convert raw data with shape (subject, rater) to (rater1, rater2)
brings data into correct format for cohens_kappa
data : array_like, 2-Dim
bins : None, int or tuple of array_like
arr : nd_array, (n_cat, n_cat)
no NaN handling, delete rows with missing values
This works also for more than two raters. In that case the dimension of the resulting contingency table is the same as the number of raters instead of 2-dimensional.