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What is the R language?
R language, also known as R language, is a highly liberalized programming language that is widely used in fields such as statistics, data science, and machine learning. The R environment provides a variety of free packages, enabling users to perform fast and effective data analysis and research. Since R is an open source software, users can download and use it for free, which makes R widely used in academic research, education, and non-profit organizations.
The origin of the R language
The R language was originally developed by New Zealand statisticians Ross Ihaka and Robert Gentleman in 1993, when they wanted to create an open source statistical software similar to the S language to provide a wider range of statistical methods and tools. The S language is a commercial product that requires a paid license, so Ihaka and Gentleman hope to create a free, open-source alternative so that more people can easily perform statistical analysis. This is the origin of the R language.
What can the R language be used for?
Here are some things you can do with the R language:
- Data cleaning and preprocessing: R language can be used to process huge data, remove missing values, outliers, duplicate values, etc., to ensure the completeness and accuracy of the data.
- data visualization: R language provides a variety of drawing and visualization tools that can present data graphically, such as scatter plots, histograms, heat maps, etc., to help users better understand and analyze data.
- Statistical Analysis: The R language provides a variety of statistical analysis tools, such as hypothesis testing, variance analysis, regression analysis, etc., which are convenient for users to perform statistical analysis and obtain patterns and trends in the data.
- machine learning: R language provides a variety of machine learning tools, such as supervised learning, unsupervised learning, deep learning, etc., which can be used for model training and prediction.
What are the advantages and disadvantages of the R language?
advantage:
- Strong statistical analysis ability: R language provides a variety of statistical analysis tools, including traditional statistics, machine learning, deep learning, etc., which can help users perform complex statistical analysis.
- open source: R language is an open source programming language, all R language packages are completely free, and anyone can use it freely.
- Extensive kits and tools: R language has a huge package library (Packages), all packages can be found inCRAN (Comprehensive R Archive Network)to download. So far, there are more than 16,000 packages available for download on CRAN, and this number is still increasing.
- Highly free programming environment: R language allows users to write programs freely, so that users can write programs according to their own needs and specific problems.
shortcoming:
- difficult to learn: For those who have no programming experience, it may take a long time to learn.
- Computer equipment consumes a lot: Since the R language is an interpreted language, it may consume a large amount of computer memory and computing resources when processing large data sets.
- Program development efficiency is low: Compared with some other programming languages, such as Python, Java, etc., the development efficiency of R language is relatively low. The main reason is that the syntax of R language is relatively complicated and cumbersome. In addition, the R language is mainly optimized for fields such as statistical analysis and data science, and may face some difficulties in program development in other fields.
Why learn R language?
There are many reasons to learn R language, here are a few main ones:
- big data analysis: In today's digital age, we can easily collect a large amount of data. R analysis can be used to quickly process and analyze these big data, so as to discover the hidden information and trends.
- Academic Research: R is a commonly used programming language in academia because it provides a wealth of statistical analysis and visualization tools that can help researchers perform various analyses.
- business analysis: R is an open source software, so using it for business analysis can reduce costs, for example, it can be used for various business sales forecasts, product analysis, market research, etc.
- education and learning: R is a free programming language that is great for teaching and learning. Because the R language is widely used in statistics, data science, and machine learning, many universities have begun to incorporate the R language into statistics and data science courses.
How to install R?
- Download the installation file (R download): go toR Official SiteDownload the corresponding installation file, and select the version suitable for the computer operating system to download.
- Install R (R install): Execute the downloaded installation file and follow the prompts to install.
3. Install RStudio: Optional during installation of RInstall RStudio, RStudio is a very popular R compiler and integrated development environment. Windows is very friendly for beginners, and users are strongly recommended to install it.
4. start R: After the installation is complete, you can find the shortcut of R in the computer, click it to start R.
5. installation kit:R packages can be installed through R Windows. To install the package in R you can useinstall. packages()function, for example, if you want to install the dplyr package, you can execute the following code:
install.packages("dplyr")RStudio installation and introduction
It is mainly divided into four areas, which are R script (code writing area), Environment (view file and variable area), Console (R code execution and result area) and file archive output area.
Getting started with basic operations
- Click on File,Select R script in New Fileto create a new interface for writing code.
- Write code in R script,Click [Run] on the upper right, or the shortcut key "Ctrl+Enter" to run the code.
- Once the work is done, theCode Save (Save)stand up.
