Sample Data Sets For Excel All You Need To Know About Sample Data Sets For Excel

Today’s blog will be the aboriginal in a multi-part alternation on replicating Excel functions in T-SQL, starting with HARMEAN, GEOMEAN and FREQUENCY.



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We’ll focus our solutions on creating T-SQL in-line, Table Admired Functions (iTVFs), alien in SQL Server 2005, that administer the band-aid address to a accurately advised table of sample data.  If you plan on application any of these solutions, this agency you’ll charge to acclimate them to your table of interest.  Due to the charge to abide somewhat abrupt in my explanations, I apparently won’t be accomplishing a lot of achievement testing of these iTVFs (I absolutely will not in today’s blog).  But you can blow assured I’ve put my arch to the grindstone in an attack to do my best to absorb all of the achievement best practices I apperceive of aback autograph this library of functions.

We’ll charge to assemble some sample abstracts to validate our T-SQL cipher against, so let’s alpha with a table and some sample data.

Let’s assemble an Excel spreadsheet absolute this sample abstracts and appearance Excel’s after-effects for the three functions we’ll attack to replicate.  The Breaks cavalcade represents one of the arguments to the FREQUENCY function.



In adjustment to use the Excel FREQUENCY function, I bare to apprentice how to access arrangement formulas, which you’ll additionally charge to do if you appetite to try some examples of your own that are like the above.

The harmonic beggarly of the set of observations represented by our sample can be declared as the absolute cardinal of observations disconnected by the sum of the reciprocals of the abstracts elements.  If you are into the algebraic representation of this, you can appointment the affiliated Wiki page.

This is absolutely absolutely aboveboard in T-SQL:

Note the accord amid alternate ethics and those affected by Excel above.

To accumulate things accurate and tidy, we’ll abbreviate this in an iTVF like I said I would in the introduction.

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Which we can alarm either for a distinct accumulation or the absolute set as follows.

You can additionally analysis that the harmonic beggarly for all of the sample abstracts matches our Excel spreadsheet archetype above.  These after-effects appearance hardly added attention than Excel does, but apparently you can acclimatize that if you are interested.

The geometric beggarly of the set of observations represented by our sample abstracts can be declared as the nth basis of the artefact of the ethics in the sample.  An another description is to acquisition the artefact of the ethics in the sample, and accession that to the ability that is the alternate of n.  Already again, the Wiki folio will appearance you the algebraic representation of this calculation, if that would be added bright to you.

T-SQL has a SQRT action but it does not accept a action for artful the nth root.  It does accept a POWER function, which we can use as in the accessory description.

Of course, the absolute claiming is artful the artefact of all items in the sample, which could about-face out to be absolutely ample and end up causing an addition overflow absolutely quickly.  To accord with this issue, we’re activity to use a Stupid T-SQL Trick for Logarithms that we abstruse from an beforehand blog.

Let’s attending at the after-effects from the afterward query:

By accretion the LOG10 values, we’ve got a logarithmic cardinal that can be adapted aback to the artefact of the numbers that were summed by application POWER(10.0, x), area x is SUM(LOG10(Value)).  That could be absolutely ambiguous due to the abeyant for addition overflow, but is accessible for the set of sample abstracts we’ve provided.  If we casting the SUM to a FLOAT, we’ll accept a abundant added ambit of ethics available, admitting at a accident of precision.

Also agenda that LOG10(0.0) is amorphous and will acknowledgment an error, so if you’ve got aught abstracts credibility anywhere, you’ll charge to handle that case as well.

For a quick check, we can see that 1*2*3*4 = 24 (the aftermost row or area Grp=4).

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We’re not absolutely there yet, because we still charge to booty the nth root, but we can now account the geometric beggarly thusly:

Our after-effects announce that we assume to accept nailed the geometric beggarly as affected by the Excel GEOMEAN function.

Let’s now do what we consistently like to do and said we were activity to do in the introduction, and that is to abbreviate this in an iTVF.

And we can now either alarm that action for a accumulation or we can account the geometric beggarly beyond all of the sample data.

Once again, agenda the accord amid alternate ethics and those affected by Excel above.

Building an iTVF for FREQUENCY is activity to be aloof a little added arduous than the two cases we’ve advised above.  Let’s booty a attending at a specialized concern targeting our aboriginal Grp to get started.

If you’ve looked at how FREQUENCY works, it constructs four rows from a three amount ambit (each amount actuality the high end of a range), in adjustment to acquisition annihilation beneath than the added amount (first arrangement amount returned), greater than the aboriginal amount (last arrangement amount returned), or contrarily amid average values.  Added than three rows in the ambit of advance consistently after-effects in one added row of results.

Our r1 and r2 columns can be acclimated to accomplish the ambit checks declared above.  In fact, they’re absolutely the affection of the action we’ll appearance you next.

Note that Excel’s FREQUENCY action may alone account counts amid aught and the amount in the aboriginal row, admitting what we’re about to do extends the lower end of the ambit into abrogating numbers.  The affidavit was cryptic and I didn’t alone analysis it out.  But we animate our admired readers to do so and adapt my cipher appropriately if it bigger apparel your needs that way.

sample data sets for excel
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Importing Excel Files into SAS – SAS Tutorials – LibGuides at Kent … – sample data sets for excel | sample data sets for excel

Before we actualize a action to do the abundant appropriation here, we appetite to acknowledgment Table Admired Parameters (TVPs).  This is a way of creating and application tables based on a arrangement on-the-fly (sort of) in T-SQL.  I’ve accounting afore about how TVPs can be used.  Let’s actualize one now (this is done by the CREATE TYPE AS TABLE statement):

TVPs can be created as aloft and anesthetized into a T-SQL function, bold you are application at atomic SQL 2008.

So now here’s my booty on a T-SQL iTVF to account frequency. Agenda how I canyon in the TVP as the added constant to the function.

I’ve done a brace of things in our action actuality that conceivably crave explanation:

Let’s run this bad boy through its paces.

The calligraphy aloft produces the four after-effects sets apparent below.

You ability appetite to go aback and analysis those frequencies adjoin the Excel archetype aloof to be abiding I’m not aggravating to cull a fast one on you.

So there you accept it!  Our aboriginal attack at replicating a few Excel functions in T-SQL.

And actuality you may accept been cerebration that I was activity to advise you how to excel at autograph SQL aback you aboriginal apprehend that title!  Maybe that will appear later, already I’ve ample it out myself.

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© Copyright Dwain Camps 29 Apr 2015.  All rights reserved.

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