stringdist_join: Join two tables based on fuzzy string matching of their...

In fuzzyjoin: Join Tables Together on Inexact Matching

Description

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.

Usage

stringdist_join(
  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,
  ...
)

stringdist_inner_join(x, y, by = NULL, distance_col = NULL, ...)

stringdist_left_join(x, y, by = NULL, distance_col = NULL, ...)

stringdist_right_join(x, y, by = NULL, distance_col = NULL, ...)

stringdist_full_join(x, y, by = NULL, distance_col = NULL, ...)

stringdist_semi_join(x, y, by = NULL, distance_col = NULL, ...)

stringdist_anti_join(x, y, by = NULL, distance_col = NULL, ...)

Arguments

x	A tbl
y	A tbl
by	Columns by which to join the two tables
max_dist	Maximum distance to use for joining
method	Method for computing string distance, see stringdist-metrics in the stringdist package.
mode	One of "inner", "left", "right", "full" "semi", or "anti"
ignore_case	Whether to be case insensitive (default yes)
distance_col	If given, will add a column with this name containing the difference between the two
...	Arguments passed on to stringdist

Details

If method = "soundex", the 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"))

fuzzyjoin documentation built on July 1, 2020, 7:07 p.m.