I have been working on large data set which has names of customers , each of this has to be checked with the master file which has correct names (300 KB) and if matched append the master file name to names of customer file as new column value. My prev Question worked for small data sets
Both Customer & Master file has been cleaned using tm and have tried different logic , but only works on small set of data when applied to huge files not effective, pattern matching doesn't help here my opinion cause no names comes with exact pattern
Cus File
1 chang chun petrochemical
2 chang chun plastics
3 church dwight
4 citrix systems asia pacific
5 cnh industrial services srl
6 conoco phillips
7 conocophillips
8 dfk laurence varnay
9 dtz worldwide
10 electro motive maintenance operati
11 enterasys networks
12 esso resources
13 expedia
14 expedia
15 exponential interactive aust
16 exxonmobil asia pacific pte
17 exxonmobil chemical asia pac div
18 exxonmobil png
19 formula world championship
20 fortitech asia pacific sdn bhd
Master
1 chang chun group
2 church dwight
3 citrix systems asia pacific
4 cnh industrial nv
5 conoco phillips
6 dfk laurence varnay
7 dtz group zealand
8 caterpillar
9 enterasys networks
10 exxon mobil group
11 expedia group
12 exponential interactive aust
13 formula world championship
14 fortitech asia pacific sdn bhd
15 frhi hotels resorts
16 gardner denver industries
17 glencore xstrata international plc
18 grace
19 incomm nz
20 information resources
21 kbr holdings llc
22 kennametal
23 komatsu
24 leonhard hofstetter pelzdesign
25 communications corporation
26 manhattan associates
27 mattel
28 mmg finance
29 nokia oyj group
30 nortek
i have tried with this simple loop
for (i in 1:100){
result$x[i] = agrep(result$ICIS_Cust_Names[i], result1$Master_Names, value = TRUE, max = list(del = 0.2, ins = 0.3, sub = 0.4))
#result$Y[i] = agrep(result$ICIS_Cust_Names[i], result1$Master_Names, value = FALSE, max = list(del = 0.2, ins = 0.3, sub = 0.4))
}
*result *
1 chang chun petrochemical <NA> NA
2 chang chun plastics <NA> NA
3 church dwight church dwight 2
4 citrix systems asia pacific citrix systems asia pacific 3
5 cnh industrial services srl <NA> NA
6 conoco phillips church dwight 2
7 conocophillips <NA> NA
8 dfk laurence varnay <NA> NA
9 dtz worldwide church dwight 2
10 electro motive maintenance operati <NA> NA
11 enterasys networks <NA> NA
12 esso resources church dwight 2
13 expedia <NA> NA
14 expedia <NA> NA
15 exponential interactive aust church dwight 2
16 exxonmobil asia pacific pte <NA> NA
17 exxonmobil chemical asia pac div <NA> NA
18 exxonmobil png church dwight 2
19 formula world championship <NA> NA
20 fortitech asia pacific sdn bhd
tried with lapply but no use , as you can notice my master file is large and some times i get error of rows length doesn't match!
mm<-dt[lapply(result, function(x) levenshteinDist(x ,lapply(result1, function(x) x)))]
#using looping stat. for checking each cus name with all the master names
for(i in seq(nrow(result)) )
{
if((levenshteindist(result[i],lapply(result1, function(x) String(x))))==0)
sprintf("%s", x)
}
which method would be best for this ? similar to my Q but not much helpfullI referd few Q from STO
it might be naive but when applied with huge data sets it mis behaves, can anybody familiar with R could correct me with the above code for levenshteinDist
code:
#check with each value of master file and if matches more than .90 then return master value.
for(i in seq(1:nrow(gr1))
{
for(j in seq(1:nrow(gr2))
{
gr1$jar[i,j]<-jarowinkler(gr1$ICIS_Cust_Names[i],gr2$Master_Names[j])
if(gr1$jar[i,j]>.90)
gr1$res[i] = gr2$Master_Names[j]
}
}
#Please let know if there is any minute error with this code
Please if anybody has worked with such data in R please help !
