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test_reshape.py
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test_reshape.py
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from __future__ import absolute_import, print_function, division
from datetime import datetime
from petl.test.helpers import ieq
from petl.transform.reshape import melt, recast, transpose, pivot, flatten, \
unflatten
from petl.transform.regex import split, capture
def test_melt_1():
table = (('id', 'gender', 'age'),
(1, 'F', 12),
(2, 'M', 17),
(3, 'M', 16))
expectation = (('id', 'variable', 'value'),
(1, 'gender', 'F'),
(1, 'age', 12),
(2, 'gender', 'M'),
(2, 'age', 17),
(3, 'gender', 'M'),
(3, 'age', 16))
result = melt(table, key='id')
ieq(expectation, result)
# use field index as key
result = melt(table, key=0)
ieq(expectation, result)
result = melt(table, key='id', variablefield='variable', valuefield='value')
ieq(expectation, result)
def test_melt_2():
table = (('id', 'time', 'height', 'weight'),
(1, 11, 66.4, 12.2),
(2, 16, 53.2, 17.3),
(3, 12, 34.5, 9.4))
expectation = (('id', 'time', 'variable', 'value'),
(1, 11, 'height', 66.4),
(1, 11, 'weight', 12.2),
(2, 16, 'height', 53.2),
(2, 16, 'weight', 17.3),
(3, 12, 'height', 34.5),
(3, 12, 'weight', 9.4))
result = melt(table, key=('id', 'time'))
ieq(expectation, result)
expectation = (('id', 'time', 'variable', 'value'),
(1, 11, 'height', 66.4),
(2, 16, 'height', 53.2),
(3, 12, 'height', 34.5))
result = melt(table, key=('id', 'time'), variables='height')
print(result)
ieq(expectation, result)
def test_melt_empty():
table = (('foo', 'bar', 'baz'),)
expect = (('foo', 'variable', 'value'),)
actual = melt(table, key='foo')
ieq(expect, actual)
def test_melt_1_shortrow():
table = (('id', 'gender', 'age'),
(1, 'F', 12),
(2, 'M', 17),
(3, 'M'),
(4,))
expectation = (('id', 'variable', 'value'),
(1, 'gender', 'F'),
(1, 'age', 12),
(2, 'gender', 'M'),
(2, 'age', 17),
(3, 'gender', 'M'))
result = melt(table, key='id')
ieq(expectation, result)
result = melt(table, key='id', variablefield='variable', valuefield='value')
ieq(expectation, result)
def test_melt_2_shortrow():
table = (('id', 'time', 'height', 'weight'),
(1, 11, 66.4, 12.2),
(2, 16, 53.2, 17.3),
(3, 12, 34.5),
(4, 14))
expectation = (('id', 'time', 'variable', 'value'),
(1, 11, 'height', 66.4),
(1, 11, 'weight', 12.2),
(2, 16, 'height', 53.2),
(2, 16, 'weight', 17.3),
(3, 12, 'height', 34.5))
result = melt(table, key=('id', 'time'))
ieq(expectation, result)
expectation = (('id', 'time', 'variable', 'value'),
(1, 11, 'height', 66.4),
(2, 16, 'height', 53.2),
(3, 12, 'height', 34.5))
result = melt(table, key=('id', 'time'), variables='height')
ieq(expectation, result)
def test_recast_1():
table = (('id', 'variable', 'value'),
(3, 'age', 16),
(1, 'gender', 'F'),
(2, 'gender', 'M'),
(2, 'age', 17),
(1, 'age', 12),
(3, 'gender', 'M'))
expectation = (('id', 'age', 'gender'),
(1, 12, 'F'),
(2, 17, 'M'),
(3, 16, 'M'))
# by default lift 'variable' field, hold everything else
result = recast(table)
ieq(expectation, result)
result = recast(table, variablefield='variable')
ieq(expectation, result)
result = recast(table, key='id', variablefield='variable')
ieq(expectation, result)
result = recast(table, key='id', variablefield='variable',
valuefield='value')
ieq(expectation, result)
def test_recast_2():
table = (('id', 'variable', 'value'),
(3, 'age', 16),
(1, 'gender', 'F'),
(2, 'gender', 'M'),
(2, 'age', 17),
(1, 'age', 12),
(3, 'gender', 'M'))
expectation = (('id', 'gender'),
(1, 'F'),
(2, 'M'),
(3, 'M'))
# can manually pick which variables you want to recast as fields
# TODO this is awkward
result = recast(table, key='id', variablefield={'variable': ['gender']})
ieq(expectation, result)
def test_recast_3():
table = (('id', 'time', 'variable', 'value'),
(1, 11, 'weight', 66.4),
(1, 14, 'weight', 55.2),
(2, 12, 'weight', 53.2),
(2, 16, 'weight', 43.3),
(3, 12, 'weight', 34.5),
(3, 17, 'weight', 49.4))
expectation = (('id', 'time', 'weight'),
(1, 11, 66.4),
(1, 14, 55.2),
(2, 12, 53.2),
(2, 16, 43.3),
(3, 12, 34.5),
(3, 17, 49.4))
result = recast(table)
ieq(expectation, result)
# in the absence of an aggregation function, list all values
expectation = (('id', 'weight'),
(1, [66.4, 55.2]),
(2, [53.2, 43.3]),
(3, [34.5, 49.4]))
result = recast(table, key='id')
ieq(expectation, result)
# max aggregation
expectation = (('id', 'weight'),
(1, 66.4),
(2, 53.2),
(3, 49.4))
result = recast(table, key='id', reducers={'weight': max})
ieq(expectation, result)
# min aggregation
expectation = (('id', 'weight'),
(1, 55.2),
(2, 43.3),
(3, 34.5))
result = recast(table, key='id', reducers={'weight': min})
ieq(expectation, result)
# mean aggregation
expectation = (('id', 'weight'),
(1, 60.80),
(2, 48.25),
(3, 41.95))
def mean(values):
return float(sum(values)) / len(values)
def meanf(precision):
def f(values):
v = mean(values)
v = round(v, precision)
return v
return f
result = recast(table, key='id', reducers={'weight': meanf(precision=2)})
ieq(expectation, result)
def test_recast4():
# deal with missing data
table = (('id', 'variable', 'value'),
(1, 'gender', 'F'),
(2, 'age', 17),
(1, 'age', 12),
(3, 'gender', 'M'))
result = recast(table, key='id')
expect = (('id', 'age', 'gender'),
(1, 12, 'F'),
(2, 17, None),
(3, None, 'M'))
ieq(expect, result)
def test_recast_empty():
table = (('foo', 'variable', 'value'),)
expect = (('foo',),)
actual = recast(table)
ieq(expect, actual)
def test_recast_date():
dt = datetime.now().replace
table = (('id', 'variable', 'value'),
(dt(hour=3), 'age', 16),
(dt(hour=1), 'gender', 'F'),
(dt(hour=2), 'gender', 'M'),
(dt(hour=2), 'age', 17),
(dt(hour=1), 'age', 12),
(dt(hour=3), 'gender', 'M'))
expectation = (('id', 'age', 'gender'),
(dt(hour=1), 12, 'F'),
(dt(hour=2), 17, 'M'),
(dt(hour=3), 16, 'M'))
# by default lift 'variable' field, hold everything else
result = recast(table)
ieq(expectation, result)
result = recast(table, variablefield='variable')
ieq(expectation, result)
result = recast(table, key='id', variablefield='variable')
ieq(expectation, result)
result = recast(table, key='id', variablefield='variable',
valuefield='value')
ieq(expectation, result)
def test_melt_and_capture():
table = (('id', 'parad0', 'parad1', 'parad2'),
('1', '12', '34', '56'),
('2', '23', '45', '67'))
expectation = (('id', 'parasitaemia', 'day'),
('1', '12', '0'),
('1', '34', '1'),
('1', '56', '2'),
('2', '23', '0'),
('2', '45', '1'),
('2', '67', '2'))
step1 = melt(table, key='id', valuefield='parasitaemia')
step2 = capture(step1, 'variable', 'parad(\\d+)', ('day',))
ieq(expectation, step2)
def test_melt_and_split():
table = (('id', 'parad0', 'parad1', 'parad2', 'tempd0', 'tempd1', 'tempd2'),
('1', '12', '34', '56', '37.2', '37.4', '37.9'),
('2', '23', '45', '67', '37.1', '37.8', '36.9'))
expectation = (('id', 'value', 'variable', 'day'),
('1', '12', 'para', '0'),
('1', '34', 'para', '1'),
('1', '56', 'para', '2'),
('1', '37.2', 'temp', '0'),
('1', '37.4', 'temp', '1'),
('1', '37.9', 'temp', '2'),
('2', '23', 'para', '0'),
('2', '45', 'para', '1'),
('2', '67', 'para', '2'),
('2', '37.1', 'temp', '0'),
('2', '37.8', 'temp', '1'),
('2', '36.9', 'temp', '2'))
step1 = melt(table, key='id')
step2 = split(step1, 'variable', 'd', ('variable', 'day'))
ieq(expectation, step2)
def test_transpose():
table1 = (('id', 'colour'),
(1, 'blue'),
(2, 'red'),
(3, 'purple'),
(5, 'yellow'),
(7, 'orange'))
table2 = transpose(table1)
expect2 = (('id', 1, 2, 3, 5, 7),
('colour', 'blue', 'red', 'purple', 'yellow', 'orange'))
ieq(expect2, table2)
ieq(expect2, table2)
def test_transpose_empty():
table1 = (('id', 'colour'),)
table2 = transpose(table1)
expect2 = (('id',),
('colour',))
ieq(expect2, table2)
def test_pivot():
table1 = (('region', 'gender', 'style', 'units'),
('east', 'boy', 'tee', 12),
('east', 'boy', 'golf', 14),
('east', 'boy', 'fancy', 7),
('east', 'girl', 'tee', 3),
('east', 'girl', 'golf', 8),
('east', 'girl', 'fancy', 18),
('west', 'boy', 'tee', 12),
('west', 'boy', 'golf', 15),
('west', 'boy', 'fancy', 8),
('west', 'girl', 'tee', 6),
('west', 'girl', 'golf', 16),
('west', 'girl', 'fancy', 1))
table2 = pivot(table1, 'region', 'gender', 'units', sum)
expect2 = (('region', 'boy', 'girl'),
('east', 33, 29),
('west', 35, 23))
ieq(expect2, table2)
ieq(expect2, table2)
def test_pivot_empty():
table1 = (('region', 'gender', 'style', 'units'),)
table2 = pivot(table1, 'region', 'gender', 'units', sum)
expect2 = (('region',),)
ieq(expect2, table2)
def test_flatten():
table1 = (('foo', 'bar', 'baz'),
('A', 1, True),
('C', 7, False),
('B', 2, False),
('C', 9, True))
expect1 = ('A', 1, True, 'C', 7, False, 'B', 2, False, 'C', 9, True)
actual1 = flatten(table1)
ieq(expect1, actual1)
ieq(expect1, actual1)
def test_flatten_empty():
table1 = (('foo', 'bar', 'baz'),)
expect1 = []
actual1 = flatten(table1)
ieq(expect1, actual1)
def test_unflatten():
table1 = (('lines',),
('A',),
(1,),
(True,),
('C',),
(7,),
(False,),
('B',),
(2,),
(False,),
('C',),
(9,))
expect1 = (('f0', 'f1', 'f2'),
('A', 1, True),
('C', 7, False),
('B', 2, False),
('C', 9, None))
actual1 = unflatten(table1, 'lines', 3)
ieq(expect1, actual1)
ieq(expect1, actual1)
def test_unflatten_2():
inpt = ('A', 1, True, 'C', 7, False, 'B', 2, False, 'C', 9)
expect1 = (('f0', 'f1', 'f2'),
('A', 1, True),
('C', 7, False),
('B', 2, False),
('C', 9, None))
actual1 = unflatten(inpt, 3)
ieq(expect1, actual1)
ieq(expect1, actual1)
def test_unflatten_empty():
table1 = (('lines',),)
expect1 = (('f0', 'f1', 'f2'),)
actual1 = unflatten(table1, 'lines', 3)
ieq(expect1, actual1)