join functions (left_join, inner_join) in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a left join of df1 and df2 by the column 'id'.

R Programming

result <- [1](df1, df2, by = "id")

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

Ainner_join

Bmerge

Cleft_join

Dfull_join

Attempts:

3 left

💡 Hint

Common Mistakes

Using inner_join instead of left_join will drop unmatched rows from df1.

The left_join function keeps all rows from the first data frame and adds matching rows from the second.

2fill in blank

medium

Complete the code to perform an inner join of df1 and df2 by the column 'key'.

R Programming

result <- [1](df1, df2, by = "key")

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

Afull_join

Binner_join

Cright_join

Dleft_join

Attempts:

3 left

💡 Hint

Common Mistakes

Using left_join will keep all rows from df1, not just matching ones.

The inner_join function returns only rows with matching keys in both data frames.

3fill in blank

hard

Fix the error in the code to join df1 and df2 by the column 'user_id' using inner join.

R Programming

joined_data <- [1](df1, df2, by = "user_id")

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

Ainner_join

Bleft_join

Cmerge

Djoin

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'join' instead of 'inner_join' causes an error.

The correct function for inner join in dplyr is inner_join. The option join does not exist.

4fill in blank

hard

Complete the code to perform a left join of df1 and df2 by matching df1's 'id' column to df2's 'user_id' column.

R Programming

result <- left_join(df1, df2, by = c("[1]" = "[2]"))

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

Aid

Buser_id

Ckey

Dcust_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using by='id' which won't match df2$user_id.

Using by=c('id','user_id') which requires same position columns.

When join columns have different names, use by = c("df1_col" = "df2_col").

5fill in blank

hard

Fill all three blanks to perform an inner join of df1 and df2 by 'id', handling column conflicts with suffixes '_left' and '_right'.

R Programming

result <- inner_join(df1, df2, by = "[1]", suffix = c("[2]", "[3]"))

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

Aid

B_left

C_right

D_orig

Attempts:

3 left

💡 Hint

Common Mistakes

Not specifying suffix leads to error if column names overlap.

Reversing the suffix order.

The suffix argument specifies suffixes for overlapping non-key columns: first for left df, second for right.

Practice

1. What does the left_join function do in R's dplyr package?

easy

A. Removes all rows that have any missing values.

B. Keeps only rows that match in both tables.

C. Keeps all rows from the second table and adds matching rows from the first table.

D. Keeps all rows from the first table and adds matching rows from the second table.

Solution

1. Step 1: Understand the purpose of left_join

   left_join keeps all rows from the first (left) table regardless of matches.

2. Step 2: Understand how matching rows are added

   It adds columns from the second (right) table only where keys match, filling with NA if no match.

3. Final Answer:

   Keeps all rows from the first table and adds matching rows from the second table. -> Option D

4. Quick Check:

   left_join = all left rows + matching right rows [OK]

Hint: Remember: left_join keeps all from left, adds matches [OK]

Common Mistakes:

• Confusing left_join with inner_join
• Thinking left_join removes unmatched rows
• Mixing up which table is 'left' or 'right'

2. Which of the following is the correct syntax to perform an inner join of two data frames df1 and df2 by the column id in R?

easy

A. inner_join(df1, df2, on = "id")

B. innerjoin(df1, df2, on = "id")

C. inner_join(df1, df2, by = "id")

D. innerjoin(df1, df2, by = "id")

Solution

1. Step 1: Identify correct function name and parameters

   The function is inner_join from dplyr, and it uses by to specify join columns.

2. Step 2: Check parameter names and spelling

   Correct syntax is inner_join(df1, df2, by = "id"). Other options use wrong function names or parameter names.

3. Final Answer:

   inner_join(df1, df2, by = "id") -> Option C

4. Quick Check:

   inner_join syntax uses by = "column" [OK]

Hint: Use inner_join() with by = "column" for correct syntax [OK]

Common Mistakes:

• Using 'on' instead of 'by' for join column
• Misspelling function name as innerjoin
• Confusing parameter order

3. Given these two data frames:

df1 <- data.frame(id = c(1, 2, 3), value1 = c("A", "B", "C"))
df2 <- data.frame(id = c(2, 3, 4), value2 = c("X", "Y", "Z"))

What is the result of inner_join(df1, df2, by = "id")?

medium

A. Rows with ids 2 and 3 with columns from both data frames

B. Rows with ids 1, 2, 3, 4 with all columns

C. Rows with ids 1 and 4 only

D. Rows with ids 1, 2, 3 with only columns from df1

Solution

1. Step 1: Identify matching ids in both data frames

   df1 has ids 1, 2, 3; df2 has ids 2, 3, 4. Common ids are 2 and 3.

2. Step 2: Understand inner_join output

   inner_join keeps only rows with matching ids and combines columns from both data frames for those rows.

3. Final Answer:

   Rows with ids 2 and 3 with columns from both data frames -> Option A

4. Quick Check:

   inner_join = only matching rows [OK]

Hint: inner_join keeps only rows with matching keys [OK]

Common Mistakes:

• Including unmatched rows in inner_join result
• Confusing inner_join with left_join
• Ignoring columns from second data frame

4. You run this code:

left_join(df1, df2, by = "id")

but get an error: Error: object 'df2' not found. What is the likely cause?

medium

A. The data frame df2 was not created or loaded before the join.

B. The by argument is misspelled.

C. left_join cannot join on column named 'id'.

D. You need to use inner_join instead of left_join.

Solution

1. Step 1: Analyze the error message

   The error says df2 is not found, meaning R cannot find the object named df2.

2. Step 2: Identify cause of missing object

   This usually means df2 was not created, loaded, or is misspelled before calling left_join.

3. Final Answer:

   The data frame df2 was not created or loaded before the join. -> Option A

4. Quick Check:

   Missing data frame causes object not found error [OK]

Hint: Check if all data frames exist before joining [OK]

Common Mistakes:

• Assuming join syntax error causes object not found
• Ignoring typo in data frame names
• Thinking join functions require special packages loaded

5. You have two data frames:

students <- data.frame(student_id = c(1, 2, 3, 4), name = c("Anna", "Ben", "Cara", "Dan"))
scores <- data.frame(student_id = c(2, 3, 5), score = c(88, 92, 75))

You want a table that shows all students with their scores if available, and NA if no score exists. Which join function and code should you use?

hard

A. inner_join(students, scores, by = "student_id")

B. left_join(students, scores, by = "student_id")

C. right_join(students, scores, by = "student_id")

D. full_join(students, scores, by = "student_id")

Solution

1. Step 1: Understand the goal

   You want all students listed, even if they don't have a score, with scores added where available.

2. Step 2: Choose the correct join

   left_join keeps all rows from the first table (students) and adds matching scores, filling with NA if no match.

3. Final Answer:

   left_join(students, scores, by = "student_id") -> Option B

4. Quick Check:

   left_join keeps all left rows, adds matches, fills NA [OK]

Hint: Use left_join to keep all from first table with matches [OK]

Common Mistakes:

• Using inner_join which drops students without scores
• Using right_join which keeps all scores but drops some students
• Using full_join which adds extra rows not needed