R/Guerry.R

In Guerry: Maps, Data and Methods Related to Guerry (1833) "Moral Statistics of France"

#' Data from A.-M. Guerry, "Essay on the Moral Statistics of France"
#' 
#' Andre-Michel Guerry (1833) was the first to systematically collect and
#' analyze social data on such things as crime, literacy and suicide with the
#' view to determining social laws and the relations among these variables.
#' 
#' The Guerry data frame comprises a collection of 'moral variables' on the 86
#' departments of France around 1830.  A few additional variables have been
#' added from other sources.
#' 
#' Note that most of the variables (e.g., `Crime_pers`) are scaled so that
#' 'more is better' morally.
#' 
#' Values for the quantitative variables displayed on Guerry's maps were taken
#' from Table A2 in the English translation of Guerry (1833) by Whitt and
#' Reinking.  Values for the ranked variables were taken from Table A1, with
#' some corrections applied.  The maximum is indicated by rank 1, and the
#' minimum by rank 86.
#' 
#' Numerous errors in scanning and transcription were corrected by Kathryn
#' Olivia DuBois, <kathryn.dubois@wsu.edu>
#' 
#' @name Guerry
#' @docType data
#' @format A data frame with 86 observations (the departments of France) on the following 23 variables.
#' \describe{
#'   \item{`dept`}{Department ID: Standard numbers for the departments, except for
#'     Corsica (200)}
#'   \item{`Region`}{Region of France ('N'='North', 'S'='South', 'E'='East',
#'     'W'='West', 'C'='Central'). Corsica is coded as NA}
#'   \item{`Department`}{Department name: Departments are named according to usage
#'     in 1830, but without accents. A factor with levels `"Ain"` `"Aisne"`
#'     `"Allier"` ... `"Vosges"` `"Yonne"`}
#'   \item{`Crime_pers`}{Population per Crime against persons. Source: A2 (Comptes
#'     general, 1825-1830)}
#'   \item{`Crime_prop`}{Population per Crime against property. Source: A2 (Compte
#'     general, 1825-1830)}
#'   \item{`Literacy`}{Percent Read & Write: Percent of military conscripts who can
#'     read and write. Source: A2}
#'   \item{`Donations`}{Donations to the poor. Source: A2 (Bulletin des lois)}
#'   \item{`Infants`}{Population per illegitimate birth. Source: A2 (Bureau des
#'     Longitudes, 1817-1821)}
#'   \item{`Suicides`}{Population per suicide. Source: A2 (Compte general,
#'     1827-1830)}
#'   \item{`MainCity`}{Size of principal city ('1:Sm', '2:Med', '3:Lg'), used as a
#'     surrogate for population density. Large refers to the top 10, small to the
#'     bottom 10; all the rest are classed Medium. Source: A1. An ordered factor
#'     with levels `"1:Sm"` < `"2:Med"` < `"3:Lg"`}
#'   \item{`Wealth`}{Per capita tax on personal property. A ranked index based on
#'     taxes on personal and movable property per inhabitant. Source: A1}
#'   \item{`Commerce`}{Commerce and Industry, measured by the rank of the number of
#'     patents / population. Source: A1}
#'   \item{`Clergy`}{Distribution of clergy, measured by the rank of the number of
#'     Catholic priests in active service / population. Source: A1 (Almanach
#'     officiel du clergy, 1829)}
#'   \item{`Crime_parents`}{Crimes against parents, measured by the rank of the
#'     ratio of crimes against parents to all crimes-- Average for the years
#'     1825-1830. Source: A1 (Compte general)}
#'   \item{`Infanticide`}{Infanticides per capita. A ranked ratio of number of
#'     infanticides to population-- Average for the years 1825-1830. Source: A1
#'     (Compte general)}
#'   \item{`Donation_clergy`}{Donations to the clergy. A ranked ratio of the number
#'     of bequests and donations inter vivios to population-- Average for the years
#'     1815-1824. Source: A1 (Bull. des lois, ordunn. d'autorisation)}
#'   \item{`Lottery`}{Per capita wager on Royal Lottery. Ranked ratio of the
#'     proceeds bet on the royal lottery to population--- Average for the years
#'     1822-1826. Source: A1 (Compte rendus par le ministre des finances)}
#'   \item{`Desertion`}{Military desertion, ratio of the number of young soldiers
#'     accused of desertion to the force of the military contingent, minus the
#'     deficit produced by the insufficiency of available billets-- Average of the
#'     years 1825-1827. Source: A1 (Compte du ministere du guerre, 1829 etat V)}
#'   \item{`Instruction`}{Instruction. Ranks recorded from Guerry's map of
#'     Instruction. Note: this is inversely related to `Literacy` (as defined
#'     here)}
#'   \item{`Prostitutes`}{Prostitutes in Paris. Number of prostitutes registered in
#'     Paris from 1816 to 1834, classified by the department of their birth Source:
#'     Parent-Duchatelet (1836), \emph{De la prostitution en Paris}}
#'   \item{`Distance`}{Distance to Paris (km). Distance of each department centroid
#'     to the centroid of the Seine (Paris) Source: calculated from department
#'     centroids}
#'   \item{`Area`}{Area (1000 km^2). Source: Angeville (1836)}
#'   \item{`Pop1831`}{1831 population. Population in 1831, taken from Angeville
#'     (1836), \emph{Essai sur la Statistique de la Population francaise}, in 1000s}
#' }
#' @seealso [`Angeville`] for other analysis variables
#' @references Dray, S., & Jombart, T. (2011).  Revisiting Guerry's data:
#' Introducing spatial constraints in multivariate analysis.  \emph{Annals of
#' Applied Statistics}, \bold{5}, 2278-2299
#' 
#' Brunsdon, C. and Dykes, J. (2007).  Geographically weighted visualization:
#' Interactive graphics for scale-varying exploratory analysis.
#' \emph{Geographical Information Science Research Conference (GISRUK 07)}, NUI
#' Maynooth, Ireland, April, 2007.
#' 
#' Friendly, M. (2007). A.-M. Guerry's Moral Statistics of France: Challenges
#' for Multivariable Spatial Analysis.  \emph{Statistical Science}, 22,
#' 368-399.
#' 
#' Friendly, M. (2007). Data from A.-M. Guerry, Essay on the Moral Statistics
#' of France (1833),
#' \url{https://www.datavis.ca/gallery/guerry/guerrydat.html}.
#' @source Angeville, A. (1836). \emph{Essai sur la Statistique de la
#' Population fran?aise} Paris: F. Doufour.
#' 
#' Guerry, A.-M. (1833). \emph{Essai sur la statistique morale de la France}
#' Paris: Crochard. English translation: Hugh P. Whitt and Victor W. Reinking,
#' Lewiston, N.Y. : Edwin Mellen Press, 2002.
#' 
#' Parent-Duchatelet, A. (1836). \emph{De la prostitution dans la ville de
#' Paris}, 3rd ed, 1857, p. 32, 36
#' @keywords datasets
#' @examples
#' 
#' library(car)
#' data(Guerry)
#' 
#' # Is there a relation between crime and literacy?
#' 
#' # Plot personal crime rate vs. literacy, using data ellipses. 
#' #    Identify the departments that stand out
#' set.seed(12315)
#' with(Guerry,{
#' 	dataEllipse(Literacy, Crime_pers,
#' 		levels = 0.68,
#'   	ylim = c(0,40000), xlim = c(0, 80),
#'   	ylab="Pop. per crime against persons",
#'   	xlab="Percent who can read & write",
#'   	pch = 16,
#'   	grid = FALSE,
#'   	id = list(method="mahal", n = 8, labels=Department, location="avoid", cex=1.2),
#'   	center.pch = 3, center.cex=5,
#'   	cex.lab=1.5)
#'   # add a 95% ellipse
#' 	dataEllipse(Literacy, Crime_pers,
#' 		levels = 0.95, add=TRUE,
#'   	ylim = c(0,40000), xlim = c(0, 80),
#'   	lwd=2, lty="longdash",
#'   	col="gray",
#'   	center.pch = FALSE
#'   	)
#'   
#'   # add the LS line and a loess smooth.
#'   abline( lm(Crime_pers ~ Literacy), lwd=2)	
#'   lines(loess.smooth(Literacy, Crime_pers), col="red", lwd=3)
#'   }
#'   	)
#' 
#' # A corrgram to show the relations among the main moral variables
#' # Re-arrange variables by PCA ordering.
#' 
#' library(corrgram)
#' corrgram(Guerry[,4:9], upper=panel.ellipse, order=TRUE)
#' 
#' 
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