卡方检验python代码

df = features[['Q1','Q2']]

df1 = df['Q1'].value_counts().reset_index().sort_values('index',ascending=False)
df2 = df['Q2'].value_counts().reset_index().sort_values('index',ascending=False)
df3 = pd.merge(df1,df2,left_on='index', right_on='index' )

from scipy.stats import chi2_contingency

chi2, p, dof, expected = chi2_contingency(df3[['Q1','Q2']])

print("卡方统计量：", chi2)
print("p值：", p)
print("自由度：", dof)
print("期望频数：", expected)

# 判断p值是否小于显著性水平
alpha = 0.05
if p < alpha:
    print("两个变量相关")
else:
    print("两个变量独立")