Project: Impact Analysis of GoodThought NGO Initiatives

GoodThought NGO has been a catalyst for positive change, focusing its efforts on education, healthcare, and sustainable development to make a significant difference in communities worldwide. With this mission, GoodThought has orchestrated an array of assignments aimed at uplifting underprivileged populations and fostering long-term growth.

This project offers a hands-on opportunity to explore how data-driven insights can direct and enhance these humanitarian efforts. In this project, you'll engage with the GoodThought PostgreSQL database, which encapsulates detailed records of assignments, funding, impacts, and donor activities from 2010 to 2023. This comprehensive dataset includes:

Assignments: Details about each project, including its name, duration (start and end dates), budget, geographical region, and the impact score.
Donations: Records of financial contributions, linked to specific donors and assignments, highlighting how financial support is allocated and utilized.
Donors: Information on individuals and organizations that fund GoodThought’s projects, including donor types.

Refer to the below ERD diagram for a visual representation of the relationships between these data tables:

You will execute SQL queries to answer two questions, as listed in the instructions. Good luck!

DataFrameas

df2

variable

select * from public.donors limit 5

DataFrameas

df1

variable

select * from public.donations limit 5

DataFrameas

df

variable

select * from public.assignments limit 5

DataFrameas

highest_donation_assignments

variable

-- highest_donation_assignments
-- first SQL cell

WITH donation_details AS (
    SELECT
        d.assignment_id,
        ROUND(SUM(d.amount), 2) AS rounded_total_donation_amount,
        dn.donor_type
    FROM donations d
    JOIN donors dn ON d.donor_id = dn.donor_id
    GROUP BY d.assignment_id, dn.donor_type
)
SELECT
    a.assignment_name,
    a.region,
    dd.rounded_total_donation_amount,
    dd.donor_type
FROM assignments a
JOIN donation_details dd ON a.assignment_id = dd.assignment_id
ORDER BY dd.rounded_total_donation_amount DESC
LIMIT 5;

DataFrameas

top_regional_impact_assignments

variable

-- top_regional_assignments
-- second SQL cell

WITH donation_counts AS (
    SELECT
        assignment_id,
        COUNT(donation_id) AS num_total_donations
    FROM donations
    GROUP BY assignment_id
),
ranked_assignments AS (
    SELECT
        a.assignment_name,
        a.region,
        a.impact_score,
        dc.num_total_donations,
        ROW_NUMBER() OVER (PARTITION BY a.region ORDER BY a.impact_score DESC) AS rank_in_region
    FROM assignments a
    JOIN donation_counts dc ON a.assignment_id = dc.assignment_id
    WHERE dc.num_total_donations > 0
)
SELECT
    assignment_name,
    region,
    impact_score,
    num_total_donations
FROM ranked_assignments
WHERE rank_in_region = 1
ORDER BY region ASC;