We held a reaction time experiment in which people had to resolve 20 puzzles as fast as possible. The 20 answers and reactions times are in an SPSS data file which we named trials.sav. Part of if is shown below.

In first instance, we'd just like to inspect the histograms of our reaction time variables. The easiest way is running FREQUENCIES as shown below but specifiying the right variable names is cumbersome even for this very tiny data file.

If our reaction times were adjacent, we could address the entire block with the TO keyword. We'll therefore reorder our variables with ADD FILES as shown in SPSS - Reorder Variables with Syntax. The easiest way to get the job done is ADD FILES FILE */KEEP id to agegroup [reaction time variables here] ALL. ALL refers to all variables in our data that we haven't specified yet -in this case all answer variables. This command still requires spelling out all reaction time variables unless we have Python do that for us. Let's first just look up all variable names and proceed from there.

1. Retrieve Variable Names by Index

The spss module allows us to retrieve variable names by index. Now, we've 43 variables in our data but Python starts counting from 0. So our first and last variables should be indexed 0 and 42 by Python. Let's see if that's right by running the syntax below.

2. Retrieve All Variable Indices

So if we can retrieve the first and last variable names by their Python indices -0 and 42- then we can retrieve all of them if we have all indices. A standard way for doing just that is using range.

Technically, range is an iterable object which means that we can loop over it. The syntax below shows how that works.

Result

3. Retrieve All Variable Names

We'll now run a very simple Python for loop over our variable indices. In each iteration, we'll retrieve one variable name, resulting in the names of all variables in our data. We'll filter out our target variables in the next step.

4. Filter Variable Names

Before we'll create and run the required syntax, we still need to filter out only those variables having “Time” in their variable names. We'll use a very simple Python if statement for doing so. The syntax below retrieves exactly our target variables.

5. Create Python String Holding Target Variables

We'd like to create some SPSS syntax containing the variables we selected in the previous syntax. We'll first pass the names into a Python string we'll call timeVars. We first create it as an empty string and then concatenate each variable name and a space to it.

Minor note: editing strings is considered bad practice because they're immutable. Our reason for doing so anyway is that it keeps things simple. It gets the job done just fine unless we're processing a truly massive amount of code -which we basically never do in SPSS.

6. Create Required SPSS Syntax

We're almost there. We'll now create our basic ADD FILES command as a Python string. In the syntax below, %s is a placeholder that we'll replace with our time variable names. For more details on this technique, please consult SPSS Python Text Replacement Tutorial.

7. Create and Run Desired Syntax

Let's take a close look at the syntax we just created. Is it exactly what we need? Sure? Then we'll comment out the print command and run our syntax with spss.Submit instead.

8. Run Histograms

Now that we nicely sorted our variables, running the desired histograms is easily done with the TO keyword as shown below.

Although we got our first job done, we're rather dissatisfied with the crazy long variable names. In our humble opinion, variable names should be short and simple. More elaborate descriptions of what variables mean should go into their variable labels.

We're going to do just that in our next lesson.

Let's move on.