R:使用agrep和data.table进行模糊合并 [英] R: Fuzzy merge using agrep and data.table

问题描述

我尝试合并两个data.tables，但是由于股票名称的拼写不同，我丢失了大量的数据点.因此，我正在寻找模糊合并，而不是精确匹配.

I try to merge two data.tables, but due to different spelling in stock names I lose a substantial number of data points. Hence, instead of an exact match I was looking into a fuzzy merge.

library("data.table")
dt1 = data.table(Name = c("ASML HOLDING","ABN AMRO GROUP"), A = c(1,2))
dt2 = data.table(Name = c("ASML HOLDING NV", "ABN AMRO GROUP"), B = c("p", "q"))

在名称"上合并dt1和dt2时，由于添加了"NV"，因此将不包括ASML HOLDING，而实际数据将是准确的.

When merging dt1 and dt2 on "Name", ASML HOLDING will be excluded due to the addition of "NV", while the actual data would be accurate.

首选的最终数据输出看起来像:

The prefered final data output would look somthing like:

              Name A B
1:  ABN AMRO GROUP 2 q
2: ASML HOLDING NV 1 p

接下来我要尝试的是以下内容:

What I tried next was the following:

dt1 = dt1[, dt2_NAME := agrep(dt1$Name, dt2$Name, ignore.case = TRUE, value = TRUE, max.distance = 0.05, useBytes = TRUE)]

但是，出现以下错误

参数'pattern'的长度> 1，并且仅使用第一个元素

argument 'pattern' has length > 1 and only the first element will be used

该错误是合理的，因为dt1 $ Name大于1，但是我认为如果逐行考虑dt1 $ Name，这将是一个可能的解决方案.

The error makes sense as dt1$Name is longer than 1, but I believe it would be a possible solution if it would consider dt1$Name on a row to row basis.

这可能是一个愚蠢的错误，但是由于某种原因，我无法解决这个问题.此外，我更喜欢使用data.table，因为我的数据集相当大，并且到目前为止，它的表现都非常出色.此外，我是堆栈溢出的新手，如果我的问题有所解决，请对不起.

It might be a stupid mistake, but for some reason I just can't get my head around it. Furthermore, I prefer to use data.table as my dataset is fairly large and up till now it has worked splendidly. Additionally, I am new to stack overflow, so sorry if my question is somewhat off.

最后，我找到了一段可以完成工作的代码，但是对于实际使用而言太慢了. R中的模糊合并

Lastly, I found a piece of code which does the job, but is too slow for practical usage. Fuzzy merge in R

dt1$Name_dt2 <- "" # Creating an empty column
for(i in 1:dim(dt1)[1]) {
  x <- agrep(dt1$Name[i], dt2$Name,
             ignore.case=TRUE, value=TRUE,
             max.distance = 0.05, useBytes = TRUE)
  x <- paste0(x,"")
  dt1$Name_dt2[i] <- x
}

推荐答案

使用'fuzzyjoin'的可能解决方案:

A possible solution using 'fuzzyjoin':

library(fuzzyjoin)
f <- Vectorize(function(x,y) agrepl(x, y,
                                   ignore.case=TRUE,
                                   max.distance = 0.05, useBytes = TRUE))

dt1 %>% fuzzy_inner_join(dt2, by="Name", match_fun=f)
#          Name.x A          Name.y B
#1   ASML HOLDING 1 ASML HOLDING NV p
#2 ABN AMRO GROUP 2  ABN AMRO GROUP q

注意:您也遇到的主要问题是， agrep 和 agrepl 似乎并不期望第一个参数是向量.这就是为什么我用 Vectorize 包裹通话的原因.

NOTE : The main problem, that you encountered too, was that agrep and agrepl don't seem to expect the first argument to be a vector. That's the reason why I wrapped the call with Vectorize.

该方法可以与等值联接一起使用(请注意中的列顺序，！):

This method can be used together with an equi-join (mind the order of columns in the by!):

dt1 = data.frame(Name = c("ASML HOLDING","ABN AMRO GROUP"), A = c(1,2),Date=c(1,2))
dt2 = data.frame(Name = c("ASML HOLDING NV", "ABN AMRO GROUP", "ABN AMRO GROUP"), B = c("p", "q","r"),Date=c(1,2,3))

dt1 %>% fuzzy_inner_join(dt2, by=c("Date","Name"), match_fun=f) %>% filter(Date.x==Date.y)

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