Left Join in R

What is a Left Join?

Left Join, in databases, combines information from two tables based on a column. The resulting table includes all entries from the table and only the corresponding entries from the table. If there is no match, the data from the table will be empty. This method is beneficial when you want to retain all data from one table regardless of matches in the other.

In the R programming language, using a join is advantageous for merging data from datasets. It enables you to merge two datasets by a shared column while preserving all entries from the dataset and incorporating matching entries from the right dataset. This approach prevents loss of data during merging. Ensures a comprehensive view of the combined data.

Different types of joins offer varying functionalities:

• Left Join — Includes all records from the dataset along with matching records from the dataset. Unmatched records in the dataset are represented as null.
• Inner Join — Only includes matching records in both datasets.
• Right Join — Incorporates all records from the dataset alongside matching records from the dataset. Unmatched records in the dataset are null.
• Full Join — Combines all entries, from both datasets, marking records as null regardless of their source.

dplyr Package

The dplyr package, in R is known for its user syntax that simplifies data manipulation tasks. It comes equipped with functions to filter, sort, group, summarize and change data. If you want to get started with dplyr you can first install the package by running the command install.packages("dplyr"). Once installed, load the package using library(dplyr). One handy feature is the %>% operator from the magrittr package, which allows you to chain functions together seamlessly.

Some key functions in dplyr include filter() for selecting rows based on conditions, group_by() for subgrouping data based on variables summarize() for calculating summary statistics ) for creating or altering variables and arrange() for reordering rows based on variables.

To effectively utilize dplyr for data manipulation tasks:

1. Load the package.
2. Employ functions like filter() ) arrange() summarize() and join() as needed.
3. Use the %>% operator to chain functions together to create code.

One notable advantage of using dplyr is its approach, to joins. Unlike merge() which may alter row orderings from the dataset, dplyrs left join method maintains the row sequence from the first dataframe. To execute a left join operation:‍


library(dplyr)
joined_df <- left_join(df1, df2, by = "team")

Performing a Left Join in R

A left join combines rows from two datasets based on a common variable, keeping all rows from the left dataset. This is useful for merging data from different sources into a single dataset.

Syntax of a Left Join

Using dplyr:‍


left_join(left_dataframe, right_dataframe, by = "common_column")

Example Dataset for Demonstrating Left Join

1. Employees Table:
   • Columns: employee_id, first_name, last_name, department, designation
   • Sample Data: Information for a few employees.
2. Salaries Table:
   • Columns: employee_id, salary_amount, year
   • Sample Data: Salary information for different employees.
3. Common Column: employee_id
4. Left Join:‍


library(dplyr)
joined_df <- left_join(employees, salaries, by = "employee_id")

Step-by-Step Guide to Performing a Left Join in R

Using the merge() function:

merged_df <- merge(left_df, right_df, by = "common_variable", all.x = TRUE)

Using the left_join() function from dplyr:‍


library(dplyr)
merged_df <- left_join(left_df, right_df, by = "common_variable")

Types of Joins in R

Inner Joins

Combines rows from two tables based on a matching key and includes only matching rows. Unmatched rows are excluded.

Outer Joins

Includes:

• Left Join: Keeps all observations in the left data frame and matching observations from the right.
• Right Join: Keeps all observations in the right data frame and matching observations from the left.
• Full Join: Keeps all observations from both data frames, filling non-matching observations with missing values.

Left Joins

Combines two datasets based on a common column, including all rows from the left dataset and matching rows from the right dataset. Unmatched columns are null.

To perform a left join:

left_join(left_dataframe, right_dataframe, by = "common_column")