R/dot.R

In HeeseokMoon/ggedachart: Get You to Your Desired Exploratory Data Analysis Plot Faster

#' Ranking Dot Plot.
#'
#' dot function will draw Dot Plot for Ranking analysis.
#' @param data input data.frame
#' @param x x variable
#' @param y y variable
#' @param title input data.frame
#' @param subtitle date variable
#' @param xtitle value variable
#' @param ytitle input data.frame
#' @param caption date variable
#' @return An object of class \code{ggplot}
#' @examples
#' Prepare data: group mean city mileage by manufacturer.
#' cty_mpg <- aggregate(mpg$cty, by=list(mpg$manufacturer), FUN=mean)  # aggregate
#' colnames(cty_mpg) <- c("make", "mileage")                           # change column names
#'
#' #orderbar
#' plot<- dot(data=cty_mpg,x="make",y="mileage")
#' plot
#'
#' @import ggplot2
#' @import scales
#' @import reshape2
#' @import ggthemes
#' @import gganimate
#' @import gapminder
#' @import ggalt
#' @import ggExtra
#' @import ggcorrplot
#' @import dplyr
#' @import treemapify
#' @import ggfortify
#' @import zoo
#' @import ggdendro
#' @export
dot<-function(data,x,y,
              title=NULL,subtitle=NULL,xtitle=NULL,ytitle=NULL,caption=NULL){
  df<- data
  x<- x
  y<- y

  df<- df[order(df[,y]),]
  df[,x] <- factor(df[,x], levels = df[,x])

  p<-   ggplot(df, aes_string(x=x, y=y)) +
    geom_point(col="#008FD5", size=3) +   # Draw points
    geom_segment(aes_string(x=x,
                            xend=x,
                            y=min(y),
                            yend=max(y)),
                 linetype="dashed",
                 size=0.1) +   # Draw dashed lines
    theme_fivethirtyeight() +
    theme(axis.title = element_text(),
          legend.title = element_text(face = 4,size = 10),
          legend.direction = "horizontal", legend.box = "horizontal") +
    labs(subtitle=subtitle,
         y=ytitle,
         x=xtitle,
         title=title,
         caption = caption) +
    coord_flip()

  return(p)
}