Flipkart Laptop Listings and Hardware Performance Data

Columns

• link: The direct product URL on Flipkart.
• name: The full retail product name of the laptop.
• user rating: User-provided ratings on Flipkart (note: approximately 30% of records are missing this rating).
• Price (in Indian Rupees): The price of the laptop in local currency.
• Type: The category of the laptop (e.g., gaming laptop, thin and light laptop).
• Dedicated Graphic Memory Capacity: The size of the GPU memory in Gigabytes (GB).
• Processor Brand: The manufacturer of the CPU (e.g., Intel, AMD, Apple).
• SSD: Boolean indicator (1 for Solid State Drive storage, 0 otherwise).
• RAM (in GB): The installed Random Access Memory capacity.
• RAM Type: The type of RAM used (e.g., ddr4, lpddr4x).
• Expandable Memory: Boolean indicator (1 if memory is expandable, 0 otherwise).
• Operating System: The pre-installed OS (e.g., Windows, Chrome OS, Mac).
• Touchscreen: Boolean indicator (1 if touchscreen is present, 0 otherwise).
• Screen Size (in inch): Diagonal screen measurement in inches.
• Weight (in kg): The laptop's weight in kilograms.
• Refresh Rate: The screen refresh rate.
• screen_resolution: Display resolution details.
• company: The manufacturer of the laptop (e.g., Asus, Dell, HP).
• Storage: Total storage capacity in GB.
• Processor name: The specific model name of the CPU.
• CPU_ranking: A performance rank for the processor, where a lower numerical value signifies better performance.
• battery_backup: Estimated battery life in hours.
• gpu name: The specific model name of the GPU.
• gpu_benchmark: A performance score for the GPU, where a higher score signifies better performance (sourced from gpu.userbenchmark.com).
• ram_type_tokenized: A numerical tokenisation of RAM type, where a higher number indicates newer or better technology.
• gpu_processor tokenized: A numerical tokenisation of GPU names.

Distribution

Usage

• Developing Recommender Systems that suggest laptops based on a user's desired hardware specifications or performance expectations.
• Exploratory Data Analysis (EDA) to investigate the complex relationships between pricing, processor brands, storage types, and measured performance benchmarks.
• E-commerce services market analysis, focusing on inventory, popular feature sets, and pricing structures specific to the Indian market in 2022.
• Studying the impact of ranked hardware performance (CPU/GPU) on the retail value and user reception of products.

Coverage

License

Who Can Use It

• Data Scientists and Modellers: To train machine learning algorithms, particularly for price prediction or feature importance analysis.
• E-commerce Strategists: To gain market intelligence regarding competitor product lines, pricing, and hardware trends in the Indian online retail space.
• Technology Researchers: Individuals interested in benchmarking real-world hardware performance metrics against consumer-facing specifications and retail prices.

Dataset Name Suggestions

• Laptop Ranked Specifications and Benchmarks (India 2022)
• Flipkart Laptop Listings and Hardware Performance Data
• Indian E-commerce Laptop Market Data (June 2022)

Attributes