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This project explores homelessness data across the United States using 2018 Point-in-Time count figures. By analyzing trends at the state and local (CoC) level, the project aims to uncover patterns in shelter access.

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BigQuery-Data-Exploration

-- PROJECT: Homelessness Data Exploration (2018 Focus) -- DATA SOURCE: merit-america-data-project-ew.Exploration_Project.homelessness


-- QUERY 1: Top 3 CoC Areas with Highest Number of Unaccompanied Homeless Youth Under 18 (2018)


SELECT CoC_Name, State, Homeless_Unaccompanied_Youth_Under_18 FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE Count_Year = 2018 ORDER BY Homeless_Unaccompanied_Youth_Under_18 DESC LIMIT 3;


-- QUERY 2: Unsheltered Homeless Trends in Delaware (2012–2018)


SELECT Count_Year, SUM(Unsheltered_Homeless) AS total_unsheltered FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE State = 'DE' GROUP BY Count_Year ORDER BY Count_Year ASC;

-- Observation: Review total_unsheltered year over year to confirm increasing trend.


-- QUERY 3: Number of Locations with At Least 1 Person in Safe Haven Shelter in 2018


SELECT COUNT(DISTINCT CoC_Name) AS locations_with_safe_haven FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE Count_Year = 2018 AND Sheltered_SH_Homeless > 0;


-- QUERY 4: Top 3 CoC Areas by Safe Haven (SH) Sheltered Homeless Count (2018)


SELECT CoC_Name, State, Sheltered_SH_Homeless FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE Count_Year = 2018 ORDER BY Sheltered_SH_Homeless DESC LIMIT 3;


-- QUERY 5: Top 7 States by Overall Homeless Population (2018)


SELECT State, SUM(Overall_Homeless) AS total_overall_homeless FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE Count_Year = 2018 GROUP BY State ORDER BY total_overall_homeless DESC LIMIT 7;

-- Compare these states to the U.S. 2018 population rankings for representation analysis.


-- QUERY 6: Locations with >1000 Overall Homeless AND <100 Unsheltered Homeless (2018)


SELECT CoC_Name, State, Overall_Homeless, Unsheltered_Homeless FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE Count_Year = 2018 AND Overall_Homeless > 1000 AND Unsheltered_Homeless < 100 ORDER BY Overall_Homeless DESC;

-- These areas may be effective at providing shelter despite large homeless populations.


-- QUERY 7: From the Above List, Filter for Locations Where Unsheltered is < 2% of Overall Homeless


SELECT CoC_Name, State, Overall_Homeless, Unsheltered_Homeless, ROUND(Unsheltered_Homeless / Overall_Homeless, 4) AS unsheltered_percentage FROM merit-america-data-project-ew.Exploration_Project.homelessness WHERE Count_Year = 2018 AND Overall_Homeless > 1000 AND Unsheltered_Homeless < 100 AND (Unsheltered_Homeless / Overall_Homeless) < 0.02 ORDER BY unsheltered_percentage ASC;

-- These are exemplary locations where shelter access is nearly universal among the homeless population.

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This project explores homelessness data across the United States using 2018 Point-in-Time count figures. By analyzing trends at the state and local (CoC) level, the project aims to uncover patterns in shelter access.

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