in [ ]second out[ ]array([ ]]in [ ]third out[ ]array([[- ] ]] ] ]]see table - for list of all relevant concatenation and splitting functionssome of which are provided only as convenience of the very general purpose concatenate table - array concatenation functions function description concatenate most general functionconcatenates collection of arrays along one axis vstackrow_stack stack arrays row-wise (along axis hstack stack arrays column-wise (along axis column_stack like hstackbut converts arrays to column vectors first dstack stack arrays "depth"-wise (along axis split split array at passed locations along particular axis hsplit vsplit dsplit convenience functions for splitting on axis and respectively stacking helpersr_ and c_ there are two special objects in the numpy namespacer_ and c_that make stacking arrays more concisein [ ]arr np arange( in [ ]arr arr reshape(( )in [ ]arr randn( in [ ]np r_[arr arr out[ ]array([ ] ] ] - ][- - ][- ]]in [ ]np c_[np r_[arr arr ]arrout[ ]array([ ] ] ] - ][- - ][- ]]these additionally can translate slices to arraysin [ ]np c_[ : - :- out[ ]array([ - ] - ] - ] - ] - ]]see the docstring for more on what you can do with c_ and r_ advanced array manipulation www it-ebooks info