Teradata Package for Python Function Reference | 20.00 - atan2 - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference - 20.00
- Deployment
- VantageCloud
- VantageCore
- Edition
- Enterprise
- IntelliFlex
- VMware
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Enterprise_2000
- lifecycle
- latest
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.atan2 = atan2(expression)
- DESCRIPTION:
Function computes the arctangent value based on the values in column and argument
coordinate provided as input. The arctangent is the angle whose tangent is the value in the column.
NOTES:
1. Result values return an angle between -π and π radians, excluding -π.
2. A positive result represents a counterclockwise angle from the x-axis.
3. A negative result represents a clockwise angle from the x-axis.
4. If both the values from column and argument are 0, an error is returned.
5. If the type of the column is not FLOAT, column values are converted to FLOAT
based on implicit type conversion rules. If the value cannot be converted, an
error is reported.
6. Unsupported column types:
a. BYTE or VARBYTE
b. LOBs (BLOB or CLOB)
c. CHARACTER or VARCHAR if the server character set is GRAPHIC
PARAMETERS:
expression:
Required Argument.
Specifies the y-coordinate of a point to use in the arctangent calculation.
Accepts a ColumnExpression of a numeric column or a numeric constant.
Format for the argument: '<dataframe>.<dataframe_column>'.
RAISES:
TypeError, ValueError, TeradataMlException
RETURNS:
DataFrameColumn
EXAMPLES:
# Load the data to execute the example.
>>> load_example_data("dataframe", "admissions_train")
# Create a DataFrame on 'admissions_train' table.
>>> df = DataFrame("admissions_train").iloc[:4]
>>> print(df)
masters gpa stats programming admitted
id
3 no 3.70 Novice Beginner 1
4 yes 3.50 Beginner Novice 1
2 yes 3.76 Beginner Beginner 0
1 yes 3.95 Beginner Beginner 0
# Example 1: Calculate arctangent value for the "gpa" column values as x-coordinate
# and pass it as input to DataFrame.assign().
>>> result = df.assign(col=df.gpa.atan2(1),
... col_gpa=df.gpa.atan2(df.admitted))
>>> print(result)
masters gpa stats programming admitted col col_gpa
id
3 no 3.70 Novice Beginner 1 0.263964 0.263964
4 yes 3.50 Beginner Novice 1 0.278300 0.278300
2 yes 3.76 Beginner Beginner 0 0.259940 0.000000
1 yes 3.95 Beginner Beginner 0 0.247955 0.000000
# Example 2: Filter the rows where arctangent of values in "gpa" column
# and argument are greater than 0.4.
>>> print(df[df.gpa.atan2(1) > 0.26])
masters gpa stats programming admitted
id
4 yes 3.5 Beginner Novice 1
3 no 3.7 Novice Beginner 1