If IFERROR() were to be a person, I would hug her so hard that Jo (my wife) would get in to a cat fight with her. I know many a woman (and man) who get in to a fight with Excel formulas often. But thankfully, we avoid that as IFERROR is not a real person. It is, however a darned useful formula.
Since I cannot hug a formula anymore than I can get my son to sit tight, I will go ahead and sing an ode to her, in my style – by writing about how useful and powerful IFERROR formula is.
What is IFERROR() Formula & How does it work?
Introduced since Excel 2007, IFERROR() formula checks a formula (or expression) and returns the value of formula if there is no error, otherwise a custom formula.
For eg:
=IFERROR(1/0,"Try splitting an atom instead!")
will give the message Try splitting an atom instead! because the expression 1/0 returns an error (DIV/0 error)
Where as,
=IFERROR(0/1,"Try splitting an atom instead!")
will give the value 0 since 0 divided by 1 is 0.
How does IFERROR help me?
Archimedes once said, “Give me enough data and a spreadsheet, I can make any formula return an error.”
May be he was too confident, but errors are everywhere. And that is why IFERROR is useful. It provides an elegant and simple way to tackle the errors in your workbook.
Several common uses of IFERROR are,
- 1. While writing lookup formulas like VLOOKUP, INDEX+MATCH it is common to search for values that do not exist in your data. You can wrap such formulas in IFERROR for peace of mind.
Ex:=IFERROR(VLOOKUP(...),"Not found") - 2. While using reference formulas like INDEX, OFFSET, frequently, we try to fetch the data that is not in the list of values. This returns #REF errors. You can fix them with IFERROR easily.
Ex:=IFERROR(INDEX(...),"") - 3. While using arithmetic, numeric expressions, usually we end up dividing by 0. You can fix such things by using IFERROR.
Ex:=IFERROR(AVERAGE(...),"0")— Returns 0 when the list has zero values.
Things to keep in mind while IFERRORing:
Please note that IFERROR is oblivious to the type of error. That means, no matter what the error is (DIV/0, #NAME, #N/A, #REF… etc.), IFERROR treats all of them equally and shows the same value. In other words, IFERROR is like “Catch all” in programming world.
How to handle errors if you are using Excel 2003 or below?
In earlier versions of Excel, we have a formula called as ISERROR() that can check an expression or formula for error and return TRUE if so. This formula is not same as IFERROR, but we can use it along with IF() formula to get the same result. For eg.
=IF(ISERROR(VLOOKUP(...)),"Not found",VLOOKUP(...))
works same as, =IFERROR(VLOOKUP(...),"Not found")
Notice that the ISERROR approach evaluates VLOOKUP formula twice!.
Do you IFERROR?
To err is human, to IFERROR is awesome.
Ever since discovering the IFERROR feature in Excel 2007, I have been using it so often. I use it to keep my output sheets clean and my formulas simple.
What about you? Do you use IFERROR? What is your experience like? Would you also give it a hug? If so, would your spouse get in to a cat fight with it? If so can you post some pics of it on our facebook page?
Please share your experiences and tips on using IFERROR() thru comments.
Related awesomeness:
1. How to understand and handle Excel formula errors
2. Excel formulas not working? What to do?
3. Handling errors and 5 other tips for writing better VLOOKUP formulas
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.