join functions (left_join, inner_join) in R Programming - Step-by-Step Execution

Concept Flow - join functions (left_join, inner_join)

Start with two tables

↓

Choose join type

↓

left_join

↓

Match keys in both tables

↓

left_join: keep all from left, add matches

↓

inner_join: keep only matches

↓

Resulting table

↓

End

Start with two tables, pick join type (left or inner), match keys, then produce a new table with rows combined accordingly.

Execution Sample

R Programming

library(dplyr)
left_join(df1, df2, by = "id")
inner_join(df1, df2, by = "id")

Joins two data frames df1 and df2 by the 'id' column using left and inner joins.

Execution Table

Step	Action	df1 rows	df2 rows	Join Type	Matching Keys	Result Rows	Result Description
1	Start with df1 and df2	3	2	-	-	-	df1 has 3 rows, df2 has 2 rows
2	Perform left_join by 'id'	3	2	left_join	id=1,2	3	All df1 rows kept; matched rows from df2 added; unmatched df2 rows ignored
3	Perform inner_join by 'id'	3	2	inner_join	id=1,2	2	Only rows with matching 'id' in both tables kept
4	End of joins	-	-	-	-	-	Joins complete, results ready

💡 Joins stop after matching keys and producing combined tables.

Variable Tracker

Variable	Start	After left_join	After inner_join
df1_rows	3	3	3
df2_rows	2	2	2
result_rows	-	3	2

Key Moments - 2 Insights

Why does left_join keep more rows than inner_join?

Because left_join keeps all rows from the left table (df1) even if there is no match in df2, as shown in execution_table row 2, while inner_join keeps only rows with matching keys in both tables (row 3).

What happens to rows in df2 that don't match any in df1 during left_join?

They are ignored and not included in the result, as left_join only keeps all rows from df1 and matches from df2, shown in execution_table row 2.

Visual Quiz - 3 Questions

Look at the execution_table, how many rows does the result have after left_join?

A 3

B 2

C 5

D 1

💡 Hint

Check the 'Result Rows' column in execution_table row 2 for left_join.

At which step does the join keep only matching rows from both tables?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at the 'Join Type' and 'Result Description' columns in execution_table row 3.

If df2 had an extra row with id=3, how would left_join result rows change?

A Result rows would increase by 1

B Result rows stay the same

C Result rows decrease

D Result rows become zero

💡 Hint

Left_join keeps all rows from df1; extra df2 rows without matching keys do not add rows, see key_moments explanation.

Concept Snapshot

join functions (left_join, inner_join):
- left_join keeps all rows from left table + matched rows from right
- inner_join keeps only rows with matching keys in both tables
- Use 'by' to specify key columns
- Result rows differ: left_join >= inner_join
- Useful for combining related data with different inclusion rules

Full Transcript

This visual execution shows how left_join and inner_join work in R using dplyr. We start with two tables, df1 and df2, each with some rows. The left_join keeps all rows from df1 and adds matching rows from df2 based on the 'id' column. If df2 has no matching row, the left_join result still keeps the df1 row with missing values for df2 columns. The inner_join keeps only rows where both df1 and df2 have matching 'id' values, so the result has fewer rows. The execution table tracks these steps, showing the number of rows before and after each join. The variable tracker shows how the number of rows changes. Key moments clarify why left_join keeps more rows and what happens to unmatched rows in df2. The quiz tests understanding of these concepts by asking about result row counts and join behavior. This helps beginners see exactly how these joins combine data step-by-step.