Datasets:
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README.md
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- Load `yelp_academic_dataset_business.json` and `yelp_academic_dataset_review.json` as pandas DataFrames.
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- Perform an inner merge of these datasets based on `business_id` and filter out businesses that are not restaurants (filter out rows that `categories` doesn't contain "restaurants").
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- Split the yelp restaurants dataset into a training dataset and a testing dataset by shuffling the dataset and then spliting it by 80/20.
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- Finally, we get yelp restaurants [training](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_train.csv) and [testing](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_test.csv) datasets
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(You may check the data processing by this link: [Data Process Colab Link](https://colab.research.google.com/drive/1r_gUGmsawwtFpZCj23X1jWjfEi6Dw291?usp=sharing))
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## Restaurant Dataset
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- Load `yelp_academic_dataset_business.json` and `yelp_academic_dataset_review.json` as pandas DataFrames.
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- Perform an inner merge of these datasets based on `business_id` and filter out businesses that are not restaurants (filter out rows that `categories` doesn't contain "restaurants").
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- Split the yelp restaurants dataset into a training dataset and a testing dataset by shuffling the dataset and then spliting it by 80/20.
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- Finally, we get yelp restaurants [training](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_train.csv) and [testing](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_test.csv) datasets in CSV format.
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(You may check the data processing by this link: [Data Process Colab Link](https://colab.research.google.com/drive/1r_gUGmsawwtFpZCj23X1jWjfEi6Dw291?usp=sharing))
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## Restaurant Dataset
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