def METHOD_NAME(combed_path, output_filename, format='HDF'):
    """
    Parameters
    ----------
    combed_path : str
        The root path of the combed dataset.
    output_filename : str
        The destination HDF5 filename (including path and suffix).
    """
    check_directory_exists(combed_path)
    # Open store
    store = get_datastore(output_filename, format, mode='w')
    any_file_converted = False
    for building_name, building_mapping in overall_dataset_mapping.items():
        for load_name, load_mapping in building_mapping.items():
            for load_mapping_path, meter_number in load_mapping.items():
                building_number = building_number_mapping[building_name]
                key = Key(building=building_number, meter=meter_number)
                dfs = []
                for attribute in column_mapping.keys():
                    filename_attribute = join(combed_path, building_name, load_name, load_mapping_path, "%s.csv" %attribute)
                    if not os.path.isfile(filename_attribute):
                        # File not found directly in the combed_path provided
                        # Try adding 'iiitd' to it
                        filename_attribute = join(combed_path, 'iiitd', building_name, load_name, load_mapping_path, "%s.csv" %attribute)
                    if os.path.isfile(filename_attribute):
                        exists = True
                        print(filename_attribute)
                        df = pd.read_csv(filename_attribute, names=["timestamp", attribute])
                        df.index = pd.to_datetime(df["timestamp"], unit='ms')
                        df = df.drop("timestamp", 1)
                        dfs.append(df)
                    else:
                        exists = False
                if exists:
                    total = pd.concat(dfs, axis=1)
                    total = total.tz_localize('UTC').tz_convert('Asia/Kolkata')
                    total.columns = pd.MultiIndex.from_tuples([column_mapping[x] for x in total.columns])
                    total.columns.set_names(LEVEL_NAMES, inplace=True)
                    assert total.index.is_unique
                    store.put(str(key), total)
                    any_file_converted = True
    if not any_file_converted:
        raise RuntimeError('No files converted, did you specify the correct path?')
    convert_yaml_to_hdf5(
        join(get_module_directory(), 'dataset_converters', 'combed', 'metadata'),
        output_filename
    )
    print("Done converting COMBED to HDF5!")