Datasets:
| dataset_info: | |
| features: | |
| - name: 'Unnamed: 0' | |
| dtype: int64 | |
| - name: drugName | |
| dtype: string | |
| - name: condition | |
| dtype: string | |
| - name: review | |
| dtype: string | |
| - name: rating | |
| dtype: float64 | |
| - name: date | |
| dtype: string | |
| - name: usefulCount | |
| dtype: int64 | |
| splits: | |
| - name: train | |
| num_bytes: 29016995 | |
| num_examples: 53766 | |
| download_size: 16756332 | |
| dataset_size: 29016995 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| language: | |
| - en | |
| With a dataset of over 2000 drugs for varying health situations, over 200,000 observations, 7 attributes, and tens of thousands of texts by users of their experience; categorizing these texts will be an extremely difficult task without an efficient algorithm for resolving the problem. | |
| ``` | |
| https://www.kaggle.com/ | |
| ``` |