def _init_dates(self, dates, freq):
if dates is None:
dates = self.data.row_labels
if dates is not None:
if (not datetools._is_datetime_index(dates) and
isinstance(self.data, data.PandasData)):
try:
dates = to_datetime(dates)
except ValueError:
raise ValueError("Given a pandas object and the index does "
"not contain dates")
if not freq:
try:
freq = datetools._infer_freq(dates)
except:
raise ValueError("Frequency inference failed. Use `freq` "
"keyword.")
dates = Index(dates)
self.data.dates = dates
if freq:
try: #NOTE: Can drop this once we move to pandas >= 0.8.x
_freq_to_pandas[freq]
except:
raise ValueError("freq %s not understood" % freq)
self.data.freq = freq
def _init_dates(self, dates, freq):
if dates is None:
dates = self.data.row_labels
if dates is not None:
if (not datetools._is_datetime_index(dates) and
isinstance(self.data, data.PandasData)):
try:
if is_numeric_dtype(dates):
raise ValueError
dates = to_datetime(dates)
except ValueError:
raise ValueError("Given a pandas object and the index does "
"not contain dates")
if not freq:
try:
freq = datetools._infer_freq(dates)
except:
raise ValueError("Frequency inference failed. Use `freq` "
"keyword.")
if isinstance(dates[0], datetime.datetime):
dates = DatetimeIndex(dates)
else: # preserve PeriodIndex
dates = PeriodIndex(dates)
self.data.dates = dates
self.data.freq = freq
# Test for nanoseconds in early pandas versions
if freq is not None and _freq_to_pandas[freq].freqstr == 'N':
from distutils.version import LooseVersion
from pandas import __version__ as pd_version
if LooseVersion(pd_version) < '0.14':
raise NotImplementedError('Nanosecond index not available in'
' Pandas < 0.14')
def _init_dates(self, dates, freq):
if dates is None:
dates = self.data.row_labels
if dates is not None:
if (not datetools._is_datetime_index(dates) and
isinstance(self.data, data.PandasData)):
try:
if is_numeric_dtype(dates):
raise ValueError
dates = to_datetime(dates)
except ValueError:
raise ValueError("Given a pandas object and the index does "
"not contain dates")
if not freq:
try:
freq = datetools._infer_freq(dates)
except:
raise ValueError("Frequency inference failed. Use `freq` "
"keyword.")
if isinstance(dates[0], datetime.datetime):
dates = DatetimeIndex(dates)
else: # preserve PeriodIndex
dates = PeriodIndex(dates)
self.data.dates = dates
self.data.freq = freq
# Test for nanoseconds in early pandas versions
if freq is not None and _freq_to_pandas[freq].freqstr == 'N':
from distutils.version import LooseVersion
from pandas import __version__ as pd_version
if LooseVersion(pd_version) < '0.14':
raise NotImplementedError('Nanosecond index not available in'
' Pandas < 0.14')
def _init_dates(self, dates, freq):
if dates is None:
dates = self.data.row_labels
if dates is not None:
if (not datetools._is_datetime_index(dates) and
isinstance(self.data, data.PandasData)):
try:
if is_numeric_dtype(dates):
raise ValueError
dates = to_datetime(dates)
except ValueError:
raise ValueError("Given a pandas object and the index does "
"not contain dates")
if not freq:
try:
freq = datetools._infer_freq(dates)
except:
raise ValueError("Frequency inference failed. Use `freq` "
"keyword.")
if isinstance(dates[0], datetime.datetime):
dates = DatetimeIndex(dates)
else: # preserve PeriodIndex
dates = PeriodIndex(dates)
self.data.dates = dates
self.data.freq = freq
def _init_dates(self, dates, freq):
if dates is None:
dates = self.data.row_labels
if dates is not None:
if (not datetools._is_datetime_index(dates)
and isinstance(self.data, data.PandasData)):
try:
if is_numeric_dtype(dates):
raise ValueError
dates = to_datetime(dates)
except ValueError:
raise ValueError(
"Given a pandas object and the index does "
"not contain dates")
if not freq:
try:
freq = datetools._infer_freq(dates)
except:
raise ValueError("Frequency inference failed. Use `freq` "
"keyword.")
if isinstance(dates[0], datetime.datetime):
dates = DatetimeIndex(dates)
else: # preserve PeriodIndex
dates = PeriodIndex(dates)
self.data.dates = dates
self.data.freq = freq
def _init_dates(self, dates, period):
# maybe freq to period
self.period = period or 0
if dates is None:
dates = self.data.row_labels
if dates is not None:
if (not datetools._is_datetime_index(dates) and
isinstance(self.data, data.PandasData)):
raise ValueError("Given a pandas object and the index does "
"not contain dates")
#if not freq:
# try:
# freq = datetools._infer_freq(dates)
# except:
# raise ValueError("Frequency inference failed. Use `freq` "
# "keyword.")
dates = Index(dates)
self.data.dates = dates
