economic time series are often of annualquarterlymonthlydailyor some other more specialized frequency some are completely irregularfor exampleearnings revisions for stock may arrive at any time the two main tools for frequency conversion and realignment are the resample and reindex methods resample converts data to fixed frequency while reindex conforms data to new index both support optional interpolation (such as forward fillinglogic let' consider small weekly time seriesin [ ]ts series(np random randn( )index=pd date_range(''periods= freq=' -wed')in [ ]ts out[ ]- - freqw-wed if you resample this to business daily (monday-fridayfrequencyyou get holes on the days where there is no datain [ ]ts resample(' 'out[ ]- nan nan nan nan nan nan nan nan - freqb of courseusing 'ffillas the fill_method forward fills values in those gaps this is common practice with lower frequency data as you compute time series of values on each timestamp having the latest valid or "as ofvaluein [ ]ts resample(' 'fill_method='ffill'out[ ]- - - - - financial and economic data applications www it-ebooks info