Vector
# To make vectors "x" "y" "year" and "names"
x <- c(2,3,7,9)
y <- c(9,7,3,2)
year <- 1990:1993
names <- c("payal", "shraddha", "kritika", "itida")
# Accessing the 1st and last elements of y -y[1]
length(y)
# To make a list "person" -person <- list(

R practical session 1
Basics
What is R?
R is an environment for data manipulation, statistical computing and graphics, but it can be
also used for computer programming (hence, R is a computer language, too). R is not
designed for point-and-click, but for

Exercises that Practice and Extend Skills with R
John Maindonald
April 15, 2009
Note: Asterisked exercises (or in the case of IV: aL
UExamples that Extend or Challenge, set
of exercises) are intended for those who want to explore more widely or to be chal

Graphics with R
demo(graphics)
demo(persp)
The result of a graphical function cannot be assigned to an object but is sent to a graphical
device.
A graphical device is a graphical window or a file.
There are two kinds of graphical functions:
1. The high-le

Kadi Sarva Vishwavidyalaya, Gandhinagar
MASTERS OF COMPUTER APPLICATION (MCA)
Year II (Semester IV) (W.E.F. January 2015)
Subject Name: Big Data & Data Analytics MCA-405(B)
Sub
Total
Credit
Examination scheme
Teaching scheme
5
(per week)
Th
Pr
3
4
MID
Th

1. Write the R code which store the player information like Name, Team, No of
times has played, No of goals scored till date.
a. Store the details in the .csv file
b. Display the details of a single player by entering the name
c. Display the full details

R for Beginners
Emmanuel Paradis
Institut des Sciences de lEvolution
Universite Montpellier II
F-34095 Montpellier cedex 05
France
E-mail: paradis@isem.univ-montp2.fr
I thank Julien Claude, Christophe Declercq, Elodie
Gazave, Friedrich Leisch,
Louis Luang

BIG DATA & DATA ANALYSIS
Practical Questions
1. Create two excel file which store the details of the employees personal details, official
details, based on the joining details of the employee and the increment given predict list
of employee whether promot

R Exercise
1. Create a new variable and insert a numeric variable
2. Convert the numeric variable to character
Example:
b <- as.character(b)
print (b)
3. Setup your working directory
Example:
4. Create a vector numbers from 1 to 6 and find out its class
E

Programming with R in practice
6.1 Loops and vectorization:
Example 1:
x <- rnorm(10, -5, 0.1)
y <- rnorm(10, 5, 2)
X <- cbind(x, y) # the columns of X keep the names "x" and "y"
apply(X, 2, mean)
apply(X,2, sd)
forms <- list(y ~ x, y ~ poly(x, 2)
lapply(

R Programming Function
Syntax for Writing Functions in R
func_name <- function (argument) cfw_
statement
Example of a Function
pow <- function(x, y) cfw_
# function to print x raised to the power y
result <- x^y
print(paste(x,"raised to the power",y,"is"

Big Data and Data Analysis
UNIT - I
1. What is Big Data?
2. Explain the risks of Big Data?
3. Explain the taming of big data?
4. Describe the different structure of big data?
5. How to explore the valuable data from big data?
6. Explain the ways to filter

R Manual LAB- 1
I. Working with numeric values:
x <- 10.1 # Numeric
x
y = 10
y
z = x+y
z
is.integer(z) #To check the datatype Returns False
II To convert into integer
b = as.integer(z)
b
is.integer(b)
sqrt(b)
III. Logical Operators
gr = x > y
gr
IV Condit

Vector
# To make vectors "x" "y" "year" and "names"
x <- c(2,3,7,9)
y <- c(9,7,3,2)
year <- 1990:1993
names <- c("payal", "shraddha", "kritika", "itida")
# Accessing the 1st and last elements of y -y[1]
length(y)
# To make a list "person" -person <- list(

Business Analytics
The term predictive analytics - was to distinguish statistics from more advanced type of
calculations that are used to predict likelihoods of future outcomes.
Big Data analytics uses predictive and prescriptive analytics and is changing

UNIT - II
Industry Examples of Big Data
Digital Marketing and Non- line World:
Googles Avinash Kaushik before 10 years
Data warehouse: Large, complicated, build in single source in
traditional database Oracle
Single source from ERP and other sources
Big

UNIT IV
I How R Works
1. R is an interpreted language, not a compiled one,
2. All commands typed on the keyboard are directly executed without requiring to build a
complete program like in most computer languages (C, Fortran, Pascal, . . . ).
3. Second, R

The grid and lattice packages
I.
Grid is a new graphical mode with its own system of graphical parameter.
The two main distinctions of grid compared to the base graphics are:
1. A more flexible way to split graphical devices using viewpots which could be