join functions (left_join, inner_join) in R Programming - Mini Project: Build & Apply

Using join functions (left_join, inner_join) in R

📖 Scenario: You work in a small bookstore. You have two tables: one with book details and another with sales data. You want to combine these tables to see which books sold and their details.

🎯 Goal: Learn how to use left_join and inner_join functions in R to combine two data frames based on a common column.

📋 What You'll Learn

Create two data frames named books and sales with exact data

Create a variable key_column with the column name to join on

Use left_join to join books and sales on key_column

Use inner_join to join books and sales on key_column

Print the results of both joins

💡 Why This Matters

🌍 Real World

Combining data from different sources is common in data analysis, like joining customer info with purchase records.

💼 Career

Knowing how to join tables is essential for data scientists, analysts, and anyone working with databases or data frames.

1

Create the initial data frames

Create a data frame called books with columns book_id and title containing these rows: (1, "The Alchemist"), (2, "1984"), (3, "To Kill a Mockingbird"). Also create a data frame called sales with columns book_id and copies_sold containing these rows: (1, 150), (3, 200), (4, 50).

R Programming

# Create data frames books and sales with given data
# Your code here

Need a hint?

Use data.frame() to create each table with the exact column names and values.

2

Create the join key variable

Create a variable called key_column and set it to the string "book_id" to use as the join column.

R Programming

library(dplyr)

books <- data.frame(
  book_id = c(1, 2, 3),
  title = c("The Alchemist", "1984", "To Kill a Mockingbird")
)

sales <- data.frame(
  book_id = c(1, 3, 4),
  copies_sold = c(150, 200, 50)
)

# Create key_column variable with value "book_id"
# Your code here

Need a hint?

Assign the string "book_id" to the variable key_column.

3

Perform left_join and inner_join

Use left_join to join books and sales on key_column and save the result in left_joined. Then use inner_join to join books and sales on key_column and save the result in inner_joined.

R Programming

library(dplyr)

books <- data.frame(
  book_id = c(1, 2, 3),
  title = c("The Alchemist", "1984", "To Kill a Mockingbird")
)

sales <- data.frame(
  book_id = c(1, 3, 4),
  copies_sold = c(150, 200, 50)
)

key_column <- "book_id"

# Use left_join and inner_join on books and sales using key_column
# Your code here

Need a hint?

Use left_join(books, sales, by = key_column) and assign it to left_joined. Similarly, use inner_join(books, sales, by = key_column) and assign it to inner_joined.

4

Print the joined data frames

Print the left_joined data frame, then print the inner_joined data frame.

R Programming

library(dplyr)

books <- data.frame(
  book_id = c(1, 2, 3),
  title = c("The Alchemist", "1984", "To Kill a Mockingbird")
)

sales <- data.frame(
  book_id = c(1, 3, 4),
  copies_sold = c(150, 200, 50)
)

key_column <- "book_id"

left_joined <- left_join(books, sales, by = key_column)
inner_joined <- inner_join(books, sales, by = key_column)

# Print left_joined and inner_joined
# Your code here

Need a hint?

Use print(left_joined) and print(inner_joined) to show the results.