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I agree, I like R and python for certain things. (python for most things and R for statistics and visualization). However, I really don't agree with the "X wor

I agree, I like R and python for certain things. (python for most things and R for statistics and visualization). However, I really don't agree with the "X works best for me but Y might work better for someone else so let's not fight" argument. Doesn't that imply that the question "Which is better, X or Y"? shouldn't be asked? On the contrary, I think that's often an important question when you need to practically get stuff done, choose between libraries, etc, and I want to know people's opinions.

dragonwriter 11y ago
> Doesn't that imply that the question "Which is better, X or Y"? shouldn't be asked? No, it just implies that there is, in the domain in which it is applied, no objectively correct answer.
- baldfat 11y ago
  Just be warned I named my son Soren for the founder of Existential Philosophy Soren Kierkegaard. There is no spoon.
baldfat 11y ago
Here is my opinion on Python and R. I used Pandas and switched to R. 1) Python 0 based as opposed to 1 based is big to me. I don't want to always have to minus on on columns to call them. 2) I much prefer Hadley Wickham's syntax to Pandas which closely follows it, but R piping with %>% is amazing with library magritr. Using dplyr and stringr, tidyr, rvest, httr, luberdate are awesome and consistant. 3) In R I can use dplyr whcih is fast or even use data.table for even more speed that uses a sql like syntax. In Python your choices are limited in comparison to R for tools. 4) HUGE and the reason I switched to R. I can output my graphics into a editable PowerPoint slide. My managers and company doesn't know that there are anything besides MS Office and I can give them slides that they can fiddle with for their own presentations. 5) RMarkDown and knitr for outputing reports in Word (UGH but ti works great), PDF or , LaTex or HTML is fantastic. Reproducable output is great. If I want I can also use Project Jupyter (IPython's new name in next version) with a R kernel. 6) Tools - I got RStudio installed on my work computers, and my personaly server has RStudio Server installed. This is what I have settled into using because it is the best statistic programing tool out there. Works better than Jupyter/IPython for 90% of the time, though I love Love LOVE Jupyter/IPython. 7) The community. R's community is fantastic [http://www.r-bloggers.com/ http://www.r-bloggers.com/] just look at all the daily information, new libraries and tutorials. The books are great in R, (I really enjoyed the Python Pandas Book by Wesly) Hadley Wickham's Newest book is avilable in Physical form for purchase and free on the internet [http://adv-r.had.co.nz/ http://adv-r.had.co.nz/] 8) Tutorials - Datacamp, Swirl in R tutorial, Coursera Courses, etc. are great and have just about anything you would like to learn. 9) The libraries and install system with Cran installs [http://cran.r-project.org/ http://cran.r-project.org/] and devtools to install GitHub libraries install and updated on your system [https://github.com/hadley/devtools https://github.com/hadley/devtools] I could go further but those are my opinions to why I like R so much.

dragonwriter 11y ago

> Doesn't that imply that the question "Which is better, X or Y"? shouldn't be asked? No, it just implies that there is, in the domain in which it is applied, no objectively correct answer.

baldfat 11y ago
Just be warned I named my son Soren for the founder of Existential Philosophy Soren Kierkegaard. There is no spoon.

baldfat 11y ago

Here is my opinion on Python and R. I used Pandas and switched to R. 1) Python 0 based as opposed to 1 based is big to me. I don't want to always have to minus on on columns to call them. 2) I much prefer Hadley Wickham's syntax to Pandas which closely follows it, but R piping with %>% is amazing with library magritr. Using dplyr and stringr, tidyr, rvest, httr, luberdate are awesome and consistant. 3) In R I can use dplyr whcih is fast or even use data.table for even more speed that uses a sql like syntax. In Python your choices are limited in comparison to R for tools. 4) HUGE and the reason I switched to R. I can output my graphics into a editable PowerPoint slide. My managers and company doesn't know that there are anything besides MS Office and I can give them slides that they can fiddle with for their own presentations. 5) RMarkDown and knitr for outputing reports in Word (UGH but ti works great), PDF or , LaTex or HTML is fantastic. Reproducable output is great. If I want I can also use Project Jupyter (IPython's new name in next version) with a R kernel. 6) Tools - I got RStudio installed on my work computers, and my personaly server has RStudio Server installed. This is what I have settled into using because it is the best statistic programing tool out there. Works better than Jupyter/IPython for 90% of the time, though I love Love LOVE Jupyter/IPython. 7) The community. R's community is fantastic [http://www.r-bloggers.com/ http://www.r-bloggers.com/] just look at all the daily information, new libraries and tutorials. The books are great in R, (I really enjoyed the Python Pandas Book by Wesly) Hadley Wickham's Newest book is avilable in Physical form for purchase and free on the internet [http://adv-r.had.co.nz/ http://adv-r.had.co.nz/] 8) Tutorials - Datacamp, Swirl in R tutorial, Coursera Courses, etc. are great and have just about anything you would like to learn. 9) The libraries and install system with Cran installs [http://cran.r-project.org/ http://cran.r-project.org/] and devtools to install GitHub libraries install and updated on your system [https://github.com/hadley/devtools https://github.com/hadley/devtools] I could go further but those are my opinions to why I like R so much.