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Interactive COVID 19 Data Visualization Project using Cyber GIS Tool
Interactive COVID 19 Data Visualization Project using Cyber GIS Tool
PROBLEM DESCRIPTION:
Explored the impact of COVID-19 with our interactive data visualization project. Using the Adaptive Choropleth Mapper (ACM) library, we've created an engaging dashboard that allows you to visualize and analyze COVID-19 trends across various regions.
Our project offers insights into COVID-19 confirmed cases, vaccination rates, and more, all at your fingertips. Dive into the data with user-friendly maps, charts, and graphs that make it easy to compare and understand how the pandemic has evolved over time.
With this dashboard, you can gain valuable insights into the COVID-19 situation, making it a valuable tool for policymakers, researchers, and the public alike. Explore the dynamic patterns and trends, empowering yourself to make informed decisions and contribute to effective pandemic management.
Technologies Used: Python, Pandas, GeoPandas, Matplotlib, HTML and JavaScript
APPROACH
Key Skills Utilized:
Demonstrated proficiency in data validation techniques.
Applied data preprocessing expertise.
Leveraged spatial analysis capabilities.
Utilized labeling and data mapping skills.
Showcased file organization and dashboard development proficiency.
CHALLENGES
Data Integration: Combining data from different sources (CSV and shapefile) while ensuring data consistency can be challenging.
Data Quality: Handling missing or inconsistent data in the input datasets requires robust data cleaning and preprocessing.
Parameter Management: Managing various parameters and ensuring they are used correctly for dashboard generation.
Labeling: Mapping variables to user-friendly labels for a more intuitive dashboard experience.
References:
https://github.com/cybergis/CyberGIS-Vis
https://cybergis.illinois.edu/
https://plotly.com/javascript/
https://github.com/spatialucr/geosnap-viz
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