HistData-package: Data sets from the History of Statistics and Data...
In HistData: Data Sets from the History of Statistics and Data Visualization
HistData-package R Documentation
Data sets from the History of Statistics and Data Visualization
Description
The HistData package provides a collection of data sets
that are interesting and important in the history of statistics and data visualization.
The goal of the package is to make these available, both for instructional use
and for historical research.
Some of the data sets have examples which reproduce an historical graph or analysis.
These are meant mainly as starters for more extensive re-analysis or graphical
elaboration. Some of these present graphical challenges to reproduce in R.
They are part of a program of research called statistical historiography,
meaning the use of statistical methods to study problems and questions in the
history of statistics and graphics. A main aspect of this is the increased
understanding of historical problems in science and data analysis
trough the process of trying to reproduce a graph or analysis using
modern methods. I call this "Re-visioning", meaning to see again,
hopefully in a new light.
A number of these are illustrated in our book,
Friendly & Wainer (2021), A History of Data Visualization and Graphic Communication,
and some are re-produced in R in the companion web site, https://friendly.github.io/HistDataVis/.
Details
Descriptions of each DataSet can be found using help(DataSet);
example(DataSet) will likely show applications similar to the
historical use.
Data sets included in the HistData package are:
ArbuthnotArbuthnot's data on male and female birth ratios in London from 1629-1710
ArmadaThe Spanish Armada
BowleyBowley's data on values of British and Irish trade, 1855-1899
BreslauHalley's Breslau Life Table
CavendishCavendish's 1798 determinations of the density of the earth
ChestSizesQuetelet's data on chest measurements of Scottish militiamen
CholeraWilliam Farr's Data on Cholera in London, 1849
CholeraDeaths1849Daily Deaths from Cholera and Diarrhaea in England, 1849
CushnyPeeblesCushny-Peebles data: Soporific effects of scopolamine derivatives
DactylEdgeworth's counts of dactyls in Virgil's Aeneid
DrinksWagesElderton and Pearson's (1910) data on drinking and wages
EdgeworthDeathsEdgeworth's Data on Death Rates in British Counties
FingerprintsWaite's data on Patterns in Fingerprints
GaltonGalton's data on the heights of parents and their children
GaltonFamiliesGalton's data on the heights of parents and their children, by family
GuerryData from A.-M. Guerry, "Essay on the Moral Statistics of France"
HalleyLifeTableHalley's Life Table
JevonsW. Stanley Jevons' data on numerical discrimination
Langrenvan Langren's data on longitude distance between Toledo and Rome
MacdonellMacdonell's data on height and finger length of criminals, used by Gosset (1908)
MayerMayer's data on the libration of the moon
MichelsonMichelson's 1879 determinations of the velocity of light
MinardData from Minard's famous graphic map of Napoleon's march on Moscow
NightingaleFlorence Nightingale's data on deaths from various causes in the Crimean War
OldMapsLatitudes and Longitudes of 39 Points in 11 Old Maps
PearsonLeePearson and Lee's 1896 data on the heights of parents and children classified by gender
PolioTrialsPolio Field Trials Data on the Salk vaccine
Pollen5D dataset from the 1986 JSM Challenge
ProstitutesParent-Duchatelet's time-series data on the number of prostitutes in Paris
PyxTrial of the Pyx
QuarrelsStatistics of Deadly Quarrels
SaturnLaplace's Saturn data
SnowJohn Snow's map and data on the 1854 London Cholera outbreak
VirginisJ. F. W. Herschel's data on the orbit of the twin star gamma Virginis
WheatPlayfair's data on wages and the price of wheat
YeastStudent's (1906) Yeast Cell Counts
ZeaMaysDarwin's Heights of Cross- and Self-fertilized Zea May Pairs
Author(s)
Michael Friendly
Maintainer: Michael Friendly <friendly@yorku.ca>
References
Friendly, M. (2007). A Brief History of Data Visualization.
In Chen, C., Hardle, W. & Unwin, A. (eds.)
Handbook of Computational Statistics: Data Visualization, Springer-Verlag, III, Ch. 1, 1-34.
Friendly, M. & Denis, D. (2001).
Milestones in the history of thematic cartography, statistical graphics, and data visualization.
http://datavis.ca/milestones/
Friendly, M. & Denis, D. (2005). The early origins and development of the scatterplot.
Journal of the History of the Behavioral Sciences,
41, 103-130.
Friendly, M. & Sigal, M. & Harnanansingh, D. (2016).
"The Milestones Project: A Database for the History of Data Visualization,"
In Kostelnick, C. & Kimball, M. (ed.),
Visible Numbers: The History of Data Visualization, Ashgate Press, Chapter 10.
Friendly, M. & Wainer, H. (2021). A History of Data Visualization and Graphic Communication.
Harvard University Press. Book: https://www.hup.harvard.edu/catalog.php?isbn=9780674975231, Web site:
https://friendly.github.io/HistDataVis/.
See Also
Arbuthnot,
Armada,
Bowley,
Cavendish,
ChestSizes,
Cholera,
CholeraDeaths1849,
CushnyPeebles,
Dactyl,
DrinksWages,
EdgeworthDeaths,
Fingerprints,
Galton,
GaltonFamilies,
Guerry,
HalleyLifeTable,
Jevons,
Langren,
Macdonell,
Michelson,
Minard,
Nightingale,
OldMaps,
PearsonLee,
PolioTrials,
Pollen,
Prostitutes,
Pyx,
Quarrels,
Snow,
Wheat,
Yeast,
ZeaMays
Other packages containing data sets of historical interest include:
The Guerry-package, containing maps and
other data sets related to Guerry's (1833) Moral Statistics of France.
morsecodes from the (defunct) xgobi package
for data from Rothkopf (1957) on errors in learning Morse code, a classical
example for MDS.
The psych package, containing Galton's peas data.
The same data set is contained in alr4 as galtonpeas.
The agridat contains a large number of data sets of agricultural data,
including some extra data sets related to
the classical barley data
(immer and barley)
from Immer (1934):
minnesota.barley.yield,
minnesota.barley.weather.
Examples
# see examples for the separate data sets
HistData documentation built on Aug. 10, 2023, 1:08 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| HistData-package | R Documentation |
Data sets from the History of Statistics and Data Visualization
Description
The HistData package provides a collection of data sets that are interesting and important in the history of statistics and data visualization. The goal of the package is to make these available, both for instructional use and for historical research.
Some of the data sets have examples which reproduce an historical graph or analysis. These are meant mainly as starters for more extensive re-analysis or graphical elaboration. Some of these present graphical challenges to reproduce in R.
They are part of a program of research called statistical historiography, meaning the use of statistical methods to study problems and questions in the history of statistics and graphics. A main aspect of this is the increased understanding of historical problems in science and data analysis trough the process of trying to reproduce a graph or analysis using modern methods. I call this "Re-visioning", meaning to see again, hopefully in a new light.
A number of these are illustrated in our book, Friendly & Wainer (2021), A History of Data Visualization and Graphic Communication, and some are re-produced in R in the companion web site, https://friendly.github.io/HistDataVis/.
Details
Descriptions of each DataSet can be found using help(DataSet);
example(DataSet) will likely show applications similar to the
historical use.
Data sets included in the HistData package are:
ArbuthnotArbuthnot's data on male and female birth ratios in London from 1629-1710
ArmadaThe Spanish Armada
BowleyBowley's data on values of British and Irish trade, 1855-1899
BreslauHalley's Breslau Life Table
CavendishCavendish's 1798 determinations of the density of the earth
ChestSizesQuetelet's data on chest measurements of Scottish militiamen
CholeraWilliam Farr's Data on Cholera in London, 1849
CholeraDeaths1849Daily Deaths from Cholera and Diarrhaea in England, 1849
CushnyPeeblesCushny-Peebles data: Soporific effects of scopolamine derivatives
DactylEdgeworth's counts of dactyls in Virgil's Aeneid
DrinksWagesElderton and Pearson's (1910) data on drinking and wages
EdgeworthDeathsEdgeworth's Data on Death Rates in British Counties
FingerprintsWaite's data on Patterns in Fingerprints
GaltonGalton's data on the heights of parents and their children
GaltonFamiliesGalton's data on the heights of parents and their children, by family
GuerryData from A.-M. Guerry, "Essay on the Moral Statistics of France"
HalleyLifeTableHalley's Life Table
JevonsW. Stanley Jevons' data on numerical discrimination
Langrenvan Langren's data on longitude distance between Toledo and Rome
MacdonellMacdonell's data on height and finger length of criminals, used by Gosset (1908)
MayerMayer's data on the libration of the moon
MichelsonMichelson's 1879 determinations of the velocity of light
MinardData from Minard's famous graphic map of Napoleon's march on Moscow
NightingaleFlorence Nightingale's data on deaths from various causes in the Crimean War
OldMapsLatitudes and Longitudes of 39 Points in 11 Old Maps
PearsonLeePearson and Lee's 1896 data on the heights of parents and children classified by gender
PolioTrialsPolio Field Trials Data on the Salk vaccine
Pollen5D dataset from the 1986 JSM Challenge
ProstitutesParent-Duchatelet's time-series data on the number of prostitutes in Paris
PyxTrial of the Pyx
QuarrelsStatistics of Deadly Quarrels
SaturnLaplace's Saturn data
SnowJohn Snow's map and data on the 1854 London Cholera outbreak
VirginisJ. F. W. Herschel's data on the orbit of the twin star gamma Virginis
WheatPlayfair's data on wages and the price of wheat
YeastStudent's (1906) Yeast Cell Counts
ZeaMaysDarwin's Heights of Cross- and Self-fertilized Zea May Pairs
Author(s)
Michael Friendly
Maintainer: Michael Friendly <friendly@yorku.ca>
References
Friendly, M. (2007). A Brief History of Data Visualization. In Chen, C., Hardle, W. & Unwin, A. (eds.) Handbook of Computational Statistics: Data Visualization, Springer-Verlag, III, Ch. 1, 1-34.
Friendly, M. & Denis, D. (2001). Milestones in the history of thematic cartography, statistical graphics, and data visualization. http://datavis.ca/milestones/
Friendly, M. & Denis, D. (2005). The early origins and development of the scatterplot. Journal of the History of the Behavioral Sciences, 41, 103-130.
Friendly, M. & Sigal, M. & Harnanansingh, D. (2016). "The Milestones Project: A Database for the History of Data Visualization," In Kostelnick, C. & Kimball, M. (ed.), Visible Numbers: The History of Data Visualization, Ashgate Press, Chapter 10.
Friendly, M. & Wainer, H. (2021). A History of Data Visualization and Graphic Communication. Harvard University Press. Book: https://www.hup.harvard.edu/catalog.php?isbn=9780674975231, Web site: https://friendly.github.io/HistDataVis/.
See Also
Arbuthnot,
Armada,
Bowley,
Cavendish,
ChestSizes,
Cholera,
CholeraDeaths1849,
CushnyPeebles,
Dactyl,
DrinksWages,
EdgeworthDeaths,
Fingerprints,
Galton,
GaltonFamilies,
Guerry,
HalleyLifeTable,
Jevons,
Langren,
Macdonell,
Michelson,
Minard,
Nightingale,
OldMaps,
PearsonLee,
PolioTrials,
Pollen,
Prostitutes,
Pyx,
Quarrels,
Snow,
Wheat,
Yeast,
ZeaMays
Other packages containing data sets of historical interest include:
The Guerry-package, containing maps and
other data sets related to Guerry's (1833) Moral Statistics of France.
morsecodes from the (defunct) xgobi package
for data from Rothkopf (1957) on errors in learning Morse code, a classical
example for MDS.
The psych package, containing Galton's peas data.
The same data set is contained in alr4 as galtonpeas.
The agridat contains a large number of data sets of agricultural data,
including some extra data sets related to
the classical barley data
(immer and barley)
from Immer (1934):
minnesota.barley.yield,
minnesota.barley.weather.
Examples
# see examples for the separate data sets
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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