This example shows how to use two Fame namelists to perform selection. Note that fame_namelist1 could be easily generated using the Fame WILDLIST
function. For more about WILDLIST
, see the section “The WILDLIST Function” in the Fame Command Reference Volume 2, Functions. In the following statements, four tickers are selected in fame_namelist1, but when you use the KEEP statement, the resulting data set contains only the desired IBM ticker.
libname lib8 sasefame "%sysget(FAME_DATA)" convert=(frequency=business technique=constant) crosslist=( { IBM,SPALN,SUNW,XOM }, { adjust, close, high, low, open, volume, uclose, uhigh, ulow,uopen,uvolume } ); data trout; /* eleven companies, keep only the IBM ticker this time */ set lib8.training; where date between '01mar02'd and '20mar02'd; keep IBM: ; run; title1 'TRAINING DB, Pricing Timeseries for IBM Ticker in CROSSLIST='; proc contents data=trout; run; proc print data=trout; run;
Output 41.8.1 and Output 41.8.2 show the results.
Output 41.8.1: Contents of the IBM Time Series in the Training Fame Data
TRAINING DB, Pricing Timeseries for IBM Ticker in CROSSLIST= |
Alphabetic List of Variables and Attributes | |||
---|---|---|---|
# | Variable | Type | Len |
1 | IBM.ADJUST | Num | 8 |
2 | IBM.CLOSE | Num | 8 |
3 | IBM.HIGH | Num | 8 |
4 | IBM.LOW | Num | 8 |
5 | IBM.OPEN | Num | 8 |
6 | IBM.UCLOSE | Num | 8 |
7 | IBM.UHIGH | Num | 8 |
8 | IBM.ULOW | Num | 8 |
9 | IBM.UOPEN | Num | 8 |
10 | IBM.UVOLUME | Num | 8 |
11 | IBM.VOLUME | Num | 8 |
Output 41.8.2: Listing of Ticker IBM Time Series in the Training Fame Data
TRAINING DB, Pricing Timeseries for IBM Ticker in CROSSLIST= |
Obs | IBM.ADJUST | IBM.CLOSE | IBM.HIGH | IBM.LOW | IBM.OPEN | IBM.UCLOSE | IBM.UHIGH | IBM.ULOW | IBM.UOPEN | IBM.UVOLUME | IBM.VOLUME |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 103.020 | 103.100 | 98.500 | 98.600 | 103.020 | 103.100 | 98.500 | 98.600 | 104890 | 104890 |
2 | 1 | 105.900 | 106.540 | 103.130 | 103.350 | 105.900 | 106.540 | 103.130 | 103.350 | 107650 | 107650 |
3 | 1 | 105.670 | 106.500 | 104.160 | 104.250 | 105.670 | 106.500 | 104.160 | 104.250 | 75617 | 75617 |
4 | 1 | 106.300 | 107.090 | 104.750 | 105.150 | 106.300 | 107.090 | 104.750 | 105.150 | 76874 | 76874 |
5 | 1 | 103.710 | 107.500 | 103.240 | 107.300 | 103.710 | 107.500 | 103.240 | 107.300 | 109720 | 109720 |
6 | 1 | 105.090 | 107.340 | 104.820 | 104.820 | 105.090 | 107.340 | 104.820 | 104.820 | 107260 | 107260 |
7 | 1 | 105.240 | 105.970 | 103.600 | 104.350 | 105.240 | 105.970 | 103.600 | 104.350 | 86391 | 86391 |
8 | 1 | 108.500 | 108.850 | 105.510 | 105.520 | 108.500 | 108.850 | 105.510 | 105.520 | 110640 | 110640 |
9 | 1 | 107.180 | 108.650 | 106.700 | 108.300 | 107.180 | 108.650 | 106.700 | 108.300 | 64086 | 64086 |
10 | 1 | 106.600 | 107.950 | 106.590 | 107.020 | 106.600 | 107.950 | 106.590 | 107.020 | 53335 | 53335 |
11 | 1 | 106.790 | 107.450 | 105.590 | 106.550 | 106.790 | 107.450 | 105.590 | 106.550 | 108640 | 108640 |
12 | 1 | 106.350 | 108.640 | 106.230 | 107.100 | 106.350 | 108.640 | 106.230 | 107.100 | 53048 | 53048 |
13 | 1 | 107.490 | 108.050 | 106.490 | 106.850 | 107.490 | 108.050 | 106.490 | 106.850 | 46148 | 46148 |
14 | 1 | 105.500 | 106.900 | 105.490 | 106.900 | 105.500 | 106.900 | 105.490 | 106.900 | 48367 | 48367 |