A Visual History of Nobel Prize Winners ??
Nobel is a well-known prize worldwide, and I wanted to dig into the history of the prize to figure out whether the recipients were fairly selected or not.
I have done this project through DataCamp which has taught us a history of Nobel prize winners in a visual way. First, I’ll give an overview of the project, then I’ll share the notebook I used in this project.
The aim of the project is to find out whether the prize is biased or unbiased in terms of gender and nationality.
The data was acquired from the Nobel Foundation which includes a record of each individual or organization that was awarded between 1901 and 2016.
I used pandas, seaborn, and NumPy libraries to read and visualize the dataset.
Overall, the dataset includes the year, category, prize, full name of the winner, birth city, sex, and many other attributes. The first 4 rows of the dataset as a table are below.
I was curious about the number of prizes won by male and female recipients. The result below shows there are 836 males and 49 females who won the prizes and there is a significant difference between the two genders.
What about nationalities? Let’s take a look.
The outcome displays the top 10 countries, which have had the highest number of winners.
The USA, which ranked first, has had three times as many winners as the UK, which placed second in the table. There is a large gap between the USA and other countries. Also, the outcome shows most of the winners were from European countries.
Even though most of the winners were American overall, all of the winners in 1901 were European (see the first table).
Let’s find out when the USA started to dominate the Nobel prize charts.
The table above displays the percentages of American winners per decade since 1901. Between 2000 and 2010, the percentage was 0.42 which is the highest of all time.
Plotting the data is a better idea to understand the pattern. Let's plot the data for American winners!
Overall, the percentage increased over time; however, there were some points where the percentage fell in the plotline.
Since the 1930s, the number of American recipients increased and began to dominate the number of winners in other nations.
So what about the gender of a Nobel Prize winner?
As we saw in the table before, the total number of female winners were fewer than the number of male winners. How significant is this imbalance and is it better or worse within specific prize categories?
Let’s create a plotline for a better understanding!
In general, the pattern goes up but there were no female winners in some categories: 1950-1960 in Peace and 2000-2010 in Physics.
The line graph is a bit messy as the lines are overlapping. In this imbalance, let’s pick out the first woman to win a Nobel Prize!
Marie Curie was the first woman to receive a Nobel Prize in 1903 in the Physics category.
Who were the lucky laureates who won more than one Nobel Prize?
13 people received more than one prize and the table shows some of them. Marie Curie, the first woman to receive a Nobel Prize, received 2 Nobel Prizes in 2 different categories: Physics and Chemistry.
In addition, organizations received the prize.
How old are the recipients generally when they receive the prize? Let’s calculate and plot them!
The plot shows people were around 55 when they received the prize; however, the average had gotten closer to 65. There is a large spread in the laureates’ ages: most of them are over 50 years old while some of them are very young.
Let’s look at the age trends within different prize categories.
Overall, the trend went up in all categories except Peace. Physics had the strongest trend over time: the average was just under 50, it had increased to almost 70. The recipients started to receive the Economics prize in 1970.
There are some exceptional data in the graphs. Let’s find out the youngest laureate who received the Nobel Prize!
Malala Yousafzai is the youngest winner of the Nobel Prize as of 2016. She received the Peace prize when she was 17 years old.
I hope you enjoyed learning about the Nobel Prize laureates!
Please find the notebook here and feel free to contact me if you need any further information.
Happy learning! ?????
Award-Winning Author & Journalist ?? Senior Communications Expert - Tech, Product, Policy, Change Management ?? UN Delegate - CEDAW ???? ?? Speaker
4 年This is excellent insight and a great representation of the power of data analysis! Tagging a friend in the data field that would be interested: Anne Mandich, PhD
IT Architect, Technical Manager, PMP, MScIE
4 年I love the CATEGORY / AGE regression lines... Very interesting insights. If you look close enough, there is always more to discover. (by the way, you should add MATHEMATICS category from FIELD Institute for the sake of completeness)