I have code that unpivots columns into rows. There are 19 categories of data, 15 of which have been unpivoted. However, my problem is that some of the tables that are unpivoted are not showing up on the new rows. I am asking for anyone's expertise to help as this will be helpful for me in future endeavors. I have created a table. Bear in mind this time is extremely wide/long and has 131 columns I believe and only 7 rows. Below is the table of the original data (it is make believe data of course but will be used for real data in the future). Also, the 2nd table is the how I want it to look. The 3rd table is how I how it actually looks. Under that is my code. I will glady upvote anyone who will help me. Thank you in advance.
Original data:
| usr | Company | Dept.# | Dept1 | Dept2 | Dept3 | Dept4 | Hr1 | Tr1 | F1 | A1 | HOH1 | M1 | R1 | SO1 | BIG1 | T1 | P1 | X1 | Y1 | Z1 | Tin1 | Hr1 | Tr1 | F1 | A1 | HOH1 | M1 | R1 | SO1 | BIG1 | T1 | P1 | X1 | Y1 | Z1 | Tin1 | Hr1 | Tr1 | F1 | A1 | HOH1 | M1 | R1 | SO1 | BIG1 | T1 | P1 | X1 | Y1 | Z1 | Tin1 | Hr1 | Tr1 | F1 | A1 | HOH1 | M1 | R1 | SO1 | BIG1 | T1 | P1 | X1 | Y1 | Z1 | Tin1 | Hr2 | Tr2 | F2 | A2 | HOH2 | M2 | R2 | SO2 | BIG2 | T2 | P2 | X2 | Y2 | Z2 | Tin2 | Hr2 | Tr2 | F2 | A2 | HOH2 | M2 | R2 | SO2 | BIG2 | T2 | P2 | X2 | Y2 | Z2 | Tin2 | Hr2 | Tr2 | F2 | A2 | HOH2 | M2 | R2 | SO2 | BIG2 | T2 | P2 | X2 | Y2 | Z2 | Tin2 | Hr3 | Tr3 | F3 | A3 | HOH3 | M3 | R3 | SO3 | BIG3 | T3 | P3 | X2 | Y2 | Z2 | Tin2 | Hr3 | Tr3 | F3 | A3 | HOH3 | M3 | R3 | SO3 | BIG3 | T3 | P3 | X3 | Y3 | Z3 | Tin3 | Hr4 | Tr4 | F4 | A4 | HOH4 | M4 | R4 | SO4 | BIG4 | T4 | P4 | X4 | Y4 | Z4 | Tin4 |
|------|---------|--------|-------|-------|-------|-------|-----|-----|-----|-----|------|----|----|-----|------|----|-----|-----|-----|----|------|-----|-----|----|-----|------|----|-----|-----|------|----|-----|-----|-----|----|------|-----|-----|----|-----|------|----|----|-----|------|-----|----|----|----|-----|------|-----|-----|----|-----|------|----|----|-----|------|----|----|-----|-----|----|------|-----|-----|-----|-----|------|----|----|-----|------|----|----|-----|----|-----|------|-----|-----|----|-----|------|----|----|-----|------|----|----|----|----|-----|------|-----|-----|-----|-----|------|----|----|-----|------|----|----|----|-----|----|------|-----|-----|-----|-----|------|----|-----|-----|------|----|----|-----|-----|----|------|-----|-----|-----|-----|------|----|----|-----|------|----|----|-----|-----|-----|------|-----|-----|-----|-----|------|----|----|-----|------|----|-----|-----|-----|-----|------|
| xxxx | OS | 1 | Train | | | | 20 | 89 | 355 | 123 | 435 | 90 | 5 | 55 | 676 | 34 | 43 | 984 | 345 | 74 | 846 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| xxxx | OPC | 2 | Poxy1 | Poxy2 | | | | | | | | | | | | | | | | | | 45 | 546 | 68 | 345 | 903 | 70 | 345 | 23 | 54 | 32 | 234 | 23 | 567 | 69 | 64 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 38 | 67 | 235 | 789 | 7 | 40 | 99 | 98 | 87 | 89 | 34 | 312 | 42 | 756 | 23 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| xxxx | Oxy R | 4 | H1 | H2 | H3 | H4 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 22 | 36 | 13 | 678 | 64 | 40 | 34 | 239 | 76 | 87 | 34 | 999 | 965 | 34 | 93 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 89 | 54 | 761 | 765 | 9 | 20 | 22 | 65 | 78 | 98 | 78 | 75 | 354 | 23 | 23 | | | | | | | | | | | | | | | | 36 | 80 | 123 | 543 | 17 | 20 | 11 | 908 | 988 | 7 | 86 | 245 | 546 | 763 | 324 | 25 | 90 | 111 | 432 | 84 | 25 | 63 | 784 | 98 | 78 | 854 | 754 | 234 | 865 | 43 |
| xxxx | HPK | 3 | Test1 | Test2 | Test3 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 99 | 456 | 39 | 567 | 223 | 50 | 5 | 32 | 549 | 435 | 34 | 87 | 64 | 348 | 942 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 52 | 21 | 47 | 876 | 1 | 30 | 46 | 92 | 78 | 12 | 34 | 12 | 12 | 421 | 23 | | | | | | | | | | | | | | | | 90 | 76 | 773 | 654 | 49 | 10 | 223 | 982 | 566 | 23 | 54 | 786 | 356 | 73 | 654 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| xxxx | Mano | 1 | Porp | | | | 42 | 657 | 645 | 234 | 344 | 80 | 45 | 364 | 97 | 23 | 634 | 34 | 23 | 87 | 84 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| xxxx | Macro | 2 | Otto1 | Otto2 | | | | | | | | | | | | | | | | | | 75 | 574 | 46 | 456 | 453 | 60 | 44 | 235 | 867 | 5 | 433 | 234 | 346 | 46 | 35 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 23 | 433 | 186 | 987 | 2 | 30 | 34 | 58 | 87 | 43 | 34 | 23 | 62 | 73 | 32 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
How I want it to look:
| usr | Company | Dept# | Dept | Hrs | Tr | F | A | HOH | M | R | SO | BIG | T | P | X | Y | Z | Tin |
|------|---------|-------|-------|-----|-----|-----|-----|-----|----|-----|-----|-----|-----|-----|-----|-----|-----|-----|
| xxxx | OS | 1 | Train | 20 | 89 | 355 | 123 | 435 | 90 | 5 | 55 | 676 | 34 | 43 | 984 | 345 | 74 | 846 |
| xxxx | OPC | 2 | Poxy1 | 45 | 546 | 68 | 345 | 903 | 70 | 345 | 23 | 54 | 32 | 234 | 23 | 567 | 69 | 64 |
| xxxx | OPC | 2 | Poxy2 | 38 | 67 | 235 | 789 | 7 | 40 | 99 | 98 | 87 | 89 | 34 | 312 | 42 | 756 | 23 |
| xxxx | Oxy R | 4 | H1 | 22 | 36 | 13 | 678 | 64 | 40 | 34 | 239 | 76 | 87 | 34 | 999 | 965 | 34 | 93 |
| xxxx | Oxy R | 4 | H2 | 89 | 54 | 761 | 765 | 9 | 20 | 22 | 65 | 78 | 98 | 78 | 75 | 354 | 23 | 23 |
| xxxx | Oxy R | 4 | H3 | 36 | 80 | 123 | 543 | 17 | 20 | 11 | 908 | 988 | 7 | 86 | 245 | 546 | 763 | 324 |
| xxxx | Oxy R | 4 | H4 | 25 | 90 | 111 | 432 | 84 | 25 | 63 | 784 | 98 | 78 | 854 | 754 | 234 | 865 | 43 |
| xxxx | HPK | 3 | Test1 | 99 | 456 | 39 | 567 | 223 | 50 | 5 | 32 | 549 | 435 | 34 | 87 | 64 | 348 | 942 |
| xxxx | HPK | 3 | Test2 | 52 | 21 | 47 | 876 | 1 | 30 | 46 | 92 | 78 | 12 | 34 | 12 | 12 | 421 | 23 |
| xxxx | HPK | 3 | Test3 | 90 | 76 | 773 | 654 | 49 | 10 | 223 | 982 | 566 | 23 | 54 | 786 | 356 | 73 | 654 |
| xxxx | Mano | 1 | Porp | 42 | 657 | 645 | 234 | 344 | 80 | 45 | 364 | 97 | 23 | 634 | 34 | 23 | 87 | 84 |
| xxxx | Macro | 2 | Otto1 | 73 | 574 | 46 | 456 | 453 | 60 | 44 | 235 | 867 | 5 | 433 | 234 | 346 | 46 | 35 |
| xxxx | Macro | 2 | Otto2 | 23 | 433 | 186 | 987 | 2 | 30 | 34 | 58 | 87 | 43 | 34 | 23 | 62 | 73 | 32 |
This is how it actually looks which is wrong. As you can see data is missing for some reason:
| usr | Company | Dept# | Dept | Hrs | Tr | F | A | HOH | M | R | SO | BIG | T | P | X | Y | Z | Tin |
|------|---------|-------|-------|-----|-----|-----|-----|-----|----|-----|-----|-----|-----|-----|-----|-----|-----|-----|
| xxxx | OS | 1 | Train | 20 | 89 | 355 | 123 | 435 | 90 | 5 | 55 | 676 | 34 | 43 | 984 | 345 | 74 | 846 |
| xxxx | OPC | 2 | Poxy1 | 45 | 546 | 68 | 345 | 903 | 70 | 345 | 23 | 54 | 32 | 234 | 23 | 567 | 69 | 64 |
| xxxx | OPC | 2 | Poxy2 | 38 | 67 | 235 | 789 | 7 | 40 | 99 | 98 | 87 | 89 | 34 | 312 | 42 | 756 | 23 |
| xxxx | Oxy R | 4 | H1 | 22 | 36 | 13 | 678 | 64 | 40 | 34 | 239 | 76 | 87 | 34 | 999 | 965 | 34 | 93 |
| xxxx | Oxy R | 4 | H2 | 89 | 54 | 761 | 765 | 9 | 20 | 22 | 65 | 78 | 98 | 78 | 75 | 354 | 23 | 23 |
| xxxx | Oxy R | 4 | H3 | | | | | | | | | | | | | | | |
| xxxx | Oxy R | 4 | H4 | | | | | | | | | | | | | | | |
| xxxx | HPK | 3 | Test1 | 99 | 456 | 39 | 567 | 223 | 50 | 5 | 32 | 549 | 435 | 34 | 87 | 64 | 348 | 942 |
| xxxx | HPK | 3 | Test2 | 52 | 21 | 47 | 876 | 1 | 30 | 46 | 92 | 78 | 12 | 34 | 12 | 12 | 421 | 23 |
| xxxx | HPK | 3 | Test3 | | | | | | | | | | | | | | | |
| xxxx | Mano | 1 | Porp | 42 | 657 | 645 | 234 | 344 | 80 | 45 | 364 | 97 | 23 | 634 | 34 | 23 | 87 | 84 |
| xxxx | Macro | 2 | Otto1 | 73 | 574 | 46 | 456 | 453 | 60 | 44 | 235 | 867 | 5 | 433 | 234 | 346 | 46 | 35 |
| xxxx | Macro | 2 | Otto2 | 23 | 433 | 186 | 987 | 2 | 30 | 34 | 58 | 87 | 43 | 34 | 23 | 62 | 73 | 32 |
Here is my code:
Sub buttonclick()
Dim Ary As Variant, Nary As Variant, Cary As Variant
Dim r As Long, c As Long, nr As Long, cc As Long
Cary = Array("0853", 6898, 113128, 143143)
With Sheets("Sheet1")
Ary = .Range("A2:DM" & .Range("A" & Rows.Count).End(xlUp).Row).Value2
End With
ReDim Nary(1 To UBound(Ary) * 4, 1 To 19)
For r = 1 To UBound(Ary)
For c = 4 To 7
If Ary(r, c) = "" Then Exit For
nr = nr + 1
Nary(nr, 1) = Ary(r, 1): Nary(nr, 2) = Ary(r, 2): Nary(nr, 3) = Ary(r, 3)
Nary(nr, 4) = Ary(r, c)
For cc = Left(Cary(c - 4), 2) To Right(Cary(c - 4), 2) Step 15
Nary(nr, 5) = Nary(nr, 5) & Ary(r, cc)
Nary(nr, 6) = Nary(nr, 6) & Ary(r, cc + 1)
Nary(nr, 7) = Nary(nr, 7) & Ary(r, cc + 2)
Nary(nr, 8) = Nary(nr, 8) & Ary(r, cc + 3)
Nary(nr, 9) = Nary(nr, 9) & Ary(r, cc + 4)
Nary(nr, 10) = Nary(nr, 10) & Ary(r, cc + 5)
Nary(nr, 11) = Nary(nr, 11) & Ary(r, cc + 6)
Nary(nr, 12) = Nary(nr, 12) & Ary(r, cc + 7)
Nary(nr, 13) = Nary(nr, 13) & Ary(r, cc + 8)
Nary(nr, 14) = Nary(nr, 14) & Ary(r, cc + 9)
Nary(nr, 15) = Nary(nr, 15) & Ary(r, cc + 10)
Nary(nr, 16) = Nary(nr, 16) & Ary(r, cc + 11)
Nary(nr, 17) = Nary(nr, 17) & Ary(r, cc + 12)
Nary(nr, 18) = Nary(nr, 18) & Ary(r, cc + 13)
Nary(nr, 19) = Nary(nr, 19) & Ary(r, cc + 14)
Next cc
Next c
Next r
With Sheets("Sheet2")
.UsedRange.ClearContents
.Range("A1").Resize(, 19).Value = Array("usr", "Company", "Dept.#", "Dept", "Hrs",
"Tr", "F", "A", "HOH", "M", "R", "SO", "BIG", _
"T", "P", "X", "Y", "Z", "Tin")
.Range("A2").Resize(nr, 19).Value = Nary
End With
End Sub
Excel
| A | B | C | D | E | F | G | H |
---|-----------------|----------|--------|--------|-----------|-------------|---------|----------|---
1 | Loan | 50.000 | Year | Start | Interests | Repayment | Annuity | End |
2 | Interests p.a. | 2% | 1 | 50.000 | -1.250 | -1.750 | -3.000 | 48.250 |
3 | Annuity p.a. | 3.000 | 2 | 48.250 | -1.206 | -1.794 | -3.000 | 46.456 |
4 | Maturity | ?? | 3 | 46.456 | -1.161 | -1.839 | -3.000 | 44.618 |
5 | | | 4 | 44.618 | -1.115 | -1.885 | -3.000 | 42.733 |
| | | | | | | | |
| | | | | | | | |
21 | | | 20 | 8.094 | -202 | -2.798 | -3.000 | 5.297 |
22 | | | 21 | 5.297 | -132 | -2.868 | -3.000 | 2.429 |
23 | | | 22 | 2.429 | -61 | -2.939 | -3.000 | 0 |
The above loan of 50.000 has an interest rate of 2% and an annuity of 3.000.
In the table from C1:H23 the annual development of the remaining loan is displayed.
Based on this helper table I know that the maturity of the loan is 22 years by using the following formula in Cell B4:
B4 = COUNTA(C1:C22)
However, my question is if there is an Excel-Formula that can calculate the maturity in one cell so I do not need the helper table in C1:H23?
Excel-Table:
| A | B | C | D | E | F | G |
-----|----------------|-----------------|------------------|--------|---------|---------|---------|-----
1 | month&year | date | customer | | 2020-01 | 2020-03 | 2020-04 |
-----|----------------|-----------------|------------------|--------|---------|---------|---------|-----
2 | 2020-01 | 2020-01-10 | Customer A | | 3 | 2 | 4 |
3 | 2020-01 | 2020-01-14 | Customer A | | | | |
4 | 2020-01 | 2020-01-17 | Customer B | | | | |
5 | 2020-01 | 2020-01-19 | Customer B | | | | |
6 | 2020-01 | 2020-01-23 | Customer C | | | | |
7 | 2020-01 | 2020-01-23 | Customer B | | | | |
-----|----------------|-----------------|---------------- -|--------|---------|---------|---------|-----
8 | 2020-03 | 2020-03-18 | Customer E | | | | |
9 | 2020-03 | 2020-03-19 | Customer A | | | | |
-----|----------------|-----------------|------------------|--------|---------|---------|---------|-----
10 | 2020-04 | 2020-04-04 | Customer B | | | | |
11 | 2020-04 | 2020-04-07 | Customer C | | | | |
12 | 2020-04 | 2020-04-07 | Customer A | | | | |
13 | 2020-04 | 2020-04-07 | Customer E | | | | |
14 | 2020-04 | 2020-04-08 | Customer A | | | | |
15 | 2020-04 | 2020-04-12 | Customer A | | | | |
16 | 2020-04 | 2020-04-15 | Customer B | | | | |
17 | |
In my Excel file I want to calculate the unique count of cutomers per month as you can see in Cell E2:G2.
I already inserted Column A as a helper column which extracts only the month and the year from the date in Column B.
Therefore, the date-formatting is the same as in the timline in Cell E1:G2.
I guess the formula to get the unique count per month is somehow related to =COUNTIFS($A:$A,E$1) but I have no clue how to modify this formula to get the expected values.
Do you have any idea?
Here's one approach which would work for Office 365 and if you have access to UNIQUE:
=COUNTA(UNIQUE(IF($A$2:$A$16=G$1,$C$2:$C$16,""),,FALSE))-1
For older versions, following will work with CTRL+SHIFT+ENTER (array entry)
=SUM(--(FREQUENCY(IFERROR(MATCH($A$2:$A$16&$C$2:$C$16,E$1&$C$2:$C$16,0),"a"),MATCH($A$2:$A$16&$C$2:$C$16,E$1&$C$2:$C$16,0))>0))
You can do it without any helping column.
=SUM(--(UNIQUE(FILTER($C$2:$C$16,TEXT($B$2:$B$16,"yyyy-mm")=E$1))<>""))
For older version of excel use below formula with your helper column.
=SUMPRODUCT(--($A$2:$A$16=D$1)*(1/COUNTIFS($A$2:$A$16,$A$2:$A$16,$C$2:$C$16,$C$2:$C$16)))
I am new to this site and haven't done much in Excel of decades (yes, decades), so I forgotten more than I know now.
Background: I am working on a simple pay sheet checking spreadsheet. One Worksheet is input timesheet for data entry, the complex one does all the calculations (Hourly rate; shift loading; tax formula, etc.) and the final worksheet presents the results in the same format as pay slip. Having finished the complex formulas in the calculation sheet, I am now stuck on condensing the results for the final results on the last sheet. I have try numerous functions including: vlookup, index, match, rank.eq, small and others, as per examples of other question on this site. Sample data is:
+----+-----------------------------------------------------+----------------+------------+--------------+--------+--------+-----+--------+
| | A | B | C | D | E | F | G | H |
+----+-----------------------------------------------------+----------------+------------+--------------+--------+--------+-----+--------+
| 1 | Sample data: | | | | | | | |
| 2 | Monday | Ordinary Hours | 30/04/2018 | Day Shift | 10.85 | 21.85 | 1 | 237.07 |
| 3 | Tuesday | Ordinary Hours | 1/05/2018 | | | 21.85 | 1 | |
| 4 | Wednesday | Ordinary Hours | 2/05/2018 | | | 21.85 | 1 | |
| 5 | Thursday | Ordinary Hours | 3/05/2018 | | | 21.85 | 1 | |
| 6 | Friday | Ordinary Hours | 4/05/2018 | | | 21.85 | 1 | |
| 7 | | | | | | | | |
| 8 | | | | | | | | |
| 9 | Monday | Ordinary Hours | 7/05/2018 | | | 21.85 | 1 | |
| 10 | Tuesday | Ordinary Hours | 8/05/2018 | | | 21.85 | 1 | |
| 11 | Wednesday | Ordinary Hours | 9/05/2018 | Day Shift | 10.85 | 21.85 | 1 | 237.07 |
| 12 | Thursday | Ordinary Hours | 10/05/2018 | Day Shift | 10.85 | 21.85 | 1 | 237.07 |
| 13 | Friday | Ordinary Hours | 11/05/2018 | | | 21.85 | 1 | |
| 14 | | | | | | | | |
| 15 | Monday | Overtime 1.5 | 30/04/2018 | | | 21.85 | 1.5 | |
| 16 | Tuesday | Overtime 1.5 | 1/05/2018 | Overtime 1.5 | 2 | 21.85 | 1.5 | 65.55 |
| 17 | Wednesday | Overtime 1.5 | 2/05/2018 | | | 21.85 | 1.5 | |
| 18 | Thursday | Overtime 1.5 | 3/05/2018 | | | 21.85 | 1.5 | |
| 19 | Friday | Overtime 1.5 | 4/05/2018 | | | 21.85 | 1.5 | |
| 20 | Saturday | Overtime 1.5 | 5/05/2018 | | | 21.85 | 1.5 | |
| 21 | | | | | | | | |
| 22 | Monday | Overtime 1.5 | 7/05/2018 | | | 21.85 | 1.5 | |
| 23 | Tuesday | Overtime 1.5 | 8/05/2018 | | | 21.85 | 1.5 | |
| 24 | Wednesday | Overtime 1.5 | 9/05/2018 | | | 21.85 | 1.5 | |
| 25 | Thursday | Overtime 1.5 | 10/05/2018 | | | 21.85 | 1.5 | |
| 26 | Friday | Overtime 1.5 | 11/05/2018 | | | 21.85 | 1.5 | |
| 27 | Saturday | Overtime 1.5 | 12/05/2018 | | | 21.85 | 1.5 | |
| 28 | | | | | | | | |
| 29 | | | | | | | | |
| 30 | Required result on separate sheet in same workbook: | | | | | | | |
| 31 | Taxable Allowances | Comments | Qty | Rate | Factor | Amount | | |
| 32 | Ordinary Hours | 30/04/2018 | 10.85 | 21.85 | 1 | 237.07 | | |
| 33 | Ordinary Hours | 9/05/2018 | 10.85 | 21.85 | 1 | 237.07 | | |
| 34 | Ordinary Hours | 10/05/2018 | 10.85 | 21.85 | 1 | 237.07 | | |
| 35 | Overtime 1.5 | 1/05/2018 | 2 | 21.85 | 1.5 | 65.55 | | |
| 36 | | | | | | | | |
| 37 | | | | | | | | |
| 38 | | | | | | | | |
| 39 | | | | | | | | |
| 40 | | | | | | | | |
+----+-----------------------------------------------------+----------------+------------+--------------+--------+--------+-----+--------+
I haven't written DAX in a while and I'm having a bit of a hard time putting this together and I am hoping someone could throw in a suggestion.
What I have:
Qty Table (a lot more months than January):
+----------+-----------+----------+
| Location | Date | LaborQty |
+----------+-----------+----------+
| NY | 1/3/2017 | 41.024 |
| NY | 1/4/2017 | 33.836 |
| NY | 1/5/2017 | 20.431 |
| NY | 1/6/2017 | 35.544 |
| NY | 1/7/2017 | 0 |
| NY | 1/9/2017 | 33.337 |
| NY | 1/10/2017 | 41.799 |
| NY | 1/11/2017 | 70.469 |
| NY | 1/12/2017 | 35.514 |
| NY | 1/13/2017 | 31.573 |
| NY | 1/15/2017 | 0 |
| NY | 1/16/2017 | 22.041 |
| NY | 1/17/2017 | 30.518 |
| NY | 1/18/2017 | 47.576 |
| NY | 1/19/2017 | 29.53 |
| NY | 1/20/2017 | 18.155 |
| NY | 1/21/2017 | 0 |
| NY | 1/23/2017 | 31.284 |
| NY | 1/24/2017 | 27.695 |
| NY | 1/25/2017 | 38.907 |
| NY | 1/26/2017 | 16.289 |
| NY | 1/27/2017 | 30.976 |
| NY | 1/28/2017 | 0 |
| NY | 1/30/2017 | 21.434 |
| NY | 1/31/2017 | 16.49 |
+----------+-----------+----------+...etc
Rates Table:
+----------+-----------+------------+-----------+---------+-----------+--------+
| Location | DateFrom | DateTo | MonthFrom | MonthTo | RateType | Amount |
+----------+-----------+------------+-----------+---------+-----------+--------+
| NY | 1/1/2017 | 6/30/2017 | 1 | 6 | LaborRate | 129.7 |
| NY | 7/1/2017 | 9/30/2017 | 7 | 9 | LaborRate | 129.8 |
| NY | 10/1/2017 | 12/31/2017 | 10 | 12 | LaborRate | 129.9 |
| DC | 1/1/2017 | 6/30/2017 | 1 | 6 | LaborRate | 130.1 |
| DC | 7/1/2017 | 9/30/2017 | 7 | 9 | LaborRate | 130.5 |
| DC | 10/1/2017 | 12/31/2017 | 10 | 12 | LaborRate | 130.7 |
+----------+-----------+------------+-----------+---------+-----------+--------+
Desired type of output for the month (e.g. LaborQty x LaborRate):
+-------+----------+-----------+------------+
| Month | LaborQty | LaborRate | Result |
+-------+----------+-----------+------------+
| 1 | 674.22 | 129.74 | 87473.3 |
| 2 | 350 | 129.74 | 45409 |
| 3 | 375 | 129.74 | 48652.5 |
| 4 | 400 | 129.74 | 51896 |
| 5 | 380 | 129.74 | 49301.2 |
| 6 | 500 | 129.74 | 64870 |
| 7 | 550 | 129.76 | 71368 |
| 8 | 600 | 129.76 | 77856 |
| 9 | 675 | 129.76 | 87588 |
| 10 | 700 | 129.98 | 90986 |
| 11 | 780 | 129.98 | 101384.4 |
+-------+----------+-----------+------------+
What I am trying to write:
A DAX measure that will output amount like the one shown in the result column. If I where to write a linq query for picking the correct rate it will look something like this:
LaborRate = db.Rates
.Where(a => a.DateFrom <= SelectedDate & a.DateTo >= SelectedDate & a.RateType == "LaborRate")
.Select(a => a.Amount).Sum();
I have tried a combination of CALCULATE, SUM, SUMX, FILTER, RELATED but I couldn't get it to work. Any advice would be much appreciated. What would be the simplest approach?
I was able to achieve this by doing the following.
Add Month = MONTH(Qty[Date]) as a calculated column to your Qty table.
Create a TotalLaborQty measure in the Qty table as SUM(Qty[LaborQty]).
Define a LaborRate measure in the Rates table as detailed below.
Define a Result measure as [TotalLaborQty] * [LaborRate].
Set them up in a matrix with Qty[Location] and Qty[Month] in the rows and the three measures as the values.
LaborRate =
VAR SelectedMonth = SELECTEDVALUE(Qty[Month])
VAR SelectedLocation = SELECTEDVALUE(Qty[Location])
RETURN CALCULATE(SUM(Rates[Amount]),
FILTER(ALL(Rates),
Rates[MonthFrom] <= SelectedMonth &&
Rates[MonthTo] >= SelectedMonth &&
Rates[Location] = SelectedLocation))