R/summaryStatistic.R

In jmoss13148/wgd: This Package Loads Information About Williams College Graduates between 2004 and 2016

#' @title Summary Statistic
#' @description Uses the data from the readNameData() function to compute relavent summary statistics
#' @param type The type of statistics to be computed. The options are "popular", "most popular", "name length",
#' "name length plot", and "least popular."
#' @return If the user codes popular, the function returns a dataframe with the six most popular names
#' over the past 13 years. If the user codes most popular, the function returns a dataframe reporting all
#' names that have been in the top six over the past 13 years, and how many times each name has been in the top six.
#' If the user codes name length, the function returns a dataframe reporting the average first name length of the
#' graduating class for each year. If the user codes name length plot, the function reports name length data in
#' the form of a scatterplot. If the user codes least popular, the function returns a random sample of first names that
#' have only occurred at Williams one time since 2004.
#' @usage
#' summaryStatistic(type)
#' @export

summaryStatistic <- function(type){

datasets <- c("names2004.txt", "names2005.txt", "names2006.txt", "names2007.txt", "names2008.txt", "names2009.txt", "names2010.txt", "names2011.txt", "names2012.txt", "names2013.txt", "names2014.txt", "names2015.txt", "names2016.txt")

## for computing the most popular names
dat <- data.frame(x <- 1:6)
for(i in 1:length(datasets)){
  popular <- as.data.frame(tail(sort(table(readNameData(datasets[i])[, 1])))) ## subset for most popular names of certain year
  popular <- popular[order(popular$Var1, decreasing = TRUE), ]
  dat <- cbind(dat, popular)
}
total <- dat[, seq(2, ncol(dat), 2)] ## dataframe with 6 most popular names for each year
names(total) <- c("2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015", "2016")

## for computing the average first name length
num <- numeric(length(datasets))
for(i in 1:length(datasets)){
  num[i] <- mean(readNameData(datasets[i])[, 2]) ## average name length for each graduating class year
}
names(num) <- c("2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015", "2016")

if(type %in% c("popular", "most popular", "name length", "name length plot", "least popular")){


if(type == "popular"){
return(total)
}

if(type == "most popular"){
num <- character()
for(i in 1:ncol(total)){
  names <- as.character(total[, i])
  num <- c(num, names) ## bind together most popular names from each year
}
sorted <- sort(table(num)) ## gather the information in a table
ordered <- as.data.frame(sorted)
ordered <- ordered[order(ordered[, 2], decreasing = TRUE), ]
names(ordered) <- c("Name", "# times in top 6")
return(ordered) ## dataframe containing names that have been in the top six, and how many times each name is been in the top six
}

if(type == "name length"){
return(num)
}

if(type == "name length plot"){
plot(names(num), num, main = "First Name Length", ylab = "Number of Characters", xlab = "Year", col = "purple", pch = 16)
abline(lm(num ~ as.numeric(names(num))))
}

if(type == "least popular"){

full <- rbind(readNameData("names2004.txt"), readNameData("names2005.txt"), readNameData("names2006.txt"), readNameData("names2007.txt"), readNameData("names2008.txt"), readNameData("names2009.txt"), readNameData("names2010.txt"), readNameData("names2011.txt"), readNameData("names2011.txt"), readNameData("names2012.txt"), readNameData("names2013.txt"), readNameData("names2014.txt"), readNameData("names2015.txt"), readNameData("names2016.txt"))
full <- full[, 1]
tab <- sort(table(full))
one <- tab[tab == 1] ## first names that have only occured one time since 2004
leastPopular <- sample(one, 100) ## random sample of 100 names that have only occured one time
return(leastPopular)
}
}
else { stop("Please enter a correct summary type. The options are popular, most popular, name length, name length plot, and least popular") }
}