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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 2 new columns ({'category_id', 'edge'}) and 3 missing columns ({'review_count', 'name', 'stars'}).
This happened while the csv dataset builder was generating data using
hf://datasets/codeloverhxy/yelp/yelp_academic_dataset_business_category.csv (at revision 0c1673d9192cbf68fe0bbae63f73ce7310f15549)
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
business_id: string
category_id: int64
edge: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 609
to
{'business_id': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'stars': Value(dtype='float64', id=None), 'review_count': 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 2 new columns ({'category_id', 'edge'}) and 3 missing columns ({'review_count', 'name', 'stars'}).
This happened while the csv dataset builder was generating data using
hf://datasets/codeloverhxy/yelp/yelp_academic_dataset_business_category.csv (at revision 0c1673d9192cbf68fe0bbae63f73ce7310f15549)
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.
business_id string | name string | stars float64 | review_count int64 |
|---|---|---|---|
Pns2l4eNsfO8kk83dixA6A | Abby Rappoport, LAC, CMQ | 5 | 7 |
mpf3x-BjTdTEA3yCZrAYPw | The UPS Store | 3 | 15 |
tUFrWirKiKi_TAnsVWINQQ | Target | 3.5 | 22 |
MTSW4McQd7CbVtyjqoe9mw | St Honore Pastries | 4 | 80 |
mWMc6_wTdE0EUBKIGXDVfA | Perkiomen Valley Brewery | 4.5 | 13 |
CF33F8-E6oudUQ46HnavjQ | Sonic Drive-In | 2 | 6 |
n_0UpQx1hsNbnPUSlodU8w | Famous Footwear | 2.5 | 13 |
qkRM_2X51Yqxk3btlwAQIg | Temple Beth-El | 3.5 | 5 |
k0hlBqXX-Bt0vf1op7Jr1w | Tsevi's Pub And Grill | 3 | 19 |
bBDDEgkFA1Otx9Lfe7BZUQ | Sonic Drive-In | 1.5 | 10 |
UJsufbvfyfONHeWdvAHKjA | Marshalls | 3.5 | 6 |
eEOYSgkmpB90uNA7lDOMRA | Vietnamese Food Truck | 4 | 10 |
il_Ro8jwPlHresjw9EGmBg | Denny's | 2.5 | 28 |
jaxMSoInw8Poo3XeMJt8lQ | Adams Dental | 5 | 10 |
0bPLkL0QhhPO5kt1_EXmNQ | Zio's Italian Market | 4.5 | 100 |
MUTTqe8uqyMdBl186RmNeA | Tuna Bar | 4 | 245 |
rBmpy_Y1UbBx8ggHlyb7hA | Arizona Truck Outfitters | 4.5 | 10 |
M0XSSHqrASOnhgbWDJIpQA | Herb Import Co | 4 | 5 |
8wGISYjYkE2tSqn3cDMu8A | Nifty Car Rental | 3.5 | 14 |
ROeacJQwBeh05Rqg7F6TCg | BAP | 4.5 | 205 |
WKMJwqnfZKsAae75RMP6jA | Roast Coffeehouse and Wine Bar | 4 | 40 |
qhDdDeI3K4jy2KyzwFN53w | Barnes & Noble Booksellers | 4 | 38 |
kfNv-JZpuN6TVNSO6hHdkw | Hibachi Express | 4 | 20 |
9OG5YkX1g2GReZM0AskizA | Romano's Macaroni Grill | 2.5 | 339 |
4iRzR7OaS-QaSXuvYxEGKA | Super Dog | 4 | 6 |
PSo_C1Sfa13JHjzVNW6ziQ | Indian Walk Veterinary Center | 5 | 15 |
noByYNtDLQAra9ccqxdfDw | H&M | 3 | 24 |
tMkwHmWFUEXrC9ZduonpTg | The Green Pheasant | 4 | 161 |
QdN72BWoyFypdGJhhI5r7g | Bar One | 4 | 65 |
sqSqqLy0sN8n2IZrAbzidQ | Domino's Pizza | 3.5 | 8 |
fvWn8oXXwbj2l79cochZyw | Altitude Trampoline Park - Boise | 5 | 30 |
Mjboz24M9NlBeiOJKLEd_Q | DeSandro on Main | 3 | 41 |
8sshLb4UU7emeUDvtJWnpA | DanceLine | 4.5 | 11 |
kV_Q1oqis8Qli8dUoGpTyQ | Ardmore Pizza | 3.5 | 109 |
w_AMNoI1iG9eay7ncmc67w | River 127 | 3 | 12 |
aPNXGTDkf-4bjhyMBQxqpQ | Craft Hall | 3.5 | 65 |
2xVsWBNFwZOxIOdd9Mwnww | Cheeseburger In Paradise | 2.5 | 20 |
mGFsPRHdE6SMV1gYQ6GzgQ | T-Mobile | 2 | 6 |
LcAozWCMLGjwRbokaJAKMg | Edwardsville Children's Museum | 4.5 | 12 |
fSCNwMtNNQY9QT69Cj9fiA | Sierra Pro Events | 5 | 7 |
x1mhq4IpWctQOBM06dU8vg | Diamond Hair Company | 1.5 | 25 |
ljxNT9p0y7YMPx0fcNBGig | Tony's Restaurant & 3rd Street Cafe | 3 | 94 |
lwItZ1Ck3KtpCgG4CPFmpQ | Stomel Elliot Attorney-At-Law | 5 | 5 |
Kq51_lGAgAigqmENITTr-A | Bala Better Health | 4 | 13 |
mglME3E7esPSpIF5bias8w | Pier 1 | 2.5 | 8 |
wghnIlMb_i5U46HMBGx9ig | China Dragon Restaurant | 3 | 23 |
JX4tUpd09YFchLBuI43lGw | Naked Cyber Cafe & Espresso Bar | 4 | 12 |
lk9IwjZXqUMqqOhM774DtQ | Caviar & Bananas | 3.5 | 159 |
bCBPXIVfVzBZBEpFu29dcg | All In Shipping | 5 | 5 |
ABxoFuzZy5mqQ8C5FJJajQ | Core de Roma | 5 | 12 |
Hwt3_mOEmU-t--ywcemnMg | Gold's Gym | 3 | 17 |
REwfwz-_-CMQ7Np5UVi9Qg | Jennie Deckert | 5 | 7 |
5BmQX4UVJY19mMtafMg7JA | Breadland Organic Whole Grain Bakery | 4 | 23 |
cVBxfMC4lp3DnocjYA3FHQ | Paws The Cat Cafe | 5 | 20 |
0qNpTGTcqPwOLi2hADx4Xw | Charlie's Market | 3 | 9 |
xM6LoUcnpDpMBzXs_7dXAg | Fairfield Inn & Suites | 3 | 37 |
txyXRytGjwOXvS8s4sc-WA | Smoothie King | 3 | 29 |
DQ7PyYlp2bX96WZa7TcaWQ | LensCrafters | 2.5 | 8 |
uI9XODGY_2_ieTE6xJ0myw | Roman Forum | 4 | 23 |
JgpnXv_0XhV3SfbfB50nxw | Joe's Pizza | 4 | 35 |
Si6LXSR9gvAbmgO5DzV2cw | Lafitte's Landing Seafood House | 2.5 | 38 |
seKihQKpGGnCeLuELRQPSQ | Twin Peaks | 3.5 | 257 |
L_TT0BFmFwORAMaA83K54A | Village Tap Room | 2.5 | 23 |
mjWvAkNqoA6Y5P03sDSzfA | Educational Outfitters | 2 | 10 |
qfWJmJ0g96eM_fWma3ja0g | Doc Magrogan's Oyster House - West Chester | 3 | 114 |
uczmbBk5O3tYhGue13dCDg | New Orleans Spirit Tours | 4 | 38 |
n7AQvGvNHlmun3kqXeBKVQ | Roy's Appliance Service | 5 | 5 |
eYxGFkxo6m3SYGVTh5m2nQ | Big Boyz Toyz Motorcycle Rentals | 4.5 | 8 |
lOP3HxdUTaq0eXhwR_KC-w | Sweet Things Chocolates | 4 | 13 |
KWA2qtdwVEkMpd5soSKaGA | Publix Super Market | 3.5 | 7 |
gbN4RuUiiBxQ2GBFQ2p3Cw | Mr. Margarita | 5 | 7 |
B2qqjCl_BNNnXvWWfpFiLA | Pottery Barn Kids | 1.5 | 13 |
7PDi_iyik3jraDAzWwwR4Q | Chase JP Morgan Bank Credit Card Services | 1.5 | 111 |
8rb-3VYXE37IZix4yOdskw | Sharky's Sports Bar & Grill | 2.5 | 29 |
9Rww8yE6Dm4dSMEq09nwXg | Holly Nails & Spa | 4.5 | 16 |
aCDY7vXYMs54EbYuQScsnQ | 39 North Taproom & Grill | 4.5 | 25 |
-4dYswJy7SPcbcERvitmIg | Pathmark | 2.5 | 34 |
mFTaYsRDyeFaY2NDLfSaAA | River City Games | 4.5 | 5 |
x9K0RfZaT_zlw6DklBDzjw | Gavi Italian Restaurant | 3.5 | 9 |
pJfh3Ct8iL58NZa8ta-a5w | Top Shelf Sports Lounge | 4.5 | 95 |
cvP_vh_bOLbCY3eoY1Xw-A | Fishers Freedom Festival | 4.5 | 7 |
7clCBgNbd-x2Wj96lZ6Mjw | Bier Brewery and Tap Room | 4.5 | 139 |
ppFCk9aQkM338Rgwpl2F5A | Wawa | 3 | 56 |
NZ_bFJma7brQUfln5h1UAg | Super Sushi Kyo Hin | 3.5 | 6 |
eMjnw_7wp-CscyNh6Lu0ZA | AM&PM Locksmith | 4.5 | 58 |
IDtLPgUrqorrpqSLdfMhZQ | Helena Avenue Bakery | 4 | 389 |
sE6jSnvMts_MAn-b4OkMAw | K-9 Groom Room | 4 | 5 |
YNjyv0gfOr2g8lbmUpTnKg | Copper Vine | 4.5 | 350 |
LhpPSrulqVeTyJeK2xydvQ | Fresh Fruits & Salads | 4.5 | 6 |
oaboaRBUgGjbo2kfUIKDLQ | Mike's Ice Cream | 4.5 | 593 |
-ZXYcCyDjj1QimnJyGtYtg | Gilley's Antique Mall | 4.5 | 24 |
nUqrF-h9S7myCcvNDecOvw | Iron Horse Auto Body | 4.5 | 32 |
vR9_bhoszcpXbB_APv6Xlw | James Dant | 5 | 31 |
RK6-cJ9hj53RzOlCBmpT-g | Impasto | 5 | 5 |
ZM46RDLXaFNo_z6t-j_L4w | Absolutely Perfect Inc | 3.5 | 5 |
pEm4xNCk8d0TF6A1gi-WDQ | TKO DJs | 3.5 | 17 |
J_ksUDPpzPwfTGtI4zTRnQ | Riverview Room | 4.5 | 7 |
knQ4vIgx-r85kjlWVVjcpQ | Silver and Blue Outfitters | 4.5 | 5 |
U2Tzy6J9aAAg9pzXsgdkvg | Premier Mortgage Resources | 5 | 6 |
1MeIwdbTnZOBFCKOrgaxuw | Ricardo's Italian Cafe | 3.5 | 80 |
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