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
|
from __future__ import absolute_import, print_function, division
# fieldmap()
############
import petl as etl
from collections import OrderedDict
table1 = [['id', 'sex', 'age', 'height', 'weight'],
[1, 'male', 16, 1.45, 62.0],
[2, 'female', 19, 1.34, 55.4],
[3, 'female', 17, 1.78, 74.4],
[4, 'male', 21, 1.33, 45.2],
[5, '-', 25, 1.65, 51.9]]
mappings = OrderedDict()
# rename a field
mappings['subject_id'] = 'id'
# translate a field
mappings['gender'] = 'sex', {'male': 'M', 'female': 'F'}
# apply a calculation to a field
mappings['age_months'] = 'age', lambda v: v * 12
# apply a calculation to a combination of fields
mappings['bmi'] = lambda rec: rec['weight'] / rec['height']**2
# transform and inspect the output
table2 = etl.fieldmap(table1, mappings)
table2
# rowmap()
##########
import petl as etl
table1 = [['id', 'sex', 'age', 'height', 'weight'],
[1, 'male', 16, 1.45, 62.0],
[2, 'female', 19, 1.34, 55.4],
[3, 'female', 17, 1.78, 74.4],
[4, 'male', 21, 1.33, 45.2],
[5, '-', 25, 1.65, 51.9]]
def rowmapper(row):
transmf = {'male': 'M', 'female': 'F'}
return [row[0],
transmf[row['sex']] if row['sex'] in transmf else None,
row.age * 12,
row.height / row.weight ** 2]
table2 = etl.rowmap(table1, rowmapper,
fields=['subject_id', 'gender', 'age_months', 'bmi'])
table2
# rowmapmany()
##############
import petl as etl
table1 = [['id', 'sex', 'age', 'height', 'weight'],
[1, 'male', 16, 1.45, 62.0],
[2, 'female', 19, 1.34, 55.4],
[3, '-', 17, 1.78, 74.4],
[4, 'male', 21, 1.33]]
def rowgenerator(row):
transmf = {'male': 'M', 'female': 'F'}
yield [row[0], 'gender',
transmf[row['sex']] if row['sex'] in transmf else None]
yield [row[0], 'age_months', row.age * 12]
yield [row[0], 'bmi', row.height / row.weight ** 2]
table2 = etl.rowmapmany(table1, rowgenerator,
fields=['subject_id', 'variable', 'value'])
table2.lookall()
|
