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+ dataset_size: 7197687124
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+ - config_name: Digital_Ebook_Purchase_v1_00
2101
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2102
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+ dtype: string
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+ - name: review_body
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+ dtype: string
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+ - name: review_date
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+ dtype: string
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+ splits:
2141
+ - name: train
2142
+ num_bytes: 7302303804
2143
+ num_examples: 12520722
2144
+ download_size: 2689739299
2145
+ dataset_size: 7302303804
2146
+ duplicated_from: amazon_us_reviews
2147
+ ---
2148
+
2149
+ # Dataset Card for "amazon_us_reviews"
2150
+
2151
+ ## Table of Contents
2152
+ - [Dataset Description](#dataset-description)
2153
+ - [Dataset Summary](#dataset-summary)
2154
+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
2155
+ - [Languages](#languages)
2156
+ - [Dataset Structure](#dataset-structure)
2157
+ - [Data Instances](#data-instances)
2158
+ - [Data Fields](#data-fields)
2159
+ - [Data Splits](#data-splits)
2160
+ - [Dataset Creation](#dataset-creation)
2161
+ - [Curation Rationale](#curation-rationale)
2162
+ - [Source Data](#source-data)
2163
+ - [Annotations](#annotations)
2164
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
2165
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
2166
+ - [Social Impact of Dataset](#social-impact-of-dataset)
2167
+ - [Discussion of Biases](#discussion-of-biases)
2168
+ - [Other Known Limitations](#other-known-limitations)
2169
+ - [Additional Information](#additional-information)
2170
+ - [Dataset Curators](#dataset-curators)
2171
+ - [Licensing Information](#licensing-information)
2172
+ - [Citation Information](#citation-information)
2173
+ - [Contributions](#contributions)
2174
+
2175
+ ## Dataset Description
2176
+
2177
+ - **Homepage:** [https://s3.amazonaws.com/amazon-reviews-pds/readme.html](https://s3.amazonaws.com/amazon-reviews-pds/readme.html)
2178
+ - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2179
+ - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2180
+ - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2181
+ - **Size of downloaded dataset files:** 32377.29 MB
2182
+ - **Size of the generated dataset:** 82820.19 MB
2183
+ - **Total amount of disk used:** 115197.49 MB
2184
+
2185
+ ### Dataset Summary
2186
+
2187
+ 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.
2188
+ 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).
2189
+ Each Dataset contains the following columns :
2190
+ marketplace - 2 letter country code of the marketplace where the review was written.
2191
+ customer_id - Random identifier that can be used to aggregate reviews written by a single author.
2192
+ review_id - The unique ID of the review.
2193
+ product_id - The unique Product ID the review pertains to. In the multilingual dataset the reviews
2194
+ for the same product in different countries can be grouped by the same product_id.
2195
+ product_parent - Random identifier that can be used to aggregate reviews for the same product.
2196
+ product_title - Title of the product.
2197
+ product_category - Broad product category that can be used to group reviews
2198
+ (also used to group the dataset into coherent parts).
2199
+ star_rating - The 1-5 star rating of the review.
2200
+ helpful_votes - Number of helpful votes.
2201
+ total_votes - Number of total votes the review received.
2202
+ vine - Review was written as part of the Vine program.
2203
+ verified_purchase - The review is on a verified purchase.
2204
+ review_headline - The title of the review.
2205
+ review_body - The review text.
2206
+ review_date - The date the review was written.
2207
+
2208
+ ### Supported Tasks and Leaderboards
2209
+
2210
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2211
+
2212
+ ### Languages
2213
+
2214
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2215
+
2216
+ ## Dataset Structure
2217
+
2218
+ ### Data Instances
2219
+
2220
+ #### Apparel_v1_00
2221
+
2222
+ - **Size of downloaded dataset files:** 648.64 MB
2223
+ - **Size of the generated dataset:** 2254.36 MB
2224
+ - **Total amount of disk used:** 2903.00 MB
2225
+
2226
+ An example of 'train' looks as follows.
2227
+ ```
2228
+ {
2229
+ "customer_id": "45223824",
2230
+ "helpful_votes": 0,
2231
+ "marketplace": "US",
2232
+ "product_category": "Apparel",
2233
+ "product_id": "B016PUU3VO",
2234
+ "product_parent": "893588059",
2235
+ "product_title": "Fruit of the Loom Boys' A-Shirt (Pack of 4)",
2236
+ "review_body": "I ordered the same size as I ordered last time, and these shirts were much larger than the previous order. They were also about 6 inches longer. It was like they sent men's shirts instead of boys' shirts. I'll be returning these...",
2237
+ "review_date": "2015-01-01",
2238
+ "review_headline": "Sizes not correct, too big overall and WAY too long",
2239
+ "review_id": "R1N3Z13931J3O9",
2240
+ "star_rating": 2,
2241
+ "total_votes": 0,
2242
+ "verified_purchase": 1,
2243
+ "vine": 0
2244
+ }
2245
+ ```
2246
+
2247
+ #### Automotive_v1_00
2248
+
2249
+ - **Size of downloaded dataset files:** 582.15 MB
2250
+ - **Size of the generated dataset:** 1518.88 MB
2251
+ - **Total amount of disk used:** 2101.03 MB
2252
+
2253
+ An example of 'train' looks as follows.
2254
+ ```
2255
+ {
2256
+ "customer_id": "16825098",
2257
+ "helpful_votes": 0,
2258
+ "marketplace": "US",
2259
+ "product_category": "Automotive",
2260
+ "product_id": "B000E4PCGE",
2261
+ "product_parent": "694793259",
2262
+ "product_title": "00-03 NISSAN SENTRA MIRROR RH (PASSENGER SIDE), Power, Non-Heated (2000 00 2001 01 2002 02 2003 03) NS35ER 963015M000",
2263
+ "review_body": "Product was as described, new and a great look. Only bad thing is that one of the screws was stripped so I couldn't tighten all three.",
2264
+ "review_date": "2015-08-31",
2265
+ "review_headline": "new and a great look. Only bad thing is that one of ...",
2266
+ "review_id": "R2RUIDUMDKG7P",
2267
+ "star_rating": 3,
2268
+ "total_votes": 0,
2269
+ "verified_purchase": 1,
2270
+ "vine": 0
2271
+ }
2272
+ ```
2273
+
2274
+ #### Baby_v1_00
2275
+
2276
+ - **Size of downloaded dataset files:** 357.40 MB
2277
+ - **Size of the generated dataset:** 956.30 MB
2278
+ - **Total amount of disk used:** 1313.70 MB
2279
+
2280
+ An example of 'train' looks as follows.
2281
+ ```
2282
+ This example was too long and was cropped:
2283
+
2284
+ {
2285
+ "customer_id": "23299101",
2286
+ "helpful_votes": 2,
2287
+ "marketplace": "US",
2288
+ "product_category": "Baby",
2289
+ "product_id": "B00SN6F9NG",
2290
+ "product_parent": "3470998",
2291
+ "product_title": "Rhoost Nail Clipper for Baby - Ergonomically Designed and Easy to Use Baby Nail Clipper, Natural Wooden Bamboo - Baby Health and Personal Care Kits",
2292
+ "review_body": "\"This is an absolute MUST item to have! I was scared to death to clip my baby's nails. I tried other baby nail clippers and th...",
2293
+ "review_date": "2015-08-31",
2294
+ "review_headline": "If fits so comfortably in my hand and I feel like I have ...",
2295
+ "review_id": "R2DRL5NRODVQ3Z",
2296
+ "star_rating": 5,
2297
+ "total_votes": 2,
2298
+ "verified_purchase": 1,
2299
+ "vine": 0
2300
+ }
2301
+ ```
2302
+
2303
+ #### Beauty_v1_00
2304
+
2305
+ - **Size of downloaded dataset files:** 914.08 MB
2306
+ - **Size of the generated dataset:** 2397.39 MB
2307
+ - **Total amount of disk used:** 3311.47 MB
2308
+
2309
+ An example of 'train' looks as follows.
2310
+ ```
2311
+ {
2312
+ "customer_id": "24655453",
2313
+ "helpful_votes": 1,
2314
+ "marketplace": "US",
2315
+ "product_category": "Beauty",
2316
+ "product_id": "B00SAQ9DZY",
2317
+ "product_parent": "292127037",
2318
+ "product_title": "12 New, High Quality, Amber 2 ml (5/8 Dram) Glass Bottles, with Orifice Reducer and Black Cap.",
2319
+ "review_body": "These are great for small mixtures for EO's, especially for traveling. I only gave this 4 stars because of the orifice reducer. The hole is so small it is hard to get the oil out. Just needs to be slightly bigger.",
2320
+ "review_date": "2015-08-31",
2321
+ "review_headline": "Good Product",
2322
+ "review_id": "R2A30ALEGLMCGN",
2323
+ "star_rating": 4,
2324
+ "total_votes": 1,
2325
+ "verified_purchase": 1,
2326
+ "vine": 0
2327
+ }
2328
+ ```
2329
+
2330
+ #### Books_v1_00
2331
+
2332
+ - **Size of downloaded dataset files:** 2740.34 MB
2333
+ - **Size of the generated dataset:** 7193.86 MB
2334
+ - **Total amount of disk used:** 9934.20 MB
2335
+
2336
+ An example of 'train' looks as follows.
2337
+ ```
2338
+ This example was too long and was cropped:
2339
+
2340
+ {
2341
+ "customer_id": "49735028",
2342
+ "helpful_votes": 0,
2343
+ "marketplace": "US",
2344
+ "product_category": "Books",
2345
+ "product_id": "0664254969",
2346
+ "product_parent": "248307276",
2347
+ "product_title": "Presbyterian Creeds: A Guide to the Book of Confessions",
2348
+ "review_body": "\"The Presbyterian Book of Confessions contains multiple Creeds for use by the denomination. This guidebook helps he lay person t...",
2349
+ "review_date": "2015-08-31",
2350
+ "review_headline": "The Presbyterian Book of Confessions contains multiple Creeds for use ...",
2351
+ "review_id": "R2G519UREHRO8M",
2352
+ "star_rating": 3,
2353
+ "total_votes": 1,
2354
+ "verified_purchase": 1,
2355
+ "vine": 0
2356
+ }
2357
+ ```
2358
+
2359
+ ### Data Fields
2360
+
2361
+ The data fields are the same among all splits.
2362
+
2363
+ #### Apparel_v1_00
2364
+ - `marketplace`: a `string` feature.
2365
+ - `customer_id`: a `string` feature.
2366
+ - `review_id`: a `string` feature.
2367
+ - `product_id`: a `string` feature.
2368
+ - `product_parent`: a `string` feature.
2369
+ - `product_title`: a `string` feature.
2370
+ - `product_category`: a `string` feature.
2371
+ - `star_rating`: a `int32` feature.
2372
+ - `helpful_votes`: a `int32` feature.
2373
+ - `total_votes`: a `int32` feature.
2374
+ - `vine`: a classification label, with possible values including `Y` (0), `N` (1).
2375
+ - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1).
2376
+ - `review_headline`: a `string` feature.
2377
+ - `review_body`: a `string` feature.
2378
+ - `review_date`: a `string` feature.
2379
+
2380
+ #### Automotive_v1_00
2381
+ - `marketplace`: a `string` feature.
2382
+ - `customer_id`: a `string` feature.
2383
+ - `review_id`: a `string` feature.
2384
+ - `product_id`: a `string` feature.
2385
+ - `product_parent`: a `string` feature.
2386
+ - `product_title`: a `string` feature.
2387
+ - `product_category`: a `string` feature.
2388
+ - `star_rating`: a `int32` feature.
2389
+ - `helpful_votes`: a `int32` feature.
2390
+ - `total_votes`: a `int32` feature.
2391
+ - `vine`: a classification label, with possible values including `Y` (0), `N` (1).
2392
+ - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1).
2393
+ - `review_headline`: a `string` feature.
2394
+ - `review_body`: a `string` feature.
2395
+ - `review_date`: a `string` feature.
2396
+
2397
+ #### Baby_v1_00
2398
+ - `marketplace`: a `string` feature.
2399
+ - `customer_id`: a `string` feature.
2400
+ - `review_id`: a `string` feature.
2401
+ - `product_id`: a `string` feature.
2402
+ - `product_parent`: a `string` feature.
2403
+ - `product_title`: a `string` feature.
2404
+ - `product_category`: a `string` feature.
2405
+ - `star_rating`: a `int32` feature.
2406
+ - `helpful_votes`: a `int32` feature.
2407
+ - `total_votes`: a `int32` feature.
2408
+ - `vine`: a classification label, with possible values including `Y` (0), `N` (1).
2409
+ - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1).
2410
+ - `review_headline`: a `string` feature.
2411
+ - `review_body`: a `string` feature.
2412
+ - `review_date`: a `string` feature.
2413
+
2414
+ #### Beauty_v1_00
2415
+ - `marketplace`: a `string` feature.
2416
+ - `customer_id`: a `string` feature.
2417
+ - `review_id`: a `string` feature.
2418
+ - `product_id`: a `string` feature.
2419
+ - `product_parent`: a `string` feature.
2420
+ - `product_title`: a `string` feature.
2421
+ - `product_category`: a `string` feature.
2422
+ - `star_rating`: a `int32` feature.
2423
+ - `helpful_votes`: a `int32` feature.
2424
+ - `total_votes`: a `int32` feature.
2425
+ - `vine`: a classification label, with possible values including `Y` (0), `N` (1).
2426
+ - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1).
2427
+ - `review_headline`: a `string` feature.
2428
+ - `review_body`: a `string` feature.
2429
+ - `review_date`: a `string` feature.
2430
+
2431
+ #### Books_v1_00
2432
+ - `marketplace`: a `string` feature.
2433
+ - `customer_id`: a `string` feature.
2434
+ - `review_id`: a `string` feature.
2435
+ - `product_id`: a `string` feature.
2436
+ - `product_parent`: a `string` feature.
2437
+ - `product_title`: a `string` feature.
2438
+ - `product_category`: a `string` feature.
2439
+ - `star_rating`: a `int32` feature.
2440
+ - `helpful_votes`: a `int32` feature.
2441
+ - `total_votes`: a `int32` feature.
2442
+ - `vine`: a classification label, with possible values including `Y` (0), `N` (1).
2443
+ - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1).
2444
+ - `review_headline`: a `string` feature.
2445
+ - `review_body`: a `string` feature.
2446
+ - `review_date`: a `string` feature.
2447
+
2448
+ ### Data Splits
2449
+
2450
+ | name | train |
2451
+ |----------------|-------:|
2452
+ |Apparel_v1_00 | 5906333|
2453
+ |Automotive_v1_00 | 3514942|
2454
+ |Baby_v1_00 | 1752932|
2455
+ |Beauty_v1_00 | 5115666|
2456
+ |Books_v1_00 | 10319090|
2457
+ |Books_v1_01 | 6106719|
2458
+ |Books_v1_02 | 3105520|
2459
+ |Camera_v1_00 | 1801974|
2460
+ |Digital_Ebook_Purchase_v1_00 | 12520722|
2461
+ |Digital_Ebook_Purchase_v1_01 | 5101693|
2462
+ |Digital_Music_Purchase_v1_00 | 1688884|
2463
+ |Digital_Software_v1_00 | 102084|
2464
+ |Digital_Video_Download_v1_00 | 4057147|
2465
+ |Digital_Video_Games_v1_00 | 145431|
2466
+ |Electronics_v1_00 | 3093869|
2467
+ |Furniture_v1_00 | 792113|
2468
+ |Gift_Card_v1_00 | 149086|
2469
+ |Grocery_v1_00 | 2402458|
2470
+ |Health_Personal_Care_v1_00 | 5331449|
2471
+ |Home_Entertainment_v1_00 | 705889|
2472
+ |Home_Improvement_v1_00 | 2634781|
2473
+ |Home_v1_00 | 6221559|
2474
+ |Jewelry_v1_00 | 1767753|
2475
+ |Kitchen_v1_00 | 4880466|
2476
+ |Lawn_and_Garden_v1_00 | 2557288|
2477
+ |Luggage_v1_00 | 348657|
2478
+ |Major_Appliances_v1_00 | 96901|
2479
+ |Mobile_Apps_v1_00 | 5033376|
2480
+ |Mobile_Electronics_v1_00 | 104975|
2481
+ |Music_v1_00 | 4751577|
2482
+ |Musical_Instruments_v1_00 | 904765|
2483
+ |Office_Products_v1_00 | 2642434|
2484
+ |Outdoors_v1_00 | 2302401|
2485
+ |PC_v1_00 | 6908554|
2486
+ |Personal_Care_Appliances_v1_00 | 85981|
2487
+ |Pet_Products_v1_00 | 2643619|
2488
+ |Shoes_v1_00 | 4366916|
2489
+ |Software_v1_00 | 341931|
2490
+ |Sports_v1_00 | 4850360|
2491
+ |Tools_v1_00 | 1741100|
2492
+ |Toys_v1_00 | 4864249|
2493
+ |Video_DVD_v1_00 | 5069140|
2494
+ |Video_Games_v1_00 | 1785997|
2495
+ |Video_v1_00 | 380604|
2496
+ |Watches_v1_00 | 960872|
2497
+ |Wireless_v1_00 | 9002021|
2498
+
2499
+ ## Dataset Creation
2500
+
2501
+ ### Curation Rationale
2502
+
2503
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2504
+
2505
+ ### Source Data
2506
+
2507
+ #### Initial Data Collection and Normalization
2508
+
2509
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2510
+
2511
+ #### Who are the source language producers?
2512
+
2513
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2514
+
2515
+ ### Annotations
2516
+
2517
+ #### Annotation process
2518
+
2519
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2520
+
2521
+ #### Who are the annotators?
2522
+
2523
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2524
+
2525
+ ### Personal and Sensitive Information
2526
+
2527
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2528
+
2529
+ ## Considerations for Using the Data
2530
+
2531
+ ### Social Impact of Dataset
2532
+
2533
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2534
+
2535
+ ### Discussion of Biases
2536
+
2537
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2538
+
2539
+ ### Other Known Limitations
2540
+
2541
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2542
+
2543
+ ## Additional Information
2544
+
2545
+ ### Dataset Curators
2546
+
2547
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
2548
+
2549
+ ### Licensing Information
2550
+
2551
+ https://s3.amazonaws.com/amazon-reviews-pds/LICENSE.txt
2552
+
2553
+ By accessing the Amazon Customer Reviews Library ("Reviews Library"), you agree that the
2554
+ Reviews Library is an Amazon Service subject to the [Amazon.com Conditions of Use](https://www.amazon.com/gp/help/customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088)
2555
+ and you agree to be bound by them, with the following additional conditions:
2556
+
2557
+ In addition to the license rights granted under the Conditions of Use,
2558
+ Amazon or its content providers grant you a limited, non-exclusive, non-transferable,
2559
+ non-sublicensable, revocable license to access and use the Reviews Library
2560
+ for purposes of academic research.
2561
+ You may not resell, republish, or make any commercial use of the Reviews Library
2562
+ or its contents, including use of the Reviews Library for commercial research,
2563
+ such as research related to a funding or consultancy contract, internship, or
2564
+ other relationship in which the results are provided for a fee or delivered
2565
+ to a for-profit organization. You may not (a) link or associate content
2566
+ in the Reviews Library with any personal information (including Amazon customer accounts),
2567
+ or (b) attempt to determine the identity of the author of any content in the
2568
+ Reviews Library.
2569
+ If you violate any of the foregoing conditions, your license to access and use the
2570
+ Reviews Library will automatically terminate without prejudice to any of the
2571
+ other rights or remedies Amazon may have.
2572
+
2573
+ ### Citation Information
2574
+
2575
+ No citation information.
2576
+
2577
+ ### Contributions
2578
+
2579
+ Thanks to [@joeddav](https://github.com/joeddav) for adding this dataset.
amazon_us_reviews.py ADDED
@@ -0,0 +1,180 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ """Amazon Customer Reviews Dataset --- US REVIEWS DATASET."""
17
+
18
+
19
+ import csv
20
+
21
+ import datasets
22
+
23
+
24
+ _CITATION = """\
25
+ """
26
+
27
+ _DESCRIPTION = """\
28
+ 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.
29
+
30
+ 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).
31
+
32
+ Each Dataset contains the following columns:
33
+
34
+ - marketplace: 2 letter country code of the marketplace where the review was written.
35
+ - customer_id: Random identifier that can be used to aggregate reviews written by a single author.
36
+ - review_id: The unique ID of the review.
37
+ - 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.
38
+ - product_parent: Random identifier that can be used to aggregate reviews for the same product.
39
+ - product_title: Title of the product.
40
+ - product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
41
+ - star_rating: The 1-5 star rating of the review.
42
+ - helpful_votes: Number of helpful votes.
43
+ - total_votes: Number of total votes the review received.
44
+ - vine: Review was written as part of the Vine program.
45
+ - verified_purchase: The review is on a verified purchase.
46
+ - review_headline: The title of the review.
47
+ - review_body: The review text.
48
+ - review_date: The date the review was written.
49
+ """
50
+
51
+ _DATA_OPTIONS = [
52
+ "Wireless_v1_00",
53
+ "Watches_v1_00",
54
+ "Video_Games_v1_00",
55
+ "Video_DVD_v1_00",
56
+ "Video_v1_00",
57
+ "Toys_v1_00",
58
+ "Tools_v1_00",
59
+ "Sports_v1_00",
60
+ "Software_v1_00",
61
+ "Shoes_v1_00",
62
+ "Pet_Products_v1_00",
63
+ "Personal_Care_Appliances_v1_00",
64
+ "PC_v1_00",
65
+ "Outdoors_v1_00",
66
+ "Office_Products_v1_00",
67
+ "Musical_Instruments_v1_00",
68
+ "Music_v1_00",
69
+ "Mobile_Electronics_v1_00",
70
+ "Mobile_Apps_v1_00",
71
+ "Major_Appliances_v1_00",
72
+ "Luggage_v1_00",
73
+ "Lawn_and_Garden_v1_00",
74
+ "Kitchen_v1_00",
75
+ "Jewelry_v1_00",
76
+ "Home_Improvement_v1_00",
77
+ "Home_Entertainment_v1_00",
78
+ "Home_v1_00",
79
+ "Health_Personal_Care_v1_00",
80
+ "Grocery_v1_00",
81
+ "Gift_Card_v1_00",
82
+ "Furniture_v1_00",
83
+ "Electronics_v1_00",
84
+ "Digital_Video_Games_v1_00",
85
+ "Digital_Video_Download_v1_00",
86
+ "Digital_Software_v1_00",
87
+ "Digital_Music_Purchase_v1_00",
88
+ "Digital_Ebook_Purchase_v1_00",
89
+ "Camera_v1_00",
90
+ "Books_v1_00",
91
+ "Beauty_v1_00",
92
+ "Baby_v1_00",
93
+ "Automotive_v1_00",
94
+ "Apparel_v1_00",
95
+ "Digital_Ebook_Purchase_v1_01",
96
+ "Books_v1_01",
97
+ "Books_v1_02",
98
+ ]
99
+
100
+ _DL_URLS = {
101
+ name: "https://s3.amazonaws.com/amazon-reviews-pds/tsv/amazon_reviews_us_" + name + ".tsv.gz"
102
+ for name in _DATA_OPTIONS
103
+ }
104
+
105
+
106
+ class AmazonUSReviewsConfig(datasets.BuilderConfig):
107
+ """BuilderConfig for AmazonUSReviews."""
108
+
109
+ def __init__(self, **kwargs):
110
+ """Constructs a AmazonUSReviewsConfig.
111
+ Args:
112
+ **kwargs: keyword arguments forwarded to super.
113
+ """
114
+ super(AmazonUSReviewsConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs),
115
+
116
+
117
+ class AmazonUSReviews(datasets.GeneratorBasedBuilder):
118
+ """AmazonUSReviews dataset."""
119
+
120
+ BUILDER_CONFIGS = [
121
+ AmazonUSReviewsConfig( # pylint: disable=g-complex-comprehension
122
+ name=config_name,
123
+ description=(
124
+ f"A dataset consisting of reviews of Amazon {config_name} products in US marketplace. Each product "
125
+ "has its own version as specified with it."
126
+ ),
127
+ )
128
+ for config_name in _DATA_OPTIONS
129
+ ]
130
+
131
+ def _info(self):
132
+ return datasets.DatasetInfo(
133
+ description=_DESCRIPTION,
134
+ features=datasets.Features(
135
+ {
136
+ "marketplace": datasets.Value("string"),
137
+ "customer_id": datasets.Value("string"),
138
+ "review_id": datasets.Value("string"),
139
+ "product_id": datasets.Value("string"),
140
+ "product_parent": datasets.Value("string"),
141
+ "product_title": datasets.Value("string"),
142
+ "product_category": datasets.Value("string"),
143
+ "star_rating": datasets.Value("int32"),
144
+ "helpful_votes": datasets.Value("int32"),
145
+ "total_votes": datasets.Value("int32"),
146
+ "vine": datasets.features.ClassLabel(names=["N", "Y"]),
147
+ "verified_purchase": datasets.features.ClassLabel(names=["N", "Y"]),
148
+ "review_headline": datasets.Value("string"),
149
+ "review_body": datasets.Value("string"),
150
+ "review_date": datasets.Value("string"),
151
+ }
152
+ ),
153
+ supervised_keys=None,
154
+ homepage="https://s3.amazonaws.com/amazon-reviews-pds/readme.html",
155
+ citation=_CITATION,
156
+ )
157
+
158
+ def _split_generators(self, dl_manager):
159
+ url = _DL_URLS[self.config.name]
160
+ path = dl_manager.download_and_extract(url)
161
+
162
+ # There is no predefined train/val/test split for this dataset.
163
+ return [
164
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"file_path": path}),
165
+ ]
166
+
167
+ def _generate_examples(self, file_path):
168
+ """Generate features given the directory path.
169
+
170
+ Args:
171
+ file_path: path where the tsv file is stored
172
+ Yields:
173
+ The features.
174
+ """
175
+
176
+ with open(file_path, "r", encoding="utf-8") as tsvfile:
177
+ # Need to disable quoting - as dataset contains invalid double quotes.
178
+ reader = csv.DictReader(tsvfile, dialect="excel-tab", quoting=csv.QUOTE_NONE)
179
+ for i, row in enumerate(reader):
180
+ yield i, row
dataset_infos.json ADDED
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