else:
# GH14962
expected = Series([])
if isinstance(df.index, PeriodIndex):
expected.index = df.index.asfreq(freq=freq)
else:
expected.index = df.index._shallow_copy(freq=freq)
assert_index_equal(result.index, expected.index)
assert result.index.freq == expected.index.freq
assert_almost_equal(result, expected, check_dtype=False)
# test size for GH13212 (currently stays as df)
@pytest.mark.parametrize("index", tm.all_timeseries_index_generator(0))
@pytest.mark.parametrize(
"dtype",
[np.float, np.int, np.object, 'datetime64[ns]'])
def test_resample_empty_dtypes(index, dtype, resample_method):
# Empty series were sometimes causing a segfault (for the functions
# with Cython bounds-checking disabled) or an IndexError. We just run
# them to ensure they no longer do. (GH #10228)
empty_series = Series([], index, dtype)
try:
getattr(empty_series.resample('d'), resample_method)()
except DataError:
# Ignore these since some combinations are invalid
# (ex: doing mean with dtype of np.object)
pass
result = getattr(df.resample(freq), resample_method)()
if resample_method != 'size':
expected = df.copy()
else:
# GH14962
expected = Series([])
expected.index = df.index._shallow_copy(freq=freq)
assert_index_equal(result.index, expected.index)
assert result.index.freq == expected.index.freq
assert_almost_equal(result, expected, check_dtype=False)
# test size for GH13212 (currently stays as df)
@pytest.mark.parametrize("index", tm.all_timeseries_index_generator(0))
@pytest.mark.parametrize(
"dtype",
[np.float, np.int, np.object, 'datetime64[ns]'])
def test_resample_empty_dtypes(index, dtype, resample_method):
# Empty series were sometimes causing a segfault (for the functions
# with Cython bounds-checking disabled) or an IndexError. We just run
# them to ensure they no longer do. (GH #10228)
empty_series = Series([], index, dtype)
try:
getattr(empty_series.resample('d'), resample_method)()
except DataError:
# Ignore these since some combinations are invalid
# (ex: doing mean with dtype of np.object)
pass
class Base(object):
"""
base class for resampling testing, calling
.create_series() generates a series of each index type
"""
@pytest.mark.parametrize('freq', ['2D', '1H'])
def test_asfreq(self, series_and_frame, freq, create_index):
obj = series_and_frame
result = obj.resample(freq).asfreq()
new_index = create_index(obj.index[0], obj.index[-1], freq=freq)
expected = obj.reindex(new_index)
assert_almost_equal(result, expected)
def test_asfreq_fill_value(self, create_index):
# test for fill value during resampling, issue 3715
s = self.create_series()
result = s.resample('1H').asfreq()
new_index = create_index(s.index[0], s.index[-1], freq='1H')
expected = s.reindex(new_index)
assert_series_equal(result, expected)
frame = s.to_frame('value')
frame.iloc[1] = None
result = frame.resample('1H').asfreq(fill_value=4.0)
new_index = create_index(frame.index[0], frame.index[-1], freq='1H')
expected = frame.reindex(new_index, fill_value=4.0)
assert_frame_equal(result, expected)
def test_resample_interpolate(self):
# # 12925
df = self.create_series().to_frame('value')
assert_frame_equal(
df.resample('1T').asfreq().interpolate(),
df.resample('1T').interpolate())
def test_raises_on_non_datetimelike_index(self):
# this is a non datetimelike index
xp = DataFrame()
pytest.raises(TypeError, lambda: xp.resample('A').mean())
@pytest.mark.parametrize('freq', ['M', 'D', 'H'])
def test_resample_empty_series(self, freq, resample_method):
# GH12771 & GH12868
if resample_method == 'ohlc':
pytest.skip('need to test for ohlc from GH13083')
s = self.create_series()[:0]
result = getattr(s.resample(freq), resample_method)()
expected = s.copy()
expected.index = s.index._shallow_copy(freq=freq)
assert_index_equal(result.index, expected.index)
assert result.index.freq == expected.index.freq
assert_series_equal(result, expected, check_dtype=False)
@pytest.mark.parametrize('freq', ['M', 'D', 'H'])
def test_resample_empty_dataframe(self, freq, resample_method):
# GH13212
index = self.create_series().index[:0]
f = DataFrame(index=index)
# count retains dimensions too
result = getattr(f.resample(freq), resample_method)()
if resample_method != 'size':
expected = f.copy()
else:
# GH14962
expected = Series([])
expected.index = f.index._shallow_copy(freq=freq)
assert_index_equal(result.index, expected.index)
assert result.index.freq == expected.index.freq
assert_almost_equal(result, expected, check_dtype=False)
# test size for GH13212 (currently stays as df)
@pytest.mark.parametrize("index", tm.all_timeseries_index_generator(0))
@pytest.mark.parametrize("dtype",
[np.float, np.int, np.object, 'datetime64[ns]'])
def test_resample_empty_dtypes(self, index, dtype, resample_method):
# Empty series were sometimes causing a segfault (for the functions
# with Cython bounds-checking disabled) or an IndexError. We just run
# them to ensure they no longer do. (GH #10228)
empty_series = Series([], index, dtype)
try:
getattr(empty_series.resample('d'), resample_method)()
except DataError:
# Ignore these since some combinations are invalid
# (ex: doing mean with dtype of np.object)
pass
def test_resample_loffset_arg_type(self, create_index):
# GH 13218, 15002
df = self.create_series().to_frame('value')
expected_means = [
df.values[i:i + 2].mean() for i in range(0, len(df.values), 2)
]
expected_index = create_index(df.index[0],
periods=len(df.index) / 2,
freq='2D')
# loffset coerces PeriodIndex to DateTimeIndex
if isinstance(expected_index, PeriodIndex):
expected_index = expected_index.to_timestamp()
expected_index += timedelta(hours=2)
expected = DataFrame({'value': expected_means}, index=expected_index)
for arg in ['mean', {'value': 'mean'}, ['mean']]:
result_agg = df.resample('2D', loffset='2H').agg(arg)
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
result_how = df.resample('2D', how=arg, loffset='2H')
if isinstance(arg, list):
expected.columns = pd.MultiIndex.from_tuples([('value', 'mean')
])
# GH 13022, 7687 - TODO: fix resample w/ TimedeltaIndex
if isinstance(expected.index, TimedeltaIndex):
with pytest.raises(AssertionError):
assert_frame_equal(result_agg, expected)
assert_frame_equal(result_how, expected)
else:
assert_frame_equal(result_agg, expected)
assert_frame_equal(result_how, expected)
def test_apply_to_empty_series(self):
# GH 14313
series = self.create_series()[:0]
for freq in ['M', 'D', 'H']:
result = series.resample(freq).apply(lambda x: 1)
expected = series.resample(freq).apply(np.sum)
assert_series_equal(result, expected, check_dtype=False)
def test_resampler_is_iterable(self):
# GH 15314
series = self.create_series()
freq = 'H'
tg = TimeGrouper(freq, convention='start')
grouped = series.groupby(tg)
resampled = series.resample(freq)
for (rk, rv), (gk, gv) in zip(resampled, grouped):
assert rk == gk
assert_series_equal(rv, gv)
def test_resample_quantile(self):
# GH 15023
s = self.create_series()
q = 0.75
freq = 'H'
result = s.resample(freq).quantile(q)
expected = s.resample(freq).agg(lambda x: x.quantile(q))
tm.assert_series_equal(result, expected)
