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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 ({'geolocation_zip_code_prefix', 'geolocation_lat', 'geolocation_state', 'geolocation_city', 'geolocation_lng'}) and 5 missing columns ({'customer_zip_code_prefix', 'customer_state', 'customer_id', 'customer_city', 'customer_unique_id'}). This happened while the csv dataset builder was generating data using hf://datasets/Keths/Said/olist_geolocation_dataset.csv (at revision 04765c9ce909701471f20244cb1b7e1c58f08137) 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 geolocation_zip_code_prefix: int64 geolocation_lat: double geolocation_lng: double geolocation_city: string geolocation_state: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 942 to {'customer_id': Value(dtype='string', id=None), 'customer_unique_id': Value(dtype='string', id=None), 'customer_zip_code_prefix': Value(dtype='int64', id=None), 'customer_city': Value(dtype='string', id=None), 'customer_state': Value(dtype='string', 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 1577, 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 1191, 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 5 new columns ({'geolocation_zip_code_prefix', 'geolocation_lat', 'geolocation_state', 'geolocation_city', 'geolocation_lng'}) and 5 missing columns ({'customer_zip_code_prefix', 'customer_state', 'customer_id', 'customer_city', 'customer_unique_id'}). This happened while the csv dataset builder was generating data using hf://datasets/Keths/Said/olist_geolocation_dataset.csv (at revision 04765c9ce909701471f20244cb1b7e1c58f08137) 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)
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customer_id
string | customer_unique_id
string | customer_zip_code_prefix
int64 | customer_city
string | customer_state
string |
---|---|---|---|---|
06b8999e2fba1a1fbc88172c00ba8bc7 | 861eff4711a542e4b93843c6dd7febb0 | 14,409 | franca | SP |
18955e83d337fd6b2def6b18a428ac77 | 290c77bc529b7ac935b93aa66c333dc3 | 9,790 | sao bernardo do campo | SP |
4e7b3e00288586ebd08712fdd0374a03 | 060e732b5b29e8181a18229c7b0b2b5e | 1,151 | sao paulo | SP |
b2b6027bc5c5109e529d4dc6358b12c3 | 259dac757896d24d7702b9acbbff3f3c | 8,775 | mogi das cruzes | SP |
4f2d8ab171c80ec8364f7c12e35b23ad | 345ecd01c38d18a9036ed96c73b8d066 | 13,056 | campinas | SP |
879864dab9bc3047522c92c82e1212b8 | 4c93744516667ad3b8f1fb645a3116a4 | 89,254 | jaragua do sul | SC |
fd826e7cf63160e536e0908c76c3f441 | addec96d2e059c80c30fe6871d30d177 | 4,534 | sao paulo | SP |
5e274e7a0c3809e14aba7ad5aae0d407 | 57b2a98a409812fe9618067b6b8ebe4f | 35,182 | timoteo | MG |
5adf08e34b2e993982a47070956c5c65 | 1175e95fb47ddff9de6b2b06188f7e0d | 81,560 | curitiba | PR |
4b7139f34592b3a31687243a302fa75b | 9afe194fb833f79e300e37e580171f22 | 30,575 | belo horizonte | MG |
9fb35e4ed6f0a14a4977cd9aea4042bb | 2a7745e1ed516b289ed9b29c7d0539a5 | 39,400 | montes claros | MG |
5aa9e4fdd4dfd20959cad2d772509598 | 2a46fb94aef5cbeeb850418118cee090 | 20,231 | rio de janeiro | RJ |
b2d1536598b73a9abd18e0d75d92f0a3 | 918dc87cd72cd9f6ed4bd442ed785235 | 18,682 | lencois paulista | SP |
eabebad39a88bb6f5b52376faec28612 | 295c05e81917928d76245e842748184d | 5,704 | sao paulo | SP |
1f1c7bf1c9b041b292af6c1c4470b753 | 3151a81801c8386361b62277d7fa5ecf | 95,110 | caxias do sul | RS |
206f3129c0e4d7d0b9550426023f0a08 | 21f748a16f4e1688a9014eb3ee6fa325 | 13,412 | piracicaba | SP |
a7c125a0a07b75146167b7f04a7f8e98 | 5c2991dbd08bbf3cf410713c4de5a0b5 | 22,750 | rio de janeiro | RJ |
c5c61596a3b6bd0cee5766992c48a9a1 | b6e99561fe6f34a55b0b7da92f8ed775 | 7,124 | guarulhos | SP |
9b8ce803689b3562defaad4613ef426f | 7f3a72e8f988c6e735ba118d54f47458 | 5,416 | sao paulo | SP |
49d0ea0986edde72da777f15456a0ee0 | 3e6fd6b2f0d499456a6a6820a40f2d79 | 68,485 | pacaja | PA |
154c4ded6991bdfa3cd249d11abf4130 | e607ede0e63436308660236f5a52da5e | 88,034 | florianopolis | SC |
690172ab319622688d3b4df42f676898 | a96d5cfa0d3181817e2b946f921ea021 | 74,914 | aparecida de goiania | GO |
2938121a40a20953c43caa8c98787fcb | 482441ea6a06b1f72fe9784756c0ea75 | 5,713 | sao paulo | SP |
237098a64674ae89babdc426746260fc | 4390ddbb6276a66ff1736a6710205dca | 82,820 | curitiba | PR |
cb721d7b4f271fd87011c4c83462c076 | a5844ba4bfc8d0cc61d13027c7e63bcc | 8,225 | sao paulo | SP |
f681356046d9fde60e70c73a18d65ea2 | 5f102dd37243f152aec3607970aad100 | 9,121 | santo andre | SP |
167bd30a409e3e4127df5a9408ebd394 | 9c0096673baf55453a50073f12d1a37f | 74,310 | goiania | GO |
6e359a57a91f84095cc64e1b351aef8c | 2e6a42a9b5cbb0da62988694f18ee295 | 4,571 | sao paulo | SP |
e0eea8f69a457b3f1fa246e44c9ebefd | 4d221875624017bc47b4d1ce7314a5b7 | 29,311 | cachoeiro de itapemirim | ES |
e3109970a3fe8021d5ff82c577ce5606 | a8654e2af5da6bb72f52c22b164855e1 | 5,528 | sao paulo | SP |
261cb4f92498ca05d5bd1a327a261d9c | 424aca6872c5bab80780a8dec03b7516 | 12,235 | sao jose dos campos | SP |
6f92779347724b67e44e3224f3b4cffd | bf4862777db128507e9efcc789215e9b | 18,130 | sao roque | SP |
2d5831cb2dff7cdefba62e950ae3dc7b | e9dd12dca17352644a959d9dea133935 | 42,800 | camacari | BA |
b2bed119388167a954382cca36c4777f | e079b18794454de9d2be5c12b4392294 | 27,525 | resende | RJ |
469634941c27cd844170935a3cf60b95 | ef07ba9aa5226f77264ffa5762b2280b | 81,750 | curitiba | PR |
df0aa5b8586495e0ddf6b601122e43a1 | 85d234692f7bee8d6fea586e237334b6 | 13,175 | sumare | SP |
41c8f4b570869791379a925899a6af8a | fe3634ccefbcdb0537b45fd589e32e8e | 7,170 | guarulhos | SP |
54f755c3fd2709231f9964a1430c5218 | 40febde16f4718a5def537786473b0be | 93,415 | novo hamburgo | RS |
4c06b42fbf7b97ab10779cda5549cd1c | 07d190f123147d9e89d4b922543d7948 | 65,075 | sao luis | MA |
b6368ca0f56d4632f44d58ca431487b2 | dd992305cba295d997f263dbdf4e8c2e | 88,104 | sao jose | SC |
4a0e66fd30684aa1409cd1b66fec77cc | 86085586aaa8c5f47ed0b400da64c59d | 7,176 | guarulhos | SP |
c168abb9077b7821adae01dc1f0886c5 | 5ad58a4e6a1a656b6bed070cadbaa003 | 35,960 | santa barbara | MG |
a3b0fda37bae14cf754877bed475e80c | c9158d089637ab443c78984d20da7fc0 | 5,727 | sao paulo | SP |
0ccd415657ae8a6cd1c71b00155a019e | 66cc90195ca44cc7ac6a1cd0e1e1e7b2 | 7,053 | guarulhos | SP |
c532a74a3ebf1bacce2e2bcce3783317 | 91ec50a00ae74d0a229d2efdf4344e1e | 14,026 | ribeirao preto | SP |
19cecb194f54e614b70d971306a9931b | d251c190ca75786e9ab937982d60d1d4 | 30,320 | belo horizonte | MG |
f34a6e874087ec1f0e3dab9fdf659c5d | 233896de79986082f1f479f1f85281cb | 38,300 | ituiutaba | MG |
c132855c926907970dcf6f2bf0b33a24 | a8ae36a2bb6c2bbc3b5d62ede131c9ef | 18,740 | taquarituba | SP |
df85b96ba2ce3e49bde101b1614f52ac | 8d46223c91cbeb93e0930ca8bd8ffca2 | 83,085 | sao jose dos pinhais | PR |
4d27341acd30a36bca39008ee9bb9050 | e021e698833bdeb89dfef3acb2e91f37 | 89,254 | jaragua do sul | SC |
d3b6830d18c7de943d1e707d1f061d40 | 27cf4b153010911a0957150255a6c6db | 5,351 | sao paulo | SP |
79de53946db384e2d7a9bd131792ad17 | 7ce5b57a120a2da6a804afa58ffcbfb5 | 39,406 | montes claros | MG |
a562ab1e728449e3461829dfe2e36f73 | d33eeadf54cb883e79be640f38c32cdc | 14,860 | barrinha | SP |
b64ed91eab98972150bdaf77ca921934 | 3da7750bf3c1dbd724624a60a9f5942b | 21,310 | rio de janeiro | RJ |
8247b5583327ab8be19f96e1fb82f77b | d85547cd859833520b311b4458a14c1c | 23,970 | parati | RJ |
8fcaa9368903f3a9a28aeaff28c14638 | 3af0b2f7654f613ff1527b997a2ac57e | 79,804 | dourados | MS |
a9b0d1c26105279e1b8edc63d06bd668 | 3d49f4455a3947c8dd7e972b3ad8cb76 | 5,017 | sao paulo | SP |
aa9f03ecd3728c9bd12e6d962c66c7cb | b03e9d9818ee170e9d6b983803c7d406 | 75,388 | trindade | GO |
230c0d740401730c7197d16376893525 | a302a693d5722d95984e6472150b9391 | 85,808 | cascavel | PR |
a905baa530258422594f1b05615bd225 | c80da60feddb7cf8325bd104032e314a | 60,140 | fortaleza | CE |
4fa19f7da692e6bf9602aaad3c372eda | a2b8841410cf77619574d311cd06fd5e | 72,270 | brasilia | DF |
03f846ad03437d864a8d2a22976dcafe | 7677c213007e9a6ec9267ea50b5ce5bc | 2,075 | sao paulo | SP |
de4e13fd7d6469c5ada77d0843c55e42 | 0c17f9ac28cbd7323f0f4043e9db5907 | 96,015 | pelotas | RS |
8276de07ef25225d412b8462d73f8664 | 332cf4e83e16004ba7dca932ce82475b | 90,010 | porto alegre | RS |
cc32707d2e2f7c92ab449f9b28154809 | 0d516ca029d6a28d5cfddd80b27a26dc | 22,440 | rio de janeiro | RJ |
a02f66c3af7b16eec19ddcd98b645fe3 | b3548d0cec408ae13d143bb4eeebaa6c | 13,323 | salto | SP |
26acee41e2f75689a5615892f06ea0bd | c3293e875ffb1116018edf76d24e52a2 | 30,190 | belo horizonte | MG |
f64cdee66599119324ce57a97e43700d | d89e05e2d23c3d8247aeecd07758004b | 13,212 | jundiai | SP |
7ab7a537b678b6dd73d825ff6ee7be9d | dad5018ffc0de85eb72f72575b552784 | 29,307 | cachoeiro de itapemirim | ES |
7300450cedf7e4c35c243c4a03c1e8a6 | 95700615deef776ed32faa08f0be634e | 12,280 | cacapava | SP |
4c7241af24b5344cb01fe687643de4fe | b157c176c3fe04914fde33f2dc8b878a | 60,336 | fortaleza | CE |
97e126f19a6f04b3462619f36862bcd2 | d4397835ae287e492b186d497099439a | 11,310 | sao vicente | SP |
6d27a9361e591da38c87a5e70253f3f2 | 76b029c87118a29f2e3de420f5ec2fa2 | 38,408 | uberlandia | MG |
6810c3dc47f641181fcc7f73275c3d19 | 7eaa86786b5955ab188db287f4726d79 | 37,720 | botelhos | MG |
b514422efcf14bef34858a0829bef189 | b436a108536c1dabbc1d3e808d782df9 | 24,431 | sao goncalo | RJ |
0aae2862f8eac77f10a34f44860720ac | cd076285a12f40041b32f5ad8c98699f | 5,890 | sao paulo | SP |
6c9a5923526346cbc0bd7bbd92269c01 | cf6d4152d758efc43910e0141ae5b912 | 3,733 | sao paulo | SP |
1b2cb35b19b40b61f953d32ea157b337 | 468d559ef2dcd2bea6d8db78959fb90f | 83,709 | araucaria | PR |
12d1b4294fef21016c9614eb31e55e15 | 7556f182460418cf30957e6ce377c674 | 11,347 | sao vicente | SP |
f6529ffebe6b3440d45d89604a4239ac | e5dbefdfdf3eff75c8e6cd655f128279 | 26,272 | nova iguacu | RJ |
8264e3518163dd09211870b24a5d741d | 67d21c8bea9d6017d1b124d3879dd815 | 5,415 | sao paulo | SP |
8392e3d4cfeec63f2a8bfea68bf1f91f | fd2d5fdb84e65fa6b54b98b0e2df5645 | 59,655 | areia branca | RN |
38d1cd89306128348ffdf4cc23f3a50a | d491a65a6ef3c04e145d37395996bad7 | 4,548 | sao paulo | SP |
91ec76836092bba85d11761078ed7bb5 | 6edd17d0a29e2d4057e694afee5eaa3b | 28,010 | campos dos goytacazes | RJ |
f9dfa0a2934ffbb22e66924952548be8 | bf6e263ffc1f89999827615522b0aa45 | 13,573 | sao carlos | SP |
5a3260cfde2a918b597dada7ddd247bb | 6d3f61e35d0422fd8cae65b1798784be | 2,175 | sao paulo | SP |
ee3a81b2771fec5f9e982cdb1b3a4804 | a9a77b4e25980b7ca58cb71f878abb27 | 37,500 | itajuba | MG |
784c407781aa34749a388c9283782b56 | eca666aec08df69fe31aa9a11d4a3302 | 90,670 | porto alegre | RS |
3f6ede29d4c69cd3316d2035b6cec1fb | 7a380cb5434e6b6b5b37d45bb99dbe8a | 9,890 | sao bernardo do campo | SP |
6bed27564bd99d78d09c1fac13da56fd | 463093247faa080167d77f2e6d1b297d | 13,321 | salto | SP |
670254dd2e886ffe621b3831afb47d7d | 914b142462685e3161cf3a9f4152a028 | 44,380 | cruz das almas | BA |
f7cb015ff73be957ee6a30e2577742c5 | e235442a956c524e6c141141171f5801 | 27,700 | vassouras | RJ |
ea2196dc456ba36fe4f6b81dca4867d4 | 4a4de987b37555970ffcc9608d858a72 | 44,033 | feira de santana | BA |
09241c552e9fe2420997a6c535e9d408 | 44e9a1246448bd68a2e3bf0f1966c57a | 4,537 | sao paulo | SP |
e50a30de3c32f9406a7185f40ce6874d | b4d6e1b900d99b52e901860bc1f44e35 | 71,540 | brasilia | DF |
f89c1a6b9c966869e441e55bc14acddc | 809353196a0456095716566dd226bb48 | 13,569 | sao carlos | SP |
23e96758fd640560e9b1fbcda90abfc4 | 9e1f719fe5b17b9c51905fee6d6385c1 | 5,565 | sao paulo | SP |
369708cabd9831ea6fde670a3b602a92 | 94b731a41867b47c3856e324840c4c99 | 3,636 | sao paulo | SP |
5f8b4882b5a4ec7bf6d2107e6cd0cf29 | 694cb45ff29b603ac2acd51016770097 | 24,120 | niteroi | RJ |
ad6891a1937cb8723a2c08ba1ae59873 | 9dbb05f5577e862337b93feb8f358839 | 65,058 | sao luis | MA |
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