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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 5 new columns ({'NodeCount', 'EdgeCount', 'GraphID', 'RootNodeIdx', 'RootNodeId'}) and 7 missing columns ({'OriginalInDegree', 'ScriptType', 'OutDegree', 'InDegree', 'OriginalOutDegree', 'OutHopsFromRoot', 'Address'}).
This happened while the csv dataset builder was generating data using
hf://datasets/B1AAB/Bitcoin-Graph-Sampled-Communities/script_to_script_200k/raw/202509082048222123/metadata.tsv (at revision 249e7205b72b4467f384f890c26b0999a3d09c5c)
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
GraphID: int64
RootNodeId: string
RootNodeIdx: int64
NodeCount: int64
EdgeCount: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 839
to
{'Address': Value('string'), 'ScriptType': Value('int64'), 'InDegree': Value('int64'), 'OutDegree': Value('int64'), 'OriginalInDegree': Value('int64'), 'OriginalOutDegree': Value('int64'), 'OutHopsFromRoot': 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 5 new columns ({'NodeCount', 'EdgeCount', 'GraphID', 'RootNodeIdx', 'RootNodeId'}) and 7 missing columns ({'OriginalInDegree', 'ScriptType', 'OutDegree', 'InDegree', 'OriginalOutDegree', 'OutHopsFromRoot', 'Address'}).
This happened while the csv dataset builder was generating data using
hf://datasets/B1AAB/Bitcoin-Graph-Sampled-Communities/script_to_script_200k/raw/202509082048222123/metadata.tsv (at revision 249e7205b72b4467f384f890c26b0999a3d09c5c)
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.
Address
string | ScriptType
int64 | InDegree
int64 | OutDegree
int64 | OriginalInDegree
int64 | OriginalOutDegree
int64 | OutHopsFromRoot
int64 |
|---|---|---|---|---|---|---|
12q95Yvu6ef5Bgr45mjyBHrVhuR7CyxfXd
| 1
| 1
| 1
| 561
| 172
| 0
|
1PCmnvXPsarTrWQWKpjV9a2BGLzSGTCoos
| 1
| 1
| 0
| 1
| 6
| 3
|
127S9djkR2UHHwHKr3u8FLoMDXVKtwsRFL
| 1
| 1
| 0
| 429
| 1,834
| 3
|
18Zcyxqna6h7Z7bRjhKvGpr8HSfieQWXqj
| 1
| 1
| 10
| 9,021,131
| 15,754
| 2
|
19UA9qSfd5DrFWZXLtdMT4Rus9M5VM53dx
| 1
| 1
| 0
| 9,219
| 12,340
| 3
|
177fpGmiFXRsY7UeCSoRAsYe2vDmJuYVqu
| 1
| 1
| 0
| 8,853
| 8,812
| 3
|
1H9DUnxe9TgB6bdyPH6eSzdw8utwNp1kLa
| 1
| 1
| 0
| 3,750
| 4
| 1
|
16gbF8fTUeFSMK2JTLwzNK5jzRgEx5K92A
| 1
| 1
| 0
| 47
| 144
| 3
|
13fW4oyBosTQZkEALDhK5RNmtmZSe7uPe6
| 1
| 1
| 0
| 19
| 6
| 3
|
1CkmA25Dq5ZnoqM4W1SG6BrkWfo8cYfMZ2
| 1
| 1
| 0
| 2,374
| 4
| 1
|
1DE1D7c1jwBSMk9SnD47sQkYBeyG3vpVBD
| 1
| 1
| 3
| 2
| 6
| 2
|
12EnrBWJPg3FFGDzvHnAmiNDxg1MFoHjkn
| 1
| 1
| 0
| 237
| 334
| 3
|
12NArz3Aju74tZnfiytt3ZjtCn9LAcHDhw
| 1
| 1
| 0
| 8
| 370
| 3
|
13zHEiEAX9JaPCMp7hbtKZv78Yzw6ZhPLJ
| 1
| 1
| 2
| 110
| 32
| 1
|
1DQqpXSQypjk1Lc5jSvUEtW7KSdTC2KtVF
| 1
| 1
| 0
| 2
| 6
| 3
|
155fzsEBHy9Ri2bMQ8uuuR3tv1YzcDywd4
| 1
| 1
| 1
| 21,181,446
| 662
| 2
|
16dYJ31tZUvrpGMg7LP7zMXHkErvfx6Tsv
| 1
| 1
| 0
| 16
| 66
| 3
|
1DFEVhNDctAac8ar4dwuz6gRPUvMUiUaBD
| 1
| 1
| 0
| 7
| 20
| 3
|
14rkdHrh1E3L34v9vTevoJ5hGfLmM2eLTX
| 1
| 1
| 0
| 1,451
| 2,882
| 3
|
1DRpHeT3wQLPQhFzDmAhf7WB6Ypbs3EEZG
| 1
| 1
| 2
| 1
| 4
| 1
|
1Mh2MPPqfoxRcWt2M7nr66EFn1UHxUkMap
| 1
| 1
| 0
| 1
| 6
| 3
|
1KFHE7w8BhaENAswwryaoccDb6qcT6DbYY
| 1
| 1
| 10
| 282,138,435
| 3,421,428
| 2
|
1D3DKwsfphZddmbsQZwA8uYXDxSksxCf2C
| 1
| 1
| 0
| 1
| 8
| 3
|
3NA8hsjfdgVkmmVS9moHmkZsVCoLxUkvvv
| 2
| 1
| 8
| 10,915,607
| 2,770
| 0
|
1ABu1at4nq9hYQumkwVPcsZvaVPYZZCnFP
| 1
| 1
| 0
| 1
| 6
| 3
|
12Shq2AQMgHBHVffbbd9DJ9mVv9grz1o95
| 1
| 1
| 0
| 360
| 1,970
| 3
|
1ChpsS9qX87AjTqbJDnx6HJNT18ELBdqM4
| 1
| 1
| 0
| 1,419
| 0
| 1
|
1B1oYndjbpGwMVBVfNjZ1PUy6PUKaQawti
| 1
| 1
| 0
| 1
| 6
| 3
|
12FaUWDHFn4vTimdmomxBPi87fvaFL1aWw
| 1
| 1
| 0
| 1
| 6
| 3
|
1A3Z3B9QtYcA9ZMtLDxBYn6iSstDscdsqB
| 1
| 1
| 0
| 2,374
| 0
| 1
|
1ALhitdxxigF5GVXGSwS6bUZeMCiNmnabk
| 1
| 1
| 6
| 42
| 72
| 2
|
12PN1znGB4Fk24pa45cbDf1uAGPpRywGBM
| 1
| 1
| 0
| 42
| 1,070
| 3
|
14M5AsHzRQP4AznphM2v3dDgEFwfPGbEsR
| 1
| 1
| 0
| 8
| 6
| 3
|
1FYhWJRR1fphMXH9jzpPvgFQ4sEx4Wfgzg
| 1
| 0
| 3
| 3
| 6
| 0
|
12qditaGoBronpfd1iFSAneZmBs4GrkFuM
| 1
| 1
| 0
| 48
| 30
| 3
|
1LjYX8JCSSCgzUdEHVZi4qcdxzn7YEkr1M
| 1
| 1
| 0
| 408,784
| 185,976
| 3
|
1MG5fPzWBwuKEkcLrKPocRgvymmx2qSkHa
| 1
| 1
| 0
| 45
| 6
| 0
|
17ThTJxhKZQvoBM2PBVLRmr2ozcjRHKJa2
| 1
| 1
| 0
| 76
| 350
| 3
|
14vLPArARG7D6agPkoJ1BJbMoB1EvCpeM9
| 1
| 1
| 0
| 1
| 6
| 3
|
122QqT1YVpbpwnWMoXgbLvhPp3W3JDiHfB
| 1
| 1
| 0
| 31
| 22
| 3
|
1M3iEmXs6KJQszh4hGnjmvT8mUFmvu34eJ
| 1
| 1
| 0
| 2,374
| 0
| 1
|
1E4nqRyFxE5dVZCL83YR2y68tJqJurYhcR
| 1
| 1
| 1
| 1,539,343
| 1,728
| 1
|
11Qzze4DHYwZQKMWRLcWsucRrXtZBVUNc
| 1
| 1
| 0
| 1
| 0
| 3
|
1N8QiBLSV2u7SEq9JgoMrrMsnXjKxmrkiv
| 1
| 1
| 0
| 1
| 6
| 3
|
13YPQyANk8pVMDpAWyBrp68kVJoNsFNWZZ
| 1
| 1
| 0
| 3,896
| 0
| 1
|
17UHdESC3gTRaVEqzJBB8Kb2CYJoUn2UXd
| 1
| 1
| 0
| 1
| 6
| 3
|
12UxamrSnuCPmMdVwLNe7yQP4VK56W5wBt
| 1
| 1
| 0
| 60
| 28
| 3
|
12WiVxjL9qGw53SRH6wqvvScv4WztQ7Z7n
| 1
| 1
| 0
| 1
| 0
| 3
|
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End of preview.
Overview
EBA interfaces with the Bitcoin network to
create a graph of the full history of on-chain transactions,
which includes the complete trading details of >8.72B BTC.
This temporal heterogeneous graph consists of >2.4B nodes and >39.7B
time-stamped edges spanning more than a decade,
making it an ideal resource for developing models on Bitcoin
and a large-scale benchmark for graph neural networks.
Please refer to the following paper for details:
We share the complete ETL pipeline and all the data it generates. To simplify working with the pipeline and its resources, we have split them into separate repositories:
Block Metadata
This dataset provides per-block summary statistics for the Bitcoin blockchain,
covering all blocks up to height 863 000. The statistics are derived from four sources:
parsed from block headers, ETL logs, summarized from block content,
and generated from the chain in a post-processing step.
The goal of these stats is to provide block-level context; either used as an independent resource (e.g., to forecast trade volume) or to complement other datasets. For instance, they can be combined with the Bitcoin Graph or off-chain market indicators (like high, low, open, and close prices) to enhance forecasting models.
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