File size: 2,387 Bytes
6c92466 17466c0 6c92466 17466c0 6c92466 17466c0 6c92466 af4133c 9d4ec7e af4133c 9d4ec7e 7e418fc c275143 9d4ec7e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
dataset_info:
- config_name: metadata
features:
- name: asin
dtype: string
- name: title
dtype: string
- name: description
dtype: string
- name: brand
dtype: string
- name: main_cat
dtype: string
- name: category
sequence: string
- name: also_buy
sequence: string
- name: also_view
sequence: string
- name: imageURL
sequence: string
- name: imageURLHighRes
sequence: string
splits:
- name: train
num_bytes: 632329524
num_examples: 633875
download_size: 274315827
dataset_size: 632329524
- config_name: reviews
features:
- name: reviewerID
dtype: string
- name: reviewerName
dtype: string
- name: overall
sequence: int64
- name: reviewTime
sequence: timestamp[us]
- name: asin
sequence: string
- name: reviewText
sequence: string
- name: summary
sequence: string
splits:
- name: train
num_bytes: 754819358
num_examples: 283686
download_size: 417425618
dataset_size: 754819358
configs:
- config_name: metadata
data_files:
- split: train
path: metadata/train-*
- config_name: reviews
data_files:
- split: train
path: reviews/train-*
---
# Amazon Toys & Games Dataset
## Directory Structure
- **metadata**: Contains product information.
- **reviews**: Contains user reviews about the products.
- **filtered**:
- **e5-base-v2_embeddings.jsonl**: Contains "asin" and "embeddings" created with [e5-base-v2](https://huggingface.co/intfloat/e5-base-v2).
- **metadata.jsonl**: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
- **reviews.jsonl**: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include only perfect 5-star ratings with a minimum of 5 ratings.
## Usage
### Download metadata
```python
metadata = load_dataset(path="smartcat/Amazon_Toys_and_Games_2018", name="metadata", split="train")
```
### Download reviews
```python
metadata = load_dataset(path="smartcat/Amazon_Toys_and_Games_2018", name="reviews", split="train")
```
### Download filtered files
```
filtered_reviews = load_dataset(
path="smartcat/Amazon_Toys_and_Games_2018",
data_files="filtered/reviews.jsonl",
split="train",
)
```
**📎 Note:** You can set any file or list of files from the "filtered" directory as the "data_files" argument. |