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---
configs:
- config_name: small
data_files:
- split: train
path: "train-small.parquet"
- split: val
path: "val-small.parquet"
- split: test
path: "test-small.parquet"
default: true
- config_name: large
data_files:
- split: train
path: "train-large.parquet"
- split: val
path: "val-large.parquet"
- split: test
path: "test-large.parquet"
---
# ExcelFormer Benchmark
The datasets used in [ExcelFormer](https://arxiv.org/abs/2301.02819). The usage example is as follows:
```python
from datasets import load_dataset
import pandas as pd
import numpy as np
# process train split, similar to other splits
data = {}
datasets = load_dataset('jyansir/excelformer') # load 96 small-scale datasets in default
# datasets = load_dataset('jyansir/excelformer', 'large') # load 21 large-scale datasets with specification
dataset = datasets['train'].to_dict()
for table_name, table, task in zip(dataset['dataset_name'], dataset['table'], dataset['task']):
data[table_name] = {
'X_num': None if not table['X_num'] else pd.DataFrame.from_dict(table['X_num']),
'X_cat': None if not table['X_cat'] else pd.DataFrame.from_dict(table['X_cat']),
'y': np.array(table['y']),
'y_info': table['y_info'],
'task': task,
}
```
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