With each passing day the amount of information contained in a single spreadsheet, slide, document is growing. Thanks to demanding bosses, clients and colleagues, we are now supposed to provide all the relevant information in as much less space as possible.
This is where micro charting or light weight data exploration has become a rage. The idea of shrinking a chart to fit in side a cell has been catching up with corporates and individuals alike.
In this post, we are going to review 7 of the MS Excel Micro-charting Alternatives so that you have a good idea of finding the right micro charting tool for your purpose.
1. Incell excel charts using REPT() spreadsheet function
Incell charting using REPT() spreadsheet is one of the easiest ways to include some data visualization capabilities to your excel tables without sweat. Click here to learn this technique of drawing incell charts.
Advantages:
- Very easy to implement
- No need to install any VBA or Add-ins
- Suitable for simple data visualizations in tables
Disadvantages:
- You can only make variants of bar charts
- Difficult to format, highlight specific points with out tweaking
- Not suitable for corporate environment where you need lots of visualizations on the tables
2. Incell charts using REPT(), cell formatting and conditional formatting
This technique involves using in-cell charts to prepare the micro chart and then using excel features like cell alignment and conditional formatting to provide additional information, thus making the charts rich. Learn more.
Advantages:
- Moderately easy to implement
- No need for VBA or add-ins
- Suitable for visualizing project plans, sales reports etc.
Disadvantages:
- Conditional formatting has limitation of only 3 conditions / formats
- Not suitable for complex visualizations
3. Resizing regular excel charts to fit inside a cell
By resizing the normal excel charts and removing all the chart labels, axis, background etc. we can get a micro chart effect with all the goodness of regular excel charts.
Advantages:
- Since most of us familiar with regular excel charts, this is an easy to implement technique
- All the chart types are available for micro charting, so you can create spark lines, pie charts, stacked bars etc.
- Easy to format, highlight charts
Disadvantages:
- Not all charts scale elegantly
- Needs a lot of formatting to remove all the chart labels etc.
- Not suitable if you have lots of charts to prepare as maintaining that many charts is painful
4. Using custom fonts / ding bats to create micro charts
Since we can insert any character in to a cell using formula, by installing a custom bar chart / pie font in our computer we can create incell graphs in excel with ease. Click here to see example pie chart, line chart.
Advantages:
- Easy to implement
- Reduces lots of chart maintenance / creation work because of the fonts
- Suitable for simple visualizations
Disadvantages:
- Not shareable since other person need to have the font installed before seeing the spreadsheet
- Not for everyone, since installing fonts is often not possible on office computers
- Not suitable for complex visualizations / dashboards
5. Using Spark lines UDF from Daily dose of excel
If you are planning to get simple spark lines on your spreadsheet cells then Daily dose of Excel’s sparklines UDF can be handy for you. This technique takes a set of numeric values as input and draws a line in the output cell based on the input.
Advantages:
- Moderately easy to implement
- Suitable for instant spark lines
- Makes a good addition to your sales report, project plans etc.
Disadvantages:
- You need to install the User Defined VBA Function in order to get this work
- When sharing the work book with others, they need to enable UDFs / VBA to make this work
- Suitable only when you want spark lines
6. Using a free excel micro charting tool like Spark lines for Excel by Fabrice
Spark lines for Excel is an excellent alternative to make your reports / dashboards look truly professional without spending a penny. This is set of VBA UDFs defined to draw micro bar charts, line charts, bullet charts, reverse bullet charts, Pareto charts, Scale-lines, variance charts and cascade charts. The latest version is available for download on sourceforge.
Advantages:
- Totally free with truly world class micro charting in excel options
- Easy to implement if you know how to install UDFs / excel add-ins
- Suitable for enterprise class dashboards, sales reports
Disadvantages:
- Since this is a free / open source version, any implementation issues will have to be solved by you
- Requires installing UDFs on others computer or enabling VBA before you can share this with them
7. Commercial alternatives like Bonavista micro charts
Of course if you are a heavy user of micro charts and you (your company) needs a totally professional solution for your dashboards then you may want to consider one of the commercial alternatives like Bonavista micro charts.
Since they advertise on my site through Google ads, I am not planning to talk about this any further. But if you have any questions, drop a comment. Andreas, who represents both Xlcubed and Bonavista systems is a frequent commenter here and he would be happy to answer your questions.
So, which one should I use?
If you want a simple incell chart, use one of the REPT() based techniques.
and If you want a full fledged micro charts for you reports / dashboards then start with free excel spark lines and then if needed migrate to one of the commercial alternatives.
20 Responses to “Simulating Dice throws – the correct way to do it in excel”
You have an interesting point, but the bell curve theory is nonsense. Certainly it is not what you would want, even if it were true.
Alpha Bravo - Although not a distribution curve in the strict sense, is does reflect the actual results of throwing two physical dice.
And reflects the following . .
There is 1 way of throwing a total of 2
There are 2 ways of throwing a total of 3
There are 3 ways of throwing a total of 4
There are 4 ways of throwing a total of 5
There are 5 ways of throwing a total of 6
There are 6 ways of throwing a total of 7
There are 5 ways of throwing a total of 8
There are 4 ways of throwing a total of 9
There are 3 ways of throwing a total of 10
There are 2 ways of throwing a total of 11
There is 1 way of throwing a total of 12
@alpha bravo ... welcome... 🙂
either your comment or your dice is loaded 😉
I am afraid the distribution shown in the right graph is what you get when you throw a pair of dice in real world. As Karl already explained, it is not random behavior you see when you try to combine 2 random events (individual dice throws), but more of order due to how things work.
@Karl, thanks 🙂
When simulating a coin toss, the ROUND function you used is appropriate. However, your die simulation formula should use INT instead of ROUND:
=INT(RAND()*6)+1
Otherwise, the rounding causes half of each number's predictions to be applied to the next higher number. Also, you'd get a count for 7, which isn't possible in a die.
To illustrate, I set up 1200 trials of each formula in a worksheet and counted the results. The image here shows the table and a histogram of results:
http://peltiertech.com/WordPress/wp-content/img200808/RandonDieTrials.png
@Jon: thanks for pointing this out. You are absolutely right. INT() is what I should I have used instead of ROUND() as it reduces the possibility of having either 1 or 6 by almost half that of having other numbers.
this is such a good thing to learn, helps me a lot in my future simulations.
Btw, the actual graphs I have shown were plotted based on randbetween() and not from rand()*6, so they still hold good.
Updating the post to include your comments as it helps everyone to know this.
By the way, the distribution is not a Gaussian distribution, as Karl points out. However, when you add the simulations of many dice together (i.e., ten throws), the overall results will approximate a Gaussian distribution. If my feeble memory serves me, this is the Central Limit Theorem.
@Jon, that is right, you have to nearly throw infinite number of dice and add their face counts to get a perfect bell curve or Gaussian distribution, but as the central limit theorem suggests, our curve should roughly look like a bell curve... 🙂
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I'm afraid to say that this is a badly stated and ambiguous post, which is likely to cause errors and misunderstanding.
Aside from the initial use of round() instead of int(),.. (you've since corrected), you made several crucial mistakes by not accurately and unambiguously stating the details.
Firstly, you said:
"this little function generates a random fraction between 0 and 1"
Correctly stated this should be:
"this little function generates a random fraction F where 0 <= F < 1".
Secondly, I guess because you were a little fuzzy about the exact range of values returned by rand(), you have then been just as ambiguous in stating:
"I usually write int(rand()*12)+1 if I need a random number between 0 to 12".
(that implies 13 integers, not 12)
Your formula, does not return 13 integers between 0 to 12.
It returns 12 integers between 1 and 12 (inclusive).
-- As rand() returns a random fraction F where 0 <= F < 1, you can obviously can only get integers between 1 and 12 (inclusive) from your formula as stated above, but clearly not zero.
If you had said either:
"I usually write int(rand()*12) if I need a random number between 0 to 11 (inclusive)",
or:
"I usually write int(rand()*12)+1 if I need a random number between 1 to 12 (inclusive)"
then you would have been correct.
Unfortunately, you FAIL! -- repeat 5th grade please!
Your Fifth Grade Maths Teacher
Idk if I'm on the right forum for this or how soon one can reply, but I'm working on a test using Excel and I have a table set up to get all my answers from BUT I need to generate 10,000 answers from this one table. Every time, I try to do this I get 10,000 duplicate answers. I know there has to be some simple command I have left out or not used at all, any help would be extremely helpful! (And I already have the dice figured out lol)
Roll 4Dice with 20Sides (4D20) if the total < 20 add the sum of a rerolled 2D20. What is the average total over 10,000 turns? (Short and sweet)
Like I said when I try to simulate 10,000turns I just get "67" 10,000times -_- help please! 😀
@Justin
This is a good example to use for basic simulation
have a look at the file I have posted at:
https://rapidshare.com/files/1257689536/4_Dice.xlsx
It uses a variable size dice which you set
Has 4 Dice
Throws them 10,000 times
If Total per roll < 20 uses the sum of 2 extra dice Adds up the scores Averages the results You can read more about how it was constructed by reading this post: http://chandoo.org/wp/2010/05/06/data-tables-monte-carlo-simulations-in-excel-a-comprehensive-guide/
Oh derp, i fell for this trap too, thinking i was makeing a good dice roll simulation.. instead of just got an average of everything 😛
Noteably This dice trow simulate page is kinda important, as most roleplay dice games were hard.. i mean, a crit failure or crit hit (rolling double 1's or double 6's) in a a game for example dungeons and dragons, if you dont do the roll each induvidual dice, then theres a higher chance of scoreing a crit hit or a crit failure on attacking..
I've been working on this for awhile. So here's a few issues I've come across and solved.
#1. round() does work, but you add 0.5 as the constant, not 1.
trunc() and int() give you the same distributions as round() when you use the constant 1, so among the three functions they are all equally fair as long as you remember what you're doing when you use one rather than the other. I've proven it with a rough mathematical proof -- I say rough only because I'm not a proper mathematician.
In short, depending on the function (s is the number of sides, and R stands in for RAND() ):
round(f), where f = sR + 0.5
trunc(f), where f = sR + 1
int(f), where f = sR + 1
will all give you the same distribution, meaning that between the three functions they are fair and none favors something more than the others. However...
#2. None of the above gets you around the uneven distribution of possible outcomes of primes not found in the factorization of the base being used (base-10, since we're using decimal; and the prime factorization of 10 is 2 and 5).
With a 10-sided die, where your equation would be
=ROUND(6*RAND()+0.5)
Your distribution of possible values is even across all ten possibilities.
However, if you use the most basic die, a 6-sided die, the distributions favor some rolls over others. Let's assume your random number can only generate down to the thousandths (0.000 ? R ? 0.999). The distribution of possible outcomes of your function are:
1: 167
2: 167
3: 166
4: 167
5: 167
6: 166
So 4 and 6 are always under-represented in the distribution by 1 less than their compatriots. This is true no matter how many decimals you allow, though the distribution gets closer and closer to equal the further towards infinite decimal places you go.
This carries over to all die whose numbers of sides do not factor down to a prime factorization of some exponential values of 2 and 5.
So, then, how can we fix this one, tiny issue in a practical manner that doesn't make our heads hurt or put unnecessary strain on the computer?
Real quick addendum to the above:
Obviously when I put the equation after the example of the 10-sided die, I meant to put a 10*RAND() instead of a 6*RAND(). Oops!
Also, where I have 0.000 ? R ? 0.999, the ?'s are supposed to be less-than-or-equal-to signs but the comments didn't like that. Oh well.
How do you keep adding up the total? I would like to have a cell which keeps adding up the total sum of the two dices, even after a new number is generated in the cells when you refresh or generate new numbers.
So, how do you simulate rolling 12 dice? Do you write int(rand()*6) 12 times?
Is there a simpler way of simulating n dice in Excel?
I've run this code in VBA
Sub generate()
Application.ScreenUpdating = False
Application.Calculation = False
Dim app, i As Long
Set app = Application.WorksheetFunction
For i = 3 To 10002
Cells(i, 3).Value = i - 2
Cells(i, 4).Value = app.RandBetween(2, 12)
Cells(i, 5).Value = app.RandBetween(1, 6) + app.RandBetween(1, 6)
Next
Application.ScreenUpdating = True
Application.Calculation = True
End Sub
But I get the same distribution for both columns 4 and 5
Why ?
@Mohammed
I would expect to get the same distribution as you have effectively used the same function