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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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