BPt.Dataset.set_flags#

Dataset.set_flags(*, copy=False, allows_duplicate_labels=None)[source]#

Return a new object with updated flags.

Parameters

allows_duplicate_labelsbool, optional: Whether the returned object allows duplicate labels.

Returns

Series or DataFrame: The same type as the caller.

See also

DataFrame.attrs: Global metadata applying to this dataset.
DataFrame.flags: Global flags applying to this object.

Notes

This method returns a new object that’s a view on the same data as the input. Mutating the input or the output values will be reflected in the other.

This method is intended to be used in method chains.

“Flags” differ from “metadata”. Flags reflect properties of the pandas object (the Series or DataFrame). Metadata refer to properties of the dataset, and should be stored in DataFrame.attrs.

Examples

>>> df = pd.DataFrame({"A": [1, 2]})
>>> df.flags.allows_duplicate_labels
True
>>> df2 = df.set_flags(allows_duplicate_labels=False)
>>> df2.flags.allows_duplicate_labels
False