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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 6 new columns ({'jurisdiction', 'ip_country', 'app_type', 'event_id', 'country', 'local_currency'}) and 3 missing columns ({'banking_hours_indicator', 'arrival_duration_minutes', 'payment_code'}).

This happened while the csv dataset builder was generating data using

hf://datasets/navk8690/paymind-reference-data/payment_method copy.csv (at revision f739e7f1818722bbc87681447e6403b88d8ea6a0), ['hf://datasets/navk8690/paymind-reference-data@f739e7f1818722bbc87681447e6403b88d8ea6a0/arrival copy.csv', 'hf://datasets/navk8690/paymind-reference-data@f739e7f1818722bbc87681447e6403b88d8ea6a0/payment_method copy.csv', 'hf://datasets/navk8690/paymind-reference-data@f739e7f1818722bbc87681447e6403b88d8ea6a0/success copy.csv']

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/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              event_id: string
              timestamp_utc: string
              transaction_type: string
              country: string
              ip_country: string
              jurisdiction: string
              currency: string
              local_currency: string
              amount: double
              app_type: string
              hour: int64
              day_of_week: string
              is_weekend: int64
              is_cross_border: int64
              payment_type: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2081
              to
              {'timestamp_utc': Value('string'), 'transaction_type': Value('string'), 'currency': Value('string'), 'amount': Value('float64'), 'hour': Value('int64'), 'day_of_week': Value('string'), 'is_weekend': Value('int64'), 'is_cross_border': Value('int64'), 'payment_code': Value('string'), 'payment_type': Value('string'), 'banking_hours_indicator': Value('int64'), 'arrival_duration_minutes': Value('float64')}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 6 new columns ({'jurisdiction', 'ip_country', 'app_type', 'event_id', 'country', 'local_currency'}) and 3 missing columns ({'banking_hours_indicator', 'arrival_duration_minutes', 'payment_code'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/navk8690/paymind-reference-data/payment_method copy.csv (at revision f739e7f1818722bbc87681447e6403b88d8ea6a0), ['hf://datasets/navk8690/paymind-reference-data@f739e7f1818722bbc87681447e6403b88d8ea6a0/arrival copy.csv', 'hf://datasets/navk8690/paymind-reference-data@f739e7f1818722bbc87681447e6403b88d8ea6a0/payment_method copy.csv', 'hf://datasets/navk8690/paymind-reference-data@f739e7f1818722bbc87681447e6403b88d8ea6a0/success copy.csv']
              
              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.

timestamp_utc
string
transaction_type
string
currency
string
amount
float64
hour
int64
day_of_week
string
is_weekend
int64
is_cross_border
int64
payment_code
string
payment_type
string
banking_hours_indicator
int64
arrival_duration_minutes
float64
2022-06-15 00:26:25
deposit
CAD
87.87
0
Wednesday
0
0
bank_transfer
bank_transfer
0
9.84
2025-01-16 09:55:09
deposit
SGD
3,155.03
9
Thursday
0
1
worldpay
worldpay
1
0.04
2022-07-18 08:48:19
deposit
EUR
768.82
8
Monday
0
0
checkout
checkout
0
0.11
2022-12-17 07:51:10
deposit
AUD
6,300.37
7
Saturday
1
0
paypal
paypal
0
0.02
2024-10-07 02:39:27
deposit
NZD
154.82
2
Monday
0
0
revolut_pay
revolut_pay
0
0.15
2022-11-09 22:57:09
deposit
NZD
65.24
22
Wednesday
0
1
paypal
paypal
0
0.04
2025-02-08 15:36:18
deposit
USD
12,967.55
15
Saturday
1
0
wise
wise
0
2.97
2023-06-14 12:34:45
deposit
JPY
2,709.94
12
Wednesday
0
0
wise
wise
1
0.18
2023-12-08 18:33:31
withdrawal
GBP
702.84
18
Friday
0
1
wise
wise
0
7.08
2022-07-05 23:40:23
withdrawal
GBP
6,274.61
23
Tuesday
0
1
bank_transfer
bank_transfer
0
260.51
2024-07-05 17:57:48
deposit
USD
3,826.49
17
Friday
0
0
adyen
adyen
0
0.1
2026-04-10 02:14:33
deposit
EUR
2,566.8
2
Friday
0
1
bank_transfer
bank_transfer
0
504.39
2024-03-12 13:34:23
deposit
JPY
116.85
13
Tuesday
0
0
adyen
adyen
1
0.91
2023-02-04 21:11:06
deposit
USD
144.05
21
Saturday
1
0
paypal
paypal
0
0.41
2025-12-20 05:02:50
deposit
CAD
374.59
5
Saturday
1
0
wise
wise
0
3.7
2023-05-25 09:13:26
withdrawal
SGD
114.33
9
Thursday
0
0
bank_transfer
bank_transfer
1
1,022.1
2022-04-21 15:44:18
deposit
SGD
445.74
15
Thursday
0
0
checkout
checkout
1
0.56
2022-05-23 16:16:46
deposit
AUD
472.02
16
Monday
0
0
worldpay
worldpay
1
0.23
2026-02-28 04:47:34
deposit
JPY
10,541.95
4
Saturday
1
0
bank_transfer
bank_transfer
0
754.62
2022-09-12 16:55:03
deposit
EUR
324.32
16
Monday
0
0
stripe
stripe
1
0.2
2024-12-07 04:31:08
deposit
JPY
2,181.28
4
Saturday
1
0
worldpay
worldpay
0
0.5
2022-03-01 08:48:13
withdrawal
NZD
24.34
8
Tuesday
0
1
wise
wise
0
5.55
2024-03-23 00:10:51
deposit
CAD
130.81
0
Saturday
1
0
square
square
0
0.1
2024-07-12 04:29:52
deposit
EUR
9,199.56
4
Friday
0
0
worldpay
worldpay
0
0.22
2024-04-13 11:16:14
deposit
SGD
150.35
11
Saturday
1
0
square
square
0
0.25
2025-09-25 20:32:56
deposit
NZD
34.99
20
Thursday
0
0
revolut_pay
revolut_pay
0
0.78
2025-01-03 13:01:24
deposit
USD
31.71
13
Friday
0
1
adyen
adyen
1
1.53
2025-01-30 16:42:44
deposit
AUD
13,908.09
16
Thursday
0
1
wise
wise
1
21.03
2022-07-23 12:04:17
deposit
AUD
64.52
12
Saturday
1
1
stripe
stripe
0
0.01
2025-09-20 14:19:58
deposit
GBP
981.6
14
Saturday
1
0
adyen
adyen
0
0.62
2022-06-29 02:52:16
deposit
SGD
9,253.61
2
Wednesday
0
0
checkout
checkout
0
0.69
2025-04-25 05:49:54
withdrawal
CAD
441.05
5
Friday
0
0
checkout
checkout
0
48.11
2023-08-16 00:49:24
withdrawal
EUR
36.22
0
Wednesday
0
0
wise
wise
0
614.64
2023-05-22 08:30:30
deposit
GBP
218.03
8
Monday
0
0
adyen
adyen
0
0.34
2026-01-06 02:17:14
deposit
SGD
106.06
2
Tuesday
0
0
adyen
adyen
0
0.02
2023-12-12 12:47:17
deposit
SGD
10,137.34
12
Tuesday
0
0
stripe
stripe
1
0.08
2025-07-20 03:11:43
deposit
GBP
12,649.36
3
Sunday
1
0
stripe
stripe
0
0.09
2026-06-12 09:34:07
deposit
NZD
8,061.88
9
Friday
0
1
paypal
paypal
1
0.06
2022-01-15 02:38:16
deposit
USD
3,070.81
2
Saturday
1
1
checkout
checkout
0
0.33
2024-05-22 09:12:33
withdrawal
NZD
3,267.38
9
Wednesday
0
0
revolut_pay
revolut_pay
1
454.8
2023-05-26 22:12:18
deposit
EUR
35.64
22
Friday
0
0
paypal
paypal
0
0.09
2025-11-05 04:36:31
deposit
SGD
10.24
4
Wednesday
0
0
paypal
paypal
0
2.98
2025-02-23 09:44:38
deposit
EUR
5,393.08
9
Sunday
1
0
worldpay
worldpay
0
0.17
2023-08-31 09:56:59
deposit
USD
12.14
9
Thursday
0
0
revolut_pay
revolut_pay
1
0.84
2025-01-23 12:01:05
deposit
CAD
149.99
12
Thursday
0
0
paypal
paypal
1
0.08
2023-02-01 11:43:17
deposit
JPY
1,481.72
11
Wednesday
0
0
worldpay
worldpay
1
2.6
2025-03-22 05:04:44
deposit
EUR
3,236.84
5
Saturday
1
0
adyen
adyen
0
0.04
2024-04-12 13:38:37
deposit
AUD
60.11
13
Friday
0
0
worldpay
worldpay
1
0.68
2026-01-11 01:40:42
withdrawal
GBP
2,158.54
1
Sunday
1
0
revolut_pay
revolut_pay
0
1.35
2025-10-12 20:52:54
deposit
USD
912
20
Sunday
1
0
square
square
0
0.13
2022-06-25 18:03:03
deposit
NZD
1,637.49
18
Saturday
1
0
wise
wise
0
3.94
2022-10-16 18:26:57
withdrawal
NZD
10.34
18
Sunday
1
1
worldpay
worldpay
0
17.29
2022-06-10 13:29:04
deposit
NZD
5,332.56
13
Friday
0
0
worldpay
worldpay
1
1.26
2025-07-17 09:16:30
deposit
NZD
7,793.54
9
Thursday
0
0
bank_transfer
bank_transfer
1
26.25
2023-03-01 11:18:17
deposit
GBP
45.55
11
Wednesday
0
0
checkout
checkout
1
0.06
2022-11-16 01:34:04
withdrawal
GBP
5,004.82
1
Wednesday
0
0
checkout
checkout
0
60.44
2026-06-01 17:56:52
withdrawal
GBP
4,966.39
17
Monday
0
0
adyen
adyen
0
25.93
2026-03-01 00:52:45
deposit
AUD
1,442.43
0
Sunday
1
1
worldpay
worldpay
0
0.21
2023-12-01 04:42:39
deposit
CAD
8,659.03
4
Friday
0
0
paypal
paypal
0
1.07
2026-03-10 09:22:41
deposit
CAD
1,905.99
9
Tuesday
0
0
revolut_pay
revolut_pay
1
0.5
2025-09-10 14:58:58
deposit
JPY
22.39
14
Wednesday
0
0
paypal
paypal
1
0.03
2025-12-27 07:54:22
deposit
USD
11.11
7
Saturday
1
0
checkout
checkout
0
0.34
2024-07-16 08:42:52
withdrawal
NZD
14.48
8
Tuesday
0
0
bank_transfer
bank_transfer
0
640.81
2023-04-14 19:39:25
deposit
GBP
7,829.96
19
Friday
0
0
checkout
checkout
0
0.36
2024-06-05 17:22:53
deposit
USD
12.99
17
Wednesday
0
0
worldpay
worldpay
0
0.47
2024-09-22 05:28:43
withdrawal
USD
946.57
5
Sunday
1
0
paypal
paypal
0
13.78
2026-02-25 19:34:07
withdrawal
JPY
5,974.64
19
Wednesday
0
0
revolut_pay
revolut_pay
0
2.78
2024-09-10 08:26:16
withdrawal
GBP
29.07
8
Tuesday
0
0
checkout
checkout
0
4.34
2022-02-25 14:09:35
withdrawal
NZD
871.17
14
Friday
0
0
revolut_pay
revolut_pay
1
30.42
2026-06-03 14:14:49
deposit
EUR
4,757.34
14
Wednesday
0
0
adyen
adyen
1
0.06
2023-05-01 13:25:08
deposit
EUR
85.54
13
Monday
0
0
square
square
1
0.03
2022-05-10 03:50:29
withdrawal
AUD
1,774.29
3
Tuesday
0
0
adyen
adyen
0
10.45
2024-09-21 16:17:54
deposit
SGD
63.37
16
Saturday
1
0
adyen
adyen
0
0.2
2024-10-24 01:00:34
deposit
USD
7,102.78
1
Thursday
0
0
stripe
stripe
0
0.85
2023-07-19 11:40:58
deposit
JPY
836.43
11
Wednesday
0
1
checkout
checkout
1
0.21
2025-02-13 05:16:34
deposit
SGD
498.75
5
Thursday
0
0
wise
wise
0
1.52
2022-10-05 16:45:37
deposit
EUR
296.86
16
Wednesday
0
0
revolut_pay
revolut_pay
1
0.06
2023-04-06 20:29:34
withdrawal
NZD
401.03
20
Thursday
0
0
wise
wise
0
10.02
2024-10-25 17:30:17
deposit
JPY
5,863.46
17
Friday
0
0
revolut_pay
revolut_pay
0
0.56
2022-06-07 10:40:10
deposit
JPY
16.54
10
Tuesday
0
0
adyen
adyen
1
0.05
2024-04-30 23:56:24
deposit
USD
7,185.95
23
Tuesday
0
0
paypal
paypal
0
0.01
2024-05-01 15:37:37
deposit
SGD
8,805.93
15
Wednesday
0
0
checkout
checkout
1
0.06
2025-04-26 15:04:36
deposit
AUD
5,588.8
15
Saturday
1
0
worldpay
worldpay
0
0.28
2025-05-28 10:22:43
deposit
GBP
113.55
10
Wednesday
0
0
checkout
checkout
1
0.54
2025-12-05 09:10:38
deposit
AUD
24.2
9
Friday
0
0
revolut_pay
revolut_pay
1
0.13
2025-09-08 16:51:06
deposit
CAD
195.08
16
Monday
0
0
worldpay
worldpay
1
4.98
2023-01-18 20:15:31
deposit
JPY
154.31
20
Wednesday
0
0
square
square
0
0.13
2024-06-29 22:16:02
deposit
SGD
412.01
22
Saturday
1
1
paypal
paypal
0
0.09
2023-12-17 12:59:05
withdrawal
JPY
83.04
12
Sunday
1
0
revolut_pay
revolut_pay
0
23.18
2022-10-18 19:21:32
deposit
JPY
4,211.8
19
Tuesday
0
0
bank_transfer
bank_transfer
0
227.31
2025-07-08 13:49:54
deposit
AUD
2,440.87
13
Tuesday
0
0
bank_transfer
bank_transfer
1
316.22
2025-07-31 00:30:17
withdrawal
NZD
53.91
0
Thursday
0
0
paypal
paypal
0
7.4
2026-03-31 13:32:11
withdrawal
SGD
74.46
13
Tuesday
0
0
wise
wise
1
9.85
2025-12-22 11:36:14
deposit
GBP
282.19
11
Monday
0
0
worldpay
worldpay
1
1.96
2026-01-12 00:25:45
deposit
EUR
6,138.35
0
Monday
0
0
worldpay
worldpay
0
0.06
2024-03-08 22:15:43
deposit
AUD
121.74
22
Friday
0
0
stripe
stripe
0
0.01
2024-10-20 16:16:58
deposit
JPY
304.06
16
Sunday
1
1
stripe
stripe
0
0.03
2022-09-08 23:49:13
deposit
CAD
50.72
23
Thursday
0
0
worldpay
worldpay
0
0.05
2022-06-28 23:48:41
withdrawal
AUD
6,008.97
23
Tuesday
0
0
adyen
adyen
0
25.52
2023-08-16 06:57:53
deposit
GBP
6,640.32
6
Wednesday
0
1
bank_transfer
bank_transfer
0
140.87
End of preview.

PayMind Reference Dataset

Synthetic/reference payment-routing data for PayMind, an open-source payment route intelligence engine.

This dataset is designed to demonstrate PayMind's training, evaluation, and routing workflow across route selection, transaction reliability, and expected settlement time.

Important: This dataset contains synthetic/reference data only. It does not contain real customers, real transactions, payment credentials, personally identifiable information, or production payment-provider performance data.

Dataset Files

The dataset contains three primary CSV files:

payment_method.csv

Reference data for training the payment-method candidate model.

The model learns which payment routes are most relevant for a given transaction context.

success.csv

Reference data for training the transaction-success model.

The model estimates the probability of a transaction succeeding for an eligible payment route.

arrival.csv

Reference data for training the settlement model.

The model estimates expected transaction arrival/settlement times, including typical and more conservative settlement estimates.

Tasks

PayMind uses the dataset across multiple tabular machine-learning tasks:

  • Payment route selection — identify relevant payment methods for a transaction.
  • Transaction reliability — estimate the probability of successful processing.
  • Settlement estimation — estimate expected transaction arrival time.
  • Route intelligence — combine model outputs with eligibility rules and estimated fees to rank available payment routes.

Intended Use

This dataset is intended for:

  • Demonstrating the PayMind architecture
  • Training the PayMind reference models
  • Testing the PayMind training pipeline
  • Software development and integration testing
  • Machine-learning experimentation
  • Educational and research use

Users deploying PayMind in a real payment environment should train models using appropriately governed data from their own environment.

Data Source

The data provided in this repository is synthetic/reference data created for the PayMind open-source project.

It should not be interpreted as observed behaviour of any real payment provider, financial institution, customer, or payment network.

Privacy

The reference dataset is designed to contain no real:

  • Customer identities
  • Names or email addresses
  • Account or card details
  • Payment credentials
  • Authentication tokens or API keys
  • Production transaction records
  • Personally identifiable information (PII)
  • Proprietary payment-provider performance data

Reference Models

The PayMind reference models are trained using synthetic/reference data and are intended to demonstrate the architecture rather than provide production payment-routing benchmarks.

Models:
https://huggingface.co/navk8690/paymind-reference-models

Live Demo

Try PayMind through the interactive Hugging Face Space:

https://huggingface.co/spaces/navk8690/paymind

The demo evaluates transaction context, eligible payment routes, predicted reliability, settlement expectations, and estimated cost to produce a ranked route recommendation.

Source Code

PayMind is open source.

GitHub:
https://github.com/navjotk8690/paymind

The repository includes the SDK, API, model implementations, training pipeline, data contracts, reference configuration, tests, and Gradio demo.

Training

The PayMind project provides a training pipeline for rebuilding the reference models or training models using your own compatible datasets.

The expected datasets are:

payment_method.csv
success.csv
arrival.csv

Refer to the PayMind repository documentation for the exact schemas and training instructions.

Limitations

This dataset is provided as a reference implementation dataset.

Results obtained from models trained on this data:

  • Do not represent actual payment-provider performance
  • Should not be treated as production routing benchmarks
  • Do not guarantee transaction success or settlement time
  • Should not be used as a substitute for production-specific model validation
  • May not reflect the distributions, constraints, or behaviour of a real payment environment

Production users should validate their own data, models, eligibility rules, fee configuration, and ranking strategy before deployment.

License

This dataset is released under the GNU General Public License v3.0 (GPL-3.0) as part of the PayMind open-source project.

See the repository license for full terms.

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