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Pandas Should Go Extinct

eddie.codes

1–10 of 105 posts

Re: Pandas Should Go Extinct

#2
I use polars or duckdb now exclusively. Better syntax, better performance. But pandas is deeply entrenched - I try to get my team off it but it’s an uphill battle. It’s not going anywhere anytime soon.

Re: Pandas Should Go Extinct

#3
> People typically start with Excel and graduate to Pandas somewhere in the GB range. Pandas serves them well into the 10s of GBs range, and then they start hitting memory issues, slow computation, or become frustrated with Pandas’ baroque API.

Assumes that a project moves beyond 10s of GBs. I guess 99.9% of projects that import pandas fall well below this threshold.

Re: Pandas Should Go Extinct

#4
It's been a while since I've seen an actual data science post submitted to Hacker News: both because AI has superset a lot of DS tasks (e.g. vector embeddings), but also because not much new has happened in DS. Polars has been around for a bit and as noted it is much better than pandas, but otherwise the DS ecosystem has been somewhat stagnant.

I'd write more tutorials about how to use data science tooling but one consequence of AI is that all the old data sources I used to analyze such as social media and Reddit are now completely locked down (I am surprised NYC Taxi is still being updated, though). Therefore in the meantime, I'm working on making better data science tooling...although unclear to what end due to the data issue above.

Re: Pandas Should Go Extinct

#5
I've been saying this since using Databricks at a company almost a decade ago. Most folks do not need big data tools, and it's just so entrenched because everyone wanted to be a "big data" company and pandas was how you handled big data.

Re: Pandas Should Go Extinct

#6
post #3

> People typically start with Excel and graduate to Pandas somewhere in the GB range. Pandas serves them well into the 10s of GBs range, and then they start hitting memory issues, slow computation, or become frustrated with Pandas’ baroque API. Assumes that a project moves beyond 10s of GBs. I guess 99.9% of projects that import pandas fall well below this threshold.

At my work I had convinced the ML pipeline engineers to switch from pandas to polars for even small ETL pipelines and there were notable performance gain with better CPU/memory utilization.

If a library is performant at large datasets, it is likely performant at small ones too.

Re: Pandas Should Go Extinct

#7
Agreed on all counts.

In many cases I’ve found directly using python primitives to be less confusing than pandas.

Similarly, in companies I’ve worked at, the datasets just aren’t that big. Especially if you’ve got access to modern hardware.

Re: Pandas Should Go Extinct

#9
post #3

> People typically start with Excel and graduate to Pandas somewhere in the GB range. Pandas serves them well into the 10s of GBs range, and then they start hitting memory issues, slow computation, or become frustrated with Pandas’ baroque API. Assumes that a project moves beyond 10s of GBs. I guess 99.9% of projects that import pandas fall well below this threshold.

At my work I had convinced the ML pipeline engineers to switch from pandas to polars for even small ETL pipelines and there were notable performance gain with better CPU/memory utilization. If a library is performant at large datasets, it is likely performant at small ones too.

I’m not disagreeing with that statement at all. You missed my point that there are thousands of people making small Python scripts for education and personal projects everyday. In those circumstances the performance concerns are irrelevant and the ergonomics of good pandas documentation and community knowledge make it a better choice.
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