RStudio the best for statistical data
June 04, 2018
RStudio the best for statistical data
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with RStudio
Basically, I can simplify the steps when updating a database, and reduce working time. Once it is scheduled as a statistical platform, it offers me all the techniques of data analysis. In addition to programming new methods and routines in an easy and robust way, I can do any database immediately. I can perform all the data analysis and even read files of different formats.
Pros
- In the first place, because it is a language with a complex learning curve, but very robust and effective for the handling of statistical data, for developers, specialized in these languages, it can be simple.
- R is a programming language in constant evolution and has extensive documentation, ease in data preparation, with this technique is very simple, largely because it automates many processes by programming sequences.
- R works with any type of file, R is a language that allows the implementation of additional packages that provide a great capacity of data management, it is open source and free.
Cons
- RStudio facilitates the work when entering RStudio, we see the screen divided into four windows, that multiplatform R, works on Mac, Windows and UNIX Numbers.
- This means that you can work with your data, figures, analysis and, most importantly, with your instructions. It is free software, there is a large community of volunteers working to update it.
- Allowing you to face specific problems. Programs like R-studio, Java GUI for R, R-commander, RKWard, among others, and with more than 6000 packages indexed in CRAN, Biocoductor, GitHub and R-Forge.
- R has a vast [amonut] help documentation, description of packages and functions. It is difficult to find specific information at any given time.
- R is an online programming language of command, which does not involve the use of menus like other statistical programs, this makes many people who are not familiar with programming
- It is very difficult to migrate to R. But this is more than a disadvantage, because programming will better understand the basis of statistics and data analysis, compared to other people who do not use R.
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