# Combine lists with like values

**URL:** <https://forum.dynamobim.com/t/combine-lists-with-like-values/115331>\
**Category:** Civil 3D\
**Created:** [October 29, 2026, 4:11pm UTC](https://forum.dynamobim.com/t/combine-lists-with-like-values/115331 "2026-10-29T16:11:54Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![dlarson](https://avatars.discourse-cdn.com/v4/letter/d/5fc32e/32.png) [@dlarson](https://forum.dynamobim.com/u/dlarson)\
**Post date:** [October 29, 2026, 4:11pm UTC](https://forum.dynamobim.com/t/combine-lists-with-like-values/115331/1 "2026-10-29T16:11:54Z")

</div>

I’m trying to group individual lines of text based on their proximity. We often receive parcel information as single lines of text and I want to convert them to a single Mtext object.

 ![image](https://us1.discourse-cdn.com/flex022/uploads/dynamobim/original/3X/0/f/0f9d060e49299f624ba7dfc594bf4bbfab4a55a8.png)

This is what I have so far.

I have no clue how comparing 576 true/false values to a list of 24 strings consistently groups these correctly, but I’ll take it. After the List.UniqueItems I’m usually left with some duplicate though incomplete lists. I’ve been searching for a node-based way to combine the lists that have at least one matching entry. So far nothing has made a solution click for me.

If I can get the lists cleaned up I should be able to reorder the text and create a single Mtext.

 ![PARCEL TEXT COMBINE - TEST_2026-10-29_11-18-35](https://us1.discourse-cdn.com/flex022/uploads/dynamobim/original/3X/e/6/e69f0911f893efbc9ee1ceb8b54786c2b7c184e5.png)

Thank you

---

<div class="post-metadata">

**Author:** ![Mike.Buttery](https://avatars.discourse-cdn.com/v4/letter/m/b19c9b/32.png) [@Mike.Buttery](https://forum.dynamobim.com/u/Mike.Buttery)\
**Post date:** [October 30, 2026, 6:15am UTC](https://forum.dynamobim.com/t/combine-lists-with-like-values/115331/2 "2026-10-30T06:15:53Z")

</div>

When exporting a workspace, zoom in so you can read the node titles. It appears you are doing a cross (cartesian) product of all the text locations distance, then selecting on distance and culling the repeats. This could get very gnarly very quickly as you will experience exponential growth

You could use _List.GroupBySimilarity_ nodes on the Y and then the X, adjust the tolerance to suit. Finally flip the Y values of the group so selection is top down (largest to smallest). I have used rectangles here but as long as you can get a point in space you can group by cluster  
Note: pay attention to the list levels.

 ![clustering](https://us1.discourse-cdn.com/flex022/uploads/dynamobim/original/3X/c/7/c77163c2ad7a24920781a5c2714f45ade21b1aa2.png)