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R Programmingprogramming~20 mins

Merging data frames in R Programming - Practice Problems & Coding Challenges

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Challenge - 5 Problems
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Master of Merging Data Frames
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❓ Predict Output
intermediate
2:00remaining
Output of inner join with duplicate keys

What is the output of the following R code that merges two data frames with duplicate keys using merge()?

R Programming
df1 <- data.frame(id = c(1, 2, 2, 3), value1 = c('A', 'B', 'C', 'D'))
df2 <- data.frame(id = c(2, 2, 3, 4), value2 = c('X', 'Y', 'Z', 'W'))
result <- merge(df1, df2, by = 'id')
print(result)
A
  id value1 value2
1  1      A   &lt;NA&gt;
2  2      B      X
3  2      C      Y
4  3      D      Z
5  4   &lt;NA&gt;      W
B
  id value1 value2
1  2      B      X
2  2      B      Y
3  2      C      X
4  2      C      Y
5  3      D      Z
6  4   &lt;NA&gt;      W
C
  id value1 value2
1  2      B      X
2  2      C      Y
3  3      D      Z
D
  id value1 value2
1  2      B      X
2  2      B      Y
3  2      C      X
4  2      C      Y
5  3      D      Z
Attempts:
2 left
💡 Hint

Remember that merge() with default settings performs an inner join and creates all combinations of matching keys.

❓ Predict Output
intermediate
2:00remaining
Result of left join with missing keys

What will be the output of this R code that performs a left join using merge()?

R Programming
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'))
result <- merge(df1, df2, by = 'id', all.x = TRUE)
print(result)
A
  id value1 value2
1  1      A   &lt;NA&gt;
2  2      B      X
3  3      C      Y
B
  id value1 value2
1  1      A      X
2  2      B      X
3  3      C      Y
4  4   &lt;NA&gt;      Z
C
  id value1 value2
1  2      B      X
2  3      C      Y
D
  id value1 value2
1  1      A      Z
2  2      B      X
3  3      C      Y
Attempts:
2 left
💡 Hint

Check which keys are in df1 and how all.x = TRUE affects the join.

🔧 Debug
advanced
2:00remaining
Identify the error in merge syntax

What error does this R code produce?

R Programming
df1 <- data.frame(id = 1:3, val = c('A', 'B', 'C'))
df2 <- data.frame(id = 2:4, val = c('X', 'Y', 'Z'))
result <- merge(df1, df2, by.x = 'id', by.y = 'ID')
print(result)
AError: by.x and by.y must be the same length
BError: object 'ID' not found
CNo error, prints merged data frame
DError: duplicate column names in result
Attempts:
2 left
💡 Hint

Check the exact column names in both data frames and the by.x and by.y arguments.

❓ Predict Output
advanced
2:00remaining
Output of full outer join with NA values

What is the output of this R code performing a full outer join?

R Programming
df1 <- data.frame(id = c(1, 2, 3), val1 = c('A', 'B', 'C'))
df2 <- data.frame(id = c(2, 3, 4), val2 = c('X', 'Y', 'Z'))
result <- merge(df1, df2, by = 'id', all = TRUE)
print(result)
A
  id val1 val2
1  1    A    X
2  2    B    X
3  3    C    Y
B
  id val1 val2
1  2    B    X
2  3    C    Y
3  4 &lt;NA&gt;    Z
C
  id val1 val2
1  1    A &lt;NA&gt;
2  2    B    X
3  3    C    Y
4  4 &lt;NA&gt;    Z
D
  id val1 val2
1  1    A &lt;NA&gt;
2  2    B &lt;NA&gt;
3  3    C &lt;NA&gt;
4  4 &lt;NA&gt;    Z
Attempts:
2 left
💡 Hint

Remember that all = TRUE keeps all rows from both data frames.

🧠 Conceptual
expert
2:00remaining
Number of rows after merging with multiple keys

Given these data frames, how many rows will the result have after merging by id and group?

df1 <- data.frame(id = c(1,1,2), group = c('A','B','A'), val1 = c(10,20,30))
df2 <- data.frame(id = c(1,1,2,2), group = c('A','A','A','B'), val2 = c(100,200,300,400))
result <- merge(df1, df2, by = c('id', 'group'))
A3
B6
C5
D4
Attempts:
2 left
💡 Hint

Count matching pairs of id and group in both data frames and consider duplicates.