def test_mut_exclusive():
msg = "mutually exclusive arguments: '[ab]' and '[ab]'"
with tm.assert_raises_regex(TypeError, msg):
com._mut_exclusive(a=1, b=2)
assert com._mut_exclusive(a=1, b=None) == 1
assert com._mut_exclusive(major=None, major_axis=None) is None
assert com._mut_exclusive(a=None, b=2) == 2
def test_mut_exclusive():
msg = "mutually exclusive arguments: '[ab]' and '[ab]'"
with tm.assert_raises_regex(TypeError, msg):
com._mut_exclusive(a=1, b=2)
assert com._mut_exclusive(a=1, b=None) == 1
assert com._mut_exclusive(major=None, major_axis=None) is None
assert com._mut_exclusive(a=None, b=2) == 2
def reindex(self,
major=None,
items=None,
minor=None,
major_axis=None,
minor_axis=None,
copy=False):
"""
Conform / reshape panel axis labels to new input labels
Parameters
----------
major : array-like, default None
items : array-like, default None
minor : array-like, default None
copy : boolean, default False
Copy underlying SparseDataFrame objects
Returns
-------
reindexed : SparsePanel
"""
major = com._mut_exclusive(major=major, major_axis=major_axis)
minor = com._mut_exclusive(minor=minor, minor_axis=minor_axis)
if com._all_none(items, major, minor):
raise ValueError('Must specify at least one axis')
major = self.major_axis if major is None else major
minor = self.minor_axis if minor is None else minor
if items is not None:
new_frames = {}
for item in items:
if item in self._frames:
new_frames[item] = self._frames[item]
else:
raise NotImplementedError(
'Reindexing with new items not yet '
'supported')
else:
new_frames = self._frames
if copy:
new_frames = dict(
(k, v.copy()) for k, v in compat.iteritems(new_frames))
return SparsePanel(new_frames,
items=items,
major_axis=major,
minor_axis=minor,
default_fill_value=self.default_fill_value,
default_kind=self.default_kind)
def reindex(self,
major=None,
items=None,
minor=None,
method=None,
major_axis=None,
minor_axis=None,
copy=True):
"""
Conform panel to new axis or axes
Parameters
----------
major : Index or sequence, default None
Can also use 'major_axis' keyword
items : Index or sequence, default None
minor : Index or sequence, default None
Can also use 'minor_axis' keyword
method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use NEXT valid observation to fill gap
copy : boolean, default True
Return a new object, even if the passed indexes are the same
Returns
-------
Panel (new object)
"""
result = self
major = _mut_exclusive(major, major_axis)
minor = _mut_exclusive(minor, minor_axis)
if (method is None and not self._is_mixed_type
and com._count_not_none(items, major, minor) == 3):
return self._reindex_multi(items, major, minor)
if major is not None:
result = result._reindex_axis(major, method, 1, copy)
if minor is not None:
result = result._reindex_axis(minor, method, 2, copy)
if items is not None:
result = result._reindex_axis(items, method, 0, copy)
if result is self and copy:
raise ValueError('Must specify at least one axis')
return result
def reindex(self, major=None, items=None, minor=None, method=None,
major_axis=None, minor_axis=None, copy=True):
"""
Conform panel to new axis or axes
Parameters
----------
major : Index or sequence, default None
Can also use 'major_axis' keyword
items : Index or sequence, default None
minor : Index or sequence, default None
Can also use 'minor_axis' keyword
method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use NEXT valid observation to fill gap
copy : boolean, default True
Return a new object, even if the passed indexes are the same
Returns
-------
Panel (new object)
"""
result = self
major = _mut_exclusive(major, major_axis)
minor = _mut_exclusive(minor, minor_axis)
if (method is None and not self._is_mixed_type and
com._count_not_none(items, major, minor) == 3):
return self._reindex_multi(items, major, minor)
if major is not None:
result = result._reindex_axis(major, method, 1, copy)
if minor is not None:
result = result._reindex_axis(minor, method, 2, copy)
if items is not None:
result = result._reindex_axis(items, method, 0, copy)
if result is self and copy:
raise ValueError('Must specify at least one axis')
return result
def reindex(self, major=None, items=None, minor=None, major_axis=None,
minor_axis=None, copy=False):
"""
Conform / reshape panel axis labels to new input labels
Parameters
----------
major : array-like, default None
items : array-like, default None
minor : array-like, default None
copy : boolean, default False
Copy underlying SparseDataFrame objects
Returns
-------
reindexed : SparsePanel
"""
major = com._mut_exclusive(major, major_axis)
minor = com._mut_exclusive(minor, minor_axis)
if com._all_none(items, major, minor):
raise ValueError('Must specify at least one axis')
major = self.major_axis if major is None else major
minor = self.minor_axis if minor is None else minor
if items is not None:
new_frames = {}
for item in items:
if item in self._frames:
new_frames[item] = self._frames[item]
else:
raise NotImplementedError('Reindexing with new items not yet '
'supported')
else:
new_frames = self._frames
if copy:
new_frames = dict((k, v.copy()) for k, v in compat.iteritems(new_frames))
return SparsePanel(new_frames, items=items,
major_axis=major,
minor_axis=minor,
default_fill_value=self.default_fill_value,
default_kind=self.default_kind)
def reindex(self, major=None, items=None, minor=None, method=None, major_axis=None, minor_axis=None):
"""
Conform panel to new axis or axes
Parameters
----------
major : Index or sequence, default None
Can also use 'major_axis' keyword
items : Index or sequence, default None
minor : Index or sequence, default None
Can also use 'minor_axis' keyword
method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use NEXT valid observation to fill gap
Returns
-------
WidePanel (new object)
"""
result = self
major = _mut_exclusive(major, major_axis)
minor = _mut_exclusive(minor, minor_axis)
if major is not None:
result = result._reindex_axis(major, method, 1)
if minor is not None:
result = result._reindex_axis(minor, method, 2)
if items is not None:
result = result._reindex_axis(items, method, 0)
if result is self:
raise ValueError("Must specify at least one axis")
return result
