GitHub - akaidkhan/Data_Science_with_R: Introduction to R R is a programming language, which is an object oriented language created by Statisticians, R provides objects, operators and functions that allow the user to explore, model and visualize data. R is a Programming language Developed at AT&T Bell Lab. It is an open source free language, allowing anyone to use and modify it. R is licensed under the GNU General Public License, with copyright held by The R Foundation For Statistical Computing. It has no need to pay any subscription charges R has a huge active community member. If you have any question about any function any library you can Google it and you would get a proper answer and right the way. As it is an open source language, you, me and lots of Data Scientist, they actually built in all those, inbuilt function and they upload it in a website called CRAN and then you can download all those packages. Over 7800 packages listed on CRAN, here we listed some of the most powerful and commonly used in R packages. R is a cross platform. R can run in different kind of operating system and different hardware. Generally, it is used on GNU/Linux, Macintosh, and Microsoft Windows and running on both 32 and 64-bit processor. R is mainly used for Statistical Analysis and Analytics Purpose, you might be thinking why to learn again another language if you already know many programming languages like JAVA or other programming languages, and think why do you need the language because R is mainly used for all those statistical Analysis and that’s why you should learn the language R. you would understand after doing this course it is actually easy to interpret. R is the leading tool for statistics and data analysis, machine learning as well as. The programming language is more than a statistical package, you can build your own objects, functions, and packages. It is easy to use, the coding style is quite easy. R enables you to interact with many data sources: ODBC -compliant databases (Excel, Access). R also can handle CSV files, SAS, and SPSS, XML and lots of other different files as well. Similarly, it can create a very good visualization. It can produce graphics output in PDF, JPG, PNG and SVG formats and table output for LATEX and HTML. It has a lot of inbuilt functions(packages & Libraries) and the results are also easy to interpret and that’s why lots of industries are using R, it is not about the big or small. Lots of companies like Microsoft, Google are using R actively. It has a big reason, it is free and you can do POC out there. So, be confident about the fact that you are going to learn R and it has huge popularity and your market value is always higher if you know R in Data Science

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 40 Commits
Algorithm For data Science		Algorithm For data Science
R Basic Proggraming		R Basic Proggraming
R Data Manipulation		R Data Manipulation
R Data Structure		R Data Structure
R Data Visualization		R Data Visualization
R Import Export		R Import Export
.gitignore		.gitignore
Data_Science_with_R.Rproj		Data_Science_with_R.Rproj
_config.yml		_config.yml

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Introduction to R R is a programming language, which is an object oriented language created by Statisticians, R provides objects, operators and functions that allow the user to explore, model and visualize data. R is a Programming language Developed at AT&T Bell Lab. It is an open source free language, allowing anyone to use and modify it. R is …

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