19 engineers on Hacker News describe using pandas first-hand: 3 endorse it, 4 regret it, 1 are mixed.
“We use pandas + static schema wrapper + type checker, so you'll have to get exotic to break things.”
endorse · production · refactor_master · 2025-12-03 · source ↗ · wrong label?“Pandas hit GIL limits which made it too slow. Then we moved to Dask and hit GIL limits on the scheduler process.”
regret · production · marcinzm · 2022-08-02 · source ↗ · wrong label?“the LazyFrame optimizations offered by polars can never be fully taken advantage of when using pandas-based syntax”
regret · production · austospumanto · 2021-12-17 · source ↗ · wrong label?“it ultimately ended up being an order of magnitude slower because we ultimately had to call back into Python for each cell.”
regret · production · throwaway894345 · 2020-08-13 · source ↗ · wrong label?“I'll use pandas or SQL for anything more complicated than that, because it's that much more powerful.”
endorse · personal · nwallin · 2019-12-21 · source ↗ · wrong label?“Bringing it all in-mem and using pandas to do that was very slow for us.”
regret · production · geekybiz · 2019-01-24 · source ↗ · wrong label?“I don't like using pandas in prod because the performance is really sensitive to stuff like missing a type declaration”
mixed · production · ves · 2017-09-26 · source ↗ · wrong label?“Works extremely well in production, as in, on a flask web server, as well.”
endorse · production · elliott34 · 2014-10-20 · source ↗ · wrong label?“Lots of places where we replaced Pandas with DuckDB for transformations.”
neutral · production · staticautomatic · 2026-08-17 · source ↗ · wrong label?“We have about 100 deps that aside from numpy/pandas/pyarrow are pretty lightweight.”
neutral · production · alisonatwork · 2025-08-14 · source ↗ · wrong label?“you import pandas gbq and pretty much the entire google bq set of libraries is part of the build.”
neutral · production · dxbydt · 2024-07-12 · source ↗ · wrong label?“I've been using Jupyter to teach Python and Pandas to a lot of companies over the years”
neutral · production · reuven · 2023-12-16 · source ↗ · wrong label?“Dashboards running complex python + pandas tasks that pull from postgres”
neutral · production · bluecoconut · 2023-08-04 · source ↗ · wrong label?“one component for transformations (based on pandas)”
neutral · production · m_mueller · 2021-12-16 · source ↗ · wrong label?“More ram is a huge productivity enabler when working with in memory tools like pandas.”
neutral · production · efxhoy · 2021-04-27 · source ↗ · wrong label?“we ditched Pandas entirely for structured arrays.”
neutral · production · earthnail · 2017-06-08 · source ↗ · wrong label?“particularly in very low-level NumPy code, LLVM stuff with both Numba and llvmlite, pandas, Excel tools”
neutral · production · p4wnc6 · 2016-01-19 · source ↗ · wrong label?“pivot tables and plots via IPython/Jupyter notebooks with Pandas.”
neutral · personal · lmeyerov · 2015-07-24 · source ↗ · wrong label?“I have some experience using Pandas but I'd love to read about peoples experience using it in production or in large teams.”
neutral · personal · Bootvis · 2014-10-20 · source ↗ · wrong label?