def to_pydatetime(self):
"""
Return DatetimeIndex as object ndarray of datetime.datetime objects
Returns
-------
datetimes : ndarray
"""
return lib.ints_to_pydatetime(self.asi8, tz=self.tz)
def to_pydatetime(self):
"""
Return DatetimeIndex as object ndarray of datetime.datetime objects
Returns
-------
datetimes : ndarray
"""
return lib.ints_to_pydatetime(self.asi8, tz=self.tz)
def _astype_nansafe(arr, dtype):
if isinstance(dtype, basestring):
dtype = np.dtype(dtype)
if issubclass(arr.dtype.type, np.datetime64):
if dtype == object:
return lib.ints_to_pydatetime(arr.view(np.int64))
elif np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer):
if np.isnan(arr).any():
raise ValueError("Cannot convert NA to integer")
return arr.astype(dtype)
def _astype_nansafe(arr, dtype):
if isinstance(dtype, basestring):
dtype = np.dtype(dtype)
if issubclass(arr.dtype.type, np.datetime64):
if dtype == object:
return lib.ints_to_pydatetime(arr.view(np.int64))
elif (np.issubdtype(arr.dtype, np.floating)
and np.issubdtype(dtype, np.integer)):
if np.isnan(arr).any():
raise ValueError('Cannot convert NA to integer')
return arr.astype(dtype)
def _astype_nansafe(arr, dtype):
if not isinstance(dtype, np.dtype):
dtype = np.dtype(dtype)
if issubclass(arr.dtype.type, np.datetime64):
if dtype == object:
return lib.ints_to_pydatetime(arr.view(np.int64))
elif np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer):
if np.isnan(arr).any():
raise ValueError("Cannot convert NA to integer")
elif arr.dtype == np.object_ and np.issubdtype(dtype.type, np.integer):
# work around NumPy brokenness, #1987
return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
return arr.astype(dtype)
def _astype_nansafe(arr, dtype):
if not isinstance(dtype, np.dtype):
dtype = np.dtype(dtype)
if issubclass(arr.dtype.type, np.datetime64):
if dtype == object:
return lib.ints_to_pydatetime(arr.view(np.int64))
elif (np.issubdtype(arr.dtype, np.floating)
and np.issubdtype(dtype, np.integer)):
if np.isnan(arr).any():
raise ValueError('Cannot convert NA to integer')
elif arr.dtype == np.object_ and np.issubdtype(dtype.type, np.integer):
# work around NumPy brokenness, #1987
return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
return arr.astype(dtype)
def get_values(self, dtype):
if dtype == object:
flat_i8 = self.values.ravel().view(np.int64)
res = lib.ints_to_pydatetime(flat_i8)
return res.reshape(self.values.shape)
return self.values
def _mpl_repr(self):
# how to represent ourselves to matplotlib
return lib.ints_to_pydatetime(self.asi8)
def _mpl_repr(self):
# how to represent ourselves to matplotlib
return lib.ints_to_pydatetime(self.asi8)
# <codecell>
from pandas import lib
from matplotlib.ticker import FuncFormatter
fig, axes = plt.subplots(figsize=(12,8))
data = group[["poll_date", "obama_spread"]]
data = pandas.concat((data, national_data2012[["poll_date", "obama_spread"]]))
data.sort("poll_date", inplace=True)
dates = pandas.DatetimeIndex(data.poll_date).asi8
loess_res = sm.nonparametric.lowess(data.obama_spread.values, dates,
frac=.2, it=3)
dates_x = lib.ints_to_pydatetime(dates)
axes.scatter(dates_x, data["obama_spread"])
axes.plot(dates_x, loess_res[:,1], color='r')
axes.yaxis.get_major_locator().set_params(nbins=12)
axes.yaxis.set_major_formatter(FuncFormatter(edit_tick_label))
axes.grid(False, axis='x')
axes.hlines(0, dates_x[0], dates_x[-1], color='black', lw=3)
axes.margins(0, .05)
# <codecell>
loess_res[-7:,1].mean()
# <codecell>
from pandas import lib
def get_values(self, dtype):
if dtype == object:
flat_i8 = self.values.ravel().view(np.int64)
res = lib.ints_to_pydatetime(flat_i8)
return res.reshape(self.values.shape)
return self.values
