atoti.shift()#

atoti.shift(measure, on, /, *, offset=1, partitioning=None)#

Return a measure equal to the passed measure shifted to another member of the hierarchy.

Parameters:

  • measure (VariableMeasureConvertible) – The measure to shift.

  • on (Hierarchy) – The hierarchy to shift on.

  • offset (int) – The amount of members to shift by.

  • partitioning (Level | None) – The level in the hierarchy at which to start the shift over.

Return type:

MeasureDescription

Example

>>> df = pd.DataFrame(
...     columns=["Country", "City", "Price"],
...     data=[
...         ("France", "Bordeaux", 1),
...         ("France", "Lyon", 2),
...         ("France", "Paris", 3),
...         ("Germany", "Berlin", 4),
...         ("Germany", "Frankfurt", 5),
...         ("Germany", "Munich", 6),
...     ],
... )
>>> table = session.read_pandas(
...     df,
...     table_name="Shift example",
... )
>>> cube = session.create_cube(table)
>>> h, l, m = cube.hierarchies, cube.levels, cube.measures
>>> m["Shifted Price.SUM"] = tt.shift(m["Price.SUM"], h["City"], offset=2)
>>> cube.query(
...     m["Price.SUM"],
...     m["Shifted Price.SUM"],
...     levels=[l["City"]],
...     include_totals=True,
... )
          Price.SUM Shifted Price.SUM
City
Total            21
Berlin            4                 5
Bordeaux          1                 2
Frankfurt         5                 6
Lyon              2                 3
Munich            6
Paris             3

>>> h["Location"] = [l["Country"], l["City"]]
>>> m["Shifted Price.SUM"] = tt.shift(m["Price.SUM"], h["Location"], offset=1)
>>> m["Shifted Price.SUM partitioned by Country"] = tt.shift(
...     m["Price.SUM"],
...     h["Location"],
...     offset=1,
...     partitioning=l["Location", "Country"],
... )
>>> cube.query(
...     m["Price.SUM"],
...     m["Shifted Price.SUM"],
...     m["Shifted Price.SUM partitioned by Country"],
...     levels=[
...         l["Shift example", "Location", "Country"],
...         l["Shift example", "Location", "City"],
...     ],
...     include_totals=True,
... )
                  Price.SUM Shifted Price.SUM Shifted Price.SUM partitioned by Country
Country City
Total                    21
France                    6                15
        Bordeaux          1                 2                                        2
        Lyon              2                 3                                        3
        Paris             3                 4
Germany                  15
        Berlin            4                 5                                        5
        Frankfurt         5                 6                                        6
        Munich            6