Filtering a data.frame based on multiple variables

Question

I have a data.frame with 9 variables from X1 to X9. The values of these variables are double. I need to filter the lines of this data.frame that contain (Xi,Xj,Xk) == (5.2,6.3,7.1) for example.

I was able to solve individually with the code below. But I could not write something that would allow me to perform this task by changing only the values sought. How these values can occur in any combination of variables from X1 to X9 has gotten very complicated.

vars <- c("X1","X5","X9")
cond <- c(5.2,6.3,7.1)
lfbase %>%
  filter(
    .data[[vars[[1]]]] == cond[[1]],
    .data[[vars[[2]]]] == cond[[2]],
    .data[[vars[[3]]]] == cond[[3]]
  )

Answer 1

After clarification of the question in the comments:

I need to filter the lines where these measurements occur together in any of the X1 variables.... X9

The solution remains based on the command filter_at of dplyr with the argument any_vars(). But instead of the operator | OR, you apply the filters sequentially:

library(dplyr)

df1 <- lfbase %>% filter_at(vars(starts_with("X")), any_vars(. == 5.2)) %>%
                  filter_at(vars(starts_with("X")), any_vars(. == 6.3)) %>% 
                  filter_at(vars(starts_with("X")), any_vars(. == 7.1)) 

By your question, it seems that these are all variables of your dataframe ("I have a data.frame with 9 variables from X1 to X9"). If this is the case, you can simplify the above code with the filter_all:

df1 <- lfbase %>% filter_all(any_vars(. == 5.2))
              %>% filter_all(any_vars(. == 6.3))
              %>% filter_all(any_vars(. == 7.1))

If any lines containing any of the above values were to be filtered, it could be used:

library(dplyr)

df1 <- lfbase %>% filter_at(vars(starts_with("X")), any_vars(. == 5.2 | . == 6.3 | . == 7.1))

or

df1 <- lfbase %>% filter_all(any_vars(. == 5.2 | . == 6.3 | . == 7.1))