def METHOD_NAME(dataset_summary_dict, data_provider):
    """
    Produces a summary statistics per data provider (Zenodo, OSF, LORIS...) of the
    identified variables of interest.
    :param dataset_summary_dict: dictionary with the variables of interest for the summary
     :type dataset_summary_dict: dict
    :param data_provider       : name of the data provider
     :type data_provider       : str
    :return: list with the summary statistics on the variables for the data provider
     :rtype: list
    """
    dataset_number = 0
    requires_login = 0
    total_size = 0
    total_files = 0
    keywords_list = []
    for index in dataset_summary_dict:
        dataset_dict = dataset_summary_dict[index]
        if data_provider not in dataset_dict["data_provider"]:
            continue
        dataset_number += 1
        if isinstance(dataset_dict["number_of_files"], str):
            total_files += int(dataset_dict["number_of_files"].replace(",", ""))
        else:
            total_files += dataset_dict["number_of_files"]
        if dataset_dict["authorization"].lower() in ["private", "restricted"]:
            requires_login += 1
        if dataset_dict["size_unit"].lower() == "b":
            total_size += dataset_dict["dataset_size"] / pow(1024, 3)
        elif dataset_dict["size_unit"].lower() == "kb":
            total_size += dataset_dict["dataset_size"] / pow(1024, 2)
        elif dataset_dict["size_unit"].lower() == "mb":
            total_size += dataset_dict["dataset_size"] / 1024
        elif dataset_dict["size_unit"].lower() == "gb":
            total_size += dataset_dict["dataset_size"]
        elif dataset_dict["size_unit"].lower() == "tb":
            total_size += dataset_dict["dataset_size"] * 1024
        elif dataset_dict["size_unit"].lower() == "pb":
            total_size += dataset_dict["dataset_size"] * pow(1024, 2)
        for keyword in dataset_dict["keywords"]:
            if keyword not in keywords_list:
                if keyword == "canadian-open-neuroscience-platform":
                    continue
                keywords_list.append(keyword)
    return [
        data_provider,
        str(dataset_number),
        str(requires_login),
        str(total_files),
        str(round(total_size)),
        ", ".join(keywords_list),
    ]