Buckets:
| license: apache-2.0 | |
| task_categories: | |
| - text-classification | |
| - feature-extraction | |
| language: | |
| - en | |
| tags: | |
| - finance | |
| - Company documents | |
| pretty_name: northwind PurchaseOrders | |
| #### Purchase Orders Dataset | |
| This dataset consists of purchase orders from various companies. It was created by [CHERGUELAINE Ayoub](https://www.linkedin.com/in/ayoub-cherguelaine/) & [BOUBEKRI Faycal](https://www.linkedin.com/in/faycal-boubekri-832848199/) with the help of ChatGPT for the purpose of document classification and analytics. | |
| # Description | |
| The dataset contains a collection of purchase orders from different companies. Each purchase order consists of the following fields: | |
| order_id: The unique identifier for the purchase order. | |
| order_date: The date on which the purchase order was placed. | |
| customer_name: The name of the customer who placed the purchase order. | |
| products: A list of products ordered in the purchase order. Each product contains the following fields: | |
| product_id: The unique identifier for the product. | |
| product : The name of the product ordered | |
| quantity: The quantity of the product ordered. | |
| unit_price: The price per unit of the product. | |
| The dataset is provided in PDF format and can be used for document classification and analytics tasks. | |
| # Format | |
| The dataset is provided in a zip file that contains the following files: | |
| purchase_orders.pdf: A PDF file containing the purchase orders. | |
| purchase_orders.csv: A CSV file containing the purchase orders in tabular format. | |
| # License | |
| You are free to share and adapt this dataset for any purpose, provided that you give appropriate credit, provide a link to the license, and indicate if changes were made. | |
| # Acknowledgments | |
| We would like to acknowledge the Northwind database for providing the source data for this dataset. We would also like to thank ChatGPT for their assistance in creating this dataset. | |
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- 1.87 kB
- Xet hash:
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