Datasets:
metadata
license: other
pretty_name: FxBench
size_categories:
- n<1K
task_categories:
- text-generation
tags:
- spreadsheets
- excel
- formula-completion
FxBench
FxBench is a spreadsheet formula-completion benchmark. Each row contains one target formula and the corresponding workbook snapshot needed to solve it.
Dataset contents
This release contains 503 examples.
Columns in the Hugging Face Parquet split:
| Column | Type | Description |
|---|---|---|
id |
string | Public example ID in the form fxbench-{i}. |
function |
string | Primary Excel function for the target formula. |
formula |
string | Ground-truth Excel formula. Empty for ABSTAIN rows where no formula response is expected. |
target_cell |
string | Cell address where the formula belongs. |
target_sheet |
string | Worksheet containing the target cell. |
workbook |
binary | XLSX workbook snapshot bytes. |
The auxiliary metadata.jsonl manifest contains scalar public metadata only; workbook bytes are in the Parquet split.
The loadable split is data/train-00000-of-00001.parquet and stores the workbook column as XLSX bytes.
Workbook bytes are sanitized before export to remove document properties, classification-label metadata, custom properties, comment/person metadata, and local path markers while preserving workbook sheets and links.
Loading
from datasets import load_dataset
ds = load_dataset("<your-namespace>/<your-dataset-repo>", split="train")
row = ds[0]
with open(f"{row['id']}.xlsx", "wb") as f:
f.write(row["workbook"])