**DataScience+**, and kindly contributed to R-bloggers)

R is an open source programming language which is made from the dialect of S. R programming is very power when dealing with Data Manipulation and Statistical Modelling. R is widely used by data scientist and can solve complex problems containing datasets with statistical computing. R has thousands of packages which shows how powerful R can be.

R handles data analysis, statistical modelling, data visualization and many more. They include machine learning, data mining, data analysis, predictive modelling etc. R is commonly used by statisticians, data scientists, researchers and others who want to explore the meaning of their data.

I have created this series as a way to help others like me with learning the R programming language and start playing with data. Further down the road I want to introduce you with machine learning, data visualization and others but learning R is a great first step. I will be doing these tutorials using R and RStudio version 3.2.3. This list below will contain all R tutorials from the beginner to advance.

- History + Installation
- Data Types Part 1
- Data Types Part 2
- Data Types Part 3
- Data Types Part 4
- Missing Values
- Data Types Part 5
- Special Attribute
- Data Types Summary
- R Studio Appearance – Font Size, Type and Color

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**DataScience+**.

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