R Results in Quarto

Including results of R calculations in your text

You may also want to include the results of R calculations in the TEXT part of your report.

Let’s say you compute the mean of some kids’ foot lengths:

mean(~length, data = KidsFeet)

[1] 24.72308

You can use the result in the text part of your file…so you would type:

The mean length of the kids’ feet was ` r mean(~length, data=KidsFeet) ` cm.

To get:

The mean length of the kids’ feet was 24.7230769 cm.

Note: those accent marks (before the “r” and at the end of the R-code stuff) are not normal single quotes or apostrophes; they are “back-ticks” or “graves” ( ` ), just like those used to help define the start and end of R code chunks in your Quarto file. There should not actually be a space between the ` and the r.

But it’s annoying (and sometimes not really practical) to (re)type the entire R command in the text part of your file. An option is to save the quantity you want to refer to as a variable in R:

mean_length <- mean(~length, data = KidsFeet)

Then you can write: The mean foot length of the kids was ` r mean_length` cm.

To get: The mean foot length of the kids was 24.7230769 cm.

Rounding

What if you want to include a more reasonable number of decimal places? Use : The mean foot length of the kids was ` r round(mean_length, digits = 2)` cm

and you get: The mean foot length of the kids was 24.72 cm

R results with more than one value inside

What if you have an object with more than one value in it? For example, what if you computes means for both boys and girls? You can use hard brackets ( [ … ] ) to refer to the first, second, etc. entries. For example:

girlboy.means <- mean(~ length | sex,
                      data = KidsFeet)

You type: The girls’ mean foot length was ` r girlboy.means[“G”] `, and the boys’ was ` r girlboy.means[“B”] `

to get: The girls’ mean foot length was 24.3210526, and the boys’ was 25.105.

You can also use numeric indices – for example, ` r girlboy.means[2] ` instead of ` r girlboy.means[“G”] ` to get the girls’ value – but using names when you can is always safer because you don’t have to worry about whether things are stored in the order you think that they are!

If you are referring to a data table or other object with multiple rows and columns, you can use the syntax to extract a row, a column, or a specific value of interest. If you leave either or blank, all rows/columns will be included.

For example, consider a table showing some data from a survey of intro stat students ( tells whether they have gotten a speeding ticket while driving a car, and tells whether they have texted while driving a car):

student_survey <- read.csv('https://sldr.netlify.app/data/IntroStatStudents.csv', 
              na.strings = list('', 'NA'))
tally(~Ticket | Texted, 
      data = student_survey, 
      format = 'proportion')

               Texted
Ticket                  No        Yes
  I don't drive 0.03703704 0.00000000
  No            0.77777778 0.71900826
  Yes           0.14814815 0.28099174
  <NA>          0.03703704 0.00000000

What if we want to print just the first column of data?

(Note: Don’t count the row and column names when numbering the rows and columns.)

tally(~Ticket | Texted, 
      data = student_survey,
      format = 'proportion')[,1]

I don't drive            No           Yes          <NA> 
   0.03703704    0.77777778    0.14814815    0.03703704 

Or better (and clearer…)

tally(~Ticket | Texted, 
      data = student_survey,
      format = 'proportion')[, "No"]

I don't drive            No           Yes          <NA> 
   0.03703704    0.77777778    0.14814815    0.03703704 

What about the third row (for people who have gotten a ticket)?

tally(~Ticket | Texted, 
      data = student_survey, 
      format = 'proportion')["Yes",]

       No       Yes 
0.1481481 0.2809917 

What about the proportion of students with tickets, among those who’ve texted while driving? (Row 3, Column 2 = row “Yes” and column “Yes”)? Let’s first save the table so we don’t have to recompute…

driver_table <- tally(~Ticket | Texted, 
      data = student_survey, 
      format = 'proportion')

Type: The proportion of students who have texted while driving who have gotten a speeding ticket is ` r driver_table[“Yes”,“Yes”] `.

To get: The proportion of students who have texted while driving who have gotten a speeding ticket is 0.2809917.

(Like before, if it’s possible to use names instead of numeric indices, try to do so!)