def test_create_dataframe(data, columns, types, rows_allowed):
    """
    Tests whether the data in a dataframe match the column name, data type,
    and row count constraints.

    Extended description of function.

    Parameters:
    data (pandas.dataframe): Data loaded from a publicdata source (911 CSV
    from data.seattle.gov, in this case).

    columns(list): The header columns expected from the given data.

    types(list): The data types (after loading from CSV) from the given data.

    row_allowed(int): A row count that the dataframe must equal or surpass.
    In this case, 10 is tested.

    Returns:
    Boolean: Whether data passes all tests.

    """
    passed = sorted(data.columns.values.tolist()) == sorted(columns)
    if passed:
        passed = sorted(data.dtypes.tolist()) == sorted(types)
    if passed:
        passed = data.shape[0] >= rows_allowed
    return passed