|
--- |
|
language: |
|
- ru |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
- 10K<n<100K |
|
task_categories: |
|
- text-classification |
|
task_ids: |
|
- sentiment-classification |
|
--- |
|
### Dataset Summary |
|
The dataset contains user reviews about medical institutions. |
|
|
|
In total it contains 12,036 reviews. A review tagged with the <em>general</em> sentiment and sentiments on 5 aspects: <em>quality, service, equipment, food, location</em>. |
|
### Data Fields |
|
Each sample contains the following fields: |
|
- **review_id**; |
|
- **content**: review text; |
|
- **general**; |
|
- **quality**; |
|
- **service**; |
|
- **equipment**; |
|
- **food**; |
|
- **location**. |
|
### Python |
|
```python3 |
|
import pandas as pd |
|
df = pd.read_json('medical_institutions_reviews.jsonl', lines=True) |
|
df.sample(5) |
|
``` |
|
|
