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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 6 new columns ({'Low', 'Date', 'Adj.Close', 'Open', 'High', 'Volume'}) and 6 missing columns ({'close_last', 'open', 'volume', 'low', 'high', 'date'}).
This happened while the csv dataset builder was generating data using
hf://datasets/nateraw/airbnb-stock-price-new/Airbnb.csv (at revision 0ff369182bf7a0741f776cff044abdf354baa589)
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
Date: string
Adj.Close: double
Volume: double
Open: double
High: double
Low: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 926
to
{'date': Value(dtype='string', id=None), 'close_last': Value(dtype='float64', id=None), 'volume': Value(dtype='int64', id=None), 'open': Value(dtype='float64', id=None), 'high': Value(dtype='float64', id=None), 'low': 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 6 new columns ({'Low', 'Date', 'Adj.Close', 'Open', 'High', 'Volume'}) and 6 missing columns ({'close_last', 'open', 'volume', 'low', 'high', 'date'}).
This happened while the csv dataset builder was generating data using
hf://datasets/nateraw/airbnb-stock-price-new/Airbnb.csv (at revision 0ff369182bf7a0741f776cff044abdf354baa589)
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.
date
string | close_last
float64 | volume
int64 | open
float64 | high
float64 | low
float64 |
|---|---|---|---|---|---|
08-19-2022
| 114.76
| 5,288,830
| 118.18
| 119.22
| 114.1
|
08-18-2022
| 121.27
| 3,373,946
| 121.5
| 122.2
| 120.28
|
08-17-2022
| 121.87
| 4,336,182
| 121.63
| 123.27
| 120.64
|
08-16-2022
| 124.18
| 4,371,514
| 124.23
| 125.42
| 122.62
|
08-15-2022
| 126.04
| 4,884,711
| 123.55
| 126.43
| 123.2
|
08-12-2022
| 124.51
| 5,012,478
| 122.8
| 125
| 121.12
|
08-11-2022
| 121.5
| 8,110,104
| 121.3
| 127.09
| 120.96
|
08-10-2022
| 118.73
| 5,529,014
| 119.33
| 120.34
| 116.3
|
08-09-2022
| 114.44
| 4,201,213
| 115
| 115.67
| 112.8
|
08-08-2022
| 115.82
| 5,382,935
| 118.16
| 119.64
| 115.43
|
08-05-2022
| 117.11
| 6,494,951
| 115.52
| 118.87
| 114.82
|
08-04-2022
| 119.22
| 9,180,317
| 114.31
| 119.24
| 114.26
|
08-03-2022
| 115.02
| 23,354,940
| 108.23
| 115.57
| 107.65
|
08-02-2022
| 116.34
| 15,208,220
| 111.67
| 117.78
| 111.1
|
08-01-2022
| 111.2
| 6,019,506
| 110
| 113.96
| 107.48
|
07-29-2022
| 110.98
| 4,637,779
| 108.2
| 111.16
| 107.11
|
07-28-2022
| 108.84
| 4,471,883
| 108.17
| 110.06
| 104.68
|
07-27-2022
| 107.36
| 5,362,726
| 105.79
| 107.99
| 104.06
|
07-26-2022
| 101.91
| 4,190,993
| 102.38
| 103.63
| 101.1
|
07-25-2022
| 104.95
| 3,142,931
| 103.78
| 105.26
| 101.48
|
07-22-2022
| 103.97
| 4,243,932
| 108.31
| 110.1
| 102.93
|
07-21-2022
| 108.14
| 4,284,851
| 106.98
| 108.5
| 104.41
|
07-20-2022
| 107.73
| 6,834,133
| 103.11
| 108.92
| 102.75
|
07-19-2022
| 102.2
| 5,603,808
| 99.7
| 102.71
| 98.76
|
07-18-2022
| 97.67
| 7,171,484
| 96.78
| 101.88
| 95.98
|
07-15-2022
| 94.66
| 7,497,187
| 92.55
| 95.65
| 90.66
|
07-14-2022
| 91.05
| 8,334,633
| 94.28
| 94.58
| 90.17
|
07-13-2022
| 95.64
| 6,967,800
| 93.75
| 96.59
| 91.61
|
07-12-2022
| 96.55
| 4,170,185
| 95.3
| 97.69
| 93.32
|
07-11-2022
| 95.1
| 6,043,682
| 96
| 97.09
| 93.27
|
07-08-2022
| 97.35
| 5,669,474
| 96.23
| 98.12
| 93.24
|
07-07-2022
| 97.5
| 7,480,538
| 93.66
| 97.55
| 92.16
|
07-06-2022
| 92.88
| 5,702,961
| 95.29
| 96.17
| 91.8
|
07-05-2022
| 95.94
| 7,653,996
| 88.88
| 96.01
| 86.75
|
07-01-2022
| 91.41
| 5,995,434
| 89.09
| 91.46
| 87.43
|
06-30-2022
| 89.08
| 9,007,783
| 92.49
| 92.91
| 86.71
|
06-29-2022
| 93.93
| 6,522,572
| 96.83
| 97
| 92.05
|
06-28-2022
| 97.53
| 7,747,662
| 103.34
| 105.45
| 97.09
|
06-27-2022
| 101.5
| 7,352,143
| 103.96
| 104.17
| 99.33
|
06-24-2022
| 103.51
| 28,797,400
| 97.52
| 104.18
| 96.33
|
06-23-2022
| 95.72
| 12,340,820
| 100
| 100.8
| 93.02
|
06-22-2022
| 99.53
| 8,986,027
| 99
| 102.5
| 98.72
|
06-21-2022
| 102.27
| 6,532,713
| 102.69
| 104.89
| 101.62
|
06-17-2022
| 99.49
| 11,293,110
| 93.53
| 100.61
| 93.53
|
06-16-2022
| 93.26
| 9,435,656
| 96.19
| 97.5
| 92.09
|
06-15-2022
| 101.47
| 6,260,439
| 100.02
| 103.65
| 98.92
|
06-14-2022
| 98.87
| 5,915,344
| 99.54
| 101.35
| 97.2
|
06-13-2022
| 98.93
| 9,587,311
| 102.85
| 105.33
| 98.36
|
06-10-2022
| 108.91
| 6,941,056
| 111.8
| 115.13
| 108.32
|
06-09-2022
| 115.72
| 5,315,873
| 122.31
| 122.98
| 115.42
|
06-08-2022
| 123.77
| 3,775,619
| 121.43
| 125.51
| 121.23
|
06-07-2022
| 122.9
| 3,331,236
| 119.76
| 123.91
| 119.12
|
06-06-2022
| 122.02
| 4,160,239
| 123.33
| 124.18
| 119.92
|
06-03-2022
| 119.83
| 4,584,611
| 118.07
| 121.5
| 117.56
|
06-02-2022
| 121.26
| 5,177,244
| 117.13
| 123
| 116.27
|
06-01-2022
| 116.72
| 6,879,606
| 121.05
| 121.07
| 114.4
|
05-31-2022
| 120.87
| 9,117,555
| 120.5
| 122.3
| 117.16
|
05-27-2022
| 120.5
| 7,391,500
| 116
| 120.7
| 115.77
|
05-26-2022
| 114.3
| 6,883,200
| 109.74
| 115.55
| 108.11
|
05-25-2022
| 110.4
| 6,203,324
| 105.89
| 111.94
| 104.97
|
05-24-2022
| 106.24
| 6,415,752
| 111.28
| 111.42
| 103.74
|
05-23-2022
| 113.28
| 6,000,751
| 113.55
| 115.15
| 110.93
|
05-20-2022
| 112.55
| 6,961,860
| 115.46
| 116.25
| 108.5
|
05-19-2022
| 114.17
| 8,926,616
| 108.18
| 116.35
| 107.45
|
05-18-2022
| 108.03
| 9,718,744
| 116.11
| 117.04
| 107.62
|
05-17-2022
| 117.5
| 6,962,904
| 119.97
| 120.18
| 114.51
|
05-16-2022
| 114.44
| 7,588,370
| 121
| 121.07
| 113.25
|
05-13-2022
| 121.45
| 8,595,379
| 119.96
| 123.29
| 118.82
|
05-12-2022
| 115.94
| 9,264,303
| 113.66
| 120.49
| 111.22
|
05-11-2022
| 116.15
| 13,661,360
| 114.53
| 123.77
| 112.37
|
05-10-2022
| 116.13
| 13,638,470
| 122.95
| 123.46
| 113.53
|
05-09-2022
| 119.37
| 14,430,890
| 131.76
| 131.89
| 118.83
|
05-06-2022
| 135.84
| 9,573,058
| 142.7
| 143.11
| 133.04
|
05-05-2022
| 143.09
| 11,367,230
| 152.19
| 153.88
| 140.86
|
05-04-2022
| 156.18
| 20,598,070
| 152.55
| 158.74
| 145.87
|
05-03-2022
| 145
| 16,774,660
| 154.09
| 154.49
| 141.58
|
05-02-2022
| 152.78
| 5,945,287
| 153.21
| 155.13
| 147.21
|
04-29-2022
| 153.21
| 4,033,057
| 158.88
| 163.24
| 153
|
04-28-2022
| 159.74
| 4,854,490
| 154.01
| 161.26
| 153.66
|
04-27-2022
| 152.23
| 4,825,954
| 153.82
| 157.3
| 150.44
|
04-26-2022
| 153.04
| 4,075,004
| 158.4
| 159.2
| 152.8
|
04-25-2022
| 158.39
| 3,868,115
| 154.33
| 159.79
| 152.1
|
04-22-2022
| 156.09
| 3,863,419
| 157.84
| 161.67
| 154.78
|
04-21-2022
| 157.91
| 4,714,572
| 168.98
| 170.93
| 156.68
|
04-20-2022
| 164.55
| 3,997,912
| 172.61
| 172.61
| 164.31
|
04-19-2022
| 170.12
| 2,857,124
| 165.74
| 170.82
| 165.71
|
04-18-2022
| 165.74
| 3,339,887
| 169.27
| 170.12
| 164.35
|
04-14-2022
| 170.7
| 5,125,142
| 171.66
| 174.64
| 170.3
|
04-13-2022
| 171.85
| 7,211,893
| 160.84
| 172.96
| 160.65
|
04-12-2022
| 160.11
| 4,113,036
| 163.7
| 166.11
| 157.28
|
04-11-2022
| 160.25
| 3,877,215
| 159.84
| 163.57
| 157.41
|
04-08-2022
| 162.56
| 3,448,377
| 162.52
| 164.9
| 159.35
|
04-07-2022
| 165.91
| 4,146,557
| 163.19
| 167.86
| 161.71
|
04-06-2022
| 164.66
| 4,287,691
| 167.05
| 168.77
| 161.58
|
04-05-2022
| 171.21
| 4,064,959
| 177.19
| 179.09
| 170.12
|
04-04-2022
| 177.02
| 3,500,522
| 175.02
| 177.02
| 172.59
|
04-01-2022
| 173.07
| 3,644,935
| 173.06
| 177.94
| 172.23
|
03-31-2022
| 171.76
| 3,232,222
| 173.54
| 176.15
| 171.16
|
03-30-2022
| 173.63
| 3,707,406
| 173.13
| 176.82
| 172.02
|
03-29-2022
| 175.52
| 5,452,762
| 172.11
| 178.88
| 171.81
|
End of preview.
Dataset Card for Airbnb Stock Price
Dataset Summary
This contains the historical stock price of Airbnb (ticker symbol ABNB) an American company that operates an online marketplace for lodging, primarily homestays for vacation rentals, and tourism activities. Based in San Francisco, California, the platform is accessible via website and mobile app.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
This dataset was shared by @evangower
Licensing Information
The license for this dataset is cc0-1.0
Citation Information
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Contributions
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