R Dataset / Package HistData / Minard.troops
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On this R-data statistics page, you will find information about the Minard.troops data set which pertains to Data from Minard's famous graphic map of Napoleon's march on Moscow. The Minard.troops data set is found in the HistData R package. You can load the Minard.troops data set in R by issuing the following command at the console data("Minard.troops"). This will load the data into a variable called Minard.troops. If R says the Minard.troops data set is not found, you can try installing the package by issuing this command install.packages("HistData") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Minard.troops R data set. The size of this file is about 1,142 bytes. Data from Minard's famous graphic map of Napoleon's march on MoscowDescriptionCharles Joseph Minard's graphic depiction of the fate of Napoleon's Grand Army in the Russian campaign of 1815 has been called the "greatest statistical graphic ever drawn" (Tufte, 1983). Friendly (2002) describes some background for this graphic, and presented it as Minard's Chalenge: to reproduce it using modern statistical or graphic software, in a way that showed the elegance of some computer language to both describe and produce this graphic. Usagedata(Minard.troops) data(Minard.cities) data(Minard.temp) Format
Details
Sourcehttp://www.cs.uic.edu/~wilkinson/TheGrammarOfGraphics/minard.txt ReferencesFriendly, M. (2002). Visions and Re-visions of Charles Joseph Minard, Journal of Educational and Behavioral Statistics, 27, No. 1, 31-51. Friendly, M. (2003). Re-Visions of Minard. http://www.math.yorku.ca/SCS/Gallery/re-minard.html Examplesdata(Minard.troops); data(Minard.cities)## Not run: require(ggplot2) plot_troops <- ggplot(Minard.troops, aes(long, lat)) + geom_path(aes(size = survivors, colour = direction, group = group)) plot_both <- plot_troops + geom_text(aes(label = city), size = 4, data = Minard.cities) plot_polished <- plot_both + scale_size(to = c(1, 12), breaks = c(1, 2, 3) * 10^5, labels = comma(c(1, 2, 3) * 10^5)) + scale_colour_manual(values = c("grey50","red")) + xlab(NULL) + ylab(NULL) # re-scale the plot window to an aspect ratio of ~ 4 x 1 windows(width=12, height=3) plot_polished ## TODO: add the plot of temperature below## End(Not run) -- Dataset imported from https://www.r-project.org. |
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Attachment | Size |
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dataset-98157.csv | 1.12 KB |