How to conditionally exclude a chunk after evaluating his content? - r

Question

I'm creating a parametrized report in Rmarkdown, whereas some chunks should not be evaluated (included in the report) based on characteristics of the content within the chunk.
The report calculates individual summaries on a large survey for ~120 facilities with different numbers of units in them. Additionally unit size and volume is largely variable, therefore we exclude unit-analysis if the number of valid answers per unit is less than 10 (this is already recoded to NA in the dataframe-object). I therefore need to write a statement, in which the number of NA's within an object is counted per unit and if for every unit there is only NA, I'd like to do include = FALSE on the chunk. This would need to be repeated for ~50 chunks, therefore I tried to use eval.after.
Martin Schmelzer's comment made me realize I have 2 different problems:
1) I need to use regular expressions to detect the name of the object in a self-written function within the chunk.
2) I need to set up a function for conditionally evaluating eval.after in the chunks.
For Problem 1): The R-Chunk that needs to be checked for eval.after looks like this:
```{r leadership unit, eval=exclude_ifnot_unitC }
kable.unit.tblc(unitblc_leadership, caption = "Führung")
```
kable.unit.tblc(df, caption)is a self-written function that implements kableExtra()functions to style the tables and the first input is a dataframe (that was beforehand created in an R file). I should now use regular expression to extract the name of the dataframe out of the chunk, meaning everything from kable.unit.tblc(to , caption.
I tried this so far for first steps in regular expressions, but I'm not able to get the object "in between" those two expression:
x <- 'kable.unit.tblc(unitblc_leadership, caption = "Führung")'
stringr::str_extract(x, "^kable.unit.tblc\\(")
stringr::str_extract(x, ", caption")
The desired result of the extracted object would in this case be unitblc_leadership and stored in a variable, say test_object.
Regarding the second problem: I should set eval.after = 'include_if_valid' for those chunks and the function for testing this would be:
include_if_valid <- function() {
## search the chunk with regular expression for detecting the
# test object (Problem 1)
# count the number of NAs in all numeric variables of the
# test_object and if all cells are NA's give FALSE, if any
# cell has a value give TRUE
test_object %>%
select_if(is.numeric) %>%
summarise_all(.funs = list(~n.valid)) %>%
gather(key = "Unit", value = "nvalid") %>%
count(nvalid > 0) %>% pull(`nvalid > 0`)
as you can see, I need the test_object that should be derived with the function before - but I'm not sure if my intention is even possible.
The chunk should then look like something like this:
```{r leadership unit, eval.after=include_if_valid }
kable.unit.tblc(unitblc_leadership, caption = "Führung")
```
Edit: I thought too complicated - this solution by Martin worked just fine:
include_if_valid <- function(df) {
if (df %>%
select_if(is.numeric) %>%
summarise_all(.funs = list(~n.valid)) %>%
gather(key = "Unit", value = "nvalid") %>%
pull() %>% sum() > 0) {TRUE} else {FALSE}
}
and within the chunk:
{r leadership unit, eval=include_if_valid(unitblc_leadership) }
kable.unit.tblc(unitblc_leadership, caption = "Führung")

Answer 1

You can change the chunk option results to "hide", but this has to happen before you start evaluating the chunk (since eval.after is limited in which options it applies to). So to get what you want, you would need two chunks:
Compute enough to determine whether the chunk should be computed and displayed. Hide this one, in case no display is wanted.
In the next chunk, repeat calculations if you want to display them, and display the results, all conditional on the previously computed result.
Your example isn't reproducible, so here's a simple one. Suppose I only want to display x if its value is bigger than 10:
```{r include=FALSE}
# compute x as a random value between 9 and 11, but don't display anything
x <- runif(1, 9, 11)
```
```{r include = x > 10}
# display x conditional on its value being > 10
x
```

Answer 2

Here is a way to inject the data as a chunk option, check its validity and print a kable conditional on that result. Nice thing is that we can reference the first generic chunk and call it with a different dataframe.
With knit_hooks$set we create a new chunk hook named df. Everything inside if(before) will be evaluated before the chunk itself will be evaluated. The argument options contains all the chunk options set for the current chunk and envir is the chunk environment.
---
title: "Conditional Evaluation"
output: html_document
---
```{r setup, include = F}
library(dplyr)
library(knitr)
A <- data.frame(A = LETTERS[1:4])
B <- data.frame(B = rep(NA, 4))
C <- data.frame(C = letters[1:4])
include_if_valid <- function(df) {
return(all(!is.na(df)))
}
knit_hooks$set(df = function(before, options, envir) {
if (before) {
assign("valid", include_if_valid(options$df), envir = envir)
}
})
```
```{r generic, df = A, echo = F}
if(valid) kable(opts_current$get("df"))
```
```{r ref.label="generic", df = B, echo = F}
```
```{r ref.label="generic", df = C, echo = F}
```