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Data Visualization Using Plotly

In this we will covers two task:

  • Creating an animated Chloropeth  plot using plotly that analyzes a seven-day moving average of cases for some geographic unit and sub-unit (e.g. USA and states)

  • Creating an animated scatter plot of Covid-19  using Plotly that analyzes COVID cases and deaths for some geographic unit and sub-unit (e.g. USA and states). 


Any data source relevant or related to requirements is accepted (e.g international covid cases). (csv or json files are accepted) suggested data source links:



Output:




Task 1:


Objectives:

  • Create an animated choropleth plot using plotly that analyzes a seven-day moving average of cases for some geographic unit and sub-unit (e.g. USA and states)

  • Create a second, non-animated, choropleth plot that shows cumulative cases per 100,000 people for the most recent date in the data file.

Requirements:

  • Find appropriate data source that includes new COVID-19 cases per day for the geographic region. (Direct link not downloaded file.)

  • Find a data source that estimates the population for the geographic region. (Direct link not downloaded file)

  • Load both to a pandas dataframe

  • Calculate cumulative cases per 100,000 population for the sub-region (i.e., state)

  • Calculate 7-day moving average if new cases

  • Plot 7-day moving average of cases on Plotly plot and animate by day (older dates on left of slider)

  • Create a separate plot of cumulative cases per 100,000 population. This should be for the maximum date in the dataframe and should not be animated.

  • Plots will include relevant title and hover text.

  • Colors will be continous scale of your choice.


Task 2:


Objectives:

  • Create an animated scatter plot using plotly that analyzes COVID cases and deaths for some geographic unit and sub-unit (e.g. USA and states)

Requirements:

  • Find appropriate data source that includes new COVID-19 cases per day for the geographic region. (Direct link not downloaded file.)

  • Load to a pandas dataframe

  • Perform any necessary transformations to conduct analysis and plotting.

  • Plot cumulative cases as size of bubble (older dates on left of slider).

  • Color of bubble should be continous scale and represent the cumulative number of deaths for that geographic region.

  • Plots will include relevant title and hover text.

  • Colors will be continous scale of your choice.



Looking Any Data Visualization Help related to Python Machine Learning, R Programming, D3.js, then you can contact us at contact@codersarts.com


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