summarise() with group_by() in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the group_by() function do in R's dplyr package?

group_by() splits the data into groups based on one or more variables. It prepares the data so that you can perform operations on each group separately.

beginner

What is the purpose of summarise() in combination with group_by()?

summarise() creates a summary statistic for each group created by group_by(). For example, it can calculate the average or total for each group.

beginner

How do you calculate the average of a column score for each group of team in a dataframe df?

df %>%
  group_by(team) %>%
  summarise(avg_score = mean(score))

This groups the data by team and calculates the average score for each team.

beginner

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

summarise() will calculate the summary statistic for the entire dataset, not by groups.

intermediate

Can you use multiple summary functions inside summarise() after grouping?

Yes, you can calculate many summaries at once. For example:

df %>%
  group_by(team) %>%
  summarise(avg_score = mean(score), max_score = max(score))

What does group_by() do before using summarise()?

A Splits data into groups based on variables

B Deletes rows from the data

C Sorts the data alphabetically

D Changes data types of columns

group_by() organizes data into groups so that summarise() can calculate summaries for each group separately.

What will summarise() do if used without group_by()?

A Throw an error

B Calculate summary for each row

C Calculate summary for the whole dataset

D Create new groups automatically

Without grouping, summarise() returns a single summary for the entire data.

Which of these is a valid way to calculate the total sales per region using dplyr?

A df %>% filter(region) %>% summarise(total_sales = sum(sales))

B df %>% summarise(total_sales = sum(sales)) %>% group_by(region)

C df %>% group_by(sales) %>% summarise(total_region = sum(region))

D df %>% group_by(region) %>% summarise(total_sales = sum(sales))

First group by region, then summarise sales per group.

Can you use multiple summary calculations inside one summarise() call?

A Yes, you can calculate many summaries at once

B No, only one summary is allowed

C Only if you use <code>group_by()</code> twice

D Only with special packages

summarise() can include many summary columns separated by commas.

What does this code do?<br>

df %>% group_by(category) %>% summarise(count = n())

A Calculates mean of category

B Counts rows in each category group

C Filters rows with category

D Creates new categories

n() counts the number of rows in each group.

Explain how group_by() and summarise() work together to summarize data.

Think about how you might count or average scores for each team separately.

Describe a real-life example where you would use group_by() with summarise().

Imagine you have sales data and want to know total sales per store.