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In this repository, I've sourced a COVID-19 dataset, conducted exploratory data analysis (EDA), and created visualizations to gain a comprehensive understanding of the dataset's nuances.

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narayan123411/Explotary-Data-Analysis-On-Covid-19

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Four primary visualization types were developed to depict various facets of COVID-19 data.

  1. The total number of cases worldwide was displayed on an interactive tree map. This enables seeing case details by diving down from the continent to the country level.

  2. Animations of choropleth maps were created to show how cases spread over time. The expanding shaded areas successfully show how the cases have changed geographically.

  3. In order to examine potential connections between climatic variables and case growth, a scatter plot compared cases to weather.

  4. To understand the severity of the cases by age group, a stacked bar chart was used to display the percentage of deaths across various age groups.

  5. The percentage of particular coronavirus symptoms over time was plotted against the number of confirmed cases in the final graph. This indicates patterns in the prevalence of symptoms as cases increased.

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Figure 1: WHO coronavirus disease (COVID-19) dashboard

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Figure 2: Frquent Pattern visualizer

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Figure 3: Dashboard

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Figure 4: Covid19- Confirmed Cases Growth

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In this repository, I've sourced a COVID-19 dataset, conducted exploratory data analysis (EDA), and created visualizations to gain a comprehensive understanding of the dataset's nuances.

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