---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: id
    dtype: string
  - name: pre_text
    dtype: string
  - name: post_text
    dtype: string
  - name: table
    dtype: string
  - name: qa
    struct:
    - name: question
      dtype: string
    - name: program
      dtype: string
    - name: exe_ans
      dtype: string
  splits:
  - name: train
    num_bytes: 31018406
    num_examples: 7134
  - name: test
    num_bytes: 4881165
    num_examples: 1147
  download_size: 12825988
  dataset_size: 35899571
---

# FinQA Dataset (Processed)

## Dataset Description

### Dataset Summary
The FinQA dataset is designed for numerical reasoning over financial data, containing questions that require complex reasoning over tables and text from financial reports. This processed version is formatted for consistency with other financial reasoning datasets.

### Dataset Statistics
- Total examples: 8281
- Training set size: 6624 examples
- Test set size: 1657 examples

### Dataset Structure
Each example contains:
- Required columns:
  - query: The question to be answered (derived directly from qa.question)
  - context: Combined context including pre-text, table, and post-text, formatted with random section headers and separators for variety
  - output: The execution answer (derived from qa.exe_ans)
- Original FinQA fields:
  - id: Unique example identifier
  - pre_text: Text appearing before the table
  - post_text: Text appearing after the table
  - table: Tabular data in string format
  - program: The reasoning program to derive the answer
  - exe_ans: The execution result

### Context Formation
The context field is created by concatenating:
1. Pre-text with a randomly selected header (e.g., "Background:", "Context:", "Pre-text:")
2. Table data with a randomly selected header (e.g., "Data Table:", "Tabular Data:", "Table:")
3. Post-text with a randomly selected header (e.g., "Additional Information:", "Follow-up:", "Post-table:")

These sections are joined using random separators (##, 

, or --) to create variety.

## Dataset Creation

### Source Data
This dataset is derived from the FinQA dataset created by Chen et al. The original dataset is available at [FinQA GitHub Repository](https://github.com/czyssrs/FinQA).

### Citation

```
@article{chen2021finqa,
  title={FinQA: A Dataset of Numerical Reasoning over Financial Data},
  author={Chen, Zhiyu and Chen, Wenhu and Smiley, Charese and Shah, Sameena and Borova, Iana and Langdon, Dylan and Moussa, Reema and Beane, Matt and Huang, Ting-Hao and Routledge, Bryan and Wang, William Yang},
  journal={Proceedings of EMNLP 2021},
  year={2021}
}
```
### Licensing Information
This dataset is released under the MIT License, following the original FinQA dataset licensing terms.