Datasets:

vessl
/

ad-display_click-data_taobao.com

Dataset card Viewer Files Files and versions Community

Split (1)

train

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 ({'clk', 'time_stamp', 'nonclk', 'user', 'pid'}) and 5 missing columns ({'cate_id', 'brand', 'customer', 'campaign_id', 'price'}).

This happened while the csv dataset builder was generating data using

hf://datasets/vessl/ad-display_click-data_taobao.com/raw_sample.csv (at revision 5cc2d69eddfae69637fb7d953be2b61d14a40efa)

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
              user: int64
              time_stamp: int64
              adgroup_id: int64
              pid: string
              nonclk: int64
              clk: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 920
              to
              {'adgroup_id': Value(dtype='int64', id=None), 'cate_id': Value(dtype='int64', id=None), 'campaign_id': Value(dtype='int64', id=None), 'customer': Value(dtype='int64', id=None), 'brand': Value(dtype='float64', id=None), 'price': Value(dtype='float64', 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 5 new columns ({'clk', 'time_stamp', 'nonclk', 'user', 'pid'}) and 5 missing columns ({'cate_id', 'brand', 'customer', 'campaign_id', 'price'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/vessl/ad-display_click-data_taobao.com/raw_sample.csv (at revision 5cc2d69eddfae69637fb7d953be2b61d14a40efa)
              
              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.

adgroup_id int64	cate_id int64	campaign_id int64	customer int64	brand float64	price float64
63,133	6,406	83,237	1	95,471	170
313,401	6,406	83,237	1	87,331	199
248,909	392	83,237	1	32,233	38
208,458	392	83,237	1	174,374	139
110,847	7,211	135,256	2	145,952	32.99
607,788	6,261	387,991	6	207,800	199
375,706	4,520	387,991	6	null	99
11,115	7,213	139,747	9	186,847	33
24,484	7,207	139,744	9	186,847	19
28,589	5,953	395,195	13	null	428
23,236	5,953	395,195	13	null	368
300,556	5,953	395,195	13	null	639
92,560	5,953	395,195	13	null	368
590,965	4,284	28,145	14	454,237	249
529,913	4,284	70,206	14	null	249
546,930	4,284	28,145	14	null	249
639,794	6,261	70,206	14	37,004	89.9
335,413	4,284	28,145	14	null	249
794,890	4,284	70,206	14	454,237	249
684,020	6,261	70,206	14	37,004	99
500,333	5,515	70,206	14	null	69.9
479,319	4,284	70,206	14	null	249
372,438	4,284	70,206	14	null	249
382,843	4,284	70,206	14	null	249
379,665	4,284	70,206	14	null	239
715,831	4,280	70,206	14	null	59
296,360	5,515	70,206	14	null	39.9
419,844	5,515	28,145	14	247,861	75
279,841	917	8,184	15	57,034	1.88
74,914	8,863	177,913	19	83,039	10
73,381	6,159	177,913	19	376,948	12.5
203,644	6,026	177,913	19	null	9
150,738	7,395	177,913	19	432,071	21
35,032	6,261	83,264	20	457,502	668
592,998	8,993	83,266	21	72,959	48
631,409	6,181	83,266	21	72,959	368
62,924	10,956	83,271	24	417,253	11.5
8,451	1,652	83,271	24	278,112	15
141,441	8,197	83,271	24	null	8.8
688,282	8,179	422,189	32	null	45
401,736	5,285	289,503	34	164,272	76
401,735	10,479	289,503	34	164,272	698
401,759	10,479	289,503	34	null	220
384,495	5,285	289,503	34	164,272	94
370,209	10,479	289,503	34	164,272	450
384,521	10,479	289,503	34	null	430
380,685	10,479	289,503	34	383,766	360
57,396	6,564	137,334	39	125,151	39
469,820	4,613	83,298	42	375,268	10
232,298	4,613	83,298	42	400,172	20
7,459	4,613	83,298	42	400,172	360
196,498	4,613	83,298	42	400,172	266
217,341	4,613	83,298	42	400,172	198
297,127	6,955	318,659	46	108,957	1,185
401,889	4,284	318,659	46	255,785	369
405,701	8,111	318,659	46	108,957	50
422,973	4,284	318,659	46	255,785	399
422,974	4,284	318,659	46	255,785	429
405,615	6,261	318,659	46	108,957	499
401,811	6,261	318,659	46	108,957	599
405,616	6,261	318,659	46	301,254	699
389,425	4,281	318,659	46	255,785	50
576,558	4,284	83,308	47	74,078	110
51,535	4,284	83,308	47	74,078	98
376,383	4,284	83,308	47	74,078	98
464,521	4,282	83,308	47	null	130
3,681	5,199	408,101	51	97,566	65
712,009	7,962	315,907	53	null	5,999
58,881	7,209	155,966	54	349,743	1,600
308,744	7,209	155,966	54	null	878
141,629	7,209	155,966	54	310,550	600
686,089	6,937	404,062	59	115,491	799
414,843	6,937	309,598	59	63,272	499
785,062	6,937	83,339	59	115,491	799
597,103	6,937	319,166	59	125,038	699
832,820	4,292	162,111	60	295,193	276
783,981	4,292	162,111	60	295,193	276
832,945	4,292	162,111	60	295,193	158
754,747	4,292	162,111	60	295,193	296
514,810	4,502	83,347	62	null	20,000
218,523	4,502	257,310	62	null	40,000
216,123	6,640	251,637	62	null	51,800
165,521	4,502	83,347	62	null	40,000
155,501	6,640	257,310	62	null	51,800
231,961	12	83,349	63	114,512	349
208,158	12	83,349	63	114,512	359
273,414	12	83,349	63	58,175	190
599,798	8,113	83,367	68	null	45
263,507	8,929	205,399	69	406,808	58
2,892	6,800	205,399	69	434,904	17.4
40,010	7,822	77,444	69	406,808	68
157,414	5,363	17,759	71	370,950	70
8,290	10,885	13,914	72	null	138
8,297	5,874	13,914	72	193,697	90
110,394	4,833	13,914	72	409,312	90
8,105	6,814	13,914	72	null	532
8,331	10,885	13,914	72	205,431	138
63,603	6,814	83,371	72	null	532
338,430	6,142	140,936	74	null	130
393,006	4,505	328,771	74	null	130

End of preview.