Fit
Description
The td_fit_sqle()
function determines whether specified numeric transformations can be
applied to specified "target_columns" and outputs a tbl_teradata to use as input
"data" for td_transform_sqle()
function, which does the transformations.
Usage
td_fit_sqle (
data = NULL,
object = NULL,
...
)
Arguments
data |
Required Argument. |
object |
Required Argument. |
... |
Specifies the generic keyword arguments SQLE functions accept. persist: volatile: 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:
Note: |
Value
Function returns an object of class "td_fit_sqle"
which is a named list containing object of class "tbl_teradata".
Named list member(s) can be referenced directly with the "$" operator
using the name(s):result
Examples
# Get the current context/connection.
con <- td_get_context()$connection
# Load the example data.
loadExampleData("tdplyr_example", "iris_input", "transformation_table")
# Create tbl_teradata object.
iris_input <- tbl(con, "iris_input")
transformation_df <- tbl(con, "transformation_table")
# Check the list of available analytic functions.
display_analytic_functions()
# Example 1: Run td_fit_sqle() with all arguments.
fit_df <- td_fit_sqle(data=iris_input,
object=transformation_df,
object.order.column='targetcolumn'
)
# Print the result.
print(fit_df)