@@ -854,7 +854,7 @@ def _wrap_applied_output(self, *args, **kwargs):
854854 raise AbstractMethodError (self )
855855
856856 def _concat_objects (self , keys , values , not_indexed_same = False ):
857- from pandas .tools .merge import concat
857+ from pandas .tools .concat import concat
858858
859859 def reset_identity (values ):
860860 # reset the identities of the components
@@ -3507,7 +3507,7 @@ def first_non_None_value(values):
35073507 # still a series
35083508 # path added as of GH 5545
35093509 elif all_indexed_same :
3510- from pandas .tools .merge import concat
3510+ from pandas .tools .concat import concat
35113511 return concat (values )
35123512
35133513 if not all_indexed_same :
@@ -3540,7 +3540,7 @@ def first_non_None_value(values):
35403540 else :
35413541 # GH5788 instead of stacking; concat gets the
35423542 # dtypes correct
3543- from pandas .tools .merge import concat
3543+ from pandas .tools .concat import concat
35443544 result = concat (values , keys = key_index ,
35453545 names = key_index .names ,
35463546 axis = self .axis ).unstack ()
@@ -3588,7 +3588,7 @@ def first_non_None_value(values):
35883588 not_indexed_same = not_indexed_same )
35893589
35903590 def _transform_general (self , func , * args , ** kwargs ):
3591- from pandas .tools .merge import concat
3591+ from pandas .tools .concat import concat
35923592
35933593 applied = []
35943594 obj = self ._obj_with_exclusions
@@ -3980,7 +3980,7 @@ def _iterate_column_groupbys(self):
39803980 exclusions = self .exclusions )
39813981
39823982 def _apply_to_column_groupbys (self , func ):
3983- from pandas .tools .merge import concat
3983+ from pandas .tools .concat import concat
39843984 return concat (
39853985 (func (col_groupby ) for _ , col_groupby
39863986 in self ._iterate_column_groupbys ()),
@@ -4061,7 +4061,7 @@ def groupby_series(obj, col=None):
40614061 if isinstance (obj , Series ):
40624062 results = groupby_series (obj )
40634063 else :
4064- from pandas .tools .merge import concat
4064+ from pandas .tools .concat import concat
40654065 results = [groupby_series (obj [col ], col ) for col in obj .columns ]
40664066 results = concat (results , axis = 1 )
40674067
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