The Nobel Prize has been among the most prestigious international awards since 1901. Each year, awards are bestowed in chemistry, literature, physics, physiology or medicine, economics, and peace. In addition to the honor, prestige, and substantial prize money, the recipient also gets a gold medal with an image of Alfred Nobel (1833 - 1896), who established the prize.
The Nobel Foundation has made a dataset available of all prize winners from the outset of the awards from 1901 to 2023. The dataset used in this project is from the Nobel Prize API and is available in the nobel.csv file in the data folder.
In this project, you'll get a chance to explore and answer several questions related to this prizewinning data. And we encourage you then to explore further questions that you're interested in!
# Loading in required libraries
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
# Read data from csv file
nobel = pd.read_csv("data/nobel.csv")
# Add decade col to the data
nobel["decade"] = nobel['year'] // 10 * 10
# What is the most commonly awarded gender and birth country?
top_gender = nobel["sex"].value_counts().idxmax()
top_country = nobel["birth_country"].value_counts().idxmax()
print(f"The most commonly awarded gender is : {top_gender} and birth_country is : {top_country}\n")
# Which decade and Nobel Prize category combination had the highest proportion of female laureates?
female_laureates = nobel[nobel["sex"] == "Female"]
max_proportion = (female_laureates.groupby(["decade", "category"]).size() / nobel.groupby(["decade", "category"]).size()).idxmax()
max_female_dict = {
max_proportion[0] : max_proportion[1]
}
print(f"The highest proportion of female laureates in decade {max_proportion[0]} and category {max_proportion[1]}\n")
# Who was the first woman to receive a Nobel Prize, and in what category?
first_woman_receive_nobel = nobel[nobel["sex"] == "Female"].sort_values("year")
first_woman_name = first_woman_receive_nobel["full_name"].iloc[0]
first_woman_category = first_woman_receive_nobel["category"].iloc[0]
print(f"The first woman who recireceived a Nobel prize is : {first_woman_name} in category : {first_woman_category}\n")
# Which individuals or organizations have won more than one Nobel Prize throughout the years?
more_than_one = nobel["full_name"].value_counts()
repeat_list_name = more_than_one[more_than_one >= 2].index.unique()
repeat_list = list(repeat_list_name)
print(f"The idividuals who have more than one Nobel prize : {repeat_list}\n")
# Which decade had the highest ratio of US-born Nobel Prize winners to total winners in all categories?
sns.countplot(x = "decade" , data = nobel[nobel["birth_country"] == "United States of America"])
max_decade_usa = 2000