def get_loc(self, key, method=None, tolerance=None): """ Get integer location for requested label Returns ------- loc : int """ if not is_scalar(key): raise InvalidIndexError(key) orig_key = key if is_valid_nat_for_dtype(key, self.dtype): key = NaT if isinstance(key, self._data._recognized_scalars): # needed to localize naive datetimes key = self._maybe_cast_for_get_loc(key) elif isinstance(key, str): try: return self._get_string_slice(key) except (TypeError, KeyError, ValueError, OverflowError): pass try: key = self._maybe_cast_for_get_loc(key) except ValueError as err: raise KeyError(key) from err elif isinstance(key, timedelta): # GH#20464 raise TypeError( f"Cannot index {type(self).__name__} with {type(key).__name__}" ) elif isinstance(key, time): if method is not None: raise NotImplementedError( "cannot yet lookup inexact labels when key is a time object" ) return self.indexer_at_time(key) else: # unrecognized type raise KeyError(key) try: return Index.get_loc(self, key, method, tolerance) except KeyError as err: raise KeyError(orig_key) from err
def get_indexer( self, target: AnyArrayLike, method: Optional[str] = None, limit: Optional[int] = None, tolerance: Optional[Any] = None, ) -> np.ndarray: self._check_method(method) if self.is_overlapping: msg = ("cannot handle overlapping indices; use " "IntervalIndex.get_indexer_non_unique") raise InvalidIndexError(msg) target_as_index = ensure_index(target) if isinstance(target_as_index, IntervalIndex): # equal indexes -> 1:1 positional match if self.equals(target_as_index): return np.arange(len(self), dtype="intp") # different closed or incompatible subtype -> no matches common_subtype = find_common_type( [self.dtype.subtype, target_as_index.dtype.subtype]) if self.closed != target_as_index.closed or is_object_dtype( common_subtype): return np.repeat(np.intp(-1), len(target_as_index)) # non-overlapping -> at most one match per interval in target_as_index # want exact matches -> need both left/right to match, so defer to # left/right get_indexer, compare elementwise, equality -> match left_indexer = self.left.get_indexer(target_as_index.left) right_indexer = self.right.get_indexer(target_as_index.right) indexer = np.where(left_indexer == right_indexer, left_indexer, -1) elif not is_object_dtype(target_as_index): # homogeneous scalar index: use IntervalTree target_as_index = self._maybe_convert_i8(target_as_index) indexer = self._engine.get_indexer(target_as_index.values) else: # heterogeneous scalar index: defer elementwise to get_loc # (non-overlapping so get_loc guarantees scalar of KeyError) indexer = [] for key in target_as_index: try: loc = self.get_loc(key) except KeyError: loc = -1 indexer.append(loc) return ensure_platform_int(indexer)
def get_loc(self, key, method=None, tolerance=None): """ Get integer location for requested label Returns ------- loc : int """ if not is_scalar(key): raise InvalidIndexError(key) if is_valid_nat_for_dtype(key, self.dtype): key = NaT if tolerance is not None: # try converting tolerance now, so errors don't get swallowed by # the try/except clauses below tolerance = self._convert_tolerance(tolerance, np.asarray(key)) if isinstance(key, (datetime, np.datetime64)): # needed to localize naive datetimes key = self._maybe_cast_for_get_loc(key) return Index.get_loc(self, key, method, tolerance) elif isinstance(key, str): try: return self._get_string_slice(key) except (TypeError, KeyError, ValueError, OverflowError): pass try: stamp = self._maybe_cast_for_get_loc(key) return Index.get_loc(self, stamp, method, tolerance) except (KeyError, ValueError): raise KeyError(key) elif isinstance(key, timedelta): # GH#20464 raise TypeError( f"Cannot index {type(self).__name__} with {type(key).__name__}" ) if isinstance(key, time): if method is not None: raise NotImplementedError( "cannot yet lookup inexact labels when key is a time object" ) return self.indexer_at_time(key) return Index.get_loc(self, key, method, tolerance)
def get_loc(self, key, method=None, tolerance=None): """ Get integer location for requested label Returns ------- loc : int, slice, or ndarray[int] """ if not is_scalar(key): raise InvalidIndexError(key) msg = str(key) try: key = self._data._validate_scalar(key, msg, cast_str=True) except TypeError as err: raise KeyError(key) from err return Index.get_loc(self, key, method, tolerance)
def get_loc(self, key, method: Optional[str] = None, tolerance=None) -> Union[int, slice, np.ndarray]: """ Get integer location, slice or boolean mask for requested label. Parameters ---------- key : label method : {None}, optional * default: matches where the label is within an interval only. Returns ------- int if unique index, slice if monotonic index, else mask Examples -------- >>> i1, i2 = pd.Interval(0, 1), pd.Interval(1, 2) >>> index = pd.IntervalIndex([i1, i2]) >>> index.get_loc(1) 0 You can also supply a point inside an interval. >>> index.get_loc(1.5) 1 If a label is in several intervals, you get the locations of all the relevant intervals. >>> i3 = pd.Interval(0, 2) >>> overlapping_index = pd.IntervalIndex([i1, i2, i3]) >>> overlapping_index.get_loc(0.5) array([ True, False, True]) Only exact matches will be returned if an interval is provided. >>> index.get_loc(pd.Interval(0, 1)) 0 """ self._check_method(method) if not is_scalar(key): raise InvalidIndexError(key) if isinstance(key, Interval): if self.closed != key.closed: raise KeyError(key) mask = (self.left == key.left) & (self.right == key.right) else: # assume scalar op_left = le if self.closed_left else lt op_right = le if self.closed_right else lt try: mask = op_left(self.left, key) & op_right(key, self.right) except TypeError as err: # scalar is not comparable to II subtype --> invalid label raise KeyError(key) from err matches = mask.sum() if matches == 0: raise KeyError(key) elif matches == 1: return mask.argmax() return lib.maybe_booleans_to_slice(mask.view("u1"))
def get_loc(self, key, method=None, tolerance=None): """ Get integer location for requested label. Parameters ---------- key : Period, NaT, str, or datetime String or datetime key must be parseable as Period. Returns ------- loc : int or ndarray[int64] Raises ------ KeyError Key is not present in the index. TypeError If key is listlike or otherwise not hashable. """ orig_key = key if not is_scalar(key): raise InvalidIndexError(key) if isinstance(key, str): try: loc = self._get_string_slice(key) return loc except (TypeError, ValueError): pass try: asdt, reso = parse_time_string(key, self.freq) except DateParseError as err: # A string with invalid format raise KeyError(f"Cannot interpret '{key}' as period") from err grp = resolution.Resolution.get_freq_group(reso) freqn = resolution.get_freq_group(self.freq) # _get_string_slice will handle cases where grp < freqn assert grp >= freqn if grp == freqn: key = Period(asdt, freq=self.freq) loc = self.get_loc(key, method=method, tolerance=tolerance) return loc elif method is None: raise KeyError(key) else: key = asdt elif is_integer(key): # Period constructor will cast to string, which we dont want raise KeyError(key) try: key = Period(key, freq=self.freq) except ValueError as err: # we cannot construct the Period raise KeyError(orig_key) from err try: return Index.get_loc(self, key, method, tolerance) except KeyError as err: raise KeyError(orig_key) from err