After a couple of busy weeks, I was finally happy to complete my fourth project provided by DataCamp on the Data Scientist with Python Track. In the previous lessons, we have learned Python Data Science Toolbox (Part 2) and Intermediate Data Visualization with Seaborn. We explored how to use iterators, zip, enumerate, various list and dict comprehensions, and generators. We also went deeper into data visualization using Seaborn, such as regression and residual plots, heatmaps, catplots, lmplots, and various seaborn function parameters. In this project, we did not focus too much on the newly taught material but rather emphasized the basic but often overlooked concept of Data Manipulation algorithms.

The Nobel Prize is arguably the most recognizable scientific honor in the world. It is awarded annually to academics and researchers in the areas of chemistry, literature, physics, medicine, economics, and world peace. The first Nobel Prize was awarded in 1901, and although it was initially Eurocentric and Male-focused, it is now completely Biased-Free. Surely, you say?

Let's find out, then! What traits do the award recipients possess? Which nation receives it most frequently? Has anyone received it twice? You have to work this out on your own.

The Nobel Foundation's data collection is available on Kaggle and was used in this study.

1. The most Nobel of Prizes
2. So, who gets the Nobel Prize?
3. USA dominance
4. USA dominance, visualized
5. What is the gender of a typical Nobel Prize winner?
6. The first woman to win the Nobel Prize
7. Repeat laureates
8. How old are you when you get the prize?
9. Age differences between prize categories
10. Oldest and youngest winners
11. You get a prize!