Mtext("Top-right text", side = 3, adj = 1) Mtext("Bottom-left text", side = 1, adj = 0) plot(x, y, main = "Main title", cex = 2, col = "blue") In the following code block some examples are shown for both functions. On the other, the text function allows you to add text or formulas inside the plot at some position setting the coordinates. You just need to change the side and adj to obtain the combination you need.
There are 12 combinations (3 on each side of the box, as left, center and right align). On the one hand, the mtext function in R allows you to add text to all sides of the plot box. Note that the dev.cur function counts the number of current available graphics devices. While (dev.cur() > 1) dev.off() # Equivalent You can also clear the plot window in R programmatically with dev.off function, to clear the current window and with graphics.off, to clear all the plots and restore the default graphic parameters. Note that in RStudio you can navigate through all the plots you created in your session in the plots pane. In addition to being able to open and set the size of the window, this functions are used to avoid overriding the plots you create, as when creating a new plot you will lose the previous. It should be noted that in RStudio the graph will be displayed in the pane layout but if you use the corresponding function, the graph will open in a new window, just like in R base. For that purpose, you can use of the height and width arguments of the following functions, depending on your system. However, you may need to customize the height and width of the window, that defaults to 7 inches (17.78 cm). When creating plots in R base they will be opened in a new window. Plot(fun, 0, 10, main = "Plot a function") Plot(my_dates, rnorm(50), main = "Time based plot") Plot(my_factor, rnorm(32), main = "Boxplot") If you execute the following code you will obtain the different plot examples. In the following table we summarize all the available possibilities for the base R plotting function. With the plot function you can create a wide range of graphs, depending on the inputs.
You can create a plot of the previous data typing: # Plot the data We are going to simulate two random normal variables called x and y and use them in almost all the plot examples. The R plot function allows you to create a plot passing two vectors (of the same length), a dataframe, matrix or even other objects, depending on its class or the input type.
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