Setup and Context

Introduction

On November 27, 1895, Alfred Nobel signed his last will in Paris. When it was opened after his death, the will caused a lot of controversy, as Nobel had left much of his wealth for the establishment of a prize.

Alfred Nobel dictates that his entire remaining estate should be used to endow “prizes to those who, during the preceding year, have conferred the greatest benefit to humankind”.

Every year the Nobel Prize is given to scientists and scholars in the categories chemistry, literature, physics, physiology or medicine, economics, and peace.

Let's see what patterns we can find in the data of the past Nobel laureates. What can we learn about the Nobel prize and our world more generally?

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Import Statements

Notebook Presentation

Read the Data

	year	category	prize	motivation	prize_share	laureate_type	full_name	birth_date	birth_city	birth_country	birth_country_current	sex	organization_name	organization_city	organization_country	ISO
0	1901	Chemistry	The Nobel Prize in Chemistry 1901	"in recognition of the extraordinary services ...	1/1	Individual	Jacobus Henricus van 't Hoff	1852-08-30	Rotterdam	Netherlands	Netherlands	Male	Berlin University	Berlin	Germany	NLD
1	1901	Literature	The Nobel Prize in Literature 1901	"in special recognition of his poetic composit...	1/1	Individual	Sully Prudhomme	1839-03-16	Paris	France	France	Male	NaN	NaN	NaN	FRA

Caveats: The exact birth dates for Michael Houghton, Venkatraman Ramakrishnan, and Nadia Murad are unknown. I've substituted them with mid-year estimate of July 2nd.

Dataset Dimensions and Time Range

The dataset contains 962 records across 16 columns, spanning 1901 to 2023. Each row represents one prize share to one laureate or organisation.

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 962 entries, 0 to 961
Data columns (total 16 columns):
 #   Column                 Non-Null Count  Dtype 
---  ------                 --------------  ----- 
 0   year                   962 non-null    int64 
 1   category               962 non-null    object
 2   prize                  962 non-null    object
 3   motivation             874 non-null    object
 4   prize_share            962 non-null    object
 5   laureate_type          962 non-null    object
 6   full_name              962 non-null    object
 7   birth_date             934 non-null    object
 8   birth_city             931 non-null    object
 9   birth_country          934 non-null    object
 10  birth_country_current  934 non-null    object
 11  sex                    934 non-null    object
 12  organization_name      707 non-null    object
 13  organization_city      707 non-null    object
 14  organization_country   708 non-null    object
 15  ISO                    934 non-null    object
dtypes: int64(1), object(15)
memory usage: 120.4+ KB

Completeness Assessment

Organisation laureates (primarily Peace and Literature) account for most NaN values in birth_date and sex. Institution fields are empty where laureates worked independently or affiliation data is unavailable.

Check for Duplicates

np.False_

Check for NaN Values

np.True_

year                       0
category                   0
prize                      0
prize_share                0
laureate_type              0
full_name                  0
birth_date                28
birth_country             28
birth_country_current     28
sex                       28
ISO                       28
birth_city                31
motivation                88
organization_country     254
organization_name        255
organization_city        255
dtype: int64

	full_name	birth_date
24	Institut de droit international (Institute of International Law)	NaN
60	Bureau international permanent de la Paix (Permanent International Peace Bureau)	NaN
89	Comité international de la Croix Rouge (International Committee of the Red Cross)	NaN
200	Office international Nansen pour les Réfugiés (Nansen International Office for Refugees)	NaN
215	Comité international de la Croix Rouge (International Committee of the Red Cross)	NaN

	year	category	full_name	birth_city	birth_country	birth_country_current
725	2001	Literature	Sir Vidiadhar Surajprasad Naipaul	NaN	Trinidad	Trinidad
837	2010	Peace	Liu Xiaobo	NaN	China	China
957	2020	Medicine	Michael Houghton	NaN	United Kingdom	United Kingdom

	full_name	category	organization_country	organization_city	organization_name
627	Kary B. Mullis	Chemistry	United States of America	La Jolla, CA	NaN
705	Martinus J.G. Veltman	Physics	Netherlands	Bilthoven	NaN
721	William S. Knowles	Chemistry	United States of America	St. Louis, MO	NaN
777	J. Robin Warren	Medicine	Australia	Perth	NaN
831	Richard F. Heck	Chemistry	United States of America	NaN	University of Delaware

Type Conversions and Feature Engineering

Parsing birth_date to datetime enables age calculations. The prize_share fraction (e.g. 1/2) is converted to a decimal percentage to support yearly share trend analysis.

Convert Year and Birth Date to Datetime

The birth_date entries are datatype:
---datetime64[ns]---

Add a Column with the Prize Share as a Percentage

	year	category	prize	motivation	prize_share	laureate_type	full_name	birth_date	birth_city	birth_country	birth_country_current	sex	organization_name	organization_city	organization_country	ISO
0	1901	Chemistry	The Nobel Prize in Chemistry 1901	"in recognition of the extraordinary services ...	1/1	Individual	Jacobus Henricus van 't Hoff	1852-08-30	Rotterdam	Netherlands	Netherlands	Male	Berlin University	Berlin	Germany	NLD
1	1901	Literature	The Nobel Prize in Literature 1901	"in special recognition of his poetic composit...	1/1	Individual	Sully Prudhomme	1839-03-16	Paris	France	France	Male	NaN	NaN	NaN	FRA

	year	category	prize	motivation	prize_share	laureate_type	full_name	birth_date	birth_city	birth_country	birth_country_current	sex	organization_name	organization_city	organization_country	ISO	share_pct
0	1901	Chemistry	The Nobel Prize in Chemistry 1901	"in recognition of the extraordinary services ...	1/1	Individual	Jacobus Henricus van 't Hoff	1852-08-30	Rotterdam	Netherlands	Netherlands	Male	Berlin University	Berlin	Germany	NLD	100.00

Plotly Donut Chart: Percentage of Male vs. Female Laureates

Of the 934 individually tracked prizes, 58 went to women — approximately 6.2%. The donut chart below makes the scale of that disparity immediately visible.

sex
Male      876
Female     58
Name: count, dtype: int64

The First Three Female Nobel Laureates

Marie Curie (Physics, 1903), Bertha von Suttner (Peace, 1905), and Selma Lagerlöf (Literature, 1909) were the first three women to win. All three were born in countries whose names and borders have since changed.

	year	category	full_name	birth_city	birth_country
18	1903	Physics	Marie Curie, née Sklodowska	Warsaw	Russian Empire (Poland)
29	1905	Peace	Baroness Bertha Sophie Felicita von Suttner, n...	Prague	Austrian Empire (Czech Republic)
51	1909	Literature	Selma Ottilia Lovisa Lagerlöf	Mårbacka	Sweden

Six winners have received the Nobel Prize more than once — including Marie Curie (Physics 1903, Chemistry 1911) and Linus Pauling (Chemistry 1954, Peace 1962).

There are 6 winners who were awarded the prize more than once.

	year	category	laureate_type	full_name
18	1903	Physics	Individual	Marie Curie, née Sklodowska
62	1911	Chemistry	Individual	Marie Curie, née Sklodowska
89	1917	Peace	Organization	Comité international de la Croix Rouge (Intern...
215	1944	Peace	Organization	Comité international de la Croix Rouge (Intern...
278	1954	Chemistry	Individual	Linus Carl Pauling
283	1954	Peace	Organization	Office of the United Nations High Commissioner...
297	1956	Physics	Individual	John Bardeen
306	1958	Chemistry	Individual	Frederick Sanger
340	1962	Peace	Individual	Linus Carl Pauling
348	1963	Peace	Organization	Comité international de la Croix Rouge (Intern...
424	1972	Physics	Individual	John Bardeen
505	1980	Chemistry	Individual	Frederick Sanger
523	1981	Peace	Organization	Office of the United Nations High Commissioner...

Comité international de la Croix Rouge (International Committee of the Red Cross) --— Peace (1917), Peace (1944), Peace (1963)
Frederick Sanger --— Chemistry (1958), Chemistry (1980)
John Bardeen --— Physics (1956), Physics (1972)
Linus Carl Pauling --— Chemistry (1954), Peace (1962)
Marie Curie, née Sklodowska --— Physics (1903), Chemistry (1911)
Office of the United Nations High Commissioner for Refugees (UNHCR) --— Peace (1954), Peace (1981)

Prizes are awarded across six categories. Medicine leads with 222 prizes; Economics, introduced in 1969, has the fewest at 86.

6

category
Medicine      222
Physics       216
Chemistry     186
Peace         135
Literature    117
Economics      86
Name: count, dtype: int64

The Economics Prize — Awarded from 1969

Unlike the original five categories dating to 1901, the Economics prize was first awarded in 1969 to Jan Tinbergen and Ragnar Frisch.

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 962 entries, 0 to 961
Data columns (total 17 columns):
 #   Column                 Non-Null Count  Dtype         
---  ------                 --------------  -----         
 0   year                   962 non-null    int64         
 1   category               962 non-null    object        
 2   prize                  962 non-null    object        
 3   motivation             874 non-null    object        
 4   prize_share            962 non-null    object        
 5   laureate_type          962 non-null    object        
 6   full_name              962 non-null    object        
 7   birth_date             934 non-null    datetime64[ns]
 8   birth_city             931 non-null    object        
 9   birth_country          934 non-null    object        
 10  birth_country_current  934 non-null    object        
 11  sex                    934 non-null    object        
 12  organization_name      707 non-null    object        
 13  organization_city      707 non-null    object        
 14  organization_country   708 non-null    object        
 15  ISO                    934 non-null    object        
 16  share_pct              962 non-null    float64       
dtypes: datetime64[ns](1), float64(1), int64(1), object(14)
memory usage: 127.9+ KB

	category	year	full_name
393	Economics	1969	Jan Tinbergen
394	Economics	1969	Ragnar Frisch
402	Economics	1970	Paul A. Samuelson

Peace and Literature show the highest proportion of female laureates. Physics has the lowest: only 4 women among 216 prizes.

	category	sex	prize
11	Physics	Male	212
7	Medicine	Male	210
1	Chemistry	Male	179
5	Literature	Male	101
9	Peace	Male	90
3	Economics	Male	84
8	Peace	Female	17
4	Literature	Female	16
6	Medicine	Female	12
0	Chemistry	Female	7
10	Physics	Female	4
2	Economics	Female	2

Prize counts dipped during both World Wars. The rolling average reveals a steady increase from the 1950s onward, partly because more prizes are now shared among multiple recipients.

The secondary axis (inverted) plots the 5-year rolling average of prize share percentage. As annual prize counts rise, the average share per laureate falls — prizes are being split more widely.

The Countries with the Most Nobel Prizes

Birth country at current borders is used rather than country at time of birth, reducing distortion from historical boundary changes. The United States leads with 281 prizes — more than twice the UK's 105.

	birth_country_current	prize
7	Belgium	9
31	Hungary	9
33	India	9
2	Australia	10
20	Denmark	12
54	Norway	12
13	China	12
51	Netherlands	18
3	Austria	18
39	Italy	19
68	Switzerland	19
11	Canada	20
61	Russia	26
40	Japan	27
57	Poland	27
67	Sweden	29
25	France	57
26	Germany	84
73	United Kingdom	105
74	United States of America	281

Use a Choropleth Map to Show the Number of Prizes Won by Country

• Create this choropleth map using the plotly documentation:

• Experiment with plotly's available colours. I quite like the sequential colour matter on this map.

Hint: You'll need to use a 3 letter country code for each country.

	birth_country_current	ISO	prize
74	United States of America	USA	281
73	United Kingdom	GBR	105
26	Germany	DEU	84
25	France	FRA	57
67	Sweden	SWE	29

Breaking down country totals by category reveals distinct national specialisms. Germany and Japan lag the US most sharply in Economics. France leads Germany in Literature and Peace.

	birth_country_current	category	prize
204	United States of America	Medicine	78
206	United States of America	Physics	70
201	United States of America	Chemistry	55
202	United States of America	Economics	49
198	United Kingdom	Medicine	28
195	United Kingdom	Chemistry	27
76	Germany	Physics	26
71	Germany	Chemistry	26
200	United Kingdom	Physics	24
205	United States of America	Peace	19

	birth_country_current	category	cat_prize	total_prize
109	India	Physics	1	9
77	Hungary	Medicine	2	9
71	Hungary	Physics	2	9
68	India	Medicine	2	9
67	India	Literature	2	9

Number of Prizes Won by Each Country Over Time

• When did the United States eclipse every other country in terms of the number of prizes won?
• Which country or countries were leading previously?
• Calculate the cumulative number of prizes won by each country in every year. Again, use the birth_country_current of the winner to calculate this.
• Create a plotly line chart where each country is a coloured line.

The top institutions are heavily US-dominated. Harvard University and the University of Chicago are the two leading affiliated organisations by laureate count.

New York stands out as the top research hub among all cities where prize-winning research took place.

New York is the most common birth city in the dataset. Among the top five cities, three are in the United States.

The sunburst chart reveals that US research clusters are especially concentrated in specific cities — particularly Boston and New York. Germany's and France's contributions are more spread across institutions.

The laureate's age in the year of the ceremony is computed from birth_date and year and stored as winning_age.

Index(['year', 'category', 'prize', 'motivation', 'prize_share',
       'laureate_type', 'full_name', 'birth_date', 'birth_city',
       'birth_country', 'birth_country_current', 'sex', 'organization_name',
       'organization_city', 'organization_country', 'ISO', 'share_pct',
       'winning_age'],
      dtype='object')

	year	category	full_name	winning_age
0	1901	Chemistry	Jacobus Henricus van 't Hoff	49.00
1	1901	Literature	Sully Prudhomme	62.00
2	1901	Medicine	Emil Adolf von Behring	47.00
3	1901	Peace	Frédéric Passy	79.00
4	1901	Peace	Jean Henry Dunant	73.00

Malala Yousafzai is the youngest winner at 17 (Peace, 2014); John Goodenough the oldest at 97 (Chemistry, 2019). The average is approximately 60, with 75% of laureates under 69.

	year	category	full_name	winning_age
937	2019	Chemistry	John Goodenough	97.00

	year	category	full_name	winning_age
885	2014	Peace	Malala Yousafzai	17.00

Descriptive Statistics for the Laureate Age at Time of Award

• Calculate the descriptive statistics for the age at the time of the award.
• Then visualise the distribution in the form of a histogram using Seaborn's .histplot() function.
• Experiment with the bin size. Try 10, 20, 30, and 50.

count   934.00
mean     59.95
std      12.62
min      17.00
25%      51.00
50%      60.00
75%      69.00
max      97.00
Name: winning_age, dtype: float64

Age Trend Over Time

The LOWESS trend line shows winning ages around 55–57 in the early 20th century trending toward 65–70 today — consistent with prizes recognising work done decades before the award.

Winning Age Across the Nobel Prize Categories

How does the age of laureates vary by category?

• Use Seaborn's .boxplot() to show how the mean, quartiles, max, and minimum values vary across categories. Which category has the longest "whiskers"?
• In which prize category are the average winners the oldest?
• In which prize category are the average winners the youngest?

Age Trends by Category

Separate panels per category reveal diverging trends. Some categories show ages rising sharply; Peace has the widest spread. The combined chart with hue makes cross-category comparison direct.

Key Findings

• US dominance: 281 prizes (29% of all individual prizes) — more than 2× the UK's 105 and more than 3× Germany's 84.
• Gender gap: 58 of 934 individually tracked prizes went to women (6.2%). Physics has the fewest female laureates: 4 out of 216.
• Repeat winners: 6 winners received the prize more than once. Marie Curie is the only person to have won in two different scientific categories (Physics 1903, Chemistry 1911).
• Prize sharing: The average prize share per laureate has declined over time as prizes are increasingly split among multiple recipients.
• Laureate age: Mean winning age is ~60 years. The youngest winner was Malala Yousafzai at 17 (Peace, 2014); the oldest was John Goodenough at 97 (Chemistry, 2019).
• Age trend: The LOWESS regression shows winning ages have risen by roughly 8–10 years over the full 120-year span, consistent with prizes recognising earlier work.
• Economics: Newest category, first awarded 1969. Has the fewest prizes (86) and the highest proportion of US winners.
• World Wars: Both conflicts produced visible dips in the annual prize count, clearest in the 5-year rolling average.
• Research geography: The United States, United Kingdom, and Germany together account for the majority of affiliated institution records. Harvard and University of Chicago lead by laureate count.