Teradata Package for R Function Reference | 17.20 - OrdinalEncodingTransform - 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

OrdinalEncodingTransform

Description

The td_ordinal_encoding_transform_sqle() function maps the categorical value to a specified ordinal value using the td_ordinal_encoding_fit_sqle() function output.

Usage

  td_ordinal_encoding_transform_sqle (
      data = NULL,
      object = NULL,
      accumulate = NULL,
      ...
  )

Arguments

data

Required Argument.
Specifies the input tbl_teradata.
Types: tbl_teradata

object

Required Argument.
Specifies the tbl_teradata containing the ordinal encoding parameters generated by td_ordinal_encoding_fit_sqle() function or the instance of td_ordinal_encoding_fit_sqle.
Types: tbl_teradata or td_ordinal_encoding_fit_sqle

accumulate

Optional Argument.
Specifies the input tbl_teradata column(s) to copy to the output. By default, the function copies no input columns to the output.
Types: character OR vector of Strings (character)

...

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 character (Strings)

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

  • "<input.data.arg.name>.order.column" accepts character or vector of 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_ordinal_encoding_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 <- tbl(con, "titanic")
    
    # Check the list of available analytic functions.
    display_analytic_functions()
    
    # Example 1: Transform the data by identifying distinct categorical 
    #            values using input from td_ordinal_encoding_fit_sqle() function.
    ordinal_encodingfit_res_1 <- td_ordinal_encoding_fit_sqle(
                                  target.column='sex',
                                  data=titanic)
    
    ordinal_encoding_transform_out_1 <- td_ordinal_encoding_transform_sqle(
                                          data=titanic,
                                          object=
                                          ordinal_encodingfit_res_1$result,
                                          accumulate='age')
    
    # Print the result.
    print(ordinal_encoding_transform_out_1$result)
    
    # Example 2: Transform the data by identifying distinct categorical values
    #            from the input and returns the distinct categorical values
    #            along with the ordinal value for each category.
    ordinal_encodingfit_res_2 <- td_ordinal_encoding_fit_sqle(
                                   target.column='sex',
                                   approach='LIST',
                                   categories=c('category0',
                                                'category1'),
                                   ordinal.values=c(1, 2),
                                   start.value=0,
                                   default.value=-1,
                                   data=titanic)
    
    ordinal_encoding_transform_out_2 <- td_ordinal_encoding_transform_sqle(
                                          data=titanic,
                                          object=
                                            ordinal_encodingfit_res_2$result,
                                          accumulate='age')
    
    # Print the result.
    print(ordinal_encoding_transform_out_2$result)
    
    
    # Alternatively use S3 transform function to run transform on the output of
    # td_ordinal_encoding_fit_sqle() function.
    
    obj1 <- transform(ordinal_encodingfit_res_2,
                      data=titanic,
                      accumulate='age')
    
    # Print the result.
    print(obj1$result)