Find specific value in nested data frames and get position and/or value

January 26, 2022

I have a nested list sampleList that can contain a variable number of data frames. In this example there are 3 data frames:

df1 <- data.frame(id = as.integer(c(1, 6)), key = c('apple', 'apple.green'), stringsAsFactors=FALSE)
df2 <- data.frame(id = as.integer(c(1, 3, 5)), key = c('apple', 'apple.red', 'apple.red.rotten'), stringsAsFactors = FALSE)
df3 <- data.frame(id = as.integer(c(17)), key = c('orange'), stringsAsFactors = FALSE)
sampleList <- list(df1, df2, df3)

I want to search for specific integers e.g. 6 in the id column across all data frames contained in the sampleList. As a result, I need the position and if possible the associated value from the key column.

The closest I got was the position in a specific data frame e.g. 1.

which(sampleList[[1]] == 6)
[1] 2

Since the number of data frames can be different each time, I need a more dynamic query.

Thanks a lot for your help.

>Solution :

I have slightly altered the data, adding 6 to df3.

df3 <- data.frame(id = as.integer(c(17, 6)), key = c('orange', "blue"), stringsAsFactors = FALSE)

Filter(nrow, 
       lapply(sampleList, subset, id == 6)
)
[[1]]
  id         key
2  6 apple.green

[[2]]
  id  key
2  6 blue

Explanation: We can first subset the list elements based on criteria, and later Filter out those that have nrow of 0, since F == 0.

To extract the positions (stored as rownames of the data.frames),

Filter(nrow, 
       lapply(sampleList, subset, id == 6)
) |>
  lapply(\(x) as.integer(rownames(x)))

To make it clear in which data.frame matches were found,

Filter(nrow, 
       lapply(sampleList, subset, id == 6) |>
         setNames(1:length(sampleList)) # swap to appropriate naming policy
) |>
  lapply(\(x) as.integer(rownames(x)))