BRISZYBABY/African-Food-Price-Analysis

A dynamic Streamlit web application for analyzing and visualizing historical food price trends across African countries. Explore insights by country, market type, and produce category through interactive dashboards and statistical visualizations. # African-Food-Price-Analysis A dynamic Streamlit web application for analyzing and visualizing historical food price trends across African countries. Explore insights by country, market type, and produce category through interactive dashboards and statistical visualizations. # Key Analytics Overview Explore average food prices segmented by country, market type (retail, wholesale), and agricultural produce. Perform comparative trend analysis across multiple countries and markets to identify pricing disparities and economic patterns. Analyze temporal patterns using historical price data from the year 2000 onward to uncover seasonal or long-term fluctuations. Assess market behavior through statistical testing (e.g., T-tests) to determine significant price differences across market types. Visualize economic concepts such as price elasticity of demand using interactive, illustrative demand curves. # Analytical Stack Python: Core programming language for data analysis and application logic Streamlit: Interactive framework for building and deploying data-driven web applications Pandas: High-performance data manipulation and transformation Matplotlib & Seaborn: Statistical data visualization for uncovering trends and distributions SciPy: Advanced statistical testing and hypothesis validation # Core Functionalities Data Preview. Price Trends by Produce. Comparison by Market Type. Comparison by Country. Average Prices & Trends. # Requirement All dependencies are listed in requirements.txt # Author Brihanna Nwakor Data Analyst | Branding Expert