Introduction to computing_using_r

Motivation and ObjectiveFundamentals

Further Reading and ReferencesThank You

Introduction to Computing Using R

Parthasarathi Edupally

CRISIL, Risk & Analytics

Advanced Bootcamp, 2014

Parthasarathi Edupally Introduction to Computing Using R



Outline

1 Motivation and ObjectiveWhat is this module about ?Why learn R ?

2 FundamentalsLanguage FoundationsFunctionsDataVocabulary

3 Further Reading and ReferencesAdvanced TopicsReferences

4 Thank You




What is this module about ?Why learn R ?

What is this module about ?

Learn to use computational resources to solve problemsAn introduction to R statistical softwareDeep understanding of language fundamentals than lot oflanguage specific detailsA good starting point to learn scientific computing inquantitative researchNo cookbook approach to teach a programming languageJust a concise overview, have to go through resourcesmentioned for thorough understanding.






Learn to use computational resources to solve problems

An introduction to R statistical softwareDeep understanding of language fundamentals than lot oflanguage specific detailsA good starting point to learn scientific computing inquantitative researchNo cookbook approach to teach a programming languageJust a concise overview, have to go through resourcesmentioned for thorough understanding.






Learn to use computational resources to solve problemsAn introduction to R statistical softwareDeep understanding of language fundamentals than lot oflanguage specific details

A good starting point to learn scientific computing inquantitative researchNo cookbook approach to teach a programming languageJust a concise overview, have to go through resourcesmentioned for thorough understanding.






Learn to use computational resources to solve problemsAn introduction to R statistical softwareDeep understanding of language fundamentals than lot oflanguage specific detailsA good starting point to learn scientific computing inquantitative research

No cookbook approach to teach a programming languageJust a concise overview, have to go through resourcesmentioned for thorough understanding.






Learn to use computational resources to solve problemsAn introduction to R statistical softwareDeep understanding of language fundamentals than lot oflanguage specific detailsA good starting point to learn scientific computing inquantitative researchNo cookbook approach to teach a programming languageJust a concise overview, have to go through resourcesmentioned for thorough understanding.





Why learn R ?

This is why you should :Its open source, anyone can replicate your resultsA massive set of packages for statistical analysis, machinelearning etcSpecially designed for statistics and Data analysis withfeatures like missing values, Dataframes, subsetting etcStrong foundations in functional programmingDesinged to connect to low level languages for highperformance

Some drawbacks :Most of the code is written in haste to solve a pressingproblem at hand, so code is less elegant, less faster andless easier to understand.It is not particularly fast programming language.





Why learn R ?

This is why you should :Its open source, anyone can replicate your resultsA massive set of packages for statistical analysis, machinelearning etcSpecially designed for statistics and Data analysis withfeatures like missing values, Dataframes, subsetting etc

Strong foundations in functional programmingDesinged to connect to low level languages for highperformance






Why learn R ?







Why learn R ?


Some drawbacks :

Most of the code is written in haste to solve a pressingproblem at hand, so code is less elegant, less faster andless easier to understand.It is not particularly fast programming language.





Why learn R ?






Language FoundationsFunctionsDataVocabulary

Expressions

Most often when we write code we are writing anexpressionExpression describes a computation and evaluates to avalueIn Math - addition, division etcAll expressions can be represented by a function notation -It is the most general representationTypes of expressions :

primitive expression – Numbers, Names, Stringscall expressions – operator(op1, op2)

<Demo>





Expressions

Most often when we write code we are writing anexpressionExpression describes a computation and evaluates to avalue

In Math - addition, division etcAll expressions can be represented by a function notation -It is the most general representationTypes of expressions :


<Demo>





Expressions

Most often when we write code we are writing anexpressionExpression describes a computation and evaluates to avalueIn Math - addition, division etcAll expressions can be represented by a function notation -It is the most general representation

Types of expressions :primitive expression – Numbers, Names, Stringscall expressions – operator(op1, op2)

<Demo>





Expressions

Most often when we write code we are writing anexpressionExpression describes a computation and evaluates to avalueIn Math - addition, division etcAll expressions can be represented by a function notation -It is the most general representationTypes of expressions :


<Demo>





Abstraction using Names and User-defined functions

When we write code we are building complex system forcomputationAbstraction is an important idea in designing complexsystemsNaming - Simplest means of abstraction, bind names tovaluesUser-defined function :more powerful means ofabstraction, binds names to expressions






When we write code we are building complex system forcomputation

Abstraction is an important idea in designing complexsystemsNaming - Simplest means of abstraction, bind names tovaluesUser-defined function :more powerful means ofabstraction, binds names to expressions






When we write code we are building complex system forcomputationAbstraction is an important idea in designing complexsystems

Naming - Simplest means of abstraction, bind names tovaluesUser-defined function :more powerful means ofabstraction, binds names to expressions






When we write code we are building complex system forcomputationAbstraction is an important idea in designing complexsystemsNaming - Simplest means of abstraction, bind names tovalues

User-defined function :more powerful means ofabstraction, binds names to expressions






When we write code we are building complex system forcomputationAbstraction is an important idea in designing complexsystemsNaming - Simplest means of abstraction, bind names tovaluesUser-defined function :more powerful means ofabstraction, binds names to expressions





Statements

They are used to perform an action, they don’t evaluateto valueThere can be conditional and iterative statementsConditional statements:

if-elseif-elseIterative statements:

for() {}while() {}

<Demo>





Statements

They are used to perform an action, they don’t evaluateto value

There can be conditional and iterative statementsConditional statements:


for() {}while() {}

<Demo>





Statements

They are used to perform an action, they don’t evaluateto valueThere can be conditional and iterative statements

Conditional statements:if-elseif-else

Iterative statements:for() {}while() {}

<Demo>





Statements


if-elseif-else

Iterative statements:for() {}while() {}

<Demo>





Statements



for() {}while() {}

<Demo>





Environments

They are used by the interpreter to understand the scopingrulesJob of an environment is to bind set of names to set ofvalues (a bag of names)Each name points to an object stored elsewhere inmemoryEvery environment has a parent, anotherenvironment(except for empty environment)





Environments

They are used by the interpreter to understand the scopingrules

Job of an environment is to bind set of names to set ofvalues (a bag of names)Each name points to an object stored elsewhere inmemoryEvery environment has a parent, anotherenvironment(except for empty environment)





Environments

They are used by the interpreter to understand the scopingrulesJob of an environment is to bind set of names to set ofvalues (a bag of names)Each name points to an object stored elsewhere inmemory

Every environment has a parent, anotherenvironment(except for empty environment)





Environments

They are used by the interpreter to understand the scopingrulesJob of an environment is to bind set of names to set ofvalues (a bag of names)Each name points to an object stored elsewhere inmemoryEvery environment has a parent, anotherenvironment(except for empty environment)





Environments

Four Special environments:globalenv() - is the interactive workspace, environment inwhich we normally workbaseenv() - is the environment of the base packageemptyenv() - is the ultimate ancestor of all environmentsenvironment() - is the current environment

Search paths guide the interpreter to look for the values ofnames





User-defined functions

Life cycle of user-defined function :Function definition - name bound to that function in currentenvironment (enclosing environment)Function call- A new environment(calling environment) iscreated and call expression is executedPlease note there is execution environment, environment inwhich function was called.

R uses Lexical Scoping - Looks for name bindings inenclosing environment not in the execution environment.The enclosing environment determines how the functionfinds values; the binding environments determine how wefind the function.

<Demo>






Life cycle of user-defined function :Function definition - name bound to that function in currentenvironment (enclosing environment)Function call- A new environment(calling environment) iscreated and call expression is executed

Please note there is execution environment, environment inwhich function was called.


<Demo>








<Demo>







R uses Lexical Scoping - Looks for name bindings inenclosing environment not in the execution environment.

The enclosing environment determines how the functionfinds values; the binding environments determine how wefind the function.

<Demo>








<Demo>





Every value in R has a type associated with it

Native data types :Have primitive expressions that evaluate to values of thesetypesBuilt-in functions, operators, methods to manipulate thosevalues

There are also abstract data types (Data structures), whichwere defined along with there functions, methods, operators tomake R more useful for statistical analysis





Every value in R has a type associated with it

Native data types :

Have primitive expressions that evaluate to values of thesetypes

Built-in functions, operators, methods to manipulate thosevalues

There are also abstract data types (Data structures), whichwere defined along with there functions, methods, operators tomake R more useful for statistical analysis





Objects

Objects represent information - consist of data and behaviour

They can represent - things, properties, Interactions, processes

Type of an object is called class

Abstract data type(a class) is some collection ofmethods(functions) and behaviour condition defined on it.





Data structures

These are abstract data types defined in R and can beorganised according to their dimensionality and whether theyare homogeneous.

One dimensional structures - Atomic vectors, lists

Two dimensional structures - Matrices, Data frames

Multidimensional - Arrays

A data frame is the most common way of storing data in R, andmakes data analysis easier

All objects and thus data structures have attributes - to storemetadata about the object <Demo>





Data structures






All objects and thus data structures have attributes - to storemetadata about the object

<Demo>





Data structures






All objects and thus data structures have attributes - to storemetadata about the object <Demo>





<DEMO>




Advanced TopicsReferences

Important Advanced Topics

Object systems in R

Subsetting

Functional programming paradigm

Memory usage in R

Using lower level languages for better performance where everrequired in R




Advanced TopicsReferences

Resources

Advanced R by Hadley Wickham

Structure and Interpretation of Computer Programs - Berkleywebcast(CS61A, Fall 2013)

R package documentation




“To understand computations in R, two slogans are helpful:Everything that exists is an object.Everything that happens is a function call.”

John Chambers (Inventor of R).




Thank You


Introduction to computing_using_r

Engineering

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