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Datasets:
lainmn
/
AgentDS-RetailBanking

Tasks:
Tabular Classification
Feature Extraction
Text Classification
Languages:
English
Tags:
agentic-ai
synthetic-data
data-science
benchmark
human-AI-collaboration
License:
Dataset card Data Studio Files
xet
Community
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The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 11 new columns ({'SessionID', 'DstAccount', 'Channel', 'Timestamp', 'Amount', 'Timestamp_dt', 'MCC_Group', 'FraudLabel', 'TxnID', 'DeviceID', 'SrcAccount'}) and 5 missing columns ({'DefaultLabel', 'Utilisation', 'PaymentRatio', 'HardInquiries', 'Week'}).

This happened while the csv dataset builder was generating data using

hf://datasets/lainmn/AgentDS-RetailBanking/RetailBanking/transactions_train.csv (at revision e0760b4bcfc7468a9aa72c0fdbaed6131974d7ad)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Timestamp_dt: string
              TxnID: string
              Timestamp: string
              SessionID: string
              CustomerID: string
              SrcAccount: string
              DstAccount: string
              Channel: string
              MCC_Group: string
              Amount: double
              DeviceID: string
              FraudLabel: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1671
              to
              {'CustomerID': Value('string'), 'Week': Value('int64'), 'Utilisation': Value('float64'), 'PaymentRatio': Value('float64'), 'HardInquiries': Value('int64'), 'DefaultLabel': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1455, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1054, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 11 new columns ({'SessionID', 'DstAccount', 'Channel', 'Timestamp', 'Amount', 'Timestamp_dt', 'MCC_Group', 'FraudLabel', 'TxnID', 'DeviceID', 'SrcAccount'}) and 5 missing columns ({'DefaultLabel', 'Utilisation', 'PaymentRatio', 'HardInquiries', 'Week'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/lainmn/AgentDS-RetailBanking/RetailBanking/transactions_train.csv (at revision e0760b4bcfc7468a9aa72c0fdbaed6131974d7ad)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

CustomerID
string
Week
int64
Utilisation
float64
PaymentRatio
float64
HardInquiries
int64
DefaultLabel
int64
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End of preview.

🏦 AgentDS-RetailBanking

This dataset is part of the AgentDS Benchmark — a multi-domain benchmark for evaluating human-AI collaboration in real-world, domain-specific data science.

AgentDS-RetailBanking includes structured transactional data for 2 challenges:

  • Credit default prediction
  • Transaction-level fraud detection

👉 Files are organized in the RetailBanking/ folder and reused across challenges.
Refer to the included description.md for:

  • File usage and challenge mappings
  • Task descriptions and data schema notes
  • Submission format expectations

📖 More info & challenge details: https://agentds.org/domains
🔐 Get your API key: https://agentds.org/dashboard
🧠 Submit predictions via SDK: pip install agentds-bench (see main AgentDS README for usage)

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