Dataset Preview
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 3 new columns ({'price', 'category', 'name'}) and 4 missing columns ({'quantity', 'order_date', 'customer_id', 'order_id'}).
This happened while the csv dataset builder was generating data using
hf://datasets/rudrakshrakeshzodage/Product_Orders_data/updated_products.csv (at revision b7af6d2109b59969eae454b4a9d7d09fa6290aa7), ['hf://datasets/rudrakshrakeshzodage/Product_Orders_data@b7af6d2109b59969eae454b4a9d7d09fa6290aa7/updated_orders.csv', 'hf://datasets/rudrakshrakeshzodage/Product_Orders_data@b7af6d2109b59969eae454b4a9d7d09fa6290aa7/updated_products.csv']
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/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/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/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
product_id: int64
name: string
category: string
price: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 731
to
{'order_id': Value('int64'), 'customer_id': Value('int64'), 'product_id': Value('int64'), 'quantity': Value('int64'), 'order_date': Value('string')}
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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
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 3 new columns ({'price', 'category', 'name'}) and 4 missing columns ({'quantity', 'order_date', 'customer_id', 'order_id'}).
This happened while the csv dataset builder was generating data using
hf://datasets/rudrakshrakeshzodage/Product_Orders_data/updated_products.csv (at revision b7af6d2109b59969eae454b4a9d7d09fa6290aa7), ['hf://datasets/rudrakshrakeshzodage/Product_Orders_data@b7af6d2109b59969eae454b4a9d7d09fa6290aa7/updated_orders.csv', 'hf://datasets/rudrakshrakeshzodage/Product_Orders_data@b7af6d2109b59969eae454b4a9d7d09fa6290aa7/updated_products.csv']
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.
order_id int64 | customer_id int64 | product_id int64 | quantity int64 | order_date string |
|---|---|---|---|---|
1 | 110 | 47 | 4 | 22-12-2024 |
2 | 435 | 84 | 3 | 23-12-2024 |
3 | 190 | 56 | 5 | 24-12-2024 |
4 | 432 | 5 | 5 | 25-12-2024 |
5 | 353 | 14 | 1 | 26-12-2024 |
6 | 358 | 64 | 2 | 27-12-2024 |
7 | 75 | 46 | 3 | 28-12-2024 |
8 | 11 | 45 | 5 | 29-12-2024 |
9 | 67 | 18 | 2 | 30-12-2024 |
10 | 220 | 88 | 3 | 31-12-2024 |
11 | 349 | 71 | 2 | 01-01-2025 |
12 | 249 | 79 | 3 | 02-01-2025 |
13 | 87 | 53 | 2 | 03-01-2025 |
14 | 324 | 99 | 5 | 04-01-2025 |
15 | 271 | 98 | 1 | 05-01-2025 |
16 | 38 | 69 | 3 | 06-01-2025 |
17 | 182 | 85 | 3 | 07-01-2025 |
18 | 58 | 19 | 1 | 08-01-2025 |
19 | 252 | 87 | 4 | 09-01-2025 |
20 | 470 | 43 | 1 | 10-01-2025 |
21 | 119 | 34 | 5 | 11-01-2025 |
22 | 187 | 66 | 2 | 12-01-2025 |
23 | 21 | 64 | 1 | 13-01-2025 |
24 | 273 | 25 | 4 | 14-01-2025 |
25 | 147 | 73 | 2 | 15-01-2025 |
26 | 271 | 9 | 3 | 16-01-2025 |
27 | 373 | 3 | 1 | 17-01-2025 |
28 | 128 | 44 | 2 | 18-01-2025 |
29 | 305 | 71 | 4 | 19-01-2025 |
30 | 26 | 11 | 2 | 17-03-2025 |
31 | 82 | 22 | 2 | 27-11-2024 |
32 | 453 | 35 | 1 | 22-03-2025 |
33 | 491 | 9 | 1 | 18-05-2025 |
34 | 249 | 20 | 3 | 12-12-2023 |
35 | 155 | 29 | 5 | 08-05-2024 |
36 | 461 | 87 | 4 | 12-09-2024 |
37 | 366 | 31 | 2 | 16-05-2025 |
38 | 47 | 23 | 3 | 27-04-2025 |
39 | 339 | 75 | 4 | 26-03-2025 |
40 | 57 | 48 | 5 | 12-05-2024 |
41 | 339 | 1 | 1 | 12-08-2024 |
42 | 217 | 93 | 3 | 15-01-2024 |
43 | 12 | 62 | 2 | 12-08-2024 |
44 | 291 | 24 | 3 | 26-03-2025 |
45 | 108 | 73 | 4 | 29-07-2024 |
46 | 78 | 10 | 4 | 25-01-2025 |
47 | 109 | 26 | 4 | 07-02-2025 |
48 | 275 | 70 | 1 | 03-01-2025 |
49 | 200 | 54 | 5 | 21-04-2025 |
50 | 92 | 84 | 4 | 29-08-2024 |
51 | 393 | 57 | 2 | 24-05-2025 |
52 | 12 | 97 | 4 | 19-02-2024 |
53 | 287 | 83 | 4 | 15-05-2025 |
54 | 212 | 45 | 3 | 22-11-2024 |
55 | 213 | 70 | 2 | 09-03-2025 |
56 | 441 | 99 | 1 | 03-06-2025 |
57 | 123 | 40 | 4 | 06-11-2024 |
58 | 203 | 45 | 1 | 10-01-2025 |
59 | 223 | 62 | 3 | 23-04-2025 |
60 | 445 | 10 | 5 | 08-01-2025 |
61 | 167 | 53 | 3 | 24-02-2025 |
62 | 272 | 53 | 1 | 06-05-2025 |
63 | 11 | 21 | 1 | 18-03-2024 |
64 | 298 | 20 | 4 | 26-02-2025 |
65 | 480 | 97 | 1 | 28-05-2024 |
66 | 207 | 8 | 1 | 07-03-2025 |
67 | 112 | 74 | 5 | 26-05-2025 |
68 | 84 | 73 | 4 | 04-12-2024 |
69 | 203 | 12 | 3 | 03-06-2025 |
70 | 439 | 4 | 2 | 04-05-2025 |
71 | 100 | 95 | 4 | 02-04-2025 |
72 | 9 | 18 | 2 | 30-04-2025 |
73 | 330 | 60 | 5 | 16-05-2025 |
74 | 374 | 48 | 4 | 22-02-2025 |
75 | 84 | 87 | 1 | 13-07-2024 |
76 | 157 | 84 | 3 | 11-08-2024 |
77 | 272 | 19 | 3 | 10-04-2025 |
78 | 39 | 46 | 5 | 11-03-2025 |
79 | 311 | 77 | 2 | 19-05-2025 |
80 | 157 | 80 | 5 | 01-07-2024 |
81 | 380 | 29 | 3 | 23-02-2024 |
82 | 183 | 32 | 1 | 01-05-2025 |
83 | 60 | 33 | 3 | 27-05-2025 |
84 | 194 | 37 | 2 | 24-03-2025 |
85 | 168 | 15 | 1 | 14-08-2024 |
86 | 220 | 5 | 1 | 01-05-2025 |
87 | 245 | 52 | 3 | 02-05-2025 |
88 | 247 | 12 | 4 | 03-05-2025 |
89 | 18 | 98 | 3 | 04-05-2025 |
90 | 205 | 98 | 2 | 05-05-2025 |
91 | 34 | 9 | 1 | 06-05-2025 |
92 | 402 | 8 | 4 | 15-02-2025 |
93 | 499 | 26 | 2 | 24-08-2024 |
94 | 21 | 71 | 5 | 23-04-2025 |
95 | 62 | 73 | 1 | 26-11-2024 |
96 | 41 | 34 | 3 | 27-11-2024 |
97 | 420 | 65 | 3 | 28-11-2024 |
98 | 93 | 70 | 3 | 29-11-2024 |
99 | 300 | 2 | 4 | 30-11-2024 |
100 | 98 | 63 | 3 | 01-12-2024 |
End of preview.
📊 Sales Orders & Products Dataset
This repository contains sample datasets for Orders and Products that can be used for:
- Data Analysis
- Data Cleaning
- SQL Practice
- Machine Learning Projects
- Data Visualization
- ETL Pipelines
📂 Files Included
1. updated_orders.csv
Contains customer order information.
| Column | Description |
|---|---|
| order_id | Unique Order ID |
| customer_id | Unique Customer ID |
| product_id | Product purchased |
| quantity | Quantity ordered |
| order_date | Date of order |
Sample Data
order_id,customer_id,product_id,quantity,order_date
1,110,47,4,22-12-2024
2,435,84,3,23-12-2024
3,190,56,5,24-12-2024
4,432,5,5,25-12-2024
5,353,14,1,26-12-2024
6,358,64,2,27-12-2024
7,75,46,3,28-12-2024
2. updated_products.csv
Contains product catalog information.
| Column | Description |
|---|---|
| product_id | Unique Product ID |
| name | Product Name |
| category | Product Category |
| price | Product Price |
Sample Data
product_id,name,category,price
1,LibreOffice,Software,2372.30
2,GIMP,Software,3631.18
🔗 Relationship Between Files
The datasets are connected through the product_id column.
updated_orders.csv
│
│ product_id
▼
updated_products.csv
This allows joining both datasets to analyze:
- Product sales
- Revenue generation
- Customer purchasing patterns
- Category-wise performance
🚀 Example Use Cases
Total Revenue Calculation
SELECT
p.name,
SUM(o.quantity * p.price) AS revenue
FROM updated_orders o
JOIN updated_products p
ON o.product_id = p.product_id
GROUP BY p.name;
Most Sold Products
SELECT
product_id,
SUM(quantity) AS total_quantity
FROM updated_orders
GROUP BY product_id
ORDER BY total_quantity DESC;
🛠 Technologies
- CSV
- SQL
- Python
- Pandas
- Power BI
- Tableau
- Machine Learning
📈 Dataset Purpose
This dataset is created for educational and practice purposes, helping learners understand:
- Data Cleaning
- Data Analysis
- Database Management
- Data Visualization
- Business Intelligence
Author
Rudraksh Rakesh Zodage
- Downloads last month
- 15