Datasets:

tharu-jwd
/

cse-market-data

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 ({'symbol', 'sector'}) and 6 missing columns ({'low', 'open', 'volume', 'close', 'date', 'high'}).

This happened while the csv dataset builder was generating data using

hf://datasets/tharu-jwd/cse-market-data/sector_mapping.csv (at revision 669594502b85772c7b7c853067afde91402e3c2a), ['hf://datasets/tharu-jwd/cse-market-data@669594502b85772c7b7c853067afde91402e3c2a/aspi.csv', 'hf://datasets/tharu-jwd/cse-market-data@669594502b85772c7b7c853067afde91402e3c2a/sector_mapping.csv', 'hf://datasets/tharu-jwd/cse-market-data@669594502b85772c7b7c853067afde91402e3c2a/stock_prices.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
              symbol: string
              sector: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 503
              to
              {'date': Value('string'), 'open': Value('float64'), 'high': Value('float64'), 'low': Value('float64'), 'close': Value('float64'), 'volume': 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 ({'symbol', 'sector'}) and 6 missing columns ({'low', 'open', 'volume', 'close', 'date', 'high'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/tharu-jwd/cse-market-data/sector_mapping.csv (at revision 669594502b85772c7b7c853067afde91402e3c2a), ['hf://datasets/tharu-jwd/cse-market-data@669594502b85772c7b7c853067afde91402e3c2a/aspi.csv', 'hf://datasets/tharu-jwd/cse-market-data@669594502b85772c7b7c853067afde91402e3c2a/sector_mapping.csv', 'hf://datasets/tharu-jwd/cse-market-data@669594502b85772c7b7c853067afde91402e3c2a/stock_prices.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.

date string	open float64	high float64	low float64	close float64	volume null
2025-02-03	17,122.73	17,127.65	16,900.36	16,956.49	null
2025-02-05	16,956.49	16,974.58	16,440.74	16,456.1	null
2025-02-06	16,456.1	16,675.8	16,295.31	16,506.73	null
2025-02-07	16,506.73	16,746.78	16,506.38	16,734.68	null
2025-02-10	16,734.68	16,794.64	16,537.98	16,566.27	null
2025-02-11	16,566.27	16,579.41	16,304.99	16,345.3	null
2025-02-13	16,345.3	16,609.84	16,307.98	16,578.22	null
2025-02-14	16,578.22	16,950.91	16,577.77	16,936.69	null
2025-02-17	16,936.69	17,194.34	16,936.11	17,156.05	null
2025-02-18	17,156.05	17,322.14	17,152.98	17,193.79	null
2025-02-19	17,193.79	17,262.88	17,059	17,074.02	null
2025-02-20	17,074.02	17,085.39	16,829.19	16,858.97	null
2025-02-21	16,858.97	17,002.45	16,847.27	16,889.31	null
2025-02-24	16,889.31	16,906.84	16,648.38	16,671.73	null
2025-02-25	16,671.72	16,691.06	16,338.96	16,345.01	null
2025-02-27	16,345.01	16,483.22	16,321.35	16,430.77	null
2025-02-28	16,430.77	16,560.53	16,430.6	16,478.67	null
2025-03-03	16,478.68	16,545.59	16,163.26	16,167.3	null
2025-03-04	16,167.3	16,178.38	15,870.25	15,870.25	null
2025-03-05	15,870.25	16,190.51	15,866.18	16,166.53	null
2025-03-06	16,166.53	16,309.61	16,107.83	16,123.1	null
2025-03-07	16,123.1	16,154.3	16,080.87	16,115.47	null
2025-03-10	16,115.47	16,170.83	15,990.76	16,000.78	null
2025-03-11	16,000.78	16,003.62	15,710.57	15,710.57	null
2025-03-12	15,710.58	15,910.63	15,629.09	15,861.14	null
2025-03-14	15,861.14	16,029.29	15,852.97	15,860.44	null
2025-03-17	15,860.44	15,905.98	15,646.12	15,649.3	null
2025-03-18	15,649.3	15,649.3	15,386.92	15,394.16	null
2025-03-19	15,394.16	15,510.29	15,391.75	15,406.16	null
2025-03-20	15,406.16	15,693.15	15,404.45	15,662.93	null
2025-03-21	15,662.93	15,909.59	15,659.93	15,879.33	null
2025-03-24	15,879.33	15,996.93	15,846.3	15,912.61	null
2025-03-25	15,912.61	15,979.78	15,901.31	15,908.23	null
2025-03-26	15,908.23	15,959.99	15,842.17	15,847.8	null
2025-03-27	15,847.8	15,892.75	15,847.64	15,882.06	null
2025-03-28	15,882.06	15,886.19	15,798.35	15,814.82	null
2025-04-01	15,814.8	15,949.72	15,696.44	15,934.38	null
2025-04-02	15,934.38	16,047.53	15,934.15	16,007.44	null
2025-04-03	16,007.44	16,007.44	15,644.61	15,657.6	null
2025-04-04	15,657.6	15,657.6	15,280.47	15,373.35	null
2025-04-07	15,373.35	15,373.61	14,570.34	14,660.45	null
2025-04-08	14,660.45	15,148.22	14,660.45	15,127.71	null
2025-04-09	15,127.71	15,127.71	14,836.09	14,875.95	null
2025-04-10	14,875.95	15,799.22	14,875.95	15,580.83	null
2025-04-11	15,580.83	15,586.64	15,446.18	15,526.2	null
2025-04-16	15,526.2	15,646.47	15,525.35	15,625.88	null
2025-04-17	15,625.88	15,668.96	15,567.57	15,616.57	null
2025-04-21	15,616.57	15,702.23	15,595.29	15,599.61	null
2025-04-22	15,599.61	15,633.54	15,524.3	15,555.86	null
2025-04-23	15,555.86	15,614.25	15,543.42	15,543.99	null
2025-04-24	15,543.99	15,621.75	15,543.91	15,615.63	null
2025-04-25	15,615.63	15,770.76	15,614.59	15,742.04	null
2025-04-28	15,742.04	15,867.99	15,741.77	15,811.47	null
2025-04-29	15,811.47	15,923.95	15,809.75	15,867.34	null
2025-04-30	15,867.34	15,873.32	15,799.53	15,799.94	null
2025-05-02	15,799.94	15,872.32	15,796.82	15,851.74	null
2025-05-05	15,851.74	15,945.61	15,851.74	15,916.69	null
2025-05-06	15,916.69	15,985.46	15,916.69	15,961.59	null
2025-05-07	15,961.59	15,965.59	15,833.11	15,841.6	null
2025-05-08	15,841.6	15,925.92	15,838.36	15,925.92	null
2025-05-09	15,925.92	16,005.67	15,902.87	15,916.17	null
2025-05-14	15,916.17	16,188.91	15,916.17	16,131.24	null
2025-05-15	16,131.24	16,340.73	16,129.45	16,314.79	null
2025-05-16	16,314.79	16,417.17	16,314.1	16,379.39	null
2025-05-19	16,379.39	16,472.66	16,379.39	16,397.68	null
2025-05-20	16,397.68	16,429.61	16,316.4	16,336.25	null
2025-05-21	16,336.25	16,368.62	16,328.51	16,355.91	null
2025-05-22	16,355.91	16,505.13	16,355.91	16,473.37	null
2025-05-23	16,473.37	16,551.81	16,473.37	16,494.46	null
2025-05-26	16,494.46	16,556.86	16,486.77	16,496.24	null
2025-05-27	16,496.24	16,694.38	16,496.19	16,657.63	null
2025-05-28	16,657.63	16,728.13	16,610.62	16,712.87	null
2025-05-29	16,712.87	16,855.6	16,712.16	16,815.6	null
2025-05-30	16,815.6	16,879.37	16,798.37	16,854.86	null
2025-06-02	16,854.86	17,008.95	16,854.22	16,979.89	null
2025-06-03	16,979.89	17,256.73	16,979.32	17,214.39	null
2025-06-04	17,214.39	17,414.55	17,214.39	17,353.05	null
2025-06-05	17,353.05	17,455.24	17,299	17,434.94	null
2025-06-06	17,434.94	17,526.56	17,380.82	17,394.45	null
2025-06-09	17,394.45	17,514.95	17,332.97	17,500.24	null
2025-06-11	17,500.24	17,672.13	17,499.23	17,657.6	null
2025-06-12	17,657.6	17,711.77	17,559.8	17,661.45	null
2025-06-13	17,661.45	17,661.45	17,344.06	17,427.08	null
2025-06-16	17,427.08	17,427.08	17,048.66	17,360.19	null
2025-06-17	17,360.19	17,527.17	17,266.38	17,281.95	null
2025-06-18	17,281.95	17,307.61	17,041.34	17,071.44	null
2025-06-19	17,071.44	17,105.26	16,809.4	16,818.21	null
2025-06-20	16,818.21	17,114.85	16,817.56	17,087.95	null
2025-06-23	17,087.95	17,087.95	16,741.43	16,765.4	null
2025-06-24	16,765.4	17,318.09	16,765.4	17,191.2	null
2025-06-25	17,191.2	17,539.28	17,191.2	17,535.62	null
2025-06-26	17,535.62	17,767.2	17,535.62	17,740.46	null
2025-06-27	17,740.46	17,883.88	17,735.56	17,872.74	null
2025-06-30	17,872.74	18,040.28	17,872.74	18,026.72	null
2025-07-01	18,026.72	18,057.82	17,957.37	17,996.73	null
2025-07-02	17,996.73	18,144.1	17,996.53	18,141.79	null
2025-07-03	18,141.79	18,229.34	18,100.92	18,100.92	null
2025-07-04	18,100.92	18,179.44	17,974.25	18,148.34	null
2025-07-07	18,148.34	18,160.98	18,038.87	18,042.2	null
2025-07-08	18,042.2	18,063.23	17,882.89	18,032.12	null

End of preview.

CSE Market Data — Cyclone Ditwah Event Study

Dataset accompanying the paper:

Market Reactions to Natural Disasters: An Event Study of Cyclone Ditwah's Impact on the Colombo Stock Exchange Jayawardana K.P.T., Wickramaratne W.P.G.A., Wijesinghe D.S., Fernando W.T.D., Dinapura H.H.S. Department of Computer Science & Engineering, University of Moratuwa, Sri Lanka (2026)

Code and analysis notebooks: github.com/dehanf/Disaster-Shock-Market-Response

Dataset Description

Daily OHLCV (Open, High, Low, Close, Volume) records for CSE-listed stocks spanning February 2025 to February 2026, centred on the landfall of Cyclone Ditwah on 28 November 2025. The cyclone caused an estimated USD 4.1 billion in damage (~4% of Sri Lanka's GDP) and triggered the CSE's worst weekly decline since November 2022.

The dataset covers the full data pipeline from raw collection through to final filtered data used in the event study.

Files

File	Description
`stock_prices.csv`	Raw daily OHLCV for 289 CSE-listed stocks, Feb 2025 – Feb 2026 (71,044 rows)
`aspi.csv`	Daily ASPI (All Share Price Index) OHLCV — market benchmark
`sector_mapping.csv`	Ticker-to-sector mapping for CSE stocks across 19 sectors
`pipeline/collect.py`	Python web-scraping script used to collect the raw data
`pipeline/company_mapping.json`	Company name to ticker mapping used during collection
`pipeline/sample/stock_prices.csv`	Sample output from the collection pipeline
`pipeline/sample/aspi.csv`	Sample ASPI output from the collection pipeline

Data Fields

stock_prices.csv / sample/stock_prices.csv

Field	Type	Description
`symbol`	string	CSE ticker symbol (e.g. `JKH.N0000`)
`date`	date	Trading date
`open`	float	Opening price (LKR)
`high`	float	Daily high price (LKR)
`low`	float	Daily low price (LKR)
`close`	float	Closing price (LKR)
`volume`	int	Number of shares traded

sector_mapping.csv

Field	Type	Description
`ticker`	string	Short ticker (e.g. `JKH`)
`sector`	string	CSE sector (e.g. `Diversified Financials`)

Event Details

Event: Cyclone Ditwah landfall, eastern Sri Lanka
Event date: 28 November 2025
Estimation window: [−120, −6] trading days relative to event
Event windows studied: [−5,−1], [0,0], [0,+5], [−5,+30]
Stocks in final analysis: 203 (after cleaning and liquidity filtering)
Sectors: 19 CSE sectors

Collection Method

Data were collected via a custom Python web-scraping pipeline querying the CSE's public data interface. See pipeline/collect.py for the full collection script.

License

This dataset is released under CC BY 4.0. You are free to use, share, and adapt it with attribution.

Citation

@misc{jayawardana2026cyclone,
  title={Market Reactions to Natural Disasters: An Event Study of Cyclone Ditwah's Impact on the Colombo Stock Exchange},
  author={Jayawardana, K.P.T. and Wickramaratne, W.P.G.A. and Wijesinghe, D.S. and Fernando, W.T.D. and Dinapura, H.H.S.},
  year={2026},
  institution={Department of Computer Science & Engineering, University of Moratuwa}
}

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Total file size:

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