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Populations Satisfaction Indicators
Data Science and Analytics
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About
This curated collection of data, titled the 2024 Urban Bliss Index, focuses on factors influencing overall happiness across diverse global cities. It was exclusively assembled by Emirhan BULUT, aiming to unveil insights into urban living conditions and populace satisfaction. The data features vital attributes, including metrics on auditory comfort, traffic density, air quality, and economic indicators. It facilitates a nuanced exploration of urban well-being and fosters a deeper understanding of the elements shaping urban happiness. Moreover, this material establishes the groundwork for developing a sophisticated Deep Q-Network model, known as PIYAAI_2. Leveraging Reinforcement Learning, this model continually refines its predictive capabilities for forecasting future urban scenarios as it assimilates new information.
Columns
- City: The name of the urban centre being recorded (e.g., Greymouth, Hokitika).
- Month: The month in which the data was collected, with 12 unique values observed.
- Year: The year of the recording, spanning from 2024 to 2029.
- Decibel_Level: Measures the auditory comfort of the city environment, with values typically ranging between 50 and 90.
- Traffic_Density: Categorisation of traffic levels, primarily noted as Low (68%) or Medium (24%).
- Green_Space_Area: A metric representing the amount of green space, with values observed between 5 and 2425.
- Air_Quality_Index: An indicator of air quality, spanning a range from 5 to 245.
- Happiness_Score: A derived score indicating populace satisfaction, with a range from -123 to 8.6.
- Cost_of_Living_Index: An economic measure, showing a minimum value of 20 and a maximum of 130.
- Healthcare_Index: An indicator of healthcare provision, with recorded values falling between 35 and 99.
Distribution
This dataset is structured across 10 distinct columns and contains 545 valid records. Crucially, all attributes are fully populated, showing 0% missing data and 0% mismatched data for every column. The recording years are distributed from 2024 through to 2029, with the most common year being 2024. Traffic density is predominantly categorised as Low. The highest frequency of decibel levels falls within the 54.00–58.00 range. The expected update frequency for this product is Annually.
Usage
The dataset is ideal for facilitating a nuanced exploration of urban well-being. It is suitable for applications such as:
- Training the PIYAAI_2 Deep Q-Network model for predictive scenario analysis.
- Researching the intricate interplay between urban environmental factors (like air quality and noise) and subjective well-being.
- Data Analytics projects and generating Data Storytelling outputs.
- Developing policy strategies aimed at enhancing populace satisfaction and improving urban living conditions.
- Utilising data manipulation packages such as
dplyrand visualisation tools likePlotly.
Coverage
The data covers diverse global cities, with examples including Greymouth and Hokitika. The time span recorded ranges across years from 2024 through to 2029. Each record includes specific metrics for the recording month and year. The primary scope focuses on factors influencing the well-being and satisfaction of city populations.
License
CC0: Public Domain
Who Can Use It
- Policymakers: To gain insights and inform decisions regarding elements shaping urban happiness.
- Researchers: To conduct quantitative analyses on urban factors influencing subjective well-being.
- Data Analysts and Beginners: The dataset has a high usability score (10.00) and is tagged as suitable for beginner-level engagement with data analytics and related technologies.
Dataset Name Suggestions
- Urban Bliss Index
- Global City Well-being Metrics
- Populations Satisfaction Indicators
- PIYAAI_2 Model Training Data
Attributes
Original Data Source: Populations Satisfaction Indicators
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