atoti.math package

Module contents

Measures can be combined with mathematical operators.

Several native Python operators are supported:

  • The classic +, - and * operators

    >>> df = pd.DataFrame(
    ...     columns=["City", "A", "B", "C", "D"],
    ...     data=[
    ...         ("Berlin", 15.0, 10.0, 10.1, 1.0),
    ...         ("London", 24.0, 16.0, 20.5, 3.14),
    ...         ("New York", -27.0, 15.0, 30.7, 10.0),
    ...         ("Paris", 0.0, 0.0, 0.0, 0.0),
    ...     ],
    ... )
    >>> table = session.read_pandas(df, keys=["City"], table_name="Math")
    >>> cube = session.create_cube(table)
    >>> l, m = cube.levels, cube.measures
    >>> m["Sum"] = m["A.SUM"] + m["B.SUM"]
    >>> m["Substract"] = m["A.SUM"] - m["B.SUM"]
    >>> m["Multiply"] = m["A.SUM"] * m["B.SUM"]
    >>> cube.query(
    ...     m["A.SUM"],
    ...     m["B.SUM"],
    ...     m["Sum"],
    ...     m["Substract"],
    ...     m["Multiply"],
    ...     levels=[l["City"]],
    ... )
               A.SUM  B.SUM     Sum Substract Multiply
    City
    Berlin     15.00  10.00   25.00      5.00   150.00
    London     24.00  16.00   40.00      8.00   384.00
    New York  -27.00  15.00  -12.00    -42.00  -405.00
    Paris        .00    .00     .00       .00      .00
    
  • The float division / and integer division //

    >>> m["Float division"] = m["A.SUM"] / m["B.SUM"]
    >>> m["Int division"] = m["A.SUM"] // m["B.SUM"]
    >>> cube.query(
    ...     m["A.SUM"],
    ...     m["B.SUM"],
    ...     m["Float division"],
    ...     m["Int division"],
    ...     levels=[l["City"]],
    ... )
               A.SUM  B.SUM Float division Int division
    City
    Berlin     15.00  10.00           1.50         1.00
    London     24.00  16.00           1.50         1.00
    New York  -27.00  15.00          -1.80        -2.00
    Paris        .00    .00            NaN          NaN
    
  • The exponentiation **

    >>> m["a²"] = m["A.SUM"] ** 2
    >>> cube.query(m["A.SUM"], m["a²"], levels=[l["City"]])
               A.SUM      a²
    City
    Berlin     15.00  225.00
    London     24.00  576.00
    New York  -27.00  729.00
    Paris        .00     .00
    
  • The modulo %

    >>> m["Modulo"] = m["A.SUM"] % m["B.SUM"]
    >>> cube.query(m["A.SUM"], m["B.SUM"], m["Modulo"], levels=[l["City"]])
               A.SUM  B.SUM Modulo
    City
    Berlin     15.00  10.00   5.00
    London     24.00  16.00   8.00
    New York  -27.00  15.00   3.00
    Paris        .00    .00    NaN