Re: [Gretl-users] Manipulating a database

On Sat, 3 Apr 2010, Leandro Zipitria wrote: I'm going back to your original design (sheet 2 of your attached xls file), where you indicated (if I understood correctly) that you'd like to treat the supermarket as the cross-sectional "unit", and each product-price as a distinct variable. Your panel would then comprise T daily observations for each of n supermarkets (T*n rows) with m columns holding prices for m goods. (Of course there may be many missing values if not all supermarkets stock all commodities.) Given the structure of the original data this is not particularly easy to achieve, but it can be done in gretl. Since the task is complex, I suggest breaking it into two parts: 1) Create a daily time-series for each supermarket (all of the same length, T), then 2) Stick these time series blocks together to form a panel. I'm attaching an illustrative gretl script that deals with the first of these tasks. I'm assuming that a) You can sort your spreadsheet data by year and month, and read off the "global" starting and ending months (in your sample file these are 2007/3 and 2009/9). a) You then sort the spreadsheet data by supermarket, year and month (in that order), import the data into gretl, and save the data as a gretl matrix named pdata.mat: open supermarkets.xls # or whatever it's called matrix m = {dataset} mwrite (m, "pdata.mat") With that done, you are just about ready to run the attached script (which may of course need editing to work with your full data file; it works with your sample file). Look for the comment # choose your supermarket here and define supermkt_index to the index number of the supermarket for which you want a time series on the current run. One more thing: I'm using a newly added function, monthlen, which is in gretl CVS and the snapshots for Windows and OS X, but not in the 1.8.7 release. Allin Cottrell