Dear all,
Does any one knows why should I get the following error message, when trying
to do a simple data.frame??
DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS
p,DSSp,Slope, CanDens,NearestSp)
Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, :
arguments imply differing number of rows: 202, 0
The data I am using is:
Subject
BiomR
Spp
Capas
Litter
Herbs
LitterD
MaxCanH
DDifSp
DSSp
Slope
CanDens
NearestSp
1
140.74
Qfa
2
1.460
0
0.778
8
70
3.663
28
2.280
Ear
2
7.26
Aun
2
0.660
0
0.477
8
110
3.988
34
2.476
Ear
3
68.72
Qfa
2
1.019
0
1.000
8
48
2.300
48
2.476
Ear
4
0.13
Vti
2
1.719
0
0.903
4
55
4.141
28
3.258
Qco
5
2.32
Vti
2
1.719
0
0.954
4
65
3.984
32
3.051
Aun
6
2.97
Vti
2
1.719
0
0.954
6
201
3.642
22
2.000
Qfa
7
0.16
Qfa
2
1.238
2
0.778
6
72
3.105
20
1.566
Vti
8
1.76
Qfa
2
1.145
0
0.954
6
67
3.383
22
2.052
Vti
9
0.35
Qfa
3
1.092
2
0.778
6
65
3.557
30
2.106
Vti
10
0.15
Qfa
2
1.092
2
0.778
6
42
3.464
14
2.106
Vti
11
107.33
Qfa
3
1.145
5
0.903
8
147
4.035
24
2.220
Vti
12
12.32
Vti
3
1.145
5
1.000
6
208
3.464
28
2.220
Qfa
13
1.82
Vti
3
1.145
5
0.903
6
251
3.458
20
2.220
Qfa
14
1.84
Vti
1
1.019
5
0.602
6
88
3.960
28
1.363
Aun
15
3.25
Vti
2
1.719
0
0.778
6
70
4.319
14
2.621
Aun
16
3.60
Vti
1
1.460
0
0.954
6
53
4.186
26
1.902
Aun
17
0.69
Vti
2
1.238
5
0.845
4
184
3.856
44
2.547
Aun
18
1.04
Vti
1
1.019
5
0.602
4
144
3.911
32
2.052
Aun
19
0.08
Vti
2
1.460
0
0.699
6
93
3.956
36
2.547
Qco
20
10.43
Vti
2
1.145
5
0.903
6
70
3.919
23
3.258
Qco
21
0.69
Vti
3
1.145
5
0.845
8
120
4.023
30
3.051
Ear
22
13.47
Vti
3
1.460
2
0.811
8
39
3.370
42
3.152
Ear
23
2.83
Vti
2
1.019
5
0.845
6
120
4.102
24
3.258
Ear
24
1.26
Vti
2
1.019
5
0.903
6
153
4.116
30
3.152
Ear
25
0.25
Qfa
2
1.145
5
0.845
6
106
4.210
38
2.699
Qco
26
28.27
Vti
2
0.913
10
0.845
6
203
4.688
32
1.566
Qco
27
0.88
Vti
2
1.460
2
0.845
8
52
4.464
30
3.051
Qfa
28
0.08
Vti
2
1.311
0
0.477
8
86
4.486
48
2.956
Qfa
29
1.13
Vti
3
1.019
5
0.845
8
54
4.291
40
3.492
Qfa
30
11.03
Vti
2
0.821
0
0.903
4
130
4.606
42
2.699
Ear
31
0.63
Vti
2
0.821
5
0.845
4
130
4.464
44
2.699
Ear
32
0.97
Vti
2
0.737
0
0.845
4
123
4.562
34
2.699
Ear
33
4.94
Vti
2
0.737
0
0.903
4
123
4.522
48
2.699
Ear
34
2.26
Vti
2
0.821
5
0.778
4
114
4.478
46
2.699
Ear
35
0.94
Vti
2
0.660
0
0.903
4
144
4.516
31
2.699
Ear
36
0.69
Vti
2
0.589
0
0.699
4
146
4.551
35
2.699
Ear
37
0.13
Vti
3
1.019
0
0.845
8
48
4.362
14
2.343
Qfa
38
2.12
Vti
2
0.737
0
1.041
8
52
4.054
24
2.956
Qfa
39
1.77
Vti
2
0.913
0
0.903
8
56
5.198
6
2.621
Ear
40
0.32
Vti
2
1.145
5
0.954
8
118
5.138
35
3.258
Ear
41
0.11
Vti
2
1.019
0
0.602
8
84
5.237
20
2.621
Ear
42
1.57
Vti
1
0.913
0
0.954
6
137
5.038
12
3.492
Qco
43
1.77
Vti
3
0.737
0
0.954
6
141
5.026
16
3.371
Qco
44
0.17
Vti
2
0.913
0
1.000
8
69
4.901
24
3.258
Qco
45
0.41
Vti
3
1.092
2
0.954
8
81
5.129
44
4.457
Qfa
46
2.62
Vti
1
0.913
0
0.845
4
114
5.047
34
4.457
Ear
47
0.09
Vti
3
0.975
2
0.954
8
98
4.924
20
3.492
Aun
48
0.12
Vti
4
1.311
5
0.845
8
78
4.748
26
3.761
Aun
49
1.70
Vti
3
0.975
2
1.000
8
95
5.146
36
4.457
Qfa
50
14.49
Qfa
1
1.719
0
0.778
6
37
2.962
32
1.766
Pan
51
0.09
Vti
2
1.311
0
0.778
6
56
2.872
20
1.950
Pan
52
2.12
Qfa
2
1.460
0
0.845
6
203
3.097
18
3.152
Vti
53
0.23
Qfa
2
1.238
2
0.778
8
86
2.190
30
2.476
Ear
54
5.36
Qfa
2
0.975
0
0.954
6
134
3.409
42
4.684
Vti
55
0.41
Vti
2
1.145
5
0.845
6
108
3.890
36
4.945
Qco
56
0.19
Vti
1
1.719
0
0.845
6
42
4.130
35
3.492
Qco
57
15.59
Vti
3
1.719
0
1.114
6
91
4.386
16
4.257
Ear
58
3.25
Vti
3
1.719
0
0.903
6
85
4.275
36
4.257
Ear
59
2.32
Vti
3
1.460
0
0.954
6
91
4.223
32
4.257
Ear
60
4.24
Vti
3
1.719
0
1.041
6
36
4.386
42
4.257
Ear
61
31.49
Vti
3
1.719
0
1.176
6
78
4.371
43
4.257
Ear
62
2.97
Vti
3
0.786
2
0.954
6
71
3.988
22
4.076
Qco
63
0.50
Vti
3
0.706
2
0.903
6
76
4.134
20
4.076
Qco
64
20.20
Vti
2
1.719
0
1.079
6
62
3.557
18
5.640
Qfa
65
0.12
Vti
1
1.460
0
0.903
6
75
3.186
20
3.152
Qfa
66
0.10
Vti
1
1.719
0
0.903
6
90
3.154
20
3.152
Qfa
67
0.79
Vti
1
1.719
0
0.954
6
64
3.154
12
3.152
Ear
68
0.17
Vti
1
1.719
0
0.954
6
52
3.186
24
3.152
Ear
69
0.09
Qfa
1
0.589
0
0.477
4
55
3.540
32
3.492
Ear
70
1.02
Vti
2
1.719
0
0.845
6
107
3.816
38
3.911
Aun
71
12.67
Qfa
2
1.719
0
0.954
6
62
3.282
32
4.457
Aun
72
32.80
Qfa
2
1.719
0
0.699
6
56
2.962
32
4.076
Aun
73
26.64
Qfa
2
1.719
0
0.699
6
76
2.893
32
4.076
Aun
74
0.09
Vti
3
1.460
0
0.845
6
110
3.851
24
4.684
Aun
75
103.14
Qfa
2
1.719
0
0.845
6
124
3.703
28
4.257
Aun
76
0.09
Vti
2
1.719
0
0.845
6
156
3.637
26
4.257
Aun
77
248.11
Qfa
2
1.719
0
0.845
6
144
3.807
33
4.257
Aun
78
2.19
Vti
3
1.311
0
1.000
8
63
3.458
28
4.257
Aun
79
29.90
Vti
1
1.719
0
1.000
6
46
2.711
30
3.621
Qsu
80
17.81
Ral
2
1.460
0
1.000
8
55
4.516
10
4.945
Aun
81
0.11
Vti
2
1.311
0
0.954
6
84
4.189
10
5.640
Ear
82
0.53
Vti
2
1.719
0
0.845
6
23
4.389
24
4.945
Ear
83
10.30
Ral
3
1.460
0
0.903
8
42
4.843
20
5.640
Qco
84
41.56
Vti
2
1.460
0
0.778
6
74
4.008
40
5.254
Qfa
85
11.52
Qfa
2
1.719
0
0.845
8
77
3.611
34
5.640
Aun
86
113.61
Qfa
3
1.719
0
1.000
6
46
2.795
28
4.945
Ear
87
0.09
Vti
2
1.145
0
0.778
6
96
3.505
34
6.176
Qfa
88
7.63
Ral
3
1.719
0
0.845
6
45
3.344
38
5.254
Vti
89
0.09
Vti
2
0.913
0
0.602
6
66
3.980
22
4.945
Aun
90
98.52
Qfa
2
1.719
0
0.602
6
65
3.924
24
4.945
Aun
91
6.41
Qfa
1
0.291
60
0.845
6
121
3.500
30
3.152
Aun
92
0.47
Vti
1
1.019
5
0.602
6
107
4.380
22
3.152
Ear
93
0.14
Vti
1
1.145
5
0.699
6
56
4.288
28
4.457
Aun
94
1.98
Vti
1
1.145
5
0.602
6
75
4.325
28
4.457
Aun
95
6.41
Vti
1
0.460
50
0.778
6
60
4.559
20
4.257
Ear
96
3.53
Vti
1
0.523
45
0.778
6
127
4.559
22
4.257
Ear
97
0.57
Vti
1
0.523
40
0.699
6
90
4.500
30
4.257
Ear
98
2.76
Vti
1
0.345
60
0.602
6
116
4.598
22
4.257
Ear
99
1.70
Vti
1
0.240
70
0.954
6
76
4.644
36
3.258
Ear
100
0.91
Vti
1
0.240
70
0.954
6
81
4.724
35
3.258
Ear
101
18.65
Vti
1
0.523
45
0.903
6
57
4.780
30
3.258
Qco
102
0.16
Vti
1
1.719
0
0.845
4
79
4.845
40
5.640
Aun
103
0.09
Vti
2
1.719
0
0.602
6
103
4.538
30
4.076
Ear
104
1.63
Vti
1
1.719
0
0.778
6
84
4.540
36
4.257
Ear
105
15.51
Vti
1
1.460
2
0.602
6
102
4.601
30
4.257
Ear
106
2.26
Vti
2
1.719
0
0.699
6
72
4.593
38
4.257
Ear
107
8.92
Vti
2
1.311
5
1.041
6
99
4.646
28
4.257
Ear
108
5.64
Qsu
2
1.311
0
0.699
6
101
5.140
36
4.257
Ear
109
0.41
Vti
2
1.354
2
0.845
6
51
4.530
36
4.945
Ear
110
2.47
Vti
1
1.460
0
0.602
4
69
4.791
28
5.640
Ear
111
147.78
Vti
1
1.145
5
0.778
8
32
4.176
28
4.945
Qfa
112
18.94
Vti
2
1.311
5
0.903
8
31
4.252
44
4.945
Ear
113
18.66
Vti
1
0.913
20
0.778
8
54
4.023
38
4.257
Ear
114
0.44
Vti
1
1.311
5
0.602
8
38
4.127
28
4.945
Qfa
115
3.53
Vti
2
1.311
5
0.845
8
39
4.179
30
4.945
Ear
116
0.57
Vti
2
0.913
10
0.845
6
103
4.141
40
5.640
Ear
117
0.09
Vti
1
1.460
0
0.602
4
53
4.798
23
5.640
Ear
118
1.51
Vti
2
1.145
0
0.778
6
20
2.748
18
4.684
Qfa
119
187.80
Vti
2
0.401
0
1.079
6
0
2.483
0
4.684
Qfa
120
7.89
Vti
2
1.311
0
0.845
8
53
3.054
46
3.911
Qfa
121
18.06
Vti
2
1.311
0
0.845
8
58
3.303
32
6.176
Qco
122
0.16
Vti
2
1.311
0
0.903
8
37
3.323
46
6.176
Qco
123
0.09
Vti
2
1.311
0
1.000
8
21
3.253
32
6.176
Qco
124
4.65
Ral
2
1.719
0
0.602
8
31
4.583
38
6.176
Qfa
125
1.76
Vti
1
0.913
0
0.845
4
53
3.018
34
5.640
Qfa
126
1.82
Vti
1
0.913
0
0.903
4
40
2.943
38
5.640
Qfa
127
81.71
Vti
1
1.019
0
0.954
4
74
2.839
36
3.492
Qfa
128
0.60
Vti
1
1.311
0
0.845
4
78
3.045
34
3.492
Qfa
129
3.52
Vti
1
1.019
5
0.602
4
48
3.268
12
2.699
Qfa
130
1.84
Vti
1
0.660
5
0.602
4
81
3.415
38
2.699
Qfa
131
9.03
Qsu
2
1.311
0
0.845
4
23
3.383
30
2.343
Qfa
132
7.33
Qsu
2
0.821
0
0.778
4
48
3.000
10
2.000
Qfa
133
0.57
Vti
2
0.821
0
0.699
4
57
3.476
16
2.000
Qfa
134
5.23
Vti
2
1.019
0
0.903
4
78
3.899
30
3.761
Qco
135
0.13
Vti
2
1.145
0
0.778
4
77
3.924
20
3.761
Qco
136
8.38
Vti
1
1.719
0
0.699
2
23
3.317
30
1.165
Qsu
137
1.98
Vti
1
1.311
0
0.778
2
33
3.421
14
1.165
Qsu
138
3.24
Vti
1
1.019
0
0.845
2
48
3.488
24
1.165
Qsu
139
0.60
Vti
1
0.660
0
0.778
2
57
3.494
22
1.165
Qsu
140
0.09
Vti
1
0.345
2
0.699
2
78
3.658
0
1.165
Qsu
141
0.16
Qsu
1
0.345
0
0.699
2
89
2.850
0
1.165
Qfa
142
0.14
Vti
2
0.523
0
0.845
2
62
4.179
30
2.000
Qfa
143
0.47
Vti
2
0.913
0
0.954
2
18
4.000
24
2.000
Qfa
144
5.65
Vti
2
1.311
5
0.845
4
49
3.851
28
2.343
Qfa
145
0.85
Qsu
1
0.821
5
0.778
4
47
3.268
24
1.902
Qfa
146
0.85
Vti
2
0.913
5
0.699
6
16
3.071
38
4.076
Ear
147
0.66
Vti
2
1.019
5
0.845
6
51
2.943
36
4.076
Ear
148
0.11
Vti
2
1.311
0
0.699
6
65
2.882
32
4.076
Ear
149
0.09
Vti
2
1.719
0
0.699
4
29
3.642
24
6.176
Aun
150
134.70
Qfa
2
1.719
0
0.699
4
69
3.330
24
2.264
Ear
151
1.63
Aun
2
1.019
10
0.602
4
56
3.122
28
4.945
Vti
152
3.04
Vti
1
0.821
25
0.699
4
150
3.170
30
5.254
Ear
153
7.63
Qsu
1
0.523
40
0.778
4
53
3.829
24
4.945
Vti
154
0.97
Aun
3
0.821
15
0.699
4
55
3.446
34
4.457
Ear
155
87.46
Aun
1
1.019
10
0.845
4
48
2.806
0
2.956
Qsu
156
1.77
Qsu
2
1.019
10
0.903
4
66
2.882
28
2.956
Aun
157
1.17
Qsu
2
0.913
20
0.699
4
39
3.114
30
2.781
Aun
158
4.27
Qsu
1
0.913
0
0.699
4
36
2.604
28
1.902
Vti
159
43.20
Qfa
1
1.311
0
0.699
2
24
3.589
28
2.699
Aun
160
19.85
Vti
2
0.821
20
0.602
4
82
3.557
32
3.621
Qfa
161
0.63
Qsu
2
0.913
15
0.778
4
12
3.434
32
4.457
Aun
162
0.57
Vti
2
1.145
0
0.699
4
7
3.080
20
3.492
Ear
163
0.69
Vti
2
1.311
0
0.602
4
82
3.784
30
4.684
Qfa
164
0.79
Vti
3
0.821
15
0.778
4
93
3.231
26
3.621
Qfa
165
116.24
Qfa
4
1.019
10
0.845
6
96
3.458
26
3.761
Ear
166
13.08
Qfa
2
0.913
20
0.845
6
70
3.337
30
5.254
Ear
167
13.36
Qfa
2
0.821
25
0.845
6
47
3.154
34
5.254
Ear
168
9.42
Qsu
2
1.719
0
0.845
6
131
5.131
24
3.911
Ear
169
0.09
Vti
2
1.460
2
1.000
6
103
4.421
28
5.640
Aun
170
0.12
Ral
2
1.311
5
0.954
6
93
5.676
34
5.640
Aun
171
0.82
Vti
2
1.145
10
0.954
6
79
4.486
32
5.640
Aun
172
66.19
Vti
2
1.019
15
0.845
6
25
4.829
24
4.457
Ear
173
8.12
Vti
2
1.092
10
0.845
6
27
4.768
8
4.457
Ear
174
0.75
Vti
2
1.145
10
0.845
6
29
4.873
36
3.621
Ear
175
4.49
Qsu
2
1.145
10
1.000
6
22
5.547
36
3.051
Ear
176
0.17
Vti
1
0.589
20
0.301
6
9
5.297
54
3.911
Ear
177
4.12
Vti
2
1.145
10
0.845
6
20
5.534
36
3.371
Ear
178
1.34
Vti
2
1.145
10
0.778
6
49
5.562
36
3.371
Ear
179
1.48
Vti
1
1.145
10
0.699
6
34
5.574
38
3.258
Aun
180
3.82
Aun
2
1.719
0
0.699
6
54
3.500
38
5.254
Ear
181
15.59
Aun
2
1.460
2
0.000
6
66
3.383
25
5.254
Ear
182
0.66
Aun
2
1.719
0
0.954
6
79
3.452
28
5.254
Ear
183
0.16
Vti
2
1.719
0
0.699
6
89
5.911
22
5.254
Ear
184
0.16
Ral
1
1.460
2
0.845
6
21
5.713
22
4.684
Ear
185
0.11
Vti
1
1.311
5
0.954
6
14
5.285
16
4.684
Ear
186
0.42
Vti
1
1.311
5
0.845
6
14
5.259
22
4.684
Ear
187
0.38
Vti
2
1.719
0
0.477
6
34
5.201
38
5.254
Ear
188
0.09
Vti
2
1.719
0
0.845
6
52
5.123
26
4.684
Qco
189
0.41
Vti
1
1.719
0
0.845
6
71
5.078
28
5.254
Ear
190
2.97
Vti
1
1.311
5
0.477
6
72
5.082
22
3.911
Ear
191
0.13
Vti
1
0.913
10
0.845
6
63
5.138
30
3.911
Ear
192
0.09
Vti
1
1.092
2
0.602
6
43
5.158
36
3.911
Ear
193
0.75
Qsu
2
0.913
10
0.699
6
30
4.970
26
5.254
Ear
194
1.04
Aun
2
1.311
5
0.903
6
98
2.115
20
4.945
Ear
195
0.09
Vti
2
0.821
15
0.778
6
13
5.513
26
4.945
Ear
196
6.79
Vti
2
1.019
10
0.778
6
67
4.649
30
2.220
Qco
197
4.90
Vti
2
1.145
5
0.699
6
78
4.862
38
2.956
Qfa
198
11.39
Vti
2
0.737
10
0.602
6
79
4.947
42
4.257
Qco
199
1.45
Vti
2
0.913
20
0.699
6
74
4.996
44
4.257
Qco
200
0.85
Vti
2
1.719
0
0.699
8
18
4.924
36
2.162
Ear
201
0.85
Vti
3
1.719
0
0.778
8
12
4.964
38
2.162
Ear
202
0.69
Vti
3
1.719
0
0.845
8
23
4.931
30
2.162
Ear
. where I could not really find any mistake..
Hope some one can please help me on this.
Regards,
Sara Mouro
[[alternative HTML version deleted]]
Hi Your arguments has different length and therefore the error message data.frame is an object, which resembles a table from Excel, it has the same number of rows in each column>From help page:A data frame, a matrix-like structure whose columns may be of differing types (numeric, logical, factor and character and so on).> x1<-1:5 > x2<-1:3 > x3<-1:10 > data.frame(x1,x2,x3)Error in data.frame(x1, x2, x3) : arguments imply differing number of rows: 5, 3, 10 So you can recycle shorter vectors data.frame(cbind(x1,x2,x3)) or you can use list list(x1,x2,x3) I wonder how did you created your arguments? HTH Petr On 24 May 2006 at 13:05, Sara Mouro wrote: From: "Sara Mouro" <sara at gmesintra.com> To: <r-help at stat.math.ethz.ch> Date sent: Wed, 24 May 2006 13:05:45 +0100 Subject: [R] data.frame> Dear all, > > > > Does any one knows why should I get the following error message, when > trying to do a simple data.frame?? > > > > DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH > ,DDifS p,DSSp,Slope, CanDens,NearestSp) > > > > Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, > : > > arguments imply differing number of rows: 202, 0 > > > > > > The data I am using is: > > > > > Subject > > BiomR > > Spp > > Capas > > Litter > > Herbs > > LitterD > > MaxCanH > > DDifSp > > DSSp > > Slope > > CanDens > > NearestSp > > > 1 > > 140.74 > > Qfa > > 2 > > 1.460 > > 0 > > 0.778 > > 8 > > 70 > > 3.663 > > 28 > > 2.280 > > Ear > > > 2 > > 7.26 > > Aun > > 2 > > 0.660 > > 0 > > 0.477 > > 8 > > 110 > > 3.988 > > 34 > > 2.476 > > Ear > > > 3 > > 68.72 > > Qfa > > 2 > > 1.019 > > 0 > > 1.000 > > 8 > > 48 > > 2.300 > > 48 > > 2.476 > > Ear > > > 4 > > 0.13 > > Vti > > 2 > > 1.719 > > 0 > > 0.903 > > 4 > > 55 > > 4.141 > > 28 > > 3.258 > > Qco > > > 5 > > 2.32 > > Vti > > 2 > > 1.719 > > 0 > > 0.954 > > 4 > > 65 > > 3.984 > > 32 > > 3.051 > > Aun > > > 6 > > 2.97 > > Vti > > 2 > > 1.719 > > 0 > > 0.954 > > 6 > > 201 > > 3.642 > > 22 > > 2.000 > > Qfa > > > 7 > > 0.16 > > Qfa > > 2 > > 1.238 > > 2 > > 0.778 > > 6 > > 72 > > 3.105 > > 20 > > 1.566 > > Vti > > > 8 > > 1.76 > > Qfa > > 2 > > 1.145 > > 0 > > 0.954 > > 6 > > 67 > > 3.383 > > 22 > > 2.052 > > Vti > > > 9 > > 0.35 > > Qfa > > 3 > > 1.092 > > 2 > > 0.778 > > 6 > > 65 > > 3.557 > > 30 > > 2.106 > > Vti > > > 10 > > 0.15 > > Qfa > > 2 > > 1.092 > > 2 > > 0.778 > > 6 > > 42 > > 3.464 > > 14 > > 2.106 > > Vti > > > 11 > > 107.33 > > Qfa > > 3 > > 1.145 > > 5 > > 0.903 > > 8 > > 147 > > 4.035 > > 24 > > 2.220 > > Vti > > > 12 > > 12.32 > > Vti > > 3 > > 1.145 > > 5 > > 1.000 > > 6 > > 208 > > 3.464 > > 28 > > 2.220 > > Qfa > > > 13 > > 1.82 > > Vti > > 3 > > 1.145 > > 5 > > 0.903 > > 6 > > 251 > > 3.458 > > 20 > > 2.220 > > Qfa > > > 14 > > 1.84 > > Vti > > 1 > > 1.019 > > 5 > > 0.602 > > 6 > > 88 > > 3.960 > > 28 > > 1.363 > > Aun > > > 15 > > 3.25 > > Vti > > 2 > > 1.719 > > 0 > > 0.778 > > 6 > > 70 > > 4.319 > > 14 > > 2.621 > > Aun > > > 16 > > 3.60 > > Vti > > 1 > > 1.460 > > 0 > > 0.954 > > 6 > > 53 > > 4.186 > > 26 > > 1.902 > > Aun > > > 17 > > 0.69 > > Vti > > 2 > > 1.238 > > 5 > > 0.845 > > 4 > > 184 > > 3.856 > > 44 > > 2.547 > > Aun > > > 18 > > 1.04 > > Vti > > 1 > > 1.019 > > 5 > > 0.602 > > 4 > > 144 > > 3.911 > > 32 > > 2.052 > > Aun > > > 19 > > 0.08 > > Vti > > 2 > > 1.460 > > 0 > > 0.699 > > 6 > > 93 > > 3.956 > > 36 > > 2.547 > > Qco > > > 20 > > 10.43 > > Vti > > 2 > > 1.145 > > 5 > > 0.903 > > 6 > > 70 > > 3.919 > > 23 > > 3.258 > > Qco > > > 21 > > 0.69 > > Vti > > 3 > > 1.145 > > 5 > > 0.845 > > 8 > > 120 > > 4.023 > > 30 > > 3.051 > > Ear > > > 22 > > 13.47 > > Vti > > 3 > > 1.460 > > 2 > > 0.811 > > 8 > > 39 > > 3.370 > > 42 > > 3.152 > > Ear > > > 23 > > 2.83 > > Vti > > 2 > > 1.019 > > 5 > > 0.845 > > 6 > > 120 > > 4.102 > > 24 > > 3.258 > > Ear > > > 24 > > 1.26 > > Vti > > 2 > > 1.019 > > 5 > > 0.903 > > 6 > > 153 > > 4.116 > > 30 > > 3.152 > > Ear > > > 25 > > 0.25 > > Qfa > > 2 > > 1.145 > > 5 > > 0.845 > > 6 > > 106 > > 4.210 > > 38 > > 2.699 > > Qco > > > 26 > > 28.27 > > Vti > > 2 > > 0.913 > > 10 > > 0.845 > > 6 > > 203 > > 4.688 > > 32 > > 1.566 > > Qco > > > 27 > > 0.88 > > Vti > > 2 > > 1.460 > > 2 > > 0.845 > > 8 > > 52 > > 4.464 > > 30 > > 3.051 > > Qfa > > > 28 > > 0.08 > > Vti > > 2 > > 1.311 > > 0 > > 0.477 > > 8 > > 86 > > 4.486 > > 48 > > 2.956 > > Qfa > > > 29 > > 1.13 > > Vti > > 3 > > 1.019 > > 5 > > 0.845 > > 8 > > 54 > > 4.291 > > 40 > > 3.492 > > Qfa > > > 30 > > 11.03 > > Vti > > 2 > > 0.821 > > 0 > > 0.903 > > 4 > > 130 > > 4.606 > > 42 > > 2.699 > > Ear > > > 31 > > 0.63 > > Vti > > 2 > > 0.821 > > 5 > > 0.845 > > 4 > > 130 > > 4.464 > > 44 > > 2.699 > > Ear > > > 32 > > 0.97 > > Vti > > 2 > > 0.737 > > 0 > > 0.845 > > 4 > > 123 > > 4.562 > > 34 > > 2.699 > > Ear > > > 33 > > 4.94 > > Vti > > 2 > > 0.737 > > 0 > > 0.903 > > 4 > > 123 > > 4.522 > > 48 > > 2.699 > > Ear > > > 34 > > 2.26 > > Vti > > 2 > > 0.821 > > 5 > > 0.778 > > 4 > > 114 > > 4.478 > > 46 > > 2.699 > > Ear > > > 35 > > 0.94 > > Vti > > 2 > > 0.660 > > 0 > > 0.903 > > 4 > > 144 > > 4.516 > > 31 > > 2.699 > > Ear > > > 36 > > 0.69 > > Vti > > 2 > > 0.589 > > 0 > > 0.699 > > 4 > > 146 > > 4.551 > > 35 > > 2.699 > > Ear > > > 37 > > 0.13 > > Vti > > 3 > > 1.019 > > 0 > > 0.845 > > 8 > > 48 > > 4.362 > > 14 > > 2.343 > > Qfa > > > 38 > > 2.12 > > Vti > > 2 > > 0.737 > > 0 > > 1.041 > > 8 > > 52 > > 4.054 > > 24 > > 2.956 > > Qfa > > > 39 > > 1.77 > > Vti > > 2 > > 0.913 > > 0 > > 0.903 > > 8 > > 56 > > 5.198 > > 6 > > 2.621 > > Ear > > > 40 > > 0.32 > > Vti > > 2 > > 1.145 > > 5 > > 0.954 > > 8 > > 118 > > 5.138 > > 35 > > 3.258 > > Ear > > > 41 > > 0.11 > > Vti > > 2 > > 1.019 > > 0 > > 0.602 > > 8 > > 84 > > 5.237 > > 20 > > 2.621 > > Ear > > > 42 > > 1.57 > > Vti > > 1 > > 0.913 > > 0 > > 0.954 > > 6 > > 137 > > 5.038 > > 12 > > 3.492 > > Qco > > > 43 > > 1.77 > > Vti > > 3 > > 0.737 > > 0 > > 0.954 > > 6 > > 141 > > 5.026 > > 16 > > 3.371 > > Qco > > > 44 > > 0.17 > > Vti > > 2 > > 0.913 > > 0 > > 1.000 > > 8 > > 69 > > 4.901 > > 24 > > 3.258 > > Qco > > > 45 > > 0.41 > > Vti > > 3 > > 1.092 > > 2 > > 0.954 > > 8 > > 81 > > 5.129 > > 44 > > 4.457 > > Qfa > > > 46 > > 2.62 > > Vti > > 1 > > 0.913 > > 0 > > 0.845 > > 4 > > 114 > > 5.047 > > 34 > > 4.457 > > Ear > > > 47 > > 0.09 > > Vti > > 3 > > 0.975 > > 2 > > 0.954 > > 8 > > 98 > > 4.924 > > 20 > > 3.492 > > Aun > > > 48 > > 0.12 > > Vti > > 4 > > 1.311 > > 5 > > 0.845 > > 8 > > 78 > > 4.748 > > 26 > > 3.761 > > Aun > > > 49 > > 1.70 > > Vti > > 3 > > 0.975 > > 2 > > 1.000 > > 8 > > 95 > > 5.146 > > 36 > > 4.457 > > Qfa > > > 50 > > 14.49 > > Qfa > > 1 > > 1.719 > > 0 > > 0.778 > > 6 > > 37 > > 2.962 > > 32 > > 1.766 > > Pan > > > 51 > > 0.09 > > Vti > > 2 > > 1.311 > > 0 > > 0.778 > > 6 > > 56 > > 2.872 > > 20 > > 1.950 > > Pan > > > 52 > > 2.12 > > Qfa > > 2 > > 1.460 > > 0 > > 0.845 > > 6 > > 203 > > 3.097 > > 18 > > 3.152 > > Vti > > > 53 > > 0.23 > > Qfa > > 2 > > 1.238 > > 2 > > 0.778 > > 8 > > 86 > > 2.190 > > 30 > > 2.476 > > Ear > > > 54 > > 5.36 > > Qfa > > 2 > > 0.975 > > 0 > > 0.954 > > 6 > > 134 > > 3.409 > > 42 > > 4.684 > > Vti > > > 55 > > 0.41 > > Vti > > 2 > > 1.145 > > 5 > > 0.845 > > 6 > > 108 > > 3.890 > > 36 > > 4.945 > > Qco > > > 56 > > 0.19 > > Vti > > 1 > > 1.719 > > 0 > > 0.845 > > 6 > > 42 > > 4.130 > > 35 > > 3.492 > > Qco > > > 57 > > 15.59 > > Vti > > 3 > > 1.719 > > 0 > > 1.114 > > 6 > > 91 > > 4.386 > > 16 > > 4.257 > > Ear > > > 58 > > 3.25 > > Vti > > 3 > > 1.719 > > 0 > > 0.903 > > 6 > > 85 > > 4.275 > > 36 > > 4.257 > > Ear > > > 59 > > 2.32 > > Vti > > 3 > > 1.460 > > 0 > > 0.954 > > 6 > > 91 > > 4.223 > > 32 > > 4.257 > > Ear > > > 60 > > 4.24 > > Vti > > 3 > > 1.719 > > 0 > > 1.041 > > 6 > > 36 > > 4.386 > > 42 > > 4.257 > > Ear > > > 61 > > 31.49 > > Vti > > 3 > > 1.719 > > 0 > > 1.176 > > 6 > > 78 > > 4.371 > > 43 > > 4.257 > > Ear > > > 62 > > 2.97 > > Vti > > 3 > > 0.786 > > 2 > > 0.954 > > 6 > > 71 > > 3.988 > > 22 > > 4.076 > > Qco > > > 63 > > 0.50 > > Vti > > 3 > > 0.706 > > 2 > > 0.903 > > 6 > > 76 > > 4.134 > > 20 > > 4.076 > > Qco > > > 64 > > 20.20 > > Vti > > 2 > > 1.719 > > 0 > > 1.079 > > 6 > > 62 > > 3.557 > > 18 > > 5.640 > > Qfa > > > 65 > > 0.12 > > Vti > > 1 > > 1.460 > > 0 > > 0.903 > > 6 > > 75 > > 3.186 > > 20 > > 3.152 > > Qfa > > > 66 > > 0.10 > > Vti > > 1 > > 1.719 > > 0 > > 0.903 > > 6 > > 90 > > 3.154 > > 20 > > 3.152 > > Qfa > > > 67 > > 0.79 > > Vti > > 1 > > 1.719 > > 0 > > 0.954 > > 6 > > 64 > > 3.154 > > 12 > > 3.152 > > Ear > > > 68 > > 0.17 > > Vti > > 1 > > 1.719 > > 0 > > 0.954 > > 6 > > 52 > > 3.186 > > 24 > > 3.152 > > Ear > > > 69 > > 0.09 > > Qfa > > 1 > > 0.589 > > 0 > > 0.477 > > 4 > > 55 > > 3.540 > > 32 > > 3.492 > > Ear > > > 70 > > 1.02 > > Vti > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 107 > > 3.816 > > 38 > > 3.911 > > Aun > > > 71 > > 12.67 > > Qfa > > 2 > > 1.719 > > 0 > > 0.954 > > 6 > > 62 > > 3.282 > > 32 > > 4.457 > > Aun > > > 72 > > 32.80 > > Qfa > > 2 > > 1.719 > > 0 > > 0.699 > > 6 > > 56 > > 2.962 > > 32 > > 4.076 > > Aun > > > 73 > > 26.64 > > Qfa > > 2 > > 1.719 > > 0 > > 0.699 > > 6 > > 76 > > 2.893 > > 32 > > 4.076 > > Aun > > > 74 > > 0.09 > > Vti > > 3 > > 1.460 > > 0 > > 0.845 > > 6 > > 110 > > 3.851 > > 24 > > 4.684 > > Aun > > > 75 > > 103.14 > > Qfa > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 124 > > 3.703 > > 28 > > 4.257 > > Aun > > > 76 > > 0.09 > > Vti > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 156 > > 3.637 > > 26 > > 4.257 > > Aun > > > 77 > > 248.11 > > Qfa > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 144 > > 3.807 > > 33 > > 4.257 > > Aun > > > 78 > > 2.19 > > Vti > > 3 > > 1.311 > > 0 > > 1.000 > > 8 > > 63 > > 3.458 > > 28 > > 4.257 > > Aun > > > 79 > > 29.90 > > Vti > > 1 > > 1.719 > > 0 > > 1.000 > > 6 > > 46 > > 2.711 > > 30 > > 3.621 > > Qsu > > > 80 > > 17.81 > > Ral > > 2 > > 1.460 > > 0 > > 1.000 > > 8 > > 55 > > 4.516 > > 10 > > 4.945 > > Aun > > > 81 > > 0.11 > > Vti > > 2 > > 1.311 > > 0 > > 0.954 > > 6 > > 84 > > 4.189 > > 10 > > 5.640 > > Ear > > > 82 > > 0.53 > > Vti > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 23 > > 4.389 > > 24 > > 4.945 > > Ear > > > 83 > > 10.30 > > Ral > > 3 > > 1.460 > > 0 > > 0.903 > > 8 > > 42 > > 4.843 > > 20 > > 5.640 > > Qco > > > 84 > > 41.56 > > Vti > > 2 > > 1.460 > > 0 > > 0.778 > > 6 > > 74 > > 4.008 > > 40 > > 5.254 > > Qfa > > > 85 > > 11.52 > > Qfa > > 2 > > 1.719 > > 0 > > 0.845 > > 8 > > 77 > > 3.611 > > 34 > > 5.640 > > Aun > > > 86 > > 113.61 > > Qfa > > 3 > > 1.719 > > 0 > > 1.000 > > 6 > > 46 > > 2.795 > > 28 > > 4.945 > > Ear > > > 87 > > 0.09 > > Vti > > 2 > > 1.145 > > 0 > > 0.778 > > 6 > > 96 > > 3.505 > > 34 > > 6.176 > > Qfa > > > 88 > > 7.63 > > Ral > > 3 > > 1.719 > > 0 > > 0.845 > > 6 > > 45 > > 3.344 > > 38 > > 5.254 > > Vti > > > 89 > > 0.09 > > Vti > > 2 > > 0.913 > > 0 > > 0.602 > > 6 > > 66 > > 3.980 > > 22 > > 4.945 > > Aun > > > 90 > > 98.52 > > Qfa > > 2 > > 1.719 > > 0 > > 0.602 > > 6 > > 65 > > 3.924 > > 24 > > 4.945 > > Aun > > > 91 > > 6.41 > > Qfa > > 1 > > 0.291 > > 60 > > 0.845 > > 6 > > 121 > > 3.500 > > 30 > > 3.152 > > Aun > > > 92 > > 0.47 > > Vti > > 1 > > 1.019 > > 5 > > 0.602 > > 6 > > 107 > > 4.380 > > 22 > > 3.152 > > Ear > > > 93 > > 0.14 > > Vti > > 1 > > 1.145 > > 5 > > 0.699 > > 6 > > 56 > > 4.288 > > 28 > > 4.457 > > Aun > > > 94 > > 1.98 > > Vti > > 1 > > 1.145 > > 5 > > 0.602 > > 6 > > 75 > > 4.325 > > 28 > > 4.457 > > Aun > > > 95 > > 6.41 > > Vti > > 1 > > 0.460 > > 50 > > 0.778 > > 6 > > 60 > > 4.559 > > 20 > > 4.257 > > Ear > > > 96 > > 3.53 > > Vti > > 1 > > 0.523 > > 45 > > 0.778 > > 6 > > 127 > > 4.559 > > 22 > > 4.257 > > Ear > > > 97 > > 0.57 > > Vti > > 1 > > 0.523 > > 40 > > 0.699 > > 6 > > 90 > > 4.500 > > 30 > > 4.257 > > Ear > > > 98 > > 2.76 > > Vti > > 1 > > 0.345 > > 60 > > 0.602 > > 6 > > 116 > > 4.598 > > 22 > > 4.257 > > Ear > > > 99 > > 1.70 > > Vti > > 1 > > 0.240 > > 70 > > 0.954 > > 6 > > 76 > > 4.644 > > 36 > > 3.258 > > Ear > > > 100 > > 0.91 > > Vti > > 1 > > 0.240 > > 70 > > 0.954 > > 6 > > 81 > > 4.724 > > 35 > > 3.258 > > Ear > > > 101 > > 18.65 > > Vti > > 1 > > 0.523 > > 45 > > 0.903 > > 6 > > 57 > > 4.780 > > 30 > > 3.258 > > Qco > > > 102 > > 0.16 > > Vti > > 1 > > 1.719 > > 0 > > 0.845 > > 4 > > 79 > > 4.845 > > 40 > > 5.640 > > Aun > > > 103 > > 0.09 > > Vti > > 2 > > 1.719 > > 0 > > 0.602 > > 6 > > 103 > > 4.538 > > 30 > > 4.076 > > Ear > > > 104 > > 1.63 > > Vti > > 1 > > 1.719 > > 0 > > 0.778 > > 6 > > 84 > > 4.540 > > 36 > > 4.257 > > Ear > > > 105 > > 15.51 > > Vti > > 1 > > 1.460 > > 2 > > 0.602 > > 6 > > 102 > > 4.601 > > 30 > > 4.257 > > Ear > > > 106 > > 2.26 > > Vti > > 2 > > 1.719 > > 0 > > 0.699 > > 6 > > 72 > > 4.593 > > 38 > > 4.257 > > Ear > > > 107 > > 8.92 > > Vti > > 2 > > 1.311 > > 5 > > 1.041 > > 6 > > 99 > > 4.646 > > 28 > > 4.257 > > Ear > > > 108 > > 5.64 > > Qsu > > 2 > > 1.311 > > 0 > > 0.699 > > 6 > > 101 > > 5.140 > > 36 > > 4.257 > > Ear > > > 109 > > 0.41 > > Vti > > 2 > > 1.354 > > 2 > > 0.845 > > 6 > > 51 > > 4.530 > > 36 > > 4.945 > > Ear > > > 110 > > 2.47 > > Vti > > 1 > > 1.460 > > 0 > > 0.602 > > 4 > > 69 > > 4.791 > > 28 > > 5.640 > > Ear > > > 111 > > 147.78 > > Vti > > 1 > > 1.145 > > 5 > > 0.778 > > 8 > > 32 > > 4.176 > > 28 > > 4.945 > > Qfa > > > 112 > > 18.94 > > Vti > > 2 > > 1.311 > > 5 > > 0.903 > > 8 > > 31 > > 4.252 > > 44 > > 4.945 > > Ear > > > 113 > > 18.66 > > Vti > > 1 > > 0.913 > > 20 > > 0.778 > > 8 > > 54 > > 4.023 > > 38 > > 4.257 > > Ear > > > 114 > > 0.44 > > Vti > > 1 > > 1.311 > > 5 > > 0.602 > > 8 > > 38 > > 4.127 > > 28 > > 4.945 > > Qfa > > > 115 > > 3.53 > > Vti > > 2 > > 1.311 > > 5 > > 0.845 > > 8 > > 39 > > 4.179 > > 30 > > 4.945 > > Ear > > > 116 > > 0.57 > > Vti > > 2 > > 0.913 > > 10 > > 0.845 > > 6 > > 103 > > 4.141 > > 40 > > 5.640 > > Ear > > > 117 > > 0.09 > > Vti > > 1 > > 1.460 > > 0 > > 0.602 > > 4 > > 53 > > 4.798 > > 23 > > 5.640 > > Ear > > > 118 > > 1.51 > > Vti > > 2 > > 1.145 > > 0 > > 0.778 > > 6 > > 20 > > 2.748 > > 18 > > 4.684 > > Qfa > > > 119 > > 187.80 > > Vti > > 2 > > 0.401 > > 0 > > 1.079 > > 6 > > 0 > > 2.483 > > 0 > > 4.684 > > Qfa > > > 120 > > 7.89 > > Vti > > 2 > > 1.311 > > 0 > > 0.845 > > 8 > > 53 > > 3.054 > > 46 > > 3.911 > > Qfa > > > 121 > > 18.06 > > Vti > > 2 > > 1.311 > > 0 > > 0.845 > > 8 > > 58 > > 3.303 > > 32 > > 6.176 > > Qco > > > 122 > > 0.16 > > Vti > > 2 > > 1.311 > > 0 > > 0.903 > > 8 > > 37 > > 3.323 > > 46 > > 6.176 > > Qco > > > 123 > > 0.09 > > Vti > > 2 > > 1.311 > > 0 > > 1.000 > > 8 > > 21 > > 3.253 > > 32 > > 6.176 > > Qco > > > 124 > > 4.65 > > Ral > > 2 > > 1.719 > > 0 > > 0.602 > > 8 > > 31 > > 4.583 > > 38 > > 6.176 > > Qfa > > > 125 > > 1.76 > > Vti > > 1 > > 0.913 > > 0 > > 0.845 > > 4 > > 53 > > 3.018 > > 34 > > 5.640 > > Qfa > > > 126 > > 1.82 > > Vti > > 1 > > 0.913 > > 0 > > 0.903 > > 4 > > 40 > > 2.943 > > 38 > > 5.640 > > Qfa > > > 127 > > 81.71 > > Vti > > 1 > > 1.019 > > 0 > > 0.954 > > 4 > > 74 > > 2.839 > > 36 > > 3.492 > > Qfa > > > 128 > > 0.60 > > Vti > > 1 > > 1.311 > > 0 > > 0.845 > > 4 > > 78 > > 3.045 > > 34 > > 3.492 > > Qfa > > > 129 > > 3.52 > > Vti > > 1 > > 1.019 > > 5 > > 0.602 > > 4 > > 48 > > 3.268 > > 12 > > 2.699 > > Qfa > > > 130 > > 1.84 > > Vti > > 1 > > 0.660 > > 5 > > 0.602 > > 4 > > 81 > > 3.415 > > 38 > > 2.699 > > Qfa > > > 131 > > 9.03 > > Qsu > > 2 > > 1.311 > > 0 > > 0.845 > > 4 > > 23 > > 3.383 > > 30 > > 2.343 > > Qfa > > > 132 > > 7.33 > > Qsu > > 2 > > 0.821 > > 0 > > 0.778 > > 4 > > 48 > > 3.000 > > 10 > > 2.000 > > Qfa > > > 133 > > 0.57 > > Vti > > 2 > > 0.821 > > 0 > > 0.699 > > 4 > > 57 > > 3.476 > > 16 > > 2.000 > > Qfa > > > 134 > > 5.23 > > Vti > > 2 > > 1.019 > > 0 > > 0.903 > > 4 > > 78 > > 3.899 > > 30 > > 3.761 > > Qco > > > 135 > > 0.13 > > Vti > > 2 > > 1.145 > > 0 > > 0.778 > > 4 > > 77 > > 3.924 > > 20 > > 3.761 > > Qco > > > 136 > > 8.38 > > Vti > > 1 > > 1.719 > > 0 > > 0.699 > > 2 > > 23 > > 3.317 > > 30 > > 1.165 > > Qsu > > > 137 > > 1.98 > > Vti > > 1 > > 1.311 > > 0 > > 0.778 > > 2 > > 33 > > 3.421 > > 14 > > 1.165 > > Qsu > > > 138 > > 3.24 > > Vti > > 1 > > 1.019 > > 0 > > 0.845 > > 2 > > 48 > > 3.488 > > 24 > > 1.165 > > Qsu > > > 139 > > 0.60 > > Vti > > 1 > > 0.660 > > 0 > > 0.778 > > 2 > > 57 > > 3.494 > > 22 > > 1.165 > > Qsu > > > 140 > > 0.09 > > Vti > > 1 > > 0.345 > > 2 > > 0.699 > > 2 > > 78 > > 3.658 > > 0 > > 1.165 > > Qsu > > > 141 > > 0.16 > > Qsu > > 1 > > 0.345 > > 0 > > 0.699 > > 2 > > 89 > > 2.850 > > 0 > > 1.165 > > Qfa > > > 142 > > 0.14 > > Vti > > 2 > > 0.523 > > 0 > > 0.845 > > 2 > > 62 > > 4.179 > > 30 > > 2.000 > > Qfa > > > 143 > > 0.47 > > Vti > > 2 > > 0.913 > > 0 > > 0.954 > > 2 > > 18 > > 4.000 > > 24 > > 2.000 > > Qfa > > > 144 > > 5.65 > > Vti > > 2 > > 1.311 > > 5 > > 0.845 > > 4 > > 49 > > 3.851 > > 28 > > 2.343 > > Qfa > > > 145 > > 0.85 > > Qsu > > 1 > > 0.821 > > 5 > > 0.778 > > 4 > > 47 > > 3.268 > > 24 > > 1.902 > > Qfa > > > 146 > > 0.85 > > Vti > > 2 > > 0.913 > > 5 > > 0.699 > > 6 > > 16 > > 3.071 > > 38 > > 4.076 > > Ear > > > 147 > > 0.66 > > Vti > > 2 > > 1.019 > > 5 > > 0.845 > > 6 > > 51 > > 2.943 > > 36 > > 4.076 > > Ear > > > 148 > > 0.11 > > Vti > > 2 > > 1.311 > > 0 > > 0.699 > > 6 > > 65 > > 2.882 > > 32 > > 4.076 > > Ear > > > 149 > > 0.09 > > Vti > > 2 > > 1.719 > > 0 > > 0.699 > > 4 > > 29 > > 3.642 > > 24 > > 6.176 > > Aun > > > 150 > > 134.70 > > Qfa > > 2 > > 1.719 > > 0 > > 0.699 > > 4 > > 69 > > 3.330 > > 24 > > 2.264 > > Ear > > > 151 > > 1.63 > > Aun > > 2 > > 1.019 > > 10 > > 0.602 > > 4 > > 56 > > 3.122 > > 28 > > 4.945 > > Vti > > > 152 > > 3.04 > > Vti > > 1 > > 0.821 > > 25 > > 0.699 > > 4 > > 150 > > 3.170 > > 30 > > 5.254 > > Ear > > > 153 > > 7.63 > > Qsu > > 1 > > 0.523 > > 40 > > 0.778 > > 4 > > 53 > > 3.829 > > 24 > > 4.945 > > Vti > > > 154 > > 0.97 > > Aun > > 3 > > 0.821 > > 15 > > 0.699 > > 4 > > 55 > > 3.446 > > 34 > > 4.457 > > Ear > > > 155 > > 87.46 > > Aun > > 1 > > 1.019 > > 10 > > 0.845 > > 4 > > 48 > > 2.806 > > 0 > > 2.956 > > Qsu > > > 156 > > 1.77 > > Qsu > > 2 > > 1.019 > > 10 > > 0.903 > > 4 > > 66 > > 2.882 > > 28 > > 2.956 > > Aun > > > 157 > > 1.17 > > Qsu > > 2 > > 0.913 > > 20 > > 0.699 > > 4 > > 39 > > 3.114 > > 30 > > 2.781 > > Aun > > > 158 > > 4.27 > > Qsu > > 1 > > 0.913 > > 0 > > 0.699 > > 4 > > 36 > > 2.604 > > 28 > > 1.902 > > Vti > > > 159 > > 43.20 > > Qfa > > 1 > > 1.311 > > 0 > > 0.699 > > 2 > > 24 > > 3.589 > > 28 > > 2.699 > > Aun > > > 160 > > 19.85 > > Vti > > 2 > > 0.821 > > 20 > > 0.602 > > 4 > > 82 > > 3.557 > > 32 > > 3.621 > > Qfa > > > 161 > > 0.63 > > Qsu > > 2 > > 0.913 > > 15 > > 0.778 > > 4 > > 12 > > 3.434 > > 32 > > 4.457 > > Aun > > > 162 > > 0.57 > > Vti > > 2 > > 1.145 > > 0 > > 0.699 > > 4 > > 7 > > 3.080 > > 20 > > 3.492 > > Ear > > > 163 > > 0.69 > > Vti > > 2 > > 1.311 > > 0 > > 0.602 > > 4 > > 82 > > 3.784 > > 30 > > 4.684 > > Qfa > > > 164 > > 0.79 > > Vti > > 3 > > 0.821 > > 15 > > 0.778 > > 4 > > 93 > > 3.231 > > 26 > > 3.621 > > Qfa > > > 165 > > 116.24 > > Qfa > > 4 > > 1.019 > > 10 > > 0.845 > > 6 > > 96 > > 3.458 > > 26 > > 3.761 > > Ear > > > 166 > > 13.08 > > Qfa > > 2 > > 0.913 > > 20 > > 0.845 > > 6 > > 70 > > 3.337 > > 30 > > 5.254 > > Ear > > > 167 > > 13.36 > > Qfa > > 2 > > 0.821 > > 25 > > 0.845 > > 6 > > 47 > > 3.154 > > 34 > > 5.254 > > Ear > > > 168 > > 9.42 > > Qsu > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 131 > > 5.131 > > 24 > > 3.911 > > Ear > > > 169 > > 0.09 > > Vti > > 2 > > 1.460 > > 2 > > 1.000 > > 6 > > 103 > > 4.421 > > 28 > > 5.640 > > Aun > > > 170 > > 0.12 > > Ral > > 2 > > 1.311 > > 5 > > 0.954 > > 6 > > 93 > > 5.676 > > 34 > > 5.640 > > Aun > > > 171 > > 0.82 > > Vti > > 2 > > 1.145 > > 10 > > 0.954 > > 6 > > 79 > > 4.486 > > 32 > > 5.640 > > Aun > > > 172 > > 66.19 > > Vti > > 2 > > 1.019 > > 15 > > 0.845 > > 6 > > 25 > > 4.829 > > 24 > > 4.457 > > Ear > > > 173 > > 8.12 > > Vti > > 2 > > 1.092 > > 10 > > 0.845 > > 6 > > 27 > > 4.768 > > 8 > > 4.457 > > Ear > > > 174 > > 0.75 > > Vti > > 2 > > 1.145 > > 10 > > 0.845 > > 6 > > 29 > > 4.873 > > 36 > > 3.621 > > Ear > > > 175 > > 4.49 > > Qsu > > 2 > > 1.145 > > 10 > > 1.000 > > 6 > > 22 > > 5.547 > > 36 > > 3.051 > > Ear > > > 176 > > 0.17 > > Vti > > 1 > > 0.589 > > 20 > > 0.301 > > 6 > > 9 > > 5.297 > > 54 > > 3.911 > > Ear > > > 177 > > 4.12 > > Vti > > 2 > > 1.145 > > 10 > > 0.845 > > 6 > > 20 > > 5.534 > > 36 > > 3.371 > > Ear > > > 178 > > 1.34 > > Vti > > 2 > > 1.145 > > 10 > > 0.778 > > 6 > > 49 > > 5.562 > > 36 > > 3.371 > > Ear > > > 179 > > 1.48 > > Vti > > 1 > > 1.145 > > 10 > > 0.699 > > 6 > > 34 > > 5.574 > > 38 > > 3.258 > > Aun > > > 180 > > 3.82 > > Aun > > 2 > > 1.719 > > 0 > > 0.699 > > 6 > > 54 > > 3.500 > > 38 > > 5.254 > > Ear > > > 181 > > 15.59 > > Aun > > 2 > > 1.460 > > 2 > > 0.000 > > 6 > > 66 > > 3.383 > > 25 > > 5.254 > > Ear > > > 182 > > 0.66 > > Aun > > 2 > > 1.719 > > 0 > > 0.954 > > 6 > > 79 > > 3.452 > > 28 > > 5.254 > > Ear > > > 183 > > 0.16 > > Vti > > 2 > > 1.719 > > 0 > > 0.699 > > 6 > > 89 > > 5.911 > > 22 > > 5.254 > > Ear > > > 184 > > 0.16 > > Ral > > 1 > > 1.460 > > 2 > > 0.845 > > 6 > > 21 > > 5.713 > > 22 > > 4.684 > > Ear > > > 185 > > 0.11 > > Vti > > 1 > > 1.311 > > 5 > > 0.954 > > 6 > > 14 > > 5.285 > > 16 > > 4.684 > > Ear > > > 186 > > 0.42 > > Vti > > 1 > > 1.311 > > 5 > > 0.845 > > 6 > > 14 > > 5.259 > > 22 > > 4.684 > > Ear > > > 187 > > 0.38 > > Vti > > 2 > > 1.719 > > 0 > > 0.477 > > 6 > > 34 > > 5.201 > > 38 > > 5.254 > > Ear > > > 188 > > 0.09 > > Vti > > 2 > > 1.719 > > 0 > > 0.845 > > 6 > > 52 > > 5.123 > > 26 > > 4.684 > > Qco > > > 189 > > 0.41 > > Vti > > 1 > > 1.719 > > 0 > > 0.845 > > 6 > > 71 > > 5.078 > > 28 > > 5.254 > > Ear > > > 190 > > 2.97 > > Vti > > 1 > > 1.311 > > 5 > > 0.477 > > 6 > > 72 > > 5.082 > > 22 > > 3.911 > > Ear > > > 191 > > 0.13 > > Vti > > 1 > > 0.913 > > 10 > > 0.845 > > 6 > > 63 > > 5.138 > > 30 > > 3.911 > > Ear > > > 192 > > 0.09 > > Vti > > 1 > > 1.092 > > 2 > > 0.602 > > 6 > > 43 > > 5.158 > > 36 > > 3.911 > > Ear > > > 193 > > 0.75 > > Qsu > > 2 > > 0.913 > > 10 > > 0.699 > > 6 > > 30 > > 4.970 > > 26 > > 5.254 > > Ear > > > 194 > > 1.04 > > Aun > > 2 > > 1.311 > > 5 > > 0.903 > > 6 > > 98 > > 2.115 > > 20 > > 4.945 > > Ear > > > 195 > > 0.09 > > Vti > > 2 > > 0.821 > > 15 > > 0.778 > > 6 > > 13 > > 5.513 > > 26 > > 4.945 > > Ear > > > 196 > > 6.79 > > Vti > > 2 > > 1.019 > > 10 > > 0.778 > > 6 > > 67 > > 4.649 > > 30 > > 2.220 > > Qco > > > 197 > > 4.90 > > Vti > > 2 > > 1.145 > > 5 > > 0.699 > > 6 > > 78 > > 4.862 > > 38 > > 2.956 > > Qfa > > > 198 > > 11.39 > > Vti > > 2 > > 0.737 > > 10 > > 0.602 > > 6 > > 79 > > 4.947 > > 42 > > 4.257 > > Qco > > > 199 > > 1.45 > > Vti > > 2 > > 0.913 > > 20 > > 0.699 > > 6 > > 74 > > 4.996 > > 44 > > 4.257 > > Qco > > > 200 > > 0.85 > > Vti > > 2 > > 1.719 > > 0 > > 0.699 > > 8 > > 18 > > 4.924 > > 36 > > 2.162 > > Ear > > > 201 > > 0.85 > > Vti > > 3 > > 1.719 > > 0 > > 0.778 > > 8 > > 12 > > 4.964 > > 38 > > 2.162 > > Ear > > > 202 > > 0.69 > > Vti > > 3 > > 1.719 > > 0 > > 0.845 > > 8 > > 23 > > 4.931 > > 30 > > 2.162 > > Ear > > > > > > . where I could not really find any mistake.. > > > > Hope some one can please help me on this. > > > > Regards, > > Sara Mouro > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.htmlPetr Pikal petr.pikal at precheza.cz
Sara,
You didn't read your data into R correctly.
If your data are really in the form you posted (one long column
of mixed data types and lots of blank lines), then I would:
1. remove the blank lines with my text editor and save (say, mydata.txt)
2. scan() the variable names into a vector
nm <- scan("mydata.txt", what = "", nlines = 13)
3. scan() the data values into a list
x <- scan("mydata.txt",
what = list(0,0,"",0,0,0,0,0,0,0,0,0,""),
skip = 13)
4. attach the names
names(x) <- nm
5. convert to data frame
DF <- data.frame(x)
(You really shouldn't post your whole data set; a couple of records
would have been sufficient.)
Peter Ehlers
Sara Mouro wrote:> Dear all,
>
>
>
> Does any one knows why should I get the following error message, when
trying
> to do a simple data.frame??
>
>
>
>
DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS
> p,DSSp,Slope, CanDens,NearestSp)
>
>
>
> Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, :
>
> arguments imply differing number of rows: 202, 0
>
>
>
>
>
> The data I am using is:
>
>
>
>
> Subject
>
> BiomR
>
> Spp
>
> Capas
>
> Litter
>
> Herbs
>
> LitterD
>
> MaxCanH
>
> DDifSp
>
> DSSp
>
> Slope
>
> CanDens
>
> NearestSp
>
>
> 1
>
> 140.74
>
> Qfa
>
> 2
>
> 1.460
>
> 0
>
> 0.778
>
> 8
>
> 70
>
> 3.663
>
> 28
>
> 2.280
>
> Ear
>
>
> 2
>
> 7.26
>
> Aun
>
> 2
>
> 0.660
>
> 0
>
> 0.477
>
> 8
>
> 110
>
> 3.988
>
> 34
>
> 2.476
>
> Ear
>