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Well, it's a little bit of an impromptu meeting this morning.

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So and maybe brief so maybe just a quick 15 or minute 15 to 20 minute update.

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And then what we'd like to announce is on Saturdays, I think we can start doing a cannabis

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data science Saturdays statistics.

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So that's when we can really get into the meat of things.

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So I'll be putting that on the meetup agenda.

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Just to let you know, today, I am here at MJ BizCon in in Las Vegas.

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So yet again, it's one of those just ad hoc meetups.

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But I thought I could at least talk with you about what the event events yesterday was

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the Science Symposium.

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And then we can just talk to him stay to science here for a minute, and then really get into

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some real interesting things on Saturday with Saturdays statistics.

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So so real quick, Eric, you're new to the group.

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So just to kind of throw you on the spot.

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You wouldn't mind maybe introducing yourself or maybe letting us know your background and

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your angle and what you may hope to get out of the group.

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Hey, I'm Eric.

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Like you said, I am new to the group.

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Basically my background, I've done everything from like finance to actual security.

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I've been I guess in tech for the past, let's say 15 years, different aspects.

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I was a network administrator.

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So I worked mostly with hardware software.

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Then I transitioned from that to development.

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And now I've been doing data analysts at a current FinTech company in New York City.

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And I've been doing that for the past year and a half, give or take.

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So just new to data.

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And I actually didn't even know I worked in the data field.

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But I guess basically, all I thought I was doing was just reporting.

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So like my company has me doing like the business to consumers like marketing.

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And basically, I do the reporting for our entire organization that's located here.

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Texas is our headquarters.

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But we do basically if you pay on a home or a commercial real estate property, you're

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probably paying your rent through us.

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So I've been doing that for the past, like I said, year and a half, give or take.

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Also, just bringing in these headphones just to get a bit better sound here.

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No problem.

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Well, it's awesome to have you in the group.

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So what interests you about the merger of cannabis and data science?

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Well, obviously, it's a growing field, because I actually used to invest in certain stocks.

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And it's been obviously big for the past couple of years, especially with the legalization

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of it across many states in the United States.

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So just, you know, like, I'm new, like I told you.

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So I guess I'm still trying to learn everything that's not just with cannabis, but many other

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sectors.

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Okay.

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And you said your background was in cybersecurity.

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I did cybersecurity.

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But that was years ago.

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That was maybe early 2012.

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Okay.

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And can you tell me how you got into data science?

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So like I said, I started doing basically networking.

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So we did firewall systems.

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I worked mostly with hardware, creating servers, doing the whole virtualization.

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And from there, I kind of transitioned into as a web developer or a software developer.

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I used many different, so I used like Ruby on Rails.

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Obviously it depended on where I worked and what technology stack they used.

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So I went from that to like React.

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Then they threw me into learning SQL.

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So I did a lot of SQL stuff and Excel.

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I actually never needed to use Excel, so I didn't even know how to use Excel, but now

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I do.

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Yes, you'll be surprised how often you come across companies using Excel these days.

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But that's, I've heard a programmer say that that's often a prime opportunity for development.

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But anywho, well, I'll tell you about myself.

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So I started a company, Canlytics.

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And so we principally got into the space to help out laboratories.

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So we have experience building laboratory information management systems.

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So that may be up your alley, software.

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So that's how we got into the space.

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And we saw that there was a big need for statistics and analytics.

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So we're skilled at that as well.

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So we thought we could maybe share our comparative advantage with others.

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And statistics is something that we can do simply and easily.

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So we thought there was a shortage, so we thought we could provide some supply of statistics.

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So you do have any experience with stats at all?

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That is actually quite interesting.

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While I don't have experience in the cannabis sector, like I said, currently right now,

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what I do for the company that I'm working at, I do all the marketing material for them

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on.

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So I take the statistics of basically our marketing campaigns.

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And what we're trying to do is increase our credit card adoption fees.

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So I collect data for obviously every month that we send out.

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It's over like sometimes like 2 million emails, because we have many residents on our platform

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that pay their rent via credit cards, checks, cash, money order, or now cryptocurrency.

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So what we do, our company, we actually make more money when they use a credit card.

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So what I'm doing is I generate these reports from the data from Microsoft SQL, but they

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want me to present them basically in like spreadsheet format.

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And I use that in a dashboard to give to the marketing manager so he can change his marketing

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strategy so we can have a higher credit card adoption rate across, you know, our campaigns.

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We're a big fan of showing the data.

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So your managers may like this.

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So have you ever presented any figures or charts or graphs?

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Yes, yes, I have.

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Okay, so may I ask, what's your favorite way to go about creating charts or graphs?

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So mine's with Python, but it's that's just my tool, but which?

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Yeah, it's mostly Python.

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Oh, interesting.

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Awesome.

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We also do use here, they have several different tools that have dashboards.

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So we have developers and they sometimes I don't even get to choose that.

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They just tell me to basically give the data to our developers and that they're going to

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create a dashboard for it.

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So it kind of depends on what team is requiring what data and at what point.

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Sometimes we use Tableau or there's the new, I guess, like Microsoft BI.

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So it actually kind of depends.

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And like some people I know, what is that they use like Panda Pandas or something like

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that.

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But I haven't I have no experience with that.

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Yes.

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So we can show you a bit of the work we do, so we'll use Pandas to wrangle data now and

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again.

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So if you want some examples of some of the code, you should check out the cannabis data

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science repository.

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So they can put the link in the chat.

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So we'll have all of the work that we've done over the past several months.

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We'll see how we use Pandas intermittently to read in data to clean the data.

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So there's a lot to be done there.

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Well, thank you for that.

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And essentially I was thinking, yeah, so essentially maybe the meetups here on Wednesday can maybe

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be a bit more of a, you know, just a back and forth meetup.

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And then on Saturdays, we can really dive into.

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So if you'll look at the code examples, we, you know, that that so that way on Saturday,

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that'll be the more program intensive statistics heavy day.

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And then Wednesdays, we can just talk about cannabis data science and what people's interests

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are, the latest developments in the field, you know, what have you.

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So there or we can mix it up.

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So so I just thought I would put that by the group and see what people people prefer.

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But today it just happened by happenstance because I'm here at the convention and it

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actually really kicks off here at nine o'clock a.m. Pacific Standard Time.

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So I'll need to conclude here in about eight minutes or so.

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But so normally we do a longer session where we really dive into statistics.

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But unfortunately, due to circumstance, just have to keep it short today.

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But the plus side is I can fill you in about some of the things happening at MJBiz and,

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you know, some of the topics at hand.

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So for example.

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One of the big things going on right now is the hopslee in virory.

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So this is a big risk to everyone in the industry.

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Right.

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So you've got a bunch of.

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Right.

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Oh, we've got a new guest.

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But but I'll really pin these things up next time.

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So, you know, some of these interesting developments.

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We've got Miguel.

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So welcome to the group.

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So we're doing a bit of an impromptu meetup today.

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So welcome aboard.

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Happy to have you.

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And essentially thought I would tell you about we've done this kickoff Saturday statistics

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on Saturday.

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So would any of you have a good time in hand that you may be interested in doing statistics

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on Saturday if that's something that any of you are interested in?

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Eric or Heather.

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Oh, Miguel.

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Oh, cool.

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Well, I was thinking sometime in the morning.

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So we could stick with the same time.

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Eight thirty a.m. Pacific Standard Time.

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And then that would be eleven thirty a.m. Eastern Standard Time.

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If that would work for everyone.

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That works for me.

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Also, so then we can rendezvous and.

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Awesome.

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Oh, welcome in.

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Welcome back.

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So today we're doing an impromptu meetup from MJ Biz.

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Then on Saturday, we can get back to essentially we were merging economics, economic theory

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with some empirical data and seeing if we couldn't estimate some models as Heather can

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attest.

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We weren't really able to estimate one of the economic models we had.

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OK, luck with the second.

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But, you know, it led to a lot of doubt.

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Right.

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So, you know, if the economic theory doesn't pan out in one case, yeah, it just makes you

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kind of wonder.

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So long story short, we're going to revisit this on Saturday and maybe extend the data.

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So we were looking at Massachusetts and we could potentially add a couple of new states

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such as California or Colorado to the mix to sort of do a comparative analysis across

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the states.

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And so, Eric, I believe you said you were doing state by state comparative analysis.

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And if so, are there any particular states that you're interested in?

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No, I wasn't doing a state by state analysis.

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I said that I was working on that was more for our own company, not a Canada sector.

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OK.

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So, long story short, we'll really just look where there's data to be found.

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So that's what we'll really kick off on Saturday.

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And then I can report back to you and fill in my notes to you about, you know, all the

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developments here at MJBiz.

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So that way, you know, you know, OK, what's happening here in the ground floor?

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What are the latest topics at hand?

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What are people talking about?

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So a big topic at hand these days is quality assurance.

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So just to give you a brief history here in the last few minutes of quality assurance

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in the campus industry.

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So as you know, so essentially things really kicked off right in 1996.

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So this was when I was a wee child.

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And so this is when California permitted medicinal cannabis.

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This went on for, you know, not much change for many years, for a decade or so.

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And then in 2000, really when things really started moving quickly was in 2012 with the

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legalization of cannabis in Colorado and Washington.

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And so that's when, you know, stories started making it into the news.

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There is the, you know, the cannabis tourism in Colorado.

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So this is when cannabis really started to become mainstream and get onto people's radar.

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Well, it's an interesting story because you can almost tie it to this obsolete and by

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road.

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So as you know, cannabis is proliferating, right?

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You're growing the crop in this monoculture and, you know, you're inevitably going to

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introduce viruses.

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Right.

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And so these are can be impactful on agriculture.

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So the example given is the virus that wiped out the Roe Michelle banana.

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So they're not inconsequential.

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So this virus cropped up and it's proliferated.

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And, you know, this has driven a lot of concern by producers.

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And so this, I think, may have been not the reason, but maybe a factor towards, you know,

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the movement towards quality assurance.

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So they were seeing the need to, you know, start testing for microbes and, you know,

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started making sure you've got a clean facility.

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So around 2015 or so, you start seeing the first, you know, testing labs and you just

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see, you know, the development through 2018 where, you know, more and more labs are coming

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online and I think there's just wide variance in how everyone's doing things.

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And then really through 2018 to 2021, there's been a lot of progress where the industry's

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really come around where it's, we're finally seeing that, okay, you know, we're really

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seeing the emphasis on good manufacturing practices, quality control slash assurance

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programs and good laboratory practice for the labs.

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So there's still room for development.

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I'm not saying we're there.

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So for example, in the lab space right now, people are interested in testing for heavy

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metals in vaporized products or concentrates or flour or what have you, edibles.

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But there's a lot of development that needs to be done there.

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So from what they can say that it's not, you know, it's not as precise as would be needed

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for, you know, production style quality control testing.

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So there's still work to be done, you know, particularly with heavy metal testing and

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really across the board.

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But, you know, everyone's moving in that direction.

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So I think that's, you know, a brief history of, you know, the quality control and assurance.

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And so that's, you know, just a brief summary of yesterday.

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I'll flesh it out and perhaps introduce maybe a first writing, like a first blog post or

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a blog post for the group.

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But you know, today was a bit more of just a talk.

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So you know, now I'll be, you know, heading over there into this mayhem, you know, that

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is MJ Biz.

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And so I'll report back and I'll see you all at 8 through D a.m.

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Pacific Standard Time, 1130 a.m. Eastern Standard Time on Saturday.

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And we'll do some statistics.

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And so that way, you know, we can really sit down.

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We can, we'll fire up Python so you can follow along, learn some pandas, we can create some

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figures.

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And for everyone, we can always just talk Canvas, you know, Canvas data.

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So that's just here to have fun.

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So anywho, hope you all had a fun time, even if it was short and impromptu and ad hoc.

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But until next time, I hope you all stay productive and I'll see you on Saturday for Saturday

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statistics.

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And I look forward to talking with you, Eric, Heather, Miguel and everyone else.

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And I've got to dash.

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So I'm going to go ahead and end the recording here.

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It's been it's been fun.

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So thank you all for attending.

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And then we'll really dive into things on Saturday.

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Thank you.

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Take care.

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Thanks, Miguel.