The EXPAND Procedure
- Overview
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Getting Started
Converting to Higher Frequency SeriesAggregating to Lower Frequency SeriesCombining Time Series with Different FrequenciesInterpolating Missing ValuesRequesting Different Interpolation MethodsUsing the ID StatementSpecifying Observation CharacteristicsConverting Observation CharacteristicsCreating New VariablesTransforming Series -
Syntax
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Details
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Examples
- References
Identifying Observations
The variable specified in the ID statement is used to identify the observations. Usually, SAS date or datetime values are used for this variable. PROC EXPAND uses the ID variable to do the following:
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identify the time interval of the input values
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validate the input data set observations
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compute the ID values for the observations in the output data set
Identifying the Input Time Intervals
When the FROM= option is specified, observations are understood to refer to the whole time interval and not to a single time point. The ID values are interpreted as identifying the FROM= time interval containing the value. In addition, the widths of these input intervals are used by the OBSERVED= values TOTAL, AVERAGE, MIDDLE, and END.
For example, if FROM=MONTH is specified, then each observation is for the whole calendar month containing the ID value for the observation, and the width of the time interval covered by the observation is the number of days in that month. Therefore, if FROM=MONTH, the ID value ’31MAR92’D is equivalent to the ID value ’1MAR92’D–both of these ID values identify the same interval, March of 1992.
Widths of Input Time Intervals
When the FROM= option is not specified, the ID variable values are usually interpreted as referring to points in time. However, if an OBSERVED= option value is specified that assumes the observations refer to whole intervals and also requires interval widths (TOTAL or AVERAGE), then, in the absence of the FROM= specification, interval widths are assumed to be the time span between ID values. For the last observation, the interval width is assumed to be the same as for the next to last observation. (If neither the FROM= option nor the ID statement are specified, interval widths are assumed to be 1.0.) A note is printed in the SAS log warning that this assumption is made.
Validating the Input Data Set Observations
The ID variable is used to verify that successive observations read from the input data set correspond to sequential FROM= intervals. When the FROM= option is not used, PROC EXPAND verifies that the ID values are nonmissing and in ascending order. An error message is produced and the observation is ignored when an invalid ID value is found in the input data set.
ID values for Observations in the Output Data Set
The time unit used for the ID variable in the output data set is controlled by the interval value specified by the TO= option. If you specify a date interval for the TO= value, the ID variable values in the output data set are SAS date values. If you specify a datetime interval for the TO= value, the ID variable values in the output data set are SAS datetime values.
The date or datetime values for the ID variable for output observations is the first date or datetime of the TO= interval, unless the ALIGN= option is used to specify a different alignment. (For example, if TO=WEEK is specified, then the output dates are Sundays. If TO=WEEK.2 is specified, then the output date are Mondays.) See Chapter 5: Date Intervals, Formats, and Functions, for more information on interval specifications.