def zNormalise(self, inplace=True):

        samples = self.table.columns
        genes = self.table.index

        z_df = pd.DataFrame(preprocessing.scale(
            self.table, axis=1, with_mean=True, with_std=True, copy=False))

        z_df.index = genes
        z_df.columns = samples

        if inplace:
            self.table = z_df
        else:
            return Counts(z_df)
normalise each row to zero mean and unit variance
dataset/ETHPy150Open CGATOxford/cgat/CGAT/Counts.py/Counts.zNormalise