def get_result(self):
# series only
if self._is_series:
# stack blocks
if self.bm_axis == 0:
name = com.consensus_name_attr(self.objs)
cons = self.objs[0]._constructor
arrs = [ser._values for ser in self.objs]
res = concat_compat(arrs, axis=0)
result = cons(res,
index=self.new_axes[0],
name=name,
dtype=res.dtype)
return result.__finalize__(self, method="concat")
# combine as columns in a frame
else:
data = dict(zip(range(len(self.objs)), self.objs))
# GH28330 Preserves subclassed objects through concat
cons = self.objs[0]._constructor_expanddim
index, columns = self.new_axes
df = cons(data, index=index)
df.columns = columns
return df.__finalize__(self, method="concat")
# combine block managers
else:
mgrs_indexers = []
for obj in self.objs:
indexers = {}
for ax, new_labels in enumerate(self.new_axes):
# ::-1 to convert BlockManager ax to DataFrame ax
if ax == self.bm_axis:
# Suppress reindexing on concat axis
continue
# 1-ax to convert BlockManager axis to DataFrame axis
obj_labels = obj.axes[1 - ax]
if not new_labels.equals(obj_labels):
indexers[ax] = obj_labels.reindex(new_labels)[1]
mgrs_indexers.append((obj._mgr, indexers))
new_data = concatenate_block_managers(
mgrs_indexers,
self.new_axes,
concat_axis=self.bm_axis,
copy=self.copy,
)
if not self.copy:
new_data._consolidate_inplace()
cons = self.objs[0]._constructor
return cons(new_data).__finalize__(self, method="concat")
def get_result(self):
# series only
if self._is_series:
# stack blocks
if self.axis == 0:
name = com.consensus_name_attr(self.objs)
mgr = self.objs[0]._data.concat([x._data for x in self.objs],
self.new_axes)
cons = _concat._get_series_result_type(mgr, self.objs)
return cons(mgr, name=name).__finalize__(self, method="concat")
# combine as columns in a frame
else:
data = dict(zip(range(len(self.objs)), self.objs))
cons = _concat._get_series_result_type(data)
index, columns = self.new_axes
df = cons(data, index=index)
df.columns = columns
return df.__finalize__(self, method="concat")
# combine block managers
else:
mgrs_indexers = []
for obj in self.objs:
mgr = obj._data
indexers = {}
for ax, new_labels in enumerate(self.new_axes):
if ax == self.axis:
# Suppress reindexing on concat axis
continue
obj_labels = mgr.axes[ax]
if not new_labels.equals(obj_labels):
indexers[ax] = obj_labels.reindex(new_labels)[1]
mgrs_indexers.append((obj._data, indexers))
new_data = concatenate_block_managers(mgrs_indexers,
self.new_axes,
concat_axis=self.axis,
copy=self.copy)
if not self.copy:
new_data._consolidate_inplace()
cons = _concat._get_frame_result_type(new_data, self.objs)
return cons._from_axes(new_data,
self.new_axes).__finalize__(self,
method="concat")
def get_result(self):
# series only
if self._is_series:
# stack blocks
if self.bm_axis == 0:
name = com.consensus_name_attr(self.objs)
mgr = self.objs[0]._mgr.concat([x._mgr for x in self.objs],
self.new_axes[0])
cons = self.objs[0]._constructor
return cons(mgr, name=name).__finalize__(self, method="concat")
# combine as columns in a frame
else:
data = dict(zip(range(len(self.objs)), self.objs))
cons = DataFrame
index, columns = self.new_axes
df = cons(data, index=index)
df.columns = columns
return df.__finalize__(self, method="concat")
# combine block managers
else:
mgrs_indexers = []
for obj in self.objs:
indexers = {}
for ax, new_labels in enumerate(self.new_axes):
# ::-1 to convert BlockManager ax to DataFrame ax
if ax == self.bm_axis:
# Suppress reindexing on concat axis
continue
# 1-ax to convert BlockManager axis to DataFrame axis
obj_labels = obj.axes[1 - ax]
if not new_labels.equals(obj_labels):
indexers[ax] = obj_labels.reindex(new_labels)[1]
mgrs_indexers.append((obj._mgr, indexers))
new_data = concatenate_block_managers(mgrs_indexers,
self.new_axes,
concat_axis=self.bm_axis,
copy=self.copy)
if not self.copy:
new_data._consolidate_inplace()
cons = self.objs[0]._constructor
return cons(new_data).__finalize__(self, method="concat")
def get_result(self):
# series only
if self._is_series:
# stack blocks
if self.axis == 0:
name = com.consensus_name_attr(self.objs)
mgr = self.objs[0]._data.concat([x._data for x in self.objs],
self.new_axes)
cons = _concat._get_series_result_type(mgr, self.objs)
return cons(mgr, name=name).__finalize__(self, method='concat')
# combine as columns in a frame
else:
data = dict(zip(range(len(self.objs)), self.objs))
cons = _concat._get_series_result_type(data)
index, columns = self.new_axes
df = cons(data, index=index)
df.columns = columns
return df.__finalize__(self, method='concat')
# combine block managers
else:
mgrs_indexers = []
for obj in self.objs:
mgr = obj._data
indexers = {}
for ax, new_labels in enumerate(self.new_axes):
if ax == self.axis:
# Suppress reindexing on concat axis
continue
obj_labels = mgr.axes[ax]
if not new_labels.equals(obj_labels):
indexers[ax] = obj_labels.reindex(new_labels)[1]
mgrs_indexers.append((obj._data, indexers))
new_data = concatenate_block_managers(
mgrs_indexers, self.new_axes, concat_axis=self.axis,
copy=self.copy)
if not self.copy:
new_data._consolidate_inplace()
cons = _concat._get_frame_result_type(new_data, self.objs)
return (cons._from_axes(new_data, self.new_axes)
.__finalize__(self, method='concat'))
def get_result(self):
cons: Type[FrameOrSeriesUnion]
sample: FrameOrSeriesUnion
# series only
if self._is_series:
sample = cast("Series", self.objs[0])
# stack blocks
if self.bm_axis == 0:
name = com.consensus_name_attr(self.objs)
cons = sample._constructor
arrs = [ser._values for ser in self.objs]
res = concat_compat(arrs, axis=0)
result = cons(res,
index=self.new_axes[0],
name=name,
dtype=res.dtype)
return result.__finalize__(self, method="concat")
# combine as columns in a frame
else:
data = dict(zip(range(len(self.objs)), self.objs))
# GH28330 Preserves subclassed objects through concat
cons = sample._constructor_expanddim
index, columns = self.new_axes
df = cons(data, index=index)
df.columns = columns
return df.__finalize__(self, method="concat")
# combine block managers
else:
sample = cast("DataFrame", self.objs[0])
mgrs_indexers = []
for obj in self.objs:
indexers = {}
for ax, new_labels in enumerate(self.new_axes):
# ::-1 to convert BlockManager ax to DataFrame ax
if ax == self.bm_axis:
# Suppress reindexing on concat axis
continue
# 1-ax to convert BlockManager axis to DataFrame axis
obj_labels = obj.axes[1 - ax]
if not new_labels.equals(obj_labels):
# We have to remove the duplicates from obj_labels
# in new labels to make them unique, otherwise we would
# duplicate or duplicates again
if not obj_labels.is_unique:
new_labels = algos.make_duplicates_of_left_unique_in_right(
np.asarray(obj_labels), np.asarray(new_labels))
indexers[ax] = obj_labels.reindex(new_labels)[1]
mgrs_indexers.append((obj._mgr, indexers))
new_data = concatenate_block_managers(mgrs_indexers,
self.new_axes,
concat_axis=self.bm_axis,
copy=self.copy)
if not self.copy:
new_data._consolidate_inplace()
cons = sample._constructor
return cons(new_data).__finalize__(self, method="concat")
