scipy.cluster.hierarchy.dedrogram "above_threshold_color=above_threshold_color“中的错误

Question

我试图用下面的代码在Python3.5中使用ciply0.18.1(在mac上)可视化一个树状图：

import numpy as np
import pandas as pd
import scipy as sci
from matplotlib import pyplot as plt
from scipy.cluster.hierarchy import dendrogram, linkage
from scipy.cluster.hierarchy import cophenet
from scipy.spatial.distance import pdist

data = pd.read_csv("data.csv", header = 0)
data_clean = data.dropna()

cluster = data_clean[['HI','GO', 'PA', 'TE', 'GC', 'FU', 'LA']]
cluster = np.array(cluster)
cluster

data_dist = pdist(cluster) 
data_link = linkage(data_dist)

plt.figure(figsize=(25, 10))
plt.title('Hierarchical Clustering Dendrogram')
plt.xlabel('sample index')
plt.ylabel('distance')
dendrogram(data_link)

但是它返回这个错误。

---------------------------------------------------------------------------
RecursionError                            Traceback (most recent call last)
<ipython-input-14-57671852a042> in <module>()
  1 plt.figure(figsize=(7, 5))
----> 2 dendrogram(data_link)#, labels= ('HI','GO', 'PA', 'TE', 'GC', 'FU', 'LA'))
  3 plt.title('Hierarchical Clustering Dendrogram')#'Dendrograma de Clusterización Jerárquiza')
  4 plt.xlabel('sample index')#'Islas')
  5 plt.ylabel('distance')#'Disimilitud de Jaccard')

 /Users/Irbin/anaconda/lib/python3.5/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)
2289         contraction_marks=contraction_marks,
2290         link_color_func=link_color_func,
 -> 2291         above_threshold_color=above_threshold_color)
2292 
2293     if not no_plot:

/Users/Irbin/anaconda/lib/python3.5/site-packages/scipy/cluster/hierarchy.py in _dendrogram_calculate_info(Z, p, truncate_mode, color_threshold, get_leaves, orientation, labels, count_sort, distance_sort, show_leaf_counts, i, iv, ivl, n, icoord_list, dcoord_list, lvs, mhr, current_color, color_list, currently_below_threshold, leaf_label_func, level, contraction_marks, link_color_func, above_threshold_color)
2577             level=level + 1, contraction_marks=contraction_marks,
2578             link_color_func=link_color_func,
 -> 2579             above_threshold_color=above_threshold_color)
2580 
2581     max_dist = max(uamd, ubmd, h)

/Users/Irbin/anaconda/lib/python3.5/site-packages/scipy/cluster/hierarchy.py in _dendrogram_calculate_info(Z, p, truncate_mode, color_threshold, get_leaves, orientation, labels, count_sort, distance_sort, show_leaf_counts, i, iv, ivl, n, icoord_list, dcoord_list, lvs, mhr, current_color, color_list, currently_below_threshold, leaf_label_func, level, contraction_marks, link_color_func, above_threshold_color)
2577             level=level + 1, contraction_marks=contraction_marks,
2578             link_color_func=link_color_func,
 -> 2579             above_threshold_color=above_threshold_color)
2580 
2581     max_dist = max(uamd, ubmd, h)

/Users/Irbin/anaconda/lib/python3.5/site-packages/scipy/cluster/hierarchy.py in _dendrogram_calculate_info(Z, p, truncate_mode, color_threshold, get_leaves, orientation, labels, count_sort, distance_sort, show_leaf_counts, i, iv, ivl, n, icoord_list, dcoord_list, lvs, mhr, current_color, color_list, currently_below_threshold, leaf_label_func, level, contraction_marks, link_color_func, above_threshold_color)
2577             level=level + 1, contraction_marks=contraction_marks,
2578             link_color_func=link_color_func,
 -> 2579             above_threshold_color=above_threshold_color)
2580 
2581     max_dist = max(uamd, ubmd, h)

/Users/Irbin/anaconda/lib/python3.5/site-packages/scipy/cluster/hierarchy.py in _dendrogram_calculate_info
         levellevel   contraction_markscontraction_marks
         link_color_funclink_color_func

实际上，在错误报告中，使用max_dist = max(uamd, ubmd, h)的bloques被重复了太多次。分析似乎很好，但我无法绘制树状图。错误可能是什么？

Answer 1

我已经解决了。我只需要把我的数据转过来。错误被认为我的集群中有太多的组，因此Python没有足够的颜色来可视化它们。