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Election Summary
🔍 Key Insights
📊 Demographic Correlations
Correlation coefficients between demographic variables and candidate vote share. Values range from -1 (strong negative) to +1 (strong positive).
💰 Income Analysis
🎓 Education Analysis
👥 Racial Composition
Voting patterns in areas with majority (>50%) racial/ethnic populations
🌍 Hispanic/Latino & Asian Origins
Hispanic/Latino Origins
Areas where specific origin groups comprise >20% of Hispanic/Latino population
Asian Origins
Areas where specific origin groups comprise >20% of Asian population
🌍 African-Born Communities
Voting patterns by percentage of African-born population (showing non-linear relationship)
⚠️ Important Note on African-Born Analysis
This analysis reveals a non-linear relationship: Mamdani's support is strongest in areas with LOW African-born populations (0-5%) and decreases as the African-born percentage increases. In areas with >15% African-born population, Cuomo actually leads. This demonstrates why using a single threshold (like ">5%") can be misleading—it masks the underlying gradient in voting patterns.
📍 Demographics by Winner
Average demographic characteristics of Election Districts won by each candidate
Methodology
Data Sources: NYC Board of Elections (election results) and U.S. Census Bureau ACS 5-Year Estimates 2022 (demographics).
Geographic Matching: Election Districts (EDs) were spatially joined to Census Tracts using ED centroids, achieving 98% match rate (4,252 of 4,338 EDs).
Analysis Coverage: Analysis includes only EDs with complete election and demographic data.
Correlations: Pearson correlation coefficients calculated between demographic variables and candidate vote percentages.