ohio nan texas nan california nan the columns can be reindexed using the columns keywordin [ ]states ['texas''utah''california'in [ ]frame reindex(columns=statesout[ ]texas utah california nan nan nan both can be reindexed in one shotthough interpolation will only apply row-wise (axis )in [ ]frame reindex(index=[' '' '' '' ']method='ffill'columns=statesout[ ]texas utah california nan nan nan nan as you'll see soonreindexing can be done more succinctly by label-indexing with ixin [ ]frame ix[[' '' '' '' ']statesout[ ]texas utah california nan nan nan nan nan nan table - reindex function arguments argument description index new sequence to use as index can be index instance or any other sequence-like python data structure an index will be used exactly as is without any copying method interpolation (fillmethodsee table - for options fill_value substitute value to use when introducing missing data by reindexing limit when forwardor backfillingmaximum size gap to fill level match simple index on level of multiindexotherwise select subset of copy do not copy underlying data if new index is equivalent to old index true by default ( always copy data getting started with pandas www it-ebooks info