This project involved a detailed analysis of census data to uncover critical demographic insights and provide actionable recommendations for urban planning and community development. The findings were compiled into a comprehensive report for an international client, designed to inform key decisions on housing, infrastructure, healthcare, and transportation. The analysis also considered future community needs based on current demographic trends and national census data.
Project Overview
This project focused on analyzing recent census data to address key community challenges, including employment trends, housing requirements, and public infrastructure needs. The dataset included multiple variables such as age distribution, marital status, occupation, and household size, providing a holistic view of the population's structure. The final deliverable was a code analysis in Python, followed by an in-depth report that highlighted the significant trends and provided recommendations based on the data.
Key Steps and Findings
Data Cleaning and Preparation:
Missing Values: Addressed missing values in columns such as marital status, religion, and gender by replacing them with 'Unknown' to ensure data integrity.
Data Type Conversion: Converted age data to integer format for more accurate analysis.
Data Binning: Organized age data into five-year intervals, simplifying the analysis of age-related trends.
Demographic Insights:
Age Distribution: A balanced mix of young adults, middle-aged individuals, and a notable elderly population.
Marital Status: Predominantly single and married individuals, with a significant number of 'Unknown' entries highlighting gaps in data collection.
Gender Balance: A nearly equal distribution of males and females, reinforcing the need for gender-neutral planning in services and infrastructure.
Employment and Commuting Trends:
Employment Rate: Approximately 65.4% of the population is employed, aligning with national labor statistics.
Commuter Population: Around 90% of the population, including students and professionals, engage in daily commuting, underlining the need for improved transportation infrastructure.
Housing and Occupancy:
Average Household Size: The average household size was calculated at 2.62 persons per household, reflecting a mixture of small and larger family units.
Diverse Housing Needs: Based on occupancy data and marital status, the report recommended a balanced housing development strategy, catering to both single-occupancy and family homes.
Infirmity and Healthcare:
General Health: Most of the population reported no significant health issues, although some physical and mental disabilities were present.
Healthcare Recommendations: Suggested the establishment of a minor injuries unit to address general healthcare needs across all age groups.
Challenges and Solutions
Data Integrity: The dataset contained missing and incomplete entries in key columns such as marital status and infirmity. These issues were addressed by categorizing missing data to maintain consistency.
Comprehensive Analysis: Given the large variety of data points, the analysis required segmenting the data into meaningful categories. The use of Python for data cleaning and analysis allowed for efficient processing and visualization of the trends.
Client-Specific Recommendations: Tailored the findings to align with the client’s strategic goals, including the development of transportation infrastructure and diversified housing solutions.
Final Deliverables
Census Data Report: The final report provided a clear summary of the findings and actionable recommendations, such as the need for new housing developments and the construction of a train station to accommodate the large commuter population. It also emphasized data collection improvements for future censuses.
Python Code: Delivered a detailed analysis script in Python, showcasing how the data was cleaned, processed, and visualized. The code allows the client to run future analyses on updated datasets efficiently.
Impact and Recommendations
Transportation Infrastructure: Based on the high percentage of commuters (90%), the report strongly recommended building a train station to alleviate road traffic and improve daily commute efficiency.
Housing Development: Given the average household size and varied family structures, a balanced approach to housing was proposed, focusing on both low and moderate-density developments.
Healthcare Facilities: The demographic spread indicated a low but significant need for accessible healthcare services, leading to the recommendation of a minor injuries unit in the community.
Improved Data Collection: Noted the importance of more detailed data collection in future censuses, particularly for marital status and health data, to improve the accuracy of future planning.
Conclusion
This project not only provided immediate insights into the community’s current state but also offered data-driven recommendations to ensure sustainable growth. The analysis laid a foundation for long-term urban planning that can adapt to demographic shifts and support a thriving, well-functioning community.
