ID
int64
3
767
Pregnancies
int64
0
17
Glucose
int64
44
199
BloodPressure
int64
30
122
SkinThickness
int64
7
63
Insulin
int64
14
846
BMI
float64
18.2
59.4
DiabetesPedigreeFunction
float64
0.09
2.42
Age
int64
21
72
Outcome
int64
0
1
235
4
171
72
29
155
43.6
0.479
26
1
686
3
130
64
29
155
23.1
0.314
22
0
568
4
154
72
29
126
31.3
0.338
37
0
236
7
181
84
21
192
35.9
0.586
51
1
211
0
147
85
54
155
42.8
0.375
24
0
564
0
91
80
29
155
32.4
0.601
27
0
239
0
104
76
29
155
18.4
0.582
27
0
578
10
133
68
29
155
27
0.245
36
0
382
1
109
60
8
182
25.4
0.947
21
0
368
3
81
86
16
66
27.5
0.306
22
0
342
1
121
68
35
155
32
0.389
22
0
513
2
91
62
29
155
27.3
0.525
22
0
231
6
134
80
37
370
46.2
0.238
46
1
115
4
146
92
29
155
31.2
0.539
61
1
677
0
93
60
29
155
35.3
0.263
25
0
547
4
131
68
21
166
33.1
0.16
28
0
237
0
179
90
27
155
44.1
0.686
23
1
100
1
163
72
29
155
39
1.222
33
1
528
0
117
66
31
188
30.8
0.493
22
0
126
3
120
70
30
135
42.9
0.452
30
0
290
0
78
88
29
40
36.9
0.434
21
0
609
1
111
62
13
182
24
0.138
23
0
234
3
74
68
28
45
29.7
0.293
23
0
453
2
119
72
29
155
19.6
0.832
72
0
703
2
129
72
29
155
38.5
0.304
41
0
392
1
131
64
14
415
23.7
0.389
21
0
40
3
180
64
25
70
34
0.271
26
0
324
2
112
75
32
155
35.7
0.148
21
0
147
2
106
64
35
119
30.5
1.4
34
0
150
1
136
74
50
204
37.4
0.399
24
0
662
8
167
106
46
231
37.6
0.165
43
1
371
0
118
64
23
89
32.457464
1.731
21
0
477
7
114
76
17
110
23.8
0.466
31
0
596
0
67
76
29
155
45.3
0.194
46
0
734
2
105
75
29
155
23.3
0.56
53
0
680
2
56
56
28
45
24.2
0.332
22
0
414
0
138
60
35
167
34.6
0.534
21
1
303
5
115
98
29
155
52.9
0.209
28
1
455
14
175
62
30
155
33.6
0.212
38
1
394
4
158
78
29
155
32.9
0.803
31
1
631
0
102
78
40
90
34.5
0.238
24
0
620
2
112
86
42
160
38.4
0.246
28
0
347
3
116
72
29
155
23.5
0.187
23
0
635
13
104
72
29
155
31.2
0.465
38
1
593
2
82
52
22
115
28.5
1.699
25
0
192
7
159
66
29
155
30.4
0.383
36
1
96
2
92
62
28
155
31.6
0.13
24
0
197
3
107
62
13
48
22.9
0.678
23
1
30
5
109
75
26
155
36
0.546
60
0
401
6
137
61
29
155
24.2
0.151
55
0
247
0
165
90
33
680
52.3
0.427
23
0
273
1
71
78
50
45
33.2
0.422
21
0
672
10
68
106
23
49
35.5
0.285
47
0
468
8
120
72
29
155
30
0.183
38
1
90
1
80
55
29
155
19.1
0.258
21
0
549
4
189
110
31
155
28.5
0.68
37
0
144
4
154
62
31
284
32.8
0.237
23
0
214
9
112
82
32
175
34.2
0.26
36
1
10
4
110
92
29
155
37.6
0.191
30
0
13
1
189
60
23
846
30.1
0.398
59
1
253
0
86
68
32
155
35.8
0.238
25
0
345
8
126
88
36
108
38.5
0.349
49
0
244
2
146
76
35
194
38.2
0.329
29
0
28
13
145
82
19
110
22.2
0.245
57
0
732
2
174
88
37
120
44.5
0.646
24
1
557
8
110
76
29
155
27.8
0.237
58
0
367
0
101
64
17
155
21
0.252
21
0
630
7
114
64
29
155
27.4
0.732
34
1
696
3
169
74
19
125
29.9
0.268
31
1
712
10
129
62
36
155
41.2
0.441
38
1
689
1
144
82
46
180
46.1
0.335
46
1
633
1
128
82
17
183
27.5
0.115
22
0
275
2
100
70
52
57
40.5
0.677
25
0
669
9
154
78
30
100
30.9
0.164
45
0
7
10
115
72
29
155
35.3
0.134
29
0
289
5
108
72
43
75
36.1
0.263
33
0
25
10
125
70
26
115
31.1
0.205
41
1
296
2
146
70
38
360
28
0.337
29
1
285
7
136
74
26
135
26
0.647
51
0
571
2
130
96
29
155
22.6
0.268
21
0
654
1
106
70
28
135
34.2
0.142
22
0
519
6
129
90
7
326
19.6
0.582
60
0
652
5
123
74
40
77
34.1
0.269
28
0
396
3
96
56
34
115
24.7
0.944
39
0
552
6
114
88
29
155
27.8
0.247
66
0
337
5
115
76
29
155
31.2
0.343
44
1
27
1
97
66
15
140
23.2
0.487
22
0
43
9
171
110
24
240
45.4
0.721
54
1
364
4
147
74
25
293
34.9
0.385
30
0
553
1
88
62
24
44
29.9
0.422
23
0
295
6
151
62
31
120
35.5
0.692
28
0
403
9
72
78
25
155
31.6
0.28
38
0
516
9
145
88
34
165
30.3
0.771
53
1
76
7
62
78
29
155
32.6
0.391
41
0
489
8
194
80
29
155
26.1
0.551
67
0
733
2
106
56
27
165
29
0.426
22
0
251
2
129
84
29
155
28
0.284
27
0
467
0
97
64
36
100
36.8
0.6
25
0
129
0
105
84
29
155
27.9
0.741
62
1
257
2
114
68
22
155
28.7
0.092
25
0

Dataset Card for "MuGeminorum/Pima"

The dataset originates from the National Institute of Diabetes and Digestive and Kidney Diseases and aims to predict the presence or absence of diabetes through diagnostic measurements. The dataset selection adheres to specific constraints imposed on instances drawn from a more extensive database. Notably, all patients represented in this dataset are females aged at least 21, with a Pima Indian heritage.

Maintenance

git clone git@hf.co:datasets/MuGeminorum/Pima

Usage

from datasets import load_dataset

dataset = load_dataset("MuGeminorum/Pima")

for item in dataset["train"]:
    print(item)

for item in dataset["validation"]:
    print(item)

for item in dataset["test"]:
    print(item)

Mirror

https://www.modelscope.cn/datasets/MuGeminorum/Pima

Reference

[1] Pima Indians Diabetes Database
[2] Chapter IV ‐ Medical Signal Segmentation and Classification

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