Re-index either a Dataset or a DataArray. Not public API.
(
obj: T_Alignable,
indexers: Mapping[Any, Any],
method: str | None = None,
tolerance: float | Iterable[float] | str | None = None,
copy: bool = True,
fill_value: Any = dtypes.NA,
sparse: bool = False,
exclude_vars: Iterable[Hashable] = frozenset(),
)
| 1047 | |
| 1048 | |
| 1049 | def reindex( |
| 1050 | obj: T_Alignable, |
| 1051 | indexers: Mapping[Any, Any], |
| 1052 | method: str | None = None, |
| 1053 | tolerance: float | Iterable[float] | str | None = None, |
| 1054 | copy: bool = True, |
| 1055 | fill_value: Any = dtypes.NA, |
| 1056 | sparse: bool = False, |
| 1057 | exclude_vars: Iterable[Hashable] = frozenset(), |
| 1058 | ) -> T_Alignable: |
| 1059 | """Re-index either a Dataset or a DataArray. |
| 1060 | |
| 1061 | Not public API. |
| 1062 | |
| 1063 | """ |
| 1064 | |
| 1065 | # TODO: (benbovy - explicit indexes): uncomment? |
| 1066 | # --> from reindex docstrings: "any mismatched dimension is simply ignored" |
| 1067 | # bad_keys = [k for k in indexers if k not in obj._indexes and k not in obj.dims] |
| 1068 | # if bad_keys: |
| 1069 | # raise ValueError( |
| 1070 | # f"indexer keys {bad_keys} do not correspond to any indexed coordinate " |
| 1071 | # "or unindexed dimension in the object to reindex" |
| 1072 | # ) |
| 1073 | |
| 1074 | aligner = Aligner( |
| 1075 | (obj,), |
| 1076 | indexes=indexers, |
| 1077 | method=method, |
| 1078 | tolerance=tolerance, |
| 1079 | copy=copy, |
| 1080 | fill_value=fill_value, |
| 1081 | sparse=sparse, |
| 1082 | exclude_vars=exclude_vars, |
| 1083 | ) |
| 1084 | aligner.align() |
| 1085 | return aligner.results[0] |
| 1086 | |
| 1087 | |
| 1088 | def reindex_like( |
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