<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _import_data(sections, crumbs):
 """ Import the section metadata and change it to index-by-name. :param list sections: Metadata :param str pc: paleo or chron :return dict _sections: Metadata """

    logger_jsons.info("enter import_data: {}".format(crumbs))
    _sections = OrderedDict()
    try:
        for _idx, section in enumerate(sections):
            _tmp = OrderedDict()

            # Process the paleo measurement table
            if "measurementTable" in section:
                _tmp["measurementTable"] = _idx_table_by_name(section["measurementTable"], "{}{}{}".format(crumbs, _idx, "measurement"))

            # Process the paleo model
            if "model" in section:
                _tmp["model"] = _import_model(section["model"], "{}{}{}".format(crumbs, _idx, "model"))

            # Get the table name from the first measurement table, and use that as the index name for this table
            _table_name = "{}{}".format(crumbs, _idx)

            # If we only have generic table names, and one exists already, don't overwrite. Create dynamic name
            if _table_name in _sections:
                _table_name = "{}_{}".format(_table_name, _idx)

            # Put the final product into the output dictionary. Indexed by name
            _sections[_table_name] = _tmp

    except Exception as e:
        logger_jsons.error("import_data: Exception: {}".format(e))
        print("Error: import_data: {}".format(e))

    logger_jsons.info("exit import_data: {}".format(crumbs))
    return _sections