The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 9 new columns ({'name', 'avgReviewScore', 'numReviews', 'price', 'description', 'genres', 'numFollowers', 'id', 'tags'}) and 2 missing columns ({'user2', 'user1'}).
This happened while the csv dataset builder was generating data using
hf://datasets/steamgamerecommender/data_files_public/0/games.csv (at revision d31fadbdcea69f26d3a3a6515607be1a23293303)
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 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: int64
name: string
numReviews: int64
avgReviewScore: int64
price: double
genres: string
tags: string
description: string
numFollowers: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1284
to
{'user1': Value(dtype='int64', id=None), 'user2': 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 1321, 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 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 9 new columns ({'name', 'avgReviewScore', 'numReviews', 'price', 'description', 'genres', 'numFollowers', 'id', 'tags'}) and 2 missing columns ({'user2', 'user1'}).
This happened while the csv dataset builder was generating data using
hf://datasets/steamgamerecommender/data_files_public/0/games.csv (at revision d31fadbdcea69f26d3a3a6515607be1a23293303)
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.
user1 int64 | user2 int64 |
|---|---|
0 | 4,242,737 |
0 | 1 |
0 | 2 |
0 | 3 |
0 | 4,242,738 |
0 | 4,242,739 |
0 | 4 |
0 | 4,242,740 |
0 | 4,242,741 |
0 | 4,242,742 |
0 | 4,242,743 |
0 | 4,242,744 |
1 | 4,242,745 |
1 | 2,859,634 |
1 | 4,242,746 |
1 | 5 |
1 | 4,242,747 |
1 | 0 |
1 | 6 |
1 | 7 |
1 | 4,242,748 |
1 | 4,242,749 |
1 | 4,242,750 |
1 | 8 |
1 | 2,204,968 |
1 | 9 |
1 | 10 |
1 | 4,242,751 |
2 | 11 |
2 | 12 |
2 | 0 |
2 | 13 |
2 | 14 |
2 | 15 |
2 | 16 |
2 | 17 |
2 | 18 |
2 | 4,242,752 |
2 | 4,242,753 |
2 | 4,242,754 |
2 | 4,242,755 |
2 | 4,242,756 |
3 | 19 |
3 | 4,242,737 |
3 | 0 |
3 | 20 |
3 | 21 |
3 | 22 |
3 | 23 |
3 | 4,242,757 |
3 | 4,242,758 |
3 | 4,242,759 |
3 | 24 |
3 | 4,242,760 |
3 | 25 |
3 | 4,242,761 |
3 | 26 |
3 | 27 |
3 | 4,242,744 |
3 | 4,242,762 |
3 | 4,242,763 |
4 | 4,242,764 |
4 | 28 |
4 | 4,242,765 |
4 | 29 |
4 | 30 |
4 | 0 |
4 | 31 |
4 | 4,242,766 |
4 | 4,242,767 |
4 | 32 |
4 | 33 |
4 | 34 |
4 | 4,242,768 |
4 | 35 |
4 | 36 |
4 | 4,242,769 |
4 | 37 |
4 | 38 |
4 | 39 |
4 | 40 |
4 | 4,242,770 |
4 | 41 |
4 | 42 |
4 | 4,242,771 |
4 | 43 |
4 | 4,242,772 |
4 | 4,242,773 |
5 | 1,853,468 |
5 | 668,388 |
5 | 4,242,774 |
5 | 4,242,775 |
5 | 44 |
5 | 45 |
5 | 46 |
5 | 47 |
5 | 2,025,762 |
5 | 4,242,776 |
5 | 4,242,777 |
5 | 1,314,192 |
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Steam Game Ownership and User Friendships Dataset
Overview
This is a one stop shop for data necessary to make a personalized steam game recommendation system. This data was scraped from the Steam gaming platform using their open API. To the best of our knowledge, this is the first & largest open-access dataset for game ownership and user friendships of Steam data. Currently, the dataset consistents of 80k users, 34k games, 24M game ownerships, 10M friendships. User ids were anonymized by assigning a sequential id.
License
GNU General Public License v3.0
Dataset Creation
This dataset was created using Steam's Web API. Given a public Steam user id, we are able to get all the games that the user owns and all the friends the user has. Given a game id, we are able to get information about the game, such as the name, price, average steam review score, etc. We scraped this dataset using a snowball sampling (BFS) technique. First, we sampled random user ids until we found a user id that was public. We would scrape that user's games and friends, and add the new friends to the BFS queue. Then, we would pop a user off the queue, and continue the scraping process with them. This process continued until a threshold number of scraped users was met.
Dataset Structure
Each snowball (described in the dataset creation section) is formatted into its own folder named by the root (initial) user of the snowball. The users.csv file shows the user ids that contributed to the snowball, in the order that they came off the BFS queue. The friends.csv file shows all the friendships for the scraped users, formatted with user1 and user2 columns. The users_games.csv file shows that game ownerships for the scraped users along with the total and recent playtime for each user / game pair. The games.csv file shows the new games (not encountered in previous snowballs) that were encountered (owned by users) along with information such as their price, tags, description, etc.
Note: If a user was encountered in snowball B that was already scraped from snowball A, the user id will still be added to users.csv for the snowball A but friendship data and game ownership will not be added to either friends.csv or users_games.csv.
Note: If a game was encountered in snowball B that was already scraped from snowball A, the user id / game id pair will still be added to users_games.csv for the snowball A but game data will not be added to games.csv.
Dataset Usage
This dataset was created as part of a class project for a personalized Steam game recommender: gamesouprise.com.
This project is open source and can be found on GitHub.
Contact
jackson.p.rusch@vanderbilt.edu, akash.munagala@vanderbilt.edu, jeffrey.w.pan@vanderbilt.edu, arjun.batra@vanderbilt.edu
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