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Flags that apply to pandas objects.
Parameters
----------
obj : Series or DataFrame
The object these flags are associated with.
allows_duplicate_labels : bool, default True
Whether to allow duplicate labels in this object. By default,
duplicate labels are permitted. Setting this to ``False`` will
cause an :class:`errors.DuplicateLabelError` to be raised when
`index` (or columns for DataFrame) is not unique, or any
subsequent operation on introduces duplicates.
See :ref:`duplicates.disallow` for more.
.. warning::
This is an experimental feature. Currently, many methods fail to
propagate the ``allows_duplicate_labels`` value. In future versions
it is expected that every method taking or returning one or more
DataFrame or Series objects will propagate ``allows_duplicate_labels``.
Examples
--------
Attributes can be set in two ways:
>>> df = pd.DataFrame()
>>> df.flags
<Flags(allows_duplicate_labels=True)>
>>> df.flags.allows_duplicate_labels = False
>>> df.flags
<Flags(allows_duplicate_labels=False)>
>>> df.flags['allows_duplicate_labels'] = True
>>> df.flags
<Flags(allows_duplicate_labels=True)>
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Whether this object allows duplicate labels.
Setting ``allows_duplicate_labels=False`` ensures that the
index (and columns of a DataFrame) are unique. Most methods
that accept and return a Series or DataFrame will propagate
the value of ``allows_duplicate_labels``.
See :ref:`duplicates` for more.
See Also
--------
DataFrame.attrs : Set global metadata on this object.
DataFrame.set_flags : Set global flags on this object.
Examples
--------
>>> df = pd.DataFrame({"A": [1, 2]}, index=['a', 'a'])
>>> df.flags.allows_duplicate_labels
True
>>> df.flags.allows_duplicate_labels = False
Traceback (most recent call last):
...
pandas.errors.DuplicateLabelError: Index has duplicates.
positions
label
a [0, 1]
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