Toy Products On Amazon
10,000 toy products on Amazon.com
@kaggle.promptcloudhq_toy_products_on_amazon
10,000 toy products on Amazon.com
@kaggle.promptcloudhq_toy_products_on_amazon
This is a pre-crawled dataset, taken as subset of a bigger dataset (more than 115k products) that was created by extracting data from Amazon.com.
This dataset has following fields:
product_namemanufacturer - The item manufacturer, as reported on Amazon. Some common "manufacturers", like Disney, actually outsource their assembly line.pricenumber_available_in_stocknumber_of_reviewsnumber_of_answered_questions - Amazon includes a Question and Answer service on all or most of its products. This field is a count of how many questions that were asked actually got answered.average_review_ratingamazon_category_and_sub_category - A tree-based, >>-delimited categorization for the item in question.customers_who_bought_this_item_also_bought - References to other items that similar users bought. This is a recommendation engine component that played a big role in making Amazon popular initially.descriptionproduct_informationproduct_descriptionitems_customers_buy_after_viewing_this_itemcustomer_questions_and_answers - A string entry with all of the product's JSON question and answer pairs.customer_reviews - A string entry with all of the product's JSON reviews.sellers - A string entry with all of the product's JSON seller information (many products on Amazon are sold by third parties).This dataset was created by PromptCloud's in-house web-crawling service.
This detailed dataset can be used to answer questions like:
What types of toys are most popular on Amazon?
How dominant are brands in the Amazon toy market?
Can you break down reviews to analyze their sentiment and contents?
CREATE TABLE amazon_co_ecommerce_sample (
"uniq_id" VARCHAR,
"product_name" VARCHAR,
"manufacturer" VARCHAR,
"price" VARCHAR,
"number_available_in_stock" VARCHAR,
"number_of_reviews" DOUBLE,
"number_of_answered_questions" DOUBLE,
"average_review_rating" VARCHAR,
"amazon_category_and_sub_category" VARCHAR,
"customers_who_bought_this_item_also_bought" VARCHAR,
"description" VARCHAR,
"product_information" VARCHAR,
"product_description" VARCHAR,
"items_customers_buy_after_viewing_this_item" VARCHAR,
"customer_questions_and_answers" VARCHAR,
"customer_reviews" VARCHAR,
"sellers" VARCHAR
);Anyone who has the link will be able to view this.