尝试在 pandas 中使用 plt.contourf 绘制图形时如何解决此错误？

Question

在这个机器学习练习中，我想使用包含在 matplotlib 包中的 countourf 函数绘制一个二维图形。但我收到错误消息：模块'matplotlib.pyplot'没有属性'countourf'。我在下面的代码中指出了它。我使用的是anaconda3平台和Jupyter 6.0.1，我确信这个函数存在于matplotlib（版本3.1.1）中，但是，我不知道为什么会出现这个错误。谁能帮我度过这个阶段并策划我的达达？ Here is the link to find data:。提前谢谢你！

`Importing the Librairies`
import pandas as pd
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
import seaborn as sb
%matplotlib inline 

`Importing  the data`
SUV_data = pd.read_csv("C:/Users/Wolf/Documents/ExoData/Data Science Tutorial/archive/SocialNetworkAds.csv")
SUV_data

`Extratcting only the dependant variables`
x = SUV_data.iloc[:, [2,3]].values

`Extratcting only the independant variables`
y = SUV_data.iloc[:, 4].values

print("x_dependent variables = " +str(x))
print("y_independent variables = " +str(y))

x.shape, y.shape
((400, 2), (400,))

`Plotting of a map showing how the dependent and independant variables are correlated with each other(facultative)`
YES_map = sb.heatmap(SUV_data.corr())

`Splitting the data into training and set models`
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size = 0.25, random_state = 0)

X_train.shape, y_train.shape
((300, 2), (300,))

`Fitting logistic regression to training data`
from sklearn.linear_model import LogisticRegression
classifier = LogisticRegression(random_state =0)
classifier.fit(X_train, y_train)

`Predicting the test set esults`
y_pred = classifier.predict(X_test)
y_pred

`Visualize the Training set Results`
from matplotlib.colors import ListedColormap
X_set, y_set = X_train, y_train
X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.5), np.arange(start = X_set[:, 1].min() -1, stop = X_set[:, 1].max() + 1, step = 0.5))
plt.countourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape), alpha = 0.75, cmap = ListedColormap(('red', 'green')))
plt.xlim(X1.mmin(), X1.max())
plt.ylim(X2.min(), X2.max())
for i, j in enumerate(np.unique(y_set)):
    plt.scatter(X_set[y_set == j, 0], X_set[y_set == j, 1], c = ListedColormap(('red', 'green'))(i), label = j)
plt.title('Logistic Regression (Training set)')
plt.xlabel('Age')
plt.ylabel('Estimated Salary')
plt.legend()
plt.show()

AttributeError                            Traceback (most recent call last)
<ipython-input-27-7bff781bd170> in <module>
      3 X_set, y_set = X_train, y_train
      4 X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.5), np.arange(start = X_set[:, 1].min() -1, stop = X_set[:, 1].max() + 1, step = 0.5))
----> 5 ax = plt.countourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape), alpha = 0.75, cmap = ListedColormap(('red', 'green')))
      6 plt.xlim(X1.mmin(), X1.max())
      7 plt.ylim(X2.min(), X2.max())

AttributeError: module 'matplotlib.pyplot' has no attribute 'countourf'

`Here is where the error occurs. How to fix it using countorf function or other in matplotlib?`

Answer 1

我认为您正在寻找的是“contourf”而不是“countourf”功能。

这里是“contourf”函数的文档链接：

https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.contourf.html

matplotlib 库根本没有“countourf”函数。

希望对你有所帮助。