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Happiness in Cities Data
Mental Health & Wellness
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About
This dataset captures survey responses from individuals across various cities, evaluating their happiness levels in relation to different urban metrics. Its core purpose is to identify the critical factors that contribute to residents' overall happiness and satisfaction with their city lives. The data stems from a survey where participants rated aspects of their city on a scale of one to five, subsequently indicating whether they felt happy or unhappy. This resource offers valuable insights into the interplay between urban environment characteristics and personal well-being, which is a significant driver in people's lifestyle and residential choices.
Columns
- infoavail: Represents the availability of information concerning city services.
- housecost: Indicates the cost of housing within the city.
- schoolquality: Describes the overall quality of public schools.
- policetrust: Reflects the level of trust in the local police force.
- streetquality: Pertains to the maintenance and condition of streets and sidewalks.
- events: Denotes the availability of social community events.
- happy: The decision attribute, a binary variable where '0' signifies unhappy and '1' signifies happy.
Distribution
The dataset is provided as a CSV file, named
happydata.csv, with a size of 2.22 kB. It comprises 7 columns and contains 143 records for each column. All columns are valid, with no mismatched or missing values, ensuring data integrity for analysis.Usage
This dataset is ideally suited for:
- Exploratory Data Analysis: To uncover patterns and relationships between urban factors and happiness.
- Binary Classification: Building models to predict whether a city resident is likely to be happy or unhappy based on city metrics.
- Urban Planning and Policy Making: Informing decisions to improve city services and infrastructure, aiming to enhance residents' well-being.
- Social Research: Studying the sociological and psychological aspects of urban living and perceived happiness.
- Educational Purposes: Serving as a practical example for students learning data analysis, machine learning, and survey data interpretation.
Coverage
The dataset is based on a survey conducted in varying cities, suggesting a general urban focus rather than a specific geographic location. No particular time range for the survey's execution is specified. The demographic scope includes "people" or "residents of a city," without further breakdown by age, gender, or other specific groups.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: To develop predictive models and conduct statistical analyses on happiness factors.
- Urban Planners and City Councils: To gain insights into resident satisfaction and prioritise improvements in city services and amenities.
- Public Policy Researchers: To analyse the impact of policy decisions on citizens' well-being and identify areas for intervention.
- Sociologists and Psychologists: For research into quality of life, community satisfaction, and environmental psychology.
- Students and Educators: As a real-world dataset for educational projects in data science, statistics, and urban studies.
Dataset Name Suggestions
- Urban Happiness Metrics
- City Resident Satisfaction Survey
- Municipal Well-being Factors
- Urban Life Quality Indicators
- Happiness in Cities Data
Attributes
Original Data Source: Happiness in Cities Data
QUALITY