Here is an interesting problem to start your day.
Let’s say you work as DNA sequencing engineer at The Enterprise. And you just unlocked the sequence that is responsible for all male problems. The early onset of baldness. The sequence code is AAAA. And you want to find out how many times this sequence is found in a sample of DNA strings, in the range B6:B19. Essentially you want this:
So how do you write the formula?
Counting occurrences using Excel formulas
We can use LEN() and SUBSTITUTE() formulas to solve this problem.
Let’s say your target to find is in $C$3 and the full sequence is in B6. We can use below formula to find how many times C3 is present in B6.
=(LEN(B6) - LEN(SUBSTITUTE(B6,$C$3,""))/LEN($C$3)
How does this formula work?
Let’s go inside out (said male baldness to the head):
SUBSTITUTE(B6,$C$3,””): This replaces all occurrences of C3 in B6 with empty string.
LEN(SUBSTITUTE(…)): This will return the length of new text after replacing all C3s in B6.
LEN(B6): this simply gives us the length of original text
LEN(B6)-LEN(SUBSTITUTE(…)): Will give us the count of total letters replaced.
(LEN(..)-LEN(..))/LEN($C$3): Tells us how many times C3 is present in B6.
So there you go.
Download Example Workbook:
Click here to download the example workbook. Play with the formulas to learn more.
A challenge for you – Find total occurrence count with single formula:
Let’s say you want to find out how many times $C$3 is present in a range – B6:B19 with one formula. How would you write it?
Please post your answers in comments section.
Related formulas:
Check out below examples to learn more.
- Array formula to count maximum text occurrences in a range
- How to count words in a cell using formulas
- How many times a list of values occurs in another list?
- VLOOKUP based on pattern
PS: Thanks to Simran who emailed me this question.
PPS: The writer is not balding. He still sports plenty of pointy hair 🙂
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.