__mharrison__

Yeah, this was my initial thought as well... I guess they didn't ask anyone before choosing the new naming scheme. But that isn't particularly surprising.

I have a touchscreen ThinkPad. As an instructor, I found it useful to draw on slides with the pen. I rarely touch it otherwise.

I mostly use MBPs now and resort to using my iPad as a mirrored screen to draw on slides. It is hacky.

No pen support is lame.

Having said that, I'd be afraid to touch it. On one of my MBPs, I held it by putting my hands near the hinge, with my thumbs resting in the lower corners of the screen. Over (a short period of) time, the protective(?) coating on the screen wore away.

Maybe AI will finally help usher in macross movie after so many years... Ducks

I hope the Stanford profs got paid... this alum is still owed $60k for ANT pirating my books.

Numba does this. Generally as fast as Cython, but much easier to write.

How do you ensure that bootstrapping a new project has good code?

Wow, cool aesthetic. I feel like the this is what the cybertruck should have looked like but they didn't quite finish the design.

Have been using this in my terminal, editors, and books for a few years.

Lovely font.

That's the great thing about art. Reasonable folks can disagree about what art is...

My career and actions are proof to me that although I appreciate code and spent almost half of my career teaching folks the "correct" way to write Python, I (personally) don't view code as art.

Glyph didn't convince me. (And I'm biased; I've sat in multiple sessions given by his dad 20 years ago about creating good code.)

Code can be pretty, but I don't consider it art. Just like I don't consider technical documentation art.

I much prefer being able to talk to my computer and tell it to make a Stream Deck plugin to control the lights in my office and create a weather app (and show the precipitation forecast on the buttons) in 10 minutes, rather than me futzing around for two days to create something similar. Or to create the world's first(?) Telemark ski game from my Strava dumps in 30 minutes.

Admittedly, my book and course sales are down quite a bit (which I would mostly blame on AI). I'm not sure what the future holds, but change and adaptation have been pretty constant in my 25+ year career.

I do have concerns about what the minimal knowledge requirements will be for product development in the future.

There was a class action lawsuit that listed pirated books

That's a great question. I don't know what the future will be like, but looking into my crystal ball, I'm not seeing much hand-generated code. Very little (or no) human code review.

Having the taste and business sense to develop the right thing will be important. If it stops working, ask the AI to fix it.

I teach many data/ML courses for clients using their data. It is amazing how many insights both the students (as SMEs of the data) and the teacher (as an SME of the techniques) can have when going through certain techniques together. Quite often, we get a "those last 5 minutes more than paid for the training" insight.

I think that is possible with AI (I haven't experienced it), but I also feel like most folks use basic/naive/cursory techniques when using AI because they don't know what they don't know.

As an educator and author, I feel Molly's pain (Anthropic owes me $60k for pirated books). My course and book sales have dropped significantly. I feel like much of the value in my book-based knowledge is harder to discover in AI agents. (One example might be inspecting SHAP values from XGBoost models and using that as feedback to feature engineering for a linear model (like Logistic Regression)). So I'm afraid more advanced techniques might go by the wayside in the name of delivery speed.

I use AI both in the cloud (I tend to avoid Anthropic...) and with local models.

I've probably written more code in the past year than in my whole career. I can now create what I desire (I just created a telemark skiing game over the weekend based on my Strava segments). I think this has helped my teaching as well. In a recent ML course, I created many interactive examples that in the past were just doodles on my whiteboard, but are now embedded in the notebooks I give students.

I've also taught a few AI courses to clients as well. However, with the inevitable rust/ASM-ification of everything, I'm not sure how long those skills will be valid. I do, however, think that having a human in the loop for ML and data analysis is still important.

I've been in multiple workshops for creators that were ran by LinkedIn. They have all mentioned not to use links.

BTW Twitter penalizes links as well.

I misspoke, you need to use .groupby/.transform to add a new filtering column:

    (sales
      .assign(country_median=lambda df_: (
          df_.groupby("country")["amount"].transform("median")
      ))
      .query("amount <= country_median * 10")
      .assign(net=pd.col('amount') - pd.col('discount'))
      .groupby("country", as_index=False)
      .agg(total=("net", "sum"))
    )

Would love to see examples.

I'm confused, you can use filter after a groupby in pandas...

It's late here, I'm going to bed, perhaps I'll write the code tomorrow when I'm at my laptop and not on my phone.

Those are generally rules of thumbs for data pipelines. (Plus duckdb can read Excel these days I think).

This is a common complaint I get all the time (heard it this week while teaching pandas). I compare this to whitespace indentation in Python.

Lots of folks complain about it before using it. After they use it it is a non issue.

If it really is an issue (and it generally isn't a cause of vectorization removal when used correctly) and you can't get over the syntactic noise if the lambda, pandas 3 introduced pd.col (that work in most (I filed a big about some exceptions) places when you'd use lambda).

I looked at your code very quickly, but it looks like you need to use .filter after a .groupby...

Did you ever report these issues to polars developers?

I reported many bugs to both pandas and polars over the years and both teams tend to address relatively big ones. (Still have some outstanding pandas bugs that I think are a big deal but the devs disagree.)

Most of the time it works, but there are still corner cases throughout the python ML ecosystem where polars fails.

This and the decision not to natively plot with matplotlib keep me in pandas for most tasks. (Plus there's is still a relatively large demand for pandas training.)

Rewriting pandas to polars is relatively trivial for most tasks these days. Especially if you wrote your pandas code correctly.

I still prefer (and use) Pandas for EDA. I think matplotlib integration is a better choice for most viz.

Also, I'm probably in the top 3-5 worldwide for number of folks I've trained with pandas. I offer Polars training and there is little demand for it.

Use pandas if you want advanced analytics, visualization, or ml.

Use SQL if you need to move data around.

If you learn to write pandas correctly you end up writing it very similar to polars (or tidyverse).

I agree that the API has warts, though typically it is more concise than polars.

Most folks just need to learn how to use pandas well and that will open enough doors. Then they can move to polars or duck if needed.

I'm in the middle of wrapping up the edits for Effective Pandas 3rd Edition. (I also wrote a Polars book and just wrapped up a weeklong training session on pandas this week.)

Pandas is not perfect, it has a bunch of warts. But it is good enough for most. (And many of those folks are using Excel or tableau or power bi... These were the types I was training this week).

If you have medium data, migrating from pyarrow backed pandas to duck or Polars is trivial.

I spent a few tokens last year trying to create a Python lib for native (undocumented) Resolve files. I was making progress, but it was slow (I ended up scripting Resolve in different ways). I imagine that current models could reverse-engineer the native file format relatively quickly.