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Datasets:
dbiton
/
EthereumStatistics

Modalities:
Image
Size:
1M<n<10M
Tags:
Ethereum
Blockchain
Crypto
License:
Dataset card Data Studio Files Community
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 ({'mean_call_count_leaves_smart_contract', 'count_txs_value_transfer', 'mean_call_degree_smart_contract', 'mean_call_count_smart_contract', 'mean_call_height_smart_contract'})

This happened while the csv dataset builder was generating data using

hf://datasets/dbiton/EthereumStatistics/metrics_callTracer_conflict_graph.csv (at revision 87c54cb104168272c59a547e1e7f27e9806e6b00)

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/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 623, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              mean_call_count_smart_contract: double
              mean_call_height_smart_contract: double
              mean_call_degree_smart_contract: double
              mean_call_count_leaves_smart_contract: double
              count_txs_value_transfer: int64
              degree: double
              greedy_color: int64
              assortativity: double
              cluster_coe: double
              modularity: double
              transitivity: double
              diameter: double
              clique_number: int64
              density: double
              largest_conn_comp: int64
              longest_path_length_monte_carlo: int64
              max_degree: int64
              vertex_cover_pop_max_deg_approx: int64
              vertex_cover_dummy_approx: double
              vertex_cover_nx_approx: int64
              block_number: int64
              txs: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3237
              to
              {'degree': Value(dtype='float64', id=None), 'greedy_color': Value(dtype='int64', id=None), 'assortativity': Value(dtype='float64', id=None), 'cluster_coe': Value(dtype='float64', id=None), 'modularity': Value(dtype='float64', id=None), 'transitivity': Value(dtype='float64', id=None), 'diameter': Value(dtype='float64', id=None), 'clique_number': Value(dtype='int64', id=None), 'density': Value(dtype='float64', id=None), 'largest_conn_comp': Value(dtype='int64', id=None), 'longest_path_length_monte_carlo': Value(dtype='int64', id=None), 'max_degree': Value(dtype='int64', id=None), 'vertex_cover_pop_max_deg_approx': Value(dtype='int64', id=None), 'vertex_cover_dummy_approx': Value(dtype='float64', id=None), 'vertex_cover_nx_approx': Value(dtype='int64', id=None), 'block_number': Value(dtype='int64', id=None), 'txs': Value(dtype='int64', id=None)}
              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 1438, 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 1050, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, 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 ({'mean_call_count_leaves_smart_contract', 'count_txs_value_transfer', 'mean_call_degree_smart_contract', 'mean_call_count_smart_contract', 'mean_call_height_smart_contract'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/dbiton/EthereumStatistics/metrics_callTracer_conflict_graph.csv (at revision 87c54cb104168272c59a547e1e7f27e9806e6b00)
              
              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.

degree
float64
greedy_color
int64
assortativity
float64
cluster_coe
float64
modularity
float64
transitivity
float64
diameter
float64
clique_number
int64
density
float64
largest_conn_comp
int64
longest_path_length_monte_carlo
int64
max_degree
int64
vertex_cover_pop_max_deg_approx
int64
vertex_cover_dummy_approx
float64
vertex_cover_nx_approx
int64
block_number
int64
txs
int64
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152
10
5
17
20,000,082
154
6.734463
4
-0.847384
0.123338
0.156074
0.014975
2
4
0.038264
177
12
174
7
5
14
20,000,083
177
4.787879
4
-0.387398
0.259028
0.503551
0.041938
2
4
0.029194
165
19
164
14
13
24
20,000,084
165
3.776224
4
-0.563432
0.235541
0.361269
0.032566
2
4
0.026593
143
13
142
6
5
12
20,000,085
143
0.877698
3
-0.488311
0.046425
0.407283
0.126888
2
3
0.00636
34
3
33
8
8
15
20,000,086
139
4.824324
4
-0.787486
0.155091
0.211128
0.018294
2
4
0.032819
148
11
146
8
4
12
20,000,087
148
4.252101
4
-0.874343
0.069475
0.120327
0.00847
2
4
0.036035
119
13
117
8
5
13
20,000,088
119
2.47619
4
-0.766272
0.227142
0.230769
0.012515
2
4
0.01981
126
5
125
4
3
7
20,000,089
126
2.860759
4
-0.681565
0.293268
0.273005
0.040986
2
4
0.036676
79
11
78
7
5
10
20,000,090
79
2.873786
4
-0.628194
0.252514
0.319445
0.014751
2
4
0.014018
206
15
205
8
8
15
20,000,091
206
0.138462
2
-0.653061
0
0.592593
0
2
2
0.001073
5
4
4
4
4
6
20,000,092
130
3.518717
3
-0.688444
0.018786
0.517438
0.030697
4
3
0.018918
78
30
33
17
16
32
20,000,093
187
2.871287
4
-0.670519
0.195968
0.305898
0.027925
2
4
0.028713
101
7
100
5
4
6
20,000,094
101
4.039216
3
-0.947859
0.051004
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0.039992
102
9
100
4
2
8
20,000,095
102
4.409091
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-0.872339
0.151066
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4
0.033657
132
8
130
5
3
6
20,000,096
132
2.42623
4
-0.769616
0.197529
0.225712
0.01152
2
4
0.020051
122
6
121
6
2
7
20,000,097
122
4.613636
4
-0.845756
0.220058
0.137883
0.0252
2
4
0.05303
88
10
86
6
3
6
20,000,098
88
2.169492
3
-0.854242
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0.018543
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8
117
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20,000,099
118
End of preview.

Ethereum Conflict Graph Metrics

This repository contains two CSV files, one for prestateTracer and one for callTracer, each covering over 2 million recent Ethereum blocks. These files provide key metrics extracted from conflict graphs generated by their respective tracers. You can read about these tracers here:

https://geth.ethereum.org/docs/developers/evm-tracing/built-in-tracers

Dataset Overview

  • prestateTracer: Contains metrics for conflict graphs generated using prestateTracer.
  • callTracer: Contains metrics for conflict graphs generated using callTracer, includes additional metrics related to smart contract invocation call trees.

Purpose

This dataset was collected as part of the Ethereum Conflicts Graphed paper, which explores the nature of conflicts graphs in Ethereum transactions through graph-based analysis.

Source Code

This dataset was generated using the following open source code:

https://github.com/dbiton/EthGrapher

Paper

For further details, please refer to the Ethereum Conflicts Graphed paper, to be published in ICBC 2025 and linked here in the future.

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