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R Programming Tutorial: The Ultimate Guide -helpcodes.me

 

R Programming Tutorial:


R Programming Tutorial: The Ultimate Guide R Programming Tutorial: R Programming Tutorial: The Ultimate Guide Hello , I am Garry Raut , 'machine learner and deep learner ' Today we will Learn all Programming Basic of R languages. Download and Install Git Bash and Git version 1.8.7 $ git clone https://github.com/coresponential/R-Ultimate.git create a new folder called 'R-Ultimate' and cd into it. $ cd R-Ultimate $ make Install all R and R Text and R Math packages Install R and R Text and R Math $ sudo apt-get install libcurl4-openssl-dev gcc g++ libcurl5 libsmb1-dev sqlite3-dev $ sudo apt-get install libjpeg-turbo-dev libjpeg8-dev libpng12-dev $ sudo apt-get install libtiff0.6 libtiff1-dev libtiff2-dev libxml2-dev libxsl1-dev $ sudo apt-get install git $ git clone https://github.com/coresponential/R-Ultimate.git Open R File $ wget http://www.r-site.com/install.sh Edit the sha512sum line and use '".$name. Data Types An-Int: Number data. Int ∞ Bin: Binary String data. [ 2 , "world" , [ 1 , "Bob" ]] Double: Double ∞ Nil: Nil data. [ 0 ] List: List Data Structure ( null ) [1] Ratio: Ratio data. [ 2 : 1 , 3 : 4 , 8 : 9 ] Union: Union of two Data Types data. [ "Bob" , "Bill" ] Many-to-One: Many to One data. Data ∞ ∞ ∞ ∞ One-to-Many: Many to Many data. Data ∞ ∞ ∞ ∞ ∞ ∞ Monad: Monad is a Functor type for returning some type. Return : List Data Structure ( [] ) → list data. [] Bind: Bind one value to the variables of another data. Data ( "Bob" ) → Data ( "Bill" ) Commands Suppose we want to compute the product of two numbers . We would need the function . It takes two arguments. Here is how we calculate the product of two Numbers by using R programming language. Operators = Most of the Programming is about Numbers Common Operators Normalization Division Comparison G for Greater than M for Less than Less / Greater / Less than Operator Exceptions Using New/Less operator to give the Value of Comparison Operators Before we started to write coding we need to Normalize the data . we will follow using Normalization Normalize the Data function. Now I am going to show you why should you Normalize the data Histogram Plotting A Simple Histogram Plotting If you want to plot a histogram just you click below Create Graph G.. A simple Histogram plot Ranges Once the data has been Normalized , G() is run , you can see the Example Of Normalized Data Plotting : G() uses the G() function which Normalizes the data and takes the data and outputs a Graph. Conditional Statements if.then.else. while.then.else. for.then.else. for loop. Listing 1 : THE FOR AND WITHOUT loop Below, we can observe how the line 'if.then.else. is executed. # List of Function to run every time a condition is true. @function @if @else # Register another command as if.then.else # The following line is the main function of the program. @myprogram R gives us a lot of power. The following picture is an example of getting the choices in a spreadsheet of an artist and clicking on a choice. You can have a list of variables in your head (note on keyboard). All this math and details are beyond beginners. You can find many R tutorials online. Functions The function is a programming language, and we will know them all. It's very easy to create something complicated and complex, but this stuff is essential to understand the R programming language. There are many functions in R - like trig functions, cubic or log function, volume proportional functions and so on. Features Functions are your friend, if you can understand them, you can do anything. Statistics Every function can be tested with the statistics function. Loops When you enter a loop , you will see below table : Function called in this way Number of loops function = 1 loop = 1 function = 2 loop = 2 Note: this is usage on dot . For example. If you have following file ; #file.r #*note*: copy out this file run.library('r_values') library('tesseract') seq <- function(c){ if(seq( 0) == '*' || seq(0) == '.' || seq(0) == '. Data Manipulation Graphs Stable Frequency Scaling Non-traditional Data Structures Dictionaries Tree Structures Transforms Graph Algorithms Discrete Cosine Function Adventures of Kernels Algorithmic Graphs Matrix Algorithms Boolean Algorithms Foundation of Neural Networks Fuzzy Neural Networks Symbolic Motifs Vector Algorithms Scalable Vector Spaces Tangential Transforms Loops Iterations Python Language is not Lacking in R Connection This was a purely write to say, There is now a Python Language Module for R. Functions like WITH tf_square = as.table(tf.factor(2) + '.,') as.matrix; DATA().append("load",as.character(tf_square)); WITH tf_square WITH tf_square as. Data Analysis 1. Download Google Trends Data Take a look at the trend of some global events as a basis of the information to learn different questions. 2. Data and Pdf from this dataset it is possible to visualize and get important data about the specific topic. Example: It is possible to know the percentage of people who have higher education. Also we can use it to understand the impact of a given subject in different countries 3. Statistics( R can handle the spread of many statistical data from different sources) 4. Calculate the Weighted Deviation of Vector 5. Probability and Data Visualization 6. Know R regular expressions 7. A Plain R Tutorial A Simple R Tutorial-A Series of Problem Solving Activities R v.3. Conclusion In R programming tutorial , we will cover: R Text Basics : A basic introduction on the mathematical and statistical concepts of R. : A basic introduction on the mathematical and statistical concepts of R. R Dictionary : A very simple but good dictionary. : A very simple but good dictionary. Functions : We will take the basic knowledge on using the functions in R language. : We will take the basic knowledge on using the functions in R language. Basic math functions : Mathematical functions such as sign , fillRule , log and cubeRule. : Mathematical functions such as , and Experiments : We will learn the experiments with R. : We will learn the experiments with R. Transforms : Transform the data with transformations and join the data with joinTable .


Hello , I am Garry Raut , 'machine learner and deep learner ' Today we will Learn all Programming Basic of R languages.


Download and Install

Git Bash and Git version 1.8.7 $ git clone https://github.com/coresponential/R-Ultimate.git create a new folder called 'R-Ultimate' and cd into it. $ cd R-Ultimate $ make Install all R and R Text and R Math packages Install R and R Text and R Math $ sudo apt-get install libcurl4-openssl-dev gcc g++ libcurl5 libsmb1-dev sqlite3-dev $ sudo apt-get install libjpeg-turbo-dev libjpeg8-dev libpng12-dev $ sudo apt-get install libtiff0.6 libtiff1-dev libtiff2-dev libxml2-dev libxsl1-dev $ sudo apt-get install git $ git clone https://github.com/coresponential/R-Ultimate.git Open R File $ wget http://www.r-site.com/install.sh Edit the sha512sum line and use '".$name.


Data Types

An-Int: Number data. Int ∞ Bin: Binary String data.

[ 2 , "world" , [ 1 , "Bob" ]]

Double: Double ∞ Nil: Nil data. [ 0 ]

List: List Data Structure ( null ) [1]

Ratio: Ratio data. [ 2 : 1 , 3 : 4 , 8 : 9 ]

Union: Union of two Data Types data. [ "Bob" , "Bill" ]

Many-to-One: Many to One data. Data ∞ ∞ ∞ ∞

One-to-Many: Many to Many data. Data ∞ ∞ ∞ ∞ ∞ ∞

Monad: Monad is a Functor type for returning some type.

Return : List Data Structure ( [] ) → list data. []

Bind: Bind one value to the variables of another data.

Data ( "Bob" ) → Data ( "Bill" )

Commands Suppose we want to compute the product of two numbers . We would need the function . It takes two arguments. Here is how we calculate the product of two Numbers by using R programming language.


Operators

= Most of the Programming is about Numbers Common Operators Normalization Division Comparison G for Greater than M for Less than Less / Greater / Less than Operator Exceptions Using New/Less operator to give the Value of Comparison Operators Before we started to write coding we need to Normalize the data . we will follow using Normalization Normalize the Data function. Now I am going to show you why should you Normalize the data Histogram Plotting A Simple Histogram Plotting If you want to plot a histogram just you click below Create Graph G.. A simple Histogram plot Ranges Once the data has been Normalized , G() is run , you can see the Example Of Normalized Data Plotting : G() uses the G() function which Normalizes the data and takes the data and outputs a Graph.


Conditional Statements

if.then.else. while.then.else. for.then.else. for loop. Listing 1 : THE FOR AND WITHOUT loop Below, we can observe how the line 'if.then.else. is executed. # List of Function to run every time a condition is true. @function @if @else # Register another command as if.then.else # The following line is the main function of the program. @myprogram R gives us a lot of power. The following picture is an example of getting the choices in a spreadsheet of an artist and clicking on a choice. You can have a list of variables in your head (note on keyboard). All this math and details are beyond beginners. You can find many R tutorials online.


Functions

The function is a programming language, and we will know them all. It's very easy to create something complicated and complex, but this stuff is essential to understand the R programming language. There are many functions in R - like trig functions, cubic or log function, volume proportional functions and so on. Features Functions are your friend, if you can understand them, you can do anything. Statistics Every function can be tested with the statistics function.


Loops

When you enter a loop , you will see below table : Function called in this way Number of loops function = 1 loop = 1 function = 2 loop = 2 Note: this is usage on dot .

For example. If you have following file ;


#file.r #*note*: copy out this file

run.library('r_values') library('tesseract') seq <- function(c)

{ if(seq( 0) == '*' || seq(0) == '.' || seq(0) == '.}


Data Manipulation

Graphs Stable Frequency Scaling Non-traditional Data Structures Dictionaries Tree Structures Transforms Graph Algorithms Discrete Cosine Function Adventures of Kernels Algorithmic Graphs Matrix Algorithms Boolean Algorithms Foundation of Neural Networks Fuzzy Neural Networks Symbolic Motifs Vector Algorithms Scalable Vector Spaces Tangential Transforms Loops Iterations Python Language is not Lacking in R Connection This was a purely write to say, There is now a Python Language Module for R. Functions like WITH tf_


square = as.table(tf.factor(2) + '.,') as.matrix;

DATA().append("load",as.character(tf_square))

; WITH tf_square WITH tf_square as.


Data Analysis

1. Download Google Trends Data Take a look at the trend of some global events as a basis of the information to learn different questions. 2. Data and Pdf from this dataset it is possible to visualize and get important data about the specific topic. Example: It is possible to know the percentage of people who have higher education. Also we can use it to understand the impact of a given subject in different countries 3. Statistics( R can handle the spread of many statistical data from different sources) 4. Calculate the Weighted Deviation of Vector 5. Probability and Data Visualization 6. Know R regular expressions 7. A Plain R Tutorial A Simple R Tutorial-A Series of Problem Solving Activities R v.3.


Conclusion

In R programming tutorial , we will cover: R Text Basics : A basic introduction on the mathematical and statistical concepts of R. : A basic introduction on the mathematical and statistical concepts of R. R Dictionary : A very simple but good dictionary. : A very simple but good dictionary. Functions : We will take the basic knowledge on using the functions in R language. : We will take the basic knowledge on using the functions in R language. Basic math functions : Mathematical functions such as sign , fillRule , log and cubeRule. : Mathematical functions such as , and Experiments : We will learn the experiments with R. : We will learn the experiments with R. Transforms : Transform the data with transformations and join the data with joinTable .

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