190065554d8905884dff948e4bb655d431d7eec3,ggplot/stats/stat.py,stat,_calculate_groups,#stat#Any#Any#,81

Before Change

        // Combine with original data
        unique = data.groupby("group", as_index=False).apply(uniquecols)
        unique.reset_index(drop=True, inplace=True)
        missing = unique.columns - stats.columns

        // Instead of a more expensive join, make sure the order is
        // fine and concat. This is really not expected to fail

After Change

            return pd.DataFrame()

        stats = []
        for _, old in data.groupby("group"):
            new = self._calculate(old, scales)
            unique = uniquecols(old)
            missing = unique.columns - new.columns
            u = unique.loc[[0]*len(new), missing].reset_index(drop=True)
            df = pd.concat([new, u], axis=1)
            stats.append(df)

        stats = pd.concat(stats, axis=0, ignore_index=True)

        // Note: If the data coming in has columns with non-unique
        // values with-in group(s), this implementation loses the

Instances