atoti.array.replace module

atoti.array.replace(measure, replacements)

Return a measure where elements equal to a key of the replacements mapping are replaced with the corresponding value.

Parameters

• measure (MeasureDescription) – The array measure in which to replace the elements.

• replacements (Union[Mapping[float, float], Mapping[int, int]]) – The mapping from the old values to the new ones.

Example

>>> df = pd.DataFrame(
...     columns=["Store ID", "New quantity", "Old quantity"],
...     data=[
...         (
...             "Store 1",
...             [12, 6, 2, 20],
...             [6, 3, 0, 10],
...         ),
...         ("Store 2", [16, 8, 12, 15], [4, 4, 6, 3]),
...         ("Store 3", [8, -10, 0, 33], [8, 0, 2, 11]),
...     ],
... )
>>> table = session.read_pandas(df, table_name="Prices", keys=["Store ID"])
>>> cube = session.create_cube(table)
>>> l, m = cube.levels, cube.measures
>>> m["Old quantity"] = tt.value(table["Old quantity"])
>>> m["New quantity"] = tt.value(table["New quantity"])
>>> m["Quantity ratio"] = m["New quantity"] / m["Old quantity"]
>>> m["Quantity ratio"].formatter = "ARRAY[',']"
>>> cube.query(m["Quantity ratio"], levels=[l["Store ID"]])
                 Quantity ratio
Store ID
Store 1    2.0,2.0,Infinity,2.0
Store 2         4.0,2.0,2.0,5.0
Store 3   1.0,-Infinity,0.0,3.0

The function can be used to replace infinity with another value more suited to follow up computations:

>>> import math
>>> m["Quantity ratio without infinity"] = tt.array.replace(
...     m["Quantity ratio"], {math.inf: 1, -math.inf: -1}
... )
>>> m["Quantity ratio without infinity"].formatter = "ARRAY[',']"
>>> cube.query(m["Quantity ratio without infinity"], levels=[l["Store ID"]])
         Quantity ratio without infinity
Store ID
Store 1                  2.0,2.0,1.0,2.0
Store 2                  4.0,2.0,2.0,5.0
Store 3                 1.0,-1.0,0.0,3.0

Return type

MeasureDescription