Currently Reading: Hands On Data Analysis With Pandas - Stefanie Molin

Reading Statistics

Lies, Damn Lies and (these Reading) Statistics

• The stats are glaringly incorrect re: ‘Time Spent Reading’ & ‘Average Time per dat’.
  • I think the time spent discrepancy is likely because the reading material is denser and the screensaver often turns on before I go to the next page. I’m guessing that is discarding chunks of time as AFK incorrectly.
  • I wish I spent 11 minutes a day on this book. In actuality, I typically spend between 2-4 hours a day working through it. I think because I’m frequently Alt+Tabing between JupyterLab and KOReader, it gets lost in the sauce? Oh well.
• I could ‘read’ much faster but the times are longer because I create my own Jupyter Notebooks and code alongside her instead of following in the provided notebooks. Good for some extra repetitions to make the ideas stick.
• While it’s not 100% correct, it is cool seeing when I started reading, for how many days etc. Technical books require a lot more starting and stopping for coding, so I’m not very concerned about the accuracy for my general reading.

The Ups and Downs of Solo-Learning

2-3 years ago, I finished a course on Data Analysis w/ Pandas. It was good, but I didn’t utilize the things I learned very often afterwards and the skills disappeared. My Data Analysis skills have always been kinda meh, and so I decided to double back and read this book. (IIRC, I got the book on sale for $1 during a covid book bundle sale, and so learning for the low was a small but non-zero motivating factor also)

I started the book in late-December and there was some initial speedbumps that I didn’t expect (the author goes heavy into python to show how things would be done w/o the Pandas library, but to someone that doesn’t have a lot of experience w/ Python, it was overwhelming in the moment). After the first third of the book, the info was pretty fresh and more applicable towards on-the-job analysis than the prior Udemy course I took fwiw.

Fast Forward to the end of February… I was @ ~50% completion and decided to give myself a bit of structure and tackle 25% of the book per month. I broke it down further by week (6.25%) and by day (~1.5% since I take Fridays off to review). It is a bit of an uphill climb tho, because I am trying to keep the pace as the topics become more and more advanced. Last Thursday tho, I squeaked through and hit 75%. The arbitrary achievement felt unexpectedly great, NGL.

Setting SMARTer goals has been a gamechanger. Without a way to gauge my progress, the whole process starts to feel arbitrary and pointless, but the smaller daily goal motivated me. I’ve read countless articles that have spelled this out already admitteedly, so if anything, it’s probably more a surprise that it took me so long to actually implement it in my daily routine.

That isn’t to say it’s been otherwise smooth sailing. I definitely caught myself w/ a fixed mindset when I would struggle with things that I expected to rememeber from the past, or didn’t assimilate new ideas quick enough. Luckily, I’ve managed to redirect that energy by creating flashcards on sticking points, seeking out context via trusted resources (Angela Yu for python fundamentals and Claude.ai for code-checks, analogies and quick, one-off questions).

I was taking notes in the book for a while, but dealing w/ the exports et al as a bit much. I realized that I could just copy/paste into Obsidian and never looked back.

I’m in the home stretch now. I have been slacking off with the end-of-chapter exercises for the last 2-3 chapters. It’s a combination of being pressed for time, some of the content being outside of what I deem as useful, and the problems just come across as complex.

I know I need to get the repetition in order to become familiar w/ the content but also want to hit my goal of 100%. I think that after I complete the book, I will circle back w/ a personal project and also try to revisit some of the concepts.

It might warrant a separate blog post, but as someone who loves reading from his eInk tablet, this book made me realize that as much as I hate reading books from a computer screen, it is GOAT status when it comes to technical books. I didn’t realize how often my workflow required putting down my tablet and typing something into a terminal until this book. It helps that KOReader has its own desktop app that I can use too.

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