series_mutate: Transform variables in a data frame

In flexFitR: Flexible Non-Linear Least Square Model Fitting

Transform variables in a data frame

Description

This function performs transformations on specified columns of a data frame, including truncating maximum values, handling negative values, and adding a zero to the series. It allows for grouping and supports retaining metadata in the output.

Usage

series_mutate(
  data,
  x,
  y,
  grp,
  metadata,
  max_as_last = FALSE,
  check_negative = FALSE,
  add_zero = FALSE,
  interval = NULL
)

Arguments

data	A data.frame containing the input data for analysis.
x	The name of the column in data representing the independent variable (x points).
y	The name of the column(s) in data containing variables to transform.
grp	Column(s) in data used as grouping variable(s). Defaults to NULL (optional).
metadata	Names of columns to retain in the output. Defaults to NULL (optional).
max_as_last	Logical. If TRUE, appends the maximum value after reaching the maximum. Default is FALSE.
check_negative	Logical. If TRUE, converts negative values in the data to zero. Default is FALSE.
add_zero	Logical. If TRUE, adds a zero value to the series at the start. Default is FALSE.
interval	A numeric vector of length 2 (start and end) specifying the range to filter the data. Defaults to NULL.

Value

A transformed data.frame with the specified modifications applied.

Examples

data(dt_potato)
new_data <- series_mutate(
  data = dt_potato,
  x = DAP,
  y = GLI,
  grp = gid,
  max_as_last = TRUE,
  check_negative = TRUE
)

flexFitR documentation built on April 16, 2025, 5:09 p.m.