In this analysis, we calculate the total fatalities and economic losses caused by various weather events using data from the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database, which can be accessed via [this link](https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2). Additional documentation on the data variables is available here: - [Data documentation 1](https://d396qusza40orc.cloudfront.net/repdata%2Fpeer2_doc%2Fpd01016005curr.pdf) - [Data documentation 2](https://d396qusza40orc.cloudfront.net/repdata%2Fpeer2_doc%2FNCDC%20Storm%20Events-FAQ%20Page.pdf) The analysis starts by downloading and loading the data into R, followed by inspecting the raw data. We calculate the sum of fatalities and economic losses for each weather event across the United States. The events with the largest fatalities and economic losses are identified. The data is arranged in descending order based on both fatalities and economic losses. We extract the top 10 events with the highest fatalities and the top 10 with the highest economic losses. Visualizations are then created to highlight these top 10 events. This analysis helps to understand the most impactful weather events in terms of human life and economic costs. The results provide insights into the consequences of severe weather events on public health and the economy.

This professional 5-slide presentation showcases the BMI Calculator & Health Advisor Shiny application, created by Rahul Vijayraghavan on March 20, 2026. It covers the global obesity problem, demonstrates live R code for BMI calculations with WHO classification, highlights the app's interactive features, provides links to the live app and GitHub repository, and validates project requirements. The presentation features professional styling with color-coded text, Helvetica Neue typography, and responsive design for effective communication of the app's functionality and value.

Project_2026

OLYMPIC GAMES ANALYSIS