pandas.api.extensions.ExtensionArray.take#
- ExtensionArray.take(indices, *, allow_fill=False, fill_value=None)[source]#
Take elements from an array.
- Parameters
- indicessequence of int or one-dimensional np.ndarray of int
Indices to be taken.
- allow_fillbool, default False
How to handle negative values in indices.
False: negative values in indices indicate positional indices from the right (the default). This is similar to
numpy.take()
.True: negative values in indices indicate missing values. These values are set to fill_value. Any other other negative values raise a
ValueError
.
- fill_valueany, optional
Fill value to use for NA-indices when allow_fill is True. This may be
None
, in which case the default NA value for the type,self.dtype.na_value
, is used.For many ExtensionArrays, there will be two representations of fill_value: a user-facing “boxed” scalar, and a low-level physical NA value. fill_value should be the user-facing version, and the implementation should handle translating that to the physical version for processing the take if necessary.
- Returns
- ExtensionArray
- Raises
- IndexError
When the indices are out of bounds for the array.
- ValueError
When indices contains negative values other than
-1
and allow_fill is True.
See also
numpy.take
Take elements from an array along an axis.
api.extensions.take
Take elements from an array.
Notes
ExtensionArray.take is called by
Series.__getitem__
,.loc
,iloc
, when indices is a sequence of values. Additionally, it’s called bySeries.reindex()
, or any other method that causes realignment, with a fill_value.Examples
Here’s an example implementation, which relies on casting the extension array to object dtype. This uses the helper method
pandas.api.extensions.take()
.def take(self, indices, allow_fill=False, fill_value=None): from pandas.core.algorithms import take # If the ExtensionArray is backed by an ndarray, then # just pass that here instead of coercing to object. data = self.astype(object) if allow_fill and fill_value is None: fill_value = self.dtype.na_value # fill value should always be translated from the scalar # type for the array, to the physical storage type for # the data, before passing to take. result = take(data, indices, fill_value=fill_value, allow_fill=allow_fill) return self._from_sequence(result, dtype=self.dtype)