Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
Russian
Size:
10K<n<100K
Tags:
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) | |
``` | |