Adv Data Science using R Quiz and Assignment 1

These are Advance Data Science Using R Assignment 1 Solution

Quiz

Q1. How do you create a variable named x with the numeric value 5?
int x=5
All of the above
x<-5
x : 5

Answer: x<-5

Q2. How do you insert COMMENTS in R code?
None
// This is a comment
/* This is a comment

Answer: // This is a comment

Q3. What is a correct syntax to output “Hello World” in R?
‘Hello World’
“Hello World”
print(“Hello World”)
All of the other answers are correct

Answer: All of the other answers are correct

Q4. Who is introduced R Programming Language?
Ross Ihaka
Robert Gentleman
Both (A) and (B)
Florian Hahne

Answer: Both (A) and (B)

Q5. When the First appeared R Programming Language?
August 1992
August 1994
August 1993
August 1995

Answer: August 1993

Q6. Which function is often used to concatenate elements?
join()
merge()
paste()
concat()

Answer: paste()

Q7. Which statement is used to stop a loop?
stop
exit
break
return

Answer: break

Q8. Which function is used to find the amount of rows and columns in an array?
dim()
nchar()
length()
dim_len()

Answer: dim()

Q9. How do you start writing a while loop in R?
while x < y:
x < y while
while x < y
while (x < y)

Answer: while (x < y)

Q10. How do you start writing an if statement in R?
if (x > y)
if x > y:
if x > y then:
None of the above

Answer: if (x > y)

Q11. Which function is used to add additional columns in a matrix?
add()
cbind()
join()
append_item()

Answer: cbind()

Q12. Which function is used to draw points (markers) in a diagram?
d()
draw()
plot()
canvas()

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Answer: plot()

Q13. How can you assign the same value to multiple variables in one line?
var1, var2, var3 <- “Orange”
var1, var2, var3 = “Orange”
var1, var2, var3 => “Orange”
var1 <- var2 <- var3 <- “Orange”

Answer: var1 <- var2 <- var3 <- “Orange”

Q14. Which operator is used to add together two values?
The & sign
The + sign
The * sign
None of the above

Answer: The + sign

Q15. The following values: 10.5, 55 and 787, belongs to which data type?
numeric
integer
complex
All of the above

Answer: numeric

These are Advance Data Science Using R Assignment 1 Solution

Assignment

Q1. Explain Some of the Similarities and Differences Between R and Python.

Solution:

Key Difference Between R and Python

  • R is mainly used for statistical analysis while Python provides a more general approach to data science
  • The primary objective of R is Data analysis and Statistics whereas the primary objective of Python is Deployment and Production
  • R users mainly consists of Scholars and R&D professionals while Python users are mostly Programmers and Developers
  • R provides flexibility to use available libraries whereas Python provides flexibility to construct new models from scratch
  • R is difficult to learn at the beginning while Python is Linear and smooth to learn
  • R is integrated to Run locally while Python is well-integrated with apps
  • Both R and Python can handle huge size of database
  • R can be used on the R Studio IDE while Python can be used on Spyder and Ipython Notebook IDEs
  • R consists various packages and libraries like tidyverse, ggplot2, caret, zoo whereas Python consists packages and libraries like pandas, scipy, scikit-learn, TensorFlow, caret
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Q2. Write and Explain Some of the Most Common Syntaxes in R?

Solution:

  • In R, the primary assignment operator is <- as in:
    • x <- 3
    • Not x = 3
    • To add to the potential confusion, the equals sign actually can be used as an assignment operator in R — most (but not all) of the time.
  • One more note about variables: R is a case-sensitive language. So, variable x is not the same as X. That applies to just about everything in R; for example, the function subset() would not be the same as Subset().
  • To put multiple values into a single variable, you use the c() function, such as:
    • my_vector <- c(1, 1, 2, 3, 5, 8)
    • If you forget that c(), you’ll get an error.
  • Performing a mathematical operation on a vector variable will automatically loop through each item in the vector. Many R functions are already vectorized, but others aren’t, and it’s important to know the difference. if() is not vectorized, for example, but there’s a version ifelse() that is.

Q3. (a) How Do You Assign a Variable in R?
(b) List Some of the Best Packages For:
i. Data Visualization
ii. Data Mining
iii. Data Imputation

Solution:

(a):

There are different ways to define a variable in R which are:

  • In R, a variable always starts with a letter or with a period. A variable if started with a dot cannot be succeeded by a number.
  • Variables cannot be created with keywords which are already predefined in R; that is keywords which are reserved, as their names or identifiers.
  • A variable in R can be defined using just letters or an underscore with letters, dots along with letters. We can even define variables as a mixture of digits, dot, underscore and letters.
  • In R, a few instances of names of variables that are relevant are name, Var, var_1, .var, var.1
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(b):

(i): Packages for Data Visualization

  1. ggplot2.
  2. Lattice.
  3. highcharter.
  4. Leaflet.
  5. RColorBrewer.
  6. Plotly.
  7. sunburstR.
  8. RGL.

(ii): Packages for Data Mining

reshape

sna social network analysis

tm: a framework for text mining applications
lda: fit topic models with LDA
topicmodels: fit topic models with LDA and CTM
RTextTools: automatic text classification via supervised

(iii): Packages for Data Imputation

  1. MICE
  2. Amelia
  3. missForest
  4. Hmisc
  5. mi

These are Advance Data Science Using R Assignment 1 Solution

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