.onAttach <- function(libname, pkgname) {
packageStartupMessage("Nice that you are using my first package")
}
#' Compare the height of persons in a dataset with the mean of the height of the other persons
#'
#' @param students.input A data.frame containig names and height of students
#' @param sex.specific=TRUE A logical that tells if gender spcific mean or mean of whole population should be compared
#' @return Difference in height to gender specific mean or the whole population.
#' @import checkmate
#' @importFrom magrittr %>%
#' @export
checkHeight <- function(students.input, sex.specific = TRUE, print.statement = FALSE){
#Check if sex.specific is a logical value
assertLogical(sex.specific)
#Check if print.statement is a logical value
assertLogical(print.statement)
#Check if the Data Frame has at least 4 rows and 5 columns without missing values
assertDataFrame(students.input, min.rows = 4, ncols = 5, any.missing = FALSE)
#Check if first and second column are Numeric
assertNumeric(c(students.input[,1], students.input[,2]))
#Check if third column is numeric and has values between 1.30 and 2.40
assertNumeric(students.input[,3], lower = 1.29, upper = 2.41)
#Check if 4th column is of type factor and has values "M" and "F"
assertFactor(students.input[,4], levels = c("M","F"))
#Check if 5th column is Character
assertCharacter(students.input[,5])
#Check if the sex specific height difference or the difference to the whole population should be calculated
if(sex.specific == TRUE){
#Calculate the gender specific means
women_mean_height = as.numeric(students.input %>%
dplyr::group_by(sex) %>%
summarise(compareheight:::mean(height)) %>%
filter(sex == "F") %>%
select("compareheight:::mean(height)"))
men_mean_height = as.numeric(students.input %>%
dplyr::group_by(sex) %>%
summarise(compareheight:::mean(height)) %>%
filter(sex == "M") %>%
select("compareheight:::mean(height)"))
#initialize an empty vector to save the genderspecific height differnces
height_vector = c()
#apply a function to the rows of the input dataframe
height_vector = apply(students.input, MARGIN = 1,
FUN = function(student){
#substract the gender specific means from the individuals to get height differnces
(if (student["sex"] == "M") men_mean_height - as.numeric(student["height"])
else women_mean_height - as.numeric(student["height"]) )
} )
#create the final dataframe containing name od the students and the height differnces
#multiple height differences by 100 to get values in cm
result.frame = data.frame("name" = students.input$name, "sexspec_height_diff" = height_vector*100)
} else{
#initialize an empty vector to save the height differnces
height_vector = c()
#calculate the mean height of the whole population
mean_height = compareheight:::mean(students.input$height)
#apply a function to the rows of the input dataframe
height_vector = apply(students.input, MARGIN = 1,
FUN = function(student){
#substract the gender specific means from the individuals to get height differnces
mean_height - as.numeric(student["height"])
} )
#create the final dataframe containing name od the students and the height differnces
#multiple height differences by 100 to get values in cm
result.frame = data.frame("name" = students.input$name, "height_diff" = height_vector*100)
}
#return the dataframe
if(print.statement == TRUE){
print("Yippie, I calculated the mean differences!")
}
return(result.frame)
}
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