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Is your feature request related to a problem? Please describe.
The notebook "COVID19 Analysis.ipynb" in the "Timeline Analysis Covid-19" project lacks detailed geospatial visualization, hindering users' ability to understand regional trends and patterns effectively. Adding geospatial analysis with choropleth maps and interactive features can provide valuable insights into the geographic distribution of COVID-19 metrics.
Describe the solution you'd like.
I propose to enhance the notebook "COVID19 Analysis.ipynb" by incorporating detailed geospatial visualization techniques. Specifically, I suggest the following modifications:
Integrate a geospatial plotting library such as Plotly or Folium to create choropleth maps color-coded based on COVID-19 metrics such as confirmed cases, deaths, and testing rates.
Implement interactive features like tooltips to provide detailed information about specific regions when users hover over them.
Utilize a reliable geospatial dataset (e.g., GeoJSON) to accurately represent the boundaries of regions and countries.
Describe alternatives you've considered.
As alternatives, I have considered:
Manually creating static maps using visualization libraries like Matplotlib or Seaborn. However, this approach lacks interactivity and may not provide detailed information about specific regions.
Using pre-built geospatial visualization tools like Folium or Plotly. These tools offer extensive customization options and interactive features, making them well-suited for our requirements.
Add any other context or screenshots about the feature request here.
Adding geospatial analysis will significantly enhance the notebook "COVID19 Analysis.ipynb", allowing users to visualize regional trends and hotspots more effectively. The interactive nature of the maps will enable users to explore the data dynamically and gain deeper insights into the geographic distribution of COVID-19 metrics.
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
The notebook "COVID19 Analysis.ipynb" in the "Timeline Analysis Covid-19" project lacks detailed geospatial visualization, hindering users' ability to understand regional trends and patterns effectively. Adding geospatial analysis with choropleth maps and interactive features can provide valuable insights into the geographic distribution of COVID-19 metrics.
Describe the solution you'd like.
I propose to enhance the notebook "COVID19 Analysis.ipynb" by incorporating detailed geospatial visualization techniques. Specifically, I suggest the following modifications:
Describe alternatives you've considered.
As alternatives, I have considered:
Add any other context or screenshots about the feature request here.
Adding geospatial analysis will significantly enhance the notebook "COVID19 Analysis.ipynb", allowing users to visualize regional trends and hotspots more effectively. The interactive nature of the maps will enable users to explore the data dynamically and gain deeper insights into the geographic distribution of COVID-19 metrics.
The text was updated successfully, but these errors were encountered: