pycharm使用matplotlib画图出错failed to start because it could not find or load the Qt platform plugins...

这里有很多博主说更改环境变量，即

但是这样会引起其他软件的冲突，比如onedrive，还有Microsoft SQL Server Management Studio 18也连接不上主机用户。

我找到另一个方法，就是再加一句

matplotlib.use('TKAgg')

就可以了，

下面是一个泰坦尼克号生还者预测的一段代码，利用泰坦尼克号数据建立了回归模型，画出混淆矩阵。matplotlib.use('TKAgg')运用

import pandas as pd
import statsmodels.api as sma
from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay
import matplotlib.pyplot as plt
from pylab import *
mpl.rcParams['font.sans-serif'] = ['SimHei']

train_set = pd.read_csv('D:\我的文档\研一课程\数理统计\Titanic.csv')
train_set['Sex'].replace(['female', 'male'], [0, 1], inplace=True)  # onehot-encoding
print(train_set.isnull().any())  # 统计data里每一列是否有空值
print(train_set.head())          # 查看数据的前五行

train_set['Q'] = train_set.Embarked.apply(lambda x: 1 if x == 'Q' else 0)
train_set['S'] = train_set.Embarked.apply(lambda x: 1 if x == 'S' else 0)
train_set['C'] = train_set.Embarked.apply(lambda x: 1 if x == 'C' else 0)
# print(train_set['Q'])
y = train_set['Survived']
X = train_set[[
    'Pclass',
    'Sex',
    'Age',
    'SibSp',
    'Parch',
    'Fare',
    'Q',
    'S',
    # 'C',
]]
print(train_set.head())
results = sma.Logit(y, X).fit()
print(results.summary())

y_predict = results.predict(X)
y_predict = round(y_predict, 0)
cm = confusion_matrix(y, y_predict)
dl = ['死亡人数', '生存人数']
disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=dl)
disp = ConfusionMatrixDisplay(confusion_matrix=cm)
matplotlib.use('TKAgg')
disp.plot()
plt.xticks(fontsize=15)
plt.yticks(fontsize=15)
plt.ylabel('实际情况', fontsize=15)
plt.xlabel('预测情况', fontsize=15)
plt.show()

新手上路，多多指教，文明留言！