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amazon_us_reviews

References:

Books_v1_01

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_01')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 6106719
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Watches_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Watches_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 960872
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Personal_Care_Appliances_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Personal_Care_Appliances_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 85981
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Mobile_Electronics_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Electronics_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 104975
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Video_Games_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Games_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 145431
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Software_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Software_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 102084
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Major_Appliances_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Major_Appliances_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 96901
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Gift_Card_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Gift_Card_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 149086
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Video_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 380604
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Luggage_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Luggage_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 348657
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Software_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Software_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 341931
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_Games_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Video_Games_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 1785997
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Furniture_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Furniture_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 792113
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Musical_Instruments_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Musical_Instruments_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 904765
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Music_Purchase_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Music_Purchase_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 1688884
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Books_v1_02

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_02')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 3105520
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Home_Entertainment_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Home_Entertainment_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 705889
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Grocery_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Grocery_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 2402458
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Outdoors_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Outdoors_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 2302401
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Pet_Products_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Pet_Products_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 2643619
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_DVD_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Video_DVD_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 5069140
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Apparel_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Apparel_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 5906333
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

PC_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/PC_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 6908554
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Tools_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Tools_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 1741100
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Jewelry_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Jewelry_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 1767753
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Baby_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Baby_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 1752932
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Home_Improvement_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Home_Improvement_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 2634781
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Camera_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Camera_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 1801974
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Lawn_and_Garden_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Lawn_and_Garden_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 2557288
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Office_Products_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Office_Products_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 2642434
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Electronics_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Electronics_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 3093869
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Automotive_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Automotive_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 3514942
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Video_Download_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Download_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 4057147
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Mobile_Apps_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Apps_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 5033376
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Shoes_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Shoes_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 4366916
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Toys_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Toys_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 4864249
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Sports_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Sports_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 4850360
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Kitchen_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Kitchen_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 4880466
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Beauty_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Beauty_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 5115666
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Music_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Music_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 4751577
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Health_Personal_Care_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Health_Personal_Care_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 5331449
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Ebook_Purchase_v1_01

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_01')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 5101693
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Home_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Home_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 6221559
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Wireless_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Wireless_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 9002021
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Books_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 10319090
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Ebook_Purchase_v1_00

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_00')
  • Description:
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • License: No known license
  • Version: 0.1.0
  • Splits:
Split Examples
'train' 12520722
  • Features:
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}