118 lines
3.7 KiB
Python
118 lines
3.7 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING
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import weakref
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if TYPE_CHECKING:
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from pandas.core.generic import NDFrame
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class Flags:
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"""
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Flags that apply to pandas objects.
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Parameters
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----------
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obj : Series or DataFrame
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The object these flags are associated with.
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allows_duplicate_labels : bool, default True
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Whether to allow duplicate labels in this object. By default,
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duplicate labels are permitted. Setting this to ``False`` will
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cause an :class:`errors.DuplicateLabelError` to be raised when
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`index` (or columns for DataFrame) is not unique, or any
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subsequent operation on introduces duplicates.
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See :ref:`duplicates.disallow` for more.
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.. warning::
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This is an experimental feature. Currently, many methods fail to
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propagate the ``allows_duplicate_labels`` value. In future versions
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it is expected that every method taking or returning one or more
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DataFrame or Series objects will propagate ``allows_duplicate_labels``.
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Examples
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--------
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Attributes can be set in two ways:
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>>> df = pd.DataFrame()
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>>> df.flags
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<Flags(allows_duplicate_labels=True)>
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>>> df.flags.allows_duplicate_labels = False
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>>> df.flags
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<Flags(allows_duplicate_labels=False)>
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>>> df.flags['allows_duplicate_labels'] = True
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>>> df.flags
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<Flags(allows_duplicate_labels=True)>
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"""
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_keys: set[str] = {"allows_duplicate_labels"}
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def __init__(self, obj: NDFrame, *, allows_duplicate_labels: bool) -> None:
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self._allows_duplicate_labels = allows_duplicate_labels
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self._obj = weakref.ref(obj)
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@property
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def allows_duplicate_labels(self) -> bool:
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"""
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Whether this object allows duplicate labels.
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Setting ``allows_duplicate_labels=False`` ensures that the
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index (and columns of a DataFrame) are unique. Most methods
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that accept and return a Series or DataFrame will propagate
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the value of ``allows_duplicate_labels``.
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See :ref:`duplicates` for more.
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See Also
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--------
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DataFrame.attrs : Set global metadata on this object.
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DataFrame.set_flags : Set global flags on this object.
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Examples
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--------
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>>> df = pd.DataFrame({"A": [1, 2]}, index=['a', 'a'])
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>>> df.flags.allows_duplicate_labels
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True
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>>> df.flags.allows_duplicate_labels = False
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Traceback (most recent call last):
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...
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pandas.errors.DuplicateLabelError: Index has duplicates.
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positions
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label
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a [0, 1]
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"""
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return self._allows_duplicate_labels
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@allows_duplicate_labels.setter
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def allows_duplicate_labels(self, value: bool) -> None:
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value = bool(value)
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obj = self._obj()
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if obj is None:
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raise ValueError("This flag's object has been deleted.")
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if not value:
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for ax in obj.axes:
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ax._maybe_check_unique()
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self._allows_duplicate_labels = value
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def __getitem__(self, key: str):
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if key not in self._keys:
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raise KeyError(key)
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return getattr(self, key)
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def __setitem__(self, key: str, value) -> None:
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if key not in self._keys:
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raise ValueError(f"Unknown flag {key}. Must be one of {self._keys}")
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setattr(self, key, value)
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def __repr__(self) -> str:
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return f"<Flags(allows_duplicate_labels={self.allows_duplicate_labels})>"
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def __eq__(self, other) -> bool:
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if isinstance(other, type(self)):
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return self.allows_duplicate_labels == other.allows_duplicate_labels
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return False
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