Guided Project: Analysing CIA Factbook Data with SQL

Hello, wonderful community! It’s been a while since I shared a guided project here. I have wanted to explore SQL in jupyter notebook for some time now, and I am excited that Dataquest addressed this area in the DataScience path.

I set a goal to use SQL alone for this analysis which meant that I could not use python visualization libraries. As an alternative, I decided to explore external sources to explain some of my insights and obtained supporting visualizations online. This added an extra layer of challenge and made the project time-consuming, but it was worth it!

Project notebook:
notebook.ipynb (96.2 KB)

Link to last mission screen: Learn data science with Python and R projects

Link to project on Github

I have included the complete list of all external sources used in the reference section. Your feedback and suggestions would be appreciated.

Thank you :raised_hands:
Click here to view the jupyter notebook file in a new tab

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Hi @israelogunmola! Thanks for sharing this amazing project with the Community :slight_smile: I liked that you put together a lot of background information; that’s indeed an important skill for a data analyst.

I have just a few comments:

  • When you compute the average world population, bear in mind that you also include the entities like European Union so it shifts the real average number a lot. You removed World and Antarctica, which is good but do not forget about the other entities. This is what you do in the next step, but also compute the correct average population
  • In 2021, the crude death rate for the world was 7.64 deaths per thousand population, and the crude birth rate for the world is 17.76 births per thousand. — that’s surprising, considering that COVID-19 was still roaming… Have you checked the data for 2020?

That’s it for me. All the rest seems OK. I haven’t thoroughly checked your code and trust that it is correct. Happy coding!

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