决策树可视化时报0xb2的错误

我的代码：

-- coding: UTF-8 --

from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from sklearn import tree
import pandas as pd
import numpy as np
import pydotplus

if name == 'main':
with open('lenses.txt', 'r',encoding="unicode_escape") as fr: #加载文件
lenses = [inst.strip().split('\t') for inst in fr.readlines()] #处理文件
lenses_target = [] #提取每组数据的类别，保存在列表里
for each in lenses:
lenses_target.append(each[-1])
#print(lenses_target)

lensesLabels = ['age', 'prescript', 'astigmatic', 'tearRate']            #特征标签       
lenses_list = []                                                        #保存lenses数据的临时列表
lenses_dict = {}                                                        #保存lenses数据的字典，用于生成pandas
for each_label in lensesLabels:                                            #提取信息，生成字典
    for each in lenses:
        lenses_list.append(each[lensesLabels.index(each_label)])
    lenses_dict[each_label] = lenses_list
    lenses_list = []
# print(lenses_dict)                                                        #打印字典信息
lenses_pd = pd.DataFrame(lenses_dict)                                    #生成pandas.DataFrame
# print(lenses_pd)                                                        #打印pandas.DataFrame
le = LabelEncoder()                                                        #创建LabelEncoder()对象，用于序列化           
for col in lenses_pd.columns:                                            #序列化
    lenses_pd[col] = le.fit_transform(lenses_pd[col])
# print(lenses_pd)                                                        #打印编码信息

clf = tree.DecisionTreeClassifier(max_depth = 4)                        #创建DecisionTreeClassifier()类
clf.fit(lenses_pd.values.tolist(), lenses_target)                    #使用数据，构建决策树

dot_data=tree.export_graphviz(clf, out_file = None,                            #绘制决策树
                    feature_names = lenses_pd.keys(),
                    class_names = clf.classes_,
                    filled=True, impurity=False,
                    rounded=True,
                    special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data)
graph.write_pdf("tree.pdf")