Well-known open source analysis tools include R language and what

Famous open source analysis tools include R language, python, Julia, etc. R language is an excellent tool for statistical computing and statistical graphics; Julia is an advanced and efficient programming language designed for technical computing; Python is an interpreted, object-oriented high-level programming language that can be used for scientific computing, Data mining and more.

The operating environment of this tutorial: Windows 7 system, Dell G3 computer.

Famous open source analysis tools include R language, python, Julia, etc.

Julia is a high-level and efficient programming language designed for technical computing. Its syntax is similar to other computing environments. It is designed for distributed computing and parallelism, and is best known for its high efficiency close to that of the C language.

According to the developer, “We hope that this open source language is as fast as C...as versatile as Python, as simple as R for statistics, as convenient as Perl for text processing, and as easy as Matlab. Linear algebra is as powerful, and it can connect various programs just like Shell."

Python was designed in the early 1990s by Guido van Rossum of the Dutch Society for Mathematics and Computer Science as a replacement for a language called ABC. Python provides efficient high-level data structures and enables simple and effective object-oriented programming. Python's syntax and dynamic typing, as well as the nature of an interpreted language, make it a programming language for scripting and rapid application development on most platforms. With the continuous update of the version and the addition of new language features, it is gradually used for independent, large-scale Project development.

The Python interpreter is easily extensible and can be extended with new functions and data types using the C language or C (or other languages ​​that can be called through C). Python can also be used as an extension programming language in customizable software. Python's rich standard library provides source code or machine code suitable for each major system platform.

Python syntax is very simple and has a wealth of modules and packages that can be used for scientific computing, data mining, deep learning, etc.

R language is a language and operating environment used for statistical analysis and graphics. R is a free, free, open source software belonging to the GNU system. It is an excellent tool for statistical computing and statistical graphics.

R, as a statistical analysis software, integrates statistical analysis and graphic display. It can run on UNIX, Windows and Macintosh operating systems, and is embedded with a very convenient and practical help system. Compared with other statistical analysis software, R has the following features:

• R is free software. This means it's completely free and open source. You can download any relevant installation programs, source codes, program packages and their source codes and documentation from its website and its mirrors. The standard installation file itself comes with many modules and built-in statistical functions. After installation, many commonly used statistical functions can be directly implemented.

• R is a programmable language. As an open statistical programming environment, the syntax is easy to understand and it is easy to learn and master the syntax of the language. And after learning it, we can program our own functions to extend the existing language. This is why its update speed is much faster than general statistical software, such as SPSS, SAS, etc. Most of the latest statistical methods and techniques are directly available in R.

• All R functions and data sets are stored in the package. Only when a package is loaded, its contents can be accessed. Some commonly used and basic program packages have been included in the standard installation file. With the emergence of new statistical analysis methods, the program packages included in the standard installation file are also constantly changing with version updates. In the other version of the installation file, the program packages already included are: base-R basic module, mle-maximum likelihood estimation module, ts-time series analysis module, mva-multivariate statistical analysis module, survival-survival analysis module, etc. wait.

• R is highly interactive. Except that the graphics output is in another window, its input and output windows are all performed in the same window. If there is an error in the input syntax, you will be prompted immediately in the window. It has a memory function for previously entered commands and can be used at any time. Reproduce, edit and modify to meet user needs. The output graphics can be directly saved as JPG, BMP, PNG and other image formats, and can also be directly saved as PDF files. In addition, it has good interfaces with other programming languages ​​and databases.

• If you join the R help mailing list, you may receive dozens of emails about R every day. You can discuss various issues with the world's leading experts in statistical computing. It can be said that it is the largest and most cutting-edge gathering place for statistician thinking in the world.

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