试着画seaborn箱线图

sns.boxplot(data=df_filtered[df_filtered['Class'] == 1].drop(['Plot', 'Class'], axis=1))

字符串
但它又回来了

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

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问题是，我在不同的数据上使用了完全相同的命令，它工作得很好。我已经用这种方式制作了许多箱线图。此外，matplotlib版本的工作原理：

plt.boxplot(x=df_filtered[df_filtered['Class'] == 1].drop(['Plot', 'Class'], axis=1))

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的
显然，我可以只使用matplotlib命令，但这样我就必须重做所有以前的图，这是不好的，我想知道到底出了什么问题。这是一个bug，还是我错过了什么？
编辑：以下是完整的traceback：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_7004\328781716.py in ?()
     11 df_filtered_sorted = df_filtered.sort_values(by='Class')
     12 
---> 13 class_labels = df_filtered_sorted['Class'].unique()
     14 n_rows = len(class_labels) // 2 + len(class_labels) % 2
     15 n_cols = 2
     16 

~\miniconda3\envs\general\lib\site-packages\seaborn\categorical.py in ?(data, x, y, hue, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth, whis, ax, **kwargs)
   2227     dodge=True, fliersize=5, linewidth=None, whis=1.5, ax=None,
   2228     **kwargs
   2229 ):
   2230 
-> 2231     plotter = _BoxPlotter(x, y, hue, data, order, hue_order,
   2232                           orient, color, palette, saturation,
   2233                           width, dodge, fliersize, linewidth)
   2234 

~\miniconda3\envs\general\lib\site-packages\seaborn\categorical.py in ?(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth)
    781     def __init__(self, x, y, hue, data, order, hue_order,
    782                  orient, color, palette, saturation,
    783                  width, dodge, fliersize, linewidth):
    784 
--> 785         self.establish_variables(x, y, hue, data, orient, order, hue_order)
    786         self.establish_colors(color, palette, saturation)
    787 
    788         self.dodge = dodge

~\miniconda3\envs\general\lib\site-packages\seaborn\categorical.py in ?(self, x, y, hue, data, orient, order, hue_order, units)
    458                 if order is None:
    459                     order = []
    460                     # Reduce to just numeric columns
    461                     for col in data:
--> 462                         if variable_type(data[col]) == "numeric":
    463                             order.append(col)
    464                 plot_data = data[order]
    465                 group_names = order

~\miniconda3\envs\general\lib\site-packages\seaborn\_oldcore.py in ?(vector, boolean_type)
   1498     if pd.api.types.is_categorical_dtype(vector):
   1499         return VariableType("categorical")
   1500 
   1501     # Special-case all-na data, which is always "numeric"
-> 1502     if pd.isna(vector).all():
   1503         return VariableType("numeric")
   1504 
   1505     # Special-case binary/boolean data, allow caller to determine

~\miniconda3\envs\general\lib\site-packages\pandas\core\generic.py in ?(self)
   1517     @final
   1518     def __nonzero__(self) -> NoReturn:
-> 1519         raise ValueError(
   1520             f"The truth value of a {type(self).__name__} is ambiguous. "
   1521             "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
   1522         )

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

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