Kibisuvictor/African-Weather-Analysis-Dashboard

# African-Weather-Analysis-Dashboard An interactive R Shiny dashboard designed to explore, visualize, and analyze weather patterns across the African continent using the Global Weather Repository. This project implements advanced data science techniques, including dimensionality reduction (t-SNE/UMAP) and network analysis, to uncover climatic similarities between regions. ## 🚀 Features *Regional Overview*: Interactive heatmaps and distribution plots summarizing weather metrics by subregion and country. *High-Dimensional Analysis*: Explore complex weather clusters using t-SNE and UMAP algorithms, with dynamic controls for perplexity and color mapping. *Similarity Networks*: A graph-based view of African capitals based on Euclidean distance of weather conditions, featuring Louvain Community Detection. *Temporal Trends*: Animated bubble plots (via gganimate) showing the evolution of temperature, humidity, and wind over time. *Case Study*: A deep-dive network analysis of Eastern African capitals specifically for April 1st, 2025. *Data Explorer*: A granular filtering system with an interactive DT table for raw data inspection. ## 🛠️ Tech Stack Language: R Framework: Shiny, shinydashboard Data Manipulation: tidyverse, lubridate, janitor Visualization: plotly, ggplot2, viridis, ggrepel Advanced Analytics: Rtsne, uwot (UMAP), igraph Animation: gganimate, gifski ## 📦 Installation & Setup ### Clone the repository: ### Ensure you have the dataset: Place the GlobalWeatherRepository.csv file in the root directory of the project. ### Install dependencies: Open R and run: R install.packages(c("shiny", "shinydashboard", "tidyverse", "lubridate", "plotly", "janitor", "Rtsne", "uwot", "igraph", "gganimate", "ggrepel", "viridis", "DT", "shinycssloaders")) ### Run the Application: shiny::runApp() ## 📊 Methodology ### Dimensionality Reduction To visualize the 7-dimensional weather space (Temperature, Pressure, Humidity, Precipitation, Cloud Cover, Wind Degree, and Wind …