Ive spent the last 2 days trying to get this, and I really just need a few pointers. Im using Excel 2010 w/ Power Pivot and calculating inventories. I am trying to get the amount sold between 2 dates. I recorded the quantity on hand if the item was in stock.
Item # Day Date Qty
Black Thursday 11/6/2014 2
Blue Thursday 11/6/2014 3
Green Thursday 11/6/2014 3
Black Friday 11/7/2014 2
Green Friday 11/7/2014 2
Black Monday 11/10/2014 3
Blue Monday 11/10/2014 4
Green Monday 11/10/2014 3
Is there a way to do this in dax? I may have to go back and calculate the differences for each record in excel, but Id like to avoid that if possible.
Somethings that have made this hard for me.
1) I only record the inventory Mon-Fri. I am not sure this will always be the case so i'd like to avoid a dependency on this being only weekdays.
2) When there is none in stock, I dont have a record for that day
Ive tried, CALCULATE with dateadd and it gave me results nearly right, but it ended up filtering out some of the results. Really was odd, but almost right.
Any Help is appreciated.
Bryan, this may not totally answer your question as there are a couple of things that aren't totally clear to me but it should give you a start and I'm happy to expand my answer if you provide further info.
One 'pattern' you can use involves the TOPN function which when used with the parameter n=1 can return the earliest or latest value from a table that it sorts by dates and can be filtered to be earlier/later than dates specified.
For this example I am using a 'disconnected' date table from which the user would select the two dates required in a slicer or report filter:
=
CALCULATE (
SUM ( inventory[Qty] ),
TOPN (
1,
FILTER ( inventory, inventory[Date] <= MAX ( dates[Date] ) ),
inventory[Date],
0
)
)
In this case the TOPN returns a single row table of the latest date earlier than or equal to the latest date provided. The 1st argument in the TOPN specifies the number of rows, the second the table to use, the 3rd the column to sort on and the 4th says to sort descending.
From here it is straightforward to adapt this for a second measure that finds the value for the latest date before or equal to the earliest date selected (i.e. swap MIN for MAX in MAX(dates[Date])).
Hope this helps.
Jacob
*prettified using daxformatter.com
Related
I need your help in creating a DAX measure that would help me resolving the following problem:
I have a table that shows case number, creation date and closure date:
case_number creation_date closure_date
CA001 4/15/2020 4/19/2020
CA002 4/17/2020 4/20/2020
CA003 4/19/2020 4/21/2020
CA004 4/19/2020 4/20/2020
I have a pivot with various measures where row headers are consecutive days from a related Calendar table. One of the columns I need is a number of active cases in given day (number of cases that were created before or the same day as the context date, AND closed after the context date). The expected outcome would be like this:
date open_cases
4/13/2020 0
4/14/2020 0
4/15/2020 1
4/16/2020 1
4/17/2020 2
4/18/2020 2
4/19/2020 3
4/20/2020 1
4/21/2020 0
in regular Excel, the formula that calculates the same would be =COUNTIFS(table_cases[creation_date],"<="&[#date],table_cases[closure_date],">"&[#date]), but in my case this will be a part of a bigger pivot table/dashboard and I need to write a measure in DAX that would calculate this.
I would appreciate your help in this matter.
Best regards,
Michal
There are a variety of ways to read the current context. You can use MAX or VALUES or SELECTEDVALUE (if available). These don't all behave exactly the same, so use whichever is appropriate for your situation.
open_cases =
VAR RowDate = MAX ( Calendar[date] )
RETURN
CALCULATE (
COUNT ( table_cases[case_number] ),
table_cases[creation_date] <= RowDate,
table_cases[closure_date] > RowDate
)
Here, MAX is evaluated within the filter context, so it should return the value in the current row (or the maximal date for subtotals and grand totals).
I have looked into the Forcast & Trend formula but I cannot figure it out for the life of me.
I want to work out the trend 14 days from now.
I have a set of data:
A1 - A30 with dates
B1 - B30 with daily ticket count for the business.
I would like to make a result in another cell that would predict what the estimated total ticket count would be 14 days from now. I do not need all 14 days, just the 14th day.
If I was to try show you what the formula looks like in my head it would be:
=trend/forecast(B1:B30,14)
or
=Predict(B1:B30)*14
Unfortunately it is not as easy as that. How can I do this?
I think you want to use the Forecast function. The inputs you have do not match the correct format though.
FORECAST( x, known y's, known x's) where...
x = the series (or date) you want to forecast
known y's = historical tickets per day
known x's = historical dates (or series)
The below example allows you to forecast tickets for any date (Forecasted Date) given the historical information (table on left). If your table is not formatted with actual dates, just create a series (first day = 1, second day = 2, etc.) and forecast that way.
Given the historical data, the forecasted tickets for Aug 28th (14 days after last known value) are 16.7
I have a table within PowerPivot currently that tracks a count of customers through our sales pipeline. From (by sales location) first interaction to charged sale. So far, I’ve creates a moving 5-day average that averages each task. Below is the DAX formula I’ve created thus far and an example table.
=
CALCULATE (
SUM ( [Daily Count] ),
DATESINPERIOD ( Table1[Date], LASTDATE ( Table1[Date] ), -7, DAY ),
ALLEXCEPT ( Table1, Table1[Sales Location], Table1[Group] )
)
/ 5
Where I’m struggling is being able to come up with a way to exclude weekends and company observed holidays. Additionally, if a holiday falls on a weekday I would like to remove that from the average and go back an additional day (to smooth the trend).
For example, on 11/26/18 (the Monday after Thanksgiving and Black Friday) I would like to average the five business days previous (11/26/18, 11/21-11/19, and 11/16). In the example above, the moving total and average for the previous 5 days should be Intake = 41 (total) 8.2 (average), Appointment = 30 (total) 6 (average), and Sale = 13 (total) and 2.6 (average).
Based on the formula currently, each of these numbers is inaccurate. Is there an easy way to exclude these days?
Side note: I’ve created an ancillary table with all holidays that is related to the sales data that I have.
Thank you for the help!
For this, I'd recommend using a calendar table related to Table1 on the Date column that also has a column IsWorkday with 1 if that day is a workday and 0 otherwise.
Once you have that set up, you can write a measure like this:
Moving Avg =
VAR Last5Workdays =
SELECTCOLUMNS (
TOPN (
5,
FILTER (
DateTable,
DateTable[Date] <= EARLIER ( Table1[Date] )
&& DateTable[IsWorkday] = 1
),
DateTable[Date], DESC
),
"Workday", DateTable[Date]
)
RETURN
CALCULATE (
SUM ( Table1[Daily Count] ),
Table1[Date] IN Last5Workdays
ALLEXCEPT ( Table1, Table1[Sales Location], Table1[Group] ),
)
/ 5
The TOPN function here returns the top 5 rows of the DateTable where each row must be a workday that is less than or equal to the date in your current Table1 row (the EARLIER function refers to the earlier row context that defines the current row).
I then use SELECTCOLUMNS to turn this table into a list by selecting a single column (which I've named Workday). From there, it's basically your measure with the date filter changed a bit.
#alexisolson Thank you for the response here. I was actually able to figure this out over the weekend but forgot to close out the thread (sorry about that! Appreciate your help either way). But I did something fairly similar to what you mentioned above.
I created a date table (CorpCalendar) that was only inclusive of working days. Then I created an index column within the CorpCalendar table to give each row a unique number in ascending order. From there, I linked the CorpCalendar table to my SalesData table by related dates and used the LOOKUPVALUE function to bring the index value over from the CorpCalendar table to the SalesData table. In a separate column I subtracted 4 from the date index value to get an index adjustment column (for a range of five days from the actual date index and the adjustment...if that makes sense). I then added an additional LOOKUPVALUE helper column to match the adjusted date index column to the appropriate working day.Lastly, I then used the following function to get the 5 day rolling average.
=CALCULATE(sum(Combined[Daily Count]),DATESBETWEEN(Combined[Date - Adjusted],Combined[Date - Adjusted (-5)],Combined[Date - Adjusted]),ALLEXCEPT(Combined,Combined[Group]))/5
This is probably more convoluted than necessary, however, it got me to the answer I was looking for. Let me know if this makes sense and if you have any suggestions for future scenarios like this.
Thanks again!
I am looking to calculate the sales for the SAMEPERIODLASTYEAR. I have a table which looks at the sales for the last few years and using the SAMEPERIODLASTYEAR function I can draw back to last January as a whole, but what I am wanting is to pull it to the date exactly and not to the end of the current month last year.
My formula below is pulling through for example all of January last year.
Sales Last Year:=CALCULATE([Sum of Sales],SAMEPERIODLASTYEAR(Dates[Date]))
Is there a way of doing this using just the SAMEPERIODLASTYEAR function rather than indivudual daily calculations?
I do not claim that this is the best (or only) way to do this, but how about:
Sales Last Year =
CALCULATE (
[Sum of Sales],
FILTER (
SAMEPERIODLASTYEAR ( 'Dates'[Date] ),
'Dates'[Date]
< DATE ( YEAR ( TODAY () ) - 1, MONTH ( TODAY () ), DAY ( TODAY () ) )
)
)
Essentially, I've added a FILTER() statement around the SAMEPERIODLASTYEAR clause, and filtered the results to be before the current date last year. If today is 8-Jan-2018, this means any sales on or after 8-Jan-2017 will be filtered out.
In essence, I'm taking the current date (TODAY()), breaking it down into its component parts, subtracting 1 from the year, then building it back up into a date value using the DAX DATE() function.
The reason I do this rather than using DATEADD() to subtract a year Excel-style is because DATEADD requires a table of dates as an input and TODAY() is a single date. You therefore cannot put TODAY() into DATEADD() directly.
Instead of using TODAY(), I could have a measure that identifies the most recent date for which there is data and call that instead. It's the same solution.
I'd be curious if others have a better way to do this. This strikes me as a common problem people must run into a lot.
I’m trying to compare a measure as of today through the same day and month for the prior 4 years (e.g. through June 6 of 2016, 2015, 2014, etc.).
For each year, I decided to count the number of days since the beginning of the year, and sum my values through that number of days for each year.
To identify whether a date should be included in the year to date comparison, I used the formula where my date is in cell A1:
=IF((A1-DATE(YEAR(A1),1,1)+1)<=(TODAY()-DATE(YEAR(TODAY()),1,1)+1),1,0)
I’m looking for a way around the issue of the extra day added to leap years. In other words, after February 28th, the day count will always be off by one in a leap year, and trying to use Februrary 29th in a non-leap year will return an error.
I’d like to adjust this formula, but I’m open to using a different function & formula if it gets me the right results.
you can check any information about February, 29th. If an error occurs, you know its no leap year. Catch that error with =IFERROR(;).
Assuming a table structure like this:
A:Date | B:Value
----------------------
01/01/2016 | 0
01/01/2015 | 1
01/01/2014 | 2
01/01/2013 | 3
01/01/2012 | 4
Formula
To - for example - calculate the average of the previous four (excluding the current) years on January 1st (today is 01/01/2016):
=SUMPRODUCT(
(MONTH(A:A)=MONTH(compare))*
(DAY(A:A)=DAY(compare))*
(YEAR(A:A)>YEAR(compare)-5)*
(YEAR(A:A)<YEAR(compare))*
(B:B)
) / (
SUMPRODUCT(
(MONTH(A:A)=MONTH(compare))*
(DAY(A:A)=DAY(compare))*
(YEAR(A:A)>YEAR(compare)-5)*
(YEAR(A:A)<YEAR(compare))*
1
)
)
Result
For the above example, the result is 2.5
Explanation
To select only those rows representing the same month and day:
(MONTH(A:A)=MONTH(compare))*(DAY(A:A)=DAY(compare))
To select only those values from the previous 4 years (excluding the current):
(YEAR(A:A)>YEAR(compare)-5)*(YEAR(A:A)<YEAR(compare))*
The actual values we are interested in:
(B:B)
Divide by 4 for the average over the last four years. This assumes there is no missing data which might be an issue. You could use another SUMPRODUCT (replace B:B with 1) to count the number of resulting rows and divide by that number to handles this case. This seems to be rather slow, but it works.
Note
For performance reason you should not use A:A (a full column) in the formula, just use the actual range you need, which will likely be much faster.