Shulou(Shulou.com)06/01 Report--

What are the functions of the R language that the editor will bring to you in this issue? the article is rich in content and analyzes and narrates it from a professional point of view. I hope you can get something after reading this article.

Some practitioners in the industry do not recognize the value of R language, they think that R language is only for statistical analysis.

The R language does provide comprehensive statistical analysis packages, such as CRAN,Bioconductor,Neuroconductor, and ROpenSci;, and provides excellent package management capabilities.

However, in the communication with friends in the computer field, R language has actually grown into a multi-functional programming language, and its function is far from limited to data analysis. However, many of the excellent features of the R language are not familiar to people outside the R language community.

I'm going to introduce you to those unknown but incredibly easy to use R language features.

1.R 's markup language can make repeatable Word and Powerpoint documents.

The rmarkdown package in the R language can make repeatable Word documents and Powerpoint slides with only a single line of YAML code to change.

two。 It takes only a few lines of code to build and run an interactive web application

A few lines of R code can generate an interactive web application. For example, if you use the flexdashboard package in R, you only need 36 lines of code to generate an interactive dynamic report to explore the correlation between your BMI index and the results of national health and nutrition check samples.

3. A few lines or even one line of R code can support the operation of network applications.

Another cool feature is that with the rsconnect package, the R language can also support the operation of web applications in just one or two lines of code. These applications can be supported either through their own servers or through cloud servers such as shinyapps.io.

4. By using dplyr/dbplyr in R language, almost all kinds of databases can be connected.

Using the dbplyr package, it is very convenient to connect to a variety of databases in R language, whether local or remote. This feature allows R language users to extract data from mainstream databases independently without worrying about the underlying database. The R language bigrquery package can also directly take advantage of BigQuery and other large-scale data stores.

5. Local or multiple different data stores, which can be manipulated using the same dblyr syntax in R language

When you learn how to use dplyr to convert data, local and remote databases and data stores can use the same code to operate. This feature simplifies and unifies the process of operating multiple databases and data languages.

6. You can use Keras and Tensorflow to train deep learning models.

With the keras package or TensorFlow interface, you can use the R language to learn pre-training or to develop new deep learning models.

7.R language can write and support application program interface (API)

Plumbr package can directly convert R function into network application interface (API), and can be easily integrated into downstream applications. If you also have Rstuodio Connect installed, these functions can be deployed as easily as web applications.

8. You can use R language to generate the interface of electronic games.

Not only network applications, R language can even generate the interface of electronic games. The nessy package can help you generate and deploy NES-style Shiny applications.

9. You can call Spark cluster directly through R language to analyze data.

Do you want to use large-scale data to train large and complex machine learning models? The R language sparklyr package helps you accomplish this task directly on a stand-alone or large Spark cluster.

10. You can learn R interactively in R language.

The R language swirl package can be used to generate interactive R language learning tutorials.

This paper introduces the functions of ten R languages, which are certainly not all the excellent features of R language. For example, you can also connect to AWS Polly to generate speech synthesis software, or use R to generate Shiny applications that respond to voice commands, or even write deep learning software to use acceleration data to judge Harry Potter spells. R is no longer just a programming language that can only be used for data analysis (although it is super strong in this respect! ), a mastery of the R language can open the door for you to develop practical and fun applications.

These are the functions of the R language shared by the editor. If you happen to have similar doubts, you might as well refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.

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