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labontyk
New Member

Compare semesters-registration fall 2015 to fall 2014

I work at a college and have a term (semester) field, an example would be 2014fall and 2015fall.  The terms started on different dates (off a few days each year say 2014 was 10/11 and 2015 was 10/14).  I have a slicer set up to show 2014fall and 2015 fall on a cluster column chart.  Now I want to compare them.  They show up in the graph as two separte mini graphs (one in 2014 and one in 2015) because the x axis has dates, when I want them side by side, but the dates don't match.  I have date in axis, term in legend and headcount in value fields for the chart.   I also created a DAX function called datelastyear (subtracted 363 days from this years dates) but not sure how to use it in the graph if I need it.  HELP!

1 ACCEPTED SOLUTION

Do you have a date lookup/dimension table?

 

If so, you could create a column called semester_day  which had a number 1 to 365 starting on the first day of the semester, you could also have the same for semester_week 1 to 52.

 

You could then use semster_day (or week) as the X axis, headcount for the value and semester year as the legend.

 

If you added a weekday column (just containing the name of the day) as well you could do analsyis comparing the days of the week to see which had the highest headcount 

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2 REPLIES 2
Greg_Deckler
Super User
Super User

So, you should be able to replace Date with DateLastYear for this year's data in the x-axis and then the dates should match, right?


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DAX is easy, CALCULATE makes DAX hard...

Do you have a date lookup/dimension table?

 

If so, you could create a column called semester_day  which had a number 1 to 365 starting on the first day of the semester, you could also have the same for semester_week 1 to 52.

 

You could then use semster_day (or week) as the X axis, headcount for the value and semester year as the legend.

 

If you added a weekday column (just containing the name of the day) as well you could do analsyis comparing the days of the week to see which had the highest headcount 

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