Michael Friendly [aut, cre],
Stephane Dray [ctb],
Hadley Wickham [ctb],
James Hanley [ctb],
Dennis Murphy [ctb]

Data Sets from the History of Statistics and Data Visualization

c(person(given = "Michael", family = "Friendly", role=c("aut", "cre"), email="friendly@yorku.ca"),
person(given = "Stephane", family = "Dray", role="ctb"),
person(given = "Hadley", family = "Wickham", role="ctb"),
person(given = "James", family = "Hanley", role="ctb"),
person(given = "Dennis", family = "Murphy", role="ctb"),
person(given = "Peter", family = "Li", role="ctb")
)
gtools, KernSmooth, maps, ggplot2, proto, grid, reshape,
plyr, lattice, jpeg, car, gplots, sp, heplots, knitr, rmarkdown
Michael Friendly [aut, cre],
Stephane Dray [ctb],
Hadley Wickham [ctb],
James Hanley [ctb],
Dennis Murphy [ctb],
Peter Li [ctb]

The 'HistData' package provides a collection of small 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 these present interesting challenges for graphics
or analysis in R.
gtools, KernSmooth, maps, ggplot2, proto, grid, reshape,
plyr, lattice, jpeg, car, gplots, sp, heplots, knitr,
rmarkdown, effects, lubridate

The 'HistData' package provides a collection of small 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 these present interesting
challenges for graphics or analysis in R.

gtools, KernSmooth, maps, ggplot2, scales, proto, grid,
reshape, plyr, lattice, jpeg, car, gplots, sp, heplots, knitr,
rmarkdown, effects, lubridate, gridExtra

gtools, KernSmooth, maps, ggplot2, scales, proto, grid,
reshape, plyr, lattice, jpeg, car, gplots, sp, heplots, knitr,
rmarkdown, effects, lubridate, gridExtra, vcd, MASS

This package provides a number of utility functions useful for manipulating large histograms.  This includes methods to trim, subset, merge buckets, merge histograms, convert to CDF, and calculate information loss due to binning.  It also provides a protocol buffer representations of the default R histogram class to allow histograms over large data sets to be computed and manipulated in a MapReduce environment.