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- sqrt(column_expression_or_constant)
- DESCRIPTION:
Function computes the square root of an argument.
PARAMETERS:
column_expression_or_constant:
Required Argument.
Specifies a ColumnExpression of a numeric column or a constant value.
Format for the argument: '<dataframe>.<dataframe_column>.expression'.
Notes:
1. If the type of the column/argument is not FLOAT, column values are converted to FLOAT
based on implicit type conversion rules. If an argument cannot be converted, an
error is reported. For more information on implicit type conversion,
see Teradata Vantage™ Data Types and Literals, B035-1143.
2. Unsupported column types:
a. BYTE or VARBYTE
b. LOBs (BLOB or CLOB)
c. CHARACTER or VARCHAR if the server character set is GRAPHIC
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 sign() function.
>>> from sqlalchemy import func
# Create a sqlalchemy Function object and pass the Function object as input to DataFrame.assign().
>>> df = admissions_train.assign(sqrt_gpa = func.sqrt(admissions_train.gpa.expression),
... sqrt_const = func.SQRT(25))
>>> print(df)
masters gpa stats programming admitted sqrt_const sqrt_gpa
id
5 no 3.44 Novice Novice 0 5.0 1.854724
34 yes 3.85 Advanced Beginner 0 5.0 1.962142
13 no 4.00 Advanced Novice 1 5.0 2.000000
40 yes 3.95 Novice Beginner 0 5.0 1.987461
22 yes 3.46 Novice Beginner 0 5.0 1.860108
19 yes 1.98 Advanced Advanced 0 5.0 1.407125
36 no 3.00 Advanced Novice 0 5.0 1.732051
15 yes 4.00 Advanced Advanced 1 5.0 2.000000
7 yes 2.33 Novice Novice 1 5.0 1.526434
17 no 3.83 Advanced Advanced 1 5.0 1.957039
>>>
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