机器学习一元线性回归错误

Question

当我再用一元线性回归画散点图的时候报了这个错

import pandas as pd
import matplotlib.pyplot as plt
df=pd.read_csv('chage.csv')
df['Deaths']=df['Deaths'].str.replace(',','')
df['Total']=df['Total'].str.replace(',','')
from sklearn import linear_model
df['Deaths'].astype(float) 
df['Total'].astype(float) 
# 设定x和y的值
x = df[['Deaths']] 
y = df[['Total']]
regr=linear_model.LinearRegression()  
# 拟合fit()
regr.fit(x,y)
print(regr.coef_)    # 权重
print(regr.intercept_)
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei'] 
plt.rcParams['axes.unicode_minus'] = False
plt.xlabel('Deaths')
plt.ylabel('Total')
# 画出原始点:散点图scatter
plt.scatter(x, y, color='black')
# 画出预测点，预测点的宽度为1，颜色为红色
plt.scatter(x, regr.predict(x), color='red',linewidth=1)
plt.legend(['原始值','预测值'], loc = 2)
plt.show()

这是我的数据集

Answer 1

• 这篇文章讲的很详细，请看：多元线性回归解决机器学习问题的一般方法