Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Level up your Power BI skills this month - build one visual each week and tell better stories with data! Get started

Reply
y5famfnatudu
Resolver I
Resolver I

Averagex vs Division (which one for calculating Tickets per Working Day)

Hello,

 

I'm sorry if it's a stupid question, I would like to calculate the number of tickets per working day.

Should I be using Averagex(Working_Days, Tickets) or Divide (Tickets, Working_Days)? and Why?

 

Thank you so much

Simon

1 ACCEPTED SOLUTION
OwenAuger
Super User
Super User

Hello Simon,

Quite an interesting question actually 🙂

 

The "correct" method to use would depend on your exact requirements.

 

The key points to be aware of (I'm making some assumptions about how you've defined Working_Days and Tickets):

  • AVERAGEX disregards any rows of the table supplied in the 1st argument where the 2nd argument is blank. In your case, this would have the effect of dividing Tickets by the count of working days where Tickets is nonblank.
  • The DIVIDE method would include all Working Days regardless of the values of Tickets

Personally, I prefer to use the DIVIDE method as I would generally want to count all Working Days regardless of whether Tickets has a nonblank value on any given date.

 

To illustrate, I have attached a small PBIX example. For this example, let's assume that Working Days are Mon-Fri.

OwenAuger_1-1688295084327.png

The two important measures to illustrate the difference are:

# Tickets per Working Day AVERAGEX = 
AVERAGEX (
    FILTER ( 'Date', 'Date'[Work Day] = 1 ),
    [# Tickets]
)
# Tickets per Working Day DIVIDE = 
DIVIDE ( [# Tickets], [Working Days Count] )

In this example, over the first 7 days of January 2023:

  • # Tickets = 17
  • Number of working days on which # Tickets is nonblank = 4 (Mon, Wed, Thu, Fri)
  • Number of working days total = 5 (Mon-Fri)
  • AVERAGEX measure returns 17 / 4 = 4.25
  • DIVIDE measure returns 17 / 5 = 3.40

Regards


Owen Auger
Did I answer your question? Mark my post as a solution!
Blog
LinkedIn

View solution in original post

2 REPLIES 2
OwenAuger
Super User
Super User

Hello Simon,

Quite an interesting question actually 🙂

 

The "correct" method to use would depend on your exact requirements.

 

The key points to be aware of (I'm making some assumptions about how you've defined Working_Days and Tickets):

  • AVERAGEX disregards any rows of the table supplied in the 1st argument where the 2nd argument is blank. In your case, this would have the effect of dividing Tickets by the count of working days where Tickets is nonblank.
  • The DIVIDE method would include all Working Days regardless of the values of Tickets

Personally, I prefer to use the DIVIDE method as I would generally want to count all Working Days regardless of whether Tickets has a nonblank value on any given date.

 

To illustrate, I have attached a small PBIX example. For this example, let's assume that Working Days are Mon-Fri.

OwenAuger_1-1688295084327.png

The two important measures to illustrate the difference are:

# Tickets per Working Day AVERAGEX = 
AVERAGEX (
    FILTER ( 'Date', 'Date'[Work Day] = 1 ),
    [# Tickets]
)
# Tickets per Working Day DIVIDE = 
DIVIDE ( [# Tickets], [Working Days Count] )

In this example, over the first 7 days of January 2023:

  • # Tickets = 17
  • Number of working days on which # Tickets is nonblank = 4 (Mon, Wed, Thu, Fri)
  • Number of working days total = 5 (Mon-Fri)
  • AVERAGEX measure returns 17 / 4 = 4.25
  • DIVIDE measure returns 17 / 5 = 3.40

Regards


Owen Auger
Did I answer your question? Mark my post as a solution!
Blog
LinkedIn

WOW @OwenAuger , a great description for how it works, I really appreciate it so much.

Regards, Simon

Helpful resources

Announcements
April Power BI Update Carousel

Power BI Monthly Update - April 2026

Check out the April 2026 Power BI update to learn about new features.

Fabric SQL PBI Data Days

Data Days 2026 coming soon!

Sign up to receive a private message when registration opens and key events begin.

New to Fabric survey Carousel

New to Fabric Survey

If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.

Power BI DataViz World Championships carousel

Power BI DataViz World Championships - June 2026

A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.