#RSTUDIO GGPLOT2 RED RECTANGLE HOW TO#
#RSTUDIO GGPLOT2 RED RECTANGLE FULL#
#RSTUDIO GGPLOT2 RED RECTANGLE CODE#

If you assign the boxplot to a variable, you can return a list with different components. Points(means, 1:ncol(my_df), col = 'red', pch = 19) Means <- colMeans(my_df) # Equivalent (more efficient)īoxplot(my_df, col = rgb(0, 1, 1, alpha = 0.25),įunction(i) segments(x0 = mean(my_df),

#RSTUDIO GGPLOT2 RED RECTANGLE CODE#

You can follow the code block to add the lines and points for horizontal and vertical box and whiskers diagrams. In order to calculate the mean for each group you can use the apply function by columns or the colMeans function. In this case, you can make use of the lapply function to avoid for loops. You can also add the mean point to boxplot by group. You can change the mean function of the previous code for other function to display other measures. # abline(v = mean(x), col = 2, lwd = 2) # Entire line # abline(h = mean(x), col = 2, lwd = 2) # Entire line

#RSTUDIO GGPLOT2 RED RECTANGLE HOW TO#

In the following code block we show you how to add mean points and segments to both type of boxplots when working with a single boxplot. Note that the code is slightly different if you create a vertical boxplot or a horizontal boxplot. For that purpose, you can use the segments function if you want to display a line as the median, or the points function to just add points. Nevertheless, you may also like to display the mean or other characteristic of the data. Legend('topright', legend = 'Boxplot', # Position and titleįill = rgb(1, 0, 0, alpha = 0.4), # Colorīy default, when you create a boxplot the median is displayed. Main = 'Customized boxplot in base R', # Title

Horizontal = FALSE, # Horizontal or vertical plot Grid(nx = NULL, ny = NULL, col = 'white', lty = 1,

#RSTUDIO GGPLOT2 RED RECTANGLE FULL#

Review the full list of graphical boxplot parameters in the pars argument of help(bxp) or ?bxp. Note that there are even more arguments than the ones in the following example to customize the boxplot, like boxlty, boxlwd, medlty or staplelwd. In the following block of code we show a wide example of how to customize an R box plot and how to add a grid. # Boxplot from the R trees datasetīoxplot(trees, col = rainbow(ncol(trees)))īoxplot(stacked_df$values ~ stacked_df$ind,Ī boxplot can be fully customized for a nice result. Thus, each boxplot will have a different color. Note that you can change the boxplot color by group with a vector of colors as parameters of the col argument. Now, you can plot the boxplot with the original or the stacked dataframe as we did in the previous section. Nevertheless, you can convert this dataset as one of the same format as the chickwts dataset with the stack function. Note the difference respect to the chickwts dataset. For illustration purposes we are going to use the trees dataset. In case all variables of your dataset are numeric variables, you can directly create a boxplot from a dataframe.

Rstudio ggplot2 red rectangle