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Stage C: Data storytelling with Python libraries

This project uses Python libraries like BeautifulSoup to scrape data from the web and seaborn for visualization. The datasets used for this project include: a record of COVID19 cases in Nigeria from the website of Nigeria Center for Diseases Control (NCDC); daily record of cases across different countries from a Github repository owned by John Hopkins University CSSE; files in csv format containing information on Nigeria’s Real GDP, budgets and vulnerability index. These datasets gave access to the following information:

  • Number of confirmed, recovered, and death cases across each state in Nigeria.
  • Updated record of cases in the whole of Nigeria, and in 278 other countries, dated from the first day of COVID19 insurgence till the day of collection (5th March, 2022).
  • Budget details for each state in Nigeria.
  • The real GDP for the country across all 4 quarters, over the period of 2014 to 2020.

Method of Analysis

  • Data collection
  • Date cleaning
  • Data visualization
  • Interpretation and drawing insights

The Who, What, and Why

This story is directed at Nigerian healthcare providers, policy makers, and families that are impacted by COVID-19, directly or indirectly. The selected datasets are from reliable sources with updated information on COVID 19 infection across different regions. Also, I've tried to identify the relationship between the real GDP and the distribution of the virus in Nigeria. This is important to determine how much coronavirus affects the economy, if certain measures should be taken to neutralize its effect considering the other factors that directly impacts the economy like the ongoing fuel scarcity, and the potential roles of each audience category in COVID 19 management. It also intends to shed some light on if COVID 19 is actually a worse economic threat than other existing factors.

Conclusion

Data storytelling is more about the WHY than the writing. I think there's still more to learn about sourcing for data because the datasets used for this project are not all up to date, particularly the real GDP numbers. It's not because I couldn't find data on GDP, but those on platforms like statista, nairametrics, and national bureau of statistics were not consistent. Feel free to reach out for comments, suggestions and whatnot. I'm still learning.

NB: The most recent data in this project is dated 5th of March, 2022.

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