数据挖掘 - 树状图：ValueError：Series 的真值不明确。使用 a.empty、a.bool()、a.item()、a.any() 或 a.all() - 吾爱随笔录

我正在尝试绘制一个树状图来聚类数据，但这个错误阻止了我。我的约会在这里。

我首先选择了要使用的列：

    df_euro = pd.read_csv('https://assets.datacamp.com/production/repositories/655/datasets/2a1f3ab7bcc76eef1b8e1eb29afbd54c4ebf86f2/eurovision-2016.csv')
   samples = df_euro.iloc[:, 2:7].values[:42]
   country_names = df_euro.iloc[:, 1].values[:42]
            
        # Calculate the linkage: mergings
            mergings = linkage(samples , method = 'complete')
            # Plot the dendrogram
            dendrogram(
                mergings,
                labels = y,
                leaf_rotation = 90,
                leaf_font_size = 6
            )
            plt.show()

但是我收到了这个我无法理解的错误。我用谷歌搜索并检查两者是否具有相同的形状 (1066,5) 和 (1066,)。features 和 country_names 都没有 NA。

我知道问题出在标签上，因为当我删除它时它运行良好，但我找不到解决它的方法。任何帮助将不胜感激。或者，如何将标签添加到树状图中？

我得到的错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-113-7fffdc847e5e> in <module>
      4 mergings = linkage(feat, method = 'complete')
      5 # Plot the dendrogram
----> 6 dendrogram(
      7     mergings,
      8     labels = target_col,

C:\ProgramData\Anaconda3\lib\site-packages\scipy\cluster\hierarchy.py in dendrogram(Z, p, truncate_mode, color_threshold, get_leaves, orientation, labels, count_sort, distance_sort, show_leaf_counts, no_plot, no_labels, leaf_font_size, leaf_rotation, leaf_label_func, show_contracted, link_color_func, ax, above_threshold_color)
   3275                          "'bottom', or 'right'")
   3276 
-> 3277     if labels and Z.shape[0] + 1 != len(labels):
   3278         raise ValueError("Dimensions of Z and labels must be consistent.")
   3279 

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   1476 
   1477     def __nonzero__(self):
-> 1478         raise ValueError(
   1479             f"The truth value of a {type(self).__name__} is ambiguous. "
   1480             "Use a.empty, a.bool(), a.item(), a.any() or a.all()."

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