Interactive data table in pluto jl via a silly hack

Julia is a powerful programming language that is widely used for data analysis and scientific computing. One of its popular features is Pluto.jl, a notebook interface that allows for interactive data exploration. In this article, we will explore different ways to create an interactive data table in Pluto.jl using a silly hack.

Option 1: Using HTML and CSS

The first option is to use HTML and CSS to create an interactive data table in Pluto.jl. We can start by creating a simple HTML table and styling it using CSS. Here’s an example:

using PlutoUI

function create_table(data)
    table_html = """
    
    """
    
    for row in data
        table_html *= ""
        for value in row
            table_html *= ""
        end
        table_html *= ""
    end
    
    table_html *= """
        

        

            

                
Column 1
                
Column 2
                
Column 3
            
        
        
$value
    
    """
    
    PlutoUI.HTML(table_html)
end

data = [["Value 1", "Value 2", "Value 3"], ["Value 4", "Value 5", "Value 6"]]
create_table(data)

This code defines a function create_table that takes a 2D array of data as input and generates an HTML table. The table is then displayed using the PlutoUI.HTML function. You can customize the table by modifying the HTML and CSS code.

Option 2: Using DataFrames.jl

The second option is to use the DataFrames.jl package to create an interactive data table in Pluto.jl. DataFrames.jl provides a powerful data manipulation and analysis toolkit. Here’s an example:

using DataFrames
using PlutoUI

function create_table(data)
    df = DataFrame(data)
    PlutoUI.Table(df)
end

data = [["Value 1", "Value 2", "Value 3"], ["Value 4", "Value 5", "Value 6"]]
create_table(data)

This code defines a function create_table that takes a 2D array of data as input and converts it into a DataFrame. The DataFrame is then displayed using the PlutoUI.Table function. You can perform various operations on the DataFrame, such as filtering, sorting, and aggregating the data.

Option 3: Using DataTables.jl

The third option is to use the DataTables.jl package to create an interactive data table in Pluto.jl. DataTables.jl provides a flexible and feature-rich data table library. Here’s an example:

using DataTables
using PlutoUI

function create_table(data)
    table = DataTable(data)
    PlutoUI.Table(table)
end

data = [["Value 1", "Value 2", "Value 3"], ["Value 4", "Value 5", "Value 6"]]
create_table(data)

This code defines a function create_table that takes a 2D array of data as input and creates a DataTable object. The DataTable is then displayed using the PlutoUI.Table function. You can customize the appearance and behavior of the DataTable by modifying its options.

After exploring these three options, it is clear that using DataTables.jl provides the most flexibility and features for creating an interactive data table in Pluto.jl. It allows for advanced data manipulation and provides a rich set of options for customizing the table. Therefore, Option 3 is the better choice for creating an interactive data table in Pluto.jl.