Welcome to the Canis Hack Data Visualizations repository! This project aims to showcase insightful visualizations created during the Canis Pro hackathon. The visualizations are built using Tableau to analyze and present data in a meaningful way.
The dataset used for these visualizations includes information about social media entities, their followers on various platforms, and other relevant details. The data is structured to provide a comprehensive view of each entity's online presence.
Here are the technologies and tools used in this project:
Provide a high-level overview of the entities and their follower counts across all platforms.
Use a bar chart to compare the total follower/subscriber counts for each entity.
Explore follower counts based on the region of focus.
Use a stacked bar chart to compare follower counts for each platform based on the region of focus.
Analyze follower counts based on the language of the content.
Use a grouped bar chart to compare follower counts for each platform based on the language.
Compare follower counts for entities owned by different organizations.
Use a bar chart to compare the follower counts for each platform based on the entity owner.
Analyze follower counts for each entity on individual social media platforms.
Use a line chart to show the growth or distribution of followers on each social media platform for each entity.
Explore entities with high engagement across multiple platforms.
Use a scatter plot to identify entities with high engagement across multiple platforms.
Provide detailed information for a specific entity.
Use a detailed table or card view for the selected entity.
- Clone the repository:
git clone https://github.com/AKILSADIK/Canis-Hack-Data-Visualization - Navigate to the project directory.
- Open Tableau.
- Load the provided dataset.
- Open each visualization workbook.
Thank you to the contributors who participated in the Canis Hack Data Visualizations project:
- Akil Sadik M H
- Hari Hrithik R A
- Cibi Jegan A
- [Yeshwanth N B]
Contribute to the project by forking the repository, creating a new branch, making changes, and creating a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.