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Day 2

Data Science Summer Institute 2024

Bryan Stutzman

Instructor of Mathematics

NCSSM - Morganton

bryan.stutzman@ncssm.edu

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What is it? Why is it important?

Data Visualization

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London, early 1850s

Cholera was rampant throughout London and no one knew why.

Illustration from Punch (1852).

We may think of data science as a relatively new field, but powerful examples of its use can be found from quite some time ago. One famous one is from London in the 1850s. In those days, as now, London was a great center of trade and the arts, but there were some parts of it where the people were quite poor. The living conditions were crowded. It was dirty. Disease was rife, and into London, from time to time, would sweep the disease called cholera.

People in those days didn't understand how infectious diseases passed from one person to another. This disease would arrive, and hundreds of people would die in a week and tens of thousands in a month, and then mercifully, it would pass, but people would wait in trepidation for it to come again. This illustration is from the satirical magazine Punch and notice that it's called "A Court for King Cholera." Cholera ruled, and the people of London were at its mercy.

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Miasmas and Miasmatists

Bad smells given off by waste and rotting matter were believed to be the main source of disease.

Suggested remedies:

“fly to clene air”
“a pocket full o’posies”
“fire off barrels of gunpowder”

Staunch believers:

Florence Nightingale
Edwin Chadwick, Commissioner of the General Board of Health

Now, people did try to explain how diseases were spread, and the leading cause was bad smell. Bad smells given off by rotting matter were believed to be the primary source of disease, and the people who believed in this were called miasmatists because bad smells are called miasmas.

People suggested remedies. Fly to clene air was one of them. Some of you may remember from a nursery rhyme a pocket full of posies. If you carry a sweet-smelling bunch of flowers in your pocket, you might be able to use it to ward off the bad smells. That is the miasmas. Someone rather alarmingly suggested firing off barrels of gunpowder in the middle of London, so that the smell of the gunpowder would vanquish the miasmas. This may seem ridiculous now with all the advances we've made in medical science, however some very well-known people were miasmatists. You might recognize the name of Florence Nightingale, the great nurse. Even the Commissioner of the General Board of Health in London was himself a miasmatist. But one man was not.

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John Snow, 1813-1858

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Data Visualization

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[CLICK]

The black rectangle at this address represents one person who died of cholera at that address. [CLICK] Here is a taller black rectangle that consists of little rectangles stacked up. Several people died at this address, and you can see, [CLICK] a lot of people died here. Because he felt that dirty water was the cause of this disease, he also marked the pumps. [CLICK] You can see that the black rectangles sort of flare out around the Broad Street pump.

John Snow believed that drinking water from the Broad Street pump was causing the spread of the disease. [CLICK] To be confident about this, he had to explain the parts of the map that were not consistent with this theory. Here, for example, is the Lion brewery, [CLICK] quite close to the Broad Street pump. Why was that? Well, the people in the brewery drank what they brewed. Should they want water, the brewery had its own well.

So did the workhouse [CLICK], where there were a lot of poor people, very few deaths. The workhouse, too, had its own well.

[CLICK] Some of the deaths in regions far away from the pump were those of little children who drank from the Broad Street pump on their way to school. These addresses are actually closer to the Rupert Street pump, but the Rupert Street pump was inconvenient to get to because it was at the end of a dead-end street. It was a lot more convenient to get water from Broad Street.

John Snow was very confident that he had, if not causation, certainly a clear enough association that he wanted to take action. He asked the local municipal authority to disable the handle of the Broad Street pump. That meant that people could no longer drink from it. The deaths from cholera died down. Possibly, they were on the wane already because the epidemic was passing, but it is believed that he might have saved several lives from future epidemics.

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John Snow, 1813-1858

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Other famous data visualizations

Hans Rosling: Gapminder

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Other famous data visualizations

Charles Minard: Napoleon's Russian campaign (1869) (Video)

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Other famous data visualizations

Florence Nightingale: "Diagram of the causes of mortality…" (1858)

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Other famous data visualizations

W.E.B Dubois: "The Exhibit of American Negroes" (1900)

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What makes for an effective data visualization?

Integrity�Data visualizations should be accurate, consistent, and honest�
Interestingness�Data visualizations should be relevant, meaningful, and tell a story�
Usefulness�Data visualizations should be useable, fit your goals, and efficient�
Beauty�Data visualizations should be visually pleasing with a beautiful structure

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Text Analysis

Classroom Activity

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I. YOU don't know about me without you have read a book by the name of The Adventures of Tom Sawyer; but that ain't no matter. That book was made by Mr. Mark Twain, and he told the truth, mainly. There was things which he stretched, but mainly he told the truth. That is nothing. I never seen anybody but lied one time or another, without it was Aunt Polly, or the widow, or maybe Mary. Aunt Polly--Tom's Aunt Polly, she is--and Mary, and the Widow Douglas is all told about in that book, which is mostly a true book, with some stretchers, as I said before. Now the way that the book winds up is this: Tom and me found the money that the robbers hid in the cave, and it made us rich. We got six thousand dollars apiece--all gold. It was an awful sight of money when it was piled up. Well, Judge Thatcher he took it and put it out at interest, and it fetched us a dollar a day apiece all the year round--more than a body could tell what to do with. The Widow Douglas she took me for her son, and allowed she would sivilize me; but it was rough living in the house all the time, considering how dismal regular and decent the widow was in all her ways; and so when I couldn't stand it no longer I lit out...

gutenberg.org

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I. YOU don't know about me without you have read a book ...

II. WE went tiptoeing along a path amongst the trees bac ...

III. WELL, I got a good going-over in the morning from o ...

IV. WELL, three or four months run along, and it was wel ...

V. I had shut the door to. Then I turned around and ther ...

VI. WELL, pretty soon the old man was up and around agai ...

VII. "GIT up! What you 'bout?" I opened my eyes and look ...

VIII. THE sun was up so high when I waked that I judged ...

IX. I wanted to go and look at a place right about the m ...

X. AFTER breakfast I wanted to talk about the dead man a ...

XI. "COME in," says the woman, and I did. She says: "Tak ...

XII. IT must a been close on to one o'clock when we got ...

XIII. WELL, I catched my breath and most fainted. Shut u ...

XIV. BY and by, when we got up, we turned over the truck ...

XV. WE judged that three nights more would fetch us to C ...

XVI. WE slept most all day, and started out at night, a ...

XVII. IN about a minute somebody spoke out of a window w ...

XVIII. COL. Grangerford was a gentleman, you see. He was ...

XIX. TWO or three days and nights went by; I reckon I mi ...

XX. THEY asked us considerable many questions; wanted to ...

XXI. IT was after sun-up now, but we went right on and d ...

XXII. THEY swarmed up towards Sherburn's house, a-whoopi ...

XXIII. WELL, all day him and the king was hard at it, ri ...

XXIV. NEXT day, towards night, we laid up under a little ...

XXV. THE news was all over town in two minutes, and you ...

XXVI. WELL, when they was all gone the king he asks Mary ...

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So many!

Tools for Data Visualization

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CoDAP (https://codap.concord.org)

CODAP is free open source software for data analysis built for use in schools. With CODAP, you can explore, visualize, and learn from data in any content area. Their mission is to make data literacy accessible for all students.

Dataset: Chronic Kidney Disease (159 observations)

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Jupyter Notebooks (https://jupyter.org/)

Dataset: World Data Statistics (41,415 observations)

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Google Sheets (https://sheets.google.com)

Dataset: World Data Statistics (41,415 observations)

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Places to find data

Social Explorer: https://www.socialexplorer.com/explore-maps
Data Commons: https://www.datacommons.org/
NOAA (Classroom-ready data resources): https://www.noaa.gov/education/resource-collections/data/classroom-ready
Dataquest Article: https://www.dataquest.io/blog/free-datasets-for-projects/
Dropbase: https://www.dropbase.io/post/top-11-open-and-public-data-sources
Data.gov: https://data.gov/
Data is Plural: https://www.data-is-plural.com/
Arctype: https://arctype.com/blog/public-datasets-for-analysis/
Knowledgehut: https://www.knowledgehut.com/blog/data-science/data-science-datasets
Geekflare: https://geekflare.com/open-datasets-for-data-science/
Open Numbers: https://open-numbers.github.io/datasets.html
NASA Data Sets: https://data.nasa.gov/
National University Library: https://resources.nu.edu/researchprocess/datasets