widen_means: Widening the data frame and calculating the means based on...

In agryt/xrfr: Converting XRF Data from Kilo-counts per Second to Micromolar

Description

This function will widen your data like widen() but also calculate the mean concentrations based on two factors, for example location and depth.

See vignette("xrfr") for more information.

Usage

widen_means(project_data, first_factor, second_factor = NULL)

Arguments

project_data	The name of the data frame created with convertxrf().
first_factor	The name of the column that shows the first or only factor you want to calculate means based on, for example depth.
second_factor	The name of the column that shows a potential second factor you want to calculate means based on, for example location.

Value

description The function creates a data frame where the columns available are your two factors (for example location and depth) and each element.

Examples

## Not run: 
rawdata.df <- read_delim("xrf_rawdata.txt", delim = "\t", locale = locale(decimal_mark = ","))
projectinfo.df <- read_excel("xrf_projectinfo.xlsx")
baseinfo.df <- read_excel("xrf_setup.xlsx")

projectfile.df <- readxrf(raw_data = rawdata.df, project_info = projectinfo.df)
project.df <- convertxrf(imported_data = projectfile.df, base_info = baseinfo.df, year = "2019", first_element = "C", last_element = "As")

means.df <- widen_means(project_data = project.df, first_factor = "Treatment", second_factor = "Day")

## End(Not run)

agryt/xrfr documentation built on May 13, 2021, 8:24 p.m.