Understanding the Problem

Working with nested data structures in R is a common task, especially when dealing with JSON responses or complex data pipelines. A common issue occurs when a list-column contains nested data frames (or tibbles) with column names identical to the parent data frame (e.g., columns x and y).

When you run standard tidyr::unnest() on such a data frame, R attempts to perform a horizontal join (column-bind), appending new wide columns like x...1 and x...3 instead of appending the nested content as new rows below the original parent row.

Here, we will explore why this happens and look at the most efficient, scalable ways to unnest list-columns into new rows under existing column names, even on large datasets (30,000+ rows / 1GB+ memory).

The Problem Demonstrated

Consider the following sample dataset: