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Project 2 in Columbia University. Created the baseline of the shiny app, defining the UI and the server along with the baseline for the visualizations Engineered a Shiny web application featuring heatmaps for visualizing disaster types and COVID -19 case distributions, enabling state specific and temporal data analysis.

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Project 2: Shiny App Development

Dominant Disaster Type by State and COVID-19 Cases

Term: Spring 2024

Screenshot 2024-02-21 at 9 25 51 AM
  • Team #3

  • Dominant Disaster Type by State and COVID-19 Cases:

    • Team members
      • Cho, Yerin
      • Chen, Tianyi
      • Li, Zhaoyang
      • Wang, Yinpei
  • Project summary:

  • Overview The purpose of this project is to visualize and analyze the dominant disaster types by state and COVID-19 cases using an interactive Shiny web application. The application consists of four visualization pages, each providing unique insights into disaster occurrences and COVID-19 cases across different states.

  • Visualization Pages

  1. Heatmap of Dominant Disaster Types This page displays a heatmap visualization showing the dominant disaster types by state. Users can select a specific incident type from the dropdown menu to explore the distribution of that particular disaster type across states.
  2. COVID-19 Cases Heatmap The COVID-19 Cases Heatmap page presents a geographical heatmap illustrating the distribution of COVID-19 cases across different states. Users have the option to select specific states and compare cases over weekends using a checkbox.
  3. Total COVID Cases by State This page showcases a comparative plot of total COVID-19 cases by state. Users can select multiple states from the dropdown menu to visualize and compare the total number of cases.
  4. COVID Cases Comparison Over Time The COVID Cases Comparison page provides insights into COVID-19 cases over time and across different states. Users can select multiple states and choose to compare cases over weekends using a checkbox. The visualization includes a line plot depicting the trend of COVID-19 cases over time for the selected states.
  • Contribution statement: (default) Yerin, Tianyi, Zhaoyang and Yinpei designed the study. Yinpei downloaded the required datasets and conducted data preprocessing in coordination with the project. Zhaoyang created the baseline of the shiny app, defining the UI and the server along with the baseline for the visualizations. Yerin created additional visualizations and worked with the overall display of the app, including the interactive sidebar panels. As the team leader, Yerin also managed the overall project timeline for each team member and held meetings. Tianyi refined the existing visualization and created additional visualization; he checked the proper operation of the project as well. Tianyi was also responsible for the presentation. All team members contributed to the GitHub repository. All team members approve our work presented in our GitHub repository, including this contribution statement.

Following suggestions by RICH FITZJOHN (@richfitz). This folder is orgarnized as follows.

proj/
├── app/
├── lib/
├── data/
├── doc/
└── output/

Please see each subfolder for a README file.

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Project 2 in Columbia University. Created the baseline of the shiny app, defining the UI and the server along with the baseline for the visualizations Engineered a Shiny web application featuring heatmaps for visualizing disaster types and COVID -19 case distributions, enabling state specific and temporal data analysis.

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