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CSV Dataset - COVID - Alexander Bell

✓ Published0🌍 Public
Aabell@wpi.edu
Last edited Sep 11, 2024
Created on Sep 2, 2024

This example displays the first entry of a COVID-19 dataset as a formatted JSON object in a large monospace font. The dataset, loaded from a CSV file, contains country-level statistics including confirmed cases, recoveries, critical cases, and deaths. The code parses the CSV, converts numeric fields to numbers, and uses template literals to render the JSON string within a `<pre>` element. It demonstrates a minimal approach to inspecting structured data without additional visualization libraries.

AI-generated description

The COVID 19 Dataset, loaded and parsed as CSV.

This dataset contains information about cases of COVID 19 across countries. This information includes confirmed cases, the amount of people who recovered, and the amount of COVID related deaths occured. It also includes the last update for each country as a date + time.

Tasks for this dataset:

  1. I want to see how geographical location affect total number of cases
  2. I want to see how affluence affects recovered cases (would require more data)
  3. I want to see which regions of the world had the most deaths/recoveries
  4. I want to see if there are any "inconsistencies" in data, which could be related to lying on public reports
  5. I want to see which countries had the "best method" of dealing with COVID, by comparing total population to confirmed cases and recoveries to deaths.
MIT Licensed

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