# Iterate over rows en columns to set a new background color.įor i in range(SpssDataCells.GetNumRows()):įor j in range(SpssDataCells.GetNumColumns()): PivotTable = OutputItem.GetSpecificType() OutputItem = OutputItems.GetItemAt(index) # Call the list of items in that document. OutputDoc = SpssClient.GetDesignatedOutputDoc() You’ll need the data from the previous steps to execute this one. In this example, we’ll create a table and change the background colors.
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Now that we know how to manipulate data, it’s time to do something even cooler: alter the output. Things that were unchangeable can suddenly be changed. # Set the values of the new variable per row.ĭ] = val_listīuilt-in functions II: accessing the outputįrom Python you can access anything in SPSS. The first number sets the type(numeric), the second sets #the width (2), the third sets the decimals (0). This allows us to write to file without using spss.Submit(). In the following example, we open the data set and add a new variable to the data. This is achieved by using the spss.dataset class. To do much of anything in SPSS, you’ll need access to the current data set. Now that we have the basics down, let’s explore some of the other neat built-in functions from the SPSS module.īuilt-in functions I: accessing data sets It was an entirely useless one, but I still suggest you take a moment to celebrate. There! You just automated your first SPSS procedure. Add the following to your syntax file before running again: Now let’s try repeating this process in a Pythonic while-loop. This should display a frequency table of a variable you just created. # Import the SPSS and SPSS Client modules. Paste the following into your syntax editor and select “run all”:
This function allows you to send syntax commands to SPSS from within a Python block. The first one we’ll explore is the spss.Submit() function.
This ensures that a ton of built-in functions are available to you. Welcome to the world of Python! When using Python in SPSS, the first order of business is to import the SPSS module into your Python script.
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The code you enter in this block will not be parsed as SPSS syntax, but as Python code. To start using Python, simply open a syntax file and create a BEGIN PROGRAM – END PROGRAM block. For older versions, the plugin can be found here. It ships with SPSS versions 22 and later. Complete the first 9 pages of the tutorial (including “functions”) and you should know all you need for now.įirst, make sure you have the Python plugin installed. If you are completely new to Python, I recommend learning the basics here. Some familiarity with coding in Python is assumed. In this tutorial, we’ll step through the basics of using Python with SPSS. Among other things, it allows SPSS users to condense tedious or repetitive syntax scripting into a few lines of awesome Python code. The Python programming language is a useful skill in the tool box of any data geek.
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