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REF: share searchsorted between DTI/TDI/PI, insert between DTI/TDI #31143

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Merged
merged 1 commit into from
Jan 20, 2020
Merged

REF: share searchsorted between DTI/TDI/PI, insert between DTI/TDI #31143

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69 changes: 68 additions & 1 deletion pandas/core/indexes/datetimelike.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,12 +27,13 @@
)
from pandas.core.dtypes.concat import concat_compat
from pandas.core.dtypes.generic import ABCIndex, ABCIndexClass, ABCSeries
from pandas.core.dtypes.missing import isna
from pandas.core.dtypes.missing import is_valid_nat_for_dtype, isna

from pandas.core import algorithms
from pandas.core.accessor import PandasDelegate
from pandas.core.arrays import DatetimeArray, ExtensionArray, TimedeltaArray
from pandas.core.arrays.datetimelike import DatetimeLikeArrayMixin
from pandas.core.base import _shared_docs
import pandas.core.indexes.base as ibase
from pandas.core.indexes.base import Index, _index_shared_docs
from pandas.core.indexes.extension import (
Expand Down Expand Up @@ -221,6 +222,18 @@ def take(self, indices, axis=0, allow_fill=True, fill_value=None, **kwargs):
self, indices, axis, allow_fill, fill_value, **kwargs
)

@Appender(_shared_docs["searchsorted"])
def searchsorted(self, value, side="left", sorter=None):
if isinstance(value, str):
raise TypeError(
"searchsorted requires compatible dtype or scalar, "
f"not {type(value).__name__}"
)
if isinstance(value, Index):
value = value._data

return self._data.searchsorted(value, side=side, sorter=sorter)

_can_hold_na = True

_na_value = NaT
Expand Down Expand Up @@ -883,6 +896,60 @@ def _wrap_joined_index(self, joined, other):
kwargs["tz"] = getattr(other, "tz", None)
return self._simple_new(joined, name, **kwargs)

# --------------------------------------------------------------------
# List-Like Methods

def insert(self, loc, item):
"""
Make new Index inserting new item at location
Parameters
----------
loc : int
item : object
if not either a Python datetime or a numpy integer-like, returned
Index dtype will be object rather than datetime.
Returns
-------
new_index : Index
"""
if isinstance(item, self._data._recognized_scalars):
item = self._data._scalar_type(item)
elif is_valid_nat_for_dtype(item, self.dtype):
# GH 18295
item = self._na_value
elif is_scalar(item) and isna(item):
raise TypeError(
f"cannot insert {type(self).__name__} with incompatible label"
)

freq = None
if isinstance(item, self._data._scalar_type) or item is NaT:
self._data._check_compatible_with(item, setitem=True)

# check freq can be preserved on edge cases
if self.size and self.freq is not None:
if item is NaT:
pass
elif (loc == 0 or loc == -len(self)) and item + self.freq == self[0]:
freq = self.freq
elif (loc == len(self)) and item - self.freq == self[-1]:
freq = self.freq
item = item.asm8

try:
new_i8s = np.concatenate(
(self[:loc].asi8, [item.view(np.int64)], self[loc:].asi8)
)
return self._shallow_copy(new_i8s, freq=freq)
except (AttributeError, TypeError):

# fall back to object index
if isinstance(item, str):
return self.astype(object).insert(loc, item)
raise TypeError(
f"cannot insert {type(self).__name__} with incompatible label"
)


class DatetimelikeDelegateMixin(PandasDelegate):
"""
Expand Down
72 changes: 2 additions & 70 deletions pandas/core/indexes/datetimes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,19 +14,18 @@
tslib as libts,
)
from pandas._libs.tslibs import ccalendar, fields, parsing, timezones
from pandas.util._decorators import Appender, Substitution, cache_readonly
from pandas.util._decorators import cache_readonly

from pandas.core.dtypes.common import _NS_DTYPE, is_float, is_integer, is_scalar
from pandas.core.dtypes.dtypes import DatetimeTZDtype
from pandas.core.dtypes.missing import is_valid_nat_for_dtype, isna
from pandas.core.dtypes.missing import isna

from pandas.core.accessor import delegate_names
from pandas.core.arrays.datetimes import (
DatetimeArray,
tz_to_dtype,
validate_tz_from_dtype,
)
from pandas.core.base import _shared_docs
import pandas.core.common as com
from pandas.core.indexes.base import Index, maybe_extract_name
from pandas.core.indexes.datetimelike import (
Expand Down Expand Up @@ -826,19 +825,6 @@ def slice_indexer(self, start=None, end=None, step=None, kind=None):

# --------------------------------------------------------------------

@Substitution(klass="DatetimeIndex")
@Appender(_shared_docs["searchsorted"])
def searchsorted(self, value, side="left", sorter=None):
if isinstance(value, str):
raise TypeError(
"searchsorted requires compatible dtype or scalar, "
f"not {type(value).__name__}"
)
if isinstance(value, Index):
value = value._data

return self._data.searchsorted(value, side=side)

def is_type_compatible(self, typ) -> bool:
return typ == self.inferred_type or typ == "datetime"

Expand All @@ -848,60 +834,6 @@ def inferred_type(self) -> str:
# sure we can't have ambiguous indexing
return "datetime64"

def insert(self, loc, item):
"""
Make new Index inserting new item at location

Parameters
----------
loc : int
item : object
if not either a Python datetime or a numpy integer-like, returned
Index dtype will be object rather than datetime.

Returns
-------
new_index : Index
"""
if isinstance(item, self._data._recognized_scalars):
item = self._data._scalar_type(item)
elif is_valid_nat_for_dtype(item, self.dtype):
# GH 18295
item = self._na_value
elif is_scalar(item) and isna(item):
# i.e. timedeltat64("NaT")
raise TypeError(
f"cannot insert {type(self).__name__} with incompatible label"
)

freq = None
if isinstance(item, self._data._scalar_type) or item is NaT:
self._data._check_compatible_with(item, setitem=True)

# check freq can be preserved on edge cases
if self.size and self.freq is not None:
if item is NaT:
pass
elif (loc == 0 or loc == -len(self)) and item + self.freq == self[0]:
freq = self.freq
elif (loc == len(self)) and item - self.freq == self[-1]:
freq = self.freq
item = item.asm8

try:
new_i8s = np.concatenate(
(self[:loc].asi8, [item.view(np.int64)], self[loc:].asi8)
)
return self._shallow_copy(new_i8s, freq=freq)
except (AttributeError, TypeError):

# fall back to object index
if isinstance(item, str):
return self.astype(object).insert(loc, item)
raise TypeError(
f"cannot insert {type(self).__name__} with incompatible label"
)

def indexer_at_time(self, time, asof=False):
"""
Return index locations of index values at particular time of day
Expand Down
8 changes: 1 addition & 7 deletions pandas/core/indexes/period.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
from pandas._libs.tslibs import NaT, frequencies as libfrequencies, resolution
from pandas._libs.tslibs.parsing import parse_time_string
from pandas._libs.tslibs.period import Period
from pandas.util._decorators import Appender, Substitution, cache_readonly
from pandas.util._decorators import Appender, cache_readonly

from pandas.core.dtypes.common import (
ensure_platform_int,
Expand All @@ -30,7 +30,6 @@
raise_on_incompatible,
validate_dtype_freq,
)
from pandas.core.base import _shared_docs
import pandas.core.common as com
import pandas.core.indexes.base as ibase
from pandas.core.indexes.base import (
Expand Down Expand Up @@ -465,11 +464,6 @@ def astype(self, dtype, copy=True, how="start"):
# TODO: should probably raise on `how` here, so we don't ignore it.
return super().astype(dtype, copy=copy)

@Substitution(klass="PeriodIndex")
@Appender(_shared_docs["searchsorted"])
def searchsorted(self, value, side="left", sorter=None):
return self._data.searchsorted(value, side=side, sorter=sorter)

@property
def is_full(self) -> bool:
"""
Expand Down
74 changes: 2 additions & 72 deletions pandas/core/indexes/timedeltas.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
import numpy as np

from pandas._libs import NaT, Timedelta, index as libindex
from pandas.util._decorators import Appender, Substitution
from pandas.util._decorators import Appender

from pandas.core.dtypes.common import (
_TD_DTYPE,
Expand All @@ -16,12 +16,11 @@
is_timedelta64_ns_dtype,
pandas_dtype,
)
from pandas.core.dtypes.missing import is_valid_nat_for_dtype, isna
from pandas.core.dtypes.missing import isna

from pandas.core.accessor import delegate_names
from pandas.core.arrays import datetimelike as dtl
from pandas.core.arrays.timedeltas import TimedeltaArray, _is_convertible_to_td
from pandas.core.base import _shared_docs
import pandas.core.common as com
from pandas.core.indexes.base import Index, _index_shared_docs, maybe_extract_name
from pandas.core.indexes.datetimelike import (
Expand Down Expand Up @@ -345,82 +344,13 @@ def _partial_td_slice(self, key):

raise NotImplementedError

@Substitution(klass="TimedeltaIndex")
@Appender(_shared_docs["searchsorted"])
def searchsorted(self, value, side="left", sorter=None):
if isinstance(value, str):
raise TypeError(
"searchsorted requires compatible dtype or scalar, "
f"not {type(value).__name__}"
)
if isinstance(value, Index):
value = value._data

return self._data.searchsorted(value, side=side, sorter=sorter)

def is_type_compatible(self, typ) -> bool:
return typ == self.inferred_type or typ == "timedelta"

@property
def inferred_type(self) -> str:
return "timedelta64"

def insert(self, loc, item):
"""
Make new Index inserting new item at location

Parameters
----------
loc : int
item : object
If not either a Python datetime or a numpy integer-like, returned
Index dtype will be object rather than datetime.

Returns
-------
new_index : Index
"""
# try to convert if possible
if isinstance(item, self._data._recognized_scalars):
item = self._data._scalar_type(item)
elif is_valid_nat_for_dtype(item, self.dtype):
# GH 18295
item = self._na_value
elif is_scalar(item) and isna(item):
# i.e. datetime64("NaT")
raise TypeError(
f"cannot insert {type(self).__name__} with incompatible label"
)

freq = None
if isinstance(item, self._data._scalar_type) or item is NaT:
self._data._check_compatible_with(item, setitem=True)

# check freq can be preserved on edge cases
if self.size and self.freq is not None:
if item is NaT:
pass
elif (loc == 0 or loc == -len(self)) and item + self.freq == self[0]:
freq = self.freq
elif (loc == len(self)) and item - self.freq == self[-1]:
freq = self.freq
item = item.asm8

try:
new_i8s = np.concatenate(
(self[:loc].asi8, [item.view(np.int64)], self[loc:].asi8)
)
tda = type(self._data)._simple_new(new_i8s, freq=freq)
return self._shallow_copy(tda)
except (AttributeError, TypeError):

# fall back to object index
if isinstance(item, str):
return self.astype(object).insert(loc, item)
raise TypeError(
f"cannot insert {type(self).__name__} with incompatible label"
)


TimedeltaIndex._add_logical_methods_disabled()

Expand Down