Hello Guys, I hope everyone is having a fabulous week.
I decided to take a break from the guided projects and attempt a project of my own. I wanted to measure if I could apply the concepts I have learned so far to a dataset I gathered on my own.
For a while I have had some questions on how Africa is developing, compared to the rest of the world. To answer this question, I collected data on several metrics (Human development index, Fertility rate, Employment rate, Civil liberty score, Life expectancy and Population density), then compared them across different continents and sub-continents.
There are certain limitations to my analysis, and I tried to point most of them out in the Limitations section. I also refrained from including a summary at the top of my notebook (just this time ). I wanted to save it for the last sections. I hope you find the work interesting.
As usual, any contributions and feedback would be well appreciated.
Bro what a project! This is like A Textbook example!
Everything is so well structured and explained. It’s not even like sections could be replaced in sequence. This is the data analysis that narrates and keeps you hooked on a story!
As a formality of being the nagger, do you suppose the continent(s)/countries with a population density higher than the 5000 mark might be interesting data points to further drill down and analyze? I mean the HDI score although shows a weak correlation but the score is pretty high for these regions!
EDIT: I somehow forgot to discuss this. I assumed the higher the civil liberty score the higher freedom citizens have which may result in higher HDI scores, however, this moderate correlation is kinda surprising! Also, the medical care and war-zone pointers are poignant!
Thank you for the kind words @Rucha . I really appreciate the feedback.
I also expected to find stronger correlation between civil liberty scores and HDI and was quite surprised by the moderate correlation. However, I understood much later that the wide range of the 11 factors that are used to estimate Civil liberty (freedom of cultural expression, religious institutions and expression; freedom of assembly and demonstration, of political organization and professional organization, and collective bargaining; independence of the media and the judiciary etc.) may not neccessarily have been captured and factored into the HDI index calculations (which majorly involves education standards, living standards and health standards alone). Perhaps, correlating Civil liberty with another metric such as Happiness Score might produce more interesting results
Your observation on population density is apt and definitely worth exploring further I will look into this for the thrill it might bring: Its always nice to play data detective.
Thanks again for taking the time to review my work
@israelogunmola I initially started this message by using my usual format, but I can’t because most of my sections would be empty. You have done an absolutely wonderful project. I learned a lot including the existence of the joypy library.
I absolutely loved your visualizations , including your last one HDI vs. Life Expectancy. I wanted to do something similar to that in another project, was not sure how to approach it.
If there is one thing I have to point out to help improve your project is function documentation. Seeing as you have seen my projects, I think you might have noticed it. You can check this on how to document functions.
Thank you for the feedback @jesmaxavier . I am happy you loved the Joypy Library
I really appreciate you pointing out the function documentation, I have used the comprehensive style in many of my previous projects, however, I wasn’t quite sure if they were necessary for the functions used in this one. The fact that you have pointed this out means I will definitely include it in a new commit on GitHub
Thanks again, your reviews are always apt and educative