Central Tendency Plot

Creating centralTendencyPlot function

As one of the measures I wanted to plot was the mode, and there is no mode function already programmed into R, one needed to be created.

getMode <- function(v, na.rm = FALSE) {
        if(na.rm){ #if na.rm is TRUE, remove NA values from input x
                v <- v[!is.na(v)]
        }
        uniqv <- unique(v) # get unique values from v
        # first gets the positions of uniqv which match values in v
        # then counts the number of times each position shows up
        # then gets the position that shows up the most
        # then subsets uniqv by the position that shows up the most
        uniqv[which.max(tabulate(match(v, uniqv)))]
}

The next step was to create the plot itself

centralTendencyPlot <- function (data, variable){
        # load required library
        library(ggplot2)
        # set the aesthetic to use the variable as defining the x axis
        ggplot(data, aes(x = .data[[variable]])) + 
        # plot the density
        geom_density() +
        # add a line for the mean
        geom_vline(aes(xintercept = mean(.data[[variable]],
                                         na.rm= TRUE),
                       linetype = "Mean"), colour = "red") + 
        # add a line for the median
        geom_vline(aes(xintercept = median(.data[[variable]],
                                           na.rm = TRUE),
                       linetype = "Median"), colour = "blue") + 
        # add a line for the mode
        geom_vline(aes(xintercept = getMode(.data[[variable]],
                                            na.rm = TRUE),
                       linetype = "Mode"), colour = "green") +
        # create the legend
        scale_linetype_manual(name = "Measures of Central Tendency",
                              # whole lines
                              values = c("Mean" = 1, "Median" = 1,
                                         "Mode" = 1),
                              # color in the legend
                              guide = guide_legend(
                                      override.aes = list(
                                              colour = c("red","blue",
                                                         "green"))))
}

This then works as follows:

centralTendencyPlot(airquality,"Solar.R")

It makes it easy to use in other dataframes:

library(readxl)
df <- read_xlsx("C:\\Users\\Pedro Henrique\\Desktop\\L8_dataset.xlsx")
centralTendencyPlot(df,"ertime")

ertimelog <- log(df$ertime)
centralTendencyPlot(as.data.frame(ertimelog),"ertimelog")

In summary, this was a fun function to construct, and useful at that.