R – a Global Sensation in Data Science

The second part of the breaking-the-ice brief introduction in R scripting for humanity scholars. Devoted mostly to graphics. See also supplementary materials at GitHub: https://github.com/alexei-kouprianov/Breaking-the-ice-with-R Original version was uploaded on February 12, 2022.

The previous chapter presented the six phases of the Data Analytics Lifecycle. • Phase 1: Discovery • Phase 2: Data Preparation • Phase 3: Model Planning • Phase 4: Model Building • Phase 5: Communicate Results • Phase 6: Operationalize

Social Research Foundation, 2019

Today's researchers, business organizers depend upon facts and figures. It has been frequently observed that a vast amount of data surrounds them. Data is treated as a raw material of any research, business, or any other developmental activates. Currently, data has become an essential component of businesses, industries, research organizations, and technological development. We are living in an era of Big data. The volume of data used is rapidly growing every second. Data visualization helps people to the recognized significance of data by summarizing and presenting simply. Data visualization is a process to describe massive data in an accessible, understandable, and straightforward format. A researcher must understand the importance of data visualization and its relationship to research. In the present chapter, we introduce data and visualization of data, and also providing some techniques for visualization of data using statistical software R.

The popularity of R is increasing in national statistical offices not only for simulation tasks. Nowadays R is also used in the production process. A lot of new features for various tasks in official statistics have been developed over the last years and these features are freely available in the form of add-on package.

In the last decade, open source programming technology is widely used among statisticians for developing a new statistical software and data analysis. This is R software environment and the main objective of this paper is to underline the importance of R for statistical computations, data analysis, visualization and applications in various fields. Regarding to this, the paper is primarily intended for people already familiar with common statistical concepts. Thus the statistical methods used to illustrate the R performance are not explained in detail. The main intention is to offer an overview to get started, to motivate beginners by illustrating the flexibility of R, and to show how simply it enables the user to carry out statistical computations.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2020

SWANSTAT is a user-friendly web application and free license that developed from the R programming language using shinydashboard Package. This research aims to create SWANSTAT was to streamline the routine workflow of data analysis so that users who are unfamiliar with R can perform the analysis interactively in a web browser with a cloud computing using a shiny server. The software development method used in this study is the SDLC with the waterfall model. The result of this research is the SWANSTAT software was developed using R by combining various packages and can be accessed online through various types of browsers on http://apps.swanstatistics.com. Besides, SWANSTAT consist of various features including the best visualization, the basis of statistical methods, help documents and tutorials. This research will continuously develop this application by enriching the latest statistical method, as well as improving the quality of features for data science needs. Keywords: SWANSTAT R programming language Shiny server Data science tools Shinydashboard package This is an open access article under the CC BY-SA license.