atoti.parent_value(measure, /, *, degrees, apply_filters=False, total_value=None, dense=False)
Return a measure which values are equal to the values of the given measure, at a member that is located at a higher level on each of the specified hierarchy. This operation is also called drilling up a hierarchy.- Parameters:
- measure (VariableMeasureConvertible | str) – The measure from which the values are copied.
- degrees (Mapping [Hierarchy , int ]) – The number of levels to go up to select the parent member along any given hierarchy.
- apply_filters (bool) – Whether or not the query filters on hierarchies specified in the degrees mapping must be applied when computing the value at the parent member.
- total_value (MeasureConvertible | None) – The value to return when the drill up went above the top level of all the hierarchies in the degrees mapping.
- dense (bool) – When
True, the parent value will be replicated on all members of the levels of the hierarchies in the degrees mapping, even those with no value for the given measure.
- Return type: MeasureDefinition
Example
>>> df = pd.DataFrame(
... columns=["Year", "Month", "Day", "Shop", "Quantity", "Other"],
... data=[
... (2019, 7, 1, "Shop1", 15, 245),
... (2019, 7, 2, "Shop1", 20, 505),
... (2019, 6, 1, "Shop2", 25, 115),
... (2019, 6, 2, "Shop2", 15, 135),
... (2018, 7, 1, "Shop1", 5, 55),
... (2018, 7, 2, "Shop2", 10, 145),
... (2018, 6, 1, "Shop1", 15, 145),
... (2018, 6, 2, "Shop2", 5, 155),
... ],
... )
>>> table = session.read_pandas(
... df,
... table_name="Parent Value",
... default_values={"Year": 0, "Month": 0, "Day": 0},
... )
>>> cube = session.create_cube(table)
>>> h, l, m = cube.hierarchies, cube.levels, cube.measures
>>> h["Date"] = [table["Year"], table["Month"], table["Day"]]
>>> m["Degree 1"] = tt.parent_value(m["Quantity.SUM"], degrees={h["Date"]: 1})
>>> m["Degree 2"] = tt.parent_value(m["Quantity.SUM"], degrees={h["Date"]: 2})
>>> m["Degree 2 with Quantity total"] = tt.parent_value(
... m["Quantity.SUM"],
... degrees={h["Date"]: 2},
... total_value=m["Quantity.SUM"],
... )
>>> m["Degree 2 with Other total"] = tt.parent_value(
... m["Quantity.SUM"],
... degrees={h["Date"]: 2},
... total_value=m["Other.SUM"],
... )
>>> cube.query(
... m["Quantity.SUM"],
... m["Other.SUM"],
... m["Degree 1"],
... m["Degree 2"],
... m["Degree 2 with Quantity total"],
... m["Degree 2 with Other total"],
... levels=[l["Day"]],
... include_totals=True,
... )
Quantity.SUM Other.SUM Degree 1 Degree 2 Degree 2 with Quantity total Degree 2 with Other total
Year Month Day
Total 110 1,500 110 1,500
2018 35 500 110 110 1,500
6 20 300 35 110 110 110
1 15 145 20 35 35 35
2 5 155 20 35 35 35
7 15 200 35 110 110 110
1 5 55 15 35 35 35
2 10 145 15 35 35 35
2019 75 1,000 110 110 1,500
6 40 250 75 110 110 110
1 25 115 40 75 75 75
2 15 135 40 75 75 75
7 35 750 75 110 110 110
1 15 245 35 75 75 75
2 20 505 35 75 75 75
>>> h["Date"].slicing = True
>>> cube.query(
... m["Quantity.SUM"],
... m["Other.SUM"],
... m["Degree 1"],
... m["Degree 2"],
... m["Degree 2 with Quantity total"],
... m["Degree 2 with Other total"],
... levels=[l["Day"]],
... include_totals=True,
... )
Quantity.SUM Other.SUM Degree 1 Degree 2 Degree 2 with Quantity total Degree 2 with Other total
Year Month Day
2018 35 500 35 500
6 20 300 35 35 500
1 15 145 20 35 35 35
2 5 155 20 35 35 35
7 15 200 35 35 500
1 5 55 15 35 35 35
2 10 145 15 35 35 35
2019 75 1,000 75 1,000
6 40 250 75 75 1,000
1 25 115 40 75 75 75
2 15 135 40 75 75 75
7 35 750 75 75 1,000
1 15 245 35 75 75 75
2 20 505 35 75 75 75
>>> h["Date"].slicing = False
>>> m["Degree 1 with applied filter"] = tt.parent_value(
... m["Quantity.SUM"], degrees={h["Date"]: 1}, apply_filters=True
... )
>>> cube.query(
... m["Quantity.SUM"],
... m["Degree 1"],
... m["Degree 1 with applied filter"],
... levels=[l["Day"]],
... include_totals=True,
... filter=l["Year"] == "2018",
... )
Quantity.SUM Degree 1 Degree 1 with applied filter
Year Month Day
Total 35
2018 35 110 35
6 20 35 35
1 15 20 20
2 5 20 20
7 15 35 35
1 5 15 15
2 10 15 15
>>> cube.query(
... m["Quantity.SUM"],
... m["Degree 1"],
... m["Degree 1 with applied filter"],
... levels=[l["Day"]],
... include_totals=True,
... filter=l["Shop"] == "Shop1",
... )
Quantity.SUM Degree 1 Degree 1 with applied filter
Year Month Day
Total 55
2018 20 55 55
6 15 20 20
1 15 15 15
7 5 20 20
1 5 5 5
2019 35 55 55
7 35 35 35
1 15 35 35
2 20 35 35
See also:
atoti.total() to take the value at the top level member on each given hierarchy.