SPSS doesn’t offer an easy way to set decimal places for output tables. This tutorial proposes a very simple tool for setting decimal places in basic output tables after they’ve been produced. It works best for simple tables such as DESCRIPTIVES, MEANS or CROSSTABS.
Setting Decimal Places for Output Tables
- First, make sure that the SPSS Python Essentials are installed and run properly.
- Download and double click the SPSS Output Decimals Tool to install it. Note that this is an SPSS custom dialog.
- Run one or more tables, for example with DESCRIPTIVES, MEANS or CROSSTABS. Select one or more of them in the output viewer window.
- Go to .
- Choose which columns you’d like to process for all selected tables and the desired number of decimal places.
- Click syntax. or and run the
- Different decimal places for different columns can be set by running the tool repeatedly over the same tables, specifying different columns and decimal places in each run.*
The diagram below illustrates how to specify columns. Note that the first “columns” don’t count; according to SPSS pivot table terminology, these are not columns but row labels.*
Note that row and column labels are never affected by the Output Decimals tool. Although the diagram shows value labels (“Very bad” and so on) here instead of values, this is not always the case. If values are shown, then decimal places for row and column labels can easily be set by FORMATS.
SPSS Decimal Places in Output – Alternatives
- Since Python was introduced in SPSS version 14, Python scripting is the way to go for setting decimal places for output tables. The level of control it offers is basically unlimited but most users may find Python scripts hard to write and they require a lot of syntax. The output decimals tool uses Python scripting under the hood.
- The classical approach to setting decimal places for output tables is an SPSS script. Note that SPSS scripts (.sbs files) are very different from SPSS syntax (.sps) files. SPSS scripts are considered deprecated since Python scripting was introduced as its successor in SPSS version 14.
- SPSS OUTPUT MODIFY can be used for modifiying basically anything about SPSS output tables including decimal places and text styles. Due to its complexity, however, we find it rather hard to get things done with it. Personally, we strongly prefer simpler tools even if they offer less functionality.
SPSS Python Syntax Example
data list free/id.
0 0 0 0 0 0 0 0 0 0 0
end data.do repeat v = v1 to v5.
compute v = rv.binom(5,.5).
end repeat.************20. GENERATE SOME TABLES.
descriptives v1 v2.
means v1 by v2.
crosstabs v1 by v2/cells column.
************30. DEFINE FUNCTION.
outputDoc = SpssClient.GetDesignatedOutputDoc()
outputItems = outputDoc.GetOutputItems()
for index in range(outputItems.Size()):
outputItem = outputItems.GetItemAt(index)
if outputItem.GetType() == SpssClient.OutputItemType.PIVOT and outputItem.IsSelected():
pTable = outputItem.GetSpecificType()
dataCells = pTable.DataCellArray()
for row in range(dataCells.GetNumRows()):
if cols.lower() != ‘all’:
colList = [int(col) – 1 for col in cols.split(‘,‘)] #Because indexed at 0
print “Invalid column specification. Please specify positive integers separated by commas or the ‘ALL’ keyword.”
colList = range(dataCells.GetNumColumns())
for col in colList:
************40. TEST: SELECT (ONLY) DESCRIPTIVES TABLE IN OUTPUT AND RUN.
************50. TEST: SELECT (ONLY) MEANS TABLE IN OUTPUT AND RUN.
************60. TEST: SELECT (ONLY) CROSSTAB IN OUTPUT AND RUN.