te": "Ohio",
    ...         "shortname": "OH",
    ...         "info": {"governor": "John Kasich"},
    ...         "counties": [
    ...             {"name": "Summit", "population": 1234},
    ...             {"name": "Cuyahoga", "population": 1337},
    ...         ],
    ...     },
    ... ]
    >>> result = pd.json_normalize(
    ...     data, "counties", ["state", "shortname", ["info", "governor"]]
    ... )
    >>> result
             name  population    state shortname info.governor
    0        Dade       12345   Florida    FL    Rick Scott
    1     Broward       40000   Florida    FL    Rick Scott
    2  Palm Beach       60000   Florida    FL    Rick Scott
    3      Summit        1234   Ohio       OH    John Kasich
    4    Cuyahoga        1337   Ohio       OH    John Kasich

    >>> data = {"A": [1, 2]}
    >>> pd.json_normalize(data, "A", record_prefix="Prefix.")
        Prefix.0
    0          1
    1          2

    Returns normalized data with columns prefixed with the given string.
    F