By now, we know how to remove duplicates from data. You can use the Remove Duplicates button to do that.
But do you know that we can use remove duplicates button to get rid off duplicate combinations too?
Remove duplicate combinations – Tutorial
To remove duplicate combinations in your data, just follow below 4 steps:
- Select your data
- Click on Data > Remove Duplicates button
- Make sure all columns are checked
- Click ok and done!
See this demo:
How to remove duplicate combinations in some of the columns
If you just want to remove duplicate combinations of Product & Store alone, you can still use Remove Duplicates feature.
This time, select all 3 columns, but check only first 2 columns in the remove duplicate screen. That should do the trick.
More ways to deal with duplicate data
Duplicate data is not a unique problem, its everywhere. That is why at Chandoo.org, we have a plethora of tips, tutorials & videos to help you deal with the problem. Check out below links to learn more.
- Advanced & array formula approaches:
- Pivot Tables & other techniques:
- Highlighting duplicate entries:
How do you deal with duplicates?
I use remove duplicates button every time I get raw data. It is such a time saver. When I want a more automated solution, I use formulas or pivot tables to knockoff the duplicates.
What about you? How do you deal with duplicates in your data? Please share your tips by posting a comment.
This post is part of Awesome August Excel Festival.
One Response to “SQL vs. Power Query – The Ultimate Comparison”
Enjoyed your SQL / Power Query podcast (A LOT). I've used SQL a little longer than Chandoo. Power Query not so much.
Today I still use SQL & VBA for my "go to" applications. While I don't pull billions of rows, I do pull millions. I agree with Chandoo about Power Query (PQ) lack of performance. I've tried to benchmark PQ to SQL and I find that a well written SQL will work much faster. Like mentioned in the podcast, my similar conclusion is that SQL is doing the filtering on the server while PQ is pulling data into the local computer and then filtering the data. I've heard about PQ query folding but I still prefer SQL.
My typical excel application will use SQL to pull data from an Enterprise DB. I load data into Structured Tables and/or Excel Power Pivot (especially if there's lot of data).
I like to have a Control Worksheet to enter parameters, display error messages and have user buttons to execute VBA. I use VBA to build/edit parameters used in the SQL. Sometimes I use parameter-based SQL. Sometimes I create a custom SQL String in a hidden worksheet that I then pull into VBA code (these may build a string of comma separated values that's used with a SQL include). Another SQL trick I like to do is tag my data with a YY-MM, YY-QTR, or YY-Week field constructed form a Transaction Date.
In an application, I like to create a dashboard(s) that may contain hyperlinks that allow the end-user to drill into data. Sometimes the hyperlink will point to worksheet and sometimes to a supporting workbook. In some cases, I use a double click VBA Macro that will pull additional data and direct the user to a supplemental worksheet or pivot table.
In recent years I like Dynamic Formulas & Lambda Functions. I find this preferable to pivot tales and slicers. I like to use a Lambda in conjunction with a cube formula to pull data from a power pivot data model. I.E. a Lambda using a cube formula to aggregate Accounting Data by a general ledger account and financial period. Rather than present info in a power pivot table, you can use this combination to easily build financial reports in a format that's familiar to Accounting Professionals.
One thing that PQ does very well is consolidating data from separate files. In the old days this was always a pain.
I've found that using SQL can be very trying (even for someone with experience). It's largely an iterative process. Start simple then use Xlookup (old days Match/Index). Once you get the relationships correct you can then use SQL joins to construct a well behaved SQL statement.
Most professional enterprise systems offer a schema that's very valuable for constructing SQL statements. For any given enterprise system there's often a community of users that will share SQL. I.E. MS Great Plains was a great source (but I haven't used them in years).
Hope this long reply has value - keep up the good work.