Teradata Package for Python Function Reference | 20.00 - regr_r2 - 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
- Product Category
- Teradata Vantage
- teradataml.dataframe.dataframe.DataFrame.regr_r2 = regr_r2(expression)
- DESCRIPTION:
Function returns the column-wise coefficient of determination for all
non-null data pairs of the dependent and independent variable arguments.
The function considers ColumnExpression as a dependent variable and
"expression" as an independent variable.
Note:
When there are fewer than two non-null data point pairs in the data
used for the computation, the function returns NULL.
PARAMETERS:
expression:
Required Argument.
Specifies a ColumnExpression of a column or name of the column or a
literal representing an independent variable for the regression.
An independent variable is something that is varied under your control
to test the behavior of another variable.
Types: ColumnExpression OR int OR float OR str
RETURNS:
teradataml DataFrame
RAISES:
RuntimeError - If none of the columns support the aggregate operation.
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 1: Calculate the coefficient of determination of the column 'gpa'
# for all non-null data pairs with dependent variable as all other
# valid columns.
>>> df = admissions_train.regr_r2(admissions_train.gpa)
>>> df
regr_r2_id regr_r2_gpa regr_r2_admitted
0 0.000193 1.0 0.000496
>>>
# Example 2: Calculate the coefficient of determination of the column 'gpa'
# for all non-null data pairs with dependent variable as all other
# valid columns, for each level of 'programming'.
>>> df = admissions_train.groupby("programming").regr_r2(admissions_train.gpa)
>>> df
programming regr_r2_id regr_r2_gpa regr_r2_admitted
0 Advanced 0.027757 1.0 0.237888
1 Novice 0.000523 1.0 0.013146
2 Beginner 0.076917 1.0 0.174361
>>>