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

Teradata® R Package Function Reference

Product
Teradata R Package
Release Number
16.20
Published
February 2020
Language
English (United States)
Last Update
2020-02-28
dita:id
B700-4007
lifecycle
previous
Product Category
Teradata Vantage

Description

This function (td_scale_by_partition_mle) scales the sequences in each partition independently, using the same formula as the function Scale(td_scale_mle).

Usage

  td_scale_by_partition_mle (
    data = NULL,
    method = NULL,
    miss.value = "KEEP",
    input.columns = NULL,
    global = FALSE,
    accumulate = NULL,
    multiplier = 1,
    intercept = "0",
    data.sequence.column = NULL,
    data.partition.column = NULL
  )

Arguments

data

Required Argument.
Specifies the input tbl_teradata dataset for scale function.

data.partition.column

Required Argument.
Partition By Columns for data. Values to this argument can be provided as vector, if multiple columns are used for partition.

method

Required Argument.
Specifies one or more statistical methods to use to scale the data set. For method values and descriptions. If you specify multiple methods, the output tbl_teradata includes the column scalemethod (which contains the method name) and a row for each input-row/method combination.
Permitted Values: MEAN, SUM, USTD, STD, RANGE, MIDRANGE, MAXABS.

miss.value

Optional Argument.
Specifies how the td_scale_by_partition_mle function is to process NULL values in input, as follows: to process NULL values in input, as follows:

  1. KEEP : Keep NULL values,

  2. OMIT : Ignore any row that has a NULL value,

  3. ZERO : Replace each NULL value with zero,

  4. LOCATION : Replace each NULL value with its location value.

Default Value: "KEEP".
Permitted Values: KEEP, OMIT, ZERO, LOCATION.

input.columns

Required Argument.
Specifies the input tbl_teradata columns that contain the attribute values of the samples.

global

Optional Argument.
Specifies whether all input columns are scaled to the same location and scale.
Note: Each input column is scaled separately. Default Value: FALSE.

accumulate

Optional Argument.
Specifies the input tbl_teradata columns to copy to the output table. By default, the function copies no input tbl_teradata columns to the output table.
Tip: To identify the sequences in the output, specify the partition columns in this argument.

multiplier

Optional Argument.
Specifies one or more multiplying factors to apply to the input variables (multiplier in the following formula):
X' = intercept + multiplier * (X - location)/scale If you specify only one multiplier, it applies to all columns specified by the input.columns argument. If you specify multiple multiplying factor, each multiplier applies to the corresponding input column. For example, the first multiplier applies to the first column specified by the InputColumns argument, the second multiplier applies to the second input column, and so on.
Default Value: 1.

intercept

Optional Argument.
Specifies one or more addition factors incrementing the scaled results-intercept in the following formula:
X' = intercept + multiplier * (X - location)/scale
If you specify only one intercept, it applies to all columns specified by the input.columns argument. If you specify multiple addition factors, each intercept applies to the corresponding input column. The syntax of intercept is: [-]number | min | mean | max where min, mean, and max are the global minimum, maximum, mean values in the corresponding columns. The function scales the values of min, mean, and max. For example, if intercept is "- min" and multiplier is 1, the scaled result is transformed to a nonnegative sequence according to this formula, where scaledmin is the scaled value: X' = -scaledmin + 1 * (X - location)/scale The Default Value: "0".

data.sequence.column

Optional Argument.
Specifies the vector of column(s) that uniquely identifies each row of the input argument "data". The argument is used to ensure deterministic results for functions which produce results that vary from run to run.

Value

Function returns an object of class "td_scale_by_partition_mle" which is a named list containing Teradata tbl object.
Named list member can be referenced directly with the "$" operator using name: result.

Examples

    # Get the current context/connection
    con <- td_get_context()$connection
    
    # Load example data.
    loadExampleData("scalemap_example", "scale_housing")

    # Create remote tibble objects.
    scale_housing_input <- tbl(con, "scale_housing")
    
    # Create remote tibble objects.
    # Example 1 - This function scales the sequences on partition cloumn 'lotsize' using
    # the same formula as the function td_scale_mle().
    td_scale_by_partition_out <- td_scale_by_partition_mle(data=scale_housing_input,
                                                       data.partition.column ="lotsize", 
                                                       input.columns = c("id","price", "lotsize", "bedrooms", "bathrms"), 
                                                       method = c("maxabs"), 
                                                       accumulate = c("types") 
                                                      )