Welcome to the Cannabis Data Science Meetup Group.
Thrilled to have you all here.
This is a roundtable for all of you brilliant minds
to come together.
I'll join you too.
And we can talk about cannabis data, various scientific ways
that we can analyze the data.
Why?
Well, the cannabis industry has been moving forward.
It's going through turbulent times.
And the way I say is we can let the politicians politic.
We can let the lawyers that practice law and all of that
jazz.
What can we add to the table?
We can calculate statistics.
And I think that adds an extraordinary amount
to the picture.
So today, once again, we'll put a bunch of really cool
statistics in your pocket.
Because that's what I do.
I just start calculating most basic statistics
and work my way up.
And I love presenting to all of you
because I actually want your red ink.
So please be super critical of my work
because this is just like a first draft, a rough draft
of some data analytics.
And the way any good writer gets better
is by getting critiqued by an editor.
So please view yourselves as critical editors.
And then if you ever have any research
that you want to bring here and get critiqued
by a friendly group of peers, you're welcome to.
So that's sort of the mission of the group.
So just going to, if you want, I always do this.
Let me know if this is ever painful.
But I always find it's pretty fun just to go around
and let everybody just maybe say a quick word for themselves
and maybe what you're working on this week
or anything you want to see added to the table,
any data that you're after, anything at all.
So I may actually go in reverse order today
if that's OK with everybody.
Just kind of interested.
And so Ruth, if you've got your microphone set up,
we'd love to hear about some of the things
you want to bring to the picture.
That way we can let some of the newer members speak
and then we can let the veterans have their say.
Also, you may just be muted this time around.
OK, there we go.
No real data issues to report.
I'm giving a talk tomorrow on evolution of science
and technology in cannabis and how I think the research
into medical cannabis is going to end up being like penicillin
and it will have wide-ranging implications
for many other disciplines and throughout society.
So I'm excited about that.
But no real data work to report.
It's cool that you bring that up because we can't forget
about the medical side of the picture.
And as I'll show you today, I don't think it's going anywhere.
You've got the tiniest bit of data points
that we can actually begin to actually uncover
a little bit about medical cannabis.
So I just scraped the surface so there's actually more for you
to dive into.
So cool data today.
Thanks for joining me.
Kayla, I know you were interested in strains.
You're running copyright, not copyright,
copyright left cultivars.
Coincidentally, we'll be talking about a few cultivars today.
We'd love to go a bit further in depth.
So once again, we'll just scrape the surface.
So this is something you can go much deeper on.
But once again, we'd love to hear about what you want to put
on the table for today.
Cool. Yeah, thanks.
Well, I've just been working on refining the intake system
for the backend, the database and for the galaxy
that we're working on.
We're working on a copyleft protected open source
public collaboration galaxy where we can have systems
for open collaboration and breeding as well as sharing
trait and gene information that can lead towards openly sharing
the benefits of that in breeding,
in understanding the meaning of the genes,
and even like being able to build that out.
So I've been working kind of on the backend there.
So I'm a little out of breath.
I just finished my workout right before this.
But anyways, we're also working with this app that the
University of Kansas put together and modifying that in tandem
with them to be usable in the field for cannabis growers
to document all that information that I just said,
get it into our galaxy.
So I've been pretty deep into that work this last week,
as well as we're building a bot, an AI-powered chat bot
that has natural farming and Frickshark beta and similar
information there, working with people like maybe in Thailand
and Ghana, other places to see if we can hone it in for their
farmers, cannabis included, but that's more broadly just for
plants in general and more organic farming techniques.
So yeah, that's really what I've been deep on.
I'm excited to see the data though and chit chat.
And you know, I love networking in this space and building
these connections, moving this open science along.
So thanks for bringing us all here to collaborate.
I love it.
Tons of ideas, but I'll let Ruth chime in so I don't steal
the show.
Ruth, what do you think?
That's really interesting.
I'm interested in understanding our, if you're looking at
strain genetics and profiles and stuff, are you seeing an
increase in variety or decrease in variety?
So are we seeing essentially more incestuousness or are we
actually getting more variety out there?
So that's a great question.
That's one of the questions that we hope to answer.
But the real down in the dirt answer is that we just don't
know.
And there's even like been a number of papers attempting to
do this that in the papers tend to also admit that we just
don't have the data to know that.
And so a lot of what we're trying to do at Copyloaf
is just create the systems where the community can then get
the data together and then we can figure out the real answers
to those questions and more questions.
Now, are you looking at data just within the country?
I mean, you mentioned like Ghana and I mean, certainly in a
lot of areas in Europe.
I've seen studies done and they tend to focus on, you know,
there's studies done out of, was it like Amsterdam or Sweden
or something trying to look at kind of the variety in the
plants there.
But they tend to go into one area and get a sampling there.
And I'd be interested almost like in a global sampling, is
anything like that being done?
Yeah, it seems like you're thinking along the same line
that we're doing.
So our perspective is a little bit different, you know,
talking.
We kind of came out of a community series of meetings,
open meetings, and there were researchers, there were people
who had kind of been burned out by the phylos incident.
There were like all of these different interests.
There were people from the highlands of Tibet and in
Thailand.
And so we have like lots of different influences in the
formation and we decided that our approach should be entirely
open.
And so we're not going in and getting a data set.
We're creating a system that anyone can put their data into
and know that it won't be hijacked, that it will be kept in
these open source systems where we can't even, as the holders
of it, lock it down because of the licensing terms.
Can you put a link to kind of your site or whatever it is
that you're doing into the notes?
So I would love to share that with other people.
I'm sure a lot of people would be very interested in that.
And thank you very much for doing that.
Oh, yeah, absolutely.
It's a big passion and also it's a lot of fun.
And yeah, it's copyleftcultivars.com.
So I'll put that there in the chat.
Yeah, we're super just open collaboration themed.
So feel free to reach out.
You know, I don't want to drag the meeting too far into kind of
recruiting or networking for the nonprofit because I know we have
some really cool information also that Keegan has brought.
But yeah, I want to be super open also to anybody who wants to
jump in and be involved with the work we're doing.
This is the fun thing about the meetup because we can actually go
off road.
So right, there's no reason we have to stay on the agenda.
We don't have to stay on the trail.
And I think you're doing a much more rigorous job at this because
Ruth asked a super interesting question, which is, you know,
what's going on with the diversity in cannabis?
Like, so I guess you would think genetic diversity.
So, of course, you need to do some genetic testing.
But what came to my mind is we could estimate perhaps what's
going on.
And once again, we don't have genetic data, but we have strain
data.
And so that's what I'll share with you today.
And so what we could just do, this is more of just a product count
versus diversity count, but you could just count all the unique
strains that are tested in any given month and see if that's
going up or down.
Once again, that doesn't necessarily mean diversity is going
up or down because you may just have, and I'll show you later,
you may have like runts and white runts and yellow runts and all
of that jazz.
So just because there's a proliferate variation of strain
names doesn't mean diversity is going up or down.
But any, Yasha, you have some thoughts?
Yeah, I want to second what everyone else is saying.
I think what you're working on is really cool.
And Copyleft is an excellent name.
And to back up what Keegan is saying, I really like the concept
of when you have something that you're the first to measure,
if you can measure it from multiple different approaches,
one is from the data and strain names, another one could be from
the bouquet of compounds found within the open data,
a third is genetic testing.
I don't know what else, maybe just like culturally, what are
people talking about more, what comes up more as mentioned in
terms of strains, but there may be multiple sources that point
at the same thing that could make the work that much more
certain.
I like the idea of having compounds as identifiers.
That's a great one.
Yeah, we're actually currently working on with the app trying
to figure out how we make those parts collectible, so to speak,
since it was built for like corn, for example, field crops
like that.
But yeah, I love that as a possible identifier as well.
And yeah, the strain name idea is a great one, and I think you
can also use tools like Seed Finder or like we have a project
going where we're web scraping Seed Finder and a bunch of other
sites like that that already have Creative Commons repositories
of strain names and like their parents listed, and then we're
putting it in Gephi, which is a data visualizer that does the
network graphs, and you can build like these genealogy networks.
And so you can actually be like, okay, so all these strains are
in this cluster, so they're not very diverse, at least by
self-reported data, not always the most accurate, but then at
least it's what we've got, right?
And then we can take that and then be like, oh, but these
strains over here are in like a list like what Keegan's going to
go over, and oh, those ones are actually like very unique.
They're not in this cluster or they're not in our galaxy at all.
I think that's an interesting way to pursue that line of
questioning.
Ruth, you may want to go because I feel like there are so many
good ideas here.
Yeah, well, I just read an article and I posted a link to
it in the comments.
They discovered a new class in addition to terpenes called
flavorants, which are adding, you know, supplementing and
distinguishing the smells and they think the effects because
they said if you look across strains, you have plants with
very different, with similar terpenes are creating different
effects.
So this is yet another differentiator and we know that
they're finding all new, I guess, markers.
They're still trying to figure out how different compounds
create their effects and what are the important ingredients.
And, you know, first we start with cannabinoids and then we
moved on to terpenes and I've heard of flavonoids, but I just
heard about flavorants and it's just, I'll stop there.
I'll go on forever if I don't.
I found the first batch of COAs that had flavonoids on them.
We've been collecting Florida COAs, haven't parsed them yet.
We're moving so quick, it's hard to, right, that's why it's all
hands on deck and I love having your help here because I only
have so much time to even look at the data.
So a lot of the data goes unlooked at.
But we are collecting COAs from Florida and I have noticed that
some of, not all, but some of the tests do have flavonoids on
there.
So it's going to be a whole other suite of compounds.
We're going to have to think about how to collect and
standardize.
And then the other thought that goes in line with both Caleb and
Yasha's thought is that's an even better idea than looking at
the number of unique strains by month is somehow think of a
metric that encapsulates the diversity of chemicals you're
measuring.
I don't even know what it would be, but I'm sure there would be
some statistical, some statistic, which is basically, I don't
know, variance or something.
Maybe you just look at, but I don't know how you would do it
cross compound.
So maybe that's something for you all to kind of research.
You know, what statistical concept could encapsulate just
could we somehow measure just the total variation of chemicals
we're seeing on a month by month basis?
So that's a big concept.
So that Yasha, that and Caleb, brilliant ideas.
We'll have to investigate that further.
So I don't think we can do that today.
We may be able to off road with the strain names by month.
So we'll try to save time to do that.
And then actually final thought, and then Larissa and Candice, I
don't want to leave you out of the picture, so I'll let you
jump in.
But final thought is, Caleb, what's cool is I'll get you a
large data set today, but it's kind of lacking in data points.
So the data set we have today, it's got like strain name, total
THC, and that's pretty much it.
And when it was tested.
What you could do is what I'd love to do is augment data sets.
You would take this data set and augment it with your own strain
data.
And it's going to be imperfect, right?
You would love to actually have those samples tested for terpenes.
But I don't know.
I think any measure is better than no measure.
And so basically what you're augmenting with it would basically be
averages.
So you, for example, we've got blue dream tested.
So, you know, what if you augmented that with just the average
terpene values you've seen for blue dream?
So that's a great idea.
Yeah.
I know that I love your red ink.
So jump in.
Yeah.
Sorry.
There's so much to say about this.
I think it's a fascinating project.
I know that a huge number of flowers that are sold are not two
flowers that are sold as blue dream may have nothing to do with each
other genetically or through their compounds.
But what I do believe we would see is a cluster of samples being
nearly identical within blue dream.
And maybe those can be identified as, okay, let's call this A1.
And then many other clusters like that.
Listen, I would talk about this all day.
I'll stop.
But there's one more thing that a single strain may have slightly or
significantly different analytes based on its age and growing
conditions.
But I do believe that we likely have enough data through off the
shelf testing and open data that would be able to show what is a
single strain and how broad does it go within testing?
Thank you.
You're 100% correct.
And basically what you're working on is there's going to be error,
right, as soon as we estimate.
I mean, as soon as we introduce estimates, there's going to be error.
And the error may be non-negligible.
There could be strong biases.
There's a lot going on.
So what I would hope is if you say you were going to do that, would
love a large sample size because as we've mentioned, you know, the
law of large numbers.
But I don't know if that would necessarily get rid of any bias.
So the bias may be baked in.
But why would I even do that?
Well, I would just want basically just a rough idea.
So today we'll look at, like, say the top 20 strains in Michigan.
And, you know, wouldn't it be cool to just know just approximately what
is the chemical profile of these top strains?
Unfortunately, we don't have the actual terpene data.
It may not have been measured.
Those products were grown, sold, smoked, gone.
So we can't even measure them for terpenes anymore.
So what do we do when there's missing data?
The best we can do is estimate.
But once again, the bias and error may be so great, it may be not
worthwhile.
So good considerations all around.
But Caleb, you have some thoughts?
And then Larisa and Candice, I'll let you chime in if you want to.
Sorry to continue this rabbit hole, but I just thought maybe about the
missing data that the consumers may also not have that information.
And so the relevance for consumer choice may not be super high because
they may be making the decision based on the perception of the strain,
which is what we have the data of.
That's a phenomenal point.
I don't even know all the implications, but it's definitely a thing.
People definitely say they could go and ask for a blue dream.
That one's maybe a bit more standard, but something like a GMO, that could
be all over the board, in my opinion.
But anywho, those are just opinions.
We can get to the data here in a second.
But Larisa, you don't have to be put on the spot, but if you want to chime
in and put anything on the table for today, you're welcome to.
Basically we're talking about lab tests, cannabis data, and specifically I
have a big data set from Michigan to share with you today.
And you're also welcome to just listen in.
So just interrupt forcefully if you want to at any point.
But Candice, do you have anything you want to put on the table for today?
I don't have anything.
I think this is great, though.
Being able to pick a product based on chemical profile versus somebody
coming up with strain names would be a great future for patients and
consumers.
Yeah, exactly.
And I think that it harks back to what's the point of all of this?
Why are we on this whole rabbit?
Why are we down this rabbit hole in the first place?
Well, what data do we have?
We have often, like we said, just the strain name.
And if you go to the store, you're going to see strain names and the THC
numbers.
But as we've mentioned, what's more important and what we think is the
actual causal effect, right, it's not that the product was named Blue
Dream that it's having a certain effect, but it's actually the chemicals
you're consuming.
So that's basically what we're after.
And as always, we think from my economics training or schooling that
the better information consumers have, then they'll be able to make better
decisions.
And on average, they'll live happier lives.
So that's all.
And so that's why Copy Left Cultivores, Caleb, you're doing a really good
deed is by simply getting that information out there.
You should be helping people make better decisions, right?
Not everybody is going to look at the data, but the ones that are interested,
they should be able to look at the data if they want to.
But I didn't do the best job saying the mission, but hopefully you all have
your own missions as well, and this is in accordance with them.
But on that note, instead of me just being long-winded and speaking, do you
want to actually see the data we have here?
So that could be quite fun.
So let me share my screen with you.
So instead of just, right, that's what's fun here is instead of just talk,
talk, talk, we can actually look at the data.
So last week, we were fortunate enough to be able to see the data from
Massachusetts.
And today we're fortunate to be able to see the total THC numbers for these
products in Michigan.
And we've got a time range here dating from, here I'll print it out here in
one second.
It's roughly the third quarter of 2020 through the end of 2022.
Don't have a ton of data, but we basically have an indicator if it's
medical or adult use.
We know which lab tested it.
Everything I believe is marked.
Actually, there's various types of categories.
And so this is in fact a place for further data cleaning if any of you all
are interested.
But...
I apologize, do you mind if I interrupt really quick?
Please.
So two quick things.
I actually have to jump off in a minute.
I will be looking for this video later.
And just so you're aware, total THC in Michigan is defined as.877 times THCA
plus delta 9THC plus delta 8THC.
Just so that when you compare it to other states, that's how...
Can you say that one more time, please?
So it's decarboxylated THCA plus delta 9THC plus delta 8THC.
Okay, so it also has delta 8THC.
But that's so rare that it shouldn't make any difference.
Yeah, from my understanding, that one was usually less than.1% when we
observed it.
So that will buys the numbers up.
But just a hair.
But that's a really good note.
And that's why as a data scientist, it's worthwhile to wear many caps.
And one of the caps you want to wear is historian slash...
Well, you are a researcher.
But you want to be digging through all the testing regulations and figure out
things like that because they can have big implications.
But good find, Yasha.
But I'll move quick here.
But long story short, we've got data from the end of June 2020.
And then the last observation was the beginning of 2023.
So I'll start limiting the time range further along.
But real quick, really just going to focus on, of course, total THC today.
So I'll leave all the cool terpenes to Caleb.
But what can we do with this limited number of data points?
So once again, I think we can go pretty far with this.
So what do we have here?
We had 80,000 samples that were tested in this time range.
And let's just start visualizing them.
So just have tons of visualizations for you today.
So we'll just start going through them one by one.
Whatever reason, the plotting doesn't take my style right away.
So here's where we were in 2020 with about a thousand tests per month.
And you notice while it has been turbulent times in the cannabis industry in Michigan,
Michigan has seen what I would say is substantial growth over the past two and a half years.
And we still need to know what's going on this year.
It's 2023.
But we'll see that data when the time comes.
But this is what you want to see in a market.
This is, that's growth.
If you're a lab in Michigan, that's a lot of revenue for you.
And then as always, we say that the number of tests is essentially a proxy for the supply.
Once again, it's an imperfect estimate because batch sizes may be changing.
Maybe they're still producing the same amount of cannabis, but they're just making it in smaller batches.
But if you go under the assumption that batch size is staying the same during this time period,
then you would think, OK, tests are growing.
Ruth had mentioned medical cannabis, and we can actually break this into two pieces here.
The adult use versus the medical.
And I'll let you all make your own interpretations of this.
But what I interpret this is, right, they're both around 500 tests per month in the beginning.
And I think maybe the medical and adult use, right, combined were just filling the entire supply of Michigan.
And maybe there was kind of some overlap.
Maybe some adult use consumers were getting medical.
Maybe some medical consumers were getting adult use, maybe a little bit of crossover.
And so I think what you see is you see the rise of adult, the rise in the market, and that's mostly going to adult use.
And it looks to me like maybe the people that there were some people buying medical, and they may have transitioned to buying adult use.
But it looks like there's, you know, may kind of reach almost like a steady state there of, you know, around 500 or so medical tests per month.
So that's kind of my interpretation of this is there is basically like a baseline medical community.
But maybe, you know, in the early days, you know, maybe some people were seeking adult use, but they were classified as medical.
So that's my interpretation of it. Do any of you want to chime in on your thoughts?
Yeah, I. Yeah, you see this exact same pattern in every state that opens up. And this is a little misleading because in every state you have medical comes first.
Medical predates for usually a couple of years and medical use takes off.
And then as soon as rec use comes in, medical use starts to level off and then it declines and it essentially dies.
And the adult use ends up essentially killing off medical because all the focus and resource resources switch away from medical.
And it's very unfortunate. But it's I mean, it's the reality.
And what's interesting here is I have exact same graphs on sales and it looks identical.
So in this case, yes, the tests are very good proxy for total revenues. But again, you see this exact same picture in every state.
Good, good point. I would just like to say, you know, I wouldn't count the medical market out yet.
You know, it's maybe still about, you know, a fifth to a quarter the size of the adult use market.
So anything that large is non negligible. And this is actually I guess more than 500.
It's between 500 and a thousand. But Ruth, unfortunately, I think you do speak some truth in that you're right.
If, say, you did get into business to produce medical cannabis, you know, that would be, you know, taking taking a hit.
But. But yes, I went I'm going to have to research more about the licensing, because I wonder, is it possible for a license to produce both medical and adult use cannabis?
Or do you have to produce specifically for one type that varies by state and the laws have changed over time.
And early on, they said to growers, you have to you have to designate which plants are medical and which are recreational.
And they kept them separate throughout the pipeline. So the supply chain. But I think there's intermingling.
You also have differences by state with big implications. And for example, in California, what you see is the people involved in medical tend to do everything medical.
And they're very different companies in organizations from people involved in rec.
However, in other states, most other states, as I said, you start off with medical and the first licensees for medical and then the medical licensees get priority when they open up to adult use.
So the medical licensees are also adult use growers and dispensers.
And this is kind of creating a problem because a new state, you have a lot of organizations go in there and the money is in adult use and they don't really care about medical.
But they go in at medical in order to get the priority for when they open up to adult use.
There's a huge amount of gaming going on.
But there's there's huge implications for, as I said, for resources available for medical users and adult use users and essentially all the money is in adult use.
So the resources very quickly get focused and shift over to adult use.
And one last thing is I believe that when they did the Booker Schumer Booker Schumer Weiman proposal or whatever, this was kind of an iteration back on what the national bill for for for legalizing cannabis federally looked like.
My understanding is that whole bill, however long it was, didn't include the word patient once.
So even federal government isn't really focused on that.
And my belief is that all medical use is going to end up being pushed into the pharma industry and the pharma model, which personally I'm no fan of.
But I think that's where it's going.
It's definitely something that's going to have to be addressed at some point, Ruth, because, as you pointed out, this has big implications.
Because you're kind of like yo yoing around these medical patients and consumers.
The problem is that if you look at and this would be a very interesting analysis is if you go and if you look at all the COAs that are labeled for medical and that are labeled for adult use and you compare them, the adult the adult use is focused on high THC cannabis.
But the medical have much more variety and there's much lower THC and there's higher ratios of CBD to THC.
And there's just and so the problem is, is when you get pushed over to adult use, you lose all that variety that the medical users need in order to address a particular conditions.
Actually, let's go off-roading because Ruth, you just raised the most one of the most critical, one of the most interesting things.
So I'll have to maybe circle back for some of this analysis on on labs for for Yasha's sake because I'm sure Yasha will find this interesting.
But actually, Ruth, we can once again.
It's just a one hour meetup after all, so we can only get so far.
So, you know, don't take my analysis as gospel.
But what we can do is.
Chalk out how you could actually begin to analyze that because remember, we've got strain data here.
We have total THC here and we have medical classification.
So we can see.
Are there, you know, more or less medical strains, maybe relative to the number of tests.
So we talked about diversity in strains.
Well, it could vary between medical and adult use.
And then, too, we can check out the total THC numbers.
Actually, let's do that right now.
So so first, before we get into the conditionals, here's just the unconditional average THC.
And remember, Yasha's point that this includes Delta eight to.
OK, so let's put the medical on the side burner for now, but this is we'll do some off roading because it's more fun anyways.
But here's the total THC. Cool.
We've seen that distribution before.
And just the only note is the 99th percentile is actually similar to what we observed in Massachusetts.
The mean actually may be similar to but maybe slightly higher.
And actually, this is just the.
When the first condition we've added, but here's the distributions between medical THC and adult use THC.
And if you look at it's actually it's actually kind of interesting if we look at year by year.
But this this one is for twenty twenty two.
And so you can actually do a test to see if they're statistically different.
But I think it's just that we have just a giant sample size, so it's maybe easy to see the conclude that things are different.
But it could be that the difference may not actually be that much.
Can you get it? Can you get a count? And also, can you do CBD instead of THC?
We don't actually have CBD here, unfortunately.
I wonder if we could do that one in Washington.
But here I'll get you the count for them real quick.
I think we have ten thousand medical samples and thirty three thousand adult use samples in twenty twenty two.
That's a decent percentage for the medical.
So I'm surprised that they're that close.
Well, Michigan's are super interesting market.
Michigan's went a mark to this phrase gets used a lot these days that people are sleeping on something.
Well, people were sleeping on Michigan in the sense that it's not your traditional East Coast market.
And it's not your traditional West Coast market either.
Like the the West Coast markets like California, Oregon, Washington and Colorado.
I mean, I think those markets are quite mature at this stage.
And you kind of saw like some pretty like like there are a lot of companies there, but there's definitely some big, big players there.
And then the East Coast is way as much different because the story there is just regulations.
Right. Like from my understanding, really competitive, maybe to get a license like maybe in Massachusetts.
Super difficult to get a license in Florida.
And then, you know, the difference between the left coast and the right coast, the east and west, the West Coast is generally unintegrated.
You're allowed to integrate, but you're not required.
And in almost every case on the East Coast, you're required to be vertically integrated.
So on the on the West in Colorado, California, Oregon, Washington, Michigan, you have hundreds or thousands of licensees.
Whereas in the East, you only have tens of licensees because you you end up with a few large companies because they're they're required to be vertically integrated.
And that creates a hugely different dynamic in all respects.
And exactly. And then so Michigan just didn't fit either of those models.
In fact, its history goes back to I think they originally there was a lot of small time growers who were maybe were doing mostly medical.
From my understanding, there was like just a lot of medical plots, you know, like, you know, the hundred hundred plants or what have you.
So I think. I think your medical thing was there first in Michigan, and it's had a long history.
So it's not like people there are inexperienced.
So you have a bunch of highly experienced growers that were starting at a lot of small businesses.
And actually now, now is a good time to show this to like, for example, like, look at the number of labs in Michigan.
Like, there's there's 24 labs in Michigan, and it's just not really, of course, like they're dominated by a couple of them.
But, you know, like I think in Washington, we're down, you know, there's maybe fewer than 10 labs now.
So it's like I said, me included, I was just sleeping on Michigan. They just.
It's a I mean, we saw it earlier with the the this chart here with the rise in adult use.
It's a pretty it's a pretty vibrant market there.
And for medical, too. So it's a long story short. Don't don't discount the market in Michigan.
OK, so where were we though? Oh, yeah, there is.
Let's get back to the strains instead of just talking so highly about Michigan.
OK, so we're looking at the THC. We noticed that there may or may not be a difference between THC with adult use in medical.
And my hypothesis there is maybe still either the overlap or here is actually my better my better hypothesis.
The labs don't know how to handle medical. Right.
So it's you know, they're they're basically just the labs, I think, are just testing maybe everything the same.
But actually, that's not a really good, good hypothesis.
I just realized because the medical growers would maybe select lower THC varieties.
But OK, I don't know. That wasn't a very good idea. So maybe I'll move on to the next chart here unless anyone else has any thoughts, comments, questions.
But here's here's just one chart that would just be pertinent to show once again.
This is this is something that's come up a lot in prior meetups, so I don't want to spend too, too much time on it other than then pointed out.
And then I kind of want to move on to the strains.
But just, you know, here's just the average THC in Michigan around the 21 percent.
And you see some labs testing higher than average and some labs actually testing much lower than average.
And I actually is left for there's left for.
So basically, I just wanted to make one comment here is basically if you look at this chart here.
So keep in mind. So basically look at these two charts side by side.
So you've got the average THC by lab and then you have the total number of lab tests.
And so what you see here is. You know, lab lab one and lab nine, they do have large market shares, you know, and they are testing quite above average.
But what's interesting is lab for you know, lab for has a large market share in their testing, you know, just about average.
So basically, my comment there is there may be just a lot of cultivators out there who just truly want a good measure of their products.
You know, they're just like, OK, like, you know, enough is enough of the high THC numbers.
I actually just want like a good measure of what I'm growing.
So so I just kind of wanted to point that out that this one lab has pretty much.
Like their average pretty much matches the average in the market.
And remember what we were saying about sort of the law of large numbers.
And this is like the rule about the consensus is let a bunch of people measure something.
And then the average is kind of close to the true average.
So so basically, in my opinion, you know, the closer you are to this red line, which could be biased, then, you know, the closer you are to being accurate.
And so I don't know, just wanted to to hark on a good job for lab for for being close to accurate and have a high market share.
So, anywho, back to the strains, though, because that's sort of the more fun topic, because both Caleb and Ruth, you had pertinent questions and statistics that you're after there.
OK, Caleb, this is where.
I asked chat GPT to write me a quick function, but this is just to get the job done for today.
This is in no way a substitute for what you're doing.
So basically what the problem here is, is if we look at the product name.
It is wild. You know, you've got Buds by Sensei Star, you know, triangle, mints, Buds.
This one's got underscores in it. 100 GMO, crash or bulk flower.
Ideally, we could identify the strain name out of this. Right. This is GMO, crash or probably, you know, this one's probably pineapple express.
So on and so forth. And it looks like I even made a mistake here because I think our kid archive is on our list, but it looks like this one's actually Mac Bang.
So long story short is just getting the strain name out of the product name is a non-trivial task.
And so this function will imperfectly do work for today, but we've we've had whole meetups in the past talking about how how in the world are we going to get these strain names?
Because, Caleb, that's kind of the heart of this is right. You're sourcing like known strain names, but there could be unknown strains that are out there that you can identify.
But you know, you may have to identify them from data like this, which is, you know, an absolute mess. You know, what if nobody's documented GMO skittles before?
Like, why would we want to leave that undocumented just because it's got a little bit of noise in the product name?
So you all move quick since we're really have so much time. OK, so long story short, going to just add the the strain name and it's going to be imperfect here.
But you can see that this is at least better than it was. So dinosaur food. That's a cool one. Never heard of that strain before. Oreos, Groundhog Day.
So so this is just a way that we can start accumulating strain names because that's a challenge we've had is just finding like an original way to get strain names.
But why why are we even doing this? Well, check this out.
Once again, this is going to be imperfect, but you can start to just count the number of strains.
And these are some of the classic strains that we see over and over again. Right.
Wedding cake. Just I don't know what it is about it.
I think it must just be really easy to grow, but it must also be a popular seller.
So, Caleb, this is why I was saying that if you were able to augment your terpene data.
Like that's what you could try to explain. Like, why are these the top strains in Michigan?
Once again, as in like I'm going to use strains in quotation marks because, you know, what you know, what is a strain, so to speak.
Great. See, here's the archive, which I think is actually the Mac.
So long story short.
This is what's growing. And here's where we can get really cool with it and maybe even try to go off road real quick.
Bye.
Here, in fact, while I'm talking about this chart, I'll show you basically how I code these days.
So basically how I code these days is right. I've got it to do here.
We want to look at the, you know, adult use versus medical top strains.
So, you know, theoretically, I could just don't let me bore you to death with this.
But basically, I just go to chat GPT and I would just say something like, can you visualize the top or the average brutal THC by top strains for medical products versus adult.
Let you do medical products for now.
So chat GPT will be working on this one, and then we'll see how close they how close they get.
So long story short.
Here are, you know, the top strains in Michigan.
And the one thing I would like to point out to you is.
You do see some strains of course, you know, testing well above average.
Right. So, you know, cush mints GMO.
Even wedding cake, you know, they're, they're probably significantly above average.
But what's, what's cool is you actually see some here like like remember we talked about blue dream earlier, you do see some strains that are, I mean blue dream is significantly.
Probably statistically below average.
But, you know, it's a good two and a half percentage points, actually maybe even maybe even maybe couldn't be close to 3%. Oh yeah, so the average is about 21 and a half percent.
So it's almost 4% lower in average total THC on average than the other strains and an orange creamsicle pure Michigan.
And this one Franklin fields are also all, you know, a good bit below average.
So, this is maybe an interesting signal that
total THC may not be all there is to the picture. Right. If it was that no one would ever pick blue dream. Right. Blue dream made it on to the top 20, despite having a below average total THC.
So this is Caleb, this is an opportunity for you is why is blue dream a top seller.
People would love to know why, you know, why is pure Michigan, a top seller.
This is what people are trying to figure out right everybody's getting plants in the ground. They want to know what plants are going to be successful.
You know and, you know, consumers to rate.
You know, it's fun to know what all the different strains there are in the market.
Okay, so real quick. Let's just see real quick if Chachi PT was able to make any
wasn't a they weren't able to do it for us. So let's see if real quick, if you have just a quick five minutes to add.
I promised we'd go off road. So let's see if we can't find the top 20 medical strains and their average THC.
Okay, so we're going to need to do something like this. But first, we want to make sure that we're only getting medical products.
So, so, so let's just try this. So, and once again, when you go off road, you know, we may spin our tires, but it may work out.
So let's see medical.
We'll just call this medical. So let's just see if this works.
Okay, so we have 8000 strains. Let's just take a look at this and just see what's going on with this.
Okay, so we've got products here.
Got the strain name. Okay, we should just be able to more or less just copy and paste the, the rest of this code.
And then we can, you know, change it to medical, and then this should more or less work. And we did it without Chachi PT. Okay, so this is medical here.
And then basically, I'm just replacing some sample with medical.
And then that should do the trick. So over and then I'll just change some of the titles here. So overall medical, medical,
overall 99 percentile medical THC, average to the top 20 medical strains.
And then medical, the top 20 medical. Okay, and there we have it. We've hopefully answered a brand new question here.
Oh, no.
The strain counts as this last thing I need.
Okay, one second. We may be able to do this.
I would love to be able to do this for you. Sorry if I'm boring you.
Cross our fingers.
And we now know the top 20. Look, I misspelled it. So we'll just bear with that for the time being.
So check this out. Here are the top 20 medical strains.
And check this out.
Here, Ruth, you may be interested in this in Caleb to walk, you know, what could potentially explain the difference between the why medical patients are favoring certain strains over why adult use patients are favoring certain strains.
You see wedding cake and gorilla glue still high on the chart.
Orange creamsicle has gone way up. Blue Dream has moved its rank up.
And you see this, these two other strains that are below average THC Russian snow and batched, which I've got a feeling I botched that strain name.
So that's, that's wild. And then check this out. You also see these two strains. The kush mints was on the top 20 before.
But check this one out. You now have the S, the S the, what's it called SFV OG, the San Fernando Valley OG testing at a whopping 27% total THC.
So that's, that's wild right there.
But, but I, I may have gone a little over and want to be respectful of all of everybody's time. So I may go ahead and stop presenting, but we'd love to, to get any of your thoughts there.
Did you find this analysis interesting? Was there anything that comes to mind? Do you see any fruitful avenues for further research? Love to get your input real quick.
If anyone wants to chime in.
You're looking at THC and I agree that's important, but there's other aspects there too. And so I think that if you were to say, well, why are these so popular? You need to dig past THC and that would probably explain it.
Help explain it.
Yeah, I've had similar thoughts with that too. That was kind of where I was going is it's a really nuanced question. Right. And so there's a lot of factors and then there's the factors that are like quantifiable.
And then there are some pretty non quantifiable or hard to quantify elements like social elements. Right. We've got like, I did Lil Wayne talk about gelato in a song. Right. I mean, that just like totally skews everything.
So there's a lot of layers to that question, but I like the avenue. I also think price, if we could get metric price data from that same timeframe, and then ratio the strains based on the average price in that timeframe, we would get a lot of great information on whether consumers were simply making an economics decision.
And those were like easy to produce and market affordable strands.
I love the ideas and this is what brilliant statisticians have fun at lunch talking about. And what you're basically talking about is, what do we pack into X, you know, what's our explanatory variable.
We're trying to explain, in this case is just number of tests. And that's our proxy for popularity.
How do we explain that right now are only explanatory variables THC doesn't seem like that's all there is to the picture.
This is why I would love to, you know, augment the average terpene value see if there was matter.
I love Caleb you had the idea.
Add price.
If I was an economist I should be. I should have thought of that one.
Right. Everything's a function of price.
Well, actually, price factors in, but actually, just put your that you see why I'm not an economist, but the long story short.
Oh yeah, then the final point you had, what if a famous celebrity talked about it, and that's basically that is an explanatory variable, but it's how would you quantify that.
So that's, that's kind of what you could.
Maybe have fun about it right. You could actually maybe think about some way you could actually quantify that, like you could just have a counter like how many times has this strain been referenced in media.
You could look at sales or tests over time. And if you have a suddenly a strange spikes, then probably there was some event, like a mention.
But this is once again imperfect but like I said, it's a starting point where you could do something like, like Google Trends, you know, just try to see if you know blue dream or gelato is trending.
The data spread is infinite you can, I love this about the data sciences, this is a great example of how it can go infinitely, we can just keep crawling for more and more information.
And my mind is like, oh yeah we can get hashtags we could scrape social media, and network that out and have influencers have different like rating ratios for their levels influence and other things like that.
And then we can just try to gather and manage and then mesh into this.
So it's basically, you should have some sort of like hypothesis so maybe that's what you should all brainstorm about is, you know, what could potentially be a reason to explain the these popular strains into then Caleb you had the idea like oh, maybe it's price.
And then you go try to get the price data. So it's, it's basically you don't just go off to get data for data sake. You first get your hypothesis, then collect the data, and then test your hypothesis.
So, so I love it. We've got a few hypotheses to test right we can get price data, maybe some sort of popularity measure, and then I'm going to be thinking of my own hypotheses for, you know, why in the world is medical, like why are the medical popular strains
different.
And then, hopeful, most importantly, let me just hear. I'll just give you the rough link and you'll have to dig down. It's basically season three.
Number 132, but the data is there on GitHub. So I encourage you all to get this data set into your hands and take a look at it yourself.
You know this was just the first slice and dice of the data, but hopefully there's something I missed that you could find. And once again, augment this with other data sets and that could open up a lot of doors.
On that note, thank you all for coming. Thanks for bringing your brilliant ideas, some really really really good ideas today. Thank you immensely for helping advance canvas science.