Learning Objectives

After completing this lesson, you’ll be able to:

• Manipulate lists and extract information from them using common list transformers.
• Join records and build a list from shared attributes using the ListBuilder.
• Create records from key-value pairs stored in lists.
• Conduct advanced list manipulation using the PythonCaller.
• Use the List Element Selection dialog to create new attributes using list values.

Instructions

In this lesson, you will:

• Scroll down to read the text below.
  
  • Optional: You can view the video instead of reading the text. The video covers the text material.
• Complete the exercise by following the steps.
• Complete the Quiz toward the bottom of the page.
• Optional: Let us know if you found this lesson relevant to your role by filling out the survey at the bottom of the page.
• Click 'Next' to mark the lesson complete.

Resources

• Starting workspace
  • C:\FMEData\Workspaces\AdvancedDataTransformation\manipulate-lists-using-transformers.fmw
• Complete workspace
  • C:\FMEData\Workspaces\AdvancedDataTransformation\manipulate-lists-using-transformers-complete.fmw
• street-trees.csv
  • C:\FMEData\Resources\FormBasic\street-trees.csv
• parks-polygon-representation.geojson 
  • C:\FMEData\Resources\FormBasic\parks-polygon-representation.geojson

Exercise

Jennifer's workspace creates a list of every tree in each park. She's added a TestFilter to filter park polygons that have trees.

She'd like to update the workspace to do the following:

1. Filter the data to examine parks with trees.
2. Find the most common genus among all park trees.
3. Store the name of that genus in a new attribute.

1) Open Starting Workspace and Run It

• Start FME Workbench (2026.1 or later).
• Open the starting workspace (C:\FMEData\Workspaces\AdvancedDataTransformation\manipulate-lists-using-transformers.fmw).
• Run the workspace with caching enabled.

2) Create a Single List Using a ListBuilder

To get the most common genus, we need to combine the separate lists for each park record into a single list. We can do that using an ListBuilder transformer.

• Add a ListBuilder connected to the TestFilter's Trees output port.
• Set List Name to _list and add just _trees{}.GENUS_NAME to the list.

• Click OK.
• Run the workspace.
• Inspect the ListBuilder's single output record.
• In the Record Information window, find the new _list attribute with 125 elements.
  • Each element stores the _trees list for each park, recording the genus of each tree.
  • You could normally use an Aggregator here instead, using Generate List and adding _trees{}.GENUS_NAME to the list. The result would be the same as using the ListBuilder. However, there is a bug in FME 2026.1 that results in excess nulls in Aggregator lists. This bug is fixed in 2026.2.

3) Count Genus Names Using a ListHistogrammer

• Add a ListHistogrammer connected to the ListBuilder's Output port.
  • This transformer lets us count the times each genus appears in this new list.
• Configure the ListHistogrammer to use _list{}.trees{}.GENUS_NAME as the Source List Attribute.
  • This configuration means the transformer will count the values of all GENUS_NAME attributes in the list and store the result in a new list attribute called _histogram.

• Click OK.
• Run the workspace
• Inspect the ListHistogrammer's Output cache.
• In the Record Information Window, find the new _histogram list attribute.
  • Make sure you collapse the large _list attribute still present on the record; _histogram will be below it in the Record Information Window.
• Expand the_histogram attribute to see the histogram's results.
  • The most common value is stored as element 0 in the list, with the count attribute reflecting the number of times it appears in the list and the attribute value showing the genus name. 
  • Take note of the top GENUS_NAME; you will need it for the quiz.

4) Store the Result Using an AttributeCreator

Now we have found the most common genus, we'd like to store its name in an attribute. 

• Add an AttributeCreator attached to the ListHistogrammer's Output port.
• Add a new Output Attribute called TopGenus.
• Click the ellipsis button to open the Text Editor.

• Double-click _histogram{}.value on the left under FME Feature Attributes to insert it.

• Observe a behavior unique to list attributes. Instead of inserting  _histogram{}.value in the Text Editor, the List Element Selection dialog appears.

• Leave the value of 0 because we want to extract the value of the first element in the list, which is the most common genus.
• Click OK.

Jennifer runs the workspace and inspects the AttributeCreator's Output cache. The new attribute stores the name of the genus:

Challenges

Challenge #1: Find the most and least common genus for trees within parks.

Challenge #2: How do you think the process outlined here will handle ties?

Challenge #3: Don't hard-code the list element in the AttributeCreator. How can you use transformers to extract the index of the most and least common genus instead?

Challenge #4: Is there an easier way to get this answer from the starting data? Do you have to use lists?

Learn More

You can use many other list transformers you could use to continue to process and analyze the tree list. Here are some examples:

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