Teradata Package for R Function Reference | 17.20 - SimpleImputeTransform - 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

SimpleImputeTransform

Description

td_simple_impute_transform_sqle() function substitutes specified values for missing values in the input data. The specified values is generated by td_simple_impute_fit_sqle() function output.

Usage

  td_simple_impute_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 output of td_simple_impute_fit_sqle() function or the instance of td_simple_impute_fit_sqle.
Types: tbl_teradata or td_simple_impute_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_simple_impute_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.
    titanic <- tbl(con, "titanic")
    
    # Check the list of available analytic functions.
    display_analytic_functions()
    
    # Example 1: Fill missing values of "age" column with median value and
    #            impute value "General" on "cabin" column.
    fit_obj <- td_simple_impute_fit_sqle(data=titanic,
                                         stats.columns="age",
                                         literals.columns="cabin",
                                         stats="median",
                                         literals="General")
    
    # Print the result.
    print(fit_obj$result)
    
    # Impute the values for missing values.
    # Note that tbl_teradata representing the model is passed as
    # input to "object".
    obj <- td_simple_impute_transform_sqle(data=titanic,
                                           object=fit_obj$result)
    
    # Print the result.
    print(obj$result)
    
    # Example 2: Impute the values for missing values. Note that model is passed
    #            as instance of td_simple_impute_transform_sqle to "object".
    obj1 <- td_simple_impute_transform_sqle(data=titanic,
                                            object=fit_obj)
    
    # Print the result.
    print(obj1$result)
    
    # Alternatively use S3 transform function to run transform on the output of
    # td_simple_impute_fit_sqle() function.
    
    obj1 <- transform(fit_obj,
                      data=titanic)
    
    # Print the result.
    print(obj1$result)