PC Component Prices Comparison
Detailed Prices, Scores, and Reviews from Different Brands and Categories
@kaggle.thedevastator_pc_component_prices_comparison
Detailed Prices, Scores, and Reviews from Different Brands and Categories
@kaggle.thedevastator_pc_component_prices_comparison
By [source]
This dataset is the perfect resource to analyze and compare prices, scores, and reviews of a wide assortment of PC components across various brands and categories. Utilize this data to make well-informed decisions regarding your purchase. Our data set includes the latest timestamps collected from industry leaders, so you can always be sure that what you’re seeing is up-to-date. Specifically this database includes every insightful detail such as company name, brand name, category information along with product numbers as well as price points both on individual products as well as averages by brand and category for easier comparison shopping. Furthermore users are able to see in depth scores for each product combined with image urls for easy research and above all reviews from other users who have used the same product before you decide on anything making it easy to decide if the price tag or quality of the product is worth it or not. Let our comprehensive comparison save you time and hassle when buying your next PC component!
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This dataset provides a comprehensive comparison of prices, scores, reviews, product numbers and more from a variety of different PC components from different brands and categories. In order to use this dataset effectively and gain the best insights, it is important to be aware of the following points:
1. Categories: The data can be filtered by category so if you are looking for particular type of component like graphic card or processor you can filter out easily.
Here’s how you can do that: Sort the data by category column (in Ascending Order) and all items related to the same categories will appear together in a consecutive sequence.2. Brands: To get an overview of brands related to a particular category check out
brand_namecolumn; Here you will see all different brands sorted under each category along with their corresponding prices and scores etc., Similarly, You can also sort them in ascending/descending order based on price or score or any other parameter mentioned above in our Columns section3. Filtering Your Results : Sort your results according to many factors like
price,reviews,score. For example if your preference as per budget is low price then sort by usingpricecolumn in ascending order & similarly for with regards to quality score then sort using score column descending order & if reviews highly matters then go with descending order under ‘reviews’ columns4 Searching Desired Component(PC): Where ever applicable text search feature also available such as searching for desired prefixed term may appear at most times;it filters any matching pattern noted within product_number field Therefore try including appropriate terms before running searches. Excluding dates from your terms might help getting best possible outcomes
- Use this dataset to compare PC components across various brands, categories and prices to create personalized PC builds with the most cost-efficient components.
- Compare the scores and reviews of different products to identify the best value for money options across categories, brands, etc.
- Analyze the dataset to find trends in terms of which companies provide better performance at lower prices or have a higher proportion of positive reviews over time
If you use this dataset in your research, please credit the original authors.
Data Source
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
File: ComponentesPC_Scraper_DataSet.csv
| Column name | Description |
|---|---|
| timestamp | Date and time of the data entry. (DateTime) |
| company_name | Name of the company that manufactures the product. (String) |
| brand_name | Brand name of the product. (String) |
| category | Category of the product. (String) |
| product_number | Unique identifier of the product. (String) |
| price | Price of the product in US dollars. (Float) |
| score | User rating of the product. (Integer) |
| image_url | URL of the product image. (String) |
| reviews | User reviews of the product. (String) |
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .
CREATE TABLE componentespc_scraper_dataset (
"timestamp" BIGINT,
"company_name" VARCHAR,
"name" VARCHAR,
"brand_name" VARCHAR,
"category" VARCHAR,
"product_number" VARCHAR,
"price" DOUBLE,
"score" DOUBLE,
"image_url" VARCHAR,
"reviews" BIGINT
);Anyone who has the link will be able to view this.