CONTEXT- The used and refurbished device market has grown considerably over the past decade as it provide cost-effective alternatives to both consumers and businesses that are looking to save money when purchasing one. Maximizing the longevity of devices through second-hand trade also reduces their environmental impact and helps in recycling and reducing waste. Here is a sample dataset of normalized used and new pricing data of refurbished / used devices.
OBJECTIVE- The objective is to do Exploratory Data Analytics and apply Linear Regression to create a model which can help in pricing of such devices.
META DATA
device_brand: Name of manufacturing brand
os: OS on which the device runs
screen_size: Size of the screen in cm
4g: Whether 4G is available or not
5g: Whether 5G is available or not
front_camera_mp: Resolution of the rear camera in megapixels
back_camera_mp: Resolution of the front camera in megapixels
internal_memory: Amount of internal memory (ROM) in GB
ram: Amount of RAM in GB
battery: Energy capacity of the device battery in mAh
weight: Weight of the device in grams
release_year: Year when the device model was released
days_used: Number of days the used/refurbished device has been used
normalized_new_price: Normalized price of a new device of the same model
normalized_used_price (TARGET): Normalized price of the used/refurbished device