Merging data frames in R Programming - Step-by-Step Execution

Concept Flow - Merging data frames

Start with two data frames

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Choose merge key(s)

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Apply merge function

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Match rows by key(s)

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Combine matching rows

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Result: merged data frame

Merging data frames means combining rows from two tables based on matching values in one or more columns.

Execution Sample

R Programming

df1 <- data.frame(ID = c(1, 2, 3), Name = c("Anna", "Ben", "Cara"))
df2 <- data.frame(ID = c(2, 3, 4), Score = c(88, 92, 75))
merged_df <- merge(df1, df2, by = "ID")
print(merged_df)

This code merges two data frames on the 'ID' column, keeping only rows with matching IDs.

Execution Table

Step	Action	df1 Rows	df2 Rows	Matching IDs	Resulting Rows
1	Start with df1 and df2	IDs: 1,2,3	IDs: 2,3,4	-	-
2	Select merge key 'ID'	-	-	-	-
3	Find matching IDs	-	-	2, 3	-
4	Combine rows with matching IDs	-	-	-	Rows with ID 2 and 3
5	Create merged_df with columns ID, Name, Score	-	-	-	2 rows: (2, Ben, 88), (3, Cara, 92)
6	Print merged_df	-	-	-	ID Name Score 2 Ben 88 3 Cara 92

💡 Merge completes after combining rows with matching IDs 2 and 3.

Variable Tracker

Variable	Start	After merge	Final
df1	ID:1,2,3; Name:Anna,Ben,Cara	Unchanged	Unchanged
df2	ID:2,3,4; Score:88,92,75	Unchanged	Unchanged
merged_df	Not defined	Rows with ID 2 and 3 combined	2 rows: ID=2,3 with Name and Score columns

Key Moments - 3 Insights

Why does the merged data frame only have rows with IDs 2 and 3?

Because merge by default keeps only rows where the key 'ID' exists in both data frames, as shown in execution_table step 3 and 4.

What happens to rows with IDs 1 and 4?

They are dropped because they don't have matching IDs in the other data frame, as seen in execution_table step 3.

Can we keep all rows from both data frames?

Yes, by using parameters like all=TRUE in merge(), but this example uses default inner join behavior.

Visual Quiz - 3 Questions

Look at the execution_table, what are the matching IDs found at step 3?

A 1 and 4

B 1, 2, 3, 4

C 2 and 3

D No matching IDs

💡 Hint

Check the 'Matching IDs' column in execution_table row with Step 3.

At which step does the merged data frame get created?

A Step 5

B Step 4

C Step 2

D Step 6

💡 Hint

Look for the step mentioning 'Create merged_df' in execution_table.

If we want to keep all rows from df1 even if no match in df2, what parameter should we add to merge()?

A all=TRUE

B all.x=TRUE

C all.y=TRUE

D by.x=TRUE

💡 Hint

Recall merge() parameters for left join behavior.

Concept Snapshot

merge(x, y, by) combines two data frames x and y by matching values in 'by' columns.
Default keeps only rows with keys in both frames (inner join).
Use all=TRUE for full join, all.x=TRUE for left join.
Result has columns from both frames merged by key.

Full Transcript

Merging data frames in R means joining two tables by matching values in one or more columns. We start with two data frames, choose the column(s) to match on, then use the merge() function. The function finds rows with matching keys and combines their columns into a new data frame. By default, only rows with keys in both data frames are kept. Rows without matches are dropped. You can change this behavior with parameters like all=TRUE or all.x=TRUE. The example merges two data frames on the 'ID' column, resulting in a data frame with only IDs 2 and 3, combining their information.