SlideShare a Scribd company logo
Prelude to Level Two
Hellen Gakuruh
January 19, 2017
Nitty Gritty of R
Welcome to level 2, in this level we delve into R programming. The assumption is that you
have basic knowledge of R and can make a function call.
In this session, just like it's predecessor (Level One), the approach would be non-text book
and more on concept building with an aim of making the transition to programming as easy
as possible.
Level two is meant to impart some programming skills for those interested in going beyond
R's functions. The skills learnt in this level are all geared towards developing user defined
functions which can be packaged and shared on GitHub and/or CRAN. This level will also
introduce a growing issue, that is, reproducible analysis. Therefore, if your goal is to learn
how to use R to do basic analysis using R's functions, then you can skip the second level and
only refer to it as need be.
What we will cover:
• SessionEleven: Looping System in R
• SessionTwelve: Environments
• SessionThirteen: Introduction to function development
• SessionFourteen: Reproducible Analysis in R (Rmarkdown and Shiny)
• SessionFifteen: Package Development

More Related Content

Similar to Prelude to level_two

Introduction to Renjin, the alternative engine for R
Introduction to Renjin, the alternative engine for R Introduction to Renjin, the alternative engine for R
Introduction to Renjin, the alternative engine for R
Zurich_R_User_Group
 
R Brownbag Seminar 2.1
R Brownbag Seminar 2.1R Brownbag Seminar 2.1
R Brownbag Seminar 2.1
Muhammad Nabi Ahmad
 
R programming
R programmingR programming
R programming
Pooja Sharma
 
Financial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali Tirmizi
Financial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali TirmiziFinancial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali Tirmizi
Financial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali Tirmizi
Dr. Muhammad Ali Tirmizi., Ph.D.
 
R vs Matlab: which one is more powerful and why
R vs Matlab:  which one is more powerful and why R vs Matlab:  which one is more powerful and why
R vs Matlab: which one is more powerful and why
Stat Analytica
 
Introduction to R Programming
Introduction to R ProgrammingIntroduction to R Programming
Introduction to R Programming
hemasri56
 
Introduction to R and R Studio
Introduction to R and R StudioIntroduction to R and R Studio
Introduction to R and R Studio
Rupak Roy
 
R tutorial
R tutorialR tutorial
Best corporate-r-programming-training-in-mumbai
Best corporate-r-programming-training-in-mumbaiBest corporate-r-programming-training-in-mumbai
Best corporate-r-programming-training-in-mumbai
Unmesh Baile
 
INT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdf
INT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdfINT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdf
INT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdf
Veerpalkhaira
 
How to get started with R programming
How to get started with R programmingHow to get started with R programming
How to get started with R programming
Ramon Salazar
 
R crash course
R crash courseR crash course
R crash course
Tomislav Hengl
 
R Vs Python – The most trending debate of aspiring Data Scientists
R Vs Python – The most trending debate of aspiring Data ScientistsR Vs Python – The most trending debate of aspiring Data Scientists
R Vs Python – The most trending debate of aspiring Data Scientists
abhishekdf3
 
R programming advantages and disadvantages
R programming advantages and disadvantagesR programming advantages and disadvantages
R programming advantages and disadvantages
PrwaTech
 
Inroduction to r
Inroduction to rInroduction to r
Inroduction to r
manikanta361
 
Better graphics in R
Better graphics in RBetter graphics in R
V mukti proposal
V mukti proposalV mukti proposal
V mukti proposal
VMukti Solutions Pvt. Ltd.
 
Introduction to R software, by Leire ibaibarriaga
Introduction to R software, by Leire ibaibarriaga Introduction to R software, by Leire ibaibarriaga
Introduction to R software, by Leire ibaibarriaga
DTU - Technical University of Denmark
 
Data analysis with R and Julia
Data analysis with R and JuliaData analysis with R and Julia
Data analysis with R and Julia
Mark Tabladillo
 
Reproducible Research in R and R Studio
Reproducible Research in R and R StudioReproducible Research in R and R Studio
Reproducible Research in R and R Studio
Susan Johnston
 

Similar to Prelude to level_two (20)

Introduction to Renjin, the alternative engine for R
Introduction to Renjin, the alternative engine for R Introduction to Renjin, the alternative engine for R
Introduction to Renjin, the alternative engine for R
 
R Brownbag Seminar 2.1
R Brownbag Seminar 2.1R Brownbag Seminar 2.1
R Brownbag Seminar 2.1
 
R programming
R programmingR programming
R programming
 
Financial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali Tirmizi
Financial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali TirmiziFinancial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali Tirmizi
Financial Risk Mgt - Lec 4 by Dr. Syed Muhammad Ali Tirmizi
 
R vs Matlab: which one is more powerful and why
R vs Matlab:  which one is more powerful and why R vs Matlab:  which one is more powerful and why
R vs Matlab: which one is more powerful and why
 
Introduction to R Programming
Introduction to R ProgrammingIntroduction to R Programming
Introduction to R Programming
 
Introduction to R and R Studio
Introduction to R and R StudioIntroduction to R and R Studio
Introduction to R and R Studio
 
R tutorial
R tutorialR tutorial
R tutorial
 
Best corporate-r-programming-training-in-mumbai
Best corporate-r-programming-training-in-mumbaiBest corporate-r-programming-training-in-mumbai
Best corporate-r-programming-training-in-mumbai
 
INT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdf
INT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdfINT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdf
INT232 __ DATA SCIENCE TOOLBOX _ R PROGRAMMING.pdf
 
How to get started with R programming
How to get started with R programmingHow to get started with R programming
How to get started with R programming
 
R crash course
R crash courseR crash course
R crash course
 
R Vs Python – The most trending debate of aspiring Data Scientists
R Vs Python – The most trending debate of aspiring Data ScientistsR Vs Python – The most trending debate of aspiring Data Scientists
R Vs Python – The most trending debate of aspiring Data Scientists
 
R programming advantages and disadvantages
R programming advantages and disadvantagesR programming advantages and disadvantages
R programming advantages and disadvantages
 
Inroduction to r
Inroduction to rInroduction to r
Inroduction to r
 
Better graphics in R
Better graphics in RBetter graphics in R
Better graphics in R
 
V mukti proposal
V mukti proposalV mukti proposal
V mukti proposal
 
Introduction to R software, by Leire ibaibarriaga
Introduction to R software, by Leire ibaibarriaga Introduction to R software, by Leire ibaibarriaga
Introduction to R software, by Leire ibaibarriaga
 
Data analysis with R and Julia
Data analysis with R and JuliaData analysis with R and Julia
Data analysis with R and Julia
 
Reproducible Research in R and R Studio
Reproducible Research in R and R StudioReproducible Research in R and R Studio
Reproducible Research in R and R Studio
 

More from Hellen Gakuruh

R training2
R training2R training2
R training2
Hellen Gakuruh
 
R training6
R training6R training6
R training6
Hellen Gakuruh
 
R training5
R training5R training5
R training5
Hellen Gakuruh
 
R training4
R training4R training4
R training4
Hellen Gakuruh
 
R training3
R training3R training3
R training3
Hellen Gakuruh
 
R training
R trainingR training
R training
Hellen Gakuruh
 
Prelude to level_three
Prelude to level_threePrelude to level_three
Prelude to level_three
Hellen Gakuruh
 
SessionThree_IntroductionToVersionControlSystems
SessionThree_IntroductionToVersionControlSystemsSessionThree_IntroductionToVersionControlSystems
SessionThree_IntroductionToVersionControlSystems
Hellen Gakuruh
 
Day 2
Day 2Day 2
Day 1
Day 1Day 1
Introduction_to_Regular_Expressions_in_R
Introduction_to_Regular_Expressions_in_RIntroduction_to_Regular_Expressions_in_R
Introduction_to_Regular_Expressions_in_R
Hellen Gakuruh
 
SessionTen_CaseStudies
SessionTen_CaseStudiesSessionTen_CaseStudies
SessionTen_CaseStudies
Hellen Gakuruh
 
webScrapingFunctions
webScrapingFunctionswebScrapingFunctions
webScrapingFunctions
Hellen Gakuruh
 
SessionNine_HowandWheretoGetHelp
SessionNine_HowandWheretoGetHelpSessionNine_HowandWheretoGetHelp
SessionNine_HowandWheretoGetHelp
Hellen Gakuruh
 
SessionEight_PlottingInBaseR
SessionEight_PlottingInBaseRSessionEight_PlottingInBaseR
SessionEight_PlottingInBaseR
Hellen Gakuruh
 
SessionSeven_WorkingWithDatesandTime
SessionSeven_WorkingWithDatesandTimeSessionSeven_WorkingWithDatesandTime
SessionSeven_WorkingWithDatesandTime
Hellen Gakuruh
 
SessionSix_TransformingManipulatingDataObjects
SessionSix_TransformingManipulatingDataObjectsSessionSix_TransformingManipulatingDataObjects
SessionSix_TransformingManipulatingDataObjects
Hellen Gakuruh
 
Files
FilesFiles
SessionFive_ImportingandExportingData
SessionFive_ImportingandExportingDataSessionFive_ImportingandExportingData
SessionFive_ImportingandExportingData
Hellen Gakuruh
 
SessionFour_DataTypesandObjects
SessionFour_DataTypesandObjectsSessionFour_DataTypesandObjects
SessionFour_DataTypesandObjects
Hellen Gakuruh
 

More from Hellen Gakuruh (20)

R training2
R training2R training2
R training2
 
R training6
R training6R training6
R training6
 
R training5
R training5R training5
R training5
 
R training4
R training4R training4
R training4
 
R training3
R training3R training3
R training3
 
R training
R trainingR training
R training
 
Prelude to level_three
Prelude to level_threePrelude to level_three
Prelude to level_three
 
SessionThree_IntroductionToVersionControlSystems
SessionThree_IntroductionToVersionControlSystemsSessionThree_IntroductionToVersionControlSystems
SessionThree_IntroductionToVersionControlSystems
 
Day 2
Day 2Day 2
Day 2
 
Day 1
Day 1Day 1
Day 1
 
Introduction_to_Regular_Expressions_in_R
Introduction_to_Regular_Expressions_in_RIntroduction_to_Regular_Expressions_in_R
Introduction_to_Regular_Expressions_in_R
 
SessionTen_CaseStudies
SessionTen_CaseStudiesSessionTen_CaseStudies
SessionTen_CaseStudies
 
webScrapingFunctions
webScrapingFunctionswebScrapingFunctions
webScrapingFunctions
 
SessionNine_HowandWheretoGetHelp
SessionNine_HowandWheretoGetHelpSessionNine_HowandWheretoGetHelp
SessionNine_HowandWheretoGetHelp
 
SessionEight_PlottingInBaseR
SessionEight_PlottingInBaseRSessionEight_PlottingInBaseR
SessionEight_PlottingInBaseR
 
SessionSeven_WorkingWithDatesandTime
SessionSeven_WorkingWithDatesandTimeSessionSeven_WorkingWithDatesandTime
SessionSeven_WorkingWithDatesandTime
 
SessionSix_TransformingManipulatingDataObjects
SessionSix_TransformingManipulatingDataObjectsSessionSix_TransformingManipulatingDataObjects
SessionSix_TransformingManipulatingDataObjects
 
Files
FilesFiles
Files
 
SessionFive_ImportingandExportingData
SessionFive_ImportingandExportingDataSessionFive_ImportingandExportingData
SessionFive_ImportingandExportingData
 
SessionFour_DataTypesandObjects
SessionFour_DataTypesandObjectsSessionFour_DataTypesandObjects
SessionFour_DataTypesandObjects
 

Recently uploaded

一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
nyfuhyz
 
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
ihavuls
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
javier ramirez
 
Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......
Sachin Paul
 
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
v7oacc3l
 
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docxDATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
SaffaIbrahim1
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Fernanda Palhano
 
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
wyddcwye1
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
aqzctr7x
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
nuttdpt
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
AndrzejJarynowski
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
Social Samosa
 
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more importantChallenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
Sm321
 
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
Social Samosa
 
DSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelinesDSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelines
Timothy Spann
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
roli9797
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
vikram sood
 
Everything you wanted to know about LIHTC
Everything you wanted to know about LIHTCEverything you wanted to know about LIHTC
Everything you wanted to know about LIHTC
Roger Valdez
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Kiwi Creative
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
nuttdpt
 

Recently uploaded (20)

一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
 
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
 
Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......
 
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
 
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docxDATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
 
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
 
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more importantChallenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
 
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
 
DSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelinesDSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelines
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
 
Everything you wanted to know about LIHTC
Everything you wanted to know about LIHTCEverything you wanted to know about LIHTC
Everything you wanted to know about LIHTC
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
 

Prelude to level_two

  • 1. Prelude to Level Two Hellen Gakuruh January 19, 2017 Nitty Gritty of R Welcome to level 2, in this level we delve into R programming. The assumption is that you have basic knowledge of R and can make a function call. In this session, just like it's predecessor (Level One), the approach would be non-text book and more on concept building with an aim of making the transition to programming as easy as possible. Level two is meant to impart some programming skills for those interested in going beyond R's functions. The skills learnt in this level are all geared towards developing user defined functions which can be packaged and shared on GitHub and/or CRAN. This level will also introduce a growing issue, that is, reproducible analysis. Therefore, if your goal is to learn how to use R to do basic analysis using R's functions, then you can skip the second level and only refer to it as need be. What we will cover: • SessionEleven: Looping System in R • SessionTwelve: Environments • SessionThirteen: Introduction to function development • SessionFourteen: Reproducible Analysis in R (Rmarkdown and Shiny) • SessionFifteen: Package Development