def get_result(self):
if self._is_series:
if self.axis == 0:
new_data = com._concat_compat([x.get_values() for x in self.objs])
name = com._consensus_name_attr(self.objs)
return Series(new_data, index=self.new_axes[0], name=name).__finalize__(self, method='concat')
else:
data = dict(zip(range(len(self.objs)), self.objs))
index, columns = self.new_axes
tmpdf = DataFrame(data, index=index)
if columns is not None:
tmpdf.columns = columns
return tmpdf.__finalize__(self, method='concat')
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=True)
return self.objs[0]._from_axes(new_data, self.new_axes).__finalize__(self, method='concat')
def get_result(self):
if self._is_series:
if self.axis == 0:
new_data = com._concat_compat([x.get_values() for x in self.objs])
name = com._consensus_name_attr(self.objs)
return Series(new_data, index=self.new_axes[0], name=name).__finalize__(self, method='concat')
else:
data = dict(zip(range(len(self.objs)), self.objs))
index, columns = self.new_axes
tmpdf = DataFrame(data, index=index)
if columns is not None:
tmpdf.columns = columns
return tmpdf.__finalize__(self, method='concat')
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()
return self.objs[0]._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.axis == 0:
new_data = com._concat_compat([x._values for x in self.objs])
name = com._consensus_name_attr(self.objs)
return (Series(new_data, index=self.new_axes[0],
name=name,
dtype=new_data.dtype)
.__finalize__(self, method='concat'))
# combine as columns in a frame
else:
data = dict(zip(range(len(self.objs)), self.objs))
index, columns = self.new_axes
tmpdf = DataFrame(data, index=index)
# checks if the column variable already stores valid column
# names (because set via the 'key' argument in the 'concat'
# function call. If that's not the case, use the series names
# as column names
if (columns.equals(Index(np.arange(len(self.objs)))) and
not self.ignore_index):
columns = np.array([data[i].name
for i in range(len(data))],
dtype='object')
indexer = isnull(columns)
if indexer.any():
columns[indexer] = np.arange(len(indexer[indexer]))
tmpdf.columns = columns
return tmpdf.__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()
return (self.objs[0]._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.axis == 0:
# concat Series with length to keep dtype as much
non_empties = [x for x in self.objs if len(x) > 0]
if len(non_empties) > 0:
values = [x._values for x in non_empties]
else:
values = [x._values for x in self.objs]
new_data = _concat._concat_compat(values)
name = com._consensus_name_attr(self.objs)
cons = _concat._get_series_result_type(new_data)
return (cons(new_data, index=self.new_axes[0],
name=name, dtype=new_data.dtype)
.__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.axis == 0:
# concat Series with length to keep dtype as much
non_empties = [x for x in self.objs if len(x) > 0]
if len(non_empties) > 0:
values = [x._values for x in non_empties]
else:
values = [x._values for x in self.objs]
new_data = _concat._concat_compat(values)
name = com._consensus_name_attr(self.objs)
cons = _concat._get_series_result_type(new_data)
return (cons(new_data, index=self.new_axes[0],
name=name, dtype=new_data.dtype)
.__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):
if self._is_series and self.axis == 0:
new_data = np.concatenate([x.values for x in self.objs])
name = com._consensus_name_attr(self.objs)
return Series(new_data, index=self.new_axes[0], name=name)
elif self._is_series:
data = dict(zip(self.new_axes[1], self.objs))
return DataFrame(data, index=self.new_axes[0], columns=self.new_axes[1])
else:
new_data = self._get_concatenated_data()
return self.objs[0]._from_axes(new_data, self.new_axes)
def get_result(self):
if self._is_series and self.axis == 0:
new_data = com._concat_compat([x.values for x in self.objs])
name = com._consensus_name_attr(self.objs)
return Series(new_data, index=self.new_axes[0], name=name)
elif self._is_series:
data = dict(zip(self.new_axes[1], self.objs))
return DataFrame(data, index=self.new_axes[0],
columns=self.new_axes[1])
else:
new_data = self._get_concatenated_data()
return self.objs[0]._from_axes(new_data, self.new_axes)
def get_result(self):
if self._is_series and self.axis == 0:
new_data = com._concat_compat([x.values for x in self.objs])
name = com._consensus_name_attr(self.objs)
return Series(new_data, index=self.new_axes[0], name=name)
elif self._is_series:
data = dict(itertools.izip(xrange(len(self.objs)), self.objs))
tmpdf = DataFrame(data, index=self.new_axes[0])
tmpdf.columns = self.new_axes[1]
return tmpdf
else:
new_data = self._get_concatenated_data()
return self.objs[0]._from_axes(new_data, self.new_axes)
def get_result(self):
if self._is_series and self.axis == 0:
new_data = com._concat_compat([x.values for x in self.objs])
name = com._consensus_name_attr(self.objs)
return Series(new_data, index=self.new_axes[0], name=name)
elif self._is_series:
data = dict(itertools.izip(xrange(len(self.objs)), self.objs))
tmpdf = DataFrame(data, index=self.new_axes[0])
tmpdf.columns = self.new_axes[1]
return tmpdf
else:
new_data = self._get_concatenated_data()
return self.objs[0]._from_axes(new_data, self.new_axes)
def get_result(self):
if self._is_series and self.axis == 0:
new_data = com._concat_compat([x.get_values() for x in self.objs])
name = com._consensus_name_attr(self.objs)
new_data = self._post_merge(new_data)
return Series(new_data, index=self.new_axes[0], name=name)
elif self._is_series:
data = dict(zip(range(len(self.objs)), self.objs))
index, columns = self.new_axes
tmpdf = DataFrame(data, index=index)
if columns is not None:
tmpdf.columns = columns
return tmpdf
else:
new_data = self._get_concatenated_data()
new_data = self._post_merge(new_data)
return self.objs[0]._from_axes(new_data, self.new_axes)
def get_result(self):
if self._is_series and self.axis == 0:
new_data = com._concat_compat([x.get_values() for x in self.objs])
name = com._consensus_name_attr(self.objs)
new_data = self._post_merge(new_data)
return Series(new_data, index=self.new_axes[0], name=name)
elif self._is_series:
data = dict(zip(range(len(self.objs)), self.objs))
index, columns = self.new_axes
tmpdf = DataFrame(data, index=index)
if columns is not None:
tmpdf.columns = columns
return tmpdf
else:
new_data = self._get_concatenated_data()
new_data = self._post_merge(new_data)
return self.objs[0]._from_axes(new_data, self.new_axes)
