README
character
12
This S dump contains 22 data sets from the
book Visualizing Data published by
Hobart Press (books@hobart.com).
The dump was created by data.dump()
and can be read back into S by data.restore().
The name of each S data set is the name of
the data set used in the book. To find the
description of the data set in the book look
under the entry - data, name - in the index.
For example, one data set is barley.
To find the description of barley, look
in the index under the entry - data, barley.
Playfair
structure
3
.Data
list
2
population
numeric
22
60
63
75
80
80
80
90
120
130
140
145
160
180
200
210
220
250
255
380
690
900
1100
diameter
numeric
22
9.1440000000000001
9.652000000000001
10.16
10.667999999999999
10.16
11.43
12.192
14.224
14.478
14.731999999999999
14.731999999999999
15.24
15.748000000000001
16.256
16.256
17.271999999999998
18.795999999999999
19.304000000000002
23.876000000000001
31.496000000000002
35.052
39.624000000000002
row.names
character
22
Edinburgh
Stockholm
Florence
Genoa
Turin
Warsaw
Copenhagen
Lisbon
Palermo
Madrid
Berlin
Rome
Petersburgh
Venice
Dublin
Amsterdam
Moscow
Vienna
Naples
Paris
Constantinople
London
class
character
1
data.frame
animal
structure
3
.Data
list
3
name
structure
3
.Data
integer
64
36
37
40
8
41
57
19
30
61
27
38
22
50
14
16
52
21
59
5
2
31
39
56
23
45
43
60
48
20
13
6
42
64
53
51
49
54
26
35
29
55
24
28
34
11
18
46
47
44
12
15
32
25
58
3
7
4
33
1
63
62
17
9
10
.Label
character
64
African Elephant
African Giant Pouched Rat
Allosaurus
Anatosaurus
Arctic Ground Squirrel
Artic Fox
Asian Elephant
Big Brown Bat
Blue Whale
Brachiosaurus
Brazilian Tapir
Camptosaurus
Cat
Chinchilla
Cow
Desert Hedgehog
Diplodocus
Donkey
Eastern American Mole
Echidna
European Hedgehog
Galago
Genet
Giant Armadillo
Giraffe
Goat
Golden Hamster
Gray Seal
Gray Wolf
Ground Squirrel
Guinea Pig
Horse
Iguanodon
Jaguar
Kangaroo
Lesser Short-tailed Shrew
Little Brown Bat
Mole Rate
Mountain Beaver
Mouse
Musk Shrew
Nine-banded Armadillo
North American Opossum
Okapi
Phalanger
Pig
Protoceratops
Rabbit
Raccoon
Rat
Red Fox
Rock Hyrax (a)
Rock Hyrax (b)
Roe Deer
Sheep
Slow Loris
Star Nosed Mole
Stegosaurus
Tenrec
Tree Hyrax
Tree Shrew
Triceratops
Tyrannosaurus
Water Opossum
class
character
1
factor
body.weight
numeric
64
5
10
23
23
48
60
75
101
104
120
122
200
280
425
550
750
785
900
920
1000
1040
1350
1400
1410
1620
1700
2000
2500
3000
3300
3385
3500
3500
3600
4235
4288
14830
27660
35000
36330
55500
60000
85000
100000
160000
187100
192000
200000
250000
400000
465000
521000
529000
2000000
2300000
2547000
3400000
5000000
6654000
7700000
9400000
11700000
58059000
87000000
brain.weight
numeric
64
0.14000000000000001
0.25
0.29999999999999999
0.40000000000000002
0.33000000000000002
1
1.2
4
2.5
1
3
5
1.8999999999999999
6.4000000000000004
2.3999999999999999
12.300000000000001
3.5
2.6000000000000001
5.7000000000000002
6.5999999999999996
5.5
8.0999999999999996
12.5
17.5
11.4
6.2999999999999998
12.300000000000001
12.1
25
25.600000000000001
44.5
10.800000000000001
3.8999999999999999
21
50.399999999999999
39.200000000000003
98.200000000000003
115
56
119.5
175
81
325
157
169
419
180
30
490
46
423
655
680
56
335
4603
300
250
5712
404
140
100
6800
309
row.names
character
64
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
class
character
1
data.frame
barley
structure
3
.Data
list
4
yield
numeric
120
27
48.866669999999999
27.433340000000001
39.933329999999998
32.966670000000001
28.966670000000001
43.066659999999999
55.200000000000003
28.766670000000001
38.133330000000001
29.133330000000001
29.66667
35.133330000000001
47.333329999999997
25.766670000000001
40.466670000000001
29.66667
25.699999999999999
39.899999999999999
50.233330000000002
26.133330000000001
41.333329999999997
23.033329999999999
26.300000000000001
36.566659999999999
63.833300000000001
43.766669999999998
46.933329999999998
29.766670000000001
33.933329999999998
43.266669999999998
58.100000000000001
28.699999999999999
45.666670000000003
32.166670000000003
33.600000000000001
36.600000000000001
65.7667
30.366669999999999
48.566659999999999
24.933340000000001
28.100000000000001
32.766669999999998
48.566659999999999
29.866669999999999
41.600000000000001
34.700000000000003
32
24.66667
46.766669999999998
22.600000000000001
44.100000000000001
19.699999999999999
33.066659999999999
39.299999999999997
58.799999999999997
29.466670000000001
49.866669999999999
34.466670000000001
31.600000000000001
26.899999999999999
33.466670000000001
34.366660000000003
32.966670000000001
22.133330000000001
22.566669999999998
36.799999999999997
37.733330000000002
35.133330000000001
26.16667
14.43333
25.866669999999999
27.433340000000001
38.5
35.033329999999999
20.633330000000001
16.633330000000001
22.233329999999999
26.800000000000001
37.399999999999999
38.833329999999997
32.066659999999999
32.233330000000002
22.466670000000001
29.066669999999998
49.2333
46.633330000000001
41.833329999999997
20.633330000000001
30.600000000000001
26.433340000000001
42.200000000000003
43.533340000000003
34.333329999999997
19.466670000000001
22.699999999999999
25.566669999999998
44.700000000000003
47
30.533329999999999
19.899999999999999
22.5
28.066669999999998
36.033329999999999
43.200000000000003
25.233329999999999
26.766670000000001
31.366669999999999
30
41.266669999999998
44.233330000000002
32.133330000000001
15.23333
27.366669999999999
38
58.166670000000003
47.166670000000003
35.899999999999999
20.66667
29.33333
variety
structure
3
.Data
integer
120
3
3
3
3
3
3
7
7
7
7
7
7
1
1
1
1
1
1
5
5
5
5
5
5
10
10
10
10
10
10
8
8
8
8
8
8
2
2
2
2
2
2
6
6
6
6
6
6
4
4
4
4
4
4
9
9
9
9
9
9
3
3
3
3
3
3
7
7
7
7
7
7
1
1
1
1
1
1
5
5
5
5
5
5
10
10
10
10
10
10
8
8
8
8
8
8
2
2
2
2
2
2
6
6
6
6
6
6
4
4
4
4
4
4
9
9
9
9
9
9
.Label
character
10
Svansota
No. 462
Manchuria
No. 475
Velvet
Peatland
Glabron
No. 457
Wisconsin No. 38
Trebi
class
character
2
ordered
factor
year
structure
3
.Data
integer
120
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
.Label
character
2
1932
1931
class
character
2
ordered
factor
site
structure
3
.Data
integer
120
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
3
6
4
5
1
2
.Label
character
6
Grand Rapids
Duluth
University Farm
Morris
Crookston
Waseca
class
character
2
ordered
factor
row.names
character
120
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
class
character
1
data.frame
bin.packing
structure
3
.Data
list
2
empty.space
numeric
275
1.5771269604424727
1.242905970725666
1.3892459682715281
0.63631701286314279
0.44334998737769443
1.5228420823430029
1.0353560455891073
4.5827678535744401
1.3641070442986873
0.84452098154064703
1.3439380004846906
1.9079580165867267
1.0057079791090084
1.0875469461203788
1.0075709818167302
1.1792910027093397
4.4688637400928481
1.1694929550074666
2.4868290414650325
0.44876799803911532
4.1142191923767104
1.2977850534325515
1.2885470232835798
1.1557819891669459
1.2915450334585945
0.83193498797223564
0.4018910079583865
1.0583230248207849
1.6362520260147813
0.70976502179270351
1.3732329638511493
1.1513919771767527
1.4652309591120101
0.55284501361657989
1.3321080166882286
0.92283201649782942
1.2443710645576149
1.3399829899235403
0.89293801643315429
1.5888580157429617
0.56909398992653881
0.55757497176450466
0.93340999450209283
0.71047699381479135
3.0105467986915553
0.56710602736760662
1.2048669981029188
0.59488701752162565
1.3964569333622188
0.84944802411460629
6.7839408209576142
1.0293910503582888
0.80302101459671693
0.94090097934887218
1.2516690593870883
1.0267230260312654
1.1554289968633087
1.49417200786587
0.61118799462301132
0.89066797242382645
1.1670440448220842
0.86472099798886159
0.76116599136844987
1.2171269562595373
1.1517959846148174
0.69378501457288366
0.95631301130188351
1.1806540492854347
0.97764897423278529
1.2886110412258209
0.8572760170144037
1.3879450281413921
1.4433150234838394
0.89489298903970649
1.5550099265664237
0.76370399435428693
6.4154639549049453
1.57099399722077
1.5267080042533423
0.9522969722857646
1.7636959933338492
1.2516319821123421
0.75221902281070585
0.65995001024610211
1.1576830216557743
1.7331429957465772
0.74075001352434033
1.1794960433893811
1.5746929488312809
1.0782059477961665
1.0093599558126263
1.25177096291026
1.200206035937496
6.756915542505074
1.2850650411795055
1.5675679482445046
0.86519903366892614
0.94155198434967335
0.8830599740324786
1.6171840604879282
1.5418330351048608
1.6147329913232724
0.83562999835853247
1.3315160184764177
1.0043619869064977
1.7923899637331382
1.0623550410535461
1.8674689350026457
1.2953959852957204
1.2516510635851845
1.490779033812184
0.85720401487858888
0.93888300232827615
1.7033058918560773
0.83833700639364006
1.6604151012012909
1.465119940823105
1.483548018060538
1.5467109575680484
1.2854160285067344
0.89554101552722709
0.8030999954857827
1.7989959389015693
1.89845803930901
1.0918409882255795
1.0692160120961405
1.866615959938956
1.5568449436629659
1.2241660363842601
1.4283089698763449
1.3002300429156555
1.9670669829101761
1.3335180081731588
1.2384049845197647
1.4545580445304171
1.4805300470490821
1.0464620574751049
1.3436909668475745
1.5757509538059957
1.9497750393841793
1.9714499802747629
1.4235179525919817
1.298208943903064
1.5412450004557741
1.3978409845129112
2.0961389594372117
1.2835479784322492
1.9253318926917091
1.8639370016414489
1.3165500256375251
2.1987739906052219
1.777329023802926
2.28563910970832
2.334373956779662
1.5815089628848829
1.6943900580528117
1.4312640121441753
1.6972819122214371
2.306060159735309
1.8545240379074468
2.2298802089216081
1.8965329809073432
2.0202961355960776
2.0311318741293927
2.0344838840321726
2.0626399454939786
2.1970310625481893
1.7689950829705492
1.9012818932970827
1.4451199664745285
2.2286670417372472
2.5695528226761226
1.6412680168446689
1.7590030724391124
1.6737108815218811
2.3125391378019007
1.6704309733494613
2.1716409891667201
2.5120620224766395
2.0352608619919637
2.3743409580496579
2.40960004510073
1.9698610418659035
2.0566139997342412
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2.0291909906662555
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1.887240992091916
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1.7887550986621739
1.9947010560858771
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2.4385150465585879
2.3921398494212989
2.46031599444545
2.4622258776205976
2.4857599240393746
2.0973931516550182
1.9970649219950329
3.0389600998045156
2.8542698238327331
2.9161631496622871
2.4045538624996459
2.6733040341941248
2.1496078939941241
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2.8623519334943719
2.2540308888226721
2.1547878755965648
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2.0469720068357113
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2.1601709627811569
2.6176090398188063
2.4628318343045295
2.5244468487474512
2.2368071063808084
2.8529979479007173
3.534629968296565
3.0503699670671933
3.2855060390109427
3.455059021277064
2.6742858673751702
3.0920538194528948
2.6897509402392039
2.9117092514237606
3.4505449485504025
3.0462270514762477
2.8453799959790658
3.2173138984442651
3.0642172147269862
2.9417078524235545
2.8157589545806734
3.0005800876754138
3.6745431854390707
2.8490341086456707
3.8709281111038938
3.6341661011454303
2.9119820970327854
3.2975660851725013
3.1530620030866863
2.677820931107052
3.5184577629232958
4.4707998221034861
4.0357256745316521
3.3955289922667276
4.0412577337863826
4.2052976791094272
3.6619431062957641
3.2683710801391337
3.6933021605658953
4.143940981440223
4.2182829342190722
3.8234282105423669
3.2975372027888894
3.8894389531683258
3.7445631880977279
3.5961520578382813
4.0579349945164154
4.0102976408824196
3.4674039170589555
3.5284369046110786
4.2428380215827781
3.7045668719037219
4.100688117741746
3.8038558568745033
3.6826406903600075
number.runs
numeric
275
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
125
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
250
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
500
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
4000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
8000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
16000
32000
32000
32000
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23
24
25
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31
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36
37
38
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41
42
43
44
45
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50
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63
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81
82
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89
90
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100
101
102
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107
108
109
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118
119
120
121
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126
127
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139
140
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145
146
147
148
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152
153
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165
166
167
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255
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16
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190
118
149
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322
44
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269
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314
276
267
272
175
264
175
48
260
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285
187
220
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294
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81
82
213
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253
254
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24
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192
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259
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183
189
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230
259
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112
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224
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238
201
238
14
139
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191
131
223
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11.5
row.names
character
111
1
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
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98
99
100
101
102
103
104
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823
1
2
3
4
5
6
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9
10
11
12
13
14
15
16
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727
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729
730
731
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785
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795
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802
803
804
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807
808
809
810
811
812
813
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815
816
817
818
819
820
821
822
823
class
character
1
data.frame
food.web
structure
3
.Data
list
2
mean.length
single
113
3.130000114440918
2.7100000381469727
2.2999999523162842
2.7400000095367432
2
3.8199999332427979
2.7899999618530273
2.440000057220459
2.8599998950958252
2
2
2.25
2.5
2.4000000953674316
2.3299999237060547
2.1400001049041748
3.559999942779541
2
3
3.2599999904632568
4.6100001335144043
3.690000057220459
2.4000000953674316
2.7000000476837158
2.1600000858306885
2.9300000667572021
2.8900001049041748
1.9600000381469727
3.1400001049041748
5.0199999809265137
3.9000000953674316
3.8599998950958252
1.9299999475479126
2.559999942779541
2.7200000286102295
2.0699999332427979
2.75
2.130000114440918
1.7999999523162842
1.8799999952316284
5.9200000762939453
4.9499998092651367
3.130000114440918
3.630000114440918
2.1400001049041748
4.429999828338623
4.2199997901916504
3.5299999713897705
2.559999942779541
2.440000057220459
3.2799999713897705
2.0799999237060547
1.9500000476837158
2.5799999237060547
2.4600000381469727
2.2200000286102295
3.2899999618530273
4.2800002098083496
2.369999885559082
2.3599998950958252
2
3
3.1600000858306885
1.6699999570846558
1.8500000238418579
2.9300000667572021
3.940000057220459
2.630000114440918
3.619999885559082
2.4900000095367432
5.1500000953674316
3.9500000476837158
2.380000114440918
2.380000114440918
2.75
2.6700000762939453
3.630000114440918
3.1500000953674316
3.4100000858306885
3.3499999046325684
2.7300000190734863
3.7100000381469727
2.4500000476837158
3.6099998950958252
3.6099998950958252
4.0900001525878906
2.9100000858306885
1.9500000476837158
2.8900001049041748
1.8400000333786011
3
2
2.119999885559082
3.3499999046325684
2.5
1.9199999570846558
2
3.5399999618530273
2.5099999904632568
3.3399999141693115
1.6699999570846558
3.9700000286102295
5.5900001525878906
3.1600000858306885
3.6700000762939453
2.4100000858306885
2.5
2.2699999809265137
2.880000114440918
2.130000114440918
2.440000057220459
1.8300000429153442
2.1099998950958252
dimension
structure
3
.Data
integer
113
2
2
1
2
2
2
2
2
2
1
1
1
1
2
2
2
3
2
3
3
3
2
1
3
3
2
3
2
3
3
3
3
2
1
1
2
2
2
2
3
3
3
3
2
1
3
2
2
2
1
2
1
1
2
1
1
2
2
3
3
1
1
1
1
1
1
2
3
2
2
3
3
3
1
3
2
2
2
2
2
2
2
2
2
2
3
2
1
3
1
3
1
1
1
1
1
1
1
1
1
2
3
3
1
1
1
1
1
1
1
1
2
2
.Label
character
3
Two
Mixed
Three
class
character
2
ordered
factor
row.names
character
113
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
class
character
1
data.frame
fusion.time
structure
3
.Data
list
2
time
numeric
78
47.200009999999999
21.999980000000001
20.399989999999999
19.700009999999999
17.399999999999999
14.699999999999999
13.399990000000001
13
12.300000000000001
12.200010000000001
10.300000000000001
9.6999999999999993
9.6999999999999993
9.5
9.0999999999999996
8.9000000000000004
8.9000000000000004
8.4000000000000004
8.09999
7.9000000000000004
7.7999999999999998
6.9000000000000004
6.2999999999999998
6.0999999999999996
5.5999999999999996
4.7000000000000002
4.7000000000000002
4.2999999999999998
4.2000000000000002
3.8999999999999999
3.3999999999999999
3.1000000000000001
3.1000000000000001
2.7000000000000002
2.3999999999999999
2.2999999999999998
2.2999999999999998
2.1000000000000001
2.1000000000000001
2
1.8999999999999999
1.7
1.7
19.700009999999999
16.19998
15.9
15.40002
9.6999999999999993
8.9000000000000004
8.5999999999999996
8.5999999999999996
7.4000000000000004
6.2999999999999998
6.0999999999999996
6
6
5.9000000000000004
4.9000000000000004
4.5999999999999996
3.7999999999999998
3.6000000000000001
3.5
3.2999999999999998
3.2999999999999998
2.8999999999999999
2.7999999999999998
2.7000000000000002
2.3999999999999999
2.2999999999999998
2
1.8
1.7
1.7
1.6000000000000001
1.3999999999999999
1.2
1.1000000000000001
1
nv.vv
structure
3
.Data
integer
78
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
.Label
character
2
NV
VV
class
character
1
factor
row.names
character
78
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
class
character
1
data.frame
ganglion
structure
3
.Data
list
2
area
numeric
14
11.051
13.865
22.513999999999999
32.810000000000002
33.771000000000001
31.094000000000001
53.607999999999997
62.600000000000001
81.063999999999993
66.512
106.873
100.55800000000001
113.325
140.91800000000001
cp.ratio
numeric
14
2.5597584798437221
2.8168341294679626
2.957259209444818
3.4223177332059853
3.4966101694915253
3.7512701817771252
4.5491021946353358
4.6822066822066821
6.85273492286115
6.9825723248518647
10.90625
11.255759007678677
11.104895104895105
18.299625468164795
row.names
character
14
1
2
3
4
5
6
7
8
9
10
11
12
13
14
class
character
1
data.frame
hamster
structure
3
.Data
list
6
lung
numeric
73
0.96950000000000003
1.141003
0.872
0.7399
1.139302
1.1256029999999999
0.36720000000000003
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0.49719999999999998
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0.6532
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0.56130000000000002
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0.622
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1.050003
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0.87390000000000001
0.82599999999999996
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1.177802
1.011903
0.98199999999999998
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0.61899999999999999
0.78490000000000004
0.50919999999999999
0.56869999999999998
1.4364030000000001
1.072503
1.1626030000000001
0.96499999999999997
1.023903
0.3216
1.1653020000000001
0.85319999999999996
0.63539999999999996
0.64890000000000003
0.96199999999999997
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0.98240000000000005
0.95920000000000005
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1.1194029999999999
1.074803
0.93640000000000001
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1.094503
1.140603
0.7722
1.026003
1.4602029999999999
0.8891
1.652102
0.81000000000000005
1.1918029999999999
0.72370000000000001
0.83850000000000002
1.066703
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1.0052030000000001
heart
numeric
73
1.3520019999999999
1.499403
1.2685029999999999
1.270203
1.4962029999999999
1.191403
0.6986
0.41930000000000001
0.41339999999999999
0.52980000000000005
0.60199999999999998
0.42299999999999999
0.51290000000000002
0.57150000000000001
0.51870000000000005
0.54790000000000005
0.50009999999999999
0.94230000000000003
0.79500000000000004
0.50509999999999999
0.59989999999999999
1.034402
0.74460000000000004
0.90229999999999999
0.76280000000000003
0.89810000000000001
1.5094030000000001
0.67230000000000001
0.96040000000000003
0.94830099999999995
1.3692029999999999
1.2080029999999999
1.286003
1.0690029999999999
1.000202
1.116703
0.86980000000000002
0.87909999999999999
0.99319999999999997
0.94840000000000002
1.2746029999999999
1.5450029999999999
1.0789029999999999
0.49869999999999998
1.6300030000000001
1.1439029999999999
0.89400000000000002
1.239403
0.80389999999999995
1.038503
1.1543030000000001
1.490302
1.0950029999999999
1.276303
1.4415020000000001
1.1714020000000001
1.2496020000000001
1.1425019999999999
1.524003
1.3694029999999999
1.791703
1.181203
1.536402
1.8390029999999999
1.6295029999999999
1.086903
1.1765030000000001
1.772203
0.93940000000000001
1.3015030000000001
1.035703
1.046203
1.0150030000000001
liver
numeric
73
8.1854960000000005
8.5445069999999994
6.8230089999999999
9.0675089999999994
9.6219929999999998
9.7432090000000002
2.7266029999999999
1.744202
2.6617030000000002
3.262105
3.6231059999999999
2.0776029999999999
2.8608030000000002
2.8093029999999999
3.602503
2.863604
2.9257010000000001
2.6974040000000001
2.746604
3.1271040000000001
3.4968020000000002
3.1108030000000002
2.6780029999999999
8.3070909999999998
3.7972049999999999
4.8976980000000001
7.4927970000000004
2.6366049999999999
12.80401
5.3908969999999998
8.1258909999999993
7.1872040000000004
7.9245020000000004
4.402304
8.0259049999999998
5.9198950000000004
3.264904
3.6023010000000002
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6.9735990000000001
11.9148
6.5425040000000001
8.1096109999999992
1.6264019999999999
7.0897030000000001
4.0120009999999997
2.6877010000000001
8.7761089999999999
3.4576020000000001
8.3850189999999998
7.531301
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15.4923
10.998810000000001
5.9829030000000003
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5.3614030000000001
12.1655
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12.18871
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8.2657070000000008
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8.8597000000000001
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5.7391949999999996
spleen
numeric
73
0.22550020000000001
0.27049980000000001
0.049999990000000001
0.1129998
0.1198
0.1392999
0.047800009999999997
0.0448
0.056799959999999997
0.075100029999999998
0.070100010000000004
0.038300019999999997
0.074499960000000004
0.055900020000000002
0.060400000000000002
0.068700040000000004
0.078000070000000005
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0.065699939999999998
0.075500010000000006
0.043600050000000001
0.066799940000000002
0.04500005
0.099699969999999999
0.068499920000000006
0.082099969999999994
0.1739001
0.053600019999999998
0.1192998
0.082799940000000002
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0.078399979999999994
0.1193999
0.075200020000000006
0.1056
0.095200010000000002
0.087599990000000003
0.1795998
0.1187
0.1042999
0.1072
0.10620010000000001
0.1424
0.029300030000000001
0.1443999
0.07689994
0.046300000000000001
0.1144998
0.071300080000000002
0.19899990000000001
0.059500009999999999
0.15670000000000001
0.2959
0.16170000000000001
0.1308
0.1283
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0.1043998
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0.089600009999999994
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0.062800060000000005
0.13300010000000001
0.073899930000000003
0.12139999999999999
0.16599990000000001
0.042099989999999997
0.066399990000000006
0.1018999
0.056799959999999997
0.095000080000000001
kidney
numeric
73
1.3480030000000001
1.322103
0.89700100000000005
1.278003
1.415003
1.3405020000000001
0.81989999999999996
0.82240000000000002
1.0697030000000001
0.96009999999999995
1.163503
0.81989999999999996
0.98250000000000004
1.007403
1.0751029999999999
0.95960000000000001
0.95889999999999997
1.0797030000000001
1.010103
1.0798030000000001
1.197603
1.2131019999999999
1.0426029999999999
1.368603
1.0629029999999999
1.011903
1.3171029999999999
1.098303
1.5933029999999999
1.187203
1.3538019999999999
1.4338029999999999
1.6396029999999999
1.2131019999999999
1.5638030000000001
1.258203
1.348203
1.177203
1.316503
1.469303
1.4999020000000001
1.267703
1.4012020000000001
0.82520000000000004
1.288403
1.2271030000000001
0.99390100000000003
1.426202
1.1646030000000001
1.3135030000000001
1.386703
1.3642030000000001
1.4378029999999999
1.339402
1.1359030000000001
1.237903
1.179503
1.1625030000000001
1.393303
1.3234030000000001
1.4783029999999999
1.169303
1.3031029999999999
1.2291030000000001
1.7082029999999999
1.1400030000000001
1.2493030000000001
1.738103
1.030402
1.369103
1.3696029999999999
1.1443019999999999
0.89680000000000004
testes
numeric
73
0.34150019999999998
0.41699999999999998
1.220002
0.8145
1.156803
1.359901
0.77699989999999997
0.93179999999999996
2.0503019999999998
1.518802
1.546403
0.50379980000000002
1.524502
1.7051019999999999
0.94489999999999996
1.5587029999999999
1.6449009999999999
0.90539999999999998
1.486202
1.486202
1.9766030000000001
0.65539990000000004
0.7566001
1.5738030000000001
0.32050000000000001
1.2826029999999999
0.97919999999999996
0.8226
1.7674030000000001
0.63870009999999999
0.49259999999999998
0.83160000000000001
0.76280009999999998
0.58509990000000001
0.89960010000000001
0.66020000000000001
0.43480000000000002
0.74770009999999998
0.98109999999999997
0.5630001
1.4698020000000001
0.47689999999999999
1.068703
0.31679990000000002
0.56319989999999998
0.64539999999999997
0.39929999999999999
0.77170000000000005
1.4088020000000001
1.303803
0.38120009999999999
0.30820029999999998
1.4476039999999999
1.3480030000000001
2.1885029999999999
2.2372030000000001
0.96619999999999995
2.2818019999999999
2.4244029999999999
1.754702
1.486003
1.251603
1.1469009999999999
1.7150030000000001
0.97609999999999997
1.1141019999999999
1.9837009999999999
1.7519020000000001
0.4890002
0.75460000000000005
0.58689990000000003
0.48499999999999999
0.43869999999999998
row.names
character
73
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
class
character
1
data.frame
livestock
structure
3
.Data
list
3
livestock.type
structure
3
.Data
integer
130
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
.Label
character
5
Horses
Sheep
Cattle
Pigs
Poultry
class
character
2
ordered
factor
country
structure
3
.Data
integer
130
1
8
11
13
14
9
24
4
23
16
3
10
12
18
15
2
20
7
21
19
5
6
25
22
26
17
1
8
11
13
14
9
24
4
23
16
3
10
12
18
15
2
20
7
21
19
5
6
25
22
26
17
1
8
11
13
14
9
24
4
23
16
3
10
12
18
15
2
20
7
21
19
5
6
25
22
26
17
1
8
11
13
14
9
24
4
23
16
3
10
12
18
15
2
20
7
21
19
5
6
25
22
26
17
1
8
11
13
14
9
24
4
23
16
3
10
12
18
15
2
20
7
21
19
5
6
25
22
26
17
.Label
character
26
Albania
Norway
Greece
Finland
Sweden
Switzerland
Portugal
Austria
Denmark
Hungary
Belgium
Ireland
Bulgaria
Czechoslovakia
Netherlands
East Germany
Yugoslavia
Italy
Spain
Poland
Romania
United Kingdom
France
West Germany
Turkey
Russia et al.
class
character
2
ordered
factor
count
numeric
130
478000
2536000
3246000
1796000
5131000
2873000
15098000
1719000
23599000
5690000
831000
1922000
6908000
8734000
5241000
971000
11912000
1173000
6303000
4495000
1902000
1954000
16983000
13155000
42200000
5474000
125000
3920000
5108000
3808000
7126000
9317000
22478000
1475000
11711000
12107000
1107000
9035000
1031000
8928000
10254000
687000
19471000
2448000
12464000
11263000
2677000
2071000
11000
7975000
33100000
7867000
484000
11371000
29448000
41096000
49212000
16296000
83033000
7763000
234131000
51356000
29846000
45397000
9903000
137999000
88174000
5571000
67244000
4143000
109244000
42824000
11393000
6188000
59660000
130018000
385000000
65690000
43000
35000
31000
120000
44000
41000
369000
20000
278000
81000
420000
120000
68000
273000
59000
25000
1734000
23000
566000
242000
57000
45000
784000
140000
1556000
573000
914000
326000
123000
11271000
990000
58000
1172000
104000
14346000
2220000
12669000
3183000
3323000
10497000
1210000
1999000
3899000
2811000
17748000
16543000
437000
336000
70093000
32888000
21000000
7384000
row.names
character
130
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
class
character
1
data.frame
melanoma
structure
3
.Data
list
2
year
numeric
37
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
incidence
numeric
37
0.90000000000000002
0.80000000000000004
0.80000000000000004
1.3
1.3999999999999999
1.2
1.7
1.8
1.6000000000000001
1.5
1.5
2
2.5
2.7000000000000002
2.8999999999999999
2.5
3.1000000000000001
2.3999999999999999
2.2000000000000002
2.8999999999999999
2.5
2.6000000000000001
3.2000000000000002
3.7999999999999998
4.2000000000000002
3.8999999999999999
3.7000000000000002
3.2999999999999998
3.7000000000000002
3.8999999999999999
4.0999999999999996
3.7999999999999998
4.7000000000000002
4.4000000000000004
4.7999999999999998
4.7999999999999998
4.7999999999999998
row.names
character
37
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
class
character
1
data.frame
ozone
structure
3
.Data
list
2
yonkers
numeric
132
47
37
45
52
51
22
27
25
55
72
132
106
42
45
80
107
21
50
31
37
19
33
22
45
36
24
88
111
117
31
37
93
106
64
83
97
79
36
51
75
104
107
68
19
67
20
35
30
31
81
119
76
108
85
96
48
60
54
71
50
37
47
71
46
41
49
59
25
45
40
13
46
62
80
39
74
66
82
47
28
44
55
34
60
70
41
96
54
100
44
44
75
86
70
53
36
117
43
27
77
75
87
47
114
66
18
25
14
27
9
16
67
74
74
75
74
42
38
23
50
34
58
35
24
27
17
21
14
32
51
15
21
stamford
numeric
132
66
52
49
64
68
26
86
52
75
87
188
103
82
71
103
240
31
40
47
51
31
47
14
71
61
47
196
131
173
37
47
215
230
69
98
125
94
72
72
125
143
192
122
32
114
32
23
71
38
136
169
152
201
134
206
92
101
119
124
83
60
124
142
124
64
75
103
46
68
87
27
73
59
119
64
111
80
68
24
24
82
100
55
91
87
64
170
86
202
71
85
122
155
80
71
28
212
80
24
80
169
174
141
202
113
38
38
28
52
14
38
94
89
99
150
146
113
66
38
80
80
99
71
42
52
33
38
24
61
108
38
28
row.names
character
132
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
class
character
1
data.frame
polarization
structure
3
.Data
list
2
concentration
numeric
355
9
9
10
12
12
13.5
14
15
15
15
15
15
15.5
15.5
15.5
16
16
16
16
16
17
19
19
19
19
19
19
19
19
19
19
19
19
20
20.5
20.5
21
21
21
22
22
22.5
23
24
24
24
24
24
24.5
25
25
25.5
25.5
25.5
25.5
26.5
26.5
26.5
26.5
26.5
27
27
27.5
27.5
27.5
27.5
29
29
29
29.5
29.5
29.5
30
30
30
30
30.5
30.5
30.5
30.5
30.5
30.5
30.5
30.5
30.5
30.5
31
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
31.5
33
33
33
34
34
34
34.5
34.5
35
35
35.5
35.5
35.5
35.5
35.5
36
36
36
37
37
37
37
37
37.5
37.5
38.5
38.5
39
39
39
39
39
39.5
39.5
39.5
39.5
39.5
40
40
40
40.5
40.5
40.5
40.5
41
41.5
41.5
41.5
41.5
41.5
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
43
43.5
44.5
45
45.5
45.5
45.5
45.5
45.5
45.5
45.5
45.5
45.5
45.5
46
46
46
46.5
46.5
47
47
47
48
48
48.5
48.5
48.5
48.5
48.5
49
49
50.5
50.5
50.5
50.5
50.5
50.5
50.5
51
51
51
51
51
51.5
52
52
52.5
52.5
52.5
54
54
54
55.5
56.5
56.5
56.5
56.5
56.5
56.5
56.5
56.5
57.5
59.5
60
60
61
61
61
62
62
62
62
62
62
62
62
62
62
62.5
62.5
63
63
63
63
63
63.5
64
64.5
64.5
64.5
65
65
66
66
66
66
66.5
66.5
66.5
66.5
66.5
66.5
68.5
68.5
68.5
69
69
69
69.5
69.5
70
70
70
70
70.5
70.5
70.5
71.5
71.5
71.5
72
72.5
73
73.5
73.5
74
75
76
77
77.5
77.5
78
78
78
78
78
78
79.5
80
80
80
80
80.5
80.5
80.5
81
81
81.5
81.5
81.5
82
82
82
82.5
85
85
85.5
85.5
86.5
86.5
89.5
89.5
90
90
90
90
90.5
92
92
92
92
96
98
98
100.5
106
107
108.5
112
116
118.5
118.5
121.5
122.5
babinet
numeric
355
25.899999999999999
24.600000000000001
20.699999999999999
22.5
25.300000000000001
23.899999999999999
25.5
20.600000000000001
20.899999999999999
24.199999999999999
24.300000000000001
24.600000000000001
24.100000000000001
24.199999999999999
25.699999999999999
23.399999999999999
24.100000000000001
24.199999999999999
24.600000000000001
25.5
22.5
22.199999999999999
23.699999999999999
23.899999999999999
23.899999999999999
24
24
24.899999999999999
24.899999999999999
25.100000000000001
25.300000000000001
25.399999999999999
25.600000000000001
25
22.600000000000001
23.199999999999999
21.300000000000001
21.5
24.199999999999999
23.300000000000001
24.699999999999999
24.199999999999999
24
24.300000000000001
24.800000000000001
25.100000000000001
25.300000000000001
25.800000000000001
25.699999999999999
23.100000000000001
23.699999999999999
24.199999999999999
24.800000000000001
25.100000000000001
25.300000000000001
23.300000000000001
23.600000000000001
23.800000000000001
23.899999999999999
25.100000000000001
18
18
22.399999999999999
22.699999999999999
24.100000000000001
24.300000000000001
23.199999999999999
24.699999999999999
24.899999999999999
22.699999999999999
23.5
23.699999999999999
24
24.199999999999999
24.399999999999999
24.5
18
18
20
21.199999999999999
21.800000000000001
24
24
24.699999999999999
24.699999999999999
24.899999999999999
24.399999999999999
21.199999999999999
21.399999999999999
21.800000000000001
22.199999999999999
22.199999999999999
22.300000000000001
22.300000000000001
22.300000000000001
22.399999999999999
22.5
22.699999999999999
23.399999999999999
23.600000000000001
23.899999999999999
24.199999999999999
23.699999999999999
23.800000000000001
23.899999999999999
23.600000000000001
23.800000000000001
23.899999999999999
22.199999999999999
22.5
20.800000000000001
21
21.100000000000001
21.899999999999999
22.399999999999999
23.100000000000001
23.600000000000001
22.100000000000001
22.600000000000001
23.199999999999999
20.800000000000001
21.800000000000001
21.899999999999999
22.300000000000001
23.300000000000001
22.5
23.100000000000001
21.100000000000001
21.300000000000001
20.600000000000001
20.800000000000001
21.5
21.5
21.800000000000001
22.600000000000001
22.600000000000001
22.699999999999999
22.899999999999999
23.100000000000001
20.100000000000001
21
25
20.5
22.5
22.600000000000001
23.300000000000001
21.399999999999999
20.800000000000001
21.100000000000001
22.5
22.600000000000001
22.699999999999999
19.5
19.699999999999999
19.800000000000001
20
20.199999999999999
20.300000000000001
20.399999999999999
20.600000000000001
21.5
21.699999999999999
22
22.100000000000001
22.199999999999999
22.300000000000001
22.899999999999999
23.199999999999999
23.5
24.399999999999999
23.800000000000001
21.399999999999999
19.699999999999999
23.800000000000001
22.600000000000001
20.5
20.699999999999999
20.800000000000001
20.899999999999999
21
21.300000000000001
21.399999999999999
21.600000000000001
21.699999999999999
22.300000000000001
22.5
23.800000000000001
24.199999999999999
20.699999999999999
22.699999999999999
20
20.100000000000001
20.199999999999999
21
22.399999999999999
19.699999999999999
20.5
20.600000000000001
21.600000000000001
21.800000000000001
20.199999999999999
20.300000000000001
19.399999999999999
19.899999999999999
20
20.199999999999999
20.300000000000001
24.199999999999999
24.199999999999999
21.600000000000001
22.300000000000001
22.5
24.699999999999999
24.699999999999999
17.5
19.899999999999999
20.899999999999999
24.100000000000001
24.100000000000001
24.100000000000001
20.300000000000001
22.199999999999999
22.300000000000001
17.899999999999999
17.699999999999999
17.899999999999999
19.100000000000001
19.300000000000001
19.699999999999999
19.800000000000001
19.899999999999999
21.199999999999999
22.300000000000001
19.899999999999999
18.199999999999999
20
18.100000000000001
22.699999999999999
23.300000000000001
18.199999999999999
18.699999999999999
18.899999999999999
19
19.100000000000001
19.300000000000001
19.600000000000001
19.699999999999999
23.899999999999999
23.899999999999999
20.699999999999999
20.899999999999999
23.600000000000001
23.600000000000001
24.199999999999999
24.199999999999999
24.199999999999999
19.699999999999999
18
23.899999999999999
23.899999999999999
23.899999999999999
19.899999999999999
21
18.800000000000001
19
19.199999999999999
20.800000000000001
18
18.100000000000001
18.300000000000001
20.399999999999999
20.399999999999999
20.399999999999999
18.5
18.600000000000001
20.5
18.100000000000001
18.300000000000001
18.899999999999999
20.699999999999999
20.699999999999999
14.5
14.5
18.5
19.800000000000001
18.199999999999999
18.300000000000001
18.899999999999999
17.300000000000001
18.699999999999999
21.600000000000001
18.5
16.399999999999999
19
19.300000000000001
19.699999999999999
17.300000000000001
18.300000000000001
18.800000000000001
17.399999999999999
21
21
17.5
17.600000000000001
17.699999999999999
17.800000000000001
18
18.5
17.699999999999999
19.5
21.899999999999999
21.899999999999999
21.899999999999999
16
16.800000000000001
17.300000000000001
20
18
15.800000000000001
22.699999999999999
22.699999999999999
16.800000000000001
17.399999999999999
22.399999999999999
18.199999999999999
17.899999999999999
18.399999999999999
17.300000000000001
17.699999999999999
18
18.199999999999999
17.399999999999999
17.5
15
22.899999999999999
22.899999999999999
22.899999999999999
17.100000000000001
15
15.800000000000001
17.399999999999999
17.5
16.100000000000001
16.199999999999999
16
15
15.699999999999999
15.5
15.9
17.899999999999999
16.100000000000001
15.199999999999999
15.1
16.399999999999999
15.6
row.names
character
355
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
class
character
1
data.frame
rubber
structure
3
.Data
list
5
hardness
integer
30
45
55
61
66
71
71
81
86
53
60
64
68
79
81
56
68
75
83
88
59
71
80
82
89
51
59
65
74
81
86
tensile.strength
integer
30
162
233
232
231
231
237
224
219
203
189
210
210
196
180
200
173
188
161
119
161
151
165
151
128
161
146
148
144
134
127
abrasion.loss
integer
30
372
206
175
154
136
112
55
45
221
166
164
113
82
32
228
196
128
97
64
249
219
186
155
114
341
340
283
267
215
148
ts.low
numeric
30
-18
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-7
0
-19
-61
-19
-29
-15
-29
-52
-19
-34
-32
-36
-46
-53
ts.high
numeric
30
0
53
52
51
51
57
44
39
23
9
30
30
16
0
20
0
8
0
0
0
0
0
0
0
0
0
0
0
0
0
row.names
character
30
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
class
character
1
data.frame
run.time
structure
3
.Data
list
4
time
numeric
36
1.25
1.3899999999999999
1.78
3.2400000000000002
2.48
3.8900000000000001
0.80000000000000004
0.89000000000000001
1.23
2.0099999999999998
2.1000000000000001
2.8199999999999998
0.56999999999999995
0.68000000000000005
0.88
0.88
1.7
1.6200000000000001
0.96999999999999997
0.95999999999999996
1.6699999999999999
3.8900000000000001
1.3600000000000001
4.1699999999999999
0.53000000000000003
0.56000000000000005
1.01
2.2000000000000002
0.93000000000000005
2.3100000000000001
0.17000000000000001
0.20999999999999999
0.27000000000000002
0.28000000000000003
0.52000000000000002
0.45000000000000001
algorithm
structure
4
.Data
integer
36
3
3
3
3
3
3
2
2
2
2
2
2
1
1
1
1
1
1
3
3
3
3
3
3
2
2
2
2
2
2
1
1
1
1
1
1
.Label
character
3
new
ucb
7th
.Names
character
36
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
class
character
2
ordered
factor
machine
structure
4
.Data
integer
36
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
.Label
character
2
mips
vax
.Names
character
36
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
class
character
2
ordered
factor
input
structure
4
.Data
integer
36
1
2
3
5
4
6
1
2
3
5
4
6
1
2
3
5
4
6
1
2
3
5
4
6
1
2
3
5
4
6
1
2
3
5
4
6
.Label
character
6
integer
float
double
pointer
record
string
.Names
character
36
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
class
character
2
ordered
factor
row.names
character
36
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
class
character
1
data.frame
singer
structure
3
.Data
list
2
height
integer
235
64
62
66
65
60
61
65
66
65
63
67
65
62
65
68
65
63
65
62
65
66
62
65
63
65
66
65
62
65
66
65
61
65
66
65
62
63
67
60
67
66
62
65
62
61
62
66
60
65
65
61
64
68
64
63
62
64
62
64
65
60
65
70
63
67
66
65
62
68
67
67
63
67
66
63
72
62
61
66
64
60
61
66
66
66
62
70
65
64
63
65
69
61
66
65
61
63
64
67
66
68
70
65
65
65
64
66
64
70
63
70
64
63
67
65
63
66
66
64
64
70
70
66
66
66
69
67
65
69
72
71
66
76
74
71
66
68
67
70
65
72
70
68
64
73
66
68
67
64
68
73
69
71
69
76
71
69
71
66
69
71
71
71
69
70
69
68
70
68
69
72
70
72
69
73
71
72
68
68
71
66
68
71
73
73
70
68
70
75
68
71
70
74
70
75
75
69
72
71
70
71
68
70
75
72
66
72
70
69
72
75
67
75
74
72
72
74
72
72
74
70
66
68
75
68
70
72
67
70
70
69
72
71
74
75
voice.part
structure
3
.Data
integer
235
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
.Label
character
8
Bass 2
Bass 1
Tenor 2
Tenor 1
Alto 2
Alto 1
Soprano 2
Soprano 1
class
character
2
ordered
factor
row.names
character
235
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
class
character
1
data.frame
slope
structure
3
.Data
list
4
error
numeric
44
18.90625
16.33333
19.4375
17.44791
17.036460000000002
14.59896
11.63021
9.1354199999999999
7.5833300000000001
6.0416660000000002
5.4583300000000001
16.057279999999999
16.973960000000002
13.69792
12.05729
11.95833
11.97396
9.8177099999999999
9.1822909999999993
7.65625
5.3072900000000001
5.9166660000000002
8.2447909999999993
9.2135409999999993
9.4791699999999999
9.0260409999999993
8.1354199999999999
5.96875
6.3229160000000002
6.40625
6.078125
4.8020800000000001
3.1041669999999999
5.78125
6.3489599999999999
7.9947900000000001
7.9739599999999999
6.5729199999999999
6.4791660000000002
6.9010400000000001
7.1145800000000001
6.6354199999999999
5.7708300000000001
3.3697900000000001
percent
numeric
44
50
55
60
65
70
75
80
85
90
95
100
50
55
60
65
70
75
80
85
90
95
100
50
55
60
65
70
75
80
85
90
95
100
50
55
60
65
70
75
80
85
90
95
100
distance
numeric
44
37.405230000000003
37.152299999999997
36.899790000000003
36.647799999999997
36.396270000000001
36.145299999999999
35.894930000000002
35.645159999999997
35.396079999999998
35.147669999999998
34.899999999999999
30.075050000000001
29.579699999999999
29.087689999999998
28.599270000000001
28.114730000000002
27.634229999999999
27.158049999999999
26.686340000000001
26.21932
25.757149999999999
25.299990000000001
17.435690000000001
16.53969
15.66512
14.81283
13.9834
13.17728
12.39471
11.6358
10.900499999999999
10.18866
9.5
0.264824
1.5744860000000001
2.7964500000000001
3.9352200000000002
4.9957539999999998
5.9832299999999998
6.9028200000000002
7.7595999999999998
8.5583899999999993
9.3037600000000005
10
resolution
numeric
44
5.010459
4.5045900000000003
3.9995970000000001
3.495549
2.9925299999999999
2.4906069999999998
1.9898560000000001
1.4903500000000001
0.99215900000000001
0.49535259999999998
0
9.5500889999999998
8.5593789999999998
7.5753690000000002
6.5985659999999999
5.6294490000000001
4.6684789999999996
3.7160890000000002
2.7726839999999999
1.8386400000000001
0.91430299999999998
0
15.87139
14.079359999999999
12.33024
10.62565
8.9668100000000006
7.3545590000000001
5.7894300000000003
4.2716029999999998
2.8010060000000001
1.377318
0
19.47035
16.851019999999998
14.40709
12.12956
10.00848
8.0335300000000007
6.1943400000000004
4.4807899999999998
2.883213
1.3924639999999999
0
row.names
character
44
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
class
character
1
data.frame
soil
structure
3
.Data
list
5
northing
numeric
8641
0.017999999999999999
0.0178
0.017600000000000001
0.017399999999999999
0.017100000000000001
0.016899999999999998
0.0167
0.016500000000000001
0.016300000000000002
0.0161
0.015900000000000001
0.015599999999999999
0.0154
0.0152
0.014999999999999999
0.014800000000000001
0.0146
0.0144
0.014199999999999999
0.013900000000000001
0.013699999999999999
0.0135
0.013300000000000001
0.013099999999999999
0.0129
0.012699999999999999
0.0124
0.012199999999999999
0.012
0.011800000000000001
0.011599999999999999
0.0114
0.0112
0.010999999999999999
0.010800000000000001
0.010500000000000001
0.0103
0.0101
0.0099000000000000008
0.0096999999999999986
0.0094999999999999998
0.009300000000000001
0.0089999999999999993
0.0088000000000000005
0.0086
0.0084000000000000012
0.008199999999999999
0.0080000000000000002
0.0077999999999999996
0.0076
0.0073000000000000001
0.0070999999999999995
0.0069000000000000008
0.0067000000000000002
0.0064999999999999997
0.0063
0.0060999999999999995
0.0057999999999999996
0.0055999999999999999
0.0054000000000000003
0.0051999999999999998
0.0050000000000000001
0.50800000000000001
0.49910000000000004
0.49030000000000001
0.48139999999999999
0.47249999999999998
0.46360000000000001
0.45480000000000004
0.44589999999999996
0.437
0.42810000000000004
0.41930000000000001
0.41039999999999999
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numeric
8641
0.016
0.0252
0.034500000000000003
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1.1536
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1.1089
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1.091
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1.0284
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0.80510000000000004
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0.86250000000000004
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0.9103
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0.9294
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0.9486
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1.006
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1.0347
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1.0825
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1.1112
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1.159
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1.1877
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1.2259
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1.2642
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1.4842
1.4937
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1.5129000000000001
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1.532
resistivity
numeric
8641
34.149999999999999
34.810000000000002
35.649999999999999
36.439999999999998
37.100000000000001
37.530000000000001
37.579999999999998
37.409999999999997
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39.32
39.93
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36.450000000000003
35.170000000000002
34.57
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36.189999999999998
37.310000000000002
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41.090000000000003
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42.840000000000003
41.350000000000001
37.979999999999997
34.380000000000003
32.170000000000002
31.379999999999999
31.02
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42.020000000000003
51.789999999999999
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44.57
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34.539999999999999
35.310000000000002
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41.350000000000001
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48.43
49.899999999999999
49.82
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43.799999999999997
43.039999999999999
45.840000000000003
50.869999999999997
56.25
61.210000000000001
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72.420000000000002
78.569999999999993
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70.030000000000001
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39.119999999999997
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37.990000000000002
36.640000000000001
34.869999999999997
33.18
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29.18
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32.020000000000003
33.960000000000001
57.240000000000002
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41.380000000000003
40.920000000000002
44.18
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44.840000000000003
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31.260000000000002
28.489999999999998
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31.34
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34.460000000000001
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33.25
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28.02
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30.82
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29.66
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28.890000000000001
28.75
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30.329999999999998
30.640000000000001
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30.149999999999999
30.84
32.979999999999997
36.43
40.630000000000003
45.32
51.060000000000002
58.810000000000002
67.980000000000004
75.230000000000004
76.5
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62.780000000000001
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50.210000000000001
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29.84
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31.27
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31.98
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34.619999999999997
33.600000000000001
31.02
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26.43
25.879999999999999
25.960000000000001
26.010000000000002
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25.68
25.68
25.84
26.030000000000001
26.219999999999999
26.489999999999998
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27.52
28.059999999999999
28.370000000000001
28.329999999999998
27.93
27.25
26.449999999999999
25.699999999999999
25.219999999999999
25.289999999999999
25.98
26.949999999999999
27.719999999999999
28.109999999999999
28.300000000000001
28.43
28.510000000000002
28.489999999999998
28.440000000000001
28.43
28.489999999999998
28.539999999999999
28.420000000000002
28.059999999999999
27.469999999999999
26.780000000000001
26.16
25.75
25.600000000000001
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32.07
30.960000000000001
29.219999999999999
27.640000000000001
26.789999999999999
26.600000000000001
26.719999999999999
27
27.5
28.170000000000002
28.68
28.57
27.68
26.5
25.850000000000001
26.190000000000001
27.43
29.219999999999999
31.260000000000002
33.229999999999997
34.840000000000003
36.100000000000001
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38.259999999999998
37.460000000000001
35.759999999999998
33.530000000000001
31.059999999999999
28.559999999999999
26.390000000000001
25.02
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35.420000000000002
35.590000000000003
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35.520000000000003
34.340000000000003
32.460000000000001
30.68
29.670000000000002
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31.199999999999999
29.879999999999999
28.23
27.09
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28.48
29.030000000000001
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30.07
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29.859999999999999
29.109999999999999
28.57
28.52
28.800000000000001
28.91
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27.530000000000001
26.68
26.219999999999999
25.949999999999999
25.52
24.920000000000002
24.420000000000002
24.149999999999999
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25.93
28.030000000000001
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31.329999999999998
27.170000000000002
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29.77
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30.399999999999999
29.98
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30.91
30.91
30.68
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32.189999999999998
33.950000000000003
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36.82
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41.619999999999997
44.420000000000002
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50.119999999999997
54.25
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51.420000000000002
53.280000000000001
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46.469999999999999
39.899999999999999
35.799999999999997
34.369999999999997
32.509999999999998
28.280000000000001
23.52
21.420000000000002
22.5
24.48
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82.909999999999997
81.730000000000004
80.5
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75.760000000000005
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84.879999999999995
97.450000000000003
111.47
120.77
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88.170000000000002
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81.25
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76.340000000000003
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106.17
113.64
124
138.43000000000001
152.55000000000001
61.810000000000002
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104.44
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60
61.640000000000001
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62
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56.420000000000002
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48.32
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42.75
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48.82
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35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
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35
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35
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35
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35
35
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35
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35
35
35
35
35
35
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35
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36
36
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36
36
36
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36
36
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36
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37
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37
37
37
37
37
37
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37
37
37
37
37
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37
37
37
37
37
37
37
37
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37
37
37
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37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
37
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37
37
38
38
38
38
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38
38
38
38
38
38
38
38
38
38
38
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38
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38
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38
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38
38
38
38
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38
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38
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38
38
38
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38
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38
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38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
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39
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39
39
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39
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39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
.Label
character
40
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
.Names
character
8641
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
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7788
7789
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7793
7794
7795
7796
7797
7798
7799
7800
7801
7802
7803
7804
7805
7806
7807
7808
7809
7810
7811
7812
7813
7814
7815
7816
7817
7818
7819
7820
7821
7822
7823
7824
7825
7826
7827
7828
7829
7830
7831
7832
7833
7834
7835
7836
7837
7838
7839
7840
7841
7842
7843
7844
7845
7846
7847
7848
7849
7850
7851
7852
7853
7854
7855
7856
7857
7858
7859
7860
7861
7862
7863
7864
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7866
7867
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7870
7871
7872
7873
7874
7875
7876
7877
7878
7879
7880
7881
7882
7883
7884
7885
7886
7887
7888
7889
7890
7891
7892
7893
7894
7895
7896
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7898
7899
7900
7901
7902
7903
7904
7905
7906
7907
7908
7909
7910
7911
7912
7913
7914
7915
7916
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7918
7919
7920
7921
7922
7923
7924
7925
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7928
7929
7930
7931
7932
7933
7934
7935
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7938
7939
7940
7941
7942
7943
7944
7945
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7948
7949
7950
7951
7952
7953
7954
7955
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7957
7958
7959
7960
7961
7962
7963
7964
7965
7966
7967
7968
7969
7970
7971
7972
7973
7974
7975
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7977
7978
7979
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7981
7982
7983
7984
7985
7986
7987
7988
7989
7990
7991
7992
7993
7994
7995
7996
7997
7998
7999
8000
8001
8002
8003
8004
8005
8006
8007
8008
8009
8010
8011
8012
8013
8014
8015
8016
8017
8018
8019
8020
8021
8022
8023
8024
8025
8026
8027
8028
8029
8030
8031
8032
8033
8034
8035
8036
8037
8038
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8041
8042
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8044
8045
8046
8047
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8050
8051
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8055
8056
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8061
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8064
8065
8066
8067
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8069
8070
8071
8072
8073
8074
8075
8076
8077
8078
8079
8080
8081
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8083
8084
8085
8086
8087
8088
8089
8090
8091
8092
8093
8094
8095
8096
8097
8098
8099
8100
8101
8102
8103
8104
8105
8106
8107
8108
8109
8110
8111
8112
8113
8114
8115
8116
8117
8118
8119
8120
8121
8122
8123
8124
8125
8126
8127
8128
8129
8130
8131
8132
8133
8134
8135
8136
8137
8138
8139
8140
8141
8142
8143
8144
8145
8146
8147
8148
8149
8150
8151
8152
8153
8154
8155
8156
8157
8158
8159
8160
8161
8162
8163
8164
8165
8166
8167
8168
8169
8170
8171
8172
8173
8174
8175
8176
8177
8178
8179
8180
8181
8182
8183
8184
8185
8186
8187
8188
8189
8190
8191
8192
8193
8194
8195
8196
8197
8198
8199
8200
8201
8202
8203
8204
8205
8206
8207
8208
8209
8210
8211
8212
8213
8214
8215
8216
8217
8218
8219
8220
8221
8222
8223
8224
8225
8226
8227
8228
8229
8230
8231
8232
8233
8234
8235
8236
8237
8238
8239
8240
8241
8242
8243
8244
8245
8246
8247
8248
8249
8250
8251
8252
8253
8254
8255
8256
8257
8258
8259
8260
8261
8262
8263
8264
8265
8266
8267
8268
8269
8270
8271
8272
8273
8274
8275
8276
8277
8278
8279
8280
8281
8282
8283
8284
8285
8286
8287
8288
8289
8290
8291
8292
8293
8294
8295
8296
8297
8298
8299
8300
8301
8302
8303
8304
8305
8306
8307
8308
8309
8310
8311
8312
8313
8314
8315
8316
8317
8318
8319
8320
8321
8322
8323
8324
8325
8326
8327
8328
8329
8330
8331
8332
8333
8334
8335
8336
8337
8338
8339
8340
8341
8342
8343
8344
8345
8346
8347
8348
8349
8350
8351
8352
8353
8354
8355
8356
8357
8358
8359
8360
8361
8362
8363
8364
8365
8366
8367
8368
8369
8370
8371
8372
8373
8374
8375
8376
8377
8378
8379
8380
8381
8382
8383
8384
8385
8386
8387
8388
8389
8390
8391
8392
8393
8394
8395
8396
8397
8398
8399
8400
8401
8402
8403
8404
8405
8406
8407
8408
8409
8410
8411
8412
8413
8414
8415
8416
8417
8418
8419
8420
8421
8422
8423
8424
8425
8426
8427
8428
8429
8430
8431
8432
8433
8434
8435
8436
8437
8438
8439
8440
8441
8442
8443
8444
8445
8446
8447
8448
8449
8450
8451
8452
8453
8454
8455
8456
8457
8458
8459
8460
8461
8462
8463
8464
8465
8466
8467
8468
8469
8470
8471
8472
8473
8474
8475
8476
8477
8478
8479
8480
8481
8482
8483
8484
8485
8486
8487
8488
8489
8490
8491
8492
8493
8494
8495
8496
8497
8498
8499
8500
8501
8502
8503
8504
8505
8506
8507
8508
8509
8510
8511
8512
8513
8514
8515
8516
8517
8518
8519
8520
8521
8522
8523
8524
8525
8526
8527
8528
8529
8530
8531
8532
8533
8534
8535
8536
8537
8538
8539
8540
8541
8542
8543
8544
8545
8546
8547
8548
8549
8550
8551
8552
8553
8554
8555
8556
8557
8558
8559
8560
8561
8562
8563
8564
8565
8566
8567
8568
8569
8570
8571
8572
8573
8574
8575
8576
8577
8578
8579
8580
8581
8582
8583
8584
8585
8586
8587
8588
8589
8590
8591
8592
8593
8594
8595
8596
8597
8598
8599
8600
8601
8602
8603
8604
8605
8606
8607
8608
8609
8610
8611
8612
8613
8614
8615
8616
8617
8618
8619
8620
8621
8622
8623
8624
8625
8626
8627
8628
8629
8630
8631
8632
8633
8634
8635
8636
8637
8638
8639
8640
8641
8642
8643
8644
8645
8646
8647
8648
8649
8650
8651
8652
8653
8654
8655
8656
8657
8658
8659
8660
8661
8662
8663
8664
8665
8666
8667
8668
8669
8670
8671
8672
8673
8674
8675
8676
8677
8678
8679
8680
8681
8682
8683
8684
8685
8686
8687
8688
8689
8690
8691
8692
8693
8694
8695
8696
8697
8698
8699
8700
8701
8702
8703
8704
8705
8706
8707
8708
8709
8710
8711
8712
8713
8714
8715
8716
8717
8718
8719
8720
8721
8722
8723
8724
8725
8726
8727
class
character
1
factor
row.names
character
8641
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
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201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
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251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
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291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
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348
349
350
351
352
353
354
355
356
357
358
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362
363
364
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370
371
372
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375
376
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381
382
383
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388
389
390
391
392
393
394
395
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397
398
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400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
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425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
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0.20000000000000001
0.20000000000000001
0.20000000000000001
0.20000000000000001
1.3999999999999999
1.5
1.5
1.3
1.5
1.3
1.6000000000000001
1
1.3
1.3999999999999999
1
1.5
1
1.3999999999999999
1.3
1.3999999999999999
1.5
1
1.5
1.1000000000000001
1.8
1.3
1.5
1.2
1.3
1.3999999999999999
1.3999999999999999
1.7
1.5
1
1.1000000000000001
1
1.2
1.6000000000000001
1.5
1.6000000000000001
1.5
1.3
1.3
1.3
1.2
1.3999999999999999
1.2
1
1.3
1.2
1.3
1.3
1.1000000000000001
1.3
2.5
1.8999999999999999
2.1000000000000001
1.8
2.2000000000000002
2.1000000000000001
1.7
1.8
1.8
2.5
2
1.8999999999999999
2.1000000000000001
2
2.3999999999999999
2.2999999999999998
1.8
2.2000000000000002
2.2999999999999998
1.5
2.2999999999999998
2
2
1.8
2.1000000000000001
1.8
1.8
1.8
2.1000000000000001
1.6000000000000001
1.8999999999999999
2
2.2000000000000002
1.5
1.3999999999999999
2.2999999999999998
2.3999999999999999
1.8
1.8
2.1000000000000001
2.3999999999999999
2.2999999999999998
1.8999999999999999
2.2999999999999998
2.5
2.2999999999999998
1.8999999999999999
2
2.2999999999999998
1.8
variety
structure
3
.Data
integer
150
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
.Label
character
3
Setosa
Versicolor
Virginica
class
character
1
factor
row.names
character
150
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
class
character
1
data.frame