https://github.com/aaryan-agr/noaa-hurricane-data-analysis
This project analyzes historical hurricane data from the NOAA dataset to identify trends, patterns, and impacts of hurricanes over time. Using R, we clean, process, and visualize storm trajectories, wind speeds, and pressure changes. The analysis includes geospatial visualizations and time-series trends to understand hurricane intensity.
https://github.com/aaryan-agr/noaa-hurricane-data-analysis
climate-analysis climate-data-analysis geospatial-analysis r time-series-analysis
Last synced: 3 months ago
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This project analyzes historical hurricane data from the NOAA dataset to identify trends, patterns, and impacts of hurricanes over time. Using R, we clean, process, and visualize storm trajectories, wind speeds, and pressure changes. The analysis includes geospatial visualizations and time-series trends to understand hurricane intensity.
- Host: GitHub
- URL: https://github.com/aaryan-agr/noaa-hurricane-data-analysis
- Owner: Aaryan-Agr
- Created: 2025-03-05T01:13:32.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-03-05T01:55:57.000Z (4 months ago)
- Last Synced: 2025-03-05T02:23:10.588Z (4 months ago)
- Topics: climate-analysis, climate-data-analysis, geospatial-analysis, r, time-series-analysis
- Homepage:
- Size: 29.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# NOAA Hurricane Data Analysis
## Overview
This project analyzes historical hurricane data from the NOAA (National Oceanic and Atmospheric Administration) dataset. It focuses on identifying trends, patterns, and impacts of hurricanes over time using R and RMarkdown.
## Features
- Data cleaning and preprocessing of NOAA hurricane records.
- Exploratory data analysis (EDA) with visualizations.
- Statistical analysis of hurricane intensity, frequency, and impact.
- Time series analysis to identify trends.
- Mapping hurricane paths using geospatial data.
## Dataset
The data used in this project comes from NOAA's publicly available hurricane records. The dataset includes details such as:
- Hurricane name and year
- Wind speed and pressure
- Latitude and longitude coordinates
- Category and damage estimates
## Technologies Used
- **R**: For data analysis and visualization.
- **RMarkdown**: For generating reproducible reports.
- **ggplot2**: For visualization.
- **dplyr**: For data manipulation.
- **tidyverse**: For streamlined data handling.
## How to Run
1. Clone this repository:
```sh
git clone https://github.com/Aaryan-agr/noaa-hurricane-analysis.git
2. Open the project in RStudio.
3. Install dependencies if needed.
``` r
install.packages(c("tidyverse", "ggplot2", "dplyr"))
```
4. Run the RMarkdown file
## Results
The analysis aims to provide insights into:
- Changes in hurricane intensity over time.
- Regional distribution of hurricanes.
- Correlations between climate patterns and hurricane activity.
## Future Improvements
- Incorporate machine learning models for predictive analysis.
- Enhance geospatial visualizations with interactive maps.
- Compare NOAA data with other meteorological datasets.