Add datasets

R/data.R

@@ -1,13 +1,88 @@
+#' Hongite Mineralogy
+#'
+#' Mineral compositions of 25 specimens of hongite.
+#' @format A [`data.frame`] with 5 variables (minerals):
+#'  \describe{
+#'    \item{`A`}{Albite (weight percent).}
+#'    \item{`B`}{Blandite (weight percent).}
+#'    \item{`C`}{Cornite (weight percent).}
+#'    \item{`D`}{Daubite (weight percent).}
+#'    \item{`E`}{Endite (weight percent).}
+#'  }
+#' @references
+#'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
+#'  London: Chapman and Hall.
+#' @family datasets
+#' @keywords datasets
+"hongite"
+
+#' Kongite Mineralogy
+#'
+#' Mineral compositions of 25 specimens of kongite.
+#' @format A [`data.frame`] with 5 variables (minerals):
+#'  \describe{
+#'    \item{`A`}{Albite (weight percent).}
+#'    \item{`B`}{Blandite (weight percent).}
+#'    \item{`C`}{Cornite (weight percent).}
+#'    \item{`D`}{Daubite (weight percent).}
+#'    \item{`E`}{Endite (weight percent).}
+#'  }
+#' @references
+#'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
+#'  London: Chapman and Hall.
+#' @family datasets
+#' @keywords datasets
+"kongite"
+
+#' Boxite Mineralogy
+#'
+#' Mineral compositions and depths of 25 specimens of boxite.
+#' @format A [`data.frame`] with 5 variables (minerals):
+#'  \describe{
+#'    \item{`A`}{Albite (weight percent).}
+#'    \item{`B`}{Blandite (weight percent).}
+#'    \item{`C`}{Cornite (weight percent).}
+#'    \item{`D`}{Daubite (weight percent).}
+#'    \item{`E`}{Endite (weight percent).}
+#'    \item{`depth`}{Depth (meter).}
+#'  }
+#' @references
+#'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
+#'  London: Chapman and Hall.
+#' @family datasets
+#' @keywords datasets
+"boxite"
+
+#' Coxite Mineralogy
+#'
+#' Mineral compositions, depths and porosity of 25 specimens of coxite.
+#' @format A [`data.frame`] with 5 variables (minerals):
+#'  \describe{
+#'    \item{`A`}{Albite (weight percent).}
+#'    \item{`B`}{Blandite (weight percent).}
+#'    \item{`C`}{Cornite (weight percent).}
+#'    \item{`D`}{Daubite (weight percent).}
+#'    \item{`E`}{Endite (weight percent).}
+#'    \item{`depth`}{Depth (meter).}
+#'    \item{`porosity`}{Porosity (percent).}
+#'  }
+#' @references
+#'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
+#'  London: Chapman and Hall.
+#' @family datasets
+#' @keywords datasets
+"coxite"
+
 #' Arctic Lake
 #'
 #' Sand, silt, clay compositions of 39 sediment samples at different water
 #' depths in an Arctic lake.
 #' @format A [`data.frame`] with 4 variables:
 #'  \describe{
-#'    \item{sand}{Sand content (percent).}
-#'    \item{silt}{Silt content (percent).}
-#'    \item{clay}{Clay content (percent).}
-#'    \item{depth}{Water depth (m).}
+#'    \item{`sand`}{Sand content (percent).}
+#'    \item{`silt`}{Silt content (percent).}
+#'    \item{`clay`}{Clay content (percent).}
+#'    \item{`depth`}{Water depth (m).}
 #'  }
 #' @references
 #'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
@@ -16,39 +91,52 @@
 #' @keywords datasets
 "arctic"
 
-#' Hongite Mineralogy
+#' Skye Lavas Compositions
 #'
-#' Mineral compositions of 25 rock specimens of hongite type.
-#' @format A [`data.frame`] with 5 variables (minerals):
+#' Chemical compositions of 23 aphyric Skye lavas.
+#' @format A [`data.frame`] with 3 variables (percent):
 #'  \describe{
-#'    \item{A}{Albite (percent).}
-#'    \item{B}{Blandite (percent).}
-#'    \item{C}{Cornite (percent).}
-#'    \item{D}{Daubite (percent).}
-#'    \item{E}{Endite (percent).}
+#'    \item{`A`}{Na2O + K2O.}
+#'    \item{`F`}{Fe2O3.}
+#'    \item{`M`}{MgO.}
 #'  }
-#' @references
+#' @source
 #'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
-#'  London: Chapman and Hall.
+#'  London: Chapman and Hall. \doi{10.1007/978-94-009-4109-0}.
 #' @family datasets
 #' @keywords datasets
-"hongite"
+"lava"
+
+#' Predator-Prey Compositions
+#'
+#' Predator-prey compositions at 25 different sites.
+#' @format A [`data.frame`] with 3 variables (proportions):
+#'  \describe{
+#'    \item{`P`}{Predator.}
+#'    \item{`Q`}{Prey of species Q.}
+#'    \item{`R`}{Prey of species R.}
+#'  }
+#' @source
+#'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.
+#'  London: Chapman and Hall. \doi{10.1007/978-94-009-4109-0}.
+#' @family datasets
+#' @keywords datasets
+"predator"
 
-#' Thin Sections
+#' Thin Sections Compositions
 #'
 #' Mineral compositions of five slides as reported by five analysts.
 #' @format A [`data.frame`] with 9 variables:
 #'  \describe{
-#'    \item{analyst}{Analyst number.}
-#'    \item{slide}{Slide number.}
-#'    \item{quartz}{Quartz (percent).}
-#'    \item{microcline}{Microcline (percent).}
-#'    \item{plagioclass}{Plagioclass (percent).}
-#'    \item{biotite}{Biotite (percent).}
-#'    \item{plagioclass}{Plagioclass (percent).}
-#'    \item{muscovite}{Muscovite (percent).}
-#'    \item{opaques}{Opaque minerals (percent).}
-#'    \item{nonopaques}{Non-opaque minerals (percent).}
+#'    \item{`analyst`}{Analyst number.}
+#'    \item{`slide`}{Slide number.}
+#'    \item{`quartz`}{Quartz (percent).}
+#'    \item{`microcline`}{Microcline (percent).}
+#'    \item{`plagioclass`}{Plagioclass (percent).}
+#'    \item{`biotite`}{Biotite (percent).}
+#'    \item{`muscovite`}{Muscovite (percent).}
+#'    \item{`opaques`}{Opaque minerals (percent).}
+#'    \item{`nonopaques`}{Non-opaque minerals (percent).}
 #'  }
 #' @references
 #'  Aitchison, J. (1986). *The Statistical Analysis of Compositional Data*.

data-raw/DATASET.R

@@ -1,9 +1,24 @@
 ## Data from Aitchison (1986)
+hongite <- read.csv("data-raw/hongite.csv", header = TRUE, row.names = 1)
+usethis::use_data(hongite, overwrite = FALSE)
+
+kongite <- read.csv("data-raw/kongite.csv", header = TRUE, row.names = 1)
+usethis::use_data(kongite, overwrite = FALSE)
+
+boxite <- read.csv("data-raw/boxite.csv", header = TRUE, row.names = 1)
+usethis::use_data(boxite, overwrite = FALSE)
+
+coxite <- read.csv("data-raw/coxite.csv", header = TRUE, row.names = 1)
+usethis::use_data(coxite, overwrite = FALSE)
+
 arctic <- read.csv("data-raw/arctic.csv", header = TRUE, row.names = 1)
 usethis::use_data(arctic, overwrite = FALSE)
 
-hongite <- read.csv("data-raw/hongite.csv", header = TRUE, row.names = 1)
-usethis::use_data(hongite, overwrite = FALSE)
+lava <- read.csv("data-raw/lava.csv", header = TRUE, row.names = 1)
+usethis::use_data(lava, overwrite = FALSE)
+
+predator <- read.csv("data-raw/predator.csv", header = TRUE, row.names = 1)
+usethis::use_data(predator, overwrite = FALSE)
 
 slides <- read.csv("data-raw/slides.csv", header = TRUE, row.names = NULL)
 usethis::use_data(slides, overwrite = FALSE)

data-raw/boxite.csv

@@ -0,0 +1,26 @@
+,A,B,C,D,E,depth
+B1,43.5,25.1,14.7,10.0,6.7,1
+B2,41.1,27.5,13.9,9.5,8.0,2
+B3,41.5,20.1,20.6,11.1,6.7,3
+B4,33.9,37.8,11.1,11.5,5.7,4
+B5,46.5,16.0,15.6,14.3,7.6,5
+B6,45.3,19.4,14.8,13.5,9.3,6
+B7,33.2,25.2,15.2,17.1,9.3,7
+B8,40.8,15.1,21.7,14.6,7.8,8
+B9,33.0,30.8,15.1,12.9,8.2,9
+B10,28.2,38.6,12.1,14.1,6.9,10
+B11,33.9,31.5,15.4,12.0,7.2,11
+B12,48.7,19.3,13.4,10.7,7.9,12
+B13,37.8,37.1,10.4,8.6,6.1,13
+B14,42.0,26.6,13.7,10.5,7.2,14
+B15,44.2,26.5,12.9,9.6,6.8,15
+B16,39.7,23.2,20.6,10.2,6.3,16
+B17,39.3,28.1,13.0,13.6,6.0,17
+B18,34.1,26.7,13.6,17.0,8.6,18
+B19,36.2,35.3,11.2,11.9,5.4,19
+B20,39.5,36.0,9.4,8.4,6.7,20
+B21,39.5,22.5,18.7,11.4,7.9,21
+B22,33.0,33.5,17.7,9.8,6.0,22
+B23,42.3,16.6,16.9,17.0,7.2,23
+B24,39.9,19.0,13.4,21.3,6.4,24
+B25,37.8,30.9,11.9,12.9,6.5,25

data-raw/coxite.csv

@@ -0,0 +1,26 @@
+,A,B,C,D,E,depth,porosity
+C1,44.2,31.9,5.4,10.5,8.0,1,21.8
+C2,49.0,25.4,5.8,11.3,8.5,2,25.2
+C3,50.2,24.8,5.7,11.1,8.2,3,26.1
+C4,49.9,24.7,5.4,11.4,8.6,4,26.3
+C5,48.5,27.8,5.9,10.2,7.6,5,22.6
+C6,45.9,27.1,6.9,11.5,8.6,6,21.4
+C7,44.1,31.9,6.0,10.2,7.8,7,22.0
+C8,46.4,29.9,5.5,10.3,7.9,8,22.0
+C9,45.7,27.0,6.2,12.0,9.1,9,23.1
+C1O,46.4,30.0,5.1,10.4,8.1,10,24.0
+C11,41.7,30.2,7.7,11.6,8.8,11,18.4
+C12,44.9,25.7,7.7,12.4,9.3,12,20.5
+C13,48.6,27.7,5.8,10.2,7.7,13,22.9
+C14,49.7,26.7,4.9,10.6,8.1,14,27.2
+C15,49.6,24.4,6.4,11.2,8.4,15,23.4
+C16,46.5,28.6,5.9,10.7,8.3,16,22.5
+C17,47.3,24.2,7.9,11.8,8.8,17,21.6
+C18,44.7,30.0,6.8,10.5,8.0,18,20.5
+C19,48.0,25.6,7.0,11.1,8.3,19,22.7
+C20,50.0,23.8,6.6,11.2,8.4,20,23.7
+C21,51.4,24.2,5.7,10.7,8.0,21,26.2
+C22,53.3,25.1,5.2,9.4,7.0,22,26.4
+C23,47.9,25.4,6.7,11.4,8.6,23,22.2
+C24,43.5,29.8,6.7,11.2,8.8,24,19.5
+C25,44.5,29.2,6.5,11.2,8.6,25,21.3

data-raw/kongite.csv

@@ -0,0 +1,26 @@
+,A,B,C,D,E
+K1,33.5,6.1,41.3,7.1,12.0
+K2,47.6,14.9,16.1,14.8,6.6
+K3,52.7,23.9,6.0,8.7,8.7
+K4,44.5,24.2,10.7,11.9,8.7
+K5,42.3,47.6,0.6,4.1,5.4
+K6,51.8,33.2,1.9,7.0,6.1
+K7,47.9,21.5,10.7,9.5,10.4
+K8,51.2,23.6,6.2,13.3,5.7
+K9,19.3,2.3,65.8,5.8,6.8
+K10,46.1,23.4,10.4,11.5,8.6
+K11,30.6,6.7,43.0,6.3,13.4
+K12,49.7,28.1,5.1,8.0,9.1
+K13,49.4,24.3,7.6,8.5,10.2
+K14,38.4,9.5,30.6,14.8,6.7
+K15,41.6,19.0,17.3,13.8,8.3
+K16,42.3,43.3,1.6,5.9,6.9
+K17,45.7,23.9,10.3,11.6,8.5
+K18,45.5,20.3,13.6,10.9,9.7
+K19,52.1,17.9,10.7,7.9,11.4
+K20,46.2,14.3,18.5,12.2,8.8
+K21,47.2,30.9,4.6,6.3,11.0
+K22,45.4,33.3,4.0,11.9,5.4
+K23,48.6,23.4,8.7,10.7,8.6
+K24,31.2,4.5,47.0,10.2,7.1
+K25,44.3,15.0,19.4,10.5,10.8

data-raw/lava.csv

@@ -0,0 +1,24 @@
+,"A","F","M"
+"S1",52,42,6
+"S2",52,44,4
+"S3",47,48,5
+"S4",45,49,6
+"S5",40,50,10
+"S6",37,54,9
+"S7",27,58,15
+"S8",27,54,19
+"S9",23,59,18
+"S10",22,59,19
+"S11",21,60,19
+"S12",25,53,22
+"S13",24,54,22
+"S14",22,55,23
+"S15",22,56,22
+"S16",20,58,22
+"S17",16,62,22
+"S18",17,57,26
+"S19",14,54,32
+"S20",13,55,32
+"S21",13,52,35
+"S22",14,47,39
+"S23",24,56,20

data-raw/predator.csv

@@ -0,0 +1,26 @@
+,P,Q,R
+S1,0.123,0.649,0.227
+S2,0.218,0.557,0.225
+S3,0.072,0.787,0.142
+S4,0.103,0.703,0.195
+S5,0.158,0.450,0.392
+S6,0.257,0.372,0.370
+S7,0.129,0.439,0.433
+S8,0.120,0.531,0.340
+S9,0.096,0.677,0.227
+S10,0.131,0.666,0.203
+S11,0.241,0.581,0.178
+S12,0.134,0.600,0.266
+S13,0.184,0.579,0.236
+S14,0.053,0.688,0.259
+S15,0.106,0.673,0.221
+T1,0,0.478,0.522
+T2,0,0.583,0.417
+T3,0,0.380,0.620
+T4,0,0.682,0.318
+T5,0,0.628,0.372
+T6,0,0.597,0.403
+T7,0,0.514,0.486
+T8,0,0.563,0.437
+T9,0,0.603,0.397
+T1O,0,0.775,0.225