Leave entitlement vs. usage analysis with Power Query

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Last Friday, I asked you to analyze “sick leave entitlement vs. usage” data and answer homework questions. We got several interesting responses to that. Today, let me share a quick video highlighting how to analyze such data with Power Query.

entitlement-vs-usage-power-query-analysis

This is part of our Power Mondays series, where every Monday you will learn something new & useful about Power BI, Power Query and Power Pivot.

Leave Entitlement vs. Usage Analysis – The problem

The problem is simple. We have a bunch of employees with their leave entitlement. We also know how many leaves they took.

sample data - sick leave entitlement vs. usage

 

Given these two tables, you want to answer questions like:

  • Which employees took exactly 100% of their allocated leave?
  • Which people never took any leave?
  • Who are the people taking 100% of their leave?

If you also know when an employee took the leave (date), you can ask questions like:

  • Assuming leave entitlement resets at start of year (1 Jan), which employees are using 100% of their entitlement

Leave Entitlement vs. Usage Analysis – Solution with Power Query

While we can use Excel formulas (or VBA, pivot tables + power pivot etc.) to answer the questions above, I think using Power Query is the simplest way to crack this.

I made a quick video explaining the problem, solution, how to enhance it when you have multi-year data. Check it out below (or on our Youtube channel).

You will also learn:

  • How to merge (join) two tables in Power Query
  • Using basic & advanced group by in Power Query
  • How to extract year from date values
  • Replacing errors with some value
  • Creating conditional columns in PQ

 

Download solution workbook

Click here to download the solution workbook for this topic. Examine the Power Query definitions to learn more.

How do you like the Power Query solution?

I love how versatile and elegant Power query based solutions are. What about you? Do you use PQ to solve problems like this? Please share your experience / feedback in the comments section.

 

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3 Responses to “Filter one table if the value is in another table (Formula Trick)”

  1. Montu says:

    What about the opposite? I want a list of products without sales or customers with no orders. So I would exclude the ones that are on the other table.

    • Chandoo says:

      Good question. You can check for the =0 as countifs result. for example,
      =FILTER(orders, COUNTIFS(products, orders[Product])=0)
      should work in this case.

      PS: I have added this example to the article now.

  2. Raphael says:

    Hi there!

    Could i check if there was a way to return certain fields of the table only?

    so based off your example above, i would like to continue to use the 'Products" table as a way to filter out items from my "Orders" table, but only want to show maybe only the "Product" and "Order Value" fields, rather than all 5 fields (sales person, customer, product, date, order value).

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