Dataset: Used Phones & Tablets Pricing Dataset

About this Dataset

Used Phones & Tablets Pricing Dataset

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

Tables

Used Device Data

@kaggle.ahsan81_used_handheld_device_data.used_device_data

100.96 KB
3454 rows
15 columns


CREATE TABLE used_device_data (
  "device_brand" VARCHAR,
  "os" VARCHAR,
  "screen_size" DOUBLE,
  "n_4g" VARCHAR,
  "n_5g" VARCHAR,
  "rear_camera_mp" DOUBLE,
  "front_camera_mp" DOUBLE,
  "internal_memory" DOUBLE,
  "ram" DOUBLE,
  "battery" DOUBLE,
  "weight" DOUBLE,
  "release_year" BIGINT,
  "days_used" BIGINT,
  "normalized_used_price" DOUBLE,
  "normalized_new_price" DOUBLE
);