Dark Mode
Smartphone Specification Pricing Data
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a rich collection of mobile phone features intended for classification tasks. It allows users to predict the price range of cell phones based on their specifications. The data includes details on battery power, camera quality, memory, and connectivity options, making it an ideal resource for understanding the factors influencing mobile device pricing.
Columns
- battery_power: The total energy capacity of the battery in milliampere-hours (mAh).
- blue: Indicates whether the device has Bluetooth capability (1 for yes, 0 for no).
- clock_speed: The processing speed of the microprocessor.
- dual_sim: Specifies if the device supports two SIM cards simultaneously (1 for yes, 0 for no).
- fc: The quality of the front camera in MegaPixels.
- four_g: Indicates whether the device supports 4G network connectivity (1 for yes, 0 for no).
- int_memory: The internal storage capacity of the device in Gigabytes.
- m_dep: The physical depth of the device in Centimetres.
- mobile_wt: The weight of the device.
- n_cores: The number of processor cores in the device.
- pc: The quality of the primary camera in MegaPixels.
- px_height: The height of the screen's pixel resolution.
- px_width: The width of the screen's pixel resolution.
- ram: The amount of random access memory in Megabytes.
- sc_h: The height of the device screen in Centimetres.
- sc_w: The width of the device screen in Centimetres.
- talk_time: The maximum talk time supported by a fully charged battery.
- three_g: Indicates whether the device supports 3G network connectivity (1 for yes, 0 for no).
- touch_screen: Specifies if the device has a touch screen (1 for yes, 0 for no).
- wifi: Indicates whether the device has Wi-Fi capability (1 for yes, 0 for no).
- price_range: The categorised price of the device, serving as the target variable for classification.
Distribution
The dataset is provided as a CSV file named 'CellPhone_test.csv'. It contains 1000 records (rows) and 21 columns, with a file size of 63.85 kB. All columns appear to be free of missing data.
Usage
This dataset is ideally suited for machine learning classification problems. Potential applications include:
- Developing models to predict the price range of new mobile phone models based on their specifications.
- Market analysis to understand which features have the strongest impact on mobile phone pricing.
- Feature engineering for mobile device attributes.
- Educational purposes for learning and applying classification algorithms.
Coverage
The sources do not specify the geographic, time range, or demographic scope of the data.
License
CC0: Public Domain
Who Can Use It
- Data scientists and machine learning engineers for building predictive models.
- Researchers interested in consumer electronics pricing and specification analysis.
- Students and educators learning about supervised machine learning, particularly classification.
- Business analysts seeking insights into mobile phone market dynamics.
Dataset Name Suggestions
- Mobile Phone Price Prediction Dataset
- Cell Phone Features & Price Classification
- Smartphone Specification Pricing Data
- Handset Price Classifier Features
- Mobile Device Price Categorisation
Attributes
Original Data Source: Smartphone Specification Pricing Data
QUALITY