I have to visualize an accumulated monthly budget on a daily level.
Means a running total for the individual month on a daily basis.
The budget targets are provided in a table like this:
+------+------------+--------+
| Area | Year-Week | Budget |
+------+------------+--------+
| A | 2020-01 | 50 |
| A | 2020-02 | 25 |
| A | 2020-03 | 50 |
| A | 2020-04 | 25 |
| B | 2020-01 | 50 |
| B | 2020-02 | 50 |
| B | 2020-03 | 50 |
| B | 2020-04 | 75 |
+------+------------+--------+
As you can see, the monthly budget for January is the sum of 2020-01 - 2020-04
The structure is provided in the calendar table. So I have the information on which week belongs to which month.
What I need to do is to create a dax measure that divides the weekly budget by the working days.
THe calendar has also the information of calendar days. For this purpose I have add this measure:
Working Days =
VAR vSelectedMonth =
SELECTEDVALUE ( 'Calendar'[Fiscal Month Number])
RETURN
CALCULATE (
COUNTROWS ( 'Calendar' ),
FILTER (
'Calendar',
'Calendar'[Fiscal Month Number] = vSelectedMonth
&& 'Calendar'[IsWorkingDay] = 1
)
)
Now, how can I divide the weekly budget by the working days for the corresponding week and than to accumulate this information for the whole month?
Based on the provided information the result should be something like that:
+------+------------+----------------+
| Area | Date | Running Budget |
+------+------------+----------------+
| A | 01.01.2020 | 10 |
| A | 02.01.2020 | 20 |
| A | 03.01.2020 | 30 |
| A | 04.01.2020 | 40 |
| A | 05.01.2020 | 50 |
| A | 06.01.2020 | 50 |
| A | 07.01.2020 | 50 |
| A | 08.01.2020 | 55 |
+------+------------+----------------+
Of course, if the corresponding date is not a working day, that value from the day before should be shown.
I am grateful for every help!
Please let me know if you need further information.
Best Regards
Related
I am trying to implement a YtD measure for my report in Excel with Power Pivot. My source looks roughly like this:
Table 1
| Month | Store | Branch | Article | Value |
|----------|-------|--------|---------|-------|
| January | 1 | A | Sales | 200 |
| January | 1 | A | Costs | 100 |
| January | 1 | A | Rent | 10 |
| February | 1 | A | Costs | 20 |
| February | 1 | A | Sales | 80 |
| March | 1 | A | Costs | 30 |
| March | 1 | A | Sales | 80 |
| February | 2 | B | Sales | 100 |
| February | 2 | B | Costs | 40 |
| February | 2 | B | Rent | 20 |
Linked to it, are a table Table 2 of months (name - number from 1 to 12), a table Table 3 of unique articles and a table Table 4 of unique stores with their branches.
I want to be able to display YtD for every article depending on the chosen month.
I have measures:
Val. := sum(table1[Value])
YtD1:= calculate(Val., all('Table 2'[Name]))
The former sums across all the values, which are filtered by article in my pivot report. The latter calculates a YtD across all months. It works, but I have to rewrite it so that it responds to filtering the last month and sums from the first month to the selected month.
I have tried to format month numbers to process them as dates (e.g. first day of the month), but couldn't appropriately handle the FORMAT function.
I have also tried to do a sum of months, i.e.:
YtD2= calculate(Val., filter(Table2;Table2[Number]<=2))
which, I hoped, would count months from January to February. It doesn't seem to do any good, resulting in numbers I cannot explain.
My desired output should look like this:
| Store | Sales | | Costs | |
|-------|-------|-----|-------|-----|
| | Val. | YtD | Val. | YtD |
| 1 | 80 | 280 | 20 | 120 |
| 2 | 100 | 100 | 40 | 40 |
if data is filtered by February.
Or
| Store | Sales | | Costs | |
|-------|-------|-----|-------|-----|
| | Val. | YtD | Val. | YtD |
| 1 | 160 | 360 | 50 | 150 |
| 2 | 100 | 100 | 40 | 40 |
if February and March are selected (Val. is displayed for February and March, but YtD from January to March).
Is there a way to implement this in DAX? Can this be done without conversion from month names (or numbers) to some date&
If not, can I get it to work for a month filter instead of a month slicer? That is, if only one month can be selected.
I cannot use variables and similar Power BI features.
Try:
YTD :=
VAR MaxSelectedMonth =
MAX( Table2[Number] )
RETURN
CALCULATE(
[Val.],
FILTER(
ALL( Table2 ),
Table2[Number] <= MaxSelectedMonth
)
)
Within an Azure dashboard I'm wanting to create a tile which shows exceptions over the last 7 days, however the KQL below will obviously only return a data point where there has been an exception on a particular day.
How do I get it to return zero on a day when there were no exceptions?
exceptions
| where (* has 'insights')
and timestamp >= ago(7d)
| summarize Count=count()
by Date2=bin(timestamp, 1d)
| project Date=(format_datetime(Date2 , 'dd-MM-yyyy')), Count
| sort by Date
Use make_series instead of summarize.
Here's an example:
range x from 0 to 99 step 1
| where x !between(60 .. 79)
| make-series count() on x step 10
| mv-expand count_, x
| project x, count_
Output:
| x | count_ |
|----|--------|
| 0 | 10 |
| 10 | 10 |
| 20 | 10 |
| 30 | 10 |
| 40 | 10 |
| 50 | 10 |
| 60 | 0 |
| 70 | 0 |
| 80 | 10 |
| 90 | 10 |
+-------------+----------+----------+--------+------------------+
| customer_id | date | time | answer | missed_call_type |
+-------------+----------+----------+--------+------------------+
| 101 | 2018/8/3 | 12:13:00 | no | employee |
| 102 | 2018/8/3 | 12:15:00 | no | customer |
| 103 | 2018/8/3 | 12:20:00 | no | employee |
| 102 | 2018/8/3 | 15:15:00 | no | customer |
| 101 | 2018/8/3 | 18:15:00 | no | employee |
| 105 | 2018/8/3 | 18:18:00 | no | customer |
| 102 | 2018/8/3 | 19:18:00 | no | employee |
+-------------+----------+----------+--------+------------------+
I got a table whick looks like this and wanted to calculate average interval time for those who did not answer the phone.
for this example,the average interval time is:
{(18:15:00-12:13:00)+[(19:18:00-15:15:00)+(15:15:00-12:15:00)]/2}/2
the problem is I could only manipulate it in Excel...someone knows Excel please help!or any suggestion is fine,I am familiar with SQL.
I've entered your data as shown below, and added a time_to_next_call-column which calculates the interval until the next call to the same customer_id using the formula: =INDEX(C3:C$8,MATCH(A2,A3:A$8,0))-C2 for the first cell in the data set.
Then, list your customer IDs in a column, and use and AVERAGEIF-function to calcualte the average time_to_next_call for that customer_ID, as shown below:
As I've placed the customer_id 101 in cell A12, my function for calculating the average time_to_next_call is: =AVERAGEIFS($F$2:$F$8,$A$2:$A$8,A13,$F$2:$F$8,">0")
Adjust your ranges as appropriate to fit your workbook. Hope this helps
I have a table with the following criteria.There are multiple week endings for multiple projects. The hour/cost column can be positive or negative and are correlated (positive hours/positive costs). I'm able to get a distinct count of week ending for the project if there are any costs to it(+or-), but I want to get a distinct count only if the sum of hours or costs are positive.
Since charges can be + or -, and potentially cancel out for a week ending, this would alter my average formula if it were to count a week with sum of 0.
I'm trying to build a calculated field that I could add to my Pivot table that lists the actual charged weeks when I filter by Project. In the sample, there are 4 unique dates with sum greater than 0, but my current formula gives me 7 unique dates, disregarding positive sum.
WeekEndDate| Project | Hours | Cost
Sample Data
+---------------+---------+--------+-------------+
| WeekEndDate | Project | Hours | Cost |
+---------------+---------+--------+-------------+
| 10/7/16 | C7119A | 2.00 | $122.00 |
| 10/7/16 | C7119A | 32.00 | $1,952.00 |
| 10/7/16 | C7119A | 1.50 | $91.50 |
| 10/7/16 | C7119A | -32.00 | ($1,952.00) |
| 10/14/16 | C7119A | 10.00 | $610.00 |
| 10/14/16 | C7119A | -10.00 | ($610.00) |
| 10/21/16 | C7119A | 19.50 | $1,189.50 |
| 10/21/16 | C7119A | -19.50 | ($1,189.50) |
| 10/28/16 | C7119A | 2.00 | $122.00 |
| 10/28/16 | C7119A | 3.00 | $183.00 |
| 10/28/16 | C7119A | -3.00 | ($183.00) |
| 10/28/16 | C7119A | -2.00 | ($122.00) |
| 11/4/16 | C7119A | 1.00 | $61.00 |
| 11/11/16 | C7119A | 3.50 | $213.50 |
| 1/13/17 | C7119A | 3.00 | $183.00 |
+---------------+---------+--------+-------------+
You can do this using SUMMARIZE().
First create a calculated column to get a distinct ID on the project/week combo:
ProjectWeek =CONCATENATE([Project],[Week End Date])
Then create a calculated measure to count the weeks with positive sum of hours:
Positive Project Weeks:= COUNTROWS(Filter(ADDCOLUMNS(
SUMMARIZE('Project Costs','Project Costs'[Week End Date]),
"WeekSum", MAXX(Values('Project Costs'[ProjectWeek]),
CALCULATE(Sum([Hours]),ALL('Project Costs'[Hours])))),
[WeekSum] >0))
SUMMARIZE creates a table that contains the distinct WeekEndDate values.
ADDCOLUMNS creates a column in that table that shows the sum of hours for that WeekEndDate.
Filter removes the rows in our virtual table that have a sum of hours less than or equal to 0.
Countrows then counts the rows left in the table, which is equal to the distinct count of end dates.
If you don't create the calculated column for ProjectWeek and instead use WeekEndDate in the MAXX(VALUES()) functions, you will get a total of 7 instead of 4.
I have a file that has data stored in it the following way (weekly data example)
+----------+----------+----------+----------+----------+----------+
| | WK1 | WK2 | WK3 | WK4 | WK5 |
+----------+----------+----------+----------+----------+----------+
| DT Begin | 29.12.14 | 05.01.15 | 12.01.15 | 19.01.15 | 26.01.15 |
| DT End | 04.01.15 | 11.01.15 | 18.01.15 | 25.01.15 | 01.02.15 |
| XData | 50 | 10 | 10 | 10 | 50 |
+----------+----------+----------+----------+----------+----------+
My problem ist to aggregate the XData on a monthly basis. For that I want to break the data down for days and then calculate the average.
Edit: I changed the table as it was not clear what I meant. This averages to ((50*4)+(10*21)+(5*50))/31 = 22.90
+------------+-------+
| Date | Value |
+------------+-------+
| 01.01.2015 | 50 |
| 02.01.2015 | 50 |
| 03.01.2015 | 50 |
| 04.01.2015 | 50 |
| 05.01.2015 | 10 |
| 06.01.2015 | 10 |
| 07.01.2015 | 10 |
| 08.01.2015 | 10 |
| 09.01.2015 | 10 |
| 10.01.2015 | 10 |
| 11.01.2015 | 10 |
| 12.01.2015 | 10 |
| 13.01.2015 | 10 |
| 14.01.2015 | 10 |
| 15.01.2015 | 10 |
| 16.01.2015 | 10 |
| 17.01.2015 | 10 |
| 18.01.2015 | 10 |
| 19.01.2015 | 10 |
| 20.01.2015 | 10 |
| 21.01.2015 | 10 |
| 22.01.2015 | 10 |
| 23.01.2015 | 10 |
| 24.01.2015 | 10 |
| 25.01.2015 | 10 |
| 26.01.2015 | 50 |
| 27.01.2015 | 50 |
| 28.01.2015 | 50 |
| 29.01.2015 | 50 |
| 30.01.2015 | 50 |
| 31.01.2015 | 50 |
+------------+-------+
| Average | 22.90 |
+------------+-------+
After having done this calculation I want to summarize the data as follows for the entire year:
+-------+-------+-------+------+------+
| | Jan | Feb | Mar | ... |
+-------+-------+-------+------+------+
| XData | 22.90 | 22.00 | 23.1 | ... |
+-------+-------+-------+------+------+
Being a newbie in Excel VBA, I have extreme trouble doing this.
I know how to get to the value of a cell (Range.Value) but not how to find data in a particular week (as WK1 is there for 2014 as well) Range.Find with a date other than the one in the cell itself does not seem to work.
Whar I am asking for is a way to approach this problem. My particular difficulties are to:
Find the data in the worksheet
split the week values into day values (see table above)
Copy the data or hold it in some sort of data structure
calculate the average (this should be ease then)
fill in the data on a monthly basis
As you can see, I have trouble even getting started - any hints would be greatly appreciated. Maybe I'm thinking of this entirely too complicated? Thank you!