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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 4 new columns ({'name', 'product_id', 'date', 'sales_volume'}) and 4 missing columns ({'hierarchy', 'category', 'weight', 'parent_id'}).
This happened while the csv dataset builder was generating data using
zip://prices.csv::/tmp/hf-datasets-cache/medium/datasets/17724936252140-config-parquet-and-info-winea724-quanttide-cpi-da-0165f833/hub/datasets--winea724--quanttide-cpi-data/snapshots/f554402a3860c7563f8d97ea61e614df2202ff2a/cpi_data.zip, [/tmp/hf-datasets-cache/medium/datasets/17724936252140-config-parquet-and-info-winea724-quanttide-cpi-da-0165f833/hub/datasets--winea724--quanttide-cpi-data/snapshots/f554402a3860c7563f8d97ea61e614df2202ff2a/cpi_data.zip (origin=hf://datasets/winea724/quanttide-cpi-data@f554402a3860c7563f8d97ea61e614df2202ff2a/cpi_data.zip)]
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
product_id: int64
date: string
price: double
sales_volume: int64
category_id: int64
name: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 947
to
{'category_id': Value('int64'), 'category': Value('string'), 'hierarchy': Value('int64'), 'weight': Value('float64'), 'price': Value('float64'), 'parent_id': Value('float64')}
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 1347, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, 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 4 new columns ({'name', 'product_id', 'date', 'sales_volume'}) and 4 missing columns ({'hierarchy', 'category', 'weight', 'parent_id'}).
This happened while the csv dataset builder was generating data using
zip://prices.csv::/tmp/hf-datasets-cache/medium/datasets/17724936252140-config-parquet-and-info-winea724-quanttide-cpi-da-0165f833/hub/datasets--winea724--quanttide-cpi-data/snapshots/f554402a3860c7563f8d97ea61e614df2202ff2a/cpi_data.zip, [/tmp/hf-datasets-cache/medium/datasets/17724936252140-config-parquet-and-info-winea724-quanttide-cpi-da-0165f833/hub/datasets--winea724--quanttide-cpi-data/snapshots/f554402a3860c7563f8d97ea61e614df2202ff2a/cpi_data.zip (origin=hf://datasets/winea724/quanttide-cpi-data@f554402a3860c7563f8d97ea61e614df2202ff2a/cpi_data.zip)]
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.
category_id int64 | category string | hierarchy int64 | weight float64 | price null | parent_id null |
|---|---|---|---|---|---|
1,101,000,000 | 食品 | 1 | 0.1869 | null | null |
1,102,000,000 | 烟酒及用品 | 1 | 0.0191 | null | null |
1,103,000,000 | 衣着 | 1 | 0.1639 | null | null |
1,104,000,000 | 家庭设备用品及维修服务 | 1 | 0.1102 | null | null |
1,105,000,000 | 医疗保健和个人用品 | 1 | 0.1728 | null | null |
1,106,000,000 | 交通和通信 | 1 | 0.0981 | null | null |
1,107,000,000 | 娱乐教育文化用品及服务 | 1 | 0.159 | null | null |
1,108,000,000 | 居住 | 1 | 0.09 | null | null |
1,101,010,000 | 粮食 | 2 | 0.0075 | null | null |
1,101,020,000 | 淀粉 | 2 | 0.007 | null | null |
1,101,030,000 | 干豆类及豆制品 | 2 | 0.0051 | null | null |
1,101,040,000 | 油脂 | 2 | 0.0036 | null | null |
1,101,050,000 | 肉禽及其制品 | 2 | 0.0415 | null | null |
1,101,060,000 | 蛋 | 2 | 0.0044 | null | null |
1,101,070,000 | 水产品 | 2 | 0.0035 | null | null |
1,101,080,000 | 菜 | 2 | 0.0128 | null | null |
1,101,090,000 | 调味品 | 2 | 0.0143 | null | null |
1,101,100,000 | 糖 | 2 | 0.022 | null | null |
1,101,110,000 | 茶及饮料 | 2 | 0.0147 | null | null |
1,101,120,000 | 干鲜瓜果 | 2 | 0.0159 | null | null |
1,101,130,000 | 糕点饼干面包 | 2 | 0.0149 | null | null |
1,101,140,000 | 液体乳及乳制品 | 2 | 0.0122 | null | null |
1,101,150,000 | 在外用膳食品 | 2 | 0.0075 | null | null |
1,102,010,000 | 烟草 | 2 | 0.0093 | null | null |
1,102,020,000 | 酒 | 2 | 0.0052 | null | null |
1,102,030,000 | 吸烟、饮酒用品 | 2 | 0.0046 | null | null |
1,103,010,000 | 服 装 | 2 | 0.1151 | null | null |
1,103,020,000 | 衣着材料 | 2 | 0.0098 | null | null |
1,103,030,000 | 鞋袜帽 | 2 | 0.0298 | null | null |
1,103,040,000 | 衣着加工服务 | 2 | 0.0092 | null | null |
1,104,010,000 | 耐用消费品 | 2 | 0.0541 | null | null |
1,104,020,000 | 室内装饰品 | 2 | 0.0153 | null | null |
1,104,030,000 | 床上用品 | 2 | 0.0127 | null | null |
1,104,040,000 | 家庭日用杂品 | 2 | 0.0221 | null | null |
1,104,050,000 | 家庭服务及加工维修服务 | 2 | 0.006 | null | null |
1,105,010,000 | 医疗保健 | 2 | 0.0958 | null | null |
1,105,020,000 | 个人用品及服务 | 2 | 0.077 | null | null |
1,106,010,000 | 交通 | 2 | 0.0691 | null | null |
1,106,020,000 | 通信 | 2 | 0.029 | null | null |
1,107,010,000 | 文娱用耐用消费品及服务 | 2 | 0.0362 | null | null |
1,107,020,000 | 教育 | 2 | 0.0314 | null | null |
1,107,030,000 | 文化娱乐 | 2 | 0.0833 | null | null |
1,107,040,000 | 旅游 | 2 | 0.0081 | null | null |
1,108,010,000 | 建房及装修材料 | 2 | 0.0425 | null | null |
1,108,020,000 | 租房 | 2 | 0.0066 | null | null |
1,108,030,000 | 自有住房 | 2 | 0.0179 | null | null |
1,108,040,000 | 水、电、燃料 | 2 | 0.023 | null | null |
1,101,010,001 | 大米 | 3 | 0.0061 | null | null |
1,101,010,002 | 面粉 | 3 | 0.0011 | null | null |
1,101,010,003 | 粮食制品 | 3 | 0.0003 | null | null |
1,101,020,001 | 淀 粉 | 3 | 0.007 | null | null |
1,101,030,001 | 干 豆 | 3 | 0.0027 | null | null |
1,101,030,002 | 豆 制 品 | 3 | 0.0024 | null | null |
1,101,040,001 | 食用植物油 | 3 | 0.0022 | null | null |
1,101,040,002 | 植物油制品 | 3 | 0.0014 | null | null |
1,101,050,101 | 猪 肉 | 3 | 0.007 | null | null |
1,101,050,102 | 牛 肉 | 3 | 0.001 | null | null |
1,101,050,103 | 羊 肉 | 3 | 0.0064 | null | null |
1,101,050,104 | 畜肉副产品 | 3 | 0.007 | null | null |
1,101,050,201 | 鸡 | 3 | 0.0084 | null | null |
1,101,050,202 | 鸭 | 3 | 0.0052 | null | null |
1,101,050,301 | 畜肉制品 | 3 | 0.0009 | null | null |
1,101,050,302 | 禽制品 | 3 | 0.0056 | null | null |
1,101,060,001 | 鲜蛋 | 3 | 0.004 | null | null |
1,101,060,002 | 蛋 制 品 | 3 | 0.0004 | null | null |
1,101,070,101 | 淡水鱼 | 3 | 0.0004 | null | null |
1,101,070,102 | 海水鱼 | 3 | 0.001 | null | null |
1,101,070,201 | 虾 蟹 类 | 3 | 0.0021 | null | null |
1,101,080,001 | 鲜菜 | 3 | 0.0023 | null | null |
1,101,080,002 | 干菜及菜制品 | 3 | 0.0048 | null | null |
1,101,080,003 | 薯类 | 3 | 0.0057 | null | null |
1,101,090,001 | 盐 | 3 | 0.0003 | null | null |
1,101,090,002 | 酱油 | 3 | 0.0053 | null | null |
1,101,090,003 | 醋 | 3 | 0.0019 | null | null |
1,101,090,004 | 味精 | 3 | 0.0068 | null | null |
1,101,100,001 | 食糖 | 3 | 0.0062 | null | null |
1,101,100,002 | 糖果 | 3 | 0.0066 | null | null |
1,101,100,003 | 巧克力制品 | 3 | 0.0052 | null | null |
1,101,100,004 | 糖类小食品 | 3 | 0.004 | null | null |
1,101,110,101 | 茶叶 | 3 | 0.0021 | null | null |
1,101,110,200 | 固体饮料 | 3 | 0.0043 | null | null |
1,101,110,202 | 液体饮料 | 3 | 0.0056 | null | null |
1,101,110,203 | 冷冻饮品 | 3 | 0.0027 | null | null |
1,101,120,001 | 鲜瓜果 | 3 | 0.0077 | null | null |
1,101,120,002 | 干果 | 3 | 0.0082 | null | null |
1,101,130,001 | 糕点 | 3 | 0.0001 | null | null |
1,101,130,002 | 饼干 | 3 | 0.0072 | null | null |
1,101,130,003 | 面包 | 3 | 0.0076 | null | null |
1,101,140,001 | 巴氏杀菌奶或消毒奶 | 3 | 0.0016 | null | null |
1,101,140,002 | 酸奶 | 3 | 0.0066 | null | null |
1,101,140,003 | 奶粉 | 3 | 0.004 | null | null |
1,101,150,001 | 主食 | 3 | 0.0033 | null | null |
1,101,150,002 | 炒 菜 | 3 | 0.0027 | null | null |
1,101,150,003 | 地方小吃 | 3 | 0.0015 | null | null |
1,102,010,001 | 国产卷烟 | 3 | 0.0021 | null | null |
1,102,010,002 | 进口卷烟 | 3 | 0.0072 | null | null |
1,102,020,001 | 白酒 | 3 | 0.0032 | null | null |
1,102,020,002 | 葡萄酒 | 3 | 0.001 | null | null |
1,102,020,003 | 啤酒 | 3 | 0.001 | null | null |
1,102,030,001 | 吸烟用品 | 3 | 0.0036 | null | null |
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