Modern Pandas (Part 2): Method Chaining
tomaugspurger.github.io
Modern Pandas (Part 2): Method Chaining
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Re: Modern Pandas (Part 2): Method Chaining
#2When the book is revised, I guess they should take all pandas features from 1.0 or some later 1.x release for granted.
Re: Modern Pandas (Part 2): Method Chaining
#3Tom Augspurger is one of those names you recognize when you subscribe to the pandas repo. He is very involved in the project! Great to see his thoughts and how he uses it.
Re: Modern Pandas (Part 2): Method Chaining
#4Pandas may be OK for people who need to do a little data processing in their Python project, but I still recommend R and the tidyverse to those who need a serious tool of thought for analytics. Everything is so much more tidy and concise and intuitive and flexible. You can usually write code that directly expresses your high-level intent with a minimum of syntactic cruft.
Full disclosure - the downside of modern R is the stack traces have been getting worse for a while.
Re: Modern Pandas (Part 2): Method Chaining
#5Pandas may be OK for people who need to do a little data processing in their Python project, but I still recommend R and the tidyverse to those who need a serious tool of thought for analytics. Everything is so much more tidy and concise and intuitive and flexible. You can usually write code that directly expresses your high-level intent with a minimum of syntactic cruft. Full disclosure - the downside of modern R is…
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Re: Modern Pandas (Part 2): Method Chaining
#6Pandas may be OK for people who need to do a little data processing in their Python project, but I still recommend R and the tidyverse to those who need a serious tool of thought for analytics. Everything is so much more tidy and concise and intuitive and flexible. You can usually write code that directly expresses your high-level intent with a minimum of syntactic cruft. Full disclosure - the downside of modern R is…
Significant part of the work is massaging data and R sucks at that compared to Python.
"if you want to do more than statistics, let’s say deployment and reproducibility, Python is a better choice." https://www.guru99.com/r-vs-python.html
Re: Modern Pandas (Part 2): Method Chaining
#7Pandas may be OK for people who need to do a little data processing in their Python project, but I still recommend R and the tidyverse to those who need a serious tool of thought for analytics. Everything is so much more tidy and concise and intuitive and flexible. You can usually write code that directly expresses your high-level intent with a minimum of syntactic cruft. Full disclosure - the downside of modern R is…
It's intuitive to you but I have always found R a real pain to deal with. I acknowledge all of Pandas' flaws but R is not for me, and I've used it a lot in the past. It's all subjective and dependent on the context and requirements of a project.
Re: Modern Pandas (Part 2): Method Chaining
#8Pandas may be OK for people who need to do a little data processing in their Python project, but I still recommend R and the tidyverse to those who need a serious tool of thought for analytics. Everything is so much more tidy and concise and intuitive and flexible. You can usually write code that directly expresses your high-level intent with a minimum of syntactic cruft. Full disclosure - the downside of modern R is…
There are a number of good packages in Python specializing in variations of powerful chained processing in Pandas. My own is this one: https://github.com/WinVector/data_algebra .
Re: Modern Pandas (Part 2): Method Chaining
#9I was going to come here and post that I dislike method chaining because it is harder to read...
And then I read TFA and realize that I actually dislike people writing poorly formatted method chaining pandas code. The examples in the post are really nicely formatted and easy to read!
Re: Modern Pandas (Part 2): Method Chaining
#10Pandas may be OK for people who need to do a little data processing in their Python project, but I still recommend R and the tidyverse to those who need a serious tool of thought for analytics. Everything is so much more tidy and concise and intuitive and flexible. You can usually write code that directly expresses your high-level intent with a minimum of syntactic cruft. Full disclosure - the downside of modern R is…
Significant part of the work is massaging data and R sucks at that compared to Python. "if you want to do more than statistics, let’s say deployment and reproducibility, Python is a better choice." https://www.guru99.com/r-vs-python.html
Depends on what kind of data. R is almost always better at tabular, Python is probably usually better at unstructured.