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Pandas 3.0

268 points by jonbaer

by edschofield

17 subcomments

The design of Pandas is inferior in every way to Polars: API, memory use, speed, expressiveness. Pandas has been strictly worse since late 2023 and will never close the gap. Polars is multithreaded by default, written in a low-level language, has a powerful query engine, supports lazy, out-of memory execution, and isn’t constrained by any compatibility concerns with a warty, eager-only API and pre-Arrow data types that aren’t nullable.
It’s probably not worth incurring the pain of a compatibility-breaking Pandas upgrade. Switch to Polars instead for new projects and you won’t look back.

by postalcoder

8 subcomments

I've migrated off of pandas to polars for my workflows to reap the benefit of, in my experience a 10-20x speedup on average. I can't imagine anything bringing me back short of a performance miracle. LLMs have made syntax almost a non-barrier.

by teekert

0 subcomment

I have deep respect for Pandas, it, and Jupyter-lab were my intro to programming. And it worked much better for me, I did some "intro to Python" courses, but it was all about strs and ints. And yes, you can add strs together! Wow magic... Not for me. For me it all clicked when I first looped through a pile of Excel files (pd.read_excel()), extracted info I needed and wrote a new Excel file... Mind blown.
From there, of course, you slowly start to learn about types etc, and slowly you start to appreciate libraries and IDEs. But I knew tables, and statistics and graphs, and Pandas (with the visual style of Notebooks) lead me to programming via that familiar world. At first with some frustration about Pandas and needing to write to Excel, do stuff, and read again, but quickly moving into the opposite flow, where Excel itself became the limiting factor and being annoyed when having to use it.
I offered some "Programming for Biologists" courses, to teach people like me to do programming in this way, because it would be much less "dry" (pd.read.excel().barplot() and now you're programming). So far, wherever I offered the courses they said they prefer to teach programming "from the base up". Ah well! I've been told I'm not a programmer, I don't care. I solve problems (and that is the only way I am motivated enough to learn, I can't sit down solving LeetCode problems for hours, building exactly nothing).
(To be clear, I now do the Git, the Vim, the CI/CD, the LLM, the Bash, The Linux, the Nix, the Containers... Just like a real programmer, my journey was just different, and suited me well, I believe others can repeat my journey and find joy in programming, via a different route.)

by kayson

0 subcomment

Are there any pandas alternatives that offer stronger column typing? Ideally something where I can have the schema defined in advance, validate the data, then have the type checker be smart enough to know that df.foo exists and is float and df.bar doesn't.
I tried pandera and it left a lot to be desired. Static frame [1] seems promising but doesn't appear to be popular for some reason.
1. https://static-frame.readthedocs.io/en/latest/

by jtrueb

1 subcomments

That timestamp resolution discrepancy is going to cause so many problems

by alexcasalboni

0 subcomment

Haven't used pandas in a while, but Copy-on-Write sounds pretty cool! Is there any public benchmark I can check in 2026?

by gku

0 subcomment

The need to upgrade Pandas, combined with emerging AI tools, might accelerate Polars adoption, let’s see what happens.

by QuadmasterXLII

0 subcomment

Ugh, I'm still recovering from numpy breaking changes with 2.0

by optimalsolver

4 subcomments

How soon will the leading LLMs ingest the updated documentation? Because I'm certainly not going to.

by OutOfHere

1 subcomments

s/impactfull/impactful