def METHOD_NAME(self, context: Context, dataset_kind) -> CheckResult:
    """Run check.
    Returns
    -------
    CheckResult
        value of result is a dict of all columns with number of unique values in format {column: number_of_uniques}
        display is a series with columns that have only one unique
    """
    # Validate parameters
    df = context.get_data_by_kind(dataset_kind).sample(self.n_samples, random_state=self.random_state).data
    df = select_from_dataframe(df, self.columns, self.ignore_columns)
    num_unique_per_col = df.nunique(dropna=self.ignore_nan)
    is_single_unique_value = (num_unique_per_col == 1)
    if context.with_display and is_single_unique_value.any():
        # get names of columns with one unique value
        # pylint: disable=unsubscriptable-object
        cols_with_single = is_single_unique_value[is_single_unique_value].index.to_list()
        uniques = pd.DataFrame({
            column_name: [column.sort_values(kind='mergesort').values[0]]
            for column_name, column in df.loc[:, cols_with_single].items()
        })
        uniques.index = ['Single unique value']
        display = ['The following columns have only one unique value', uniques]
    else:
        display = None
    return CheckResult(num_unique_per_col.to_dict(), header='Single Value in Column', display=display)