Creating dummy variables (from UCLA site)

* make dummies, method 1 .
COMPUTE race1=(race=1).
COMPUTE race2=(race=2).
COMPUTE race3=(race=3).
crosstabs /tables = race by race1 
          /tables = race by race2 
          /tables = race by race3.

* make dummies, method 2 .
DO REPEAT A=race1 race2 race3 /B=1 2 3.
COMPUTE A=(race=B).
END REPEAT.
crosstabs /tables = race by race1 
          /tables = race by race2 
          /tables = race by race3.

http://www.ats.ucla.edu/stat/spss/code/dummy.htm

PSPP another data analysis software

you can download it for free here.

to explore more: Create a pivot table using Python

#Create a pivot table
        table = spss.BasePivotTable("Group Means",
                                    "OMS table subtype")
        table.Append(spss.Dimension.Place.row,
                     spss.GetVariableLabel(groupIndex))
        table.Append(spss.Dimension.Place.column,
                     spss.GetVariableLabel(sumIndex))

        category2 = spss.CellText.String("Mean")
        for cat in sorted(Counts):
            category1 = spss.CellText.Number(cat)
            table[(category1,category2)] = \
                   spss.CellText.Number(Totals[cat]/Counts[cat])

Source: SPSS online help. 

Creating new variables with R

# Three examples for doing the same computations

mydata$sum <- br="" mydata="" x1="" x2=""> mydata$mean <- br="" mydata="" x1="" x2="">
attach(mydata)
mydata$sum <- br="" x1="" x2=""> mydata$mean <- br="" x1="" x2=""> detach(mydata)

mydata <- br="" mydata="" transform=""> sum = x1 + x2,
mean = (x1 + x2)/2
) 

Source for the above code.

R help with read

help

Copying value labels from an existing variable...

OR you could use the values from another variable which has the same labels.

APPLY DICTIONARY

  /FROM *

  /SOURCE VARIABLES = b9a

  /TARGET VARIABLES =  occupf

  /FILEINFO

  /VARINFO ALIGNMENT FORMATS LEVEL MISSING VALLABELS = REPLACE VARLABEL WIDTH .