def test_to_period_tz_warning(self):
# GH#21333 make sure a warning is issued when timezone
# info is lost
ts = Timestamp('2009-04-15 16:17:18', tz='US/Eastern')
with tm.assert_produces_warning(UserWarning):
# warning that timezone info will be lost
ts.to_period('D')
def test_to_period_tz_warning(self):
# GH#21333 make sure a warning is issued when timezone
# info is lost
ts = Timestamp("2009-04-15 16:17:18", tz="US/Eastern")
with tm.assert_produces_warning(UserWarning):
# warning that timezone info will be lost
ts.to_period("D")
def finance_report(start: Timestamp,
end: Timestamp,
market: str,
symbol: str,
report_type: str,
quarter="all") -> DataFrame:
"""
:param start: start time
:param end: end time
:param market: {'HK', 'CN'}
:param symbol: stock symbol
:param report_type: {'indicator', 'balance', 'income', 'business'}
:param quarter: {'all', 'Q1', 'Q2', ‘Q3', 'Q4'}
:return: data frame contains items of financial report
"""
count = (end.to_period(freq='Q') - start.to_period(freq='Q')).n
end_timestamp = int(end.timestamp() * 1000)
urlpath = f"{market}/{report_type}.json?symbol={symbol}&&type={quarter}" \
f"&is_detail=true&count={count}×tamp={end_timestamp}"
url = urljoin(api_ref.finance_base, urlpath)
data = utls.fetch(url)
data_list = data.pop('list')
for d in data_list:
for k in d:
if isinstance(d[k], list):
d[k] = d[k][0]
df = DataFrame(data_list).drop(columns=['ctime']).rename(
columns={
'report_date': 'date'
}).set_index('date')
df.date = df.date.astype('M8[ms]')
df.report_name = df.report_name.str.replace('年报', 'Q4').str.replace('三季报', 'Q3')\
.str.replace('中报', 'Q2').str.replace('一季报', 'Q1')
return df
def _range_from_time_index(self, start: pd.Timestamp,
stop: pd.Timestamp) -> pd.DataFrame:
index = self._index
if isinstance(self._index, pd.PeriodIndex):
if isinstance(start, pd.Timestamp):
start = start.to_period(freq=self._index_freq)
if isinstance(stop, pd.Timestamp):
stop = stop.to_period(freq=self._index_freq)
if start < index[0]:
raise ValueError(START_BEFORE_INDEX_ERR)
if stop <= self._index[-1]:
return self.in_sample().loc[start:stop]
new_idx = self._extend_time_index(stop)
oos_idx = new_idx[new_idx > index[-1]]
oos = self.out_of_sample(oos_idx.shape[0], oos_idx)
if start >= oos_idx[0]:
return oos.loc[start:stop]
both = pd.concat([self.in_sample(), oos], axis=0)
return both.loc[start:stop]
def test_td64arr_sub_pi(self, box, tdi_freq, pi_freq):
# GH#20049 subtracting PeriodIndex should raise TypeError
tdi = TimedeltaIndex(['1 hours', '2 hours'], freq=tdi_freq)
dti = Timestamp('2018-03-07 17:16:40') + tdi
pi = dti.to_period(pi_freq)
# TODO: parametrize over box for pi?
tdi = tm.box_expected(tdi, box)
with pytest.raises(TypeError):
tdi - pi
def ordinal(v: pd.Timestamp, freq: str) -> int:
return v.to_period(freq).ordinal
def test_to_period(self, dt64, ts):
alt = Timestamp(dt64)
assert ts.to_period("D") == alt.to_period("D")
