# pandas 93 Hacker News commenters recommended pandas and 98 criticized it, November 2025 to November 2026. It was recommended in 11 of 13 months; owners who said how long report a median of 10 years (7 owners). **Verdict:** Widely used Python library for tabular data, valued for ergonomic exploratory analysis and a long history; critics call its API awkward and say it is not fit for production use. ## Why people recommend it - Ergonomic for exploratory analysis (5 comments): "The pandas example is a good approximation of how I think and want to transform/process data even if it is ugly under the hood." ([source](https://news.ycombinator.com/item?id=46800812)) "Pandas is clearly quite ergonomic for various exploratory interactive analyses, but the API is, imo, awful." ([source](https://news.ycombinator.com/item?id=47625247)) "the ergonomics of good pandas documentation and community knowledge make it a better choice" ([source](https://news.ycombinator.com/item?id=49668463)) - Swiss army knife for any data task (3 comments): "Pandas is the swiss knife tool of data science that lets you do anything with the data" ([source](https://news.ycombinator.com/item?id=49668786)) "being able to throw pandas at something or matplotlib or whatever is super valuable" ([source](https://news.ycombinator.com/item?id=49516446)) "Pandas is the swiss knife tool of data science that lets you do anything with the" ([source](https://news.ycombinator.com/item?id=49669065)) - Established and widely supported (2 comments): "Pandas is the most established, although has a lot of technical limitations, as well as complexities." ([source](https://news.ycombinator.com/item?id=49296105)) "has been open source for almost two decades, and is supported by many companies" ([source](https://news.ycombinator.com/item?id=47426359)) - Easy entry from Excel (3 comments): "a non-professional programmer can use scikit-learn and pandas and matplotlib to put their skills on wheels" ([source](https://news.ycombinator.com/item?id=47799300)) "Pandas and Numpy made it quite easy to get up and running with a lot of analytics." ([source](https://news.ycombinator.com/item?id=46355440)) "It was the bridge I crossed that moved me from living in Excel to living in code." ([source](https://news.ycombinator.com/item?id=46794004)) ## What people warn about - Confusing, verbose API syntax (3 comments): "The first time I read pandas code, I saw something along the lines of df[df["age"] < 3] and thought I was having a stroke." ([source](https://news.ycombinator.com/item?id=47306134)) "Pandas is clearly quite ergonomic for various exploratory interactive analyses, but the API is, imo, awful." ([source](https://news.ycombinator.com/item?id=47625247)) "Pandas is so verbose and hard to debug, most of the times struggle to be performant on small datasets." ([source](https://news.ycombinator.com/item?id=48595383)) - Slow and memory-heavy in places (2 comments): "certain idioms did not work efficiently because they escaped the pandas kernel, causing memory copy and other bad behavior" ([source](https://news.ycombinator.com/item?id=49353123)) "we finally nixed Pandas from Data Ingestion, now reading excel files takes 2 seconds instead of 2 minutes" ([source](https://news.ycombinator.com/item?id=49668702)) - Poor outside its original use (2 comments): "Pandas is really poor dataframe experience outside of it's original use case which was financial time series." ([source](https://news.ycombinator.com/item?id=46126783)) "So much of my life time has been lost trying to get dataframe and non-dataframe libraries to work together." ([source](https://news.ycombinator.com/item?id=46649587)) ## Alternatives hackers recommend - [Polars](https://hackerapproved.com/p/polars.md): 152 recommend - [NumPy](https://hackerapproved.com/p/numpy.md): 86 recommend - [SciPy](https://hackerapproved.com/p/scipy.md): 12 recommend - [sh Python library](https://hackerapproved.com/p/sh.md): 10 recommend - [Tacopy](https://hackerapproved.com/p/tacopy.md): 8 recommend ## Cite as Hacker Approved, "pandas", https://hackerapproved.com/p/pandas/ (counts from 1,795,640 Hacker News comments, November 2025 to November 2026).