def to_pytimedelta(self): """ Return TimedeltaIndex as object ndarray of datetime.timedelta objects Returns ------- datetimes : ndarray """ return libts.ints_to_pytimedelta(self.asi8)
def to_pytimedelta(self): """ Return TimedeltaIndex as object ndarray of datetime.timedelta objects Returns ------- datetimes : ndarray """ return libts.ints_to_pytimedelta(self.asi8)
def _astype_nansafe(arr, dtype, copy=True): """ return a view if copy is False, but need to be very careful as the result shape could change! """ if not isinstance(dtype, np.dtype): dtype = _coerce_to_dtype(dtype) if issubclass(dtype.type, text_type): # in Py3 that's str, in Py2 that's unicode return lib.astype_unicode(arr.ravel()).reshape(arr.shape) elif issubclass(dtype.type, string_types): return lib.astype_str(arr.ravel()).reshape(arr.shape) elif is_datetime64_dtype(arr): if dtype == object: return tslib.ints_to_pydatetime(arr.view(np.int64)) elif dtype == np.int64: return arr.view(dtype) elif dtype != _NS_DTYPE: raise TypeError("cannot astype a datetimelike from [%s] to [%s]" % (arr.dtype, dtype)) return arr.astype(_NS_DTYPE) elif is_timedelta64_dtype(arr): if dtype == np.int64: return arr.view(dtype) elif dtype == object: return tslib.ints_to_pytimedelta(arr.view(np.int64)) # in py3, timedelta64[ns] are int64 elif ((PY3 and dtype not in [_INT64_DTYPE, _TD_DTYPE]) or (not PY3 and dtype != _TD_DTYPE)): # allow frequency conversions if dtype.kind == 'm': mask = isnull(arr) result = arr.astype(dtype).astype(np.float64) result[mask] = np.nan return result raise TypeError("cannot astype a timedelta from [%s] to [%s]" % (arr.dtype, dtype)) return arr.astype(_TD_DTYPE) elif (np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer)): if not np.isfinite(arr).all(): raise ValueError('Cannot convert non-finite values (NA or inf) 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) if copy: return arr.astype(dtype) return arr.view(dtype)
def astype_nansafe(arr, dtype, copy=True): """ return a view if copy is False, but need to be very careful as the result shape could change! """ if not isinstance(dtype, np.dtype): dtype = _coerce_to_dtype(dtype) if issubclass(dtype.type, text_type): # in Py3 that's str, in Py2 that's unicode return lib.astype_unicode(arr.ravel()).reshape(arr.shape) elif issubclass(dtype.type, string_types): return lib.astype_str(arr.ravel()).reshape(arr.shape) elif is_datetime64_dtype(arr): if dtype == object: return tslib.ints_to_pydatetime(arr.view(np.int64)) elif dtype == np.int64: return arr.view(dtype) elif dtype != _NS_DTYPE: raise TypeError("cannot astype a datetimelike from [%s] to [%s]" % (arr.dtype, dtype)) return arr.astype(_NS_DTYPE) elif is_timedelta64_dtype(arr): if dtype == np.int64: return arr.view(dtype) elif dtype == object: return tslib.ints_to_pytimedelta(arr.view(np.int64)) # in py3, timedelta64[ns] are int64 elif ((PY3 and dtype not in [_INT64_DTYPE, _TD_DTYPE]) or (not PY3 and dtype != _TD_DTYPE)): # allow frequency conversions if dtype.kind == 'm': mask = isnull(arr) result = arr.astype(dtype).astype(np.float64) result[mask] = np.nan return result raise TypeError("cannot astype a timedelta from [%s] to [%s]" % (arr.dtype, dtype)) return arr.astype(_TD_DTYPE) elif (np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer)): if not np.isfinite(arr).all(): raise ValueError('Cannot convert non-finite values (NA or inf) 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) if copy: return arr.astype(dtype) return arr.view(dtype)
def _convert_datetimelike_to_object(x): # coerce datetimelike array to object dtype # if dtype is of datetimetz or timezone if x.dtype.kind == _NS_DTYPE.kind: if getattr(x, 'tz', None) is not None: x = x.astype(object).values else: shape = x.shape x = tslib.ints_to_pydatetime(x.view(np.int64).ravel(), box="timestamp") x = x.reshape(shape) elif x.dtype == _TD_DTYPE: shape = x.shape x = tslib.ints_to_pytimedelta(x.view(np.int64).ravel(), box=True) x = x.reshape(shape) return x
def convert_to_pydatetime(x, axis): # coerce to an object dtype # if dtype is of datetimetz or timezone if x.dtype.kind == _NS_DTYPE.kind: if getattr(x, 'tz', None) is not None: x = x.asobject.values else: shape = x.shape x = tslib.ints_to_pydatetime(x.view(np.int64).ravel(), box=True) x = x.reshape(shape) elif x.dtype == _TD_DTYPE: shape = x.shape x = tslib.ints_to_pytimedelta(x.view(np.int64).ravel(), box=True) x = x.reshape(shape) if axis == 1: x = np.atleast_2d(x) return x
def astype_nansafe(arr, dtype, copy=True): """ return a view if copy is False, but need to be very careful as the result shape could change! """ if not isinstance(dtype, np.dtype): dtype = pandas_dtype(dtype) if issubclass(dtype.type, text_type): # in Py3 that's str, in Py2 that's unicode return lib.astype_unicode(arr.ravel()).reshape(arr.shape) elif issubclass(dtype.type, string_types): return lib.astype_str(arr.ravel()).reshape(arr.shape) elif is_datetime64_dtype(arr): if dtype == object: return tslib.ints_to_pydatetime(arr.view(np.int64)) elif dtype == np.int64: return arr.view(dtype) elif dtype != _NS_DTYPE: raise TypeError("cannot astype a datetimelike from [{from_dtype}] " "to [{to_dtype}]".format(from_dtype=arr.dtype, to_dtype=dtype)) return arr.astype(_NS_DTYPE) elif is_timedelta64_dtype(arr): if dtype == np.int64: return arr.view(dtype) elif dtype == object: return tslib.ints_to_pytimedelta(arr.view(np.int64)) # in py3, timedelta64[ns] are int64 elif ((PY3 and dtype not in [_INT64_DTYPE, _TD_DTYPE]) or (not PY3 and dtype != _TD_DTYPE)): # allow frequency conversions if dtype.kind == 'm': mask = isna(arr) result = arr.astype(dtype).astype(np.float64) result[mask] = np.nan return result raise TypeError("cannot astype a timedelta from [{from_dtype}] " "to [{to_dtype}]".format(from_dtype=arr.dtype, to_dtype=dtype)) return arr.astype(_TD_DTYPE) elif (np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer)): if not np.isfinite(arr).all(): raise ValueError('Cannot convert non-finite values (NA or inf) 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) if dtype.name in ("datetime64", "timedelta64"): msg = ("Passing in '{dtype}' dtype with no frequency is " "deprecated and will raise in a future version. " "Please pass in '{dtype}[ns]' instead.") warnings.warn(msg.format(dtype=dtype.name), FutureWarning, stacklevel=5) dtype = np.dtype(dtype.name + "[ns]") if copy: return arr.astype(dtype) return arr.view(dtype)
def astype_nansafe(arr, dtype, copy=True): """ return a view if copy is False, but need to be very careful as the result shape could change! """ if not isinstance(dtype, np.dtype): dtype = pandas_dtype(dtype) if issubclass(dtype.type, text_type): # in Py3 that's str, in Py2 that's unicode return lib.astype_unicode(arr.ravel()).reshape(arr.shape) elif issubclass(dtype.type, string_types): return lib.astype_str(arr.ravel()).reshape(arr.shape) elif is_datetime64_dtype(arr): if dtype == object: return tslib.ints_to_pydatetime(arr.view(np.int64)) elif dtype == np.int64: return arr.view(dtype) elif dtype != _NS_DTYPE: raise TypeError("cannot astype a datetimelike from [{from_dtype}] " "to [{to_dtype}]".format(from_dtype=arr.dtype, to_dtype=dtype)) return arr.astype(_NS_DTYPE) elif is_timedelta64_dtype(arr): if dtype == np.int64: return arr.view(dtype) elif dtype == object: return tslib.ints_to_pytimedelta(arr.view(np.int64)) # in py3, timedelta64[ns] are int64 elif ((PY3 and dtype not in [_INT64_DTYPE, _TD_DTYPE]) or (not PY3 and dtype != _TD_DTYPE)): # allow frequency conversions if dtype.kind == 'm': mask = isna(arr) result = arr.astype(dtype).astype(np.float64) result[mask] = np.nan return result raise TypeError("cannot astype a timedelta from [{from_dtype}] " "to [{to_dtype}]".format(from_dtype=arr.dtype, to_dtype=dtype)) return arr.astype(_TD_DTYPE) elif (np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer)): if not np.isfinite(arr).all(): raise ValueError('Cannot convert non-finite values (NA or inf) 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) if dtype.name in ("datetime64", "timedelta64"): msg = ("Passing in '{dtype}' dtype with no frequency is " "deprecated and will raise in a future version. " "Please pass in '{dtype}[ns]' instead.") warnings.warn(msg.format(dtype=dtype.name), FutureWarning, stacklevel=5) dtype = np.dtype(dtype.name + "[ns]") if copy: return arr.astype(dtype) return arr.view(dtype)