atoti.math package

Submodules

• atoti.math.abs module
• atoti.math.ceil module
• atoti.math.cos module
• atoti.math.erf module
• atoti.math.erfc module
• atoti.math.exp module
• atoti.math.floor module
• atoti.math.isnan module
• atoti.math.log module
• atoti.math.log10 module
• atoti.math.max module
• atoti.math.min module
• atoti.math.round module
• atoti.math.sin module
• atoti.math.sqrt module
• atoti.math.tan module

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["Subtract"] = 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["Subtract"],
  ...     m["Multiply"],
  ...     levels=[l["City"]],
  ... )
             A.SUM  B.SUM     Sum Subtract 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