atoti.parent_value()#
- 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:
MeasureDescription
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 6 1 15 145 20 35 35 35 2 5 155 20 35 35 35 7 1 5 55 15 35 35 35 2 10 145 15 35 35 35 2019 6 1 25 115 40 75 75 75 2 15 135 40 75 75 75 7 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.