Kimto1/cerf-nigeria-funding-dashboard

Interactive Python and Streamlit analysis of CERF funding allocations represented in a Nigeria project-level dataset. # CERF Nigeria Funding Analysis Dashboard An end-to-end data analytics capstone project examining approved Central Emergency Response Fund (CERF) allocations represented in a supplied Nigeria project-level dataset. The project combines data cleaning, validation, exploratory analysis, interactive visualisation and dashboard development using Python, Pandas, Plotly and Streamlit. ## Project Objectives This project aims to: - Clean and standardise the supplied CERF Nigeria dataset. - Validate the accuracy and integrity of the cleaned data. - Analyse funding by agency, year, emergency type, funding window, sector combination and crisis grouping. - Identify leading agencies, sectors, years and projects. - Examine important source-data quality limitations. - Build an interactive dashboard for exploring and downloading filtered project records. ## Executive Findings The supplied dataset contains 125 projects and approximately $207.84 million in approved funding. Key findings include: - UNICEF received the highest total funding at approximately $73.20 million and implemented the largest number of projects, with 39 projects. - WFP had the highest average funding per project at approximately $4.05 million. - The two largest agencies accounted for 64.5% of total approved funding. - Displacement-related projects received approximately $109.40 million. - Rapid Response accounted for 70.6% of funding, compared with 29.4% for Underfunded Emergencies. - Food Assistance was the leading recorded sector combination, receiving approximately $46.82 million. - Funding peaked in 2021 at approximately $33.50 million. - The largest project was `20-RR-WFP-056`, valued at approximately $15 million. - Project-grouping information was absent from 51.2% of source records. - CAP-code information was absent from 69.6% of source records. These findings describe allocation patterns within the supplied dataset. They do not measure humanitarian need, programme effectiveness, expenditure or o …