This project aims to visualize climate change data to provide insights into the impact of climate change over time. It includes interactive visualizations and analysis of various climate indicators.
Data visualization is about telling the audience a story, which can help them understand and communicate the complex issues surrounding climate change. By presenting data visually, we can gain insights and identify trends that would be difficult to see in raw data alone. This project will use data visualization to explore the various impacts of climate change and show how it affects different regions and populations of India and worldwide.
We are focusing on climate change in India and what factors are responsible for the change. Various interactive visualizations include a Treemap, Time series graph, Bubble chart, Choropleth map, etc., which will give our audience a deep understanding of climate change.
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Interactive Visualizations: The project includes interactive charts, graphs, and maps that allow users to explore climate data and understand the trends and patterns.
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Climate Indicators: Multiple climate indicators, such as temperature, precipitation, sea level rise, and CO2 emissions, are visualized to provide a comprehensive view of climate change.
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Historical Analysis: The project includes historical analysis of climate data to identify long-term trends, seasonal variations, and anomalies.
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Comparative Analysis: Users can compare climate data across different regions or time periods to observe regional differences and changes over time.
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Data Sources: The project relies on reliable and authoritative sources for climate data, ensuring accuracy and credibility.
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Programming Languages: Python
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Data Visualization Libraries: Plotly, Leaflet, matplotlib, seaborn
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Tools: Tableau
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Data Processing: Pandas, NumPy
For a detailed overview of the project, findings, and methodology, please refer to the Final Report provided in the repository.
Contributions to this project are welcome. If you encounter any issues or have suggestions for improvement, please open an issue or submit a pull request.