Time based chart
Volume chart
Tick chart
Range bar chart

I'd like to see a discussion on what single chart you would call your most important or crucial, and of course the big question -- why.

Please post the chart screenshot and tell us why you chose this chart and why it's the most important. Is it a time chart, range/renko, profile, order flow, tick chart -- what & why.

I personally voted for time based and context. Using simple indicators that show me things like daily and weekly ranges help give me some context for what good entry or exit points may be. I keep it simple.

I voted for Renko/Range/Tick. Being a price action trader, I use tick charts as it compliment my style of trading, very well. Considering that each candle on a tick chart represents a number of transactions, it adds a little more depth to a traditional time based chart. Seems to smooth things out in general but also when the market is volatile as well.

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My thought is that indicators, bars, charts, etc... all are after the fact - they all illustrate what price just did.

The question I ask is why did price do that?

The reason price moves is because traders trade. And when traders trade someone is always left holding the bag - always.

Context provides you a high level view/map of where traders traded - thus you have an idea where losers are and some insight into what the market may do when it gets back to those locations - that being break out, pull back, or go sideways. But if price was just there, broke out weakly and then pulled back strongly ( measured by pace, time, alignment in multiple time frames, etc..) it's now most likely to continue in the pull back direction or go sideways. From this simple analysis, I have gone from 3 possibilities to 2 possibilities. If you learn to read it right you can get the sense of what it is highly likely to do - thus only 1 possibility - this process is an edge. The question then becomes how far and how long will it continue as well as if it does not occur at what point is the analysis simply wrong. Always remember nothing will ever be 100% accurate because the market is too big, complex and sometimes shit just happens. SFT See it, Feel it, Trust it. (so easy to type, so hard to do)

So where are the losers? Look to the left on a simple chart - peaks, valleys, thick sideways areas (barbed wire as Al Brooks calls it). All of this is context, as is the trend , especially if you see these things align on the 1, 3, 30 and day charts. Yesterdays high, close, low, open, today's open, overnight low, overnight high, etc... etc...all of these are part of context because there are so many strategies that are based on these highly visible areas. This is where the sharks live and feed, I'm just feasting on their scraps.

Find areas where traders trade, learn to understand through your analysis of what occurs at these locations, and most importantly learn to understand and trust your analysis, especially when you find yourself on the right side of the market.

Learn to enter where pain points are, the locations where losers are saying OMG this sucks I have to exit. If context is conducive, enter when they have to exit and hang on for the ride. Know where to enter, know where price should go if your are correct and know where you are definitely wrong providing the location for your stop loose. Have your targets and stop losses set before you enter (mental or physical). This type of trade can last only seconds, or it could last all day, your style will dictate how you trade it. But I always keep in mind that both Pigs and Chickens get slaughtered.

Context provides the map of these interesting locations to play the game.

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Since I am an algo trader, regular time based charts are my bread and butter. I'm recycling an image from my journal earlier tonight:

This has a custom OBV indicator, ATR and ADX, which I am currently using to explore a trading idea.

I actually prefer playing with raw data. Range bars have sucked some of my time away and I'm learning about point and click charts, since I received a free book from TASC on the Wyckoff method.

~vmodus

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I chose time-based and context/entry,exit criteria.

The lines on my charts are Y-DAY High/Low, Mid and Close. Weekly and Monthly TWAP, this is quite different from what I payed attention to before, which was a bunch of volume profile stuff and VWAPs and S&R. Just felt like it was to much to look at so decided to go with with the essentials for my trading, for now .

Velox

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Trading: The one I'm creating in the present....Index Futures mini/micro, ZF

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I view trading as a business.... because it is.

I wrote the below for someone recently in a PM and am reposting it here... basically sums it up....nut shellish.....

Said it before..... peanut butter...yep that's right...... when it's on sale....I will grab more than I currently need. It's just smart business. Run your house like a business... it's just smart. Do the same in your other business....The Business of Trading......IT'S JUST SMART. Stop complicating it with junk that has nothing to do with the world in general.

My ES chart: I'm explaining some parts and feel other parts are self-explanatory. My levels from all my charts ....including NQ YM etc taken as a whole are used to discern local market extremes....places to make a business transaction. Simple, but not easy.

I also use minute charts for ES and the gang ..... market internals again on minute charts.

Ron

...My calamity is My providence, outwardly it is fire and vengeance, but inwardly it is light and mercy...

The steed of this Valley is pain; and if there be no pain this journey will never end.

Buy Low And Sell High (read left to right or right to left....lol)

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I selected something else because its bunch of things clamped together. I'm only interested in knowing if market is relatively weak or strong, I take position in that direction and try to maximize my chances.

Here is chart I posted in some other thread today, markets were weak

And down below is the result

You can see the nice fall followed, this was globally weak session so I was bearish before market hrs but markets continued to be weak, especially after EU session.

If I had to pick one, it would be more in line with Context I guess.

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I use time-based chart along with Fibonacci retracement. Time-based chart provides all the information I need to make decision on when to enter and Fibonacci retracement provides information on when to exit. Here is an example:

Trading: Index and Stock options, Stocks (seldom), Nadex (just starting), Forex

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For those of us using bands based on moving averages Range charts provide a smoother more granular chart. Of course problems come when the market is moving to fast for you to trade it. The attached chart shows a 20 tick range chart (for day trading the /NQ). It includes a price/donchian channel length 50. It includes an indicator at the bottom that shows the candles / minute or the minutes per candle for avoiding the temptation of jumping into the market when a feeding frenzy is going on. It includes some bands and a midline for mid cross entries or outer bands for breakout entries. It also can use Candles with Red or Green arrows in them. Two reds in a row, go short, two greens in a row go long and two opposite or blank candles (no arrow) get out. I like a simple looking chart that gets my head out of the "what will the market do" thinking. The green part of the chart shows the current floating profit loss both for the chart length (5 days in this case) and for the current day. (single contract results but this can be changed as desired)

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There were almost 100 point swings several times even 30 minutes before close there was one more ended the day recovering the downturn. Pretty much the market found support at almost 100 points down SP and it always bounced back. However it hit resistance at probably down 25 points, one has to have strong stomach to short it there because the market again would touch support again at negative almost 100 points, cover it (that’s easy) and then wait to hit the resistance again and do it all over again. If the bias is positive then you can always buy at support but shorting at resistance requires experience and strong stomach to ride out if the position turned sour (which didn’t happen yesterday).

Disclaimer: I am not a trader and even if I were I could never trade that chart. My indicators are not that perfect. I don't even look at the market during trading hours and I make it a point, and only look at chart at end of day.

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Even if you are not a trader, you made the appropriate observation about support and resistance. You do not need any other indicator if you fully understand the concept of support and resistance. And, I do not think that there is any difference in doing bullish trades than bearish trades as long as you have the exact same predefined risk going into the trade.

Congratulations for your right observation.

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Trading: 6C (Low Margin,) 6E, CL, GC, ES and Maybe DX for smaller tick value

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Gartman's quote is:

“You want to be long the gold market, short the stock market, and long the bond market,” he said. “That’s the trade to have. I have that in my own account and continue to recommend it.”

How do you figure that is calling the bottom.

CNBC just posted this morning the overnight swing is 1000 points.

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Trading: Index and Stock options, Stocks (seldom), Nadex (just starting), Forex

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Come on guys, this is about your favorite CHART not your favorite stock advisor/anti advisor. Self edit please.Unless Dennis Gartman is a chart he should not be on this thread.

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I am going out of the limb here. I think this market is going to shape up to be a bell curve. Today’s market and next few weeks will shape the peak but eventually it will hit the downward slope of the bell curve.
Basically maybe we are looking at 2 days worth of rally. The day Fed cuts interest rate and the following day and then decline continues.

I agree. simple, context. That's a long way from where you were just before and after I joined this forum. ...and where I was too. I like to think of trading as surfing, or snowboarding. I'f you are a trader who does either you'll get that. Experience and context count, and from there it's how you react and adapt to an evolving situation.

Nate

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The Laplace distribution, one of the earliest known probability distributions, is a continuous probability distribution named after the French mathematician Pierre-Simon Laplace. Like the normal distribution, this distribution is unimodal (one peak) and symmetrical. However, it has a sharper peak than the normal distribution. The Laplace distribution is the distribution of the difference of two independent random variables with identical exponential distributions (Leemis, n.d.). It is often used to model phenomena with heavy tails or when data has a higher peak than the normal distribution.

This distribution is the result of two exponential distributions, one positive and one negative; It is sometimes called the double exponential distribution, because it looks like two exponential distributions spliced together back-to-back.

For those in finance, what this means is that large moves are even less likely than a normal distribution
and if anyone other than me has noticed, they all too often use a normal (Gaussian) distribution in discussing things...

my personal discovery from plotting things is what woke me up
but its not unknown

Thanks - Yes work most of the time !!!!! - But one have to find out best trading times of the day. For me it works best between 8 AM to 10-11 AM and again from 15 PM to 17:30 PM all central European time.

TraderMich

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John Ehler's discusses Laplace distribution in Rocket Science for Traders. He also explains the failings of Gaussian distributions in his varied writings.

So to keep this chart related and on-topic, here is my favorite chart this week, with Ehler's Hilbert Transform and Even Better Sinewave indicators:

~vmodus

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Care to explain this in simple terms? I dont understand how it matters whether its laplace or gaussian or whatever other name you wish to associate with the structure. From the image you posted, both models share similarities in that they have extreme outliers with the majority of data points evenly distributed around the median, just that one looks spiky and the other looks rounded. Your sample was only over two days and might be a poor representation of the total population. 1.2 million price moves means nothing in the context of the current environment. And how well does this model hold up when measured against months of data under the numerous market conditions? When all that is defined, how do you actually use the information to trade?

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My single most important chart is the 5m bar chart. Who doesn't like a 5m chart...or the tick chart equivalent? . It's interesting to see all the different charts traders use. They all display the same thing, except maybe warped in some way, to fit the individual trader's eye. It's like a glimpse into the soul....

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I voted for time based charts and context - I use a 60M chart for an intermediate look and a 20M chart for decision making. I use a renko chart for entries after a decision has been made but without the 20M, the renko is somewhat useless. I have tinkered with a renko chart that is similar in nature to a 20M chart but haven't stumbled upon anything I like. I used to flood my charts with indicators but nowadays I am just using bid|ask & up|down delta for confirmation of zones/areas of interest/etc.

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I use a modified mean renco chart. I trade with two monitors and the second monitor I use a 60-minute chart primarily for support and resistance. I'm a scalper and rarely in any trade for more than 10 minutes. Works good for me. I stopped trying to predict what the market is going to do a long time ago and just stick with price action.

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As I noted earlier, John Ehlers discusses Laplace distribution versus Gaussian distribution in his book Rocket Science for Traders. I'm sure others have done the same analysis. Volume can be 300 or 3m, but price distribution just does not fall neatly in the bell curve.

Ehlers did a couple of webinars with Big Mike, which were very informative. You can watch them over on the FIO YouTube channel. Some of the stuff went over my head (advanced/applied mathematics), but a year later I have a better understanding.

FYI, I am not a statistician, nor do I play one on the Internet.

~vmodus

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well... you just have to look... and understand the chart

the Gaussian distribution is wider...
meaning that there are more values or samples away from the center
the Laplace shows that these values drop off fast...
meaning the farther you get from zero, the drastically fewer values or samples exist

remember... these are charts of distributions..

in both cases, there are just as many up moves as down moves
there are a lot more 10 cent moves in the normal/Gaussian distribution than in the Laplace

The Laplace (or double exponential) distribution, like the normal, has a distinguished history in statistics. It has applications in image and speech recognition, ocean engineering, hydrology, and finance.

What does it look like?
The plot in Figure 1a depicts the Laplace probability density function centered at zero and, for comparison, the normal one.

To explain what these fatter tails mean, consider that the cumulative probability of the standard normal at 3 is approximately 99.9%, which justifies the common assertion that events 3 standard deviations or more above (or below) the mean are unlikely. However, the corresponding cumulative probability of the Laplace with the same median and variance is about 99.3%. Therefore the occurrence of an “extreme” event in a Laplace population is more than five times as likely as in a normal population

Maybe someone else can explain it more simply...

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Thanks for the explanation @Artfldgr and @vmodus I'll try to find that webinar and find out a bit more about the laplace theory although it will be more for curiosity than anything. When you talk about 99.9 vs 99.3 percent.'extreme event ' probabilities are you not getting caught up in irrelevant minutae? It does not matter that one is more likely then the other, what matters is that when an extreme event occurs, both models are capable of identifying it. and in any case you can define your own hypotheses rejection zones. Just because a textbook says it is 3% or 5% doesn't make it a rigid rule that you can't bend.

I'm off to find that webinar..

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for us its more about the likelyhood of the extreme event..

if the stocks were gaussian, there would be more of them moving 10 cents..
if the stocks are laplace, fewer of them will...

if the stocks were gaussian, fewer would move zero
if the stocks are laplace, many more of them stay at zero movement over time

its harder to make money in a laplace financial world..

i think you might get it easier if you think of lots of stock moves of different amounts being plotted...
how many go to zero, how many are 5 cents, how many are 10 cents, etc..

if there is this spike in the middle, then a lot more go to zero or 2 or 3 cents..
a whole lot less go to 5 cents or 10 cents...

THATS what the charts are about

my plot in the post shows the price movement from teusday close to thursday...
by far.. most of it amounted to zero... very few were 20 cent moves compared to gaussian

the bottom line about it is that its harder to make a profit..

and if you find the webinar, post it... i would like to see how to better explain it!!!
sucks to know your not doing a good job of it...

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Found and watched the webinar (in the elite section @Artfldgr). All I can say is that if you discovered an edge that printed money you would be using that edge to print money. Not writing books and selling indicators.

Also, its one thing when something works in theory and you can show how marvellously predictive an indicator is on a perfectly presented sinewave (with arrows and all) but another thing altogether when you throw it at a real chart and need to explain the losses with disclaimers like 'ah but you know thats the market you cant win them all', and others like 'it wouldnt have worked in this particular situation because of XYZ..'

This has NOTHING to do with what comes next it is simply information modelled on the past. In keeping wth the theme of the thread, here is how I use this stuff in my daily trading ritual. I am currently using the past 14 days because we are in a volatility period and I want information about whats happening now and not watered down with anything prior.

I extract RTH data for the ES and calculate the daily range. From that I determine the middle, edges, st dev, and range.

Once RTH opens, I work out what price levels are likely based on the session open.

I plot those on the graph right at the start of the session, and can be relatively comfortable that my expectations are synchronized with the current market environment.

Now the key thing to remember is that this model is simply one perspective. The best it can do is highlight what the probabilities are. It is NOT predictive in any way. If you are an inside out trader (breakout trader from value to a target) then this is a great system to determine what targets are likely to be achieved. If you are outside in (reversal trader from extremes back into value) then same thing in reverse.

So if you note that the market on Friday did not push beyond the 3rd -deviation and did not quite make the push to complete the 3rd +deviation although it got close and acheived 2nd +deviation. This is totally expected behaviour and within the rules that the market has been playing by over the past 14 days.

I did get some of that final move on Friday (target to +1SD). Not all but enough to close the day out positive.

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Nicely done. It's good to be able to read something and know if you think it makes sense (I think it does ), and if it shows you something in an enlightening way (ditto.)

Let me make two comments, not criticisms, more like calling attention to terminology or phrasing:

1. Of course "information modeled on the past" can tell you something about what comes next. You just did that, in a probabilistic way.

2. Of course it is "predictive," in the only sense that anything can be predictive: there is an assignable probability to it. If you can't assign an exact probability for some reason, but you can still distinguish between more probable and less probable scenarios, then that is also "predictive," but less so. If by "predictive" you mean something besides "predictive with at least some sort of assignable probability," then you don't have any ability to predict anything.

For example, I accept the weather forecast as being reasonably likely to happen, and often plan what I do based partially on it. I know it is often right, but not a certainty.

I hope I didn't state this so strongly that it comes out that I disagree with what you wrote. Tell me if so, because I think what you wrote is very good, and I didn't mean to say otherwise.

An edge after all may be only a slight leaning of probability in one direction, which is quite enough over time if you can manage other factors right (losses, asset weighting, etc.). I doubt that anyone has anything much more than that.

Bob.

When one door closes, another opens.
-- Cervantes, Don Quixote

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Thanks @bobwest. The deviations plotted n the chart are more about setting expectations and visualising what the market has been doing. If I were to drill down and try to determine probabilities for those deviations to be achieved I would use measured moves and basic price action principles.

What does that mean in practice?

If you take a look at the chart in my previous post do you notice the size of each of those swings? Thats where you determine probabilities. So you extract all those swing numbers for the past 14 days. RTH only - Im not interested in overnight or European hours.
You group the numbers, and find the percentages as in the screenshot below:

What that breakdown tells you is that swing sizes between 20-29 points occur the most often at 24% of the time. The next most frequent ranges fall between 10-19 points at 21% of the time. ANd so on. You can use these statistics to find high probability trade locations. So for instance if the market surges 100 points and through your analysis you have determined that a swing size between 100-110 occur 1.3% of the time and that this has only happened 4 times in the last 289 samples, then you might have a reason to look for signs that price is going to revert back to value.
Any trade using this reasoning would be a high probability trade. But you cannot simply rely solely on the stats. You still have to use common sense and basic price action principles when you make your decision. For instance the footprint charts which I believe holds key information (and which I am still learning about) with regards to volume, order flow and trader positioning. These things all have to come together and the pieces have to fit together in a logical way where you aren't thinking too hard about it.

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Trading: 6C (Low Margin,) 6E, CL, GC, ES and Maybe DX for smaller tick value

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@Grantx, May I ask what you are using to draw these statistics? I know there was a function in NT7 PAS that did not move to NT8. Would you share this indicator?

It's all manual I'm afraid. It can be done though python or excel. If you want I can show you step by step how to do it. It is very easy and yields invaluable information.

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[QUOTE=Grantx;785565]Thanks @bobwest. The deviations plotted n the chart are more about setting expectations and visualising what the market has been doing. If I were to drill down and try to determine probabilities for those deviations to be achieved I would use measured moves and basic price action principles.

What does that mean in practice?

If you take a look at the chart in my previous post do you notice the size of each of those swings? Thats where you determine probabilities. So you extract all those swing numbers for the past 14 days. RTH only - Im not interested in overnight or European hours.
You group the numbers, and find the percentages as in the screenshot below:

What that breakdown tells you is that swing sizes between 20-29 points occur the most often at 24% of the time. The next most frequent ranges fall between 10-19 points at 21% of the time. ANd so on. You can use these statistics to find high probability trade locations. So for instance if the market surges 100 points and through your analysis you have determined that a swing size between 100-110 occur 1.3% of the time and that this has only happened 4 times in the last 289 samples, then you might have a reason to look for signs that price is going to revert back to value.
Any trade using this reasoning would be a high probability trade. But you cannot simply rely solely on the stats. You still have to use common sense and basic price action principles when you make your decision. For instance the footprint charts which I believe holds key information (and which I am still learning about) with regards to volume, order flow and trader positioning. These things all have to come together and the pieces have to fit together in a logical way where you aren't thinking too hard about it.[/QUOTE @Grantx I've come across similar analysis done by FT71 in one of his webinars and he calls it as "Harmonic Rotations". May I know whether you have seen this webinar and not considering approach discussed by FT71 for some reason?

This was an excellent webinar, so much good advice. Thanks for reposting that Big Mike. I found the probability graphs on the scale out method very interesting.
I am trying to figure out how …

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A practical gaussian example from today. First the daily prep:

Then the distribution (right skew ) falling within the gaussian distribution framework calculated from the most recent days of volatility. On the right is the TPO chart on the left are deviation price markers showing higher probability price reversal levels or targets depending on your style. Today is not over yet, but if you go back over the past few days you will see very similar behavior.

Any data can be plotted into different distributions, it doesn't make the data actual distribution that way
the same data you have you can also apply a Laplace distribution and many others...
However its the fit that matters... not what you apply to the data...

and from another on finance
Against the Norm: Modeling Daily Stock Returns with the Laplace Distribution
Many introductory-level courses teach students to use the normal approximation for daily stock returns when modeling over a long period of time, but even some of the most influential names in mathematical finance agree that daily returns fall outside the realm of the normal distribution. 1 While it is true in many cases that the
distributions of daily stock returns tend to be symmetrical, the distributions also have fat-tails, meaning there is a greater likelihood of observing extreme cases

how to apply this? i dont know...
i also cant truly tell you with confidence what would happen if you are using gaussian distribution for prediction on laplace shaped data... though my guess would be that due to the fatter tails and the higher center, the suprises would be more often and more detrimental than in a normal distribution.

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I wouldn't know either and I doubt it matters in my world. It works for me and is easy to understand so if you figure out how to put laplace to practical use I would be grateful to hear from you.

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At least i am honest about it...
and it probably, in your use case, doesnt matter to a great degree...

they are both symmetrical
one has data stick closer to a lower move, and slightly more chance of bigger moves
the other the moves are a bit more distributed and under performs on the outliers

given that most investors are not playing the outlier events, it probably matters less in practice (the way your using it)
and most of the papers are more for fitting simulation and complicated math prediction models... which the guy trading doesnt use (and if they did, probably would be wasting serious time doing math)...

i guess you can get a feel for the difference if you look at the two of them in those overlay charts
laplace has a narrower taller center and fatter wings..
you probably are mentally adjusting the gaussian in practice towards that end anyway..

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Thanks! The OBV is a custom indicator, but I got (borrowed, stole) the idea of coloring from the ADX. If you use TradeStation, you can just open that code and borrow it. Otherwise here is the calculation in plain English/pseudocode:

My code uses a Case statement, but if/then/else works too.

~vmodus

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