Datasets:
Tasks:
Text Classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
License:
text
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aiohttp==3.8.3 |
aiosignal==1.2.0 |
async-timeout==4.0.2 |
attrs==22.1.0 |
certifi==2022.9.24 |
charset-normalizer==2.1.1 |
datasets==2.6.1 |
dill==0.3.5.1 |
filelock==3.8.0 |
frozenlist==1.3.1 |
fsspec==2022.10.0 |
idna==3.4 |
joblib==1.2.0 |
kaggle==1.5.12 |
multidict==6.0.2 |
multiprocess==0.70.13 |
numpy==1.23.4 |
packaging==21.3 |
pandas==1.5.1 |
pyarrow==10.0.0 |
pyparsing==3.0.9 |
python-dateutil==2.8.2 |
python-slugify==6.1.2 |
pytz==2022.5 |
PyYAML==6.0 |
requests==2.28.1 |
responses==0.18.0 |
scikit-learn==1.1.3 |
scipy==1.9.3 |
six==1.16.0 |
text-unidecode==1.3 |
threadpoolctl==3.1.0 |
tqdm==4.64.1 |
typing_extensions==4.4.0 |
urllib3==1.26.12 |
xxhash==3.1.0 |
yarl==1.8.1 |
Cleaned up version of the rotten tomatoes critic reviews dataset. The original is obtained from Kaggle: https://www.kaggle.com/datasets/stefanoleone992/rotten-tomatoes-movies-and-critic-reviews-dataset
Data has been scraped from the publicly available website https://www.rottentomatoes.com as of 2020-10-31.
The clean up process drops anything without both a review and a rating, as well as standardising the ratings onto several integer, ordinal scales.
Requires the kaggle library to be installed, and kaggle API keys passed
through environment variables or in ~/.kaggle/kaggle.json. See the Kaggle
docs.
A processed version is available at https://huggingface.co/datasets/frankier/processed_multiscale_rt_critics
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