colorado utah new york two three so there are many ways to select and rearrange the data contained in pandas object for dataframethere is short summary of many of them in table - you have number of additional options when working with hierarchical indexes as you'll later see when designing pandasi felt that having to type frame[:colto select column was too verbose (and error-prone)since column selection is one of the most common operations thus made the design trade-off to push all of the rich label-indexing into ix table - indexing options with dataframe type notes obj[valselect single column or sequence of columns from the dataframe special case conveniencesboolean array (filter rows)slice (slice rows)or boolean dataframe (set values based on some criterionobj ix[valselects single row of subset of rows from the dataframe obj ix[:valselects single column of subset of columns obj ix[val val select both rows and columns reindex method conform one or more axes to new indexes xs method select single row or column as series by label icolirow methods select single column or rowrespectivelyas series by integer location get_valueset_value methods select single value by row and column label arithmetic and data alignment one of the most important pandas features is the behavior of arithmetic between objects with different indexes when adding together objectsif any index pairs are not the samethe respective index in the result will be the union of the index pairs let' look at simple examplein [ ] series([ - ]index=[' '' '' '' ']in [ ] series([- - ]index=[' '' '' '' '' ']in [ ] out[ ] - in [ ] out[ ] - - getting started with pandas www it-ebooks info