R vs Python for data analysis in R Programming - Practice Questions

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of data frame summary in R

What is the output of the following R code snippet?

R Programming

df <- data.frame(age = c(25, 30, 35, 40, 45), score = c(88, 92, 95, 85, 90))
summary(df)

A

age: 25 30 35 40 45
score: 88 92 95 85 90

B

age  score
25   88
30   92
35   95
40   85
45   90

C Error in summary(df): object 'df' not found

D

      age           score     
 Min.   :25.00   Min.   :85.00  
 1st Qu.:30.00   1st Qu.:88.00  
 Median :35.00   Median :90.00  
 Mean   :35.00   Mean   :90.00  
 3rd Qu.:40.00   3rd Qu.:92.00  
 Max.   :45.00   Max.   :95.00  

💡 Hint

summary() in R gives statistical summaries for each column in a data frame.

The summary() function in R returns minimum, 1st quartile, median, mean, 3rd quartile, and maximum for numeric columns in a data frame.

🧠 Conceptual

intermediate

Key difference in data handling between R and Python

Which statement best describes a key difference in how R and Python handle data analysis?

A R primarily uses data frames as a native data structure, while Python uses lists only.

B R has built-in support for statistical models, while Python requires external libraries for similar tasks.

C Python's pandas library provides data frames similar to R, but R's data frames are more integrated into the language.

D Python cannot handle large datasets efficiently, unlike R.

💡 Hint

Think about how each language treats data frames and libraries.

R has data frames as a core part of the language, while Python uses pandas library to provide similar functionality. R's data frames are more native and integrated.

🔧 Debug

advanced

Identify the error in R code for reading CSV

What error will this R code produce?

R Programming

data <- read.csv('datafile.csv', header=FALSE, sep=';')
head(data)

A Error: cannot open file 'datafile.csv': No such file or directory

B Error: unexpected symbol in 'read.csv('datafile.csv', header=FALSE, sep=';')'

C No error, outputs first 6 rows of data

D Error: unused argument (sep = ';')

💡 Hint

Check if the file exists in the working directory.

If the file 'datafile.csv' does not exist in the current directory, read.csv will throw a file not found error.

❓ data_output

advanced

Output of Python pandas groupby aggregation

What is the output of this Python code using pandas?

R Programming

import pandas as pd

df = pd.DataFrame({'team': ['A', 'A', 'B', 'B'], 'points': [10, 15, 10, 5]})
result = df.groupby('team').sum()
print(result)

A

      points
team         
A         25
B         15

B

team  points
A     10
A     15
B     10
B     5

C

points
A  10
B  5

D Error: 'groupby' is not a function

💡 Hint

groupby sums points for each team.

The groupby('team').sum() aggregates points by team, summing values for each group.

🚀 Application

expert

Choosing between R and Python for a project

You have a project requiring advanced statistical modeling and interactive visualizations. Which choice is best and why?

A Use R because Python lacks libraries for data visualization.

B Use R because it has strong statistical packages and interactive visualization libraries like Shiny.

C Use Python because R cannot create interactive visualizations.

D Use Python because it has better support for statistical modeling than R.

💡 Hint

Consider the strengths of each language in statistics and visualization.

R is well-known for advanced statistics and has Shiny for interactive web apps, making it ideal for this project.