names while you can address the overlap manually (see the later section on renaming axis labels)merge has suffixes option for specifying strings to append to overlapping names in the left and right dataframe objectsin [ ]pd merge(leftrighton='key 'out[ ]key key _x lval key _y rval bar one one bar one two foo one one foo one one foo two one foo two one in [ ]pd merge(leftrighton='key 'suffixes=('_left''_right')out[ ]key key _left lval key _right rval bar one one bar one two foo one one foo one one foo two one foo two one see table - for an argument reference on merge joining on index is the subject of the next section table - merge function arguments argument description left dataframe to be merged on the left side right dataframe to be merged on the right side how one of 'inner''outer''leftor 'right'innerby default on column names to join on must be found in both dataframe objects if not specified and no other join keys givenwill use the intersection of the column names in left and right as the join keys left_on columns in left dataframe to use as join keys right_on analogous to left_on for left dataframe left_index use row index in left as its join key (or keysif multiindexright_index analogous to left_index sort sort merged data lexicographically by join keystrue by default disable to get better performance in some cases on large datasets suffixes tuple of string values to append to column names in case of overlapdefaults to ('_x''_y'for exampleif 'datain both dataframe objectswould appear as 'data_xand 'data_yin result copy if falseavoid copying data into resulting data structure in some exceptional cases by default always copies combining and merging data sets www it-ebooks info