<p>从Ziggy-Eunicien答案中稍微修改了一点函数。
添加了2个修改
1） cheching一个变量是常量
2） 修正ss.chi2_列联（conf_matrix，correction=correct）-如果混淆矩阵是2x2，则为FALSE</p>
<pre><code>import scipy.stats as ss
import pandas as pd
import numpy as np
def cramers_corrected_stat(x,y):
""" calculate Cramers V statistic for categorial-categorial association.
uses correction from Bergsma and Wicher,
Journal of the Korean Statistical Society 42 (2013): 323-328
"""
result=-1
if len(x.value_counts())==1 :
print("First variable is constant")
elif len(y.value_counts())==1:
print("Second variable is constant")
else:
conf_matrix=pd.crosstab(x, y)
if conf_matrix.shape[0]==2:
correct=False
else:
correct=True
chi2 = ss.chi2_contingency(conf_matrix, correction=correct)[0]
n = sum(conf_matrix.sum())
phi2 = chi2/n
r,k = conf_matrix.shape
phi2corr = max(0, phi2 - ((k-1)*(r-1))/(n-1))
rcorr = r - ((r-1)**2)/(n-1)
kcorr = k - ((k-1)**2)/(n-1)
result=np.sqrt(phi2corr / min( (kcorr-1), (rcorr-1)))
return round(result,6)
</code></pre>
