Hi list, I have a data frame with a "Date" column and a "Price" column - for example: Date Price 01/01/2009 5.45 01/03/2009 6.53 01/04/2009 7.55 01/06/2009 6.76 01/08/2009 4.12 01/18/2009 5.87 ... As you can see, there are days for which I don't have any data. I would like to insert rows for missing dates that have values of NA for "Price" - for example: Date Price 01/01/2009 5.45 01/02/2009 NA 01/03/2009 6.53 01/04/2009 7.55 01/05/2009 NA 01/06/2009 6.76 ... With the goal of ultimately converting "Price" to a time series and dealing with the NAs via the zoo package or something similar. The first step, however is to add a row for every date. I have considered converting "Date" to a time series then using seq() to create a vector with the appropriate number of rows starting at the appropriate number of days since epoch, and then using match() to combine columns and add the desired rows. I'm new to time series in R, but it seems like there should be an easier way. I've gotten as far as Google and rseek can take me so any help would be appreciated. Bryan [[alternative HTML version deleted]]