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Pandas Exercises for Data Analysis (Interactive)

Pandas Exercises for Data Analysis (Interactive)

selva86

Comments (31)

  • ronfriedhaber
    Pandas is terrific, yet even its original author has noted inherent shortcomings [1], and there exist alternatives.Polars seems to be the most prominent competitor in the Python DataFrame space, and DuckDB appears to pursue an approach similar to SQLite, but columnar.I am personally working on a solution to a broader problem, which can also be viewed as an alternative to Pandas [2].[1] https://wesmckinney.com/blog/apache-arrow-pandas-internals/[2] https://github.com/ronfriedhaber/autark
  • 0x696C6961
    Would be nice to have a polars version of this.
  • selva86
    Build this as an interactive tool for our popular 101 Pandas exercises. The code runs entirely in local in your browser. Would love feedback on the ease of use and the editor UX.
  • kasperset
    I don't hear much about Ibis here. https://ibis-project.org On paper it sounds like a good idea. Any opinion about this option.
  • rithdmc
    Dope. I've just started using Pandas in some personal projects, and am quickly hitting my knowledge ceiling. I think this will be useful. I'll check it out properly after work.
  • sghaz
    The pricing page says, "This page doesn’t seem to exist. It looks like the link pointing here was faulty. Maybe try searching?"
  • short_sells_poo
    You'll get a lot of responses saying Polars is better than Pandas. I argue those people are missing the point and don't understand Pandas' real strength or why people choose Pandas today.Pandas was never meant to be a technologist's tool. It was meant to be a researcher's tool and was unfortunately coopted to be a technical solution as well. It has not well escaped it's roots.Pandas is fantastic for doing iterative and interactive research on semi-structured data. It has a lot of QoL facilities and utility functions for seamlessly dealing with exploratory timeseries analytics for in-core data. Data that fits into memory.For example, I can take two time series and calculate their product:ts3 = ts1 * ts2This one line does a huge amount of heavily lifting by automatically aligning the timestamps and columns between the two inputs so that I'm not accidentally multiplying two entries that have the same ordinal but not the same timestamp or column label.Can I do the same with Polars? Yes, but it comes with exponentially more cognitive overhead. And this is just one example.Pandas is ultimately a flawed product as it's origin's go back more than a decade where R's dataframe was cutting edge. A lot of innovation happened since then and the API and internals of Pandas mean that certain choices that were made early on are nontrivial to change.This doesn't change the fact that Pandas is still immensely useful. Eventually perhaps Polars will come close to it, but so far the focus wasn't on interactive use ergonomics unfortunately.As it stands, I use pandas for research and polars for production systems.
  • fud101
    what is the permission it asks for? it seems suspicious af.
  • kjkjadksj
    If you think pandas is comfortable, wait until you try base R. Such a comfortable language for data wrangling and analysis.