libs/libcommon/src/libcommon/statistics_utils.py [397:417]:
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            min_value=minimum,
            max_value=maximum,
            n_bins=NUM_BINS,
            n_samples=n_samples - nan_count,
        )

        return NumericalStatisticsItem(
            nan_count=nan_count,
            nan_proportion=nan_proportion,
            min=minimum,
            max=maximum,
            mean=mean,
            median=median,
            std=std,
            histogram=hist,
        )

    def compute_and_prepare_response(self, data: pl.DataFrame) -> StatisticsPerColumnItem:
        stats = self.compute_statistics(data, column_name=self.name, n_samples=self.n_samples)
        return StatisticsPerColumnItem(
            column_name=self.name,
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libs/libcommon/src/libcommon/statistics_utils.py [443:463]:
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            min_value=minimum,
            max_value=maximum,
            n_bins=NUM_BINS,
            n_samples=n_samples - nan_count,
        )

        return NumericalStatisticsItem(
            nan_count=nan_count,
            nan_proportion=nan_proportion,
            min=minimum,
            max=maximum,
            mean=mean,
            median=median,
            std=std,
            histogram=hist,
        )

    def compute_and_prepare_response(self, data: pl.DataFrame) -> StatisticsPerColumnItem:
        stats = self.compute_statistics(data, column_name=self.name, n_samples=self.n_samples)
        return StatisticsPerColumnItem(
            column_name=self.name,
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