def METHOD_NAME(bytes_for_rows: bytes) -> pd.DataFrame:
    if isinstance(bytes_for_rows, pa.FixedSizeBinaryArray):
        bytes_for_rows = bytes_for_rows.buffers()[1].to_pybytes()
    bytes_per_row = struct.calcsize(measurement_format)
    count_rows = len(bytes_for_rows) // bytes_per_row
    timestamps = np.zeros((count_rows), dtype=np.int64)
    latitudes = np.zeros((count_rows), dtype=np.single)
    longitudes = np.zeros((count_rows), dtype=np.single)
    amounts = np.zeros((count_rows), dtype=np.single)
    humans = np.zeros((count_rows), dtype=np.int32)
    zips = np.zeros((count_rows), dtype=np.int32)
    for row_idx in range(count_rows):
        row = struct.unpack_from(
            measurement_format, bytes_for_rows, bytes_per_row * row_idx)
        timestamps[row_idx] = row[0]
        latitudes[row_idx] = row[1]
        longitudes[row_idx] = row[2]
        amounts[row_idx] = row[3]
        humans[row_idx] = row[4]
        zips[row_idx] = row[5]
    return pd.DataFrame({
        'timestamps': timestamps,
        'latitudes': latitudes,
        'longitudes': longitudes,
        'amounts': amounts,
        'humans': humans,
        'zips': zips,
    })