Teradata Package for R Function Reference | 17.20 - OutlierFilterTransform - Teradata Package for R - Look here for syntax, methods and examples for the functions included in the Teradata Package for R.

Teradata® Package for R Function Reference

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for R
Release Number
17.20
Published
March 2024
Language
English (United States)
Last Update
2024-05-03
dita:id
TeradataR_FxRef_Enterprise_1720
Product Category
Teradata Vantage

OutlierFilterTransform

Description

td_outlier_filter_transform_sqle() function filters the outliers from the input tbl_teradata.
td_outlier_filter_transform_sqle() uses the result tbl_teradata from td_outlier_filter_fit_sqle() function to get statistics like median, count of rows, lower percentile and upper percentile for every column specified in target columns argument and filters the outliers in the input data.

Usage

  td_outlier_filter_transform_sqle (
      data = NULL,
      object = NULL,
      ...
  )

Arguments

data

Required Argument.
Specifies the input tbl_teradata.
Types: tbl_teradata

object

Required Argument.
Specifies the tbl_teradata containing the outlier metrics generated by
td_outlier_filter_fit_sqle() function or an instance of td_outlier_filter_fit_sqle.
Types: tbl_teradata or instance of td_outlier_filter_fit_sqle

...

Specifies the generic keyword arguments SQLE functions accept.
Below are the generic keyword arguments:

persist:
Optional Argument.
Specifies whether to persist the results of the function in a table or not.
When set to TRUE, results are persisted in a table; otherwise, results are garbage collected at the end of the session.
Default Value: FALSE
Types: logical

volatile:
Optional Argument.
Specifies whether to put the results of the function in a volatile table or not.
When set to TRUE, results are stored in a volatile table, otherwise not.
Default Value: FALSE
Types: logical

Function allows the user to partition, hash, order or local order the input data. These generic arguments are available for each argument that accepts tbl_teradata as input and can be accessed as:

  • "<input.data.arg.name>.partition.column" accepts character OR vector of Strings (character) (Strings)

  • "<input.data.arg.name>.hash.column" accepts character OR vector of Strings (character) (Strings)

  • "<input.data.arg.name>.order.column" accepts character OR vector of Strings (character) (Strings)

  • "local.order.<input.data.arg.name>" accepts logical

Note:
These generic arguments are supported by tdplyr if the underlying SQL Engine function supports, else an exception is raised.

Value

Function returns an object of class "td_outlier_filter_transform_sqle" which is a named list containing object of class "tbl_teradata".
Named list member(s) can be referenced directly with the "$" operator using the name(s):result

Examples

  
    
    # Get the current context/connection.
    con <- td_get_context()$connection
    
    # Load the example data.
    loadExampleData("tdplyr_example", "titanic")
    
    # Create tbl_teradata object.
    titanic_data <- tbl(con, "titanic")
    
    # Check the list of available analytic functions.
    display_analytic_functions()
    
    # Example 1: Finding outliers in column "fare" using "PERCENTILE" method.
    #            Generate fit object for column "fare".
    fit_obj <- td_outlier_filter_fit_sqle(
                data=titanic_data,
                target.columns="fare",
                lower.percentile=0.1,
                upper.percentile=0.9,
                outlier.method="PERCENTILE",
                replacement.value="MEDIAN",
                percentile.method="PERCENTILECONT")
    
    # Print the result.
    print(fit_obj$result)
    
    # Find the outliers by transforming fit object result tbl_teradata.
    # Note that tbl_teradata representing the model is passed as
    # input to "object".
    obj <- td_outlier_filter_transform_sqle(data=titanic_data,
                                            object=fit_obj$result)
    
    # Print the result.
    print(obj$result)
    
    # Example 2: Find outliers in column "fare" using "PERCENTILE"
    #            method. Note that model is passed as instance of
    #            td_outlier_filter_fit_sqle to "object".
    obj1 <- td_outlier_filter_transform_sqle(data=titanic_data,
                                             object=fit_obj)
    
    # Print the result.
    print(obj1$result)
    
    # Alternatively use S3 transform function to run transform on the output of
    # td_outlier_filter_fit_sqle() function.
    
    obj1 <- transform(fit_obj,
                      data=titanic_data)
    
    # Print the result.
    print(obj1$result)