atoti.filter()#

atoti.filter(measure, condition, /)#

Return a filtered measure.

The new measure is equal to the passed one where the condition is True and to None elsewhere.

Parameters:

measure (MeasureConvertible) – The measure to filter.
condition (Condition[HierarchyIdentifier | LevelIdentifier, Literal['eq', 'ge', 'gt', 'le', 'lt', 'ne', 'isin'], ~atoti._constant.Constant, ~typing.Literal['and'] | None]) – The condition to evaluate.

Return type:

MeasureDescription

Example

>>> from datetime import date
>>> data = pd.DataFrame(
...     {
...         "Date": [date(2021, 1, 13), date(2021, 7, 5), date(2021, 7, 6)],
...         "City": ["Paris", "Paris", "London"],
...         "Age": [18, 25, 8],
...         "Quantity": [200, 500, 100],
...     }
... )
>>> table = session.read_pandas(
...     data, default_values={"Age": 0}, table_name="City date table"
... )
>>> table.head()
        Date    City  Age  Quantity
0 2021-01-13   Paris   18       200
1 2021-07-05   Paris   25       500
2 2021-07-06  London    8       100
>>> cube = session.create_cube(table)
>>> h, l, m = cube.hierarchies, cube.levels, cube.measures
>>> h.update({name: {name: table[name]} for name in ["Date", "City", "Age"]})
>>> # Levels compared to constants of the same type:
>>> m["London Quantity.SUM"] = tt.filter(m["Quantity.SUM"], l["City"] == "London")
>>> m["Quantity.SUM before July"] = tt.filter(
...     m["Quantity.SUM"], l["Date"] < date(2021, 7, 1)
... )
>>> m["Quantity.SUM for age under 18"] = tt.filter(
...     m["Quantity.SUM"], l["Age"] <= 18
... )
>>> # A conjunction of conditions using the ``&`` operator:
>>> m["July Quantity.SUM in Paris"] = tt.filter(
...     m["Quantity.SUM"],
...     (
...         (l["City"] == "Paris")
...         & ((l["Date"]) >= date(2021, 7, 1))
...         & (l["Date"] <= date(2021, 7, 31))
...     ),
... )
>>> cube.query(
...     m["Quantity.SUM"],
...     m["London Quantity.SUM"],
...     m["Quantity.SUM before July"],
...     m["Quantity.SUM for age under 18"],
...     m["July Quantity.SUM in Paris"],
... )
  Quantity.SUM London Quantity.SUM Quantity.SUM before July Quantity.SUM for age under 18 July Quantity.SUM in Paris
0          800                 100                      200                           300                        500
>>> cube.query(
...     m["Quantity.SUM"],
...     m["London Quantity.SUM"],
...     m["Quantity.SUM before July"],
...     m["Quantity.SUM for age under 18"],
...     m["July Quantity.SUM in Paris"],
...     levels=[l["Date"], l["Age"], l["City"]],
... )
                      Quantity.SUM London Quantity.SUM Quantity.SUM before July Quantity.SUM for age under 18 July Quantity.SUM in Paris
Date       Age City
2021-01-13 18  Paris           200                                          200                           200
2021-07-05 25  Paris           500                                                                                                   500
2021-07-06 8   London          100                 100                                                    100