Help : Compare texts in two columns in the same row and get the similarity percentage

[anish.ms]

Hi,
Request help from the expert members here for the below situation-

Is there any way to compare texts in two columns in the same row and get the similarity percentage like Fuzzy Lookup does?. My problem with Fuzzy Lookup is, it checks each cell value in the first table with each cell value in the second table and it is taking very long time to complete as I have 10K+ rows data with long text. Also, I only need to check each cell value in first table with the cell value in second table in the same row. I have attached a sample file here and I need to compare the texts in column B with column D.

Request your support
Thanks!

[SamT]

A Percent match between two strings
What :help

How about some examples for you to answer
What is the % Match between:
1) "A little dog" & "A quick brown Fox... a Dog's back"
2) "John made $57." & "Sue earned 57 Dollars"

3) Molestias rem corrupti sint omnis ut alias ex. Maxime mollitia qui et voluptas dolores. Voluptas doloremque corrupti et. Nobis consequatur amet suscipit enim et. Nihil et velit praesentium maiores voluptate vel. Deleniti excepturi expedita consequatur harum saepe."

&

Molestias rem corrupti sint omns ut alias ex. Maxime mollitia qui et voluptas dolores. Voluptas doloremqu corrupti et. Nobis consequatur amet suscipit enim et. Nihil et velit praesentium maiores voluptate vel. Delenitu excepturi expedita consequatur harum saepe.

[anish.ms]

Hi Sam,
Below is the similarity I got for your examples using Fuzzy Lookup



Table1
Table2
Similarity


A little dog
A quick brown Fox... a Dog's back
0.259340659340659


John made $57.
Sue earned 57 Dollars
0.214285714285714


Molestias rem corrupti sint omnis ut alias ex. Maxime mollitia qui et voluptas dolores. Voluptas doloremque corrupti et. Nobis consequatur amet suscipit enim et. Nihil et velit praesentium maiores voluptate vel. Deleniti excepturi expedita consequatur harum saepe.
Molestias rem corrupti sint omns ut alias ex. Maxime mollitia qui et voluptas dolores. Voluptas doloremqu corrupti et. Nobis consequatur amet suscipit enim et. Nihil et velit praesentium maiores voluptate vel. Delenitu excepturi expedita consequatur harum saepe.
0.995553383087073



I really don't know the method used in Fuzzy Lookup to arrive at these similarity.

[p45cal]

In Power Query there is a fuzzy match option and, as I discovered, a similarity score too, although on mine, it was only available through editing the M-code (at least I couldn't find anything in the user-interface).
Originally the M-code was:

= Table.FuzzyNestedJoin(Table1, {"PDC_DESC"}, Table2, {"LONG_DESCRIPTION"}, "Table2", JoinKind.LeftOuter, [IgnoreCase=true, IgnoreSpace=true, Threshold=0.6])and needed editing to:
= Table.FuzzyNestedJoin(Table1, {"PDC_DESC"}, Table2, {"LONG_DESCRIPTION"}, "Table2", JoinKind.LeftOuter, [IgnoreCase=true, IgnoreSpace=true, Threshold=0.6, SimilarityColumnName="Similarity score"])and then expanded the new column. (Edit the settings in the user interface and you'll lose your manual additions)
and got:
28246
See also:
Fuzzy Matching - Scores
https://social.technet.microsoft.com/Forums/sharepoint/en-US/519c5653-3e8b-4dea-822e-df35e5f06f22/fuzzy-matching-scores
(see the last msg on the page)

Table.FuzzyJoin - PowerQuery M | Microsoft Docs
https://docs.microsoft.com/en-us/powerquery-m/table-fuzzyjoin

The time it takes may depend on the similarity threshold you choose.

[Paul_Hossler]

Lots of VBA fuzzy algorithms out there

Are you just testing between two strings in the same row?

https://www.mrexcel.com/board/threads/fuzzy-matching-new-version-plus-explanation.195635/

My small sample test workbook and yours

28250

28251

[anish.ms]

Thanks p45cal!

I'm getting the below message when I go to power query editor. I'm using office 365 with latest update. May be this is available only for Office Insiders.
28255
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[anish.ms]

Thanks a lot Paul!

[p45cal]

I'm getting the below message when I go to power query editor. I'm using office 365 with latest update. May be this is available only for Office Insiders.I'm not an 'insider'. I usually ignore this message and everything's fine.

[anish.ms]

I ignored the message and the error I'm getting is
Expression.Error: '' isn't a valid Table.FuzzyNestedJoin option. Valid options are:
ConcurrentRequests, Culture, IgnoreCase, IgnoreSpace, NumberOfMatches, Threshold, TransformationTable

I tried to do it fresh from in my sample file by opening a blank query, but I'm getting the following error

Expression.Error: The name 'Table1' wasn't recognized. Make sure it's spelled correctly.
I tried after renaming the table name

[p45cal]

A few things to try:
With the files I sent:
1. Attached is the same file as I attached in msg#4 but as an xlsx file; I have no idea whether this will make a difference.
2. Confirm that if the question pops up External connections have been disabled you click the Enable Content button.
3. Confirm that in the result table at cell H2 in either the attached file or the xlsb file refreshes properly 'out of the box' (Clear a few cells in the result table and then right-click it and choose Refresh - it should, eventually, refill those cells).
With your file:
4. Try saving it as an xlsx file (again, I'm not sure this will have any effect at all).
5. Attach it here with your attempt so far. (If it's too big, reduce the source data tables in size while making sure there are some reasonably similar rows, and at least one exactly similar row.)

[anish.ms]

1. I tried with the file you shared in #10
2. Pop up came for External connections and I clicked Enable Content
3. I deleted similarity score form cells K8 and K9 and tried to refresh. Following is the message that I'm getting
28262

28263

[p45cal]

Could you try again with this one? There was something a bit odd about the last one (you should be able to right-click on the results table, choose Table, then Edit Query…, and you couldn't on the last one).

If it's still a problem, save this file on your own system with a new name, close it and attach it here.