This learning module illustrates how to reshape data
files in SPSS. These examples take wide data files and reshape them into long form. These
show common examples of reshaping data but do not exhaustively demonstrate the
different kinds of data reshaping that you could encounter.
Example #1: One variable
Consider the file containing the kids and their heights at
one year of age (ht1) and at two years of age (ht2).
get file 'c:https://stats.idre.ucla.edu/wp-content/uploads/2016/02/kidshtwt.sav'. list famid birth ht1 ht2.
FAMID BIRTH HT1 HT2
1.00 1.00 2.80 3.40
1.00 2.00 2.90 3.80
1.00 3.00 2.20 2.90
2.00 1.00 2.00 3.20
2.00 2.00 1.80 2.80
2.00 3.00 1.90 2.40
3.00 1.00 2.20 3.30
3.00 2.00 2.30 3.40
3.00 3.00 2.10 2.90
Number of cases read: 9 Number of cases listed: 9
This is called a wide format since the
heights are contained in different variables (which makes the data set "wide"). We may want the data to be long, where each
height is in a separate observation (making the data set "long"), but there is
only one variable for height. We can use the SPSS command varstocases
to reshape the data from wide to long format. The /make
subcommand is used to create the new variables in the long data set from the
old variables in the wide data set. The first variable name given on
that subcommand, in this case, ht, is the name of the new variable.
You can call this new variable anything that you like. The keyword
from is then used, followed by the names of the variables from the wide
data set that will make up the new variable in the long data set. The
/index subcommand is then used the create the variable age.
This subcommand is optional; the reshaping will work without it. The
index variable indicates from which variable from the wide data set used on
the /make subcommand the observations comes. Hence, when the
value of age is one, the value of ht was taken from ht1.
When the value of age is two, the value of ht was taken from
ht2.
varstocases /make ht from ht1 ht2 /index = age. list famid age birth ht.
FAMID BIRTH AGE HT
1.00 1.00 1.00 2.80
1.00 1.00 2.00 3.40
1.00 2.00 1.00 2.90
1.00 2.00 2.00 3.80
1.00 3.00 1.00 2.20
1.00 3.00 2.00 2.90
2.00 1.00 1.00 2.00
2.00 1.00 2.00 3.20
2.00 2.00 1.00 1.80
2.00 2.00 2.00 2.80
2.00 3.00 1.00 1.90
2.00 3.00 2.00 2.40
3.00 1.00 1.00 2.20
3.00 1.00 2.00 3.30
3.00 2.00 1.00 2.30
3.00 2.00 2.00 3.40
3.00 3.00 1.00 2.10
3.00 3.00 2.00 2.90
Number of cases read: 18 Number of cases listed: 18
Example #2: Two variables
Let’s use the same data file, but with all of the variables.
In this example, we show how to reshape two variables at a time. Note
that you can reshape as many variables as you need by adding a /make
subcommand for each set of variables to be reshaped.
get file 'c:https://stats.idre.ucla.edu/wp-content/uploads/2016/02/kidshtwt.sav'. list.
FAMID BIRTH HT1 HT2 WT1 WT2
1.00 1.00 2.80 3.40 19 28
1.00 2.00 2.90 3.80 21 28
1.00 3.00 2.20 2.90 20 23
2.00 1.00 2.00 3.20 25 30
2.00 2.00 1.80 2.80 20 33
2.00 3.00 1.90 2.40 22 33
3.00 1.00 2.20 3.30 22 28
3.00 2.00 2.30 3.40 20 30
3.00 3.00 2.10 2.90 22 31
Number of cases read: 9 Number of cases listed: 9
varstocases /make ht from ht1 ht2 /make wt from wt1 wt2 /index = age. list.
FAMID BIRTH AGE HT WT
1.00 1.00 1.00 2.80 19.00
1.00 1.00 2.00 3.40 28.00
1.00 2.00 1.00 2.90 21.00
1.00 2.00 2.00 3.80 28.00
1.00 3.00 1.00 2.20 20.00
1.00 3.00 2.00 2.90 23.00
2.00 1.00 1.00 2.00 25.00
2.00 1.00 2.00 3.20 30.00
2.00 2.00 1.00 1.80 20.00
2.00 2.00 2.00 2.80 33.00
2.00 3.00 1.00 1.90 22.00
2.00 3.00 2.00 2.40 33.00
3.00 1.00 1.00 2.20 22.00
3.00 1.00 2.00 3.30 28.00
3.00 2.00 1.00 2.30 20.00
3.00 2.00 2.00 3.40 30.00
3.00 3.00 1.00 2.10 22.00
3.00 3.00 2.00 2.90 31.00
Number of cases read: 18 Number of cases listed: 18
Example #3: Modifying numeric suffixes
This example is like the first example in that we are reshaping only one
variable. The difference is that we will use the keyword to on
the /make subcommand so that we do not have to list all of the
variables in the wide data set that are to be included in the new variable in
the long data set. Another difference is that on the /index
subcommand we have listed the variable created on the /make subcommand,
income, in parentheses. This tells SPSS to put the values
of year (96, 97 and 98) into the variable year. If we had written
the subcommand as /index year the values given in the variable year
would have been 1, 2 and 3.
get file 'c:https://stats.idre.ucla.edu/wp-content/uploads/2016/02/faminc.sav'. list.
FAMID FAMINC96 FAMINC97 FAMINC98
3.00 75000.00 76000.00 77000.00
1.00 40000.00 40500.00 41000.00
2.00 45000.00 45400.00 45800.00
Number of cases read: 3 Number of cases listed: 3
varstocases /make income from faminc96 to faminc98 /index year (income). list.
FAMID YEAR INCOME
3.00 96.00 75000.00
3.00 97.00 76000.00
3.00 98.00 77000.00
1.00 96.00 40000.00
1.00 97.00 40500.00
1.00 98.00 41000.00
2.00 96.00 45000.00
2.00 97.00 45400.00
2.00 98.00 45800.00
Number of cases read: 9 Number of cases listed: 9
Example #4: String variables and character suffixes
It also is possible to reshape a wide data file to be long when there are character suffixes
on the names of the variables in the wide data set. Look at the
dmorder file below. Note that we want our long data set to contain a
new string variable called name.
get file 'c:https://stats.idre.ucla.edu/wp-content/uploads/2016/02/dmorder.sav'. list.
FAMID NAMED NAMEM INCD INCM
1.00 Bill Bess 30000.00 15000.00
2.00 Art Amy 22000.00 18000.00
3.00 Paul Pat 25000.00 50000.00
Number of cases read: 3 Number of cases listed: 3
varstocases /make name from named namem /make income from incd incm /index dadmom. list.
FAMID DADMOM NAME INCOME
1.00 1 Bill 30000.00
1.00 2 Bess 15000.00
2.00 1 Art 22000.00
2.00 2 Amy 18000.00
3.00 1 Paul 25000.00
3.00 2 Pat 50000.00
Number of cases read: 6 Number of cases listed: 6
Example #5: Non-contiguous variables
The only time that variables being non-contiguous is a problem is when
you want to use the keyword to to specify a range of variables.
If the variables in the wide data set are non-contiguous, you have two options
when reshaping to long. One option is just to list all of the variables
on the /make subcommand. The other option is to rearrange the
variables in the wide data set and then use the keyword to on the
/make subcommand. To rearrange the variables in the wide data set,
you can use the save command with the /keep subcommand, as shown
below. The variables will be in the data set in the order in which you
list them on the /keep subcommand.
get file 'c:https://stats.idre.ucla.edu/wp-content/uploads/2016/02/dadmomw.sav'. list.
FAMID NAMED INCD NAMEM INCM
1.00 Bill 30000.00 Bess 15000.00
2.00 Art 22000.00 Amy 18000.00
3.00 Paul 25000.00 Pat 50000.00
Number of cases read: 3 Number of cases listed: 3
save outfile = "c:dmorder.sav" /keep=famid named namem incd incm. execute. get file 'c:dmorder.sav'. list.
FAMID NAMED NAMEM INCD INCM
1.00 Bill Bess 30000.00 15000.00
2.00 Art Amy 22000.00 18000.00
3.00 Paul Pat 25000.00 50000.00
Number of cases read: 3 Number of cases listed: 3
varstocases /make name from named namem /make income from incd incm /index dadmom. list.
FAMID DADMOM NAME INC
1.00 1.00 Bill 30000.00
1.00 2.00 Bess 15000.00
2.00 1.00 Art 22000.00
2.00 2.00 Amy 18000.00
3.00 1.00 Paul 25000.00
3.00 2.00 Pat 50000.00
Number of cases read: 6 Number of cases listed: 6
Example #6: Creating an ID variable
Sometimes you want to know from which row of the wide data set the values in
the long data set came. You can create a variable in the long data set to
tell you this by using the /id subcommand, as shown below. You need
to provide a name for the new variable on the /id subcommand after the =
sign. In our example, we called the new variable id1. Notice
the difference between the /index and /id subcommands. The
/index subcommand creates a variable that tells you from what variable
the values of the reshaped variable are obtained, whereas the /id
subcommand creates a variable that tells you from what row of data in the wide
data set the observation is obtained.
get file "c:https://stats.idre.ucla.edu/wp-content/uploads/2016/02/dadmomw.sav". varstocases /make name from named namem /make income from incd incm /index dadmom /id=id1. list.
ID1 FAMID DADMOM NAME INCOME
1 1.00 1 Bill 30000.00
1 1.00 2 Bess 15000.00
2 2.00 1 Art 22000.00
2 2.00 2 Amy 18000.00
3 3.00 1 Paul 25000.00
3 3.00 2 Pat 50000.00
Number of cases read: 6 Number of cases listed: 6