https://github.com/ramyacp14/global-warming-analysis

Analyzes and visualizes global temperature data to identify climate change trends. The project includes global and seasonal temperature trend analysis, country-wise and city-specific temperature visualizations, and geospatial analysis with interactive maps and heatmaps.
https://github.com/ramyacp14/global-warming-analysis

data-visualization folium geospatial-analysis jupyter-notebook matplotlib numpy opencage-geocoder pandas plotly python seaborn

Last synced: 25 days ago
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Analyzes and visualizes global temperature data to identify climate change trends. The project includes global and seasonal temperature trend analysis, country-wise and city-specific temperature visualizations, and geospatial analysis with interactive maps and heatmaps.

• Host: GitHub
• URL: https://github.com/ramyacp14/global-warming-analysis
• Owner: ramyacp14
• Created: 2024-04-16T22:39:51.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-06T21:18:12.000Z (over 1 year ago)
• Last Synced: 2025-03-02T21:43:05.348Z (about 1 year ago)
• Topics: data-visualization, folium, geospatial-analysis, jupyter-notebook, matplotlib, numpy, opencage-geocoder, pandas, plotly, python, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 8.26 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Global Temperature Analysis Project

## Overview

This project conducts a comprehensive analysis of global temperature data to identify and visualize climate change trends. It leverages various data visualization techniques and geospatial analysis to present findings from different geographical perspectives.

## Key Analyses Performed

1. Global Temperature Trend Analysis

   - Examined long-term temperature changes using GlobalTemperatures.csv

   - Created time series visualizations to illustrate global warming trends

2. Country-wise Average Temperature Calculation

   - Calculated and visualized average temperatures for countries worldwide

   - Used choropleth maps to display global temperature distribution

3. Seasonal Temperature Analysis

   - Analyzed temperature variations across different seasons

   - Created visualizations to show seasonal patterns in various regions

4. US State Temperature Heatmap

   - Developed a heatmap visualization for temperature distribution across US states

   - Utilized geospatial libraries to map temperature data to state boundaries

5. Indian Cities Temperature Analysis

   - Focused on temperature trends in major Indian cities

   - Created city-specific visualizations and comparisons

## Geospatial Analysis

- Utilized geospatial libraries (folium, OpenCage Geocoder) for mapping and geographical data processing

- Created interactive maps to visualize temperature data on geographical layouts

- Implemented heat maps and choropleth maps for spatial temperature distribution

## Dependencies

- Data Processing: numpy, pandas

- Visualization: matplotlib, plotly, seaborn

- Geospatial Analysis: folium, opencage

## Data Sources

- GlobalLandTemperaturesByCountry.csv

- GlobalLandTemperaturesByState.csv

- GlobalLandTemperaturesByCity.csv

- GlobalTemperatures.csv

## Setup and Usage

1. Clone the repository

2. Install dependencies: `pip install -r requirements.txt`

3. Ensure data files are in the project directory

4. Run the Jupyter notebook or Python script

## Visualizations

- Interactive charts and graphs using Plotly

- Geospatial visualizations with Folium:

  - World map with country-level temperature data

  - US map with state-level temperature heatmap

  - Indian map with city-specific temperature data