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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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