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1
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2 R Under development (unstable) (2012-03-05 r58592)
3 Copyright (C) 2012 The R Foundation for Statistical Computing
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4 ISBN 3-900051-07-0
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5 Platform: x86_64-unknown-linux-gnu (64-bit)
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6
7 R is free software and comes with ABSOLUTELY NO WARRANTY.
8 You are welcome to redistribute it under certain conditions.
9 Type 'license()' or 'licence()' for distribution details.
10
11 R is a collaborative project with many contributors.
12 Type 'contributors()' for more information and
13 'citation()' on how to cite R or R packages in publications.
14
15 Type 'demo()' for some demos, 'help()' for on-line help, or
16 'help.start()' for an HTML browser interface to help.
17 Type 'q()' to quit R.
18
19 > #### Simple integrity tests of the system datasets
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20 >
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21 > options(useFancyQuotes=FALSE)
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22 > env <- as.environment("package:datasets")
23 > d <- ls(env) # don't want .names
24 > for(f in d) {
25 + cat("\n** structure of dataset ", f, "\n", sep="")
26 + str(get(f, envir=env, inherits=FALSE))
27 + }
28
29 ** structure of dataset AirPassengers
30 Time-Series [1:144] from 1949 to 1961: 112 118 132 129 121 135 148 148 136 119 ...
31
32 ** structure of dataset BJsales
33 Time-Series [1:150] from 1 to 150: 200 200 199 199 199 ...
34
35 ** structure of dataset BJsales.lead
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36 Time-Series [1:150] from 1 to 150: 10.01 10.07 10.32 9.75 10.33 ...
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37
38 ** structure of dataset BOD
39 'data.frame': 6 obs. of 2 variables:
40 $ Time : num 1 2 3 4 5 7
41 $ demand: num 8.3 10.3 19 16 15.6 19.8
42 - attr(*, "reference")= chr "A1.4, p. 270"
43
44 ** structure of dataset CO2
45 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 84 obs. of 5 variables:
46 $ Plant : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ...
47 $ Type : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ...
48 $ Treatment: Factor w/ 2 levels "nonchilled","chilled": 1 1 1 1 1 1 1 1 1 1 ...
49 $ conc : num 95 175 250 350 500 675 1000 95 175 250 ...
50 $ uptake : num 16 30.4 34.8 37.2 35.3 39.2 39.7 13.6 27.3 37.1 ...
51 - attr(*, "formula")=Class 'formula' length 3 uptake ~ conc | Plant
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52 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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53 - attr(*, "outer")=Class 'formula' length 2 ~Treatment * Type
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54 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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55 - attr(*, "labels")=List of 2
56 ..$ x: chr "Ambient carbon dioxide concentration"
57 ..$ y: chr "CO2 uptake rate"
58 - attr(*, "units")=List of 2
59 ..$ x: chr "(uL/L)"
60 ..$ y: chr "(umol/m^2 s)"
61
62 ** structure of dataset ChickWeight
63 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 578 obs. of 4 variables:
64 $ weight: num 42 51 59 64 76 93 106 125 149 171 ...
65 $ Time : num 0 2 4 6 8 10 12 14 16 18 ...
66 $ Chick : Ord.factor w/ 50 levels "18"<"16"<"15"<..: 15 15 15 15 15 15 15 15 15 15 ...
67 $ Diet : Factor w/ 4 levels "1","2","3","4": 1 1 1 1 1 1 1 1 1 1 ...
68 - attr(*, "formula")=Class 'formula' length 3 weight ~ Time | Chick
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69 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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70 - attr(*, "outer")=Class 'formula' length 2 ~Diet
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71 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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72 - attr(*, "labels")=List of 2
73 ..$ x: chr "Time"
74 ..$ y: chr "Body weight"
75 - attr(*, "units")=List of 2
76 ..$ x: chr "(days)"
77 ..$ y: chr "(gm)"
78
79 ** structure of dataset DNase
80 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 176 obs. of 3 variables:
81 $ Run : Ord.factor w/ 11 levels "10"<"11"<"9"<..: 4 4 4 4 4 4 4 4 4 4 ...
82 $ conc : num 0.0488 0.0488 0.1953 0.1953 0.3906 ...
83 $ density: num 0.017 0.018 0.121 0.124 0.206 0.215 0.377 0.374 0.614 0.609 ...
84 - attr(*, "formula")=Class 'formula' length 3 density ~ conc | Run
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85 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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86 - attr(*, "labels")=List of 2
87 ..$ x: chr "DNase concentration"
88 ..$ y: chr "Optical density"
89 - attr(*, "units")=List of 1
90 ..$ x: chr "(ng/ml)"
91
92 ** structure of dataset EuStockMarkets
93 mts [1:1860, 1:4] 1629 1614 1607 1621 1618 ...
94 - attr(*, "dimnames")=List of 2
95 ..$ : NULL
96 ..$ : chr [1:4] "DAX" "SMI" "CAC" "FTSE"
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97 - attr(*, "tsp")= num [1:3] 1991 1999 260
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98 - attr(*, "class")= chr [1:2] "mts" "ts"
99
100 ** structure of dataset Formaldehyde
101 'data.frame': 6 obs. of 2 variables:
102 $ carb : num 0.1 0.3 0.5 0.6 0.7 0.9
103 $ optden: num 0.086 0.269 0.446 0.538 0.626 0.782
104
105 ** structure of dataset HairEyeColor
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106 table [1:4, 1:4, 1:2] 32 53 10 3 11 50 10 30 10 25 ...
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107 - attr(*, "dimnames")=List of 3
108 ..$ Hair: chr [1:4] "Black" "Brown" "Red" "Blond"
109 ..$ Eye : chr [1:4] "Brown" "Blue" "Hazel" "Green"
110 ..$ Sex : chr [1:2] "Male" "Female"
111
112 ** structure of dataset Harman23.cor
113 List of 3
114 $ cov : num [1:8, 1:8] 1 0.846 0.805 0.859 0.473 0.398 0.301 0.382 0.846 1 ...
115 ..- attr(*, "dimnames")=List of 2
116 .. ..$ : chr [1:8] "height" "arm.span" "forearm" "lower.leg" ...
117 .. ..$ : chr [1:8] "height" "arm.span" "forearm" "lower.leg" ...
118 $ center: num [1:8] 0 0 0 0 0 0 0 0
119 $ n.obs : num 305
120
121 ** structure of dataset Harman74.cor
122 List of 3
123 $ cov : num [1:24, 1:24] 1 0.318 0.403 0.468 0.321 0.335 0.304 0.332 0.326 0.116 ...
124 ..- attr(*, "dimnames")=List of 2
125 .. ..$ : chr [1:24] "VisualPerception" "Cubes" "PaperFormBoard" "Flags" ...
126 .. ..$ : chr [1:24] "VisualPerception" "Cubes" "PaperFormBoard" "Flags" ...
127 $ center: num [1:24] 0 0 0 0 0 0 0 0 0 0 ...
128 $ n.obs : num 145
129
130 ** structure of dataset Indometh
131 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 66 obs. of 3 variables:
132 $ Subject: Ord.factor w/ 6 levels "1"<"4"<"2"<"5"<..: 1 1 1 1 1 1 1 1 1 1 ...
133 $ time : num 0.25 0.5 0.75 1 1.25 2 3 4 5 6 ...
134 $ conc : num 1.5 0.94 0.78 0.48 0.37 0.19 0.12 0.11 0.08 0.07 ...
135 - attr(*, "formula")=Class 'formula' length 3 conc ~ time | Subject
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136 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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137 - attr(*, "labels")=List of 2
138 ..$ x: chr "Time since drug administration"
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139 ..$ y: chr "Indomethacin concentration"
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140 - attr(*, "units")=List of 2
141 ..$ x: chr "(hr)"
142 ..$ y: chr "(mcg/ml)"
143
144 ** structure of dataset InsectSprays
145 'data.frame': 72 obs. of 2 variables:
146 $ count: num 10 7 20 14 14 12 10 23 17 20 ...
147 $ spray: Factor w/ 6 levels "A","B","C","D",..: 1 1 1 1 1 1 1 1 1 1 ...
148
149 ** structure of dataset JohnsonJohnson
150 Time-Series [1:84] from 1960 to 1981: 0.71 0.63 0.85 0.44 0.61 0.69 0.92 0.55 0.72 0.77 ...
151
152 ** structure of dataset LakeHuron
153 Time-Series [1:98] from 1875 to 1972: 580 582 581 581 580 ...
154
155 ** structure of dataset LifeCycleSavings
156 'data.frame': 50 obs. of 5 variables:
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157 $ sr : num 11.43 12.07 13.17 5.75 12.88 ...
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158 $ pop15: num 29.4 23.3 23.8 41.9 42.2 ...
159 $ pop75: num 2.87 4.41 4.43 1.67 0.83 2.85 1.34 0.67 1.06 1.14 ...
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160 $ dpi : num 2330 1508 2108 189 728 ...
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161 $ ddpi : num 2.87 3.93 3.82 0.22 4.56 2.43 2.67 6.51 3.08 2.8 ...
162
163 ** structure of dataset Loblolly
164 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 84 obs. of 3 variables:
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165 $ height: num 4.51 10.89 28.72 41.74 52.7 ...
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166 $ age : num 3 5 10 15 20 25 3 5 10 15 ...
167 $ Seed : Ord.factor w/ 14 levels "329"<"327"<"325"<..: 10 10 10 10 10 10 13 13 13 13 ...
168 - attr(*, "formula")=Class 'formula' length 3 height ~ age | Seed
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169 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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170 - attr(*, "labels")=List of 2
171 ..$ x: chr "Age of tree"
172 ..$ y: chr "Height of tree"
173 - attr(*, "units")=List of 2
174 ..$ x: chr "(yr)"
175 ..$ y: chr "(ft)"
176
177 ** structure of dataset Nile
178 Time-Series [1:100] from 1871 to 1970: 1120 1160 963 1210 1160 1160 813 1230 1370 1140 ...
179
180 ** structure of dataset Orange
181 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 35 obs. of 3 variables:
182 $ Tree : Ord.factor w/ 5 levels "3"<"1"<"5"<"2"<..: 2 2 2 2 2 2 2 4 4 4 ...
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183 $ age : num 118 484 664 1004 1231 ...
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184 $ circumference: num 30 58 87 115 120 142 145 33 69 111 ...
185 - attr(*, "formula")=Class 'formula' length 3 circumference ~ age | Tree
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186 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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187 - attr(*, "labels")=List of 2
188 ..$ x: chr "Time since December 31, 1968"
189 ..$ y: chr "Trunk circumference"
190 - attr(*, "units")=List of 2
191 ..$ x: chr "(days)"
192 ..$ y: chr "(mm)"
193
194 ** structure of dataset OrchardSprays
195 'data.frame': 64 obs. of 4 variables:
196 $ decrease : num 57 95 8 69 92 90 15 2 84 6 ...
197 $ rowpos : num 1 2 3 4 5 6 7 8 1 2 ...
198 $ colpos : num 1 1 1 1 1 1 1 1 2 2 ...
199 $ treatment: Factor w/ 8 levels "A","B","C","D",..: 4 5 2 8 7 6 3 1 3 2 ...
200
201 ** structure of dataset PlantGrowth
202 'data.frame': 30 obs. of 2 variables:
203 $ weight: num 4.17 5.58 5.18 6.11 4.5 4.61 5.17 4.53 5.33 5.14 ...
204 $ group : Factor w/ 3 levels "ctrl","trt1",..: 1 1 1 1 1 1 1 1 1 1 ...
205
206 ** structure of dataset Puromycin
207 'data.frame': 23 obs. of 3 variables:
208 $ conc : num 0.02 0.02 0.06 0.06 0.11 0.11 0.22 0.22 0.56 0.56 ...
209 $ rate : num 76 47 97 107 123 139 159 152 191 201 ...
210 $ state: Factor w/ 2 levels "treated","untreated": 1 1 1 1 1 1 1 1 1 1 ...
211 - attr(*, "reference")= chr "A1.3, p. 269"
212
213 ** structure of dataset Seatbelts
214 mts [1:192, 1:8] 107 97 102 87 119 106 110 106 107 134 ...
215 - attr(*, "dimnames")=List of 2
216 ..$ : NULL
217 ..$ : chr [1:8] "DriversKilled" "drivers" "front" "rear" ...
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218 - attr(*, "tsp")= num [1:3] 1969 1985 12
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219 - attr(*, "class")= chr [1:2] "mts" "ts"
220
221 ** structure of dataset Theoph
222 Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 132 obs. of 5 variables:
223 $ Subject: Ord.factor w/ 12 levels "6"<"7"<"8"<"11"<..: 11 11 11 11 11 11 11 11 11 11 ...
224 $ Wt : num 79.6 79.6 79.6 79.6 79.6 79.6 79.6 79.6 79.6 79.6 ...
225 $ Dose : num 4.02 4.02 4.02 4.02 4.02 4.02 4.02 4.02 4.02 4.02 ...
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226 $ Time : num 0 0.25 0.57 1.12 2.02 ...
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227 $ conc : num 0.74 2.84 6.57 10.5 9.66 8.58 8.36 7.47 6.89 5.94 ...
228 - attr(*, "formula")=Class 'formula' length 3 conc ~ Time | Subject
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229 .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
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230 - attr(*, "labels")=List of 2
231 ..$ x: chr "Time since drug administration"
232 ..$ y: chr "Theophylline concentration in serum"
233 - attr(*, "units")=List of 2
234 ..$ x: chr "(hr)"
235 ..$ y: chr "(mg/l)"
236
237 ** structure of dataset Titanic
238 table [1:4, 1:2, 1:2, 1:2] 0 0 35 0 0 0 17 0 118 154 ...
239 - attr(*, "dimnames")=List of 4
240 ..$ Class : chr [1:4] "1st" "2nd" "3rd" "Crew"
241 ..$ Sex : chr [1:2] "Male" "Female"
242 ..$ Age : chr [1:2] "Child" "Adult"
243 ..$ Survived: chr [1:2] "No" "Yes"
244
245 ** structure of dataset ToothGrowth
246 'data.frame': 60 obs. of 3 variables:
247 $ len : num 4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ...
248 $ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ...
249 $ dose: num 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ...
250
251 ** structure of dataset UCBAdmissions
252 table [1:2, 1:2, 1:6] 512 313 89 19 353 207 17 8 120 205 ...
253 - attr(*, "dimnames")=List of 3
254 ..$ Admit : chr [1:2] "Admitted" "Rejected"
255 ..$ Gender: chr [1:2] "Male" "Female"
256 ..$ Dept : chr [1:6] "A" "B" "C" "D" ...
257
258 ** structure of dataset UKDriverDeaths
259 Time-Series [1:192] from 1969 to 1985: 1687 1508 1507 1385 1632 ...
260
261 ** structure of dataset UKgas
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262 Time-Series [1:108] from 1960 to 1987: 160.1 129.7 84.8 120.1 160.1 ...
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263
264 ** structure of dataset USAccDeaths
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265 Time-Series [1:72] from 1973 to 1979: 9007 8106 8928 9137 10017 ...
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266
267 ** structure of dataset USArrests
268 'data.frame': 50 obs. of 4 variables:
269 $ Murder : num 13.2 10 8.1 8.8 9 7.9 3.3 5.9 15.4 17.4 ...
270 $ Assault : int 236 263 294 190 276 204 110 238 335 211 ...
271 $ UrbanPop: int 58 48 80 50 91 78 77 72 80 60 ...
272 $ Rape : num 21.2 44.5 31 19.5 40.6 38.7 11.1 15.8 31.9 25.8 ...
273
274 ** structure of dataset USJudgeRatings
275 'data.frame': 43 obs. of 12 variables:
276 $ CONT: num 5.7 6.8 7.2 6.8 7.3 6.2 10.6 7 7.3 8.2 ...
277 $ INTG: num 7.9 8.9 8.1 8.8 6.4 8.8 9 5.9 8.9 7.9 ...
278 $ DMNR: num 7.7 8.8 7.8 8.5 4.3 8.7 8.9 4.9 8.9 6.7 ...
279 $ DILG: num 7.3 8.5 7.8 8.8 6.5 8.5 8.7 5.1 8.7 8.1 ...
280 $ CFMG: num 7.1 7.8 7.5 8.3 6 7.9 8.5 5.4 8.6 7.9 ...
281 $ DECI: num 7.4 8.1 7.6 8.5 6.2 8 8.5 5.9 8.5 8 ...
282 $ PREP: num 7.1 8 7.5 8.7 5.7 8.1 8.5 4.8 8.4 7.9 ...
283 $ FAMI: num 7.1 8 7.5 8.7 5.7 8 8.5 5.1 8.4 8.1 ...
284 $ ORAL: num 7.1 7.8 7.3 8.4 5.1 8 8.6 4.7 8.4 7.7 ...
285 $ WRIT: num 7 7.9 7.4 8.5 5.3 8 8.4 4.9 8.5 7.8 ...
286 $ PHYS: num 8.3 8.5 7.9 8.8 5.5 8.6 9.1 6.8 8.8 8.5 ...
287 $ RTEN: num 7.8 8.7 7.8 8.7 4.8 8.6 9 5 8.8 7.9 ...
288
289 ** structure of dataset USPersonalExpenditure
290 num [1:5, 1:5] 22.2 10.5 3.53 1.04 0.341 44.5 15.5 5.76 1.98 0.974 ...
291 - attr(*, "dimnames")=List of 2
292 ..$ : chr [1:5] "Food and Tobacco" "Household Operation" "Medical and Health" "Personal Care" ...
293 ..$ : chr [1:5] "1940" "1945" "1950" "1955" ...
294
295 ** structure of dataset VADeaths
296 num [1:5, 1:4] 11.7 18.1 26.9 41 66 8.7 11.7 20.3 30.9 54.3 ...
297 - attr(*, "dimnames")=List of 2
298 ..$ : chr [1:5] "50-54" "55-59" "60-64" "65-69" ...
299 ..$ : chr [1:4] "Rural Male" "Rural Female" "Urban Male" "Urban Female"
300
301 ** structure of dataset WWWusage
302 Time-Series [1:100] from 1 to 100: 88 84 85 85 84 85 83 85 88 89 ...
303
304 ** structure of dataset WorldPhones
305 num [1:7, 1:7] 45939 60423 64721 68484 71799 ...
306 - attr(*, "dimnames")=List of 2
307 ..$ : chr [1:7] "1951" "1956" "1957" "1958" ...
308 ..$ : chr [1:7] "N.Amer" "Europe" "Asia" "S.Amer" ...
309
310 ** structure of dataset ability.cov
311 List of 3
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312 $ cov : num [1:6, 1:6] 24.64 5.99 33.52 6.02 20.75 ...
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313 ..- attr(*, "dimnames")=List of 2
314 .. ..$ : chr [1:6] "general" "picture" "blocks" "maze" ...
315 .. ..$ : chr [1:6] "general" "picture" "blocks" "maze" ...
316 $ center: num [1:6] 0 0 0 0 0 0
317 $ n.obs : num 112
318
319 ** structure of dataset airmiles
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320 Time-Series [1:24] from 1937 to 1960: 412 480 683 1052 1385 ...
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321
322 ** structure of dataset airquality
323 'data.frame': 153 obs. of 6 variables:
324 $ Ozone : int 41 36 12 18 NA 28 23 19 8 NA ...
325 $ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 ...
326 $ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ...
327 $ Temp : int 67 72 74 62 56 66 65 59 61 69 ...
328 $ Month : int 5 5 5 5 5 5 5 5 5 5 ...
329 $ Day : int 1 2 3 4 5 6 7 8 9 10 ...
330
331 ** structure of dataset anscombe
332 'data.frame': 11 obs. of 8 variables:
333 $ x1: num 10 8 13 9 11 14 6 4 12 7 ...
334 $ x2: num 10 8 13 9 11 14 6 4 12 7 ...
335 $ x3: num 10 8 13 9 11 14 6 4 12 7 ...
336 $ x4: num 8 8 8 8 8 8 8 19 8 8 ...
337 $ y1: num 8.04 6.95 7.58 8.81 8.33 ...
338 $ y2: num 9.14 8.14 8.74 8.77 9.26 8.1 6.13 3.1 9.13 7.26 ...
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339 $ y3: num 7.46 6.77 12.74 7.11 7.81 ...
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340 $ y4: num 6.58 5.76 7.71 8.84 8.47 7.04 5.25 12.5 5.56 7.91 ...
341
342 ** structure of dataset attenu
343 'data.frame': 182 obs. of 5 variables:
344 $ event : num 1 2 2 2 2 2 2 2 2 2 ...
345 $ mag : num 7 7.4 7.4 7.4 7.4 7.4 7.4 7.4 7.4 7.4 ...
346 $ station: Factor w/ 117 levels "1008","1011",..: 24 13 15 68 39 74 22 1 8 55 ...
347 $ dist : num 12 148 42 85 107 109 156 224 293 359 ...
348 $ accel : num 0.359 0.014 0.196 0.135 0.062 0.054 0.014 0.018 0.01 0.004 ...
349
350 ** structure of dataset attitude
351 'data.frame': 30 obs. of 7 variables:
352 $ rating : num 43 63 71 61 81 43 58 71 72 67 ...
353 $ complaints: num 51 64 70 63 78 55 67 75 82 61 ...
354 $ privileges: num 30 51 68 45 56 49 42 50 72 45 ...
355 $ learning : num 39 54 69 47 66 44 56 55 67 47 ...
356 $ raises : num 61 63 76 54 71 54 66 70 71 62 ...
357 $ critical : num 92 73 86 84 83 49 68 66 83 80 ...
358 $ advance : num 45 47 48 35 47 34 35 41 31 41 ...
359
360 ** structure of dataset austres
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361 Time-Series [1:89] from 1971 to 1993: 13067 13130 13198 13254 13304 ...
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362
363 ** structure of dataset beaver1
364 'data.frame': 114 obs. of 4 variables:
365 $ day : num 346 346 346 346 346 346 346 346 346 346 ...
366 $ time : num 840 850 900 910 920 930 940 950 1000 1010 ...
367 $ temp : num 36.3 36.3 36.4 36.4 36.5 ...
368 $ activ: num 0 0 0 0 0 0 0 0 0 0 ...
369
370 ** structure of dataset beaver2
371 'data.frame': 100 obs. of 4 variables:
372 $ day : num 307 307 307 307 307 307 307 307 307 307 ...
373 $ time : num 930 940 950 1000 1010 1020 1030 1040 1050 1100 ...
374 $ temp : num 36.6 36.7 36.9 37.1 37.2 ...
375 $ activ: num 0 0 0 0 0 0 0 0 0 0 ...
376
377 ** structure of dataset cars
378 'data.frame': 50 obs. of 2 variables:
379 $ speed: num 4 4 7 7 8 9 10 10 10 11 ...
380 $ dist : num 2 10 4 22 16 10 18 26 34 17 ...
381
382 ** structure of dataset chickwts
383 'data.frame': 71 obs. of 2 variables:
384 $ weight: num 179 160 136 227 217 168 108 124 143 140 ...
385 $ feed : Factor w/ 6 levels "casein","horsebean",..: 2 2 2 2 2 2 2 2 2 2 ...
386
387 ** structure of dataset co2
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388 Time-Series [1:468] from 1959 to 1998: 315 316 316 318 318 ...
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389
390 ** structure of dataset crimtab
391 'table' int [1:42, 1:22] 0 0 0 0 0 0 1 0 0 0 ...
392 - attr(*, "dimnames")=List of 2
393 ..$ : chr [1:42] "9.4" "9.5" "9.6" "9.7" ...
394 ..$ : chr [1:22] "142.24" "144.78" "147.32" "149.86" ...
395
396 ** structure of dataset discoveries
397 Time-Series [1:100] from 1860 to 1959: 5 3 0 2 0 3 2 3 6 1 ...
398
399 ** structure of dataset esoph
400 'data.frame': 88 obs. of 5 variables:
401 $ agegp : Ord.factor w/ 6 levels "25-34"<"35-44"<..: 1 1 1 1 1 1 1 1 1 1 ...
402 $ alcgp : Ord.factor w/ 4 levels "0-39g/day"<"40-79"<..: 1 1 1 1 2 2 2 2 3 3 ...
403 $ tobgp : Ord.factor w/ 4 levels "0-9g/day"<"10-19"<..: 1 2 3 4 1 2 3 4 1 2 ...
404 $ ncases : num 0 0 0 0 0 0 0 0 0 0 ...
405 $ ncontrols: num 40 10 6 5 27 7 4 7 2 1 ...
406
407 ** structure of dataset euro
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408 Named num [1:11] 13.76 40.34 1.96 166.39 5.95 ...
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409 - attr(*, "names")= chr [1:11] "ATS" "BEF" "DEM" "ESP" ...
410
411 ** structure of dataset euro.cross
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412 num [1:11, 1:11] 1 0.3411 7.0355 0.0827 2.3143 ...
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413 - attr(*, "dimnames")=List of 2
414 ..$ : chr [1:11] "ATS" "BEF" "DEM" "ESP" ...
415 ..$ : chr [1:11] "ATS" "BEF" "DEM" "ESP" ...
416
417 ** structure of dataset eurodist
418 Class 'dist' atomic [1:210] 3313 2963 3175 3339 2762 ...
419 ..- attr(*, "Size")= num 21
420 ..- attr(*, "Labels")= chr [1:21] "Athens" "Barcelona" "Brussels" "Calais" ...
421
422 ** structure of dataset faithful
423 'data.frame': 272 obs. of 2 variables:
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424 $ eruptions: num 3.6 1.8 3.33 2.28 4.53 ...
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425 $ waiting : num 79 54 74 62 85 55 88 85 51 85 ...
426
427 ** structure of dataset fdeaths
428 Time-Series [1:72] from 1974 to 1980: 901 689 827 677 522 406 441 393 387 582 ...
429
430 ** structure of dataset freeny
431 'data.frame': 39 obs. of 5 variables:
432 $ y : Time-Series from 1962 to 1972: 8.79 8.79 8.81 8.81 8.91 ...
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433 $ lag.quarterly.revenue: num 8.8 8.79 8.79 8.81 8.81 ...
434 $ price.index : num 4.71 4.7 4.69 4.69 4.64 ...
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435 $ income.level : num 5.82 5.83 5.83 5.84 5.85 ...
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436 $ market.potential : num 13 13 13 13 13 ...
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437
438 ** structure of dataset freeny.x
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439 num [1:39, 1:4] 8.8 8.79 8.79 8.81 8.81 ...
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440 - attr(*, "dimnames")=List of 2
441 ..$ : NULL
442 ..$ : chr [1:4] "lag quarterly revenue" "price index" "income level" "market potential"
443
444 ** structure of dataset freeny.y
445 Time-Series [1:39] from 1962 to 1972: 8.79 8.79 8.81 8.81 8.91 ...
446
447 ** structure of dataset infert
448 'data.frame': 248 obs. of 8 variables:
449 $ education : Factor w/ 3 levels "0-5yrs","6-11yrs",..: 1 1 1 1 2 2 2 2 2 2 ...
450 $ age : num 26 42 39 34 35 36 23 32 21 28 ...
451 $ parity : num 6 1 6 4 3 4 1 2 1 2 ...
452 $ induced : num 1 1 2 2 1 2 0 0 0 0 ...
453 $ case : num 1 1 1 1 1 1 1 1 1 1 ...
454 $ spontaneous : num 2 0 0 0 1 1 0 0 1 0 ...
455 $ stratum : int 1 2 3 4 5 6 7 8 9 10 ...
456 $ pooled.stratum: num 3 1 4 2 32 36 6 22 5 19 ...
457
458 ** structure of dataset iris
459 'data.frame': 150 obs. of 5 variables:
460 $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
461 $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
462 $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
463 $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
464 $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
465
466 ** structure of dataset iris3
467 num [1:50, 1:4, 1:3] 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
468 - attr(*, "dimnames")=List of 3
469 ..$ : NULL
470 ..$ : chr [1:4] "Sepal L." "Sepal W." "Petal L." "Petal W."
471 ..$ : chr [1:3] "Setosa" "Versicolor" "Virginica"
472
473 ** structure of dataset islands
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474 Named num [1:48] 11506 5500 16988 2968 16 ...
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475 - attr(*, "names")= chr [1:48] "Africa" "Antarctica" "Asia" "Australia" ...
476
477 ** structure of dataset ldeaths
478 Time-Series [1:72] from 1974 to 1980: 3035 2552 2704 2554 2014 ...
479
480 ** structure of dataset lh
481 Time-Series [1:48] from 1 to 48: 2.4 2.4 2.4 2.2 2.1 1.5 2.3 2.3 2.5 2 ...
482
483 ** structure of dataset longley
484 'data.frame': 16 obs. of 7 variables:
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485 $ GNP.deflator: num 83 88.5 88.2 89.5 96.2 ...
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486 $ GNP : num 234 259 258 285 329 ...
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487 $ Unemployed : num 236 232 368 335 210 ...
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488 $ Armed.Forces: num 159 146 162 165 310 ...
489 $ Population : num 108 109 110 111 112 ...
490 $ Year : int 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 ...
491 $ Employed : num 60.3 61.1 60.2 61.2 63.2 ...
492
493 ** structure of dataset lynx
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494 Time-Series [1:114] from 1821 to 1934: 269 321 585 871 1475 ...
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495
496 ** structure of dataset mdeaths
497 Time-Series [1:72] from 1974 to 1980: 2134 1863 1877 1877 1492 ...
498
499 ** structure of dataset morley
500 'data.frame': 100 obs. of 3 variables:
501 $ Expt : int 1 1 1 1 1 1 1 1 1 1 ...
502 $ Run : int 1 2 3 4 5 6 7 8 9 10 ...
503 $ Speed: int 850 740 900 1070 930 850 950 980 980 880 ...
504
505 ** structure of dataset mtcars
506 'data.frame': 32 obs. of 11 variables:
507 $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
508 $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
509 $ disp: num 160 160 108 258 360 ...
510 $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
511 $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
512 $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
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513 $ qsec: num 16.5 17 18.6 19.4 17 ...
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514 $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
515 $ am : num 1 1 1 0 0 0 0 0 0 0 ...
516 $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
517 $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
518
519 ** structure of dataset nhtemp
520 Time-Series [1:60] from 1912 to 1971: 49.9 52.3 49.4 51.1 49.4 47.9 49.8 50.9 49.3 51.9 ...
521
522 ** structure of dataset nottem
523 Time-Series [1:240] from 1920 to 1940: 40.6 40.8 44.4 46.7 54.1 58.5 57.7 56.4 54.3 50.5 ...
524
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525 ** structure of dataset occupationalStatus
526 'table' int [1:8, 1:8] 50 16 12 11 2 12 0 0 19 40 ...
527 - attr(*, "dimnames")=List of 2
528 ..$ origin : chr [1:8] "1" "2" "3" "4" ...
529 ..$ destination: chr [1:8] "1" "2" "3" "4" ...
530
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531 ** structure of dataset precip
532 Named num [1:70] 67 54.7 7 48.5 14 17.2 20.7 13 43.4 40.2 ...
533 - attr(*, "names")= chr [1:70] "Mobile" "Juneau" "Phoenix" "Little Rock" ...
534
535 ** structure of dataset presidents
536 Time-Series [1:120] from 1945 to 1975: NA 87 82 75 63 50 43 32 35 60 ...
537
538 ** structure of dataset pressure
539 'data.frame': 19 obs. of 2 variables:
540 $ temperature: num 0 20 40 60 80 100 120 140 160 180 ...
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541 $ pressure : num 0.0002 0.0012 0.006 0.03 0.09 0.27 0.75 1.85 4.2 8.8 ...
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542
543 ** structure of dataset quakes
544 'data.frame': 1000 obs. of 5 variables:
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545 $ lat : num -20.4 -20.6 -26 -18 -20.4 ...
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546 $ long : num 182 181 184 182 182 ...
547 $ depth : int 562 650 42 626 649 195 82 194 211 622 ...
548 $ mag : num 4.8 4.2 5.4 4.1 4 4 4.8 4.4 4.7 4.3 ...
549 $ stations: int 41 15 43 19 11 12 43 15 35 19 ...
550
551 ** structure of dataset randu
552 'data.frame': 400 obs. of 3 variables:
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553 $ x: num 0.000031 0.044495 0.82244 0.322291 0.393595 ...
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554 $ y: num 0.000183 0.155732 0.873416 0.648545 0.826873 ...
555 $ z: num 0.000824 0.533939 0.838542 0.990648 0.418881 ...
556
557 ** structure of dataset rivers
558 num [1:141] 735 320 325 392 524 ...
559
560 ** structure of dataset rock
561 'data.frame': 48 obs. of 4 variables:
562 $ area : int 4990 7002 7558 7352 7943 7979 9333 8209 8393 6425 ...
563 $ peri : num 2792 3893 3931 3869 3949 ...
564 $ shape: num 0.0903 0.1486 0.1833 0.1171 0.1224 ...
565 $ perm : num 6.3 6.3 6.3 6.3 17.1 17.1 17.1 17.1 119 119 ...
566
567 ** structure of dataset sleep
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568 'data.frame': 20 obs. of 3 variables:
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569 $ extra: num 0.7 -1.6 -0.2 -1.2 -0.1 3.4 3.7 0.8 0 2 ...
570 $ group: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...
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571 $ ID : Factor w/ 10 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
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572
573 ** structure of dataset stack.loss
574 num [1:21] 42 37 37 28 18 18 19 20 15 14 ...
575
576 ** structure of dataset stack.x
577 num [1:21, 1:3] 80 80 75 62 62 62 62 62 58 58 ...
578 - attr(*, "dimnames")=List of 2
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579 ..$ : NULL
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580 ..$ : chr [1:3] "Air.Flow" "Water.Temp" "Acid.Conc."
581
582 ** structure of dataset stackloss
583 'data.frame': 21 obs. of 4 variables:
584 $ Air.Flow : num 80 80 75 62 62 62 62 62 58 58 ...
585 $ Water.Temp: num 27 27 25 24 22 23 24 24 23 18 ...
586 $ Acid.Conc.: num 89 88 90 87 87 87 93 93 87 80 ...
587 $ stack.loss: num 42 37 37 28 18 18 19 20 15 14 ...
588
589 ** structure of dataset state.abb
590 chr [1:50] "AL" "AK" "AZ" "AR" "CA" "CO" "CT" "DE" "FL" ...
591
592 ** structure of dataset state.area
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593 num [1:50] 51609 589757 113909 53104 158693 ...
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594
595 ** structure of dataset state.center
596 List of 2
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597 $ x: num [1:50] -86.8 -127.2 -111.6 -92.3 -119.8 ...
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598 $ y: num [1:50] 32.6 49.2 34.2 34.7 36.5 ...
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599
600 ** structure of dataset state.division
601 Factor w/ 9 levels "New England",..: 4 9 8 5 9 8 1 3 3 3 ...
602
603 ** structure of dataset state.name
604 chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" "California" ...
605
606 ** structure of dataset state.region
607 Factor w/ 4 levels "Northeast","South",..: 2 4 4 2 4 4 1 2 2 2 ...
608
609 ** structure of dataset state.x77
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610 num [1:50, 1:8] 3615 365 2212 2110 21198 ...
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611 - attr(*, "dimnames")=List of 2
612 ..$ : chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" ...
613 ..$ : chr [1:8] "Population" "Income" "Illiteracy" "Life Exp" ...
614
615 ** structure of dataset sunspot.month
616 Time-Series [1:2988] from 1749 to 1998: 58 62.6 70 55.7 85 83.5 94.8 66.3 75.9 75.5 ...
617
618 ** structure of dataset sunspot.year
619 Time-Series [1:289] from 1700 to 1988: 5 11 16 23 36 58 29 20 10 8 ...
620
621 ** structure of dataset sunspots
622 Time-Series [1:2820] from 1749 to 1984: 58 62.6 70 55.7 85 83.5 94.8 66.3 75.9 75.5 ...
623
624 ** structure of dataset swiss
625 'data.frame': 47 obs. of 6 variables:
626 $ Fertility : num 80.2 83.1 92.5 85.8 76.9 76.1 83.8 92.4 82.4 82.9 ...
627 $ Agriculture : num 17 45.1 39.7 36.5 43.5 35.3 70.2 67.8 53.3 45.2 ...
628 $ Examination : int 15 6 5 12 17 9 16 14 12 16 ...
629 $ Education : int 12 9 5 7 15 7 7 8 7 13 ...
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630 $ Catholic : num 9.96 84.84 93.4 33.77 5.16 ...
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631 $ Infant.Mortality: num 22.2 22.2 20.2 20.3 20.6 26.6 23.6 24.9 21 24.4 ...
632
633 ** structure of dataset treering
634 Time-Series [1:7980] from -6000 to 1979: 1.34 1.08 1.54 1.32 1.41 ...
635
636 ** structure of dataset trees
637 'data.frame': 31 obs. of 3 variables:
638 $ Girth : num 8.3 8.6 8.8 10.5 10.7 10.8 11 11 11.1 11.2 ...
639 $ Height: num 70 65 63 72 81 83 66 75 80 75 ...
640 $ Volume: num 10.3 10.3 10.2 16.4 18.8 19.7 15.6 18.2 22.6 19.9 ...
641
642 ** structure of dataset uspop
643 Time-Series [1:19] from 1790 to 1970: 3.93 5.31 7.24 9.64 12.9 17.1 23.2 31.4 39.8 50.2 ...
644
645 ** structure of dataset volcano
646 num [1:87, 1:61] 100 101 102 103 104 105 105 106 107 108 ...
647
648 ** structure of dataset warpbreaks
649 'data.frame': 54 obs. of 3 variables:
650 $ breaks : num 26 30 54 25 70 52 51 26 67 18 ...
651 $ wool : Factor w/ 2 levels "A","B": 1 1 1 1 1 1 1 1 1 1 ...
652 $ tension: Factor w/ 3 levels "L","M","H": 1 1 1 1 1 1 1 1 1 2 ...
653
654 ** structure of dataset women
655 'data.frame': 15 obs. of 2 variables:
656 $ height: num 58 59 60 61 62 63 64 65 66 67 ...
657 $ weight: num 115 117 120 123 126 129 132 135 139 142 ...
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658 >
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