{'from_name': None,
'to_name': 'date_laboratory',
'study_day_col': 'lab_study_day',
'study_day_ref': 'date_enrolment'},
]
# Data
data = [
{'StudyNo': '32dx-001', 'DateEnrol': '2020/12/01', 'LabStudyDay': 1},
{'StudyNo': '32dx-002', 'DateEnrol': '2020/12/04', 'LabStudyDay': 5},
{'StudyNo': '32dx-003', 'DateEnrol': '2020/12/11', 'LabStudyDay': 10},
{'StudyNo': '32dx-004', 'DateEnrol': '2020/12/08 04:30', 'LabStudyDay': 0},
{'StudyNo': '32dx-005', 'LabStudyDay': 3},
{'StudyNo': '32dx-005', 'DateEnrol': '2020/12/07'}
]
# Blender template
bt = BlenderTemplate().fit(template)
# Create data
data = pd.DataFrame(data)
# Create widgets and transform
trans = RenameWidget().fit_transform(bt, data)
trans = DateFromStudyDayWidget().fit_transform(bt, trans)
# Show
print("\nOriginal:")
print(data)
print("\nTransformed:")
print(trans)
'hct': 4.0,
'wbc': 2.5
},
]
# Create templates dictionary
templates = {
'EXAM': pd.DataFrame(template_exam),
'LAB': pd.DataFrame(template_lab)
}
# Create data dictionary
data = {'EXAM': pd.DataFrame(data_exam), 'LAB': pd.DataFrame(data_lab)}
# Create blender
blender = Blender(widgets=[RenameWidget(), ReplaceWidget()])
# Fit blender to templates.
blender = blender.fit(info=templates)
# Transform data
transformed = blender.transform(data)
# Stack data
stacked = blender.stack(transformed, index='pid')
# Show
print("\nOriginal:")
for k, v in data.items():
print("\n%s:" % k)
print(v)
def test_widget_rename(bt, data):
""""""
transformed = RenameWidget().fit_transform(bt, data)
assert True
def test_widget_replace_from_dict(bt, data):
""""""
transformed = RenameWidget().fit_transform(bt, data)
transformed = ReplaceWidget().fit_transform(bt, transformed)
unique = set(transformed.gender.unique())
assert unique.issubset(set(['Male', 'Female']))
def test_widget_fit_from_json(bt_json):
""""""
widget = RenameWidget().fit(bt_json)
assert isinstance(widget, BaseWidget)
def test_widget_raises_exception_on_missing_required_columns(bt_df):
""""""
bt_df = bt_df.drop(columns='to_name')
bt = BlenderTemplate().fit(bt_df)
with pytest.raises(MissingRequiredColumns):
RenameWidget().fit(bt)
def test_widget_fit_from_df(bt_df):
""""""
widget = RenameWidget().fit(bt_df)
assert isinstance(widget, BaseWidget)
def test_widget_raises_exception_on_None():
""""""
with pytest.raises(TypeError):
RenameWidget().fit(None)
'StudyNo': '32dx-002',
'Temp': 36.5,
'Shock': False,
'Sex': 1
}, {
'StudyNo': '32dx-003',
'Temp': 39.8,
'Shock': True,
'Sex': 2
}, {
'StudyNo': '32dx-004',
'Temp': 37.4,
'Shock': False,
'Sex': 1
}]
# Create data
data = pd.DataFrame(data)
# Create widget
widget = RenameWidget().fit(template)
# Transform
transformed = widget.transform(data)
# Show
print("\nOriginal:")
print(data)
print("\nTransformed:")
print(transformed)
print("\nStacked:")
include = [
'ENROL', 'DAILY', 'INPFU', 'NS1PLATELIA', 'PCR', 'CBC', 'BIO', 'SEROLOGY',
'LAB_DIAGNOSIS'
]
# Excel sheets to exclude
exclude = ['Category', 'NS1TRIP']
# Read all data sheets
data = pd.read_excel(path_fixed, sheet_name=None)
tmps = pd.read_excel(path_ccfgs, sheet_name=None)
# Create blender
blender = Blender(widgets=[
DateTimeMergeWidget(),
RenameWidget(),
ReplaceWidget(),
#TemplateTransformWidget(),
EventWidget()
])
# Fit blender to templates.
blender = blender.fit(info=tmps)
# Transform data
transformed = blender.transform(data, include=include, exclude=exclude)
# Stacked data
stacked = blender.stack(transformed,
index='study_no',
include=include,
'wbc': 1.0,
'LabSampleStudyDay': 2
},
]
# Create DataFrames
template = pd.DataFrame(template)
data = pd.DataFrame(data)
#template = template.drop(columns=['timestamp'])
#template.timestamp = None
#template.event = None
#template = template.drop(columns=['to_name'])
# Transformed (order matters!)
transformed = RenameWidget().fit_transform(template, data)
transformed = TemplateTransformWidget().fit_transform(template, transformed)
transformed = ReplaceWidget().fit_transform(template, transformed)
transformed = DateTimeMergeWidget().fit_transform(template, transformed)
transformed = DateFromStudyDayWidget().fit_transform(template, transformed)
transformed = EventWidget().fit_transform(template, transformed)
# Stack data
stacked = StackWidget(index=['study_number']) \
.fit_transform(template, transformed)
# Show
print("\nOriginal:")
print(data)
print("\nTransformed:")
print(transformed)