https://github.com/parnika798/psychic-palm-tree

Streamlit dashboard exploring correlations between ad spending and voter turnout in the 2024 Indian General Elections. Includes dynamic filters, intuitive charts, and election campaign impact exploration.
https://github.com/parnika798/psychic-palm-tree

2024-indian-general-elections data-visualization election-data-analysis interactive-dashboard streamlit

Last synced: over 1 year ago
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Streamlit dashboard exploring correlations between ad spending and voter turnout in the 2024 Indian General Elections. Includes dynamic filters, intuitive charts, and election campaign impact exploration.

• Host: GitHub
• URL: https://github.com/parnika798/psychic-palm-tree
• Owner: Parnika798
• Created: 2024-11-08T03:48:11.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-17T05:51:52.000Z (over 1 year ago)
• Last Synced: 2025-01-21T05:28:32.574Z (over 1 year ago)
• Topics: 2024-indian-general-elections, data-visualization, election-data-analysis, interactive-dashboard, streamlit
• Language: Python
• Homepage: https://psychic-palm-tree-ezqdokxeargq5ne8ry2ria.streamlit.app/
• Size: 1.45 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
Election Data Analysis Dashboard

An interactive dashboard built using Streamlit to explore the 2024 Indian General Elections dataset. This project offers a visually engaging and analytical approach to understanding election trends, ad spending, and voter turnout.

🎯 Key Features

Dynamic Graphs: Explore election data through interactive, zoomable, and detailed visualizations.

Dropdown Metrics: Customize your data view by selecting from multiple election metrics.

Comprehensive Summaries: Access concise summaries of all graphs for quick, actionable insights.

Responsive Design: Enjoy a seamless and intuitive user experience.

📊 Dataset Description

The dataset captures key aspects of the 2024 Indian General Elections, divided into three main files:

Advertisers Data: Details on advertisers, their pages, ad spending (INR), and ad counts.

Locations Data: Information on locations and corresponding ad spending (INR).

Results Data: Election results with details on states, constituencies, total electors, voter turnout, votes, and election phases.

💻 Technologies Used

Python: For data preprocessing and analysis.

Streamlit: To develop the interactive dashboard.

Pandas & NumPy: For efficient data manipulation and calculations.

Matplotlib & Seaborn: To create compelling visualizations.