Teradata Package for R Function Reference | 17.20 - SimpleImputeFitFit - 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
ft:locale
en-US
ft:lastEdition
2024-05-03
dita:id
TeradataR_FxRef_Enterprise_1720
lifecycle
latest
Product Category
Teradata Vantage

SimpleImputeFit

Description

td_simple_impute_fit_sqle() function outputs values to substitute for missing values in the input data. The output values are input to td_simple_impute_transform_sqle() function, which makes the substitutions.

Usage

  td_simple_impute_fit_sqle (
      data = NULL,
      stats.columns = NULL,
      literals.columns = NULL,
      partition.column = NULL,
      stats = NULL,
      literals = NULL,
      ...
  )

Arguments

data

Required Argument.
Specifies the input tbl_teradata.
Types: tbl_teradata

stats.columns

Optional Argument.
Specifies the name(s) of the column(s) in "data" for which to calculate the statistics.
Types: character OR vector of Strings (character)

literals.columns

Optional Argument.
Specifies the name(s) of the column(s) in "data" for which to impute literals.
Types: character OR vector of Strings (character)

partition.column

Optional Argument.
Specifies the name(s) of the column(s) in "data" to partition on.
Types: character OR vector of Strings (character)

stats

Optional Argument.
Specifies the stats to compute on input tbl_teradata columns.
Permitted Values: MIN, MAX, MEAN, MEDIAN, MODE
Types: character OR vector of Strings (character)

literals

Optional Argument.
Specifies the literal value to impute on input tbl_teradata columns.
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 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_fit_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):

  1. output

  2. output.data

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: Create stats for "fare" column and impute value "2"
    #            in "pclass" column.
    fit_obj <- td_simple_impute_fit_sqle(data=titanic,
                                         stats.columns="fare",
                                         literals.columns="pclass",
                                         partition.column="sex",
                                         stats="median",
                                         literals="2")
    
    # Print the result.
    print(fit_obj$result)
    print(fit_obj$output.data)