Datasets:

---

Kenion31

/

ITProject

like 0

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 13 new columns ({'l1_category_id', 'l0_category_id', 'l0_category', 'l2_category_id', 'product_id', 'brand_name', 'l1_category', 'unit', 'product_type', 'manufacturer_name', 'category_flag', 'l2_category', 'product_name'}) and 47 missing columns ({'unique_l1_categories', 'top_brand_1', 'total_quantity', 'unique_l2_categories', 'is_churned', 'avg_days_between_orders', 'std_days_between_orders', 'monetary_score', 'customer_lifetime_days', 'first_purchase', 'avg_discount_per_order', 'avg_order_value', 'unique_cities_shopped', 'max_days_between_orders', 'total_revenue', 'rfm_segment', 'top_product_3', 'avg_quantity_per_order', 'top_brand_2', 'avg_item_value', 'unique_products', 'category_focus_score', 'brand_loyalty_score', 'total_orders', 'top_brand_3', 'top_product_2', 'last_purchase', 'top_product_1', 'avg_profit_per_order', 'total_profit', 'total_transactions', 'min_days_between_orders', 'customer_id', 'product_repurchase_rate', 'top_category_2', 'revenue_per_order_std', 'frequency_score', 'most_frequent_purchase_day', 'recency_score', 'top_category_3', 'unique_brands', 'customer_tenure_days', 'pct_weekend_orders', 'recency_days', 'unique_l0_categories', 'profit_per_order_std', 'top_category_1'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Kenion31/ITProject/products_cleaned.csv (at revision 068d19add1cbcbb2de9cb4622d83ce2cf4e26ea3)

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 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              product_id: int64
              product_name: string
              unit: string
              product_type: string
              brand_name: string
              manufacturer_name: string
              l0_category: string
              l1_category: string
              l2_category: string
              l0_category_id: int64
              l1_category_id: int64
              l2_category_id: int64
              category_flag: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1857
              to
              {'customer_id': Value('int64'), 'is_churned': Value('int64'), 'total_revenue': Value('float64'), 'total_profit': Value('float64'), 'total_quantity': Value('int64'), 'total_orders': Value('int64'), 'total_transactions': Value('int64'), 'first_purchase': Value('string'), 'last_purchase': Value('string'), 'avg_order_value': Value('float64'), 'avg_item_value': Value('float64'), 'avg_profit_per_order': Value('float64'), 'recency_days': Value('int64'), 'customer_lifetime_days': Value('int64'), 'customer_tenure_days': Value('int64'), 'avg_days_between_orders': Value('float64'), 'std_days_between_orders': Value('float64'), 'max_days_between_orders': Value('float64'), 'min_days_between_orders': Value('float64'), 'revenue_per_order_std': Value('float64'), 'profit_per_order_std': Value('float64'), 'pct_weekend_orders': Value('float64'), 'most_frequent_purchase_day': Value('int64'), 'unique_cities_shopped': Value('int64'), 'avg_discount_per_order': Value('float64'), 'avg_quantity_per_order': Value('float64'), 'unique_products': Value('int64'), 'unique_brands': Value('int64'), 'unique_l0_categories': Value('int64'), 'unique_l1_categories': Value('int64'), 'unique_l2_categories': Value('int64'), 'product_repurchase_rate': Value('float64'), 'brand_loyalty_score': Value('float64'), 'category_focus_score': Value('float64'), 'top_product_1': Value('float64'), 'top_product_2': Value('float64'), 'top_product_3': Value('float64'), 'top_brand_1': Value('string'), 'top_brand_2': Value('string'), 'top_brand_3': Value('string'), 'top_category_1': Value('string'), 'top_category_2': Value('string'), 'top_category_3': Value('string'), 'recency_score': Value('int64'), 'frequency_score': Value('int64'), 'monetary_score': Value('int64'), 'rfm_segment': Value('int64')}
              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 1334, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 911, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, 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 1833, 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 13 new columns ({'l1_category_id', 'l0_category_id', 'l0_category', 'l2_category_id', 'product_id', 'brand_name', 'l1_category', 'unit', 'product_type', 'manufacturer_name', 'category_flag', 'l2_category', 'product_name'}) and 47 missing columns ({'unique_l1_categories', 'top_brand_1', 'total_quantity', 'unique_l2_categories', 'is_churned', 'avg_days_between_orders', 'std_days_between_orders', 'monetary_score', 'customer_lifetime_days', 'first_purchase', 'avg_discount_per_order', 'avg_order_value', 'unique_cities_shopped', 'max_days_between_orders', 'total_revenue', 'rfm_segment', 'top_product_3', 'avg_quantity_per_order', 'top_brand_2', 'avg_item_value', 'unique_products', 'category_focus_score', 'brand_loyalty_score', 'total_orders', 'top_brand_3', 'top_product_2', 'last_purchase', 'top_product_1', 'avg_profit_per_order', 'total_profit', 'total_transactions', 'min_days_between_orders', 'customer_id', 'product_repurchase_rate', 'top_category_2', 'revenue_per_order_std', 'frequency_score', 'most_frequent_purchase_day', 'recency_score', 'top_category_3', 'unique_brands', 'customer_tenure_days', 'pct_weekend_orders', 'recency_days', 'unique_l0_categories', 'profit_per_order_std', 'top_category_1'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Kenion31/ITProject/products_cleaned.csv (at revision 068d19add1cbcbb2de9cb4622d83ce2cf4e26ea3)
              
              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)