Dataset Preview
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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 38 new columns ({'300.1', '300.3', '5868900', '5879000', '5846500', '5849700', '5859800', '200.3', '100.1', '5842700', '5873900', '5853000', '300.2', '5.1', '300', '200.2', '500', '5870000', '5861000', '5869500', '10', '5849300', '150', '5850100', '5843800', '5', '5859400', '100', '1160', '5876500', '5871000', '200', '5851000', '200.1', '300.4', '5845300', '89', '50'}) and 4 missing columns ({'34200.004241176', '1', '1.1', '16113575'}).
This happened while the csv dataset builder was generating data using
hf://datasets/totalorganfailure/lobster-data/LOBSTER_SampleFile_AAPL_2012-06-21_10/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv (at revision fb51a829d2b5a78c79468db533ba28c5f1d161d0)
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 "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
5859400: int64
200: int64
5853300: int64
18: int64
5859800: int64
200.1: int64
5853000: int64
150: int64
5861000: int64
200.2: int64
5851000: int64
5: int64
5868900: int64
300: int64
5850100: int64
89: int64
5869500: int64
50: int64
5849700: int64
5.1: int64
5870000: int64
100: int64
5849300: int64
300.1: int64
5871000: int64
10: int64
5846500: int64
300.2: int64
5873900: int64
100.1: int64
5845300: int64
300.3: int64
5876500: int64
1160: int64
5843800: int64
200.3: int64
5879000: int64
500: int64
5842700: int64
300.4: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 4565
to
{'34200.004241176': Value('float64'), '1': Value('int64'), '16113575': Value('int64'), '18': Value('int64'), '5853300': Value('int64'), '1.1': 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 "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/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 38 new columns ({'300.1', '300.3', '5868900', '5879000', '5846500', '5849700', '5859800', '200.3', '100.1', '5842700', '5873900', '5853000', '300.2', '5.1', '300', '200.2', '500', '5870000', '5861000', '5869500', '10', '5849300', '150', '5850100', '5843800', '5', '5859400', '100', '1160', '5876500', '5871000', '200', '5851000', '200.1', '300.4', '5845300', '89', '50'}) and 4 missing columns ({'34200.004241176', '1', '1.1', '16113575'}).
This happened while the csv dataset builder was generating data using
hf://datasets/totalorganfailure/lobster-data/LOBSTER_SampleFile_AAPL_2012-06-21_10/AAPL_2012-06-21_34200000_57600000_orderbook_10.csv (at revision fb51a829d2b5a78c79468db533ba28c5f1d161d0)
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.
34200.004241176
float64 | 1
int64 | 16113575
int64 | 18
int64 | 5853300
int64 | 1.1
int64 |
|---|---|---|---|---|---|
34,200.004261
| 1
| 16,113,584
| 18
| 5,853,200
| 1
|
34,200.004447
| 1
| 16,113,594
| 18
| 5,853,100
| 1
|
34,200.025552
| 1
| 16,120,456
| 18
| 5,859,100
| -1
|
34,200.02558
| 1
| 16,120,480
| 18
| 5,859,200
| -1
|
34,200.025613
| 1
| 16,120,503
| 18
| 5,859,300
| -1
|
34,200.050241
| 1
| 16,127,688
| 100
| 5,850,000
| 1
|
34,200.201518
| 1
| 16,166,035
| 100
| 5,859,300
| -1
|
34,200.201736
| 3
| 16,113,594
| 18
| 5,853,100
| 1
|
34,200.201742
| 3
| 16,113,584
| 18
| 5,853,200
| 1
|
34,200.201743
| 3
| 16,120,456
| 18
| 5,859,100
| -1
|
34,200.201768
| 3
| 16,120,503
| 18
| 5,859,300
| -1
|
34,200.201781
| 3
| 16,120,480
| 18
| 5,859,200
| -1
|
34,200.201966
| 1
| 16,166,175
| 2
| 5,849,900
| 1
|
34,200.205573
| 1
| 16,167,159
| 18
| 5,853,600
| 1
|
34,200.205597
| 1
| 16,167,166
| 18
| 5,853,500
| 1
|
34,200.27174
| 1
| 3,647,217
| 20
| 5,857,300
| 1
|
34,200.27174
| 1
| 5,740,544
| 40
| 5,857,400
| -1
|
34,200.27174
| 1
| 2,109,823
| 50
| 5,857,000
| 1
|
34,200.27174
| 1
| 3,570,647
| 50
| 5,857,500
| -1
|
34,200.27174
| 1
| 3,237,773
| 20
| 5,856,900
| 1
|
34,200.27174
| 1
| 3,647,221
| 5
| 5,857,500
| -1
|
34,200.27174
| 1
| 3,583,158
| 5
| 5,856,500
| 1
|
34,200.27174
| 1
| 3,647,222
| 7
| 5,857,500
| -1
|
34,200.27174
| 1
| 3,647,220
| 20
| 5,856,400
| 1
|
34,200.27174
| 1
| 5,230,851
| 20
| 5,857,500
| -1
|
34,200.27174
| 1
| 4,731,250
| 3
| 5,856,000
| 1
|
34,200.27174
| 1
| 1,373,927
| 25
| 5,857,800
| -1
|
34,200.27174
| 1
| 1,601,225
| 20
| 5,857,800
| -1
|
34,200.27174
| 1
| 2,606,421
| 4
| 5,858,000
| -1
|
34,200.27174
| 1
| 1,364,835
| 5
| 5,858,200
| -1
|
34,200.27174
| 1
| 7,277,867
| 7
| 5,858,300
| -1
|
34,200.274847
| 3
| 16,167,159
| 18
| 5,853,600
| 1
|
34,200.274848
| 3
| 16,113,575
| 18
| 5,853,300
| 1
|
34,200.27493
| 3
| 16,167,166
| 18
| 5,853,500
| 1
|
34,200.275016
| 4
| 5,740,544
| 40
| 5,857,400
| -1
|
34,200.275016
| 4
| 3,570,647
| 25
| 5,857,500
| -1
|
34,200.275057
| 4
| 3,647,217
| 1
| 5,857,300
| 1
|
34,200.275063
| 4
| 3,647,217
| 10
| 5,857,300
| 1
|
34,200.275072
| 4
| 3,570,647
| 25
| 5,857,500
| -1
|
34,200.275072
| 4
| 3,647,221
| 5
| 5,857,500
| -1
|
34,200.275072
| 4
| 3,647,222
| 7
| 5,857,500
| -1
|
34,200.275072
| 4
| 5,230,851
| 20
| 5,857,500
| -1
|
34,200.275072
| 4
| 1,373,927
| 25
| 5,857,800
| -1
|
34,200.275072
| 4
| 1,601,225
| 20
| 5,857,800
| -1
|
34,200.275072
| 5
| 0
| 100
| 5,857,900
| -1
|
34,200.275072
| 4
| 2,606,421
| 4
| 5,858,000
| -1
|
34,200.275072
| 4
| 1,364,835
| 5
| 5,858,200
| -1
|
34,200.275072
| 4
| 7,277,867
| 7
| 5,858,300
| -1
|
34,200.275072
| 5
| 0
| 3
| 5,859,000
| -1
|
34,200.275072
| 5
| 0
| 200
| 5,859,000
| -1
|
34,200.275072
| 5
| 0
| 1
| 5,859,100
| -1
|
34,200.275072
| 5
| 0
| 1
| 5,859,200
| -1
|
34,200.275072
| 5
| 0
| 300
| 5,859,200
| -1
|
34,200.275072
| 4
| 16,166,035
| 37
| 5,859,300
| -1
|
34,200.275087
| 1
| 16,182,629
| 100
| 5,852,500
| 1
|
34,200.275123
| 1
| 16,182,649
| 50
| 5,857,400
| 1
|
34,200.277208
| 3
| 15,836,282
| 100
| 5,868,900
| -1
|
34,200.277699
| 3
| 15,847,383
| 100
| 5,873,900
| -1
|
34,200.280396
| 1
| 16,183,794
| 18
| 5,857,700
| 1
|
34,200.280424
| 1
| 16,183,801
| 18
| 5,857,600
| 1
|
34,200.280446
| 1
| 16,183,806
| 18
| 5,857,500
| 1
|
34,200.29384
| 1
| 16,186,225
| 100
| 5,857,000
| 1
|
34,200.347391
| 1
| 16,196,199
| 100
| 5,859,300
| -1
|
34,200.358687
| 4
| 16,166,035
| 4
| 5,859,300
| -1
|
34,200.393803
| 1
| 16,207,125
| 100
| 5,859,400
| -1
|
34,200.393976
| 3
| 16,182,649
| 50
| 5,857,400
| 1
|
34,200.394002
| 3
| 16,183,801
| 18
| 5,857,600
| 1
|
34,200.394003
| 3
| 16,183,806
| 18
| 5,857,500
| 1
|
34,200.394048
| 1
| 16,207,170
| 100
| 5,859,900
| -1
|
34,200.395117
| 1
| 16,207,442
| 200
| 5,859,800
| -1
|
34,200.417747
| 4
| 16,183,794
| 18
| 5,857,700
| 1
|
34,200.417747
| 4
| 3,647,217
| 9
| 5,857,300
| 1
|
34,200.417747
| 5
| 0
| 23
| 5,857,200
| 1
|
34,200.418944
| 5
| 0
| 77
| 5,857,200
| 1
|
34,200.418944
| 4
| 2,109,823
| 23
| 5,857,000
| 1
|
34,200.41909
| 1
| 16,211,220
| 18
| 5,859,200
| -1
|
34,200.459503
| 3
| 16,186,225
| 100
| 5,857,000
| 1
|
34,200.4597
| 1
| 16,220,046
| 100
| 5,854,500
| 1
|
34,200.484613
| 1
| 16,225,065
| 300
| 5,870,000
| -1
|
34,200.484768
| 1
| 16,225,109
| 300
| 5,870,000
| -1
|
34,200.502026
| 3
| 16,220,046
| 100
| 5,854,500
| 1
|
34,200.544528
| 1
| 16,235,607
| 5
| 5,863,300
| -1
|
34,200.6106
| 3
| 16,196,199
| 100
| 5,859,300
| -1
|
34,200.610751
| 3
| 16,211,220
| 18
| 5,859,200
| -1
|
34,200.615389
| 1
| 16,249,592
| 100
| 5,854,400
| 1
|
34,200.698811
| 1
| 16,265,081
| 100
| 5,854,500
| 1
|
34,200.701389
| 1
| 16,265,573
| 100
| 5,858,700
| -1
|
34,200.702574
| 1
| 16,265,761
| 67
| 5,854,400
| 1
|
34,200.76306
| 4
| 2,109,823
| 1
| 5,857,000
| 1
|
34,200.833565
| 3
| 16,265,081
| 100
| 5,854,500
| 1
|
34,200.833761
| 1
| 16,284,218
| 100
| 5,857,000
| 1
|
34,200.834525
| 3
| 16,284,218
| 100
| 5,857,000
| 1
|
34,200.834769
| 1
| 16,284,304
| 100
| 5,854,500
| 1
|
34,200.887406
| 5
| 0
| 47
| 5,858,600
| -1
|
34,200.887489
| 1
| 16,291,236
| 18
| 5,857,000
| 1
|
34,200.887549
| 1
| 16,291,244
| 18
| 5,857,100
| 1
|
34,200.888239
| 3
| 16,284,304
| 100
| 5,854,500
| 1
|
34,200.888357
| 1
| 16,291,389
| 100
| 5,856,000
| 1
|
34,200.888642
| 3
| 16,291,389
| 100
| 5,856,000
| 1
|
34,200.8888
| 1
| 16,291,456
| 100
| 5,856,100
| 1
|
End of preview.
LOBSTER Sample Data
LOBSTER (Limit Order Book System) sample L3 order book data for June 21, 2012.
Dataset Description
LOBSTER provides limit order book data from NASDAQ TotalView-ITCH messages.
- AAPL: 1, 5, 10, 30, 50 levels
- AMZN: 1, 5, 10 levels
- GOOG: 1, 5, 10 levels
- INTC: 1, 5, 10 levels
- MSFT: 1, 5, 10, 30, 50 levels
- SPY: 30, 50 levels
Configurations
Each ticker/level combination has its own configuration with two splits:
- message: Order book events (time-series of market events)
- orderbook: Order book snapshots at each event time
File Structure
Each ticker has two CSV files:
Message file (
*_message_*.csv): Order book events- Columns: time, event_type, order_id, size, price, direction
- Types: 1=New, 2=Cancel, 3=Delete, 4=Exec(Visible), 5=Exec(Hidden), 7=Halt
Orderbook file (
*_orderbook_*.csv): Order book snapshots- Columns: ask_price_1, ask_size_1, bid_price_1, bid_size_1, ... (up to N levels)
- Prices in fixed-point (multiply by 10^-4)
Usage
from datasets import load_dataset
# Load a specific ticker configuration
dataset = load_dataset("your-username/lobster-sample-data", "AAPL_10levels")
# Access message data
messages = dataset["message"]
# Access orderbook data
orderbooks = dataset["orderbook"]
Source
Data provided by LOBSTER - Limited Order Book System.
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