test_pivot.py 文件源码

def test_pivot_columns_lexsorted(self):

        n = 10000

        dtype = np.dtype([
            ("Index", object),
            ("Symbol", object),
            ("Year", int),
            ("Month", int),
            ("Day", int),
            ("Quantity", int),
            ("Price", float),
        ])

        products = np.array([
            ('SP500', 'ADBE'),
            ('SP500', 'NVDA'),
            ('SP500', 'ORCL'),
            ('NDQ100', 'AAPL'),
            ('NDQ100', 'MSFT'),
            ('NDQ100', 'GOOG'),
            ('FTSE', 'DGE.L'),
            ('FTSE', 'TSCO.L'),
            ('FTSE', 'GSK.L'),
        ], dtype=[('Index', object), ('Symbol', object)])
        items = np.empty(n, dtype=dtype)
        iproduct = np.random.randint(0, len(products), n)
        items['Index'] = products['Index'][iproduct]
        items['Symbol'] = products['Symbol'][iproduct]
        dr = pd.date_range(date(2000, 1, 1),
                           date(2010, 12, 31))
        dates = dr[np.random.randint(0, len(dr), n)]
        items['Year'] = dates.year
        items['Month'] = dates.month
        items['Day'] = dates.day
        items['Price'] = np.random.lognormal(4.0, 2.0, n)

        df = DataFrame(items)

        pivoted = df.pivot_table('Price', index=['Month', 'Day'],
                                 columns=['Index', 'Symbol', 'Year'],
                                 aggfunc='mean')

        self.assertTrue(pivoted.columns.is_monotonic)