def equals(self, other): """ Determines if two Index objects contain the same elements. """ if self is other: return True if (not hasattr(other, 'inferred_type') or other.inferred_type != 'datetime64'): if self.offset is not None: return False try: other = DatetimeIndex(other) except: return False if self.tz is not None: if other.tz is None: return False same_zone = lib.get_timezone(self.tz) == lib.get_timezone(other.tz) else: if other.tz is not None: return False same_zone = True return same_zone and np.array_equal(self.asi8, other.asi8)
def _write_index(self, group, key, index): if isinstance(index, MultiIndex): setattr(group._v_attrs, '%s_variety' % key, 'multi') self._write_multi_index(group, key, index) elif isinstance(index, BlockIndex): setattr(group._v_attrs, '%s_variety' % key, 'block') self._write_block_index(group, key, index) elif isinstance(index, IntIndex): setattr(group._v_attrs, '%s_variety' % key, 'sparseint') self._write_sparse_intindex(group, key, index) else: setattr(group._v_attrs, '%s_variety' % key, 'regular') converted, kind, _ = _convert_index(index) self._write_array(group, key, converted) node = getattr(group, key) node._v_attrs.kind = kind node._v_attrs.name = index.name if isinstance(index, (DatetimeIndex, PeriodIndex)): node._v_attrs.index_class = _class_to_alias(type(index)) if hasattr(index, 'freq'): node._v_attrs.freq = index.freq if hasattr(index, 'tz') and index.tz is not None: zone = lib.get_timezone(index.tz) if zone is None: zone = lib.tot_seconds(index.tz.utcoffset()) node._v_attrs.tz = zone
def _prep_index(self,obj,duplicates={},data_start=0): info = {} types = {} data = [] for i in range(obj.index.nlevels): name = obj.index.names[i] if name == None: str_name = 'index_%d'%i else: str_name = str(name) if str_name in info: if str_name in duplicates: duplicates[str_name] += 1 else: duplicates[str_name] = 1 str_name = str_name + '_%d'%duplicates[str_name] if isinstance(obj.index, MultiIndex): values = obj.index.levels[i] else: values = obj.index.values converted, kind, type = _convert_index(values,position=data_start+i) info[str_name] = {'name_data':name} if hasattr(values, 'freq'): info[str_name]['freq'] = values.freq if hasattr(values, 'tz') and values.tz is not None: zone = lib.get_timezone(values.tz) if zone is None: zone = lib.tot_seconds(values.tz.utcoffset()) info[str_name]['tz'] = zone info[str_name]['kind'] = kind info[str_name]['isIndex'] = True info[str_name]['position'] = i types[str_name] = type data.append(converted) return info,types,data,duplicates,i+1
def _infer(a, b): tz = a.tzinfo if b and b.tzinfo: assert (lib.get_timezone(tz) == lib.get_timezone(b.tzinfo)) return tz
def _infer(a, b): tz = a.tzinfo if b and b.tzinfo: assert(lib.get_timezone(tz) == lib.get_timezone(b.tzinfo)) return tz