Ozgur, C., Colliau, T., Rogers, G., Hughes, Z., & Myer-Tyson, B. (2017). MatLab vs. Python vs. R. Journal of Data Science, 15(3), 355-372.

This paper expounds on R, Python and MatLab effectiveness. The paper has been written in such a way that it is suited for teaching in colleges and universities or any other institution of higher learning. It explains the basic knowledge of all three programming languages while trying to explain who uses the languages mostly. It also gives a list of the advantages and disadvantages of each of the three programming languages that are R, Python, and MatLab. It further discusses the advantages of one programming language over the other and vice versa.

This paper further explains the utilization of the three programming languages, analysis of one over the other and the comparison of a programming language to other programming languages. The examples given in this paper are real-life examples and where the analysis processes are explained in every programming language. Before the author finished writing this paper, he introduces “new” statistical methods where R is now being compared with SAS and SPSS accompanied by good examples that help us who are the readers of this paper broaden our understanding in the field of Data Analysis, Data Mining, and Big Data. At the very end of this paper, the authors of this paper give their experiences on all three programming languages.

Matloff, N. (2011). The art of R programming: A tour of statistical software design. No Starch Press.

In this paper, all that concerns R programming is discussed fully starting from running R program, simulations and doing math in R all the way to installation and usage of R packages and libraries. It has only majored in discussing R programming language and how it can be incorporated with other programming languages like Object Oriented Programming (OOP).

How I can describe this paper in a few words is that the paper has all the information concerning the R programming language. It explicitly explains the debugging facilities used in R and how these facilities are used in this programming language. If the problem has been not knowing how to interface R programming to other programming languages, the problem is solved in this paper where it explains how to interface R with C and C++ programming languages. It also introduces a package where R can be used from Python. This is achieved by installing a package called RPy and following the RPy syntax as explained in this paper.

Chun, W. (2001). Core python programming (Vol. 1). Prentice Hall Professional.

The Author of this paper Wesley J. Chun has precisely explained all that is concerned with the python programming language including definitions, History of python, the features that python programming language has, how to obtain python and he also added the installation procedure of python. The syntax of python and the objects used in python are correctly mentioned and examples are given in this paper that help the readers of this paper deepen their roots in Python programming language. This book is meant for starters, intermediates, and experts of python programming language suitable for teaching at colleges.

In this book, there are advanced topics in part two where other advanced programming languages are incorporated and can be integrated with Python. The programming languages that are discussed in the advanced topics of this book include web programming, graphical user interface programming with TKinter, Multithreaded programming, Network programming among others. In summary, this is the best paper for starting up in learning and understanding Python programming.

Jones, O., Maillardet, R., & Robinson, A. (2014). Introduction to scientific programming and simulation using R. Chapman and Hall/CRC.

The motivation behind the writing of this book is the rapid growth of R programming, its development, and the application of this programming language in a number of fields. The book illustrates the application of R programming in different disciplines of the education curriculum. The book is helpful and of use to the developers and programmers who use the R programming language in developing software. It also helps those doing data analysis and statistics.

The authors of this book have majored in simulation using R programming starting from the introductory part of R programming and later in the inner topics, this book describes how simulation can be done using R programming. In addition, the book has explained some key terms in statistics and data analysis also explaining how R programming is used in these other branches of science. The summary of this book is that it gives a clear understanding of how R programming is used in Data Analysis and Statistics.

Chambers, J. (2008). Software for data analysis: programming with R. Springer Science & Business Media.

This paper starts with an introductory part of the principles and concepts used in R. After the introduction, the paper now goes deeper to explain the usage of R programming and its evaluation. The examples that are given in this paper help the statisticians in getting to know how to plot different plots using R programming. In this chapter, the packages and libraries are explained then a guide on how to find and install these packages is given.

The authors of the book did just end there, they further give real-world examples on the application of R programming in businesses and industries. They explain that R programming has many businesses in gaining huge profits due to the statistical approach of R programming that helps them learn the trends in the market and make a quality decision and at times predict the likeliness of events in the future using R programming tools and techniques.

Sanner, M. F. (1999). Python: a programming language for software integration and development. J Mol Graph Model, 17(1), 57-61.

This paper starts by giving a definition of what python is and a brief history of python programming language. In its introductory part, it adds the python extensions, how python performs and finally how python programming language functions as a tool for integration. In the part where python is explained as a tool for integration, the author explains how the functionality of python is being implemented and how advantageous this is on the independence of the platform.

This paper brings in a new term used in the python programming language called Wrapping. Quoting from this paper, “this is a process where an existing C, C++ or Fotran code is accessed from the python programming language.” These existing codes can be re- implemented using python. Wrapping a code happens when just re-implementing it does not make sense. A better example is given in this paper to explain how to wrap code and how this wrapping occurs.

Lutz, M. (2013). Learning python: Powerful object-oriented programming. " O'Reilly Media, Inc.".

This paper is quite interactive since it starts with a question and answers session. The questions in this section try to answer all the questions or rather the frequently asked question concerning python programming language. These questions are answered in a way that even a first-time learner in python can understand and familiarize himself or herself with this programming language.