Variable Explorer data truncation and memory overhead with large DataFrames

The Spyder Variable Explorer provides a GUI-based table viewer to inspect NumPy arrays and Pandas DataFrames, offering an alternative to the truncated output typically seen in the IPython console. To maintain IDE stability and prevent freezing, Spyder implements internal limits on the number of rows and columns rendered in this view.

When working with datasets exceeding these internal thresholds, there is a tension between the need for comprehensive data visibility and the memory overhead required to populate the viewer. It is unclear how the IDE handles the transition from a scrollable view to a truncated state when the underlying object size exceeds available system memory or specific internal configuration limits.

• What are the specific internal limits governing row and column truncation within the Variable Explorer for Pandas DataFrames?
• Is there a mechanism to adjust these display bounds without risking IDE instability?