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igf.txt
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igf.txt
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id sex age weight height ethnicity igfi igfbp3 als pinp ictp p3np
1 Female 15 42 162 Asian 189.000 4.00000 323.667 353.970 11.2867 8.3367
2 Male 16 44 160 Caucasian 160.000 3.75000 333.750 375.885 10.4300 6.7450
3 Female 15 43 157 Asian 146.833 3.43333 248.333 199.507 8.3633 12.5000
4 Female 15 42 155 Asian 185.500 3.40000 251.000 483.607 13.3300 14.2767
5 Female 16 47 167 Asian 192.333 4.23333 322.000 105.430 7.9233 4.5033
6 Female 25 45 160 Asian 110.000 3.50000 284.667 76.487 4.9833 4.9367
7 Female 19 45 161 Asian 157.000 3.20000 274.000 75.880 6.3500 5.3200
8 Female 18 43 153 Asian 146.000 3.40000 303.000 86.360 7.3700 4.6700
9 Female 15 41 149 Asian 197.667 3.56667 308.500 254.803 11.8700 6.8200
10 Female 24 45 157 African 148.000 3.40000 273.000 44.720 3.7400 6.1600
11 Female 26 45 159 Asian 105.333 3.30000 295.333 78.500 4.7167 5.3467
12 Male 15 47 164 Asian 162.000 3.50000 287.333 742.680 21.2367 13.8867
13 Female 15 43 150 Asian 170.000 3.15000 254.500 111.753 7.3133 6.1433
14 Male 15 46 162 Asian 192.000 3.30000 305.000 548.313 13.5300 9.9433
15 Female 19 48 168 Caucasian 314.500 4.75000 381.750 85.990 5.8050 3.7400
16 Female 15 48 165 Caucasian 334.000 3.80000 312.000 154.700 11.4700 5.3950
17 Female 20 45 156 Asian 125.667 3.53333 281.500 67.910 4.8900 4.3300
18 Female 22 46 157 Caucasian 100.167 2.76667 249.000 70.643 5.2300 4.6800
19 Female 20 45 154 Asian 165.000 3.76667 234.000 77.327 4.2200 4.4233
20 Female 21 46 157 Caucasian 145.000 3.30000 303.000 44.560 4.9300 5.5900
21 Female 18 45 155 Asian 161.667 3.10000 300.333 148.117 7.3200 4.8600
22 Male 14 49 166 Asian 164.500 3.50000 251.333 585.180 16.5467 13.5167
23 Female 16 44 153 Asian 177.333 3.90000 299.000 126.970 7.3667 7.1367
24 Female 14 47 162 Asian 161.333 3.36667 312.000 115.260 8.7733 8.7933
25 Male 15 46 158 Asian 160.333 3.45000 277.000 474.643 16.8133 10.3450
26 Male 26 48 160 Caucasian 165.333 3.66667 290.667 76.027 3.7533 4.3833
27 Female 34 51 170 African 148.667 3.36667 235.333 26.740 3.6267 4.2167
28 Female 19 46 155 Caucasian 164.000 4.40000 420.000 89.890 5.5250 5.5967
29 Female 18 48 162 Asian 186.167 3.13333 227.000 74.113 5.4000 5.5867
30 Male 22 48 162 African 149.000 3.60000 285.333 170.193 8.1200 6.4900
31 Female 24 60 196 African 185.167 3.86667 281.667 88.927 4.9733 5.1433
32 Female 25 53 178 Caucasian 168.333 4.00000 307.667 82.660 4.3767 5.8933
33 Female 19 51 170 Caucasian 162.500 3.73333 419.333 73.013 5.3233 4.3800
34 Male 17 51 169 Asian 141.833 3.80000 251.667 360.983 11.8333 9.6633
35 Male 15 47 158 Asian 155.500 3.43333 246.667 544.207 12.3367 10.5400
36 Female 24 51 166 Caucasian 106.000 3.85000 282.375 30.120 3.8975 3.6333
37 Male 19 59 191 Caucasian 187.333 3.96667 317.667 153.917 8.3433 5.1367
38 Female 24 47 156 Caucasian 188.500 3.20000 250.000 69.260 3.7900 3.8100
39 Female 18 50 164 Asian 137.333 3.80000 253.000 64.710 4.4267 6.5067
40 Male 16 53 172 Asian 190.000 3.60000 297.500 554.417 15.4933 10.3300
41 Female 18 48 159 Asian 136.667 3.03333 262.333 178.513 6.6633 5.4500
42 Female 16 47 155 Asian 216.500 3.40000 314.667 131.797 7.1433 7.1800
43 Female 16 50 165 Asian 181.167 3.36667 262.000 201.703 8.4933 8.6600
44 Male 14 47 156 Asian 204.333 3.70000 276.000 662.400 16.0200 16.3033
45 Female 21 50 162 Asian 130.000 3.33333 263.833 59.490 5.1867 6.3500
46 Female 21 51 164 Asian 109.333 2.90000 204.333 114.100 5.5367 3.7833
47 Female 19 48 155 Caucasian 138.000 3.80000 369.500 60.313 6.1200 3.9767
48 Female 18 53 170 Caucasian 227.500 4.25000 433.000 110.905 7.9150 5.4550
49 Female 21 54 173 Caucasian 163.333 5.10000 407.000 38.093 4.5733 4.6833
50 Female 13 49 160 Asian 427.000 4.06667 361.667 502.050 13.6333 14.4200
51 Male 24 54 173 African 94.667 2.60000 192.667 109.073 4.2100 5.4400
52 Female 25 50 163 African 98.667 2.93333 209.667 65.407 3.8300 3.2267
53 Female 22 50 163 Asian 101.000 3.16667 255.000 101.397 7.3267 7.9667
54 Male 17 51 164 Caucasian 149.500 3.70000 341.000 137.583 7.6833 5.4333
55 Male 20 50 161 Asian 139.000 3.56667 280.000 148.070 5.4167 5.1500
56 Male 14 51 164 Asian 160.333 3.20000 267.333 380.737 13.5033 10.0767
57 Male 16 51 164 Asian 154.667 3.40000 248.333 462.213 14.0867 11.7367
58 Female 21 50 159 Asian 165.000 3.26667 304.000 90.647 6.3267 5.0967
59 Female 21 51 162 Asian 171.333 3.83333 372.000 42.897 5.0533 4.9200
60 Female 22 50 160 Asian 138.333 3.16667 328.333 31.370 3.6833 3.6900
61 Female 17 52 165 Caucasian 178.833 4.00000 370.000 124.537 7.3367 5.4100
62 Female 18 54 169 Caucasian 221.667 4.56667 471.667 70.307 5.8667 4.5000
63 Male 25 55 172 African 135.000 2.50000 225.000 56.280 4.8200 4.8200
64 Female 21 49 156 Asian 132.667 4.20000 282.000 70.790 4.8433 3.9733
65 Male 15 51 163 Caucasian 188.500 3.95000 366.500 212.250 8.0150 5.5650
66 Male 17 49 155 Caucasian 166.500 4.05000 340.000 195.425 8.5550 7.1400
67 Female 14 53 168 Caucasian 239.333 4.63333 360.333 233.117 8.1333 8.2533
68 Female 27 55 173 Caucasian 122.000 3.93333 277.000 96.403 3.0633 4.5167
69 Female 23 49 155 Asian 127.667 3.00000 222.333 60.943 4.1900 4.3367
70 Male 16 51 162 Asian 145.333 3.23333 253.667 319.290 11.5567 9.2733
71 Female 16 50 158 Asian 188.000 3.80000 309.000 147.020 8.4000 6.8100
72 Female 15 47 151 Asian 172.167 3.10000 280.667 121.030 6.4033 4.4033
73 Male 16 55 174 Asian 195.667 3.03333 235.000 438.540 19.5800 9.0067
74 Male 23 52 166 Asian 129.000 3.16667 339.000 112.533 4.2300 3.9900
75 Female 26 56 174 Caucasian 85.714 3.84286 313.571 32.723 4.6933 3.9817
76 Male 27 53 165 Caucasian 138.333 3.16667 244.333 60.483 4.6400 3.3900
77 Male 18 53 165 Others 274.000 4.50000 388.667 245.923 9.8433 7.8533
78 Female 20 53 164 Asian 116.667 2.96667 255.167 73.790 4.9567 5.2333
79 Female 19 51 160 Asian 222.000 3.60000 390.333 95.453 6.4400 5.0067
80 Female 20 53 165 Asian 161.333 3.70000 302.000 52.140 4.1533 4.2067
81 Female 19 55 170 Asian 152.000 3.33333 257.333 56.693 4.6133 4.0433
82 Female 18 55 170 Asian 142.000 3.50000 302.667 70.810 5.0333 4.9533
83 Female 19 51 160 Asian 154.667 3.60000 330.333 189.427 6.7433 5.6067
84 Female 19 51 160 Asian 194.000 3.73333 370.167 89.990 7.1600 5.7933
85 Female 18 57 176 Caucasian 172.000 4.23333 431.667 55.287 5.2200 3.7767
86 Female 25 53 165 Caucasian 124.333 5.23333 406.167 92.983 5.8350 5.9633
87 Female 23 55 169 Asian 178.333 3.83333 364.333 45.280 2.6967 3.6033
88 Male 24 50 157 African 105.000 2.00000 206.667 68.160 3.6500 4.0767
89 Female 15 53 165 Asian 96.000 3.53333 294.333 53.420 4.9433 2.3433
90 Female 19 48 150 Asian 182.333 3.43333 288.333 62.750 5.5667 6.4133
91 Female 20 49 153 Asian 176.000 4.46667 368.167 67.330 5.5867 5.5233
92 Male 19 57 175 Asian 125.333 3.03333 205.167 132.563 7.3300 5.3167
93 Male 17 56 174 Caucasian 200.333 3.90000 274.000 251.523 9.5133 6.4567
94 Female 25 52 162 Caucasian 103.000 3.50000 266.000 58.880 3.9100 3.6800
95 Male 20 53 165 Others 127.000 3.90000 328.000 122.210 6.4700 7.3100
96 Female 14 49 153 Caucasian 223.000 4.96667 383.000 222.200 9.6367 9.3567
97 Female 17 54 168 Caucasian 204.667 4.96667 441.333 64.130 5.1600 4.4367
98 Male 18 55 169 Asian 178.667 3.86667 273.000 185.913 7.5267 8.8333
99 Female 18 48 151 Asian 237.000 3.46667 324.333 105.127 5.9867 5.6600
100 Male 15 54 168 Asian 130.000 2.70000 259.333 325.840 10.2767 6.5933