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#' @title Perform a pairwise count of words by id
#'
#' @description This is a 'data.table' implementation that mimics the output of
#' `pairwise_count()` from 'widyr' to reduce package dependency. This is used
#' internally within `tm_cooc()`.
#'
#' @param data Data frame output from `tm_clean()`.
#' @param id String to represent the id variable. Defaults to `"line"`.
#' @param word String to represent the word variable. Defaults to `"word"`.
#'
#' @return
#' data frame with the following columns representing a pairwise count:
#' - `"item1"`
#' - `"item2"`
#' - `"n"`
#'
#' @importFrom data.table ":=" "%like%" "%between%" rbindlist as.data.table
#'
#' @family Support
#' @family Text-mining
#'
#' @examples
#' td <- data.frame(line = c(1, 1, 2, 2),
#' word = c("work", "meeting", "catch", "up"))
#'
#' pairwise_count(td, id = "line", word = "word")
#'
#' @export
pairwise_count <- function(data,
id = "line",
word = "word"){
# Make sure data.table knows we know we're using it
.datatable.aware = TRUE
data <-
data %>%
dplyr::rename(word := !!sym(word),
id := !!sym(id))
DT <- data.table::as.data.table(data)
# convert to character
DT[, word := as.character(word)]
# subset those with >1 per id
DT2 <- DT[, N := .N, by = id][N>1]
# create all combinations of 2
# return as a data.table with these as columns `V1` and `V2`
# then count the numbers in each id
out_data <-
DT2[, rbindlist(utils::combn(word,2,
FUN = function(x) as.data.table(as.list(x)),
simplify = FALSE)), by = id] %>%
.[, .N, by = list(V1,V2)]
# format and sort
out_data %>%
dplyr::as_tibble() %>%
dplyr::rename(item1 = "V1",
item2 = "V2",
n = "N") %>%
dplyr::arrange(desc(n))
}
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