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)
