Update documentation and NEWS.md

NAMESPACE

@@ -29,4 +29,5 @@ importFrom(dplyr,pull)
 importFrom(stats,pnorm)
 importFrom(stats,runif)
 importFrom(utils,installed.packages)
+importFrom(utils,packageVersion)
 useDynLib(zoomerjoin, .registration = TRUE)

NEWS.md

@@ -3,10 +3,11 @@
 ## New features
 
 * Several performance improvements (#101, #104).
+* Added support for joining based on hamming distance (#100).
 
 ## Bug fixes
 
-* When `clean = TRUE`, strings were not coerced to lower case. This is now the 
+* When `clean = TRUE`, strings were not coerced to lower case. This is now the
   case (#105).
 * Fix argument `progress`, which didn't print anything when it was `TRUE` (#107).
 

R/euclidean_logical_joins.R

@@ -1,4 +1,4 @@
-#' Spatial joins Using LSH
+#' Fuzzy joins for Euclidean distance using Locality Sensitive Hashing
 #'
 #' @inheritParams jaccard_left_join
 #' @param threshold The distance threshold below which units should be

R/hamming_logical_joins.R

@@ -1,4 +1,4 @@
-#' Fuzzy inner-join using minihashing
+#' Fuzzy joins for Hamming distance using Locality Sensitive Hashing
 #'
 #' Find similar rows between two tables using the hamming distance. The hamming
 #' distance is equal to the number characters two strings differ by, or is
@@ -39,7 +39,39 @@
 #' to adhere to the same standards as the dplyr-joins, and uses the same
 #' logical joining patterns (i.e. inner-join joins and keeps only observations in both datasets).
 #'
+#' @rdname hamming-joins
 #' @export
+#' @examples
+#' # load baby names data
+#' # install.packages("babynames")
+#' library(babynames)
+#'
+#' baby_names <- data.frame(name = tolower(unique(babynames$name))[1:500])
+#' baby_names_mispelled <- data.frame(
+#'   name_mispelled = gsub("[aeiouy]", "x", baby_names$name)
+#' )
+#'
+#' # Run the join and only keep rows that have a match:
+#' hamming_inner_join(
+#'   baby_names,
+#'   baby_names_mispelled,
+#'   by = c("name" = "name_mispelled"),
+#'   threshold = 3,
+#'   n_bands = 150,
+#'   band_width = 10,
+#'   clean = FALSE # default
+#' )
+#'
+#' # Run the join and keep all rows from the first dataset, regardless of whether
+#' # they have a match:
+#' hamming_left_join(
+#'   baby_names,
+#'   baby_names_mispelled,
+#'   by = c("name" = "name_mispelled"),
+#'   threshold = 3,
+#'   n_bands = 150,
+#'   band_width = 10,
+#' )
 hamming_inner_join <- function(a, b,
                            by = NULL,
                            n_bands = 100,
@@ -58,14 +90,7 @@ hamming_inner_join <- function(a, b,
                  clean=clean)
 }
 
-#' Fuzzy anti-join using minihashing
-#'
-#' @inheritParams hamming_inner_join
-#'
-#' @return a tibble fuzzily-joined on the basis of the variables in `by.` Tries
-#' to adhere to the same standards as the dplyr-joins, and uses the same
-#' logical joining patterns (i.e. inner-join joins and keeps only observations in both datasets).
-#'
+#' @rdname hamming-joins
 #' @export
 hamming_anti_join <- function(a, b,
                            by = NULL,
@@ -85,14 +110,7 @@ hamming_anti_join <- function(a, b,
                  clean=clean)
 }
 
-#' Fuzzy left-join using minihashing
-#'
-#' @inheritParams hamming_inner_join
-#'
-#' @return a tibble fuzzily-joined on the basis of the variables in `by.` Tries
-#' to adhere to the same standards as the dplyr-joins, and uses the same
-#' logical joining patterns (i.e. inner-join joins and keeps only observations in both datasets).
-#'
+#' @rdname hamming-joins
 #' @export
 hamming_left_join <- function(a, b,
                            by = NULL,
@@ -112,14 +130,7 @@ hamming_left_join <- function(a, b,
                  clean=clean)
 }
 
-#' Fuzzy left-join using minihashing
-#'
-#' @inheritParams hamming_inner_join
-#'
-#' @return a tibble fuzzily-joined on the basis of the variables in `by.` Tries
-#' to adhere to the same standards as the dplyr-joins, and uses the same
-#' logical joining patterns (i.e. inner-join joins and keeps only observations in both datasets).
-#'
+#' @rdname hamming-joins
 #' @export
 hamming_right_join <- function(a, b,
                            by = NULL,
@@ -140,14 +151,7 @@ hamming_right_join <- function(a, b,
 }
 
 
-#' Fuzzy full-join using minihashing
-#'
-#' @inheritParams hamming_inner_join
-#'
-#' @return a tibble fuzzily-joined on the basis of the variables in `by.` Tries
-#' to adhere to the same standards as the dplyr-joins, and uses the same
-#' logical joining patterns (i.e. inner-join joins and keeps only observations in both datasets).
-#'
+#' @rdname hamming-joins
 #' @export
 hamming_full_join <- function(a, b,
                            by = NULL,

R/jaccard_logical_joins.R

@@ -1,4 +1,4 @@
-#' Fuzzy joins using minihashing
+#' Fuzzy joins for Jaccard distance using MinHash
 #'
 #' @param a,b The two dataframes to join.
 #'

R/string_group.R

@@ -50,7 +50,7 @@
 #'
 #' @export
 #' @importFrom stats runif
-#' @importFrom utils installed.packages
+#' @importFrom utils installed.packages packageVersion
 jaccard_string_group <- function(string, n_gram_width = 2, n_bands = 45, band_width = 8, threshold = .7, progress = FALSE) {
   if (system.file(package = "igraph") == "") {
     stop("library 'igraph' must be installed to run this function")