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#' Join two tables based on fuzzy string matching of their columns
#'
#' Join two tables based on fuzzy string matching of their columns.
#' This is useful, for example, in matching free-form inputs in
#' a survey or online form, where it can catch misspellings and
#' small personal changes.
#'
#' @param x A tbl
#' @param y A tbl
#' @param by Columns by which to join the two tables
#' @param max_dist Maximum distance to use for joining
#' @param ignore_case Whether to be case insensitive (default yes)
#' @param method Method for computing string distance, see
#' \code{stringdist-metrics} in the stringdist package.
#' @param distance_col If given, will add a column with this
#' name containing the difference between the two
#' @param mode One of "inner", "left", "right", "full" "semi", or "anti"
#' @param ... Arguments passed on to \code{\link{stringdist}}
#'
#' @details If \code{method = "soundex"}, the \code{max_dist} is
#' automatically set to 0.5, since soundex returns either a 0 (match)
#' or a 1 (no match).
#'
#' @examples
#'
#' library(dplyr)
#' library(ggplot2)
#' data(diamonds)
#'
#' d <- data_frame(approximate_name = c("Idea", "Premiums", "Premioom",
#' "VeryGood", "VeryGood", "Faiir"),
#' type = 1:6)
#'
#' # no matches when they are inner-joined:
#' diamonds %>%
#' inner_join(d, by = c(cut = "approximate_name"))
#'
#' # but we can match when they're fuzzy joined
#' diamonds %>%
#' stringdist_inner_join(d, by = c(cut = "approximate_name"))
#'
#' @export
stringdist_join <- function(x, y, by = NULL, max_dist = 2,
method = c("osa", "lv", "dl", "hamming", "lcs", "qgram",
"cosine", "jaccard", "jw", "soundex"),
mode = "inner",
ignore_case = FALSE,
distance_col = NULL, ...) {
method <- match.arg(method)
if (method == "soundex") {
# soundex always returns 0 or 1, so any other max_dist would
# lead either to always matching or never matching
max_dist <- .5
}
match_fun <- function(v1, v2) {
if (ignore_case) {
v1 <- stringr::str_to_lower(v1)
v2 <- stringr::str_to_lower(v2)
}
# shortcut for Levenshtein-like methods: if the difference in
# string length is greater than the maximum string distance, the
# edit distance must be at least that large
# length is much faster to compute than string distance
if (method %in% c("osa", "lv", "dl")) {
length_diff <- abs(stringr::str_length(v1) - stringr::str_length(v2))
include <- length_diff <= max_dist
dists <- rep(NA, length(v1))
dists[include] <- stringdist::stringdist(v1[include], v2[include], method = method, ...)
} else {
# have to compute them all
dists <- stringdist::stringdist(v1, v2, method = method, ...)
}
ret <- tibble::tibble(include = (dists <= max_dist))
if (!is.null(distance_col)) {
ret[[distance_col]] <- dists
}
ret
}
ensure_distance_col(fuzzy_join(x, y, by = by, mode = mode, match_fun = match_fun), distance_col, mode)
}
#' @rdname stringdist_join
#' @export
stringdist_inner_join <- function(x, y, by = NULL, distance_col = NULL, ...) {
stringdist_join(x, y, by, mode = "inner", distance_col = distance_col, ...)
}
#' @rdname stringdist_join
#' @export
stringdist_left_join <- function(x, y, by = NULL, distance_col = NULL, ...) {
stringdist_join(x, y, by, mode = "left", distance_col = distance_col, ...)
}
#' @rdname stringdist_join
#' @export
stringdist_right_join <- function(x, y, by = NULL, distance_col = NULL, ...) {
stringdist_join(x, y, by, mode = "right", distance_col = distance_col, ...)
}
#' @rdname stringdist_join
#' @export
stringdist_full_join <- function(x, y, by = NULL, distance_col = NULL, ...) {
stringdist_join(x, y, by, mode = "full", distance_col = distance_col, ...)
}
#' @rdname stringdist_join
#' @export
stringdist_semi_join <- function(x, y, by = NULL, distance_col = NULL, ...) {
stringdist_join(x, y, by, mode = "semi", distance_col = distance_col, ...)
}
#' @rdname stringdist_join
#' @export
stringdist_anti_join <- function(x, y, by = NULL, distance_col = NULL, ...) {
stringdist_join(x, y, by, mode = "anti", distance_col = distance_col, ...)
}
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