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- power(column_expression_or_constant1, column_expression_or_constant2)
- DESCRIPTION:
Function returns the base value (column_expression_or_constant1) raised to the
power of the exponent value (column_expression_or_constant2).
PARAMETERS:
column_expression_or_constant1:
Required Argument.
Specifies a ColumnExpression of a numeric column or a constant value that is the base value.
Format for the argument: '<dataframe>.<dataframe_column>.expression'.
column_expression_or_constant2:
Required Argument.
Specifies a ColumnExpression of a numeric column or a constant value that is the exponent value.
Format for the argument: '<dataframe>.<dataframe_column>.expression'.
NOTE:
Function accepts positional arguments only.
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("dataframe", "admissions_train")
>>>
# Create a DataFrame on 'admissions_train' table.
>>> admissions_train = DataFrame("admissions_train")
>>> admissions_train
masters gpa stats programming admitted
id
22 yes 3.46 Novice Beginner 0
36 no 3.00 Advanced Novice 0
15 yes 4.00 Advanced Advanced 1
38 yes 2.65 Advanced Beginner 1
5 no 3.44 Novice Novice 0
17 no 3.83 Advanced Advanced 1
34 yes 3.85 Advanced Beginner 0
13 no 4.00 Advanced Novice 1
26 yes 3.57 Advanced Advanced 1
19 yes 1.98 Advanced Advanced 0
>>>
# Import func from sqlalchemy to execute power() function.
>>> from sqlalchemy import func
# Create a sqlalchemy Function object and pass the Function object as input to DataFrame.assign().
# Note: We are using 'power' and 'POWER' as function names. Function names are case-insensitive.
>>> df = admissions_train.assign(pow2gpa = func.power(admissions_train.gpa.expression, 2),
... pow_admitted_gpa = func.POWER(admissions_train.gpa.expression, admissions_train.admitted.expression))
>>> print(df)
masters gpa stats programming admitted pow2gpa pow_admitted_gpa
id
13 no 4.00 Advanced Novice 1 16.0000 4.00
26 yes 3.57 Advanced Advanced 1 12.7449 3.57
5 no 3.44 Novice Novice 0 11.8336 1.00
19 yes 1.98 Advanced Advanced 0 3.9204 1.00
15 yes 4.00 Advanced Advanced 1 16.0000 4.00
40 yes 3.95 Novice Beginner 0 15.6025 1.00
7 yes 2.33 Novice Novice 1 5.4289 2.33
22 yes 3.46 Novice Beginner 0 11.9716 1.00
36 no 3.00 Advanced Novice 0 9.0000 1.00
38 yes 2.65 Advanced Beginner 1 7.0225 2.65
>>>
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