```
# Autors Darya Busen, Michael Graber
.onAttach <- function(libname, pkgname) {
packageStartupMessage("Welcome to my first R-package and thanks for using it, muchacho!")
}
#' Compare the height of persons in a dataset with the mean of the height of the other persons
#' @param students.input The original students data.frame
#' @param sex.specific Sex specific mean or mean of population
#' @param print.statement Print a message after the calculation
#' @return Return the newly created data.frame, difference in height to gender specific mean
#' @export
#' @importFrom magrittr %>%
#' @import checkmate
#' @import dplyr
checkHeight = function(students.input, sex.specific = TRUE, print.statement = FALSE){
#Do check:
#sex.specific is a logical value
assertLogical(sex.specific)
#print.statement is a logical value
assertLogical(print.statement)
#the Data Frame with a minimum of 4 rows and exactly 5 columns without any missing values
assertDataFrame(students.input, types = c("numeric", "numeric", "numeric", "factor", "character"))
#third column is numeric and has values between 1.30 and 2.40
assertNumeric(students.input[, "height"], lower = 1.3, upper = 2.40)
#4th column is of type factor and with maximum two levels "M" and "F"
assertFactor(students.input[, "sex"], levels = c("M","F"))
if(sex.specific == TRUE){
#Calculate the sex specific mean in height
male.mean = students.input[,"height"][students.input[,"sex"] == "M"] %>%
mean %>% as.numeric
female.mean = students.input[,"height"][students.input[,"sex"] == "F"] %>%
mean %>% as.numeric
# Create new list saving all the sex specific height differences
height.list = apply(students.input, MARGIN = 1,
FUN = function(student){
#substract the gender specific means from the individuals to get height differnces
(if (student["sex"] == "M") male.mean - as.numeric(student["height"])
else female.mean - as.numeric(student["height"]) )
} )
# Create a new dataframe containing only the names and the height differences
output.df = data.frame("name" = students.input$name, "sexspec_height_diff" = height.list)
#create the final dataframe containing name od the students and the height differnces
#multiple height differences by 100 to get values in cm
} else{
#calculate the mean height of the whole population
mean_height = students.input[,"height"] %>% mean %>% as.numeric
#apply a function to the rows of the input dataframe
height_vector = apply(students.input, MARGIN = 1,
FUN = function(student){
#substract the gender specific means from the individuals to get height differnces
mean_height - as.numeric(student["height"])
} )
#create the final dataframe containing name od the students and the height differnces
#multiple height differences by 100 to get values in cm
output.df= data.frame("name" = students.input$name, "sexspec_height_diff" = height.list)
}
# Print success message
if (print.statement == TRUE){
print("Yippie, I calculated the mean difference!")
}
# Return new created dataframe
return(output.df)
}
```

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