Still beginning my journey using Python so this is a simple question that I don't understand.
Trying to use Ziggy's definition statement of Cramer's V statistic from here: Using pandas, calculate Cramér's coefficient matrix
but when I put it into Python the definition doesn't end at the return:
>>> import pandas as pd
>>> def cramers_corrected_stat(confusion_matrix):
... # calculate Cramers V statistic for categorial-categorial association.
... # uses correction from Bergsma and Wicher,
... # Journal of the Korean Statistical Society 42 (2013): 323-328
...
... chi2 = ss.chi2_contingency(confusion_matrix)[0]
... n = confusion_matrix.sum()
... phi2 = chi2/n
... r,k = confusion_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)
... return np.sqrt(phi2corr / min( (kcorr-1), (rcorr-1)))
...
What am I not seeing?