### 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)
```

task_categories:text-classification task_ids:sentiment-classification multilinguality:monolingual size_categories:10K<n<100K language:ru region:us
{"language": ["ru"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"]}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #multilinguality-monolingual #size_categories-10K<n<100K #language-Russian #region-us 

### 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


### 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
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #multilinguality-monolingual #size_categories-10K<n<100K #language-Russian #region-us 
 ### 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