How can I merge split and transformed JSON data back into its original loop structure using n8n?

Below is some guidance on how to approach merging data from split loops while preserving the original grouping.

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Why the Merge Node Might Not Be Working as Expected

The Merge node works by combining data from multiple input streams, and it always gives precedence to Input 1 when the number of items is uneven. When you add your "table path" as an extra input, you may be merging data streams whose items no longer line up one‑to‑one. This can lead to an unexpected reduction in loops (for example, ending up with only 2 runs and 11 items instead of 9 runs with 52 items). In your case, the fact that merging works fine for text, pic, and other but “breaks” when adding table data indicates that the incoming items do not have a one-to-one relationship or the groups for the table are different from the others.

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How to Fix Your Workflow

1. Merge by Corresponding Key/Index:
   If the items in each loop have a unique key or index (you could add one if it’s not already there), configure the Merge node to combine the flows by matching that key. For the “Combine by Matching Fields” strategy, make sure the Input 1 and Input 2 fields are identically named (e.g. a field like “loopId” or “index”) so that n8n can correctly match the related items.

2. Use the “Include Any Unpaired Items” Option:
   When merging by position using the Combine mode, enable the option “Include Any Unpaired Items” so that items without a match in one of the inputs aren’t lost. This is important when the table output might not have a value for every item from Input 1.

3. Merge Within the Loop:
   If your transformations are done per loop, consider merging the data inside each loop iteration rather than after all loops are complete. For example, using a Loop Over Items node:

   • First, split the JSON into individual loops.
   • Process your transformations (text, pic, table, etc.) for each loop.
   • Then, merge the transformed items for that single loop (using a Merge node inside the loop or by using an expression to combine them).
   • Finally, let the Loop Over Items node combine the results.

   This way, you preserve the grouping and are not inadvertently merging across different loops.

4. Check Data Structure and Dot-Notation Matching:
   When you reference nested properties (for example, in table objects), ensure you are using the correct dot-notation (as plain text, not as an expression). Also, verify that all inputs share the same structure or keys where they need to be matched. Even a slight mismatch can lead to an incorrect merge.

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Summary

• Ensure Consistency: Add a unique identifier (or ensure a common field) that is present in every data item from the different inputs.
• Use Merge Options Appropriately: Try the “Include Any Unpaired Items” option and verify your mode (e.g., Append vs. Combine) based on your desired output.
• Consider Intra-Loop Merging: If possible, merge the data for each loop separately to avoid mixing data from unrelated loops.

By aligning the keys (or index positions) and handling unmatched items, you should be able to get the expected output of 9 runs with a total of 52 items.

Feel free to ask for examples or more details on any of these approaches!