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If you want a second line of text below your first line, you can provide multiple y-values to text( ) along with a vector of expression( ) or bquote( ) output, or use a second text( ) command with a new y-value (in the coordinates of your plot) that will end up below your first text( ) call. While it is possible to insert a newline character (\n) into a text( ) call, getting it to behave as you’d like usually (always?) proves to be an exercise in frustration when trying to print out plotmath expressions (which is what we’re doing when using things like italic( ) and the superscript ^). You could place lots of labels using the text function, but you do need to be careful about specifying where they end up. The plot with the R squared value inserted using text(). You’ll need to specify those coordinates correctly so that everything fits on the plot properly. The call to text( ) then prints the contents of mylabel on the current figure at the chosen x and y coordinates. For example: expression(Adjusted~italic(R)^2 = MYVALUE) will stick the character string “Adjusted” on the front of the output from expression( ), and insert a space between it and the R 2 to generate: Adjusted R 2=0.506. If you wanted to include some plain character strings, you can enclose them in quotes if there will be spaces between words, and separate your text from the other parts of the statement using either * (to keep parts together) or ~ (to insert a space between parts).If you skip this step, R will probably print out many more digits than you wanted. I also specified that format should print the value out with only 3 significant digits. Inside the format( ) function, I gave the name of the object holding my numerical R 2 value, r2.In this case, I’ve called the format( ) function. ( ) function, which instructs bquote( ) to evaluate the contents of. Printing the equals sign inside bquote is accomplished by typing a double equals sign, =.If you wanted multiple characters with spaces in the superscript, you’d enclose them in curly braces and quote marks, like so: italic(R)^. If you wanted a subscript, you would use the square braces instead of ^ (for example: bquote(italic(R)^2= ~.(format(r2,dig = 3)))). Thus, the 2 is inserted as a superscript character next to the R.
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Here’s the breakdown of the contents of bquote( ): ( ) function that will be evaluated like normal R code.
#HOW TO SHOW SIGNIFICANT DIGITS ON AN EXCEL GRAPH AXIS LABEL CODE#
The code inside bquote( ) behaves according to the syntax laid out in plotmath (type ?plotmath in your R terminal to see the help page), except that you can insert other objects inside the. On the right side of the equals sign is the bquote( ) function, which creates a ‘call’ object in R. The code chunk above starts by creating a new object, ‘ mylabel‘, that will hold the expression we want to display. ( format (r2, digits = 3 ) ) ) text (x = 19, y = 2.5, labels = mylabel ) I’ll start with the simple case, using text( ) to plot the R 2 value. Getting this sort of formatting correct in a R plot can be tricky. The numeric p-value should only be written to 2 significant digits.The p of the p-value should be in italics.The numeric R 2 value should only be written to 3 significant digits.Those functions are straightforward, but getting nicely formatted text into them requires the use of the bquote( ) function or the expression( ) function and the substitute( ) function. You could use the text( ) function, or as we’ll see later, the legend( ) function. Getting the values stored in r2 and my.p onto the plot takes some head scratching. To extract that single p-value in code, I can do the following: my.p = modsum$coefficients You can see the structure of the coefficients matrix as follows: modsum$coefficients The p-value I’m after is in the 2nd row and 4th column. The modsum object has a list entry called “coefficients”, which is a 2×4 matrix. The p-value for the WTMP variable is buried a little further. The adjusted R 2 value is easily available: r2 = modsum$adj.r.squared The first step is to extract those values from the model summary object we made. Getting the p-value and R 2 onto the plot takes a little more doing.