Looking for a dplyr function to apply a filter conditionally

Question

I have a data frame of various hematology values and their collection times. Those values should only be collected at specific times, but occasionally an extra one is added. I want to remove any instances where a value was collected outside the scheduled time.

To illustrate the issue, here's some code to create a very simplified version of the data frame I'm working with (plus some example schedules):

example <- tibble("Parameter" = c(rep("hgb", 3), rep("bili", 3), rep("LDH", 3)), 
                  "Collection" = c(1, 3, 4, 1, 5, 6, 0, 4, 8))

hgb_sampling <- c(1, 4)
bili_sampling <- c(1, 5)
ldh_sampling <- c(0, 4)

So, I need an way to conditionally apply a filter based on the value in the Parameter column. The solution needs to fit into a dyplr pipeline and yield something like this:

filtered <- tibble("Parameter" = c(rep("hemoglobin", 2), rep("bilirubin", 2), rep("LDH", 2)), 
                  "Collection" = c(1, 4, 1, 5, 0, 4))

I've tried a couple things (they all amount to something like the below) but the use of "Parameter" trips things up:

df <- example %>%
  {if (Parameter == "hgb") filter(., Collection %in% hgb_sampling)} 

Any suggestions?

Answer 1

You could create a reference tibble, join it with example and keep only selected rows.

library(dplyr)

ref_df <- tibble::tibble(Parameter = c("hgb","bili", "LDH"), 
                         value  = list(c(1, 4), c(1, 5), c(0, 4)))

example %>%
  inner_join(ref_df, by = 'Parameter') %>%
  group_by(Parameter) %>%
  filter(Collection %in% unique(unlist(value))) %>%
  select(Parameter, Collection)

#  Parameter Collection
#  <chr>          <dbl>
#1 hgb                1
#2 hgb                4
#3 bili               1
#4 bili               5
#5 LDH                0
#6 LDH                4