def _resample_periods(self, obj):
axlabels = obj._get_axis(self.axis)
# Start vs. end of period
memb = axlabels.asfreq(self.freq, how=self.convention)
if is_subperiod(axlabels.freq, self.freq):
# Downsampling
if len(memb) > 1:
rng = np.arange(memb.values[0], memb.values[-1])
bins = memb.searchsorted(rng, side='right')
else:
bins = np.array([], dtype=np.int32)
index = period_range(memb[0], memb[-1], freq=self.freq)
grouper = BinGrouper(bins, index)
grouped = obj.groupby(grouper, axis=self.axis)
return grouped.agg(self.how)
elif is_superperiod(axlabels.freq, self.freq):
# Generate full range
new_index = period_range(memb[0], memb[-1], freq=self.freq)
# Get the fill indexer
indexer = memb.get_indexer(new_index, method=self.fill_method,
limit=self.limit)
return _take_new_index(obj, indexer, new_index, axis=self.axis)
else:
raise ValueError('Frequency %s cannot be resampled to %s'
% (axlabels.freq, self.freq))
def test_annual_upsample(self):
targets = ['D', 'B', 'M']
for month in MONTHS:
ts = _simple_pts('1/1/1990', '12/31/1995', freq='A-%s' % month)
for targ, conv, meth in product(targets, ['start', 'end'],
['ffill', 'bfill']):
result = ts.resample(targ, fill_method=meth,
convention=conv)
expected = result.to_timestamp(targ, how=conv)
expected = expected.asfreq(targ, meth).to_period()
assert_series_equal(result, expected)
df = DataFrame({'a' : ts})
rdf = df.resample('D', fill_method='ffill')
exp = df['a'].resample('D', fill_method='ffill')
assert_series_equal(rdf['a'], exp)
rng = period_range('2000', '2003', freq='A-DEC')
ts = Series([1, 2, 3, 4], index=rng)
result = ts.resample('M', fill_method='ffill')
ex_index = period_range('2000-01', '2003-12', freq='M')
expected = ts.asfreq('M', how='start').reindex(ex_index,
method='ffill')
assert_series_equal(result, expected)
def test_annual_upsample(self):
targets = ["D", "B", "M"]
for month in MONTHS:
ts = _simple_pts("1/1/1990", "12/31/1995", freq="A-%s" % month)
for targ, conv, meth in product(targets, ["start", "end"], ["ffill", "bfill"]):
result = ts.resample(targ, fill_method=meth, convention=conv)
expected = result.to_timestamp(targ, how=conv)
expected = expected.asfreq(targ, meth).to_period()
assert_series_equal(result, expected)
df = DataFrame({"a": ts})
rdf = df.resample("D", fill_method="ffill")
exp = df["a"].resample("D", fill_method="ffill")
assert_series_equal(rdf["a"], exp)
rng = period_range("2000", "2003", freq="A-DEC")
ts = Series([1, 2, 3, 4], index=rng)
result = ts.resample("M", fill_method="ffill")
ex_index = period_range("2000-01", "2003-12", freq="M")
expected = ts.asfreq("M", how="start").reindex(ex_index, method="ffill")
assert_series_equal(result, expected)
def test_upsample_daily_business_daily(self):
ts = _simple_pts("1/1/2000", "2/1/2000", freq="B")
result = ts.resample("D")
expected = ts.asfreq("D").reindex(period_range("1/3/2000", "2/1/2000"))
assert_series_equal(result, expected)
ts = _simple_pts("1/1/2000", "2/1/2000")
result = ts.resample("H", convention="s")
exp_rng = period_range("1/1/2000", "2/1/2000 23:00", freq="H")
expected = ts.asfreq("H", how="s").reindex(exp_rng)
assert_series_equal(result, expected)
def test_upsample_daily_business_daily(self):
ts = _simple_pts('1/1/2000', '2/1/2000', freq='B')
result = ts.resample('D')
expected = ts.asfreq('D').reindex(period_range('1/3/2000', '2/1/2000'))
assert_series_equal(result, expected)
ts = _simple_pts('1/1/2000', '2/1/2000')
result = ts.resample('H', convention='s')
exp_rng = period_range('1/1/2000', '2/1/2000 23:00', freq='H')
expected = ts.asfreq('H', how='s').reindex(exp_rng)
assert_series_equal(result, expected)
def test_annual_upsample(self):
ts = _simple_pts("1/1/1990", "12/31/1995", freq="A-DEC")
df = DataFrame({"a": ts})
rdf = df.resample("D", fill_method="ffill")
exp = df["a"].resample("D", fill_method="ffill")
assert_series_equal(rdf["a"], exp)
rng = period_range("2000", "2003", freq="A-DEC")
ts = Series([1, 2, 3, 4], index=rng)
result = ts.resample("M", fill_method="ffill")
ex_index = period_range("2000-01", "2003-12", freq="M")
expected = ts.asfreq("M", how="start").reindex(ex_index, method="ffill")
assert_series_equal(result, expected)
def test_to_period(self):
from pandas.tseries.period import period_range
ts = _simple_ts('1/1/2000', '1/1/2001')
pts = ts.to_period()
exp = ts.copy()
exp.index = period_range('1/1/2000', '1/1/2001')
assert_series_equal(pts, exp)
pts = ts.to_period('M')
exp.index = exp.index.asfreq('M')
tm.assert_index_equal(pts.index, exp.index.asfreq('M'))
assert_series_equal(pts, exp)
# GH 7606 without freq
idx = DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03',
'2011-01-04'])
exp_idx = pd.PeriodIndex(['2011-01-01', '2011-01-02', '2011-01-03',
'2011-01-04'], freq='D')
s = Series(np.random.randn(4), index=idx)
expected = s.copy()
expected.index = exp_idx
assert_series_equal(s.to_period(), expected)
df = DataFrame(np.random.randn(4, 4), index=idx, columns=idx)
expected = df.copy()
expected.index = exp_idx
assert_frame_equal(df.to_period(), expected)
expected = df.copy()
expected.columns = exp_idx
assert_frame_equal(df.to_period(axis=1), expected)
def test_quarterly_resampling(self):
rng = period_range('2000Q1', periods=10, freq='Q-DEC')
ts = Series(np.arange(10), index=rng)
result = ts.resample('A')
exp = ts.to_timestamp().resample('A').to_period()
assert_series_equal(result, exp)
def test_all_values_single_bin(self):
# 2070
index = period_range(start="2012-01-01", end="2012-12-31", freq="M")
s = Series(np.random.randn(len(index)), index=index)
result = s.resample("A", how='mean')
tm.assert_almost_equal(result[0], s.mean())
def test_upsample_with_limit(self):
rng = period_range("1/1/2000", periods=5, freq="A")
ts = Series(np.random.randn(len(rng)), rng)
result = ts.resample("M", fill_method="ffill", limit=2, convention="end")
expected = ts.asfreq("M").reindex(result.index, method="ffill", limit=2)
assert_series_equal(result, expected)
def test_mixed_freq_irreg_period(self):
ts = tm.makeTimeSeries()
irreg = ts[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 16, 17, 18, 29]]
rng = period_range('1/3/2000', periods=30, freq='B')
ps = Series(np.random.randn(len(rng)), rng)
irreg.plot()
ps.plot()
def test_resample_to_quarterly(self):
for month in MONTHS:
ts = _simple_pts("1990", "1992", freq="A-%s" % month)
quar_ts = ts.resample("Q-%s" % month, fill_method="ffill")
stamps = ts.to_timestamp("D", how="start")
qdates = period_range(
ts.index[0].asfreq("D", "start"), ts.index[-1].asfreq("D", "end"), freq="Q-%s" % month
)
expected = stamps.reindex(qdates.to_timestamp("D", "s"), method="ffill")
expected.index = qdates
assert_series_equal(quar_ts, expected)
# conforms, but different month
ts = _simple_pts("1990", "1992", freq="A-JUN")
for how in ["start", "end"]:
result = ts.resample("Q-MAR", convention=how, fill_method="ffill")
expected = ts.asfreq("Q-MAR", how=how)
expected = expected.reindex(result.index, method="ffill")
# .to_timestamp('D')
# expected = expected.resample('Q-MAR', fill_method='ffill')
assert_series_equal(result, expected)
def test_resample_5minute(self):
rng = period_range('1/1/2000', '1/5/2000', freq='T')
ts = TimeSeries(np.random.randn(len(rng)), index=rng)
result = ts.resample('5min')
expected = ts.to_timestamp().resample('5min')
assert_series_equal(result, expected)
def test_resample_to_quarterly(self):
for month in MONTHS:
ts = _simple_pts('1990', '1992', freq='A-%s' % month)
quar_ts = ts.resample('Q-%s' % month, fill_method='ffill')
stamps = ts.to_timestamp('D', how='start')
qdates = period_range(ts.index[0].asfreq('D', 'start'),
ts.index[-1].asfreq('D', 'end'),
freq='Q-%s' % month)
expected = stamps.reindex(qdates.to_timestamp('D', 'e'),
method='ffill')
expected.index = qdates
assert_series_equal(quar_ts, expected)
# conforms, but different month
ts = _simple_pts('1990', '1992', freq='A-JUN')
for how in ['start', 'end']:
result = ts.resample('Q-MAR', convention=how, fill_method='ffill')
expected = ts.asfreq('Q-MAR', how=how)
expected = expected.reindex(result.index, method='ffill')
# .to_timestamp('D')
# expected = expected.resample('Q-MAR', fill_method='ffill')
assert_series_equal(result, expected)
def test_annual_upsample(self):
ts = _simple_pts('1/1/1990', '12/31/1995', freq='A-DEC')
df = DataFrame({'a': ts})
rdf = df.resample('D', fill_method='ffill')
exp = df['a'].resample('D', fill_method='ffill')
assert_series_equal(rdf['a'], exp)
rng = period_range('2000', '2003', freq='A-DEC')
ts = Series([1, 2, 3, 4], index=rng)
result = ts.resample('M', fill_method='ffill')
ex_index = period_range('2000-01', '2003-12', freq='M')
expected = ts.asfreq('M', how='start').reindex(ex_index,
method='ffill')
assert_series_equal(result, expected)
def test_frame_to_period(self):
K = 5
from pandas.tseries.period import period_range
dr = date_range('1/1/2000', '1/1/2001')
pr = period_range('1/1/2000', '1/1/2001')
df = DataFrame(randn(len(dr), K), index=dr)
df['mix'] = 'a'
pts = df.to_period()
exp = df.copy()
exp.index = pr
assert_frame_equal(pts, exp)
pts = df.to_period('M')
tm.assert_index_equal(pts.index, exp.index.asfreq('M'))
df = df.T
pts = df.to_period(axis=1)
exp = df.copy()
exp.columns = pr
assert_frame_equal(pts, exp)
pts = df.to_period('M', axis=1)
tm.assert_index_equal(pts.columns, exp.columns.asfreq('M'))
self.assertRaises(ValueError, df.to_period, axis=2)
def test_resample_tz_localized(self):
dr = date_range(start="2012-4-13", end="2012-5-1")
ts = Series(lrange(len(dr)), dr)
ts_utc = ts.tz_localize("UTC")
ts_local = ts_utc.tz_convert("America/Los_Angeles")
result = ts_local.resample("W")
ts_local_naive = ts_local.copy()
ts_local_naive.index = [x.replace(tzinfo=None) for x in ts_local_naive.index.to_pydatetime()]
exp = ts_local_naive.resample("W").tz_localize("America/Los_Angeles")
assert_series_equal(result, exp)
# it works
result = ts_local.resample("D")
# #2245
idx = date_range("2001-09-20 15:59", "2001-09-20 16:00", freq="T", tz="Australia/Sydney")
s = Series([1, 2], index=idx)
result = s.resample("D", closed="right", label="right")
ex_index = date_range("2001-09-21", periods=1, freq="D", tz="Australia/Sydney")
expected = Series([1.5], index=ex_index)
assert_series_equal(result, expected)
# for good measure
result = s.resample("D", kind="period")
ex_index = period_range("2001-09-20", periods=1, freq="D")
expected = Series([1.5], index=ex_index)
assert_series_equal(result, expected)
def _resample_periods(self, obj):
axlabels = obj._get_axis(self.axis)
if len(axlabels) == 0:
new_index = PeriodIndex(data=[], freq=self.freq)
return obj.reindex(new_index)
else:
start = axlabels[0].asfreq(self.freq, how=self.convention)
end = axlabels[-1].asfreq(self.freq, how=self.convention)
new_index = period_range(start, end, freq=self.freq)
# Start vs. end of period
memb = axlabels.asfreq(self.freq, how=self.convention)
if is_subperiod(axlabels.freq, self.freq) or self.how is not None:
# Downsampling
rng = np.arange(memb.values[0], memb.values[-1])
bins = memb.searchsorted(rng, side='right')
grouper = BinGrouper(bins, new_index)
grouped = obj.groupby(grouper, axis=self.axis)
return grouped.aggregate(self._agg_method)
elif is_superperiod(axlabels.freq, self.freq):
# Get the fill indexer
indexer = memb.get_indexer(new_index, method=self.fill_method,
limit=self.limit)
return _take_new_index(obj, indexer, new_index, axis=self.axis)
else:
raise ValueError('Frequency %s cannot be resampled to %s'
% (axlabels.freq, self.freq))
def test_upsample_with_limit(self):
rng = period_range('1/1/2000', periods=5, freq='A')
ts = Series(np.random.randn(len(rng)), rng)
result = ts.resample('M', fill_method='ffill', limit=2)
expected = ts.asfreq('M').reindex(result.index, method='ffill',
limit=2)
assert_series_equal(result, expected)
def test_finder_monthly_long(self):
rng = period_range('1988Q1', periods=24 * 12, freq='M')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1989Q1', 'M').ordinal
self.assertEqual(rs, xp)
def test_resample_to_period_monthly_buglet(self):
# GH #1259
rng = date_range('1/1/2000', '12/31/2000')
ts = Series(np.random.randn(len(rng)), index=rng)
result = ts.resample('M', kind='period')
exp_index = period_range('Jan-2000', 'Dec-2000', freq='M')
self.assert_(result.index.equals(exp_index))
def test_resample_to_period_monthly_buglet(self):
# GH #1259
rng = date_range("1/1/2000", "12/31/2000")
ts = Series(np.random.randn(len(rng)), index=rng)
result = ts.resample("M", kind="period")
exp_index = period_range("Jan-2000", "Dec-2000", freq="M")
self.assert_(result.index.equals(exp_index))
def setUp(self):
freq = ["S", "T", "H", "D", "W", "M", "Q", "Y"]
idx = [period_range("12/31/1999", freq=x, periods=100) for x in freq]
self.period_ser = [Series(np.random.randn(len(x)), x) for x in idx]
self.period_df = [DataFrame(np.random.randn(len(x), 3), index=x, columns=["A", "B", "C"]) for x in idx]
freq = ["S", "T", "H", "D", "W", "M", "Q-DEC", "A", "1B30Min"]
idx = [date_range("12/31/1999", freq=x, periods=100) for x in freq]
self.datetime_ser = [Series(np.random.randn(len(x)), x) for x in idx]
self.datetime_df = [DataFrame(np.random.randn(len(x), 3), index=x, columns=["A", "B", "C"]) for x in idx]
def test_finder_monthly_long(self):
import matplotlib.pyplot as plt
plt.close('all')
rng = period_range('1988Q1', periods=24 * 12, freq='M')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1989Q1', 'M').ordinal
self.assert_(rs == xp)
def test_finder_monthly(self):
xp = Period('1988-1').ordinal
yrs = [1.15, 2.5, 4, 11]
for n in yrs:
rng = period_range('1987Q2', periods=int(n * 12), freq='M')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assert_(rs == xp)
def test_finder_quarterly(self):
xp = Period('1988Q1').ordinal
yrs = [3.5, 11]
for n in yrs:
rng = period_range('1987Q2', periods=int(n * 4), freq='Q')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assert_(rs == xp)
def test_finder_annual(self):
import matplotlib.pyplot as plt
xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]
for i, nyears in enumerate([5, 10, 19, 49, 99, 199, 599, 1001]):
rng = period_range('1987', periods=nyears, freq='A')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(rs, Period(xp[i], freq='A').ordinal)
plt.close(ax.get_figure())
def test_basic_downsample(self):
ts = _simple_pts("1/1/1990", "6/30/1995", freq="M")
result = ts.resample("a-dec")
expected = ts.groupby(ts.index.year).mean()
expected.index = period_range("1/1/1990", "6/30/1995", freq="a-dec")
assert_series_equal(result, expected)
# this is ok
assert_series_equal(ts.resample("a-dec"), result)
assert_series_equal(ts.resample("a"), result)
def test_basic_downsample(self):
ts = _simple_pts('1/1/1990', '6/30/1995', freq='M')
result = ts.resample('a-dec')
expected = ts.groupby(ts.index.year).mean()
expected.index = period_range('1/1/1990', '6/30/1995',
freq='a-dec')
assert_series_equal(result, expected)
# this is ok
assert_series_equal(ts.resample('a-dec'), result)
assert_series_equal(ts.resample('a'), result)
def _get_new_index(self):
""" return our new index """
ax = self.ax
if len(ax) == 0:
values = []
else:
start = ax[0].asfreq(self.freq, how=self.convention)
end = ax[-1].asfreq(self.freq, how='end')
values = period_range(start, end, freq=self.freq).values
return ax._shallow_copy(values, freq=self.freq)
def setUp(self):
TestPlotBase.setUp(self)
freq = ['S', 'T', 'H', 'D', 'W', 'M', 'Q', 'A']
idx = [period_range('12/31/1999', freq=x, periods=100) for x in freq]
self.period_ser = [Series(np.random.randn(len(x)), x) for x in idx]
self.period_df = [DataFrame(np.random.randn(len(x), 3), index=x,
columns=['A', 'B', 'C'])
for x in idx]
freq = ['S', 'T', 'H', 'D', 'W', 'M', 'Q-DEC', 'A', '1B30Min']
idx = [date_range('12/31/1999', freq=x, periods=100) for x in freq]
self.datetime_ser = [Series(np.random.randn(len(x)), x) for x in idx]
self.datetime_df = [DataFrame(np.random.randn(len(x), 3), index=x,
columns=['A', 'B', 'C'])
for x in idx]
def test_finder_quarterly(self):
import matplotlib.pyplot as plt
xp = Period('1988Q1').ordinal
yrs = [3.5, 11]
plt.close('all')
for n in yrs:
rng = period_range('1987Q2', periods=int(n * 4), freq='Q')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assert_(rs == xp)
(vmin, vmax) = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(xp, rs)
def test_finder_monthly(self):
import matplotlib.pyplot as plt
xp = Period('Jan 1988').ordinal
yrs = [1.15, 2.5, 4, 11]
for n in yrs:
rng = period_range('1987Q2', periods=int(n * 12), freq='M')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(rs, xp)
vmin, vmax = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(xp, rs)
plt.close(ax.get_figure())
def test_resample_tz_localized(self):
dr = date_range(start='2012-4-13', end='2012-5-1')
ts = Series(range(len(dr)), dr)
ts_utc = ts.tz_localize('UTC')
ts_local = ts_utc.tz_convert('America/Los_Angeles')
result = ts_local.resample('W')
ts_local_naive = ts_local.copy()
ts_local_naive.index = [
x.replace(tzinfo=None)
for x in ts_local_naive.index.to_pydatetime()
]
exp = ts_local_naive.resample('W').tz_localize('America/Los_Angeles')
assert_series_equal(result, exp)
# it works
result = ts_local.resample('D')
# #2245
idx = date_range('2001-09-20 15:59',
'2001-09-20 16:00',
freq='T',
tz='Australia/Sydney')
s = Series([1, 2], index=idx)
result = s.resample('D', closed='right', label='right')
ex_index = date_range('2001-09-21',
periods=1,
freq='D',
tz='Australia/Sydney')
expected = Series([1.5], index=ex_index)
assert_series_equal(result, expected)
# for good measure
result = s.resample('D', kind='period')
ex_index = period_range('2001-09-20', periods=1, freq='D')
expected = Series([1.5], index=ex_index)
assert_series_equal(result, expected)
def test_resample_to_quarterly(self):
for month in MONTHS:
ts = _simple_pts('1990', '1992', freq='A-%s' % month)
quar_ts = ts.resample('Q-%s' % month, fill_method='ffill')
stamps = ts.to_timestamp('D', how='end')
qdates = period_range(stamps.index[0], stamps.index[-1],
freq='Q-%s' % month)
expected = stamps.reindex(qdates.to_timestamp('D', 'e'),
method='ffill')
expected.index = qdates
assert_series_equal(quar_ts, expected)
# conforms, but different month
ts = _simple_pts('1990', '1992', freq='A-JUN')
for how in ['start', 'end']:
result = ts.resample('Q-MAR', convention=how, fill_method='ffill')
expected = ts.asfreq('Q-MAR', how=how).to_timestamp('D')
expected = expected.resample('Q-MAR', fill_method='ffill')
assert_series_equal(result, expected.to_period('Q-MAR'))
def _resample_periods(self, obj):
axlabels = obj._get_axis(self.axis)
if len(axlabels) == 0:
new_index = PeriodIndex(data=[], freq=self.freq)
return obj.reindex(new_index)
else:
start = axlabels[0].asfreq(self.freq, how=self.convention)
end = axlabels[-1].asfreq(self.freq, how=self.convention)
new_index = period_range(start, end, freq=self.freq)
# Start vs. end of period
memb = axlabels.asfreq(self.freq, how=self.convention)
if is_subperiod(axlabels.freq, self.freq):
# Downsampling
if len(memb) > 1:
rng = np.arange(memb.values[0], memb.values[-1])
bins = memb.searchsorted(rng, side='right')
else:
bins = np.array([], dtype=np.int32)
grouper = BinGrouper(bins, new_index)
grouped = obj.groupby(grouper, axis=self.axis)
return grouped.aggregate(self.how)
elif is_superperiod(axlabels.freq, self.freq):
# Get the fill indexer
indexer = memb.get_indexer(new_index,
method=self.fill_method,
limit=self.limit)
return _take_new_index(obj, indexer, new_index, axis=self.axis)
else:
raise ValueError('Frequency %s cannot be resampled to %s' %
(axlabels.freq, self.freq))
def test_resample_tz_localized(self):
dr = date_range(start='2012-4-13', end='2012-5-1')
ts = Series(lrange(len(dr)), dr)
ts_utc = ts.tz_localize('UTC')
ts_local = ts_utc.tz_convert('America/Los_Angeles')
result = ts_local.resample('W')
ts_local_naive = ts_local.copy()
ts_local_naive.index = [
x.replace(tzinfo=None)
for x in ts_local_naive.index.to_pydatetime()
]
exp = ts_local_naive.resample('W').tz_localize('America/Los_Angeles')
assert_series_equal(result, exp)
# it works
result = ts_local.resample('D')
# #2245
idx = date_range('2001-09-20 15:59',
'2001-09-20 16:00',
freq='T',
tz='Australia/Sydney')
s = Series([1, 2], index=idx)
result = s.resample('D', closed='right', label='right')
ex_index = date_range('2001-09-21',
periods=1,
freq='D',
tz='Australia/Sydney')
expected = Series([1.5], index=ex_index)
assert_series_equal(result, expected)
# for good measure
result = s.resample('D', kind='period')
ex_index = period_range('2001-09-20', periods=1, freq='D')
expected = Series([1.5], index=ex_index)
assert_series_equal(result, expected)
# GH 6397
# comparing an offset that doesn't propogate tz's
rng = date_range('1/1/2011', periods=20000, freq='H')
rng = rng.tz_localize('EST')
ts = DataFrame(index=rng)
ts['first'] = np.random.randn(len(rng))
ts['second'] = np.cumsum(np.random.randn(len(rng)))
expected = DataFrame(
{
'first': ts.resample('A', how=np.sum)['first'],
'second': ts.resample('A', how=np.mean)['second']
},
columns=['first', 'second'])
result = ts.resample('A', how={
'first': np.sum,
'second': np.mean
}).reindex(columns=['first', 'second'])
assert_frame_equal(result, expected)
def _simple_pts(start, end, freq='D'):
rng = period_range(start, end, freq=freq)
return TimeSeries(np.random.randn(len(rng)), index=rng)