370 lines
9.7 KiB
Python
370 lines
9.7 KiB
Python
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from __future__ import annotations
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import textwrap
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from typing import cast
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import numpy as np
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from pandas._libs import (
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NaT,
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lib,
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)
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from pandas._typing import Axis
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from pandas.errors import InvalidIndexError
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from pandas.core.dtypes.cast import find_common_type
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from pandas.core.algorithms import safe_sort
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from pandas.core.indexes.base import (
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Index,
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_new_Index,
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ensure_index,
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ensure_index_from_sequences,
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get_unanimous_names,
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)
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from pandas.core.indexes.category import CategoricalIndex
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from pandas.core.indexes.datetimes import DatetimeIndex
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from pandas.core.indexes.interval import IntervalIndex
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from pandas.core.indexes.multi import MultiIndex
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from pandas.core.indexes.period import PeriodIndex
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from pandas.core.indexes.range import RangeIndex
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from pandas.core.indexes.timedeltas import TimedeltaIndex
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_sort_msg = textwrap.dedent(
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"""\
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Sorting because non-concatenation axis is not aligned. A future version
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of pandas will change to not sort by default.
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To accept the future behavior, pass 'sort=False'.
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To retain the current behavior and silence the warning, pass 'sort=True'.
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"""
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)
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__all__ = [
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"Index",
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"MultiIndex",
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"CategoricalIndex",
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"IntervalIndex",
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"RangeIndex",
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"InvalidIndexError",
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"TimedeltaIndex",
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"PeriodIndex",
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"DatetimeIndex",
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"_new_Index",
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"NaT",
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"ensure_index",
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"ensure_index_from_sequences",
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"get_objs_combined_axis",
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"union_indexes",
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"get_unanimous_names",
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"all_indexes_same",
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"default_index",
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"safe_sort_index",
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]
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def get_objs_combined_axis(
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objs, intersect: bool = False, axis: Axis = 0, sort: bool = True, copy: bool = False
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) -> Index:
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"""
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Extract combined index: return intersection or union (depending on the
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value of "intersect") of indexes on given axis, or None if all objects
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lack indexes (e.g. they are numpy arrays).
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Parameters
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----------
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objs : list
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Series or DataFrame objects, may be mix of the two.
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intersect : bool, default False
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If True, calculate the intersection between indexes. Otherwise,
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calculate the union.
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axis : {0 or 'index', 1 or 'outer'}, default 0
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The axis to extract indexes from.
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sort : bool, default True
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Whether the result index should come out sorted or not.
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copy : bool, default False
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If True, return a copy of the combined index.
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Returns
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-------
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Index
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"""
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obs_idxes = [obj._get_axis(axis) for obj in objs]
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return _get_combined_index(obs_idxes, intersect=intersect, sort=sort, copy=copy)
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def _get_distinct_objs(objs: list[Index]) -> list[Index]:
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"""
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Return a list with distinct elements of "objs" (different ids).
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Preserves order.
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"""
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ids: set[int] = set()
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res = []
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for obj in objs:
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if id(obj) not in ids:
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ids.add(id(obj))
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res.append(obj)
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return res
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def _get_combined_index(
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indexes: list[Index],
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intersect: bool = False,
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sort: bool = False,
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copy: bool = False,
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) -> Index:
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"""
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Return the union or intersection of indexes.
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Parameters
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----------
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indexes : list of Index or list objects
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When intersect=True, do not accept list of lists.
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intersect : bool, default False
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If True, calculate the intersection between indexes. Otherwise,
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calculate the union.
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sort : bool, default False
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Whether the result index should come out sorted or not.
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copy : bool, default False
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If True, return a copy of the combined index.
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Returns
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-------
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Index
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"""
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# TODO: handle index names!
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indexes = _get_distinct_objs(indexes)
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if len(indexes) == 0:
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index = Index([])
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elif len(indexes) == 1:
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index = indexes[0]
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elif intersect:
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index = indexes[0]
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for other in indexes[1:]:
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index = index.intersection(other)
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else:
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index = union_indexes(indexes, sort=False)
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index = ensure_index(index)
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if sort:
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index = safe_sort_index(index)
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# GH 29879
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if copy:
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index = index.copy()
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return index
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def safe_sort_index(index: Index) -> Index:
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"""
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Returns the sorted index
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We keep the dtypes and the name attributes.
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Parameters
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----------
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index : an Index
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Returns
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-------
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Index
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"""
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if index.is_monotonic_increasing:
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return index
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try:
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array_sorted = safe_sort(index)
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except TypeError:
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pass
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else:
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if isinstance(array_sorted, Index):
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return array_sorted
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array_sorted = cast(np.ndarray, array_sorted)
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if isinstance(index, MultiIndex):
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index = MultiIndex.from_tuples(array_sorted, names=index.names)
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else:
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index = Index(array_sorted, name=index.name, dtype=index.dtype)
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return index
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def union_indexes(indexes, sort: bool | None = True) -> Index:
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"""
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Return the union of indexes.
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The behavior of sort and names is not consistent.
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Parameters
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----------
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indexes : list of Index or list objects
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sort : bool, default True
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Whether the result index should come out sorted or not.
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Returns
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-------
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Index
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"""
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if len(indexes) == 0:
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raise AssertionError("Must have at least 1 Index to union")
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if len(indexes) == 1:
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result = indexes[0]
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if isinstance(result, list):
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result = Index(sorted(result))
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return result
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indexes, kind = _sanitize_and_check(indexes)
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def _unique_indices(inds, dtype) -> Index:
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"""
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Convert indexes to lists and concatenate them, removing duplicates.
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The final dtype is inferred.
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Parameters
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----------
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inds : list of Index or list objects
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dtype : dtype to set for the resulting Index
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Returns
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-------
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Index
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"""
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def conv(i):
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if isinstance(i, Index):
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i = i.tolist()
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return i
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return Index(
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lib.fast_unique_multiple_list([conv(i) for i in inds], sort=sort),
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dtype=dtype,
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)
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def _find_common_index_dtype(inds):
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"""
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Finds a common type for the indexes to pass through to resulting index.
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Parameters
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----------
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inds: list of Index or list objects
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Returns
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-------
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The common type or None if no indexes were given
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"""
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dtypes = [idx.dtype for idx in indexes if isinstance(idx, Index)]
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if dtypes:
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dtype = find_common_type(dtypes)
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else:
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dtype = None
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return dtype
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if kind == "special":
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result = indexes[0]
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dtis = [x for x in indexes if isinstance(x, DatetimeIndex)]
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dti_tzs = [x for x in dtis if x.tz is not None]
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if len(dti_tzs) not in [0, len(dtis)]:
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# TODO: this behavior is not tested (so may not be desired),
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# but is kept in order to keep behavior the same when
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# deprecating union_many
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# test_frame_from_dict_with_mixed_indexes
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raise TypeError("Cannot join tz-naive with tz-aware DatetimeIndex")
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if len(dtis) == len(indexes):
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sort = True
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result = indexes[0]
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elif len(dtis) > 1:
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# If we have mixed timezones, our casting behavior may depend on
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# the order of indexes, which we don't want.
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sort = False
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# TODO: what about Categorical[dt64]?
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# test_frame_from_dict_with_mixed_indexes
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indexes = [x.astype(object, copy=False) for x in indexes]
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result = indexes[0]
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for other in indexes[1:]:
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result = result.union(other, sort=None if sort else False)
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return result
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elif kind == "array":
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dtype = _find_common_index_dtype(indexes)
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index = indexes[0]
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if not all(index.equals(other) for other in indexes[1:]):
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index = _unique_indices(indexes, dtype)
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name = get_unanimous_names(*indexes)[0]
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if name != index.name:
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index = index.rename(name)
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return index
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else: # kind='list'
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dtype = _find_common_index_dtype(indexes)
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return _unique_indices(indexes, dtype)
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def _sanitize_and_check(indexes):
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"""
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Verify the type of indexes and convert lists to Index.
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Cases:
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- [list, list, ...]: Return ([list, list, ...], 'list')
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- [list, Index, ...]: Return _sanitize_and_check([Index, Index, ...])
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Lists are sorted and converted to Index.
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- [Index, Index, ...]: Return ([Index, Index, ...], TYPE)
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TYPE = 'special' if at least one special type, 'array' otherwise.
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Parameters
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----------
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indexes : list of Index or list objects
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Returns
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-------
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sanitized_indexes : list of Index or list objects
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type : {'list', 'array', 'special'}
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"""
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kinds = list({type(index) for index in indexes})
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if list in kinds:
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if len(kinds) > 1:
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indexes = [
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Index(list(x)) if not isinstance(x, Index) else x for x in indexes
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]
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kinds.remove(list)
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else:
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return indexes, "list"
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if len(kinds) > 1 or Index not in kinds:
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return indexes, "special"
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else:
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return indexes, "array"
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def all_indexes_same(indexes) -> bool:
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"""
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Determine if all indexes contain the same elements.
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Parameters
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----------
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indexes : iterable of Index objects
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Returns
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-------
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bool
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True if all indexes contain the same elements, False otherwise.
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"""
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itr = iter(indexes)
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first = next(itr)
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return all(first.equals(index) for index in itr)
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def default_index(n: int) -> RangeIndex:
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rng = range(0, n)
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return RangeIndex._simple_new(rng, name=None)
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