Basic data operations in SPSS - ISS - University of Leeds

Basic data operations in SPSS for Windows 17
Version 6 (November 2009)
2.1.3 SPSS System Variables
SPSS uses a set of special variables, called system variables, with reserved names to hold the values of
commonly used data items. Their names begin with a dollar sign ($).
Table 2 lists a selection of these variables and their values.
Variable Description
$CASENUM Records the number of cases read up to and including the current case.
$SYSMIS System Missing Value
$JDATE Current date in number of days since October 14, 1582
$DATE Current date in the form dd-mmm-yy
$DATE11 Current date in the form dd-mmm-yyyy
$TIME Current date and time. Value is the number of seconds from midnight,
October 14, 1582 to the time when the value of $TIME is used.
Table 2: A selection of SPSS system variables
Although their values can not be modified, system variables may be used in the same way as normal variables
within data transformations.
2.2 Computing Counts Using COUNT
A common requirement is the need to form a count of the number of occurrences of a particular value across a
list of variables. For example, patients’ medical data may contain variables recording the presence or absence
of a host of symptoms. If the presence of a symptom is coded using ‘1’, the number of symptoms exhibited by
the patient is just the number of variables with the value ‘1’. Although the Compute facility can deal with this
problem, the Count facility provides a more efficient means of performing this task.
Task 5 Computing a Count
Objective Create a count of the number of occurrences of a value in a set of variables.
Problem The SPSS data file census.sav contains data derived from a national census. The variables
natenvir, natheal, natcrime, natdrug, nateduc, natdef and natmass record the respondents’
views on the adequacy of the Government’s spending in several areas of national importance,
such as Health and Education.
The responses to these variables are coded as follows:
Code Label
0 Missing
1 Too Little
2 About Right
3 Too Much
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