| Working with Time Series Data | 
Storing Time Series in a SAS Data Set
 This section discusses aspects of storing time series in SAS data sets. The topics discussed are the standard form of a time series data set, storing several series with different time ranges in the same data set, omitted observations, cross-sectional dimensions and BY groups, and interleaved time series. 
Any number of time series can be stored in a SAS data set. Normally, each time series is stored in a separate variable. For example, the following statements augment the USCPI data set read in the previous example with values for the producer price index: 
data usprice;
   input date : monyy7. cpi ppi;
   format date monyy7.;
   label cpi = "Consumer Price Index"
         ppi = "Producer Price Index";
datalines;
jun1990 129.9 114.3
jul1990 130.4 114.5
   ... more lines ...   
proc print data=usprice;
run;
    Figure 3.4
    Time Series Data Set Containing Two Series
| JUN1990 | 129.9 | 114.3 | 
| JUL1990 | 130.4 | 114.5 | 
| AUG1990 | 131.6 | 116.5 | 
| SEP1990 | 132.7 | 118.4 | 
| OCT1990 | 133.5 | 120.8 | 
| NOV1990 | 133.8 | 120.1 | 
| DEC1990 | 133.8 | 118.7 | 
| JAN1991 | 134.6 | 119.0 | 
| FEB1991 | 134.8 | 117.2 | 
| MAR1991 | 135.0 | 116.2 | 
| APR1991 | 135.2 | 116.0 | 
| MAY1991 | 135.6 | 116.5 | 
| JUN1991 | 136.0 | 116.3 | 
| JUL1991 | 136.2 | 116.0 | 
 
 
 
  
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