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