summarise() with group_by() in R Programming - Step-by-Step Execution

Concept Flow - summarise() with group_by()

Start with data frame

↓

Apply group_by()

↓

Data split into groups

↓

Apply summarise() to each group

↓

Combine results into summary data frame

↓

End

First, data is grouped by one or more columns, then summarise() calculates summary values for each group, producing a smaller summary table.

Execution Sample

R Programming

library(dplyr)
data <- tibble(name = c("A", "A", "B", "B"), score = c(10, 20, 30, 40))
data %>% group_by(name) %>% summarise(avg_score = mean(score))

This code groups data by 'name' and calculates the average 'score' for each group.

Execution Table

Step	Action	Group State	summarise Calculation	Output Row
1	Start with data frame	No groups	No calculation	Full data frame
2	Apply group_by(name)	Groups: A, B	No calculation yet	Data grouped by name
3	summarise(avg_score = mean(score)) for group A	Group A: rows with name 'A'	mean(10, 20) = 15	Row: name = A, avg_score = 15
4	summarise(avg_score = mean(score)) for group B	Group B: rows with name 'B'	mean(30, 40) = 35	Row: name = B, avg_score = 35
5	Combine summary rows	Groups combined	Summary complete	Output: 2 rows with avg_score per name

💡 All groups processed, summarise returns one row per group with calculated summaries.

Variable Tracker

Variable	Start	After group_by	After summarise	Final
data	[4 rows]	[Grouped by name: A, B]	[2 rows: avg_score per group]	[2 rows: summary output]
group	None	A, B groups created	Groups processed	Groups combined in output
avg_score	None	None	15 (A), 35 (B)	Summary column with averages

Key Moments - 2 Insights

Why does summarise() return fewer rows than the original data?

Because summarise() calculates one summary row per group created by group_by(), reducing multiple rows into one per group as shown in execution_table rows 3-5.

What happens if you use summarise() without group_by()?

summarise() then calculates summary over the entire data frame, returning a single row, unlike when grouped as shown in execution_table step 2.

Visual Quiz - 3 Questions

Look at the execution_table, what is the avg_score for group B at step 4?

A 35

B 40

C 30

D 70

💡 Hint

Check execution_table row 4 under 'summarise Calculation' for group B.

At which step does the data get split into groups?

A Step 1

B Step 3

C Step 2

D Step 5

💡 Hint

Look at execution_table row 2 where group_by() is applied.

If we remove group_by(), how many rows will summarise() return?

A Same as original data

B One row

C Zero rows

D Two rows

💡 Hint

Refer to key_moments explanation about summarise() without group_by().

Concept Snapshot

summarise() with group_by() in R:
- group_by() splits data into groups
- summarise() computes summary per group
- Output has one row per group
- Without group_by(), summarise() summarizes whole data
- Use with dplyr pipe %>% for chaining

Full Transcript

This visual trace shows how summarise() works with group_by() in R. First, the data frame is grouped by a column, splitting rows into groups. Then summarise() calculates summary statistics like mean for each group, returning one row per group. The execution table shows each step: starting with data, grouping by 'name', calculating average scores per group, and combining results. Variables like 'data', 'group', and 'avg_score' change as grouping and summarising happen. Key moments clarify why summarise() reduces rows and what happens without grouping. The quiz tests understanding of group values, steps, and summarise behavior. The snapshot summarizes usage and behavior for quick reference.