Advantages and disadvantages of R language

Big data R language rapid development and practice


Why R? Rich resources: covers almost all methods in data analysis for a variety of industries. Good expansibility: very convenient to write functions and packages, cross-platform, can be competent for complex data analysis, drawing beautiful graphics. Complete help system: each function has a uniform format of help, running instances. GNU software: free, software itself and package source code public.

R Comparison with other statistical software SAS: fast speed, a large number of statistical analysis modules, poor scalability, expensive. SPSS: Complex user graphical interface, easy to learn, but very difficult to program. Splus: Runs the S language, has a complex interface, is fully compatible with R, and is expensive. The user needs to be familiar with commands: working with code, memorizing common commands.

Memory: All data processing is carried out in memory, which is not suitable for processing large scale data.

Slightly slower: just-in-time compilation, about 1/20th as fast as C.

R is still much more efficient than clicking a mouse.

Advantage:

  • Can complete most of the data related analysis, statistics, mining, visualization and other work
  • Can work with big data solutions like Hadoop

Disadvantage:

  • The pesky assignment symbol <-
  • Garbled characters always come up when it comes to Chinese

Brief introduction:

R language grammar is easy to understand, it is easy to learn and master the language grammar. And once we learn it, we can write our own functions to extend existing languages. This is why it updates much faster than general statistical software such as SPSS, SAS, etc. Most of the latest statistical methods and techniques are available directly in R.

As the most popular data mining development language in the world, R language attracts more and more data analysis enthusiasts with its unique openness, high scalability and top graphics functions.


More excellent courses:

7 days to play cloud server

Redis version of the cloud database using tutorial

Play cloud storage object storage OSS introduction

Ali Cloud CDN use tutorial

Load Balancing Introduction and Product Usage Guide



Official website of Ali Yun University (Official website of Ali Yun University, Innovative Talent Workshop under cloud Ecology)