def take(self, indices, axis=0, allow_fill=True,
fill_value=None, **kwargs):
nv.validate_take(tuple(), kwargs)
indices = _ensure_platform_int(indices)
left, right = self.left, self.right
if fill_value is None:
fill_value = self._na_value
mask = indices == -1
if not mask.any():
# we won't change dtype here in this case
# if we don't need
allow_fill = False
taker = lambda x: x.take(indices, allow_fill=allow_fill,
fill_value=fill_value)
try:
new_left = taker(left)
new_right = taker(right)
except ValueError:
# we need to coerce; migth have NA's in an
# integer dtype
new_left = taker(left.astype(float))
new_right = taker(right.astype(float))
return self._shallow_copy(new_left, new_right)
def take(self, indices, axis=0, allow_fill=True,
fill_value=None, **kwargs):
nv.validate_take(tuple(), kwargs)
indices = _ensure_platform_int(indices)
taken = self._assert_take_fillable(self.codes, indices,
allow_fill=allow_fill,
fill_value=fill_value,
na_value=-1)
return self._create_from_codes(taken)
def take(self, indices, axis=0, allow_fill=True,
fill_value=None, **kwargs):
"""
Sparse-compatible version of ndarray.take
Returns
-------
taken : ndarray
"""
nv.validate_take(tuple(), kwargs)
if axis:
raise ValueError("axis must be 0, input was {axis}"
.format(axis=axis))
if is_integer(indices):
# return scalar
return self[indices]
indices = _ensure_platform_int(indices)
n = len(self)
if allow_fill and fill_value is not None:
# allow -1 to indicate self.fill_value,
# self.fill_value may not be NaN
if (indices < -1).any():
msg = ('When allow_fill=True and fill_value is not None, '
'all indices must be >= -1')
raise ValueError(msg)
elif (n <= indices).any():
msg = 'index is out of bounds for size {size}'.format(size=n)
raise IndexError(msg)
else:
if ((indices < -n) | (n <= indices)).any():
msg = 'index is out of bounds for size {size}'.format(size=n)
raise IndexError(msg)
indices = indices.astype(np.int32)
if not (allow_fill and fill_value is not None):
indices = indices.copy()
indices[indices < 0] += n
locs = self.sp_index.lookup_array(indices)
indexer = np.arange(len(locs), dtype=np.int32)
mask = locs != -1
if mask.any():
indexer = indexer[mask]
new_values = self.sp_values.take(locs[mask])
else:
indexer = np.empty(shape=(0, ), dtype=np.int32)
new_values = np.empty(shape=(0, ), dtype=self.sp_values.dtype)
sp_index = _make_index(len(indices), indexer, kind=self.sp_index)
return self._simple_new(new_values, sp_index, self.fill_value)
def take(self, indices, axis=0, allow_fill=True, fill_value=None, **kwargs):
nv.validate_take(tuple(), kwargs)
indices = _ensure_int64(indices)
maybe_slice = lib.maybe_indices_to_slice(indices, len(self))
if isinstance(maybe_slice, slice):
return self[maybe_slice]
taken = self._assert_take_fillable(
self.asi8, indices, allow_fill=allow_fill, fill_value=fill_value, na_value=tslib.iNaT
)
# keep freq in PeriodIndex, reset otherwise
freq = self.freq if isinstance(self, ABCPeriodIndex) else None
return self._shallow_copy(taken, freq=freq)
def take(self,
indices,
axis=0,
allow_fill=True,
fill_value=None,
**kwargs):
nv.validate_take(tuple(), kwargs)
indices = ensure_int64(indices)
maybe_slice = lib.maybe_indices_to_slice(indices, len(self))
if isinstance(maybe_slice, slice):
return self[maybe_slice]
taken = self._assert_take_fillable(
self.asi8,
indices,
allow_fill=allow_fill,
fill_value=fill_value,
na_value=iNaT,
)
# keep freq in PeriodArray/Index, reset otherwise
freq = self.freq if is_period_dtype(self) else None
return self._shallow_copy(taken, freq=freq)
def take(self,
indices,
allow_fill=False,
fill_value=None,
axis=None,
**kwargs):
"""
Take elements from the IntervalArray.
Parameters
----------
indices : sequence of integers
Indices to be taken.
allow_fill : bool, 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
:func:`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_value : Interval or NA, 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.
axis : any, default None
Present for compat with IntervalIndex; does nothing.
Returns
-------
IntervalArray
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.
"""
nv.validate_take(tuple(), kwargs)
fill_left = fill_right = fill_value
if allow_fill:
if fill_value is None:
fill_left = fill_right = self.left._na_value
elif is_interval(fill_value):
self._check_closed_matches(fill_value, name="fill_value")
fill_left, fill_right = fill_value.left, fill_value.right
elif not is_scalar(fill_value) and notna(fill_value):
msg = ("'IntervalArray.fillna' only supports filling with a "
"'scalar pandas.Interval or NA'. "
f"Got a '{type(fill_value).__name__}' instead.")
raise ValueError(msg)
left_take = take(self.left,
indices,
allow_fill=allow_fill,
fill_value=fill_left)
right_take = take(self.right,
indices,
allow_fill=allow_fill,
fill_value=fill_right)
return self._shallow_copy(left_take, right_take)
def take(self, indices, allow_fill=False, fill_value=None, axis=None,
**kwargs):
"""
Take elements from the IntervalArray.
Parameters
----------
indices : sequence of integers
Indices to be taken.
allow_fill : bool, 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
:func:`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_value : Interval or NA, 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.
axis : any, default None
Present for compat with IntervalIndex; does nothing.
Returns
-------
IntervalArray
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.
"""
from pandas.core.algorithms import take
nv.validate_take(tuple(), kwargs)
fill_left = fill_right = fill_value
if allow_fill:
if fill_value is None:
fill_left = fill_right = self.left._na_value
elif is_interval(fill_value):
self._check_closed_matches(fill_value, name='fill_value')
fill_left, fill_right = fill_value.left, fill_value.right
elif not is_scalar(fill_value) and notna(fill_value):
msg = ("'IntervalArray.fillna' only supports filling with a "
"'scalar pandas.Interval or NA'. Got a '{}' instead."
.format(type(fill_value).__name__))
raise ValueError(msg)
left_take = take(self.left, indices,
allow_fill=allow_fill, fill_value=fill_left)
right_take = take(self.right, indices,
allow_fill=allow_fill, fill_value=fill_right)
return self._shallow_copy(left_take, right_take)
def take(self,
indices,
*,
allow_fill=False,
fill_value=None,
axis=None,
**kwargs):
"""
Take elements from the IntervalArray.
Parameters
----------
indices : sequence of integers
Indices to be taken.
allow_fill : bool, 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
:func:`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_value : Interval or NA, 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.
axis : any, default None
Present for compat with IntervalIndex; does nothing.
Returns
-------
IntervalArray
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.
"""
nv.validate_take(tuple(), kwargs)
fill_left = fill_right = fill_value
if allow_fill:
fill_left, fill_right = self._validate_fill_value(fill_value)
left_take = take(self._left,
indices,
allow_fill=allow_fill,
fill_value=fill_left)
right_take = take(self._right,
indices,
allow_fill=allow_fill,
fill_value=fill_right)
combined = _get_combined_data(left_take, right_take)
return type(self)._simple_new(combined, closed=self.closed)