transform_data: Transform Daily and Intake Data In Five Different Data Sets
In kthorstmann/padis: Functions For The Analysis Of Wake-Forest Data

Description Usage Arguments Value Examples

View source: R/padis_specific_functions.R

This function is very specific and takes as input only the two data frames daily and intake raw data. It will then return the five data sets, named 1. "par_data", 2. "psp_long", 3. "day_data", 4. "issue_long", 5. "selection_long")

1 2	transform_data(daily_data, intake_data, write_to = "workspace", overwrite = FALSE, folder = NULL)

`daily_data`	The Daily Raw data
`intake_data`	The Raw Intake data
`write_to`	Where the results should be written to. Can either be "workspace" (default), "xlsx", or "csv". The last two write the resulting data frames into the working directory either as .xlsx-files or .csv-files
`overwrite`	Logical, should an existing data frame/object be overwritten? Default is to `FALSE`
`folder`	The folder in which the resulting data sets should be written. If no folder is specified, the current working directory (result of `getwd()`) is used

The function returns the five different data sets in long format

## not run
# these examples work only with the correct data frames
data_dy <- read.csv("Raw Diary Selection Data.csv", sep = ";", stringsAsFactors = FALSE)
data_in <- xlsx::read.xlsx("Raw Intake Sample.xlsx", 1)
transform_data(data_dy, data_in)