Pandas Show Index

The index is the part of a DataFrame everyone forgets about until something breaks. Pandas Show Index exists to drag it into the light: feed it a PDINDEX - the pack's socket type for index objects, which you'd get from the pack's Pandas Index node - and it renders the row labels as text right on the node. It's the debugging sibling of Show DataFrame, scoped specifically to the index, and it's the fastest way to check whether your row labels are what you think they are before you trust a join or a lookup.

It's part of HowToSD/ComfyUI-Data-Analysis, under its Display data category, alongside Show DataFrame and the Series-to-string converters.

How it works

Like the other display nodes, this one is an output node: it takes the PDINDEX, converts it with str(index), returns it as a list of STRINGs, and stamps the text into the node UI and the workflow metadata. So after a run, the index's values are visible on the canvas - no hunting through logs.

The input type matters here: it wants a PDINDEX, not a DataFrame. The pack's Pandas Index node produces that socket type from a DataFrame, so the typical wiring is Pandas Index → Pandas Show Index, which is the pack's own documented pattern. You wouldn't normally chain these into other data nodes; it's a viewing dead-end by design, and that's its job.

Inputs and output

• index_list - a PDINDEX (the row-label object from a DataFrame).

Output: a list of STRING (the index rendered as text).

Installation

Standard pack install. ComfyUI Manager: search Data analysis, install ComfyUI-Data-Analysis. Or:

cd ComfyUI/custom_nodes
git clone https://github.com/HowToSD/ComfyUI-Data-Analysis.git
mv ComfyUI-Data-Analysis data-analysis   # examples rely on this folder name
pip install -r requirements.txt

Restart, reload. Deps: pandas, matplotlib, seaborn, scipy, scikit-learn, openpyxl, lxml - no GPU, no models.

Notes

This node's whole value is answering "what are my row labels, actually?" - which is the first thing to check when a join comes back all NaN or a .loc-style operation misses rows, because pandas aligns on index labels and silently mismatched labels are a top-3 cause of confusing results. It's a small, single-purpose node, and that's fine. If you need the full table instead, Pandas Show DataFrame does the whole thing; this one is specifically for when the index is the suspect.