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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 2 new columns ({'face_value_million_pkr', 'coupon_rate_pct'}) and 11 missing columns ({'offered_competitive_realized_value_million_pkr', 'accepted_competitive_face_value_million_pkr', 'accepted_non_competitive_realized_value_million_pkr', 'auction_date', 'auction_type', 'accepted_competitive_realized_value_million_pkr', 'accepted_non_competitive_face_value_million_pkr', 'settlement_date', 'target_amount_million_pkr', 'offered_competitive_face_value_million_pkr', 'short_sale_accommodated_face_value_million_pkr'}).
This happened while the csv dataset builder was generating data using
hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions/data/processed/pib_outstanding_securities.csv (at revision e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02), ['hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/pib_auction_results.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/pib_outstanding_securities.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/pib_weighted_average_yields.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/tbill_auction_results.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/tbill_weighted_average_yields.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data_dictionary.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
isin: string
tenor: string
issue_date: string
maturity_date: string
coupon_rate_pct: double
face_value_million_pkr: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1018
to
{'auction_type': Value('string'), 'isin': Value('string'), 'tenor': Value('string'), 'issue_date': Value('string'), 'maturity_date': Value('string'), 'auction_date': Value('string'), 'settlement_date': Value('string'), 'target_amount_million_pkr': Value('int64'), 'offered_competitive_face_value_million_pkr': Value('float64'), 'offered_competitive_realized_value_million_pkr': Value('float64'), 'accepted_competitive_face_value_million_pkr': Value('float64'), 'accepted_competitive_realized_value_million_pkr': Value('float64'), 'accepted_non_competitive_face_value_million_pkr': Value('float64'), 'accepted_non_competitive_realized_value_million_pkr': Value('float64'), 'short_sale_accommodated_face_value_million_pkr': 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 2 new columns ({'face_value_million_pkr', 'coupon_rate_pct'}) and 11 missing columns ({'offered_competitive_realized_value_million_pkr', 'accepted_competitive_face_value_million_pkr', 'accepted_non_competitive_realized_value_million_pkr', 'auction_date', 'auction_type', 'accepted_competitive_realized_value_million_pkr', 'accepted_non_competitive_face_value_million_pkr', 'settlement_date', 'target_amount_million_pkr', 'offered_competitive_face_value_million_pkr', 'short_sale_accommodated_face_value_million_pkr'}).
This happened while the csv dataset builder was generating data using
hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions/data/processed/pib_outstanding_securities.csv (at revision e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02), ['hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/pib_auction_results.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/pib_outstanding_securities.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/pib_weighted_average_yields.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/tbill_auction_results.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data/processed/tbill_weighted_average_yields.csv', 'hf://datasets/opendoc-pakistan/pakistan_government_securities_auctions@e9f88faed4e0b7f260d5e6f24e319b8c80bc6e02/data_dictionary.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.
auction_type string | isin string | tenor string | issue_date string | maturity_date string | auction_date string | settlement_date string | target_amount_million_pkr int64 | offered_competitive_face_value_million_pkr float64 | offered_competitive_realized_value_million_pkr float64 | accepted_competitive_face_value_million_pkr float64 | accepted_competitive_realized_value_million_pkr float64 | accepted_non_competitive_face_value_million_pkr float64 | accepted_non_competitive_realized_value_million_pkr float64 | short_sale_accommodated_face_value_million_pkr float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Reopen | PK03P1502273 | 03-Year | 2024-02-15 | 2027-02-15 | 2024-07-09 | 2024-07-10 | 75,000 | 114,884 | 114,638.464 | 58,484 | 58,788.686 | 4,727.5 | 4,752.110638 | 0 |
Reopen | PK05P1701292 | 05-Year | 2024-01-17 | 2029-01-17 | 2024-07-09 | 2024-07-10 | 60,000 | 53,500 | 53,411.329 | 17,250 | 17,640.468 | 605 | 618.694594 | 0 |
Reopen | PK10P1011338 | 10-Year | 2023-11-10 | 2033-11-10 | 2024-07-09 | 2024-07-10 | 55,000 | 37,250 | 35,429.061 | 0 | 0 | 0 | 0 | 0 |
Reopen | PK03P1502273 | 03-Year | 2024-02-15 | 2027-02-15 | 2024-07-31 | 2024-08-01 | 50,000 | 254,301.4 | 258,860.002 | 100,025 | 102,110.889 | 6,963.9 | 7,109.106957 | 0 |
Reopen | PK05P1701292 | 05-Year | 2024-01-17 | 2029-01-17 | 2024-07-31 | 2024-08-01 | 40,000 | 79,055.8 | 75,928.546 | 32,381 | 31,255.211 | 1,316.1 | 1,270.342522 | 0 |
Reopen | PK10P1011338 | 10-Year | 2023-11-10 | 2033-11-10 | 2024-07-31 | 2024-08-01 | 35,000 | 26,750 | 26,208.352 | 0 | 0 | 0 | 0 | 0 |
Fresh | PK02Z2009261 | 02-Year | 2024-09-20 | 2026-09-20 | 2024-09-19 | 2024-09-20 | 75,000 | 260,501.2 | 197,150.893 | 10,000 | 7,697.38 | 24,060.4 | 18,520.20418 | 9,250 |
Fresh | PK03P2009278 | 03-Year | 2024-09-20 | 2027-09-20 | 2024-09-19 | 2024-09-20 | 50,000 | 155,957 | 155,766.306 | 1,000 | 1,026.679 | 15,875.2 | 16,298.73446 | 9,500 |
Fresh | PK05P2009299 | 05-Year | 2024-09-20 | 2029-09-20 | 2024-09-19 | 2024-09-20 | 50,000 | 183,525.5 | 184,617.487 | 1,100 | 1,123.503 | 15,466.4 | 15,796.8551 | 9,450 |
Fresh | PK10P2009349 | 10-Year | 2024-09-20 | 2034-09-20 | 2024-09-19 | 2024-09-20 | 25,000 | 30,881 | 29,846.57 | 12,381 | 12,285.407 | 3,375 | 3,348.837 | 1,250 |
Reopen | PK02Z2009261 | 02-Year | 2024-09-20 | 2026-09-20 | 2024-10-17 | 2024-10-18 | 50,000 | 139,000 | 108,761.261 | 22,000 | 17,322.429 | 5,261.5 | 4,142.815655 | 5,750 |
Reopen | PK03P2009278 | 03-Year | 2024-09-20 | 2027-09-20 | 2024-10-17 | 2024-10-18 | 50,000 | 107,555 | 111,211.834 | 7,955 | 8,337.322 | 16,898.2 | 17,710.32292 | 5,550 |
Reopen | PK05P2009299 | 05-Year | 2024-09-20 | 2029-09-20 | 2024-10-17 | 2024-10-18 | 50,000 | 313,061.5 | 327,154.845 | 55,150 | 58,220.082 | 7,632.1 | 8,056.885356 | 5,250 |
Reopen | PK10P2009349 | 10-Year | 2024-09-20 | 2034-09-20 | 2024-10-17 | 2024-10-18 | 50,000 | 98,466.5 | 98,895.126 | 61,000 | 61,950.983 | 4,940 | 5,016.926908 | 0 |
Reopen | PK02Z2009261 | 02-Year | 2024-09-20 | 2026-09-20 | 2024-11-20 | 2024-11-21 | 100,000 | 385,120 | 307,029.112 | 132,670 | 106,090.6196 | 10,837.4 | 8,666.213609 | 6,000 |
Reopen | PK03P2009278 | 03-Year | 2024-09-20 | 2027-09-20 | 2024-11-20 | 2024-11-21 | 50,000 | 44,700 | 46,814.631 | 9,900 | 10,502.4101 | 7,757 | 8,228.989408 | 0 |
Reopen | PK05P2009299 | 05-Year | 2024-09-20 | 2029-09-20 | 2024-11-20 | 2024-11-21 | 75,000 | 392,750 | 418,930.485 | 145,800 | 156,108.6689 | 7,998.6 | 8,564.116222 | 9,700 |
Reopen | PK10P2009349 | 10-Year | 2024-09-20 | 2034-09-20 | 2024-11-20 | 2024-11-21 | 75,000 | 69,944.2 | 70,348.47 | 32,231.4 | 33,222.2351 | 3,057.2 | 3,151.188091 | 2,000 |
Reopen | PK02Z2009261 | 02-Year | 2024-09-20 | 2026-09-20 | 2024-12-18 | 2024-12-19 | 150,000 | 297,750.7 | 241,284.604 | 38,450 | 31,292.3115 | 20,194.2 | 16,434.90831 | 0 |
Reopen | PK03P2009278 | 03-Year | 2024-09-20 | 2027-09-20 | 2024-12-18 | 2024-12-19 | 50,000 | 66,980 | 71,209.134 | 26,030 | 27,864.9377 | 15,197.9 | 16,269.07276 | 0 |
Reopen | PK05P2009299 | 05-Year | 2024-09-20 | 2029-09-20 | 2024-12-18 | 2024-12-19 | 100,000 | 340,000 | 367,683.079 | 181,400 | 196,896.0528 | 3,781.1 | 4,104.095287 | 0 |
Reopen | PK10P2009349 | 10-Year | 2024-09-20 | 2034-09-20 | 2024-12-18 | 2024-12-19 | 50,000 | 119,625 | 124,972.312 | 95,875 | 100,988.2939 | 900 | 947.978498 | 0 |
Fresh | PK02Z1601274 | 02-Year | 2025-01-16 | 2027-01-16 | 2025-01-15 | 2025-01-16 | 100,000 | 716,072 | 569,903.54 | 143,125 | 114,274.3081 | 25,848 | 20,637.612 | 20,750 |
Fresh | PK03P1601281 | 03-Year | 2025-01-16 | 2028-01-16 | 2025-01-15 | 2025-01-16 | 50,000 | 400,504.5 | 398,723.347 | 75,000 | 75,203.325 | 12,980 | 13,015.202 | 5,750 |
Fresh | PK05P1601302 | 05-Year | 2025-01-16 | 2030-01-16 | 2025-01-15 | 2025-01-16 | 100,000 | 378,420 | 371,959.005 | 107,020 | 105,572.1128 | 5,526.1 | 5,451.332 | 7,000 |
Fresh | PK10P1601351 | 10-Year | 2025-01-16 | 2035-01-16 | 2025-01-15 | 2025-01-16 | 50,000 | 56,212.5 | 52,573.594 | 13,712.5 | 13,135.6088 | 1,500 | 1,436.867 | 2,500 |
Fresh | PK15P1601400 | 15-Year | 2025-01-16 | 2040-01-16 | 2025-01-15 | 2025-01-16 | 50,000 | 16,500 | 14,892.028 | null | null | null | 0 | 0 |
Reopen | PK02Z1601274 | 02-Year | 2025-01-16 | 2027-01-16 | 2025-02-12 | 2025-02-13 | 100,000 | 233,540.7 | 188,186.6492 | 51,250 | 41,434.08675 | 31,736.6 | 25,658.089 | 12,250 |
Reopen | PK03P1601281 | 03-Year | 2025-01-16 | 2028-01-16 | 2025-02-12 | 2025-02-13 | 50,000 | 44,550 | 44,427.8708 | 5,550 | 5,587.8868 | 2,073 | 2,106.383 | 0 |
Reopen | PK05P1601302 | 05-Year | 2025-01-16 | 2030-01-16 | 2025-02-12 | 2025-02-13 | 100,000 | 392,550 | 386,738.8693 | 223,250 | 220,292.79 | 10,172 | 10,131.676 | 9,000 |
Reopen | PK10P1601351 | 10-Year | 2025-01-16 | 2035-01-16 | 2025-02-12 | 2025-02-13 | 50,000 | 175,030 | 166,928.2007 | 128,530 | 123,818.8637 | 1,550 | 1,507.567 | 1,000 |
Reopen | PK15P1601400 | 15-Year | 2025-01-16 | 2040-01-16 | 2025-02-12 | 2025-02-13 | 50,000 | 65,000 | 60,975.105 | null | null | null | null | 0 |
Reopen | PK02Z1601274 | 02-Year | 2025-01-16 | 2027-01-16 | 2025-03-12 | 2025-03-13 | 100,000 | 115,500 | 93,318.8255 | null | null | 0 | 0 | 0 |
Reopen | PK03P1601281 | 03-Year | 2025-01-16 | 2028-01-16 | 2025-03-12 | 2025-03-13 | 50,000 | 117,505 | 116,447.0837 | null | null | 0 | 0 | 0 |
Reopen | PK05P1601302 | 05-Year | 2025-01-16 | 2030-01-16 | 2025-03-12 | 2025-03-13 | 100,000 | 149,800 | 145,668.7876 | 500 | 493.39925 | 5,520 | 5,549.596 | 0 |
Reopen | PK10P1601351 | 10-Year | 2025-01-16 | 2035-01-16 | 2025-03-12 | 2025-03-13 | 50,000 | 78,502 | 72,974.12927 | 9,002 | 8,619.236267 | 800 | 780.834 | 0 |
Reopen | PK15P1601400 | 15-Year | 2025-01-16 | 2040-01-16 | 2025-03-12 | 2025-03-13 | 50,000 | 15,000 | 13,883.805 | null | null | 0 | 0 | 0 |
Reopen | PK02Z1601274 | 02-Year | 2025-01-16 | 2027-01-16 | 2025-04-09 | 2025-04-10 | 100,000 | 120,250 | 98,267.2 | 37,000 | 30,325.1915 | 4,615 | 3,782.449 | 0 |
Reopen | PK03P1601281 | 03-Year | 2025-01-16 | 2028-01-16 | 2025-04-09 | 2025-04-10 | 50,000 | 165,840 | 169,820.526 | 38,000 | 39,164.0195 | 582.1 | 599.931 | 0 |
Reopen | PK05P1601302 | 05-Year | 2025-01-16 | 2030-01-16 | 2025-04-09 | 2025-04-10 | 100,000 | 306,430 | 310,154.677 | 93,180 | 94,795.9766 | 5,368 | 5,461.088 | 0 |
Reopen | PK10P1601351 | 10-Year | 2025-01-16 | 2035-01-16 | 2025-04-09 | 2025-04-10 | 50,000 | 287,623 | 281,914.199 | 247,623 | 243,754.8448 | 763 | 751.081 | 0 |
Reopen | PK15P1601400 | 15-Year | 2025-01-16 | 2040-01-16 | 2025-04-09 | 2025-04-10 | 50,000 | 7,500 | 7,112.437 | null | null | null | null | 0 |
Reopen | PK02Z1601274 | 02-Year | 2025-01-16 | 2027-01-16 | 2025-05-07 | 2025-05-08 | 100,000 | 157,000 | 130,062.4785 | 104,000 | 86,307.811 | 1,591.4 | 1,320.673 | 0 |
Reopen | PK03P1601281 | 03-Year | 2025-01-16 | 2028-01-16 | 2025-05-07 | 2025-05-08 | 50,000 | 279,000 | 280,320.4225 | 71,000 | 71,527.806 | 762.7 | 796.687 | 0 |
Reopen | PK05P1601302 | 05-Year | 2025-01-16 | 2030-01-16 | 2025-05-07 | 2025-05-08 | 50,000 | 203,300 | 201,472.6635 | 66,300 | 66,014.5715 | 2,845 | 2,938.376 | 0 |
Reopen | PK10P1601351 | 10-Year | 2025-01-16 | 2035-01-16 | 2025-05-07 | 2025-05-08 | 50,000 | 185,968 | 178,104.0142 | 53,000 | 51,415.559 | 20 | 20.144 | 0 |
Reopen | PK15P1601400 | 15-Year | 2025-01-16 | 2040-01-16 | 2025-05-07 | 2025-05-08 | 50,000 | 30,000 | 28,061.97 | null | null | null | null | null |
Reopen | PK02Z1601274 | 02-Year | 2025-01-16 | 2027-01-16 | 2025-06-18 | 2025-06-19 | 100,000 | 276,030.6 | 232,395.1283 | 59,000 | 49,787.571 | 4,135 | 3,489 | 0 |
Reopen | PK03P1601281 | 03-Year | 2025-01-16 | 2028-01-16 | 2025-06-18 | 2025-06-19 | 50,000 | 188,000 | 189,654.867 | 35,000 | 37,256.2053 | 2,013 | 2,142.763 | 0 |
Reopen | PK05P1601302 | 05-Year | 2025-01-16 | 2030-01-16 | 2025-06-18 | 2025-06-19 | 50,000 | 375,489 | 378,231.251 | 123,209 | 130,783.9802 | 7,224 | 7,668.122 | 0 |
Reopen | PK10P1601351 | 10-Year | 2025-01-16 | 2035-01-16 | 2025-06-18 | 2025-06-19 | 50,000 | 87,065.1 | 83,805.70799 | 36,588.1 | 37,660.8384 | 1,609 | 1,656.151 | 0 |
Fresh | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-06-18 | 2025-06-19 | 50,000 | 290,500 | 48,276.6425 | 288,000 | 47,921.76 | null | null | null |
Fresh | PK02Z1707279 | 02-Year | 2025-07-17 | 2027-07-17 | 2025-07-16 | 2025-07-17 | 100,000 | 179,750 | 145,841.0462 | 13,300 | 10,829.24275 | 6,967.9 | 5,673 | 19,000 |
Fresh | PK03P1707286 | 03-Year | 2025-07-17 | 2028-07-17 | 2025-07-16 | 2025-07-17 | 50,000 | 134,104.6 | 131,568.8538 | 19,354.6 | 19,110.96555 | 15,910.6 | 15,710 | 6,500 |
Fresh | PK05P1707307 | 05-Year | 2025-07-17 | 2030-07-17 | 2025-07-16 | 2025-07-17 | 50,000 | 337,950 | 333,608.8953 | 247,000 | 244,303.158 | 7,840 | 7,754 | 0 |
Fresh | PK10P1707356 | 10-Year | 2025-07-17 | 2035-07-17 | 2025-07-16 | 2025-07-17 | 50,000 | 339,122.5 | 321,163.5826 | 159.3 | 152.956515 | 1,290 | 1,239 | 5,000 |
Reopen | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-07-16 | 2025-07-17 | 50,000 | 704,920 | 118,317.7884 | null | 0 | 0 | 0 | 0 |
Reopen | PK02Z1707279 | 02-Year | 2025-07-17 | 2027-07-17 | 2025-08-01 | 2025-08-04 | 100,000 | 150,250 | 122,140.3983 | 20,250 | 16,504.58975 | 2,290 | 1,866 | 5,500 |
Reopen | PK03P1707286 | 03-Year | 2025-07-17 | 2028-07-17 | 2025-08-01 | 2025-08-04 | 50,000 | 273,779 | 268,972.28 | 42,279 | 41,872.7957 | 1,811.7 | 1,794.295 | 2,750 |
Reopen | PK05P1707307 | 05-Year | 2025-07-17 | 2030-07-17 | 2025-08-01 | 2025-08-04 | 50,000 | 234,981 | 231,874.491 | 39,881 | 39,525.2236 | 3,493.8 | 3,462.63 | 0 |
Reopen | PK10P1707356 | 10-Year | 2025-07-17 | 2035-07-17 | 2025-08-01 | 2025-08-04 | 50,000 | 342,607 | 330,262.667 | 214,030 | 207,347.9677 | 1,560.3 | 1,511.589 | 5,000 |
Reopen | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-08-01 | 2025-08-04 | 50,000 | 1,032,500 | 180,097.54 | 300,000 | 52,424.5 | 87.5 | 15.291 | 0 |
Reopen | PK02Z1707279 | 02-Year | 2025-07-17 | 2027-07-17 | 2025-09-05 | 2025-09-08 | 100,000 | 91,302 | 74,904.81189 | 39,450 | 32,422.53055 | 3,839 | 3,155 | 0 |
Reopen | PK03P1707286 | 03-Year | 2025-07-17 | 2028-07-17 | 2025-09-05 | 2025-09-08 | 50,000 | 100,434 | 99,961.505 | 5,584 | 5,585.1917 | 2,561.4 | 2,561.944 | 0 |
Reopen | PK05P1707307 | 05-Year | 2025-07-17 | 2030-07-17 | 2025-09-05 | 2025-09-08 | 100,000 | 236,580 | 236,007.542 | 108,850 | 108,905.3074 | 6,143.6 | 6,146.717 | 0 |
Reopen | PK10P1707356 | 10-Year | 2025-07-17 | 2035-07-17 | 2025-09-05 | 2025-09-08 | 100,000 | 356,792.2 | 349,903.732 | 205,000 | 202,426.1375 | 2,855.3 | 2,819.442 | 0 |
Reopen | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-09-05 | 2025-09-08 | 50,000 | 497,500 | 88,129.8975 | 280,000 | 49,896.56 | 0 | 0 | 0 |
Reopen | PK02Z1707279 | 02-Year | 2025-07-17 | 2027-07-17 | 2025-10-14 | 2025-10-15 | 100,000 | 164,100 | 135,750.38 | 12,080 | 10,009.1758 | 5,473 | 4,534.786 | 0 |
Reopen | PK03P1707286 | 03-Year | 2025-07-17 | 2028-07-17 | 2025-10-14 | 2025-10-15 | 50,000 | 111,500 | 111,919.903 | 11,500 | 11,566.674 | 2,358.5 | 2,372.173 | 0 |
Reopen | PK05P1707307 | 05-Year | 2025-07-17 | 2030-07-17 | 2025-10-14 | 2025-10-15 | 100,000 | 220,450.5 | 221,233.877 | 5,938.4 | 5,991.1582 | 6,974.1 | 7,036.059 | 0 |
Reopen | PK10P1707356 | 10-Year | 2025-07-17 | 2035-07-17 | 2025-10-14 | 2025-10-15 | 150,000 | 522,799 | 522,533.251 | 333,402 | 334,882.3955 | 4,000 | 4,017.752 | 0 |
Reopen | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-10-14 | 2025-10-15 | 50,000 | 517,500 | 93,392.545 | 125,000 | 22,765.455 | 6 | 1.092736 | 0 |
Reopen | PK02Z1707279 | 02-Year | 2025-07-17 | 2027-07-17 | 2025-11-05 | 2025-11-06 | 50,000 | 160,100 | 133,117.965 | 59,600 | 49,607.8575 | 1,675.1 | 1,394.263794 | 2,500 |
Reopen | PK03P1707286 | 03-Year | 2025-07-17 | 2028-07-17 | 2025-11-05 | 2025-11-06 | 100,000 | 319,650 | 321,361.171 | 137,150 | 138,579.5174 | 2,688 | 2,716.017082 | 5,000 |
Reopen | PK05P1707307 | 05-Year | 2025-07-17 | 2030-07-17 | 2025-11-05 | 2025-11-06 | 100,000 | 179,350 | 181,062.171 | 90,700 | 91,841.7558 | 6,775 | 6,860.285508 | 0 |
Reopen | PK10P1707356 | 10-Year | 2025-07-17 | 2035-07-17 | 2025-11-05 | 2025-11-06 | 100,000 | 239,973.8 | 239,810.142 | 144,473.8 | 145,945.8869 | 2,080 | 2,101.193744 | 0 |
Reopen | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-11-05 | 2025-11-06 | 50,000 | 539,500 | 98,486.3345 | 340,000 | 62,796.3 | 10.6 | 1.957767 | 0 |
Reopen | PK02Z1707279 | 02-Year | 2025-07-17 | 2027-07-17 | 2025-12-17 | 2025-12-18 | 75,000 | 684,553 | 581,615.32 | 100,000 | 85,112.85 | 7,370 | 6,272.817045 | 9,500 |
Reopen | PK03P1707286 | 03-Year | 2025-07-17 | 2028-07-17 | 2025-12-17 | 2025-12-18 | 100,000 | 499,100 | 515,677.94 | 75,000 | 77,725.966 | 9,340.1 | 9,679.577267 | null |
Reopen | PK05P1707307 | 05-Year | 2025-07-17 | 2030-07-17 | 2025-12-17 | 2025-12-18 | 75,000 | 258,360 | 267,834.448 | 94,560 | 98,435.529 | 8,800 | 9,160.666827 | null |
Reopen | PK10P1707356 | 10-Year | 2025-07-17 | 2035-07-17 | 2025-12-17 | 2025-12-18 | 100,000 | 452,570 | 466,935.111 | 101,050 | 104,944.516 | 3,147.1 | 3,268.39076 | null |
Reopen | PK15Z1906402 | 15-Year | 2025-06-19 | 2040-06-19 | 2025-12-17 | 2025-12-18 | 50,000 | 593,705 | 112,058.506 | 36,200 | 7,002.7271 | null | null | null |
Fresh | PK02Z1501284 | 02-Year | 2026-01-15 | 2028-01-15 | 2026-01-14 | 2026-01-15 | 100,000 | 313,750 | 257,980.578 | 93,000 | 76,603.414 | 8,736.7 | 7,196.358633 | 12,000 |
Fresh | PK03P1501291 | 03-Year | 2026-01-15 | 2029-01-15 | 2026-01-14 | 2026-01-15 | 100,000 | 499,650 | 499,821.624 | 125,000 | 125,407.185 | 17,175.7 | 17,231.64125 | 14,420 |
Fresh | PK05P1501312 | 05-Year | 2026-01-15 | 2031-01-15 | 2026-01-14 | 2026-01-15 | 100,000 | 312,510 | 311,151.268 | 106,000 | 106,154.5483 | 11,065 | 11,081.09958 | 16,000 |
Fresh | PK10P1501361 | 10-Year | 2026-01-15 | 2036-01-15 | 2026-01-14 | 2026-01-15 | 100,000 | 271,000 | 266,753.452 | 126,000 | 126,092.85 | 4,925 | 4,928.619875 | 12,000 |
Fresh | PK15Z1501419 | 15-Year | 2026-01-15 | 2041-01-15 | 2026-01-14 | 2026-01-15 | 50,000 | 666,501 | 122,495.3514 | null | 0 | null | null | null |
Reopen | PK02Z1501284 | 02-Year | 2026-01-15 | 2028-01-15 | 2026-02-06 | 2026-02-09 | 100,000 | 140,000 | 115,524.4 | 32,000 | 26,470.383 | 5,258 | 4,349.414807 | 11,000 |
Reopen | PK03P1501291 | 03-Year | 2026-01-15 | 2029-01-15 | 2026-02-06 | 2026-02-09 | 100,000 | 295,975 | 297,539.249 | 150,000 | 151,188.7244 | 10,646.2 | 10,730.56932 | 9,650 |
Reopen | PK05P1501312 | 05-Year | 2026-01-15 | 2031-01-15 | 2026-02-06 | 2026-02-09 | 100,000 | 364,350 | 362,426.164 | 207,600 | 207,467.1979 | 7,170 | 7,165.413338 | 3,000 |
Reopen | PK10P1501361 | 10-Year | 2026-01-15 | 2036-01-15 | 2026-02-06 | 2026-02-09 | 100,000 | 132,750 | 130,383.711 | 58,750 | 58,578.5752 | 1,900 | 1,894.456049 | 1,000 |
Reopen | PK15Z1501419 | 15-Year | 2026-01-15 | 2041-01-15 | 2026-02-06 | 2026-02-09 | 50,000 | 811,500 | 150,995.117 | 53,000 | 10,524.303 | null | null | null |
Reopen | PK02Z1501284 | 02-Year | 2026-01-15 | 2028-01-15 | 2026-03-26 | 2026-03-27 | 100,000 | 91,000 | 73,246.649 | 38,000 | 30,763.22 | 4,080 | 3,303 | null |
Reopen | PK03P1501291 | 03-Year | 2026-01-15 | 2029-01-15 | 2026-03-26 | 2026-03-27 | 100,000 | 86,250 | 83,288.715 | 60,750 | 59,018.5 | 4,763.9 | 4,628.079263 | null |
Reopen | PK05P1501312 | 05-Year | 2026-01-15 | 2031-01-15 | 2026-03-26 | 2026-03-27 | 50,000 | 105,700 | 99,082.135 | 29,700 | 28,264.7716 | 3,940 | 3,750 | null |
Reopen | PK10P1501361 | 10-Year | 2026-01-15 | 2036-01-15 | 2026-03-26 | 2026-03-27 | 100,000 | 145,500 | 128,893.707 | null | null | null | null | null |
Reopen | PK15Z1501419 | 15-Year | 2026-01-15 | 2041-01-15 | 2026-03-26 | 2026-03-27 | 50,000 | 390,000 | 67,621.97 | 325,000 | 57,578.95 | null | null | null |
Reopen | PK02Z1501284 | 02-Year | 2026-01-15 | 2028-01-15 | 2026-04-28 | 2026-04-29 | 50,000 | 52,004 | 42,003.722 | null | null | null | null | null |
Reopen | PK03P1501291 | 03-Year | 2026-01-15 | 2029-01-15 | 2026-04-28 | 2026-04-29 | 50,000 | 54,500 | 52,720.563 | null | null | null | null | null |
Reopen | PK05P1501312 | 05-Year | 2026-01-15 | 2031-01-15 | 2026-04-28 | 2026-04-29 | 50,000 | 212,171 | 199,383.6 | null | null | null | null | null |
End of preview.
Pakistan Government Securities Auctions
Official State Bank of Pakistan auction history for Market Treasury Bills and Pakistan Investment Bonds, including detailed auction amounts, cut-off prices, weighted-average yields, and outstanding PIB securities.
Source: OpenDoc Pakistan
Pakistan Government Securities Auctions
Summary
This dataset packages official State Bank of Pakistan (SBP) auction history for Market Treasury Bills and Pakistan Investment Bonds. It includes detailed auction amounts, T-bill cut-off prices, weighted-average yields for T-bills and PIBs, and outstanding fixed-rate PIB securities.
Dataset Details
- Dataset ID:
pakistan-government-securities-auctions - Version:
0.1.0 - Category:
Economy and Finance - Tags:
finance,government-securities,treasury-bills,bonds,yields,auctions,pakistan,sbp - Language:
English - Geography:
Pakistan - Time Period:
1998 - 2026 - File Formats:
CSV - Records:
3,635 rows across 5 CSV resources - Update Frequency:
Monthly or as SBP auction files are updated - Maintainer:
OpenDoc Data Stewardship Team
Source and Provenance
- Source Name: State Bank of Pakistan (SBP), Economic Data
- Source URL: https://www.sbp.org.pk/economic-data
- Source Files:
https://www.sbp.org.pk/assets/document/tb.xlsxhttps://www.sbp.org.pk/assets/document/Pakinvestbonds.xlsx
- Source Type: Official central bank publication
- Collection Date: July 4, 2026
- Processing Pipeline: Downloaded official SBP Excel workbooks, parsed workbook XML locally, normalized old and new workbook tabs into CSV resources, converted Excel serial dates to ISO dates, removed non-numeric rejected/no-bid yield cells.
- Raw Data Availability: Public on SBP Economic Data pages.
License
- Original License: SBP public website data; explicit open redistribution license not found.
- Repository License:
LicenseRef-SBP-Public-Website - Attribution Required: Yes, cite the State Bank of Pakistan.
- Commercial Use: No explicit restriction found in the source page reviewed.
- Redistribution: No explicit restriction found in the source page reviewed; use with attribution to SBP.
- Restriction: Do not label as CC-BY or public domain unless SBP publishes explicit open-license terms.
Intended Use
Appropriate for:
- Government securities auction analysis.
- Yield-curve and money-market research.
- Fixed-income ML feature engineering.
- Backtesting macro-financial indicators at auction frequency.
Out-of-Scope Use
- Real-time trading; this is historical official auction data.
- Legal or investment advice.
- Redistribution as open data without confirming SBP terms.
Data Structure
Resources:
tbill_auction_results.csv: detailed Market Treasury Bill auction bids and accepted amounts.tbill_weighted_average_yields.csv: long-format T-bill weighted-average yields by auction and tenor.pib_auction_results.csv: detailed Pakistan Investment Bond auction bids and accepted amounts.pib_weighted_average_yields.csv: long-format PIB weighted-average yields by auction and tenor.pib_outstanding_securities.csv: outstanding fixed-rate PIB securities and face values.
Data Dictionary
See data_dictionary.csv.
Quality Report
- Quality Score: 95 / 100
- Validation Status: CSV validation passed for all resources.
- Missing Values: Yield resources have no missing values. Detailed auction resources preserve blanks where a source workbook field was not applicable, such as rejected/no-bid tenors or missing ISINs in older rows.
- Duplicate Rows: 0 duplicate rows in generated resources.
- Known Issues: PIB detailed auction workbook does not expose yield fields in the new-format sheet, so PIB weighted-average yields are provided from the old-format sheet.
Privacy and Sensitivity Review
- Privacy Level: P0 (aggregate market statistics, no personal data)
- Personal Data Present: No
- Sensitive Data Present: No
- Redactions Applied: None
Bias, Gaps, and Limitations
- SBP workbook formats changed over time; old and new formats are preserved as separate normalized resources.
- Rejected/no-bid T-bill cells are excluded from yield rows.
- The dataset reflects official auction publications, not secondary-market prices.
Example Usage
import pandas as pd
yields = pd.read_csv("data/processed/tbill_weighted_average_yields.csv")
latest = yields.sort_values("auction_date").tail(20)
print(latest[["auction_date", "tenor", "weighted_average_yield_pct"]])
Citation
State Bank of Pakistan, "Auction Result of Market Treasury Bills" and "Pakistan Investment Bonds Auction Results", curated as "Pakistan Government Securities Auctions" by OpenDoc Pakistan (OpenDoc), v0.1.0, 2026.
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