In Julia, you can use rightjoin
function to perform a right outer join on two data structures. Below are more details and examples:
A right outer join combines the rows from two data structures and returns all the rows from the second data structure, along with the matching rows from the first data structure. If there is no match in the first data structure for a row in the second data structure, the function will return NULL
or missing
for the columns in the first data structure.
Right Outer Join on DataFrames in Julia Examples
Here is an example of how to use the rightjoin
function in Julia:
using DataFrames
# Create two data frames
df1 = DataFrame(id = [1, 2, 3, 4], name = ["Alice", "Bob", "Charlie", "Dave"])
df2 = DataFrame(id = [3, 4, 5, 6], age = [20, 25, 30, 35])
# Perform a right outer join on the two data frames
df3 = rightjoin(df1, df2, on = :id)
# Print the resulting data frame
println(df3)
The output of this code will be:
4×3 DataFrame
Row │ id name age
│ Int64 String? Int64
─────┼───────────────────────
1 │ 3 Charlie 20
2 │ 4 Dave 25
3 │ 5 missing 30
4 │ 6 missing 35
As you can see, the resulting data frame contains all the rows from the second data frame, along with the matching rows from the first data frame. If there is no match in the first data frame for a row in the second data frame, the function returns missing
for the columns in the first data frame.
You can also perform a right outer join on multiple columns by specifying a vector of symbols for the on
keyword argument. For example:
df1 = DataFrame(id = [1, 2, 3, 4], name = ["Alice", "Bob", "Charlie", "Dave"], city = ["New York", "Chicago", "Los Angeles", "San Francisco"])
df2 = DataFrame(id = [3, 4, 5, 6], age = [20, 25, 30, 35], city = ["Los Angeles", "San Francisco", "Miami", "Dallas"])
df3 = rightjoin(df1, df2, on = [:id, :city])
This will perform a right outer join on both the id
and city
columns, resulting in the following data frame:
The output of this code will be:
4×4 DataFrame
Row │ id name city age
│ Int64 String? String Int64
─────┼──────────────────────────────────────
1 │ 3 Charlie Los Angeles 20
2 │ 4 Dave San Francisco 25
3 │ 5 missing Miami 30
4 │ 6 missing Dallas 35