# skfolio.utils.stats.n_bins_freedman ### skfolio.utils.stats.n_bins_freedman(x) Compute the optimal histogram bin size using the Freedman-Diaconis rule [[1]](#r8d5b646da1d1-1). * **Parameters:** **x** *ndarray of shape (n_observations,)* : The input array. * **Returns:** **n_bins** *int* : The optimal bin size. ### References * **[1]** “On the histogram as a density estimator: L2 theory”. Freedman & Diaconis (1981).