def storing_data_preparation(data):
participations = etl.rowmapmany(
etl.cut(data, 'room_id', 'summary'),
rowgenerator,
header=['room_id', 'participant_id', 'start_time', 'end_time', 'role'])
rooms = etl.cut(data, 'room_id', 'created_at', 'end_time', 'creator')
return (rooms, participations)
def get_relationships(self):
"Parses a list of `Relationship` objects."
core_file = _find_loinc_table_core_file(self.uri.path)
core = etl.fromcsv(core_file, delimiter=',')
core = etl.cut(core, ['LOINC_NUM', 'LONG_COMMON_NAME'])
hierarchy_file = _find_multi_axial_hierarchy_file(self.uri.path)
hierarchy = etl.fromcsv(hierarchy_file, delimiter=',')
hierarchy = etl.leftjoin(hierarchy, core, lkey='CODE', rkey='LOINC_NUM')
hierarchy = etl.cut(hierarchy, ['IMMEDIATE_PARENT', 'CODE', 'CODE_TEXT', 'LONG_COMMON_NAME'])
hierarchy = etl.fillright(hierarchy)
hierarchy = etl.cut(hierarchy, ['IMMEDIATE_PARENT', 'CODE', 'LONG_COMMON_NAME'])
hierarchy = etl.rename(hierarchy, 'LONG_COMMON_NAME', 'CODE_TEXT')
parents = etl.cut(hierarchy, ['CODE', 'CODE_TEXT'])
hierarchy = etl.selectne(hierarchy, 'IMMEDIATE_PARENT', '')
hierarchy = etl.leftjoin(hierarchy, parents, lkey='IMMEDIATE_PARENT', rkey='CODE', lprefix='source.', rprefix='target.')
hierarchy = etl.distinct(hierarchy)
if self.versioned:
version = _parse_version(hierarchy_file)
hierarchy = etl.addfield(hierarchy, 'version', version)
hierarchy = etl.rowmapmany(hierarchy, _to_json, ['relationship'])
return hierarchy
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]]
from petl import rowmapmany, look
look(table1)
def rowgenerator(row):
transmf = {'male': 'M', 'female': 'F'}
yield [row[0], 'gender', transmf[row[1]] if row[1] in transmf else row[1]]
yield [row[0], 'age_months', row[2] * 12]
yield [row[0], 'bmi', row[4] / row[3] ** 2]
table2 = rowmapmany(table1, rowgenerator, fields=['subject_id', 'variable', 'value'])
look(table2)
# recordmapmany
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]]
from petl import recordmapmany, look
look(table1)
def rowgenerator(rec):
transmf = {'male': 'M', 'female': 'F'}
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]]
from petl import rowmapmany, look
look(table1)
def rowgenerator(row):
transmf = {'male': 'M', 'female': 'F'}
yield [row[0], 'gender', transmf[row[1]] if row[1] in transmf else row[1]]
yield [row[0], 'age_months', row[2] * 12]
yield [row[0], 'bmi', row[4] / row[3] ** 2]
table2 = rowmapmany(table1, rowgenerator, fields=['subject_id', 'variable', 'value'])
look(table2)
# recordmapmany
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]]
from petl import recordmapmany, look
look(table1)
def rowgenerator(rec):
transmf = {'male': 'M', 'female': 'F'}
def tokenize(table):
return petl.rowmapmany(table, generate_row, header=['created_at','word'])
