def test_to_dataframe(self):
# regression test for #260
arr = DataArray(np.random.randn(3, 4),
[('B', [1, 2, 3]), ('A', list('cdef'))])
expected = arr.to_series()
actual = arr.to_dataframe()[None]
self.assertArrayEqual(expected.values, actual.values)
self.assertArrayEqual(expected.index.values, actual.index.values)
def test_to_dataframe(self):
# regression test for #260
arr = DataArray(np.random.randn(3, 4),
[('B', [1, 2, 3]), ('A', list('cdef'))])
expected = arr.to_series()
actual = arr.to_dataframe()[None]
self.assertArrayEqual(expected.values, actual.values)
self.assertArrayEqual(expected.index.values, actual.index.values)
def test_to_dataframe(self):
# regression test for #260
arr = DataArray(np.random.randn(3, 4),
[('B', [1, 2, 3]), ('A', list('cdef'))])
expected = arr.to_series()
actual = arr.to_dataframe()[None]
self.assertArrayEqual(expected.values, actual.values)
self.assertArrayEqual(expected.name, actual.name)
self.assertArrayEqual(expected.index.values, actual.index.values)
# regression test for coords with different dimensions
arr.coords['C'] = ('B', [-1, -2, -3])
expected = arr.to_series().to_frame()
expected['C'] = [-1] * 4 + [-2] * 4 + [-3] * 4
expected.columns = [None, 'C']
actual = arr.to_dataframe()
self.assertArrayEqual(expected.values, actual.values)
self.assertArrayEqual(expected.columns.values, actual.columns.values)
self.assertArrayEqual(expected.index.values, actual.index.values)
def test_resample(self):
times = pd.date_range('2000-01-01', freq='6H', periods=10)
array = DataArray(np.arange(10), [('time', times)])
actual = array.resample('6H', dim='time')
self.assertDataArrayIdentical(array, actual)
actual = array.resample('24H', dim='time')
expected = DataArray(array.to_series().resample('24H'))
self.assertDataArrayIdentical(expected, actual)
actual = array.resample('24H', dim='time', how=np.mean)
self.assertDataArrayIdentical(expected, actual)
with self.assertRaisesRegexp(ValueError, 'index must be monotonic'):
array[[2, 0, 1]].resample('1D', dim='time')
def test_resample_first(self):
times = pd.date_range('2000-01-01', freq='6H', periods=10)
array = DataArray(np.arange(10), [('time', times)])
actual = array.resample('1D', dim='time', how='first')
expected = DataArray([0, 4, 8], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
# verify that labels don't use the first value
actual = array.resample('24H', dim='time', how='first')
expected = DataArray(array.to_series().resample('24H', how='first'))
self.assertDataArrayIdentical(expected, actual)
# missing values
array = array.astype(float)
array[:2] = np.nan
actual = array.resample('1D', dim='time', how='first')
expected = DataArray([2, 4, 8], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
actual = array.resample('1D', dim='time', how='first', skipna=False)
expected = DataArray([np.nan, 4, 8], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
