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Pandas 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 serio

Pandas 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.

jmount 5y ago
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 https://github.com/WinVector/data_algebra .
- civilized 5y ago
  I like the general direction of this. I do want to note that "there are many things for X in language Y" isn't necessarily a positive thing. It often means the community lacks the clarity of thinking or will to converge on one excellent product. Instead there are lots of okayish things each developed by a single person or handful of people.
deleted 5y ago
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d0mine 5y ago
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 https://www.guru99.com/r-vs-python.html
- civilized 5y ago
  Depends on what kind of data. R is almost always better at tabular, Python is probably usually better at unstructured.
hnhg 5y ago
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.
- civilized 5y ago
  R is a mixed bag. Base R is like PHP - an organically grown mishmash of stale, ugly, inconsistent conventions, beloved only by people who have been trained in it or used it for decades. But the tidyverse has an extremely thoughtful API that is easier to learn and use than anything else in the data science world.

jmount 5y ago

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 https://github.com/WinVector/data_algebra .

civilized 5y ago
I like the general direction of this. I do want to note that "there are many things for X in language Y" isn't necessarily a positive thing. It often means the community lacks the clarity of thinking or will to converge on one excellent product. Instead there are lots of okayish things each developed by a single person or handful of people.

deleted 5y ago

[deleted]

d0mine 5y ago

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 https://www.guru99.com/r-vs-python.html

civilized 5y ago
Depends on what kind of data. R is almost always better at tabular, Python is probably usually better at unstructured.

hnhg 5y ago

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.

civilized 5y ago
R is a mixed bag. Base R is like PHP - an organically grown mishmash of stale, ugly, inconsistent conventions, beloved only by people who have been trained in it or used it for decades. But the tidyverse has an extremely thoughtful API that is easier to learn and use than anything else in the data science world.