def test_to_native_types(): index = PeriodIndex(['2017-01-01', '2017-01-02', '2017-01-03'], freq='D') # First, with no arguments. expected = np.array(['2017-01-01', '2017-01-02', '2017-01-03'], dtype='=U10') result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) # No NaN values, so na_rep has no effect result = index.to_native_types(na_rep='pandas') tm.assert_numpy_array_equal(result, expected) # Make sure slicing works expected = np.array(['2017-01-01', '2017-01-03'], dtype='=U10') result = index.to_native_types([0, 2]) tm.assert_numpy_array_equal(result, expected) # Make sure date formatting works expected = np.array(['01-2017-01', '01-2017-02', '01-2017-03'], dtype='=U10') result = index.to_native_types(date_format='%m-%Y-%d') tm.assert_numpy_array_equal(result, expected) # NULL object handling should work index = PeriodIndex(['2017-01-01', pd.NaT, '2017-01-03'], freq='D') expected = np.array(['2017-01-01', 'NaT', '2017-01-03'], dtype=object) result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) expected = np.array(['2017-01-01', 'pandas', '2017-01-03'], dtype=object) result = index.to_native_types(na_rep='pandas') tm.assert_numpy_array_equal(result, expected)
def test_to_native_types(): index = PeriodIndex(['2017-01-01', '2017-01-02', '2017-01-03'], freq='D') # First, with no arguments. expected = np.array(['2017-01-01', '2017-01-02', '2017-01-03'], dtype='=U10') result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) # No NaN values, so na_rep has no effect result = index.to_native_types(na_rep='pandas') tm.assert_numpy_array_equal(result, expected) # Make sure slicing works expected = np.array(['2017-01-01', '2017-01-03'], dtype='=U10') result = index.to_native_types([0, 2]) tm.assert_numpy_array_equal(result, expected) # Make sure date formatting works expected = np.array(['01-2017-01', '01-2017-02', '01-2017-03'], dtype='=U10') result = index.to_native_types(date_format='%m-%Y-%d') tm.assert_numpy_array_equal(result, expected) # NULL object handling should work index = PeriodIndex(['2017-01-01', pd.NaT, '2017-01-03'], freq='D') expected = np.array(['2017-01-01', 'NaT', '2017-01-03'], dtype=object) result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) expected = np.array(['2017-01-01', 'pandas', '2017-01-03'], dtype=object) result = index.to_native_types(na_rep='pandas') tm.assert_numpy_array_equal(result, expected)
def test_to_native_types(): index = PeriodIndex(["2017-01-01", "2017-01-02", "2017-01-03"], freq="D") # First, with no arguments. expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype="=U10") result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) # No NaN values, so na_rep has no effect result = index.to_native_types(na_rep="pandas") tm.assert_numpy_array_equal(result, expected) # Make sure slicing works expected = np.array(["2017-01-01", "2017-01-03"], dtype="=U10") result = index.to_native_types([0, 2]) tm.assert_numpy_array_equal(result, expected) # Make sure date formatting works expected = np.array(["01-2017-01", "01-2017-02", "01-2017-03"], dtype="=U10") result = index.to_native_types(date_format="%m-%Y-%d") tm.assert_numpy_array_equal(result, expected) # NULL object handling should work index = PeriodIndex(["2017-01-01", pd.NaT, "2017-01-03"], freq="D") expected = np.array(["2017-01-01", "NaT", "2017-01-03"], dtype=object) result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) expected = np.array(["2017-01-01", "pandas", "2017-01-03"], dtype=object) result = index.to_native_types(na_rep="pandas") tm.assert_numpy_array_equal(result, expected)