Kimto1/cerf-nigeria-funding-dashboard
Domain:
socioeconomicCreator:
Kim
Host:
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 …