Power query filter column in julian format by today

When working with Power Query in Julia, you may come across the need to filter a column by today’s date. This can be particularly useful when dealing with time-sensitive data. In this article, we will explore three different ways to achieve this.

Option 1: Using the Dates package

The first option involves using the Dates package in Julia. This package provides a wide range of functions and types for working with dates and times. To filter a column by today’s date, you can follow these steps:

using Dates

# Get today's date
today_date = Dates.today()

# Filter column by today's date
filtered_data = filter(row -> row.column_name == today_date, data)

This code snippet imports the Dates package and uses the `today()` function to get today’s date. Then, it filters the `data` column by comparing each row’s `column_name` with today’s date. The filtered data is stored in the `filtered_data` variable.

Option 2: Using the DateTime package

If you need more flexibility in working with dates and times, you can use the DateTime package. This package extends the functionality provided by the Dates package. Here’s how you can filter a column by today’s date using DateTime:

using Dates
using DateTime

# Get today's date
today_date = Dates.today()

# Convert today's date to DateTime
today_datetime = DateTime(today_date)

# Filter column by today's date
filtered_data = filter(row -> row.column_name == today_datetime, data)

In this code snippet, we first import both the Dates and DateTime packages. Then, we get today’s date using the `today()` function from the Dates package. Next, we convert today’s date to a DateTime object using the DateTime constructor. Finally, we filter the `data` column by comparing each row’s `column_name` with today’s DateTime object.

Option 3: Using the Queryverse package

If you prefer a more high-level approach, you can use the Queryverse package. This package provides a unified interface for working with data in Julia. Here’s how you can filter a column by today’s date using Queryverse:

using Queryverse

# Filter column by today's date
filtered_data = @from row in data begin
    @where row.column_name == Dates.today()
    @select row
    @collect DataFrame
end

In this code snippet, we import the Queryverse package. Then, we use the `@from` macro to specify the data source (`data`). Inside the `@from` block, we use the `@where` macro to filter the column by today’s date. The `@select` macro is used to select the filtered rows, and the `@collect` macro is used to collect the result into a DataFrame.

After exploring these three options, it is clear that the best approach depends on your specific requirements and preferences. If you need a lightweight solution with basic date functionality, Option 1 using the Dates package is a good choice. If you require more advanced date and time manipulation, Option 2 using the DateTime package is recommended. Finally, if you prefer a high-level approach with a unified interface, Option 3 using the Queryverse package is the way to go.