def __init__(self, index, warn=True):
self.index = index
self.values = np.asarray(index).view('i8')
self.warn = warn
if len(index) < 3:
raise ValueError('Need at least 3 dates to infer frequency')
self.deltas = lib.unique_deltas(self.values)
self.is_unique = len(self.deltas) == 1
self.is_monotonic = self.index.is_monotonic
def __init__(self, index, warn=True):
self.index = index
self.values = np.asarray(index).view('i8')
self.warn = warn
if len(index) < 3:
raise ValueError('Need at least 3 dates to infer frequency')
self.deltas = lib.unique_deltas(self.values)
self.is_unique = len(self.deltas) == 1
self.is_monotonic = self.index.is_monotonic
def __init__(self, index, warn=True):
from pandas.tseries.index import DatetimeIndex
if not isinstance(index, DatetimeIndex):
index = DatetimeIndex(index)
self.index = index
self.values = np.asarray(index).view('i8')
self.warn = warn
if len(index) < 3:
raise ValueError('Need at least 3 dates to infer frequency')
self.deltas = lib.unique_deltas(self.values)
self.is_unique = len(self.deltas) == 1
self.is_monotonic = self.index.is_monotonic
def ydiffs(self):
return lib.unique_deltas(self.fields['Y'].astype('i8'))
def mdiffs(self):
nmonths = self.fields['Y'] * 12 + self.fields['M']
return lib.unique_deltas(nmonths.astype('i8'))
def ydiffs(self):
return lib.unique_deltas(self.fields["Y"].astype("i8"))
def mdiffs(self):
nmonths = self.fields["Y"] * 12 + self.fields["M"]
return lib.unique_deltas(nmonths.astype("i8"))
def deltas(self):
return lib.unique_deltas(self.values)
def deltas(self):
return lib.unique_deltas(self.values)