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Ursinus College Digital Commons @ Ursinus College

Statistics and Probability Transforming Instruction in Undergraduate Mathematics via Primary Historical Sources

(TRIUMPHS)

Fall 2018

Seeing and Understanding Data Beverly Wood WW/Mathematics, Physical and Life Sciences, woodb14@erau.edu

Charlotte Bolch cbolch@ufl.edu

Follow this and additional works at: https://digitalcommons.ursinus.edu/triumphs_statistics

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Recommended Citation Wood, Beverly and Bolch, Charlotte, "Seeing and Understanding Data" (2018). Statistics and Probability. 2. https://digitalcommons.ursinus.edu/triumphs_statistics/2

Seeing and Understanding Data

Beverly Wood∗ and Charlotte Bolch†

August 21, 2019

1 Introduction

Visual displays of data are commonly used today in media reports online or in print. For example,

data visualizations are sometimes used as a marketing tool to convince people to purchase a certain

product, or they are displayed in articles or magazines as a way to graphically display data to

emphasize a certain point. In general, it is hard to imagine the majority of disciplines in science and

mathematics not using data visualizations. However, before standard data visualization techniques

were developed (and accepted by the community), mathematicians and scientists very rarely used

graphical displays or pictures to represent empirical data.

This project has four main parts. The first section introduces some of the earliest data visual-

izations, which were novel constructions in their time. Next, we consider works of Michael Florent

van Langren (1598–1675) and William Playfair (1759–1823) that contain the first known uses of

statistical representations of data, some of which are still used today. The third section focuses on

the work of Florence Nightingale (1820–1910) and Charles Joseph Minard (1781–1870) and their

ability to construct data displays that made an argument or told a story. Finally, in the last section

we consider works of Edward Tufte (1942– ) and Hans Rosling (1948–2017) that had a major impact

on the current field of data visualizations and how to best create them using computer software.

2 “Ancient” Visualization

One of the earliest data visualizations in printed form is a times-series graph (Figure 1) from the

late 10th or early 11th century that shows changes in the orbital positions of seven “planets”1 over

time and space. It appears in an appendix to a commentary on a work of Cicero (106–43 BCE) that

reviews the physics and astronomy of the day. Take a few minutes to look at the graph below, then

discuss with a partner the following questions.

∗Department of Mathematics, Physical & Life Sciences, Embry-Riddle Aeronautical University, Worldwide; Beverly.Wood@erau.edu. †School of Teaching and Learning, University of Florida, Gainesville, FL, 32601; cbolch@ufl.edu. 1At the time this graph was drawn, the term planets was used to describe heavenly bodies that seemed to “wander”

(moving relative to the background of stars) and could be seen with unaided eyes. Therefore, the sun and moon would be called planets.

1

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Figure 1. Time-series graph from the 10th or possibly 11th century [Unknown, 1010]

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Task 1 (a) As you can see, the image has no labels on the x- or y-axis. What do you think the x-axis

and y-axis represent?

(b) This graph is novel because a coordinate system was used to plot the various changes in

orbits for the seven planets over time. Why do you think that a coordinate system was

needed for this graph?

2

Now read the following discussion of this graph, written by a twentieth-century mathematician

and historian.

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The graph apparently was meant to represent a plot of the inclinations of the planetary orbits2

as a function of the time. For this purpose the zone of the zodiac was represented on a plane

with a horizontal line divided into thirty parts as the time or longitudinal axis. The vertical

axis designates the width of the zodiac. The horizontal scale appears to have been chosen for

each planet individually for the periods cannot be reconciled. The accompanying text refers

only to the amplitudes. The curves are apparently not related in time. [Funkhouser, 1936]

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Task 2 After reading Funkhouser’s discussion of the graph in Figure 1, does your interpretation of the

x- and y-axis change or stay the same? If you changed your interpretation, in what way?

3 Communicating Data Visually

In the mid-15th century, the invention of the moveable-type3 printing press by Johannes Gutenberg

had a large impact on the Renaissance, in that information was able to be spread throughout Eu-

ropean civilization quickly and accurately compared to news previously carried by word of mouth

or handwritten letters and manuscripts. With the moveable-type printing system, components of a

document that was composed of text were much more easily reproduced. However, the printing of

graphical displays rather than summary tables or lists of numbers was much more difficult because

the graphics did not have common components like the moveable type. Instead, a new graphical

display had to be created for each printing which was very expensive, limiting their use for several

more centuries.

2The inclination of a planetary orbit is the angle between the horizon and the astronomical body being observed. The website https://stellarium.org/ can be used as a virtual planetarium that you can use to find “star inclinations from anywhere on Earth.

3This is a system of printing documents on paper using moveable components that are individual characters, numbers, and punctuation marks. Earlier versions of the moveable-type printing press made from wood, clay, porcelain, or bronze materials were known in China and Korea. Gutenbergs durable alloy and mold technique made his press commercially viable.

3

3.1 Distance Graph by van Langren

In 1644, Michael Florent van Langren (1598–1675) created a graph showing determinations of the

distance (measured in degrees of longitude) from Toledo, Spain to Rome, Italy defined by various

people at different times. Statisticians and historians credit this graph as one of the first visual

representations of statistical data. Van Langren served as an astronomer to the royal house of Spain.

Although astronomers at that time were able to determine latitude from star inclinations, longitude

was much harder to determine precisely. Finding an accurate method for determining longitude was

of political and economical value to Spain and other European nations interested in navigation at

sea. Van Langren prepared his graph as part of a request to the Spanish court for financial support

of his own efforts to solve the longitude problem.

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Figure 2. Graph of the distance from Toledo, Spain to Rome, Italy by Michael Florent van

Langren [van Langren, 1643]

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Task 3 Take a few minutes to study the graph in Figure 2. What do you gather about the determination

of distance in longitude from Toledo to Rome based on the spread of data points? What do

you notice about the data points and their relation to each other?

Task 4 As a class, choose two cities near your college or university that you would like to estimate the

miles between. Then, have everyone in the class write their estimate between the two cities on

a piece of paper (rounding to the nearest tenth of a mile) along with their name. Have one or

two students write all the estimates on the board as students call out their guesses.

(a) In groups of three to four students, create a graph similar to van Langrens using the class

estimates for the distance from the chosen city A to chosen city B.

(b) Then combine pairs of the groups (total of six to eight students) and discuss each groups

graph. What are the similarities between the two graphs? Are there any differences?

What does the spread of data points look like on each graph?

4

3.2 Common Statistical Graphs by Playfair

Historians of statistics consider William Playfair4 (1759–1823) to have been the first developer of

many common statistical graphics used today, including the pie chart, the bar graph, and the statis-

tical line graph. Through these inventions he was able to create a universal common language that

was used from science to commerce as a way to understand and look at data. The bar graph below is

from his 1786 book entitled Commercial and Political Atlas. Playfair’s intention in this book was to

represent data about the import/export of many countries that were prominent in foreign commerce

at the time. The atlas did not have much success in England, but was very well received in France.

Playfair reported in regard to King Louis XVI of France that “As his majesty made Geography a

study, he at once understood the charts and was highly pleased. He said they spoke all languages

and were very clear and easily understood (as quoted in [Spence and Wainer, 2001, p. 110]). The

graph below is for the country of Scotland for one year.

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Figure 3. Playfair Bar Graph [Playfair, 1786]

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4William had two brothers with their own professional success putting their names down in history. John Playfair (1748-1819) was a noted mathematician of the Scottish Enlightenment and an original Fellow of the Royal Society of Edinburgh. James (1755-1794) was the architect for Melville Castle outside Edinburgh.

5

Task 5 Compare and contrast this bar graph with the bar graphs we use today in the newspaper and

other media. What do you see that is different between the bar graph in Figure 3 compared

to a bar graph today? Does how we interpret the bar graph in Figure 3 differ from how we

interpret bar graphs made today?

The following graph is a pie chart that was also created by William Playfair. Playfair included

this graph in his 1805 translation of D. F. Donnants 1802 French text, titled Statistical Account of

the United States of America.

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Figure 4. Playfair Pie Chart [Playfair, 1805]

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6

Task 6 Given that this pie chart was created in 1805, what do you think each slice of the pie chart

represents?

Task 7 A map of the United States in 1804 is shown below. Why do the proportions represented by

the slices of the pie chart in Figure 4 look different than how we would expect those of a pie

chart of the present day United States to look?

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Figure 5. Map of the United States in 1804 [Golbez, 2006]

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7

The following circle graph was created by William Playfair and was published in his book ti-

tled Statistical Breviary: Shewing, on a Principle Entirely New, the Resources of Every State and

Kingdom in Europe that was published in 1801.

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Figure 6. Playfair Circle Graph [Playfair, 1801]

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Task 8 (a) Figure 6 is a complicated graph. Take about five minutes to study the graph taking note

that the axis on the left side is on a different scale compared to the axis on the right side

of the graph.

(i) What does each circle represent?

(ii) Does the radius of each circle mean something?

(iii) What does the axis on the left-side represent?

(iv) What does the axis on the right-side represent?

(v) What do each of the lines on the left and right of each circle represent?

(vi) Why is there a line connecting the left and right line for each circle?

(b) Have you seen any recent data displayed in this fashion? If so, do you recall the subject

matter? If not, why do you think we dont use this type of graph anymore?

8

4 Making an Argument by Telling a Data Story

Playfairs work brought data to a much wider audience than just mathematicians used to working

with large collections of numbers or summary tables. It was all about describing social and economic

conditions without overwhelming the reader with lists of numbers. His ideas were overlooked by his

contemporaries, but they would be revisited in the 19th century with greater success.

4.1 Graphs by Florence Nightingale

The well-to-do parents of Florence Nightingale (1820–1910) knew there was something “wrong with

their youngest daughter, who preferred studying mathematics to dancing and had no interest in

accepting the several offers of marriage made to her. Victorian high society would condone no other

occupation for a young lady than keeping a husbands house (through the labor of servants) and

raising his children. Nightingale, however, longed to care for the sick and related her unusual desire

for public service to a religious calling. Nineteenth-century British society considered nursing a

degrading occupation, often associated with drunkenness, squalor, and promiscuity. After years of

denials from her mother, Nightingale took an important step toward fulfilling her dream by going to

the Deaconess School at Kaiserwerth in Germany to train as a nurse in 1851. She spent a year as

the superintendent at the Institute for the Care of Sick Gentlewomen, probably the only place she

could ever have worked with the consent of her ever-proper mother.

The outbreak of war in the Crimea presented an opportunity for Nightingale to combine her

unconventional desire for occupation, medical training, and social connections in a patriotic cause.

When the first reports from the Battle of Alma included descriptions of the disastrous state of the

field hospitals, Nightingale wrote a letter to the Minister of War (a social acquaintance) volunteering

her services as a professional nurse, which actually crossed in the mail with his request to her to

lead a party of nurses to the Crimea. What she and her nurses found upon their arrival at Scutari

exceeded even the most shocking newspaper reports. In addition to directing the nurses in her

charge regarding the nutrition and hygiene for the thousands of wounded soldiers, she organized the

chaotic administrative records and collected data that would change the British and, subsequently,

the United States Army hospitals.5

The Minister of War once again wrote to Nightingale after her return to Britain, soliciting her

opinions on the state of the Army hospitals. Her response was more than 500 pages long and included

a striking illustration of the data she had gathered at the city of Scutari (Figure 7).

5This data collection became the basis for her report to the Minister of War which earned her an honorary fellowship in the American Statistical Association in 1874. She had already been the first woman elected as a fellow in the Royal Statistical Society in 1859.

9

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Figure 7. Florence Nightingale’s “coxcombs” [Nightingale, 1858]

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The text in the bottom left of the illustration serves as a legend. Within each wedge of this odd

pie chart (also called a polar area diagram or rose diagram), the area is computed in polar coordinates

using identical common angles of 30◦. The blue represents deaths by preventable diseases, the red

represents deaths resulting from wounds, and the black represents deaths by all other causes. The

left circle displays the deaths of soldiers in the first year of the war and the right one shows the

deaths in the second year.

Task 9 (a) Compare the wedges for the same months in the two years, paying particular attention

to the proportion of each color within the wedge. Consult a timeline of the major battles

and discuss how they align with the size of wedges in either year.

(b) What data did Nightingale need in order to calculate the areas to draw and to shade?

She did not have a computer to calculate or draw this illustration for her. Speculate on

the tools she needed in order to draw these illustrations.

(c) Have you seen any recent data displayed in this fashion? If so, do you recall the subject

matter? If not, can you speculate on a modern issue that could be displayed like this?

10

4.2 Graph by Charles Minard

Arguably one of the most elegant displays of data ever produced is Charles Joseph Minards (1781–

1870) Figurative map of the successive losses in men of the French Army in the Russian campaign

1812–13 shown below.

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Figure 8. Carte figurative des pertes successives en hommes de l’Armée Franaise dans la

campagne de Russie 1812–1813 by Charles Joseph Minard [Minard, 1869]

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Minard was a civil engineer by training and trade during the Napoleonic era in France (1799–

1815), and retired from government service in 1851 as the Inspector General of Bridges and Roads.

In his retirement, he created a collection of visualizations that culminated in this astounding piece

drawn in 1869 and still admired today. Here is a link to a larger version of the graph: https:

//upload.wikimedia.org/wikipedia/commons/e/e2/Minard_Update.png

Task 10 (a) Count and describe the variables that Minard included in this visualization.

(b) The combination of so many variables on a two-dimensional representation is part of this

displays long-lasting appeal. Compare your list of variables with those of classmates and

discuss why each variable was important to Minard in the telling of this data story of the

French Army.

You probably cannot read the tiny print of the legend at the top of the graph but it makes no

mention whatsoever of Napoleon! Minards interest was in the soldiers who suffered in this misguided

march. In the graph’s legend, he also gave credit for the sources of his data and stated that the scale

on the bands is one millimeter for every 10,000 men.

11

5 Beyond Paper and Ink

Nightingale and Minard provided examples of beautiful data displays with their laboriously con-

structed visualizations that told a story almost without words. As the utility of statistics expanded

through various sciences over the course of the 19th and early 20th centuries, refinement of Playfairs

simpler constructions led to the almost ubiquitous use of data displays that have become standard

in both public and scholarly publications: bar graph, pie chart, histogram, line chart, and scatter

plot.

5.1 Tufte’s Principles of Graphical Excellence

In the preface to the second edition of The Visual Display of Quantitative Information, Edward

Tufte (1942– ) describes the genesis of the first edition as part of a seminar series with John Tukey

(1915–2000) at Princeton University. Tukeys interest in “exploratory data analysis” focused on easy-

to-construct (by hand after minimal arithmetic) displays of data to complement statistical analysis.

Two such displays are still commonplace: the boxplot and the stem-and-leaf plot.

In the 2001 edition of The Visual Display of Quantitative Information, Tufte also repeats the

nine qualities of graphical excellence from the groundbreaking 1983 edition [Tufte, 2001, p. 13]:

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Excellence in statistical graphics consists of complex ideas communicated with clarity, preci-

sion, and efficiency. Graphical displays should

• show the data

• induce the viewer to think about the substance rather than about methodology, graphic design, the technology of graphic production, or something else

• avoid distorting what the data have to say

• present many numbers in a small space

• make large data sets coherent

• encourage the eye to compare different pieces of data

• reveal the data at several levels of detail, from a broad overview to the fine structure

• serve a reasonably clear purpose: description, exploration, tabulation, or decoration

• be closely integrated with the statistical and verbal descriptions of a data set.

Graphics reveal data. Indeed graphics can be more precise and revealing than conventional

statistical computations.

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Task 11 Review each of the seven figures shown in the previous sections, choosing two about which

to write a paragraph comparing the data display with Tuftes list of graphical excellence

qualities.

12

Another idea initiated by Tufte is “data-ink ratio.” Data-ink is the part of the graph that cannot

be erased without loss of data. For example, the Playfair Circle Graph in Figure 6 includes more

gridlines than necessary to communicate the data story, thereby using too much ink on non-data.

Task 12 Keeping in mind all nine of the hallmarks of graphical excellence, review the other data

displays in this project for ink that has been spent on non-data. Write a short description

of each to describe the data-ink vs. non-data ink expended in the graphic. Support an

opinion of the “best” graphic with reference to both graphical excellence and data-ink.

5.2 Data visualizations of the 21st century

Informative and compelling displays of data in the 21st century are far less likely to require actual ink;

instead, we might be concerned about data-pixels. The challenges of printing graphics on a press have

been largely overcome as print has lost its place as the primary medium for information exchange.

The demand for digital rather than physical pages has paralleled the technological advancements

that have made the visual experience on a monitor nearly equivalent to the printed page.

Numerous software packages that include the production of standard statistical displays offer

nearly universal opportunity for users to create visual displays of data. Anyone can make a graph;

the question of quality, however, remains.

In the early 2000s, a new level of sophistication arrived to include more than bivariate data and

even larger data sets. A pioneer (and engaging showman) in this area was Hans Rosling (1948–2017),

who brought innovation to the display of public health data intended for a general audience.

Task 13 (a) Watch Rosling’s 200 Countries, 200 Years, 4 Minutes at https://youtu.be/jbkSRLYSojo.

(b) Visit the Gapminder tool https://www.gapminder.org/tools/#$chart-type=bubbles

online to re-play Rosling’s visualization at your own speed. Explore the data for a single

country by selecting it in the rightmost column. Write a paragraph about the story of the

world when the dynamic data includes all countries and another paragraph about how

the one country you watched fits or deviates from that story.

6 Conclusion

From the days when mathematicians preferred long lists of numbers to standard graphs at the click

of a mouse (or tap of a screen), visualizations have transformed the way we communicate data. King

Louis XVIs response to Playfairs work still rings true in the 21st century: “they [speak] all languages

and [are] very clear and easily understood” (as quoted in [Spence and Wainer, 2001, p. 110]). One

need not be a mathematician, statistician, or king to see and understand the story that data has to

tell.

13

References

Michael Friendly. A Brief History of Data Visualization. In C. Chen, W. Härdle, and A. Unwin,

editors, Handbook of Computational Statistics: Data Visualization, volume III, chapter 1, pages

1–34. Springer-Verlag, Heidelberg, 2006. ISBN 978-3-540-32825-4. URL http://datavis.ca/

papers/hbook.pdf.

Michael Friendly, Pedro Valero-Mora, and Joaqúın Ibáñez Ulargui. The First (Known) Statistical

Graph: Michael Florent van Langren and the “Secret” of Longitude. The American Statistician,

64(2):174–184, 2010.

H. Gary Funkhouser. A Note on a Tenth Century Graph. Osiris, 1(1):260–262, 1936.

H. Gary Funkhouser. Historical development of the graphical representation of statistical data.

Osiris, 3(1):269–405, 1937.

Golbez. Map of States and Territories of the United States of America March 27, 1804 to October 1,

1804, 2006. URL https://upload.wikimedia.org/wikipedia/commons/9/90/United_States_

1804-03-1804-10.png. [Online; accessed November 14, 2018].

V. J. Katz. A History of Mathematics: An Introduction. Addison-Wesley, Boston, MA, 3rd edition,

2009.

Charles Joseph Minard. Des tableaux graphiques et des cartes figuratives. E. Thunot et Cie, Paris,

1869.

Florence Nightingale. Notes on matters affecting the health, efficiency, and hospital administration

of the British Army: founded chiefly on the experience of the late war. Harrison, London, 1858.

William Playfair. The Commercial and Political Atlas. T. Button, Little Queen Street, 1786.

William Playfair. The Statistical Breviary. T. Bensley, Bolt Court, Fleet Street, 1801.

William Playfair. Statistical Account of the United States of America. J. Whiting, Finsbury Place,

1805. English translation of C. F. Donnant, Elémens de statistique, Paris, Batilliot Jeune, Genets

Jeune, 1802.

I. Spence and H. Wainer. William Playfair. In C. C. Heyde, E. Seneta, P. Crépel, S. E. Fienberg,

and J. Gani, editors, Statisticians of the Centuries, pages 105–110. Springer, New York, NY, 2001.

M. Stone. Florence Nightingale. In C. C. Heyde, E. Seneta, P. Crépel, S. E. Fienberg, and J. Gani,

editors, Statisticians of the Centuries, pages 171–175. Springer, New York, NY, 2001.

Edward R. Tufte. The Visual Display of Quantitative Information. Graphics Press, Cheshire, CT,

2001.

Edward R. Tufte. Beautiful Evidence, volume 1. Graphics Press, Cheshire, CT, 2006.

Edward R. Tufte and David Robins. Visual Explanations. Graphics Press, Cheshire, CT, 1997.

Edward R. Tufte, Nora Hillman Goeler, and Richard Benson. Envisioning information, volume 126.

Graphics Press, Cheshire, CT, 1990.

John W. Tukey. Exploratory Data Analysis, volume 2. Reading, MA, 1977.

14

Unknown. De cursu per zodiacum, 1010. URL https://commons.wikimedia.org/wiki/File:

Clm_14436_ecliptic_diagram.png#/media/File:Clm_14436_ecliptic_diagram.png. [Online;

accessed November 2, 2018].

Michael Florent van Langren. Graph of statistical data, showing the wide range of estimates of the

distance in longitude between Toledo and Rome, 1643. URL https://en.wikipedia.org/wiki/

Michael_van_Langren#/media/File:Grados_de_la_Longitud.jpg. [Online; accessed November

2, 2018].

15

Table of Figures: Descriptions and Links

Figure 1 De cursu per zodiacum (Course of the Zodiac), c. 1000, Appendix to Macrobius’

Commentary on Cicero’s Somnium Scipionis. https://commons.wikimedia.org/wiki/File:Clm_

14436_ecliptic_diagram.png#/media/File:Clm_14436_ecliptic_diagram.png Labels top to bot-

tom: Venus, Mercury, Saturn, Sol, Mars, Jupiter, Luna

Figure 2 Grados de la Longitud (Degrees of Longitude), 1643, Michael Florent van Langren https:

//en.wikipedia.org/wiki/Michael_van_Langren#/media/File:Grados_de_la_Longitud.jpg

Labels left-to-right: Toledo (Spain), Ianfonius (17.7◦), Mercator (19.9◦), Schonerus (20.8◦), Lants-

bergius (21.1◦), Brahe (21.4◦), Regiomontanus (25.6◦), Orontius (26.0◦), Clavius (26.4◦), Ptolomeus

(27.8◦), Argelius (28.2◦), Maginus (29.8◦), and Origanus (30.2◦)

Figure 3 Exports and Imports of Scotland to and from different parts for one Year from Christmas

1780 to Christmas 1781, 1786, William Playfair

Labels across the top, left-to-right: 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 130, 150, 170, 190, 200,

240, 260, 280, 1300000 Labels down the right, top to bottom: Names of Places, Jersey etc., Iceland,

Poland, Isle of Man, Greenland, Prussia, Portugal, Holland, Sweden, Guernsey, Germany, Denmark

and Norway, Flanders, West Indies, America, Russia, Ireland Note across the bottom: The upright

divisions are ten thousand pounds each. The black lines are Exports, the ribbed lines Imports.

Figure 4 Statistical Representation of the United States of America, 1805, William Playfair waiting

for primary source link

Note across the bottom: This newly invented method is intended to show the proportions between the

divisions in a striking manner, Total estimate 1,979,000 square miles or 1274 millions of acres. Wedge

labels, clockwise beginning at 9 oclock position: Delaware, Rhode Island, Connecticut, New York,

Vermont, New Hampshire, Maryland (????? S.M.), South Carolina (??000 Sq Miles), Massachusetts

(73,000 Sq Miles), North Carolina (??,000 Sq Miles), New Jersey (105,000 Sq Miles), Kentuckey

(115000 Sq Miles), Georgia (15?,000 Sq Miles), Virginia (169000 Sq Miles), Western Territory (Extend

450,000 Square Miles), Western Territory Newly Acquired (in 1804) Louisiana (Extent 725,000 Square

Miles), East & West Florida (not yet united)

Figure 5 States and Territories of the United States of America March 27 1804 to October 1

1804, 2006, Golbez https://upload.wikimedia.org/wikipedia/commons/9/90/United_States_

1804-03-1804-10.png

Notes above map: Ruperts Land (United Kingdom), Disputed between Indiana Territory and Rupers

Land (UK), Disputed between Massachusetts and Colony of New Brunswick (UK) Note below map:

Disputed between United States and West Florida Labels other than modern state names, left-to-right:

Unclaimed territory, Viceroyalty of New Spain (Spain), Russian America (Russia), Louisiana Purchase

(unorganized), Indiana Territory, Mississippi Territory, West Florida (Spain), East Florida (Spain)

Figure 6 Statistical Chart shewing extent the population & revenues of the principal nations of Europe

in the order of their magnitude, 1801, William Playfair

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Figure 7 Diagram of the Causes of Mortality in the Army in the East, 1858, Florence Nightingale

https://en.wikipedia.org/wiki/Pie_chart#/media/File:Nightingale-mortality.jpg

Text below the smaller diagram: The areas of the blue, read, & black wedges are each measured from

the centre as the common vertex. The blue wedges measured from the centre of the circle represent

area for area the deaths from preventable or mitigable zymotic diseases; the red wedges measured

from the centre the deaths from wounds; & the black wedges measured from the centre the deaths

from all other causes. The black line across the red triangle in Nov. 1843 marks the boundary of the

deaths from all other causes during the month. In October 1854 & April 1855, the black area coincides

with the red; in January & February 1856, the blue coincides with the black. The entire area may be

compared by following the blue, the red & the black lines enclosing them.

Figure 8 Carte figurative des pertes successives en hommes de lArme Franaise dans la campagne

de Russie 1812-1813, Drawn by M. Minard, Inspector General of Bridges and Roads (retired).

Paris, 20 November 1869. Original French version: https://en.wikipedia.org/wiki/Charles_

Joseph_Minard#/media/File:Minard.png, English reproduction: https://en.wikipedia.org/

wiki/Charles_Joseph_Minard#/media/File:Minard_Update.png

English translation of the title and text above the figure: Figurative Map of the successive losses in men

of the French Army in the Russian campaign 18121813. The numbers of men present are represented

by the widths of the colored zones at a rate of one millimeter for every ten thousand men; they are

further written across the zones. The red designates the men who enter Russia, the black those who

leave it. The information which has served to draw up the map has been extracted from the works of

M. M. Thiers, de Sgur, de Fezensac, de Chambray and the unpublished diary of Jacob, the pharmacist

of the Army since October 28th. In order to better judge with the eye the diminution of the army,

I have assumed that the troops of Prince Jrme and of Marshal Davout, who had been detached at

Minsk and Mogilev and have rejoined near Orsha and Vitebsk, had always marched with the army.

Place names, left-to-right on the eastward march: Neman River, Kaunas, Vilnius, Hlybokaye, Polotsk,

Vitebsk, Smolensk, Dorogobuzh, Gagarin, Moskva River, Moscow.

Place names, right-to-left on the westward march: Tarutino, Maloyaroslavets, Mozhaysk, Vyazma,

Orsha, Dnieper River (Mogilev), Bobr, Studzionka, Berezina River, (Minsk) Maladzyechna, Smarhon,

Neman River

Numbers of men left-to-right along the top and right-to-left along the bottom (in thousands): 422, 6,

22, 400, 60, 33, 175, 145, 127.1, 100, 100, 100, 96, 87, 55, 37, 24, 20, 50, 28, 12, 14, 8, 4, 10

Scale for the distance covered: Common leagues of France (map of M. Fezensac); labeled 0 to 50

beginning in increments of 5 up to 25.

Title below the double line: Graphic Table of the temperature in degrees below zero of the Raumur

thermometer.

Text attached to figure by vertical lines, left-to-right: The Cossacks pass the frozen Neman at a gallop.

-26◦ December 7, -30◦ December 6, -24◦ December 1, -20◦ November 28, -11◦, -21◦ November 14,

-9◦ November 9, Rain October 24, 0◦ October 18 English redrawing includes Celsius and Fahrenheit

scales as labels to the horizontal lines: 0◦R/0◦C/32◦F, -10◦R/-13◦C/10◦F, -20◦R/-25◦C/-13◦F, -30◦R/-

38◦C/-36◦F

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