e165b44b4fa265c9419194640ccf833b675d8d40,scipy/stats/_binned_statistic.py,,binned_statistic_dd,#Any#Any#Any#Any#Any#Any#Any#,360

Before Change

        result.fill(0)
        flatcount = np.bincount(binnumbers, None)
        a = flatcount.nonzero()
        for i in np.unique(binnumbers):
            for vv in builtins.range(Vdim):
                // NOTE: take std dev by bin, np.std() is 2-pass and stable
                result[vv, i] = np.std(values[vv, binnumbers == i])
    elif statistic == "count":
        result.fill(0)
        flatcount = np.bincount(binnumbers, None)
        a = np.arange(len(flatcount))

After Change

                binned_data = values[vv, binnumbers == i]
                // calc std only when binned data is 2 or more for speed up.
                if len(binned_data) >= 2:
                    result[vv, i] = np.std(binned_data)
    elif statistic == "count":
        result.fill(0)
        flatcount = np.bincount(binnumbers, None)
        a = np.arange(len(flatcount))

Instances