Pandas Ge

Pandas Ge is the >= of the comparison family. Two DataFrames in, one boolean DataFrame out, where every cell is True if the left frame's value is greater than or equal to the right frame's value at the same position. "Ge" is pandas shorthand for "greater than or equal," and the pack mirrors that naming across the whole set: Gt (>), Ge (>=), Eq (==), and the Le/Lt cousins for the flip side.

Honestly? For most people this specific node is less useful than its scalar siblings, and that's worth saying plainly. Comparing two whole DataFrames element-wise is a narrow need - matching two files position by position, or generating a comparison matrix. The far more common ask is "which rows have a value above this threshold," and that's Pandas Ge Scalar Float's job, not this one's. Reach for this when you genuinely have two same-shaped tables and want a cell-by-cell truth table.

How it works

a_dataframe.ge(b_dataframe), element-wise, with the output taking the left frame's shape and labels. Standard pandas alignment applies, so if the two frames have different indexes or columns, positions that don't line up produce NaN in the result. Comparison results are true booleans - feed them straight into Pandas Boolean Index to filter, or into a show node to eyeball where B exceeded A.

The classic pairing is with Pandas Sub: subtract two tables to get a delta, then run this against a zero-filled frame to flag every cell where the difference is non-negative. That composes into a "show me where things improved" workflow without writing any code.

Inputs and outputs

• a_dataframe (required, DATAFRAME) - the left frame.
• b_dataframe (required, DATAFRAME) - the right frame.
• DATAFRAME output - boolean result, left-aligned shape and labels.

Installing it

One pack, one install. ComfyUI Manager → search "Data analysis" → install ComfyUI-Data-Analysis → restart → reload the browser. Manual:

cd ComfyUI/custom_nodes
git clone https://github.com/HowToSD/ComfyUI-Data-Analysis
mv ComfyUI-Data-Analysis data-analysis
pip install -r data-analysis/requirements.txt

Requirements are pandas, matplotlib, seaborn, scipy, scikit-learn, openpyxl, lxml. No GPU, no model downloads. The most common "this node doesn't work" failure in this pack is actually an install failure - base ComfyUI ships without pandas, so if the requirements install silently failed, every pandas node here errors on load.