In Julia, you can use the antijoin
function from the DataFrames
package to perform an anti-join operation on two dataframes.
An anti-join returns all rows from the first dataframe (the left dataframe) that do not have a match in the second dataframe (the right dataframe). The resulting dataframe will have the same number of columns as the left dataframe, and will only contain rows that do not have a match in the right dataframe.
Here is a visual representation of an anti-join using two dataframes df1
and df2
:
df1 df2 +----+ +----+ | id | | id | +----+ +----+ | 1 | | 2 | | 2 | | 3 | | 3 | | 5 | | 4 | +----+ +----+ Result: +----+ | id | +----+ | 1 | +----+
Anti Join on DataFrames in Julia Examples
Here is an example of how to use the antijoin
function:
using DataFrames # Define the left dataframe df1 = DataFrame(id = [1, 2, 3, 4], name = ["Alice", "Bob", "Charlie", "Dave"]) # Define the right dataframe df2 = DataFrame(id = [2, 3, 5], department = ["Sales", "Marketing", "Engineering"]) # Perform the anti-join result = antijoin(df1, df2, on = :id) # Print the resulting dataframe println(result)
The output of this code will be:
2×2 DataFrame Row │ id name │ Int64 String ─────┼─────────────── 1 │ 1 Alice 2 │ 4 Dave
In this example, the antijoin
function performs an anti-join on df1
and df2
using the id
column as the join key. The resulting dataframe result
contains all rows from df1
that do not have a matching id
in df2
, and only includes the id
and name
columns from df1
.
You can also specify multiple columns as the join key by passing a vector of symbols to the on
argument, like this:
result = antijoin(df1, df2, on = [:id, :name])
In this case, the anti-join will only return rows that do not have a matching value in both the id
and name
columns.
Here is another example of using the antijoin
function to perform an anti-join on two dataframes:
using DataFrames # Define the left dataframe df1 = DataFrame(id = [1, 2, 3, 4], name = ["Alice", "Bob", "Charlie", "Dave"], department = ["Sales", "Marketing", "Engineering", "Human Resources"]) # Define the right dataframe df2 = DataFrame(id = [2, 3, 5], department = ["Sales", "Marketing", "Engineering"]) # Perform the anti-join result = antijoin(df1, df2, on = :department) # Print the resulting dataframe println(result)
The output of this code will be:
1×3 DataFrame Row │ id name department │ Int64 String String ─────┼──────────────────────────────── 1 │ 4 Dave Human Resources
In this example, the antijoin
function performs an anti-join on df1
and df2
using the department
column as the join key. The resulting dataframe result
contains all rows from df1
that do not have a matching department
in df2
, and includes all columns from df1
.
You can also specify multiple columns as the join key by passing a vector of symbols to the on
argument, like this:
result = antijoin(df1, df2, on = [:id, :department])
In this case, the anti-join will only return rows that do not have a matching value in both the id
and department
columns.
Related:
- Using Inner Join on DataFrames in Julia
- Using Right Join on DataFrames in Julia
- Using Left Join on DataFrames in Julia
- Using Semi Join on DataFrames in Julia
- Using Outer Join on DataFrames in Julia