def test_reverse_transform(self):
"""Test the ``ColumnFormula.reverse_transform`` method.
It is expected to compute the indicated column by applying the given formula.
Input:
- Table data with the column with incorrect values (pandas.DataFrame)
Output:
- Table data with the computed column (pandas.DataFrame)
"""
# Setup
column = 'c'
instance = ColumnFormula(column=column, formula=new_column)
# Run
table_data = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
'c': [1, 1, 1]
})
out = instance.reverse_transform(table_data)
# Assert
expected_out = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
'c': [5, 7, 9]
})
pd.testing.assert_frame_equal(expected_out, out)
def test_transform(self):
"""Test the ``ColumnFormula.transform`` method.
It is expected to drop the indicated column from the table.
Input:
- Table data (pandas.DataFrame)
Output:
- Table data without the indicated column (pandas.DataFrame)
"""
# Setup
column = 'c'
instance = ColumnFormula(column=column, formula=new_column)
# Run
table_data = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
'c': [5, 7, 9]
})
out = instance.transform(table_data)
# Assert
expected_out = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
})
pd.testing.assert_frame_equal(expected_out, out)
def test_is_valid_non_valid(self):
"""Test the ``ColumnFormula.is_valid`` method for a non-valid data.
If the data does not fulfill the formula, result is a series of ``False`` values.
Input:
- Table data not fulfilling the formula (pandas.DataFrame)
Output:
- Series of ``False`` values (pandas.Series)
"""
# Setup
column = 'c'
instance = ColumnFormula(column=column, formula=new_column)
# Run
table_data = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
'c': [1, 2, 3]
})
instance = ColumnFormula(column=column, formula=new_column)
out = instance.is_valid(table_data)
# Assert
expected_out = pd.Series([False, False, False])
pd.testing.assert_series_equal(expected_out, out)
def test_to_dict_column_formula_returned_function(self):
"""Test the ``Constraint.to_dict`` when the constraint is
a ColumnFormula type and is passed a function returned
from another function.
If the ``Constraint`` type is ColumnFormula,
and the formula argument is a function returned from another
function, the dictionary should contain the function as the value.
Output:
- Dict with the right values.
"""
# Run
def func_creator():
def func(x):
return x + 1
return func
instance = ColumnFormula(column='a',
formula=func_creator(),
handling_strategy='transform')
constraint_dict = instance.to_dict()
# Assert
assert constraint_dict['formula'](1) == 2
def test_to_dict_column_formula_lambda(self):
"""Test the ``Constraint.to_dict`` when the constraint is
a ColumnFormula type and is passed a lambda.
If the ``Constraint`` type is ColumnFormula,
and the formula argument is a lambda, the dictionary
should contain the lambda object as the value.
Output:
- Dict with the right values.
"""
# Run
instance = ColumnFormula(column='a',
formula=lambda x: x + 1,
handling_strategy='transform')
constraint_dict = instance.to_dict()
# Assert
assert constraint_dict['formula'](1) == 2
def test___init__(self):
"""Test the ``ColumnFormula.__init__`` method.
It is expected to create a new Constraint instance
and import the formula to use for the computation.
Input:
- column = 'c'
- formula = new_column
"""
# Setup
column = 'c'
# Run
instance = ColumnFormula(column=column, formula=new_column)
# Assert
assert instance._column == column
assert instance._formula == new_column