R is an open source programming language, which is most popular among data scientists. R isn’t just a tool for industry. It is also very popular among academic scientists and researchers. This presentations will help readers to get started with R programming.

1. Dr Nisha Arora
Getting started with R

2. Contents
2
Download & Install R
Download & install R Studio
Install Packages in R/ R Studio
Set or change working directory
Get help in R
Import & Export data sets
Shortcuts & Tips
References & Resources

3. Why R?
3

4. ALGORITHM
4
Word used by programmers whenthey do
notwant to explainwhatthey did!

5. 5
The only programmingJOKE, I know is
my code.
Just like that

6. 6

7. To download & install R
 https://cran.r-project.org/
 Operating system
 Sub-directory: base
 install R for the first time.
7

8. 8
To download & install R

9. 9
To download & install R

10. 10
To download & install R

11. 11
To download & install R

12. 12
To download & install R

13. 13
To download & install R

14. 14
To download & install R

15. 15
To download & install R

16. 16
To download & install R

17. 17
To download & install R

18. 18
To download & install R

19. 19
To download & install R

20. 20
R GUI
R studio
Includes a console, editor, as well as tools for plotting, history,
debugging and workspace management
R Commander
Enables analysts to access a selection of commonly-used R commands
using a simple interface
Rattle
A data mining toolkit which was designed to analyze large data sets
Deducer
Designed to be a easy to use alternative to proprietary data analysis
software such as SPSS and Minitab

21. 21
Download & install R Studio
 Open the URL: www.rstudio.com
 Click on “Download Rstudio” button.
 Click on "Download RStudio Desktop”.
 Click on the version recommended for your system, or the
latest
 Windows version, and save the executable file.
 Run the .exe file and follow the installation instructions.

22. 22
R packages
Base packages
Which come with R automatically
Contributed packages
Which must be downloaded for installation
To find the list of default base packages loaded at start-up
getOption("defaultPackages")
"datasets" "utils" "grDevices" "graphics" "stats" "methods"

23. 23
To install packages in R

24. 24
To install packages in R Studio

25. 25
To install packages in R Studio

26. 26
To install packages in R Studio

27. 27
To install packages in R Studio
# To see all packages installed
library()
#To see packages currently loaded
search()
#To install a package ‘caret’
install.packages(“caret”, dependencies=TRUE)
#To load a package ‘caret’
library(caret)
#To discover the contents of library package ‘caret’
library(help=caret)

28. 28
Working Directory

29. 29
Working Directory
# To check the current working directory
getwd()
# To set a new working directory
setwd("D:NISHAR CourseraR_programming")
Note: use '' or '/' in the path of directory
# The shortcut (to get/change the current working directory)
"ctr+shift+h“

30. 30
To get help in R
 Click on the 'Help' menu.
 If you want help on a specific command you can enter a search
directly from the keyboard: help(keyword), e.g., help(mean)
 A shortcut is to type: ?keyword
 If you are not sure of the command you can try the following:
apropos("part.word"), e.g., apropos(wd); apropos(“mean")
 To invoke a built-in help browser, you can type: help.start()

31. Data Sets
31
#To see the list of available data sets in R
data()
#To load an available data sets in R
data(name_of_dataset)
#For example;
data(airquality)

32. Data Sets
33

33. Import Data Sets
34
#To import Text data file in R
myTEXTdata = read.table("mydata.txt“, header = TRUE)
Make sure to set your working directory

34. Import Data Sets
35
#To import CSV data file in R
myCSVdata <- read.table("c:/mydata.csv", header=TRUE,
sep=",", row.names="id")
# note the / instead of on Windows systems
Or myCSVdata = read.csv("mydata.csv")

35. Import Data Sets
36
#To import Excel data file in R
# read in the first worksheet from the workbook myexcel.xlsx
# first row contains variable names
library(xlsx)
mydata <- read.xlsx("c:/myexcel.xlsx", 1)
# read in the worksheet named mysheet
mydata <- read.xlsx("c:/myexcel.xlsx", sheetName = "mysheet")

36. Import Data Sets
37
#To import Excel data file in R
# read in the first worksheet from the workbook myexcel.xlsx
# first row contains variable names
library(readxl)
mydata <- read_excel("c:/myexcel.xlsx", sheet =1)
# read in the worksheet named mysheet
mydata <- read_excel("c:/myexcel.xlsx", sheet = "mysheet")

37. Import Data Sets
38
To import SPSS data file in R
library(foreign); mySPSSdata <- read.spss("Housing Pricing
Data.sav“)
If SPSS dataset is in trasport format
library(Hmisc); mySPSSdata <- spss.get("c:/mydata.por",
use.value.labels=TRUE)

38. Import Data Sets
39
#To import SAS data file in R
install.packages("sas7bdat"); library(sas7bdat)
mySASdata <- read.sas7bdat("d1.sas7bdat")
If SAS dataset is in trasport format
library(Hmisc); mySASdata <- sasxport.get("c:/mydata.xpt")
# character variables are converted to R factors

39. Import Data Sets
40
#To import STATA data file in R
install.packages(“foreign")
library(foreign)
mySTATAdata <- read.dta("D://Learning//Learn
R//R_programming data and codes//sales.dta")

40. Data Sets
41

41. Export Data Sets
42
#To export R data file to a tab delimited text file
write.table(mydata, "c:/mydata.txt", sep="t")

42. Export Data Sets
43
#To export R data file CSV format
write.csv(MyData, file = "MyData.csv")
write.table(MyData, file = "MyData.csv",row.names=FALSE,
na="",col.names=FALSE, sep=",")

43. Export Data Sets
44
#To export R data file to an Excel spreadsheet
library(xlsx)
write.xlsx(mydata, "c:/mydata.xlsx")

44. Export Data Sets
45
To export R data file to SPSS
# write out text data file and an SPSS program to read it
library(foreign)
write.foreign(mydata, “D:/mydata.txt",
D:/mydata.sps", package="SPSS")

45. Export Data Sets
46
#To export R data file to SAS
# write out text datafile and an SAS program to read it
library(foreign)
write.foreign(mydata, "c:/mydata.txt",
"c:/mydata.sas", package="SAS")

46. Export Data Sets
47
#To export R data file to STATA
# export data frame to Stata binary format
library(foreign)
write.dta(mydata, "c:/mydata.dta")

47. Helpful Tips
48
#To see the list of key board shortcuts
alt + shift + k
#To save a file
ctr + s
#To run selected piece of code
ctr + r

48. Short-cuts
49
Edit -> Folding:
Collapse — Alt+L
Expand — Shift+Alt+L
Collapse All — Alt+O
Expand All — Shift+Alt+O
Code:
Insert Section — Ctrl+Shift+R
(Cmd+Shift+R on the Mac)
Jump To — Shift+Alt+J

49. Short-cuts
https://support.rstudio.com/hc/en-us/articles/200711853-Keyboard-
Shortcuts
50
Description Windows & Linux Mac
Goto File/Function Ctrl+. Ctrl+.
Move cursor to Source Editor Ctrl+1 Ctrl+1
New document (except on
Chrome/Windows)
Ctrl+Shift+N Command+Shift+N
New document (Chrome only) Ctrl+Alt+Shift+N Command+Shift+Alt+N
Open document Ctrl+O Command+O
Save active document Ctrl+S Command+S
Close active document (except
on Chrome)
Ctrl+W Command+W
Goto File/Function Ctrl+. Ctrl+.

50. 51
Get your hands dirty
 R & R Studio
 Install & Load Packages
 Arithmetic in R
 Numbers in R (NAN & NA)
 Import data to R
 Export data from R
 Descriptive Statistics
 Basic Plots

51. References
52
• Crowley, M. J. (2007). The R Book. Chichester, New
England: John Wiley & Sons, Ltd.
• An Introduction to R by W. N. Venables, D. M. Smith
and the R Core Team
• R in a Nutshell by Joseph Adler: O’Reilly
• Teetor, P. (2011). R cookbook. Sebastopol, CA:
O’Reilly Media Inc.

52. References
53
http://www.r-bloggers.com/
http://www.inside-r.org/blogs
https://blog.rstudio.org/
http://www.statmethods.net/
http://stats.stackexchange.com
https://www.researchgate.net
https://www.quora.com
https://github.com

53. References
54
https://rpubs.com/
https://www.datacamp.com/
https://www.dataquest.io/
https://www.codeschool.com/

54. 55
Reach Out to Me
http://stats.stackexchange.com/users/79100/learner
https://www.researchgate.net/profile/Nisha_Arora2/contributions
https://www.quora.com/profile/Nisha-Arora-9
nishaarora4@gmail.com

55. Thank You