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- abs(column_expression)
- DESCRIPTION:
Function computes the absolute value of an argument.
PARAMETERS:
column_expression:
Required Argument.
Specifies a ColumnExpression of a numeric column on which ABS() is requested.
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
>>>
# Example calculates absolute value for the "gpa" column with help of SQLAlchemy.
# Import func from sqlalchemy to execute ABS function.
>>> from sqlalchemy import func
# Create a sqlalchemy Function object.
>>> abs_func_ = func.abs(admissions_train.gpa.expression)
>>>
# Pass the Function object as input to DataFrame.assign().
>>> df = admissions_train.assign(abs_gpa_=abs_func_)
>>> print(df)
masters gpa stats programming admitted abs_gpa_
id
22 yes 3.46 Novice Beginner 0 3.46
36 no 3.00 Advanced Novice 0 3.00
15 yes 4.00 Advanced Advanced 1 4.00
38 yes 2.65 Advanced Beginner 1 2.65
5 no 3.44 Novice Novice 0 3.44
17 no 3.83 Advanced Advanced 1 3.83
34 yes 3.85 Advanced Beginner 0 3.85
13 no 4.00 Advanced Novice 1 4.00
26 yes 3.57 Advanced Advanced 1 3.57
19 yes 1.98 Advanced Advanced 0 1.98
>>>
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