Data frame creation in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a data frame with columns 'Name' and 'Age'.

R Programming

df <- data.frame(Name = c("Alice", "Bob"), Age = c(25, [1]))

Drag options to blanks, or click blank then click option'

A30

B"30"

CAge

Dc(30)

Attempts:

3 left

💡 Hint

Common Mistakes

Putting quotes around numbers, which makes them strings.

Using a variable name instead of a value.

The Age column should contain numeric values. Using 30 (without quotes) correctly assigns the age as a number.

2fill in blank

medium

Complete the code to create a data frame with three columns: 'ID', 'Score', and 'Passed'.

R Programming

df <- data.frame(ID = 1:3, Score = c(88, 92, 79), Passed = c(TRUE, [1], FALSE))

Drag options to blanks, or click blank then click option'

A1

B"TRUE"

CTRUE

DFALSE

Attempts:

3 left

💡 Hint

Common Mistakes

Using strings "TRUE" or "FALSE" instead of logical values.

Using numeric 1 or 0 instead of TRUE or FALSE.

The 'Passed' column should contain logical values TRUE or FALSE without quotes.

3fill in blank

hard

Fix the error in the code to create a data frame with columns 'Product' and 'Price'.

R Programming

df <- data.frame(Product = c("Pen", "Notebook"), Price = c(1.5, [1]))

Drag options to blanks, or click blank then click option'

A2.0

B"2.0"

Cprice

Dc(2.0)

Attempts:

3 left

💡 Hint

Common Mistakes

Using quotes around numbers.

Using variable names instead of values.

The Price column should contain numeric values without quotes or extra c().

4fill in blank

hard

Fill both blanks to create a data frame with columns 'City' and 'Population' where population is numeric.

R Programming

df <- data.frame(City = c("NY", "LA", "SF"), Population = c([1], [2], 3000000))

Drag options to blanks, or click blank then click option'

A8000000

B"4000000"

C3000000

Dc(3000000)

Attempts:

3 left

💡 Hint

Common Mistakes

Using strings for numbers.

Using c() inside c(), which causes errors.

Population values should be numeric without quotes or extra c().

5fill in blank

hard

Fill all three blanks to create a data frame with columns 'Name', 'Age', and 'Member' where 'Member' is logical.

R Programming

df <- data.frame(Name = c("Anna", [1], "John"), Age = c(28, 34, [2]), Member = c(TRUE, [3], FALSE))

Drag options to blanks, or click blank then click option'

A"Mike"

B30

CFALSE

D"30"

Attempts:

3 left

💡 Hint

Common Mistakes

Using numbers as strings for Age.

Using strings for logical values in Member.

Not quoting names.

Name values are strings, Age values are numeric, and Member values are logical TRUE or FALSE without quotes.

Practice

1. What is the main purpose of a data.frame in R?

easy

A. To store data in rows and columns like a spreadsheet

B. To perform mathematical calculations only

C. To create graphical plots

D. To write text files

Solution

1. Step 1: Understand the structure of a data frame

   A data frame organizes data in rows and columns, similar to a spreadsheet.

2. Step 2: Identify the main use

   It is mainly used to store and analyze mixed types of data together.

3. Final Answer:

   To store data in rows and columns like a spreadsheet -> Option A

4. Quick Check:

   Data frame = tabular data storage [OK]

Hint: Think spreadsheet style data storage [OK]

Common Mistakes:

• Confusing data frames with plotting functions
• Thinking data frames only do math
• Assuming data frames are for text files

2. Which of the following is the correct way to create a data frame with columns age and name in R?

easy

A. data.frame(age = [25, 30], name = ["Alice", "Bob"])

B. data.frame(c(25, 30), c("Alice", "Bob"))

C. data.frame(age: c(25, 30), name: c("Alice", "Bob"))

D. data.frame(age = c(25, 30), name = c("Alice", "Bob"))

Solution

1. Step 1: Check syntax for named columns

   In R, data.frame() uses the syntax column_name = vector to name columns.

2. Step 2: Identify correct vector syntax

   Vectors are created with c(), so c(25, 30) and c("Alice", "Bob") are correct.

3. Final Answer:

   data.frame(age = c(25, 30), name = c("Alice", "Bob")) -> Option D

4. Quick Check:

   Correct syntax uses = and c() [OK]

Hint: Use = to name columns and c() for vectors [OK]

Common Mistakes:

• Using colons (:) instead of =
• Using brackets [] instead of c()
• Omitting column names

3. What will be the output of the following R code?

df <- data.frame(x = c(1, 2), y = c("a", "b"))
print(df)

medium

A. x y
1 1 a
2 2 b

B. b 2 2
a 1 1
y x

C. [1] 1 2
[1] "a" "b"

D. Error: object 'df' not found

Solution

1. Step 1: Understand data frame creation

   The code creates a data frame with two columns: x (numbers) and y (characters).

2. Step 2: Understand print output format

   Printing a data frame shows row numbers and columns with their values in a table format.

3. Final Answer:

   x y 1 1 a 2 2 b -> Option A

4. Quick Check:

   Print data frame shows rows and columns [OK]

Hint: Print shows row numbers and columns in table form [OK]

Common Mistakes:

• Ignoring row numbers in output
• Confusing vector print with data frame print
• Expecting error when none occurs

4. Identify the error in the following R code that tries to create a data frame:

df <- data.frame(age = c(20, 25), name = c("John"))

medium

A. Missing comma between vectors

B. Incorrect use of quotes around names

C. Vectors have different lengths causing recycling warning

D. data.frame() cannot mix numeric and character vectors

Solution

1. Step 1: Check vector lengths

   The age vector has length 2, but name vector has length 1.

2. Step 2: Understand recycling rule

   R recycles shorter vectors to match longer ones, causing a warning when lengths differ.

3. Final Answer:

   Vectors have different lengths causing recycling warning -> Option C

4. Quick Check:

   Unequal vector lengths cause recycling warning [OK]

Hint: Ensure all vectors have same length in data.frame() [OK]

Common Mistakes:

• Assuming data.frame() needs all vectors same type
• Thinking missing commas cause error here
• Confusing quotes usage

5. You want to create a data frame from two vectors: ids = c(101, 102, 103) and scores = c(88, 92, 85). Then add a new column passed which is TRUE if score ≥ 90, otherwise FALSE. Which code correctly does this?

hard

A. All of the above

B. df <- data.frame(ids, scores, passed = scores >= 90)

C. df <- data.frame(ids, scores)
df$passed <- if(scores >= 90, TRUE, FALSE)

D. df <- data.frame(ids, scores)
df$passed <- passed >= 90

Solution

1. Step 1: Check the one-line data.frame creation

   df <- data.frame(ids, scores, passed = scores ≥ 90) correctly names columns from variable names and computes passed as logical vector.

2. Step 2: Eliminate incorrect options

   The two-line option using if(scores ≥ 90, TRUE, FALSE) has invalid syntax for if. The other two-line uses undefined passed in passed ≥ 90. All of the above is false.

3. Final Answer:

   df <- data.frame(ids, scores, passed = scores ≥ 90) -> Option B

4. Quick Check:

   Valid: column computation inside data.frame() [OK]

Hint: Create computed columns directly in data.frame() [OK]

Common Mistakes:

• Trying to add columns before creating data frame
• Using incorrect logical syntax
• Not using vectorized operations