The EXPAND Procedure
- Overview
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Getting Started
Converting to Higher Frequency Series Aggregating to Lower Frequency Series Combining Time Series with Different Frequencies Interpolating Missing Values Requesting Different Interpolation Methods Using the ID Statement Specifying Observation Characteristics Converting Observation Characteristics Creating New Variables Transforming Series -
Syntax
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Details
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Examples
- References
| ID Statement |
The ID statement names a numeric variable that identifies observations in the input and output data sets. The ID variable’s values are assumed to be SAS date or datetime values.
The input data must form time series. This means that the observations in the input data set must be sorted by the ID variable (within the BY variables, if any). Moreover, there should be no duplicate observations, and no two observations should have ID values within the same time interval as defined by the FROM= option.
If the ID statement is omitted, SAS date or datetime values are generated to label the input observations. These ID values are generated by assuming that the input data set starts at a SAS date value of 0, that is, 1 January 1960. This default starting date is then incremented for each observation by the FROM= interval (using the same logic as DATA step INTNX function). If the FROM= option is not specified, the ID values are generated as the observation count minus 1. When the ID statement is not used, an ID variable is added to the output data set named either DATE or DATETIME, depending on the value specified in the TO= option. If neither the TO= option nor the FROM= option is given, the ID variable in the output data set is named TIME.