Pybites Podcast

#163 - Andrew Farr: Fascinating Python Data Projects and Improving 1% Every Day

Julian Sequeira & Bob Belderbos

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Join host Bob as he sits down with Andrew Farr, a seasoned data engineer, to explore his career trajectories, triumphs, and challenges.

In this episode, Andrew shares his recent transition from the US to the UK, landing a new data job, and the daily grind of becoming a data engineer.

From adopting a growth mindset to honing his Python skills, Andrew reveals the secrets behind his success. Dive deep into his passion for data analysis, content creation, and the importance of self-promotion in the tech industry.

But it's not all about code. Discover Andrew's diverse interests beyond the screen, from photography to historical conservation projects. Join us as we uncover the importance of continuous learning, non-coding activities, and the encouragement needed to pursue your dreams in the world of tech.

Tune in for invaluable insights, practical advice, and a dose of inspiration to fuel your own data journey.

Chapters:
00:00 Intro snippet and music
01:00 Andrew Farr intro and win of the week
02:25 Experience of new job
03:18 1% per day improvement compounding
03:56 Only compare to your yesterday's self
04:36 Python journey and mindset
07:08 Always be coding + PDM challenge mindset
09:00 What fascinates you about data?
10:32 Some of your data projects (link with history)
12:25 Sharing work and current projects
14:07 PDM ad segment
14:33 Newsletter and consistency
15:34 How do you come up with interesting ideas
17:30 Critical thinking and the data analyst mindset
19:10 Importance of online presence for a developer
20:05 Does it become easier over time?
21:16 Additional mindset tips / selling yourself
23:15 Influence of non-coding skills
25:07 Book tips
26:42 Final shout-out / piece of advice
27:51 Wrap out and outro music

Andrew's LinkedIn and newsletter

Books:
Elizabeth's Spymaster
- Data Engineering with Google Cloud Platform

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Ad segment: PDM, become a more capable and confident developer in 12 weeks 💪 - more info

Sure. So everything that you can reach through my GitHub, through my LinkedIn profile, I try to make sure that that stays purely python and data related. So there's links to my GitHub repository on there with the sites. I am currently working on a chatbot of sorts for autistic employees like, you know, because a lot of autistic people don't really communicate well with. With individuals. So I've been doing a lot of research personally on autism and how to better, best implement some kind of technological strategy for them in the workforce. So that's one of the projects that I'm still working on. Hello and welcome to the PY Bytes podcast, where we talk about Python career and Mindset. We're your hosts. I'm Julian Sequeira. And I am Bob Baldebos. If you're looking to improve your python, your career, and learn the mindset for success, this is the podcast for you. Let's get started. All right, welcome back, everybody, to the Pibytes podcast. This is Bob Eldeboz, and I'm here with Andrew Farr. Andrew, how are you doing? I'm doing well, Bob. How are you? Yeah, I'm great. I'm excited for you to join the show. We work together in PDM. You have making leaps with your python skills and recently landed a new job. So I'm excited to talk about that, about your journey data mindset. But yeah, maybe. First of all, can you introduce yourself to the audience and if you have a win to share of the week, then more than welcome to do so as well. I'm Andrew. I was in PDM about just. I graduated just over two years ago, I believe. Now I just completed my first job as a data engineer with places for people, a company here in the UK that's after moving to the UK from the United States about a year and a half ago. So, been enjoying the ride as it's been coming. So fantastic. Yeah. Like two changes, right? Moving back and getting the job. Yeah, many more changes to come, too. Yeah. So does that count as. I guess that counts as the win, right? Or maybe something more specific. Yeah, no, that definitely counts as the wine or. Python has been a journey. So every day is a win and my world. Yeah. Awesome. So can you tell us a bit what you do day to day in the new job? Yeah, of course. So right now, I've been doing a lot of documentation because the company is switching from a legacy system into Google Cloud platform. So I've been trying to wrap my head around that system and how it's going to be implemented in Google Cloud. Been doing some documentation or rewriting the documentation, performing daily reports, fixing some very interesting UTC errors that pop up. Yeah, I'm still really new and still really green with the company, so I don't really get too into the details of the data engineering world. But every day I'm still learning and improving 1% daily like I have since we started PDM. Yeah, nice. And at 1%, is that from James clear? Where does that come from? James clear? Yeah. Atomic habits. Best book. I recommend it to everyone. Yeah, it's a game changer. Productivity rise. Right? It definitely is. It helped a lot. And 1% is all about that compounding effect, I guess. Right. Like if you just improve a little bit every day, then that starts to compound over time or what's out your mind? That. Yeah. So that's how I take it. Like, if I try to just make small incremental improvements compared to yesterday, by the end of the year, by the end of two years, I'll be in a much different place. It also helps with the mindset that it's all about me. I'm the one that has to be better than I was yesterday. I don't need to worry about how well I am doing in python compared to you or, you know, to anybody else. That mindset was really helpful in keeping me in check, if you will. Yeah, I agree. If you start to compare against some of these big names in open source, it can be very discouraging and it's just. Yeah, you missed the point. Right. Because you have to improve based on where you were yesterday, and if you anchored against that, then it's more realistic. Yeah, sorry, I skipped the question. Actually, I was going to ask about your journey in program Python. So now you landed the job and. But, yeah, tell us a bit where you came from with Python. Because when you joined PDM, you were pretty new to Python and coding overall. Right. So how was that journey for you? It's definitely been a journey. I agree with Julian. He and I messaged a couple weeks ago that the real learning and journey began when I started my data engineering job. But during COVID or when Covid hit, I was in a industry that had to be furloughed, and then that Covid affected the industry that I was in considerably. And I swore at the time that I never wanted to be put in that position again to where I was furloughed. And so I started looking around into different areas of tech that sounded interesting and landed on Python. I took a university level course before I joined you for PDM. And actually, because of the homework in that class, is how I found, because you helped me with a few of the homework assignments. And so we discussed that December to join PDM and start in January, which is what we did. And then I went through PDM, did a couple of projects. I came out of PDM and definitely was interested in the big data side of Python and the analytical side that comes with that domain. And once I graduated from PDM, I carried around my laptop with me everywhere. As you remember, I was doing anything and everything that I could possibly do with Python to gain experience for myself. I was still definitely struggling a lot with imposter syndrome and developing that mentality or that mindset that I'm the one that I have to beat. I'm not trying to. I shouldn't compare myself to anyone else in the industry. It's all about how I am and how I sell myself when it comes to gaining employment. So I did a lot of research and analysis for the rest of that year, all kinds of things. I don't know if you want to delve into any of that. I will get to the data side. Yeah, no worries. All right. And then I decided for various reasons that I wanted to move back to the UK. So that December, I, back to the UK, spent about a year working with different charities and whatnot. Gina. Still gaining experience in the data field. And at the beginning of this year, I started interviewing with the company that I'm now working for. And here we are. It's been a journey. It really has been a journey. It's such an amazing story. Right. Because the moving back, that was an important goal. Right. And how you have been able to combine it with programming in Python, where you had a lot to learn and finally accomplishing it, it took some time because, let's be honest, to be good at programming, it just takes a lot of time. So I think one of the things you mentioned, like, yeah, once you had the tools and the base knowledge through the program as well, you just started to bring the laptop everywhere you went. And it's just how it is. Right. You have to constantly practice to get better. Right. So was that something you got out of PDM? I mean, apart from the tools, but kind of that mindset, like, you have to always be coding or where that come from. So the PDM mindset was just in time training, if I remember the technology, we always say that term. Yeah. And so one of the things that I struggled with was, which is in the industry, even with experienced people, is that I'm not good enough or I don't know enough. So I kept putting myself in positions where I absolutely had to utilize Python and my analytic skills because I believe that they're a skill that you either use it and it gets better or you don't use it and it gets static and, you know, because the field is changing, it feels like almost hourly at some really big goals with Python from PDM that I wanted to accomplish. And two of them have been checked off the book, technically a third, because I am an agile worker, I do work from home and get to travel all over the UK now to do my job, which is amazing. But that mindset and just trying to find different projects and different things and new challenges that would push the envelope of what I knew and make me learn more was really an important step in the journey. Awesome. So your particular question about data. Right, so what fascinates you about it? And yeah, maybe you can share some of your researches and researching and one or more projects you have been working or still working on. Sure. Data has patterns and it holds all the answers if it's looked at correctly. It's easy for me to understand data and analyze it and come up with conclusions and, you know, it allows you to gain some insights into the bigger picture of what's going on in whatever domain you're in. One of the domains that I did look at after PDM was voting rights. You know, how the voting, how people have been voting and how it's been shifting in whatever direction it's been shifting in different countries and whatnot. And you know, it's just fascinating. We're gaining millions and millions of petabytes of data like all the time. I mean it's, we're just, we're now a data driven world in one aspect. And in order to be a part of that world, you know, you need to know how to analyze it, manipulate it and derive insightful meaning from the data that it's presented. So I was analyzing everything. I mean everything. So you asked about what I've been working on or what I. Some of the projects I've worked on. Yeah. So just, yeah, so it definitely comes also from a bit of, you know, personal interest, maybe geopolitics history and how data can. Yeah. Really not predict the future, but maybe shed a different light on or better understand it. Right. It compared a bit with reading a lot of history. Right. It makes you just better understand whats happening. Right. Yeah, it explains the present a bit more data in that regard. So I definitely, we are in a politically charged world right now, so, you know, that has been at the forefront of a lot of countries for. For a while. I'd say the entire two thousands, honestly. Of course, you know, whatever the big topics were in the news, either stateside or here in the UK, I would analyze and come up with my own analysis. I even looked at gun violence and the definitions of gun violence in the United States and why there's such a discrepancy between, you know, the number of mass shootings versus the number of mass shootings. Like I said, I just kept working hard to analyze or to just develop those skills with Python. And yeah, it's been insightful on many levels. No, it's fascinating. It's really cool how you niche down, how you really learned the skills to solve those real world practical problems that, you know, that's just interesting and keeps you more motivated. So is any of that on your GitHub? I saw that you also have a LinkedIn newsletter, I believe I do have a LinkedIn that I definitely want to link. But yeah, if you want to call out any projects on GitHub, that's fine too. But yeah, I can imagine people being interested in, especially like these specific cases you mentioned to go check that out. Sure. So everything that you can reach through my GitHub, through my LinkedIn profile, I try to make sure that that stays purely python and data related. So there's links to my GitHub repository on there with the sites. I am currently working on a chatbot of sorts for autistic employees like, you know, because a lot of autistic people don't really communicate well with, with individuals. So I've been doing a lot of research personally on autism and how to best implement some kind of technological strategy for them in the workforce. So that's one of the projects that I'm still working on. I keep having to go back to the research phase of that because there's just so much to learn in that domain. I've also been working on a building a digital archives for one of the historical sites here near where I live. The site was built in 1540s and it's still standing and they've been collecting data on it, and I've been building the database for that. So there's that project, and then of course, you know, there's different projects that are attached to my LinkedIn as well. And the newsletter was something that I noticed, or I started it because I noticed that there seemed to be a hole in the data science, data engineering space in regards like, everything that I kept bumping into was the iris data set or the Titanic data set. And it just seemed to be a very repetitive cycle of iris Titanic. And so I wanted to expand that a bit and see how I could fill in the hole of applying those principles to a much wider base than just in just twelve weeks. Pyrites elevates you from Python coder to confident developer, build real world applications, enhance your portfolio, earn a professional certification showcasing tangible skills, and unlock career opportunities you might not even imagine right now. Apply now at Pibit, ES, PDM, Iris and Titanic data sets. So I've been writing that consistently for over a year now. About a year and a half, I think I just published my 94th newsletter. It's amazing. Thank you. You have something that consistency. I think you also did all the bytes on the platform when I. Yeah, blue belt and I checked back all of that. No, I got them all done. What? Yeah, there is one bite. You're good at consistency. Thank you. There is. And that's, that's been big on the mindset. There is one bite that I still need to go back and do now that it's been published. So I'll be getting to that probably sometime next month because it's basically June anyway. But, yeah, no, consistency is really important in the programming world and end in data science and the data world as a whole. Yeah. And I think you kind of found a way to keep it interesting for you, right. By solving these real world problems. And I think that keeps you actually motivated. I have a couple of follow up questions, like, you seem to be very good at finding ideas and researching. Right. So maybe for those two things, I want to get some tips, like how do you even find a project, like the archiving thing or even come up with, like, to do data analysis of XYZ? And also, how do you then research that? Because it seems like in what you do, how you tackle it, the researching phases is quite important. Yeah. The type of person that never accepts face value for an answer. I always want to fact check what I'm reading, what I'm seeing, what's going on around me, because sometimes we're really not given the correct picture. We're just given a picture and I find things, or have found things that I'm. That just, you know, scratch that. Itch. Like, okay, I don't quite think what you're saying is correct. So let's, let's dive a little bit deeper into it. Like for example, I mean, we can just bring up the mass shooting definition. You know, there's. When I was doing the research, there were ten mass shootings, but then if you actually looked at the data, you could see that there was 682 in a calendar year. And why was that difference? And it basically had to do with whether or not the FBI responded to the event. But when you broke down the definition of a mass shooting, you could apply it to more shootings than just, you know, what was being discussed in those ten, because there was no FBI response. So that's what I mean. Like, if something makes me scratch my head or I walk away asking questions, I'm gonna try and find an answer. It might not be the right answer, but it's an answer that I will be okay with. And that's kind of how I do the research. So if you got questions to ask, I have yet to throw a question or an analytical problem at Python and not come up with some type of answer. Interesting. So, apart from genuine curiosity, it's really like critical thinking. Second, really, you know, not. Yeah. Not taking things at face value, question things. And is that just your nature, or is that from previous experience? Where's that coming from? I think part of it's my nature. I also think I actually wrote my very first newsletter, or one of my first newsletters was about the data analyst mindset, and how even in the business intelligence world, you need to be striving towards an answer. And if you're not always asking questions, I would say, are you really analyzing anything? Because there's always a question to be asked. There's always an answer that's being looked at, and sometimes the question that's being asked of you as an analyst or as, or in Bi isn't really the question that needs to be answered. So having that curiosity mindset is something that is really important in this domain, in my opinion. Yeah. And can we still read that? Nisler, if you subscribe, do we get that one or. Yeah. So you only get the latest? Yeah, no, I've got all of them. All of them are accessible. I try to publish every Wednesday and Saturday, but sometimes that's a bit much. So I definitely consistently do once a week, but 90% of the time it will be twice a week. And I tend to write the newsletter based on something similar to what I've been working on at work and kind of figure out a way to, without breaking any of confidentiality issues, address it in a public domain. Yeah. So newsletter posting on LinkedIn in central content provider. So how important is the online presence and being a content provider as a developer, or data analysis, data analysis for that matter. I think it's becoming more and more imperative that you establish an online presence and figure out a way to stand out, because the crowd, if you will, is getting highly competitive, you know, and a lot of the people will have similar backgrounds. But if you can't prove or show that you know how to do technical writing or know how to write or establish, get a point across, you know, those can't really come across in the technical interviews or even the non technical side of the interviews. And so I think it's becoming imperative to establish the, an online presence, and I think it will continue to be that way for a while. Is it becoming easier? I guess when I first did content, there was a lot of imposter syndrome that people would think, and if they would shoot it down and stuff, does it become easier over the more you publish? In your case, it does, but there's still imposter syndrome, and there's still going to be haters online that will always, always, that will tell you X, Y and Z. And that goes back to the mindset of the 1%. Just as long as I'm improving daily 1% and I'm okay with the content that I'm putting out, it doesn't matter what anyone else thinks, you're going to find those people whose opinions will matter in your domain or in your python world to listen to those mentors. And when they speak, that's when you need to pay attention. But Joe Schmoe from down the street, who's tapping away on his keyboard because he's angry, you know, don't listen to them. Basically, yeah. I learned the same. Like, there are opinions and opinions and you, you have to apply some filters and just watch for the ones that matter to you. And it's very easy to, or keyboard warrior, to put something negative out there and ruin your day, but not worth it. Not, not saying it's easy, but I think you'll learn to balance that over time. So talking about mindset, there's, throughout this whole conversation has been a lot of mindset. I. I think we can not skip it because then I get into trouble with Julian. But is there any mindset tips you want to add on top of what you already said that you think are important for developers aspiring or established? Yeah. So one thing that Reese and I talked about at the beginning of the year was how to sell yourself. And I think that that is an important mindset that you need to have. Everyone has a unique ability that sets them apart from everybody else. Mine just happens to be being able to see patterns and data and analytics and, you know, making sure that you get that point across in the interview process and showing it as your strength and learning how to sell yourself as a whole because of those strengths was something that it took a conversation with Reese to understand. And because I was always afraid that, you know, being as analytical as I am or being able to see patterns, you know, in some circles, it might have been viewed as. Because I do analyze everything, but in the right light, it can be viewed as a strength, and it will set you apart from the other candidates that are going after a job. So learning how to sell yourself is a mindset that's important. That's Reese Powell, right? That is Reese Powell, yeah. Fellow. Fellow, pdmer. And he was also on the podcast, I think, twice. Yeah. Awesome. So, yeah, you can be brilliant at something, but if you cannot communicate it or show it, then it's not worth much. Right. But it's also, like, niching down on your unique strength. Like, in your case, finding the patterns, the data analysis part, and then when you sell yourself, your skills, then really honing in on these unique abilities. Right? Yeah, it's very helpful. Cool. All right, so I have two more questions. Is there any side activities, non coding skills due to outside of work or stuff that has influenced your coding skills? So, yeah, actually, I love photography and I love running, but I bring that up because I mentioned that I volunteer at the historical site here in Sheffield, but I've been taking photographs of that site after every big storm. Well, it didn't start off that way. I just started taking photographs of the site because it's, as you can see, my background, because it's beautiful. But then I started noticing that the site looked like it was shifting or different parts of it from my eye were starting to bow out or structurally change. And so I took my photography and started feeding it into python to learn about historical conservation and how and whether or not those images that I was seeing were changing. And I've been able to talk with them about the fact that one of their walls has a 3% bow in it of the last storm. And so they've asked me to follow up on that project and just keep them up to date on the wear, the weather, where whatever the correct terminology is of how it's. How the site is degrading over time. So that's been fun. And another use of python, like, just, it's out there. You just gotta. You just gotta find it. I do run ultra marathons. I do have an 111 miles race coming up here in this summer around the Warwickshire canal system. So I do a lot of things that are non python related, but talking about tenacity. Yeah. Cool. Nice. And the last question I had is of course about the books, what you're reading or any, any book tip you might have. So one of the books I'm reading is called Elizabeth Spymaster. I've been asked to discuss how the spy networked worked in 1560 to 1580 under Walsingham when Mary Queen of Scots was a prisoner here in Sheffield. And so I've been doing a lot of research on the side regarding that and how that all has unfolded. And then because of that, I've also been doing a lot of reading on the dissolution of the monasteries because there's so many historical sites in the UK that are just fascinating. I do go around taking photos of all of them and they're on my instagram. So that's non technical. I am reading or preparing for the Google cloud data engineering certification. So I've been reading that study guide as well and practicing on that. So there's those. Really cool. Yeah, I showed a couple of books last episode, Pycon. So a 4000 weeks productivity book. Oh, nice. Something on algorithms and try to read up on LLMs as well to start doing something with the Pibytes data. I do want to get my hands on your py bytes data. I have them. I have them there. It's all the public data so we can talk. I think that'd be fun to analyze. Yeah. Well, wonderful. I will link, of course, your LinkedIn, your newsletter, the book you mentioned. Any final shout out or piece of advice for our audience? Sure. If you, if you're dreaming of doing something, do it, you know, and remember that it's a learning process along the way, but where you'll be in one year from today, be leaps and bounds from where you started and you know, look at me two years later. I'm in a field and a domain and an expertise that I very had a very limited idea of when I began Python during COVID And I'm really only just beginning to learn now and I'm looking forward to it every day. Just say go out and achieve your goals. They are achievable. Yeah, maybe. I think it's more incremental steps. Right. Because you might not be able to visualize it, but then with the 1% rule it can add up, but you have to put in the daily work, right? Yeah. Well, I'm super impressed how far you've come. Because I remember when you joined and, uh, you had very basic python skills, right? Getting stuck on beginner bytes and. And that was, that was fine, right? And now seeing all the stuff you're doing, like, that's. That's leaps and bounds, right? So it's really cool. It's been a journey. Yeah. So thanks for hopping on and sharing. I think it's, uh, it will inspire many people and, uh, I encourage them to reach out. Of course, you're also in the pie byte circle community and, uh. Yeah, again, great conversation. Thanks for. For hopping on. You're very welcome. Thanks for having me. All right, cheers. Cheers. We hope you enjoyed this episode. To hear more from us, go to pibyte friends, that is pibit es friends, and receive a free gift just for being a friend of the show. And to join our thriving community of Python programmers, go to pibytes community. That's Pybiton es community. We hope to see you there and catch you in the next episode.