Contents
R
or Python
Reference from zhihu and CSDN.
R
focuses on better user friendly data analysis, statistics and graphical models, whilePython
emphasizes productivity and code readability.R
is uncomplicated to apply complex formulas for all kinds of statistical tests and models are readily available and easily used, whilePython
is flexible for doing something novel like building websites.R
has a steep learning curve at start, you can easily learn advanced stuff once understand the basics. WhilePython
pays more attention to readability and simplicity, which makes its learning curve relatively low and gradual.R
andPython
are comparable in terms of packages, the former has comprehensive archive network called CRAN, while the latter has package index called PyPi.
The closer you are to statistics, research and data science, the more you might prefer R
; The closer you are to working in an engineering environment, the more you might prefer Python
.
Therefore, if you have enough time, you can learn both R
and Python
, but for different focuses. That is, use R
to conduct statistical tests, graph data and inspect large data, use Python
to write algorithm and deploy services.
Moreover, we can do lots of interesting projects efficiently by integrating Python
and R
with rpython and rpy2,
After all, the set of programming languages is perfect, which means it has no isolated points.
Learning Resources
Comprehensive Resources
Basis
- Advanced R and its GitHub.
- Cheat sheets.
- Books recommended by zhihu.