Q
qh8519a
I am trying to come up with a way to identify the half hour impact from
several exceptions across multiple days.
The fields that are used would be a start moment ( 9/3/2008 3:45:00 PM),
stop moment (9/3/2008 4:30:00 PM), and total minutes (45). I have hundreds
of exceptions with the above data and I need to identify the half hourly
impact. I was initially thinking of using the countif function across all 48
daily intervals, but I was getting hung up with exceptions that crossed
midnight.
When I have one exception with a start time of 7:15 and an end time of 8:20,
I would like to see the following impacts:
7:00 - .5
7:30 - 1
8:00 - .66
I have another exception with a start time 7:30 and an end time of 9:15, I
would like to see the following impacts:
7:30 – 1
8:00 – 1
8:30 – 1
9:00 - .5
Then when I roll them all up, I would see the following:
7:00 - .5
7:30 – 2
8:00 – 1.66
8:30 – 1
9:00 - .5
Thanks again for all of your help!
Drew
several exceptions across multiple days.
The fields that are used would be a start moment ( 9/3/2008 3:45:00 PM),
stop moment (9/3/2008 4:30:00 PM), and total minutes (45). I have hundreds
of exceptions with the above data and I need to identify the half hourly
impact. I was initially thinking of using the countif function across all 48
daily intervals, but I was getting hung up with exceptions that crossed
midnight.
When I have one exception with a start time of 7:15 and an end time of 8:20,
I would like to see the following impacts:
7:00 - .5
7:30 - 1
8:00 - .66
I have another exception with a start time 7:30 and an end time of 9:15, I
would like to see the following impacts:
7:30 – 1
8:00 – 1
8:30 – 1
9:00 - .5
Then when I roll them all up, I would see the following:
7:00 - .5
7:30 – 2
8:00 – 1.66
8:30 – 1
9:00 - .5
Thanks again for all of your help!
Drew