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_indexing_method(method)
if self.is_overlapping:
raise InvalidIndexError("cannot handle overlapping indices; "
"use IntervalIndex.get_indexer_non_unique")
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")
if self._is_non_comparable_own_type(target_as_index):
# different closed or incompatible subtype -> no matches
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 is_categorical_dtype(target_as_index.dtype):
target_as_index = cast("CategoricalIndex", target_as_index)
# get an indexer for unique categories then propagate to codes via take_1d
categories_indexer = self.get_indexer(target_as_index.categories)
indexer = take_1d(categories_indexer,
target_as_index.codes,
fill_value=-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
return self._get_indexer_pointwise(target_as_index)[0]
return ensure_platform_int(indexer)
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)
try:
key = self._data._validate_scalar(key, unbox=False)
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 parsable 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 (ValueError, DateParseError) as err:
# A string with invalid format
raise KeyError(f"Cannot interpret '{key}' as period") from err
reso = Resolution.from_attrname(reso)
grp = reso.freq_group
freqn = self.dtype.freq_group
# _get_string_slice will handle cases where grp < freqn
assert grp >= freqn
# BusinessDay is a bit strange. It has a *lower* code, but we never parse
# a string as "BusinessDay" resolution, just Day.
if grp == freqn or (
reso == Resolution.RESO_DAY and self.dtype.freq.name == "B"
):
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
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 parsable 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 is_valid_na_for_dtype(key, self.dtype):
key = NaT
elif isinstance(key, str):
try:
loc = self._get_string_slice(key)
return loc
except (TypeError, ValueError):
pass
try:
asdt, reso_str = parse_time_string(key, self.freq)
except (ValueError, DateParseError) as err:
# A string with invalid format
raise KeyError(f"Cannot interpret '{key}' as period") from err
reso = Resolution.from_attrname(reso_str)
grp = reso.freq_group.value
freqn = self.dtype.freq_group_code
# _get_string_slice will handle cases where grp < freqn
assert grp >= freqn
# BusinessDay is a bit strange. It has a *lower* code, but we never parse
# a string as "BusinessDay" resolution, just Day.
if grp == freqn or (reso == Resolution.RESO_DAY
and self.dtype.freq.name == "B"):
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 isinstance(key, Period):
sfreq = self.freq
kfreq = key.freq
if not (sfreq.n == kfreq.n
and sfreq._period_dtype_code == kfreq._period_dtype_code):
# GH#42247 For the subset of DateOffsets that can be Period freqs,
# checking these two attributes is sufficient to check equality,
# and much more performant than `self.freq == key.freq`
raise KeyError(key)
elif isinstance(key, datetime):
try:
key = Period(key, freq=self.freq)
except ValueError as err:
# we cannot construct the Period
raise KeyError(orig_key) from err
else:
# in particular integer, which Period constructor would cast to string
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
