I am new to spotfire so please bear with me. I have a simple problem i hope. I have a display that has well production vs time. All I need is count the number of active wells as a function of time. The number of wells in month 1 = 95 but as we approach month 60 only 3 wells are active.
The well name = API14
The columns that a plotted are Oil and Months , Line by API14
I have tried
UniqueCount([API14]) OVER (Intersect(All([Axis.Line]))) AS [Cumulative Count]
This one gave the total unique API14 over time (95 in this example - light blue line) and not the declining well count as a function of time. Any help?
Try:
UniqueCount([API14]) OVER (Intersect([MONTHS],All([Axis.Line])))
Related
hope you are doing well and can help solve this puzzle in DAX for PowerBI and PowerPivot.
I'm having troubles with my measure in the subtotals and grand totals. My scene is the following:
I have 3 tables (I share a link below with a test file so you can see it and work there :robothappy:):
1) "Data" (where every register is a sold ticket from a bus company);
2) "Km" (where I have every possible track that the bus can do with their respective kilometer). Related to "Data";
3) and a "Calendar". Related to "Data".
In "Data" I have all the tickets sold from a period with their price, the track that the passenger bought and the departure time of that track.
Each track can have more than 1 departure time (we can call it a service) but only have a specific lenght in kilometers (their kilometers are specified in the "Km" table).
Basically what I need is to calculate the revenue per kilometer for each service in a period (year, month, day).
The calculation should be, basically:
Sum of [Price] (each ticket sold in the period) / Sum of [Km] (of the period considerating the services with their respective kilometers)
I managed to calculate it for the day granularity with the following logic and measures:
Revenue = SUM(Data[Price])
Unique dates = DISTINCTCOUNT(Data[Date])
Revenue/Km = DIVIDE([Revenue]; SUM(Km[Km])*[Unique dates]; 0)
I created [Unique dates] to calculate it because I tried to managed the subtotals of track granularity taking into account that you can have more than 1 day with services within the period. For example:
For "Track 1" we have registered:
1 service on monday (lunes) at 5:00am.
Revenue = $1.140.
Km = 115.
Tickets = 6.
Revenue/Km = 1.140/115 = 9,91.
1 service on tuesday (martes) at 5:00am.
Revenue = $67.
Km = 115.
Tickets = 2.
Revenue/Km = 67/115 = 0,58.
"Subtotal Track 1" should be:
Revenue = 1.140 + 67 = 1.207.
Km = 115 + 115 = 230.
Tickets = 6 + 2 = 8.
Revenue/Km = 1.207/230 = 5,25.
So at that instance someone can think my formula worked, but the problem you can see it when I have more than 1 service per day, for example for Track 3. And also this impact in the grand total of march (marzo).
I understand that the problem is to calculate the correct kilometers for each track in each period. If you check the column "Sum[Km]" is also wrong.
Here is a table (excel file to download - tab "Goal") with the values that should appear:
[goal] https://drive.google.com/file/d/1PMrc-IUnTz0354Ko6q3ZvkxEcnns1RFM/view?usp=sharing
[pbix sample file] https://drive.google.com/file/d/14NBM9a_Frib55fvL-2ybVMhxGXN5Vkf-/view?usp=sharing
Hope you can understand my problem. If you need more details please let me know.
Thank you very much in advance!!!
Andy.-
Delete "Sum of Km" - you should always write DAX measures instead.
Create a new measure for the km traveled:
Total Km =
SUMX (
SUMMARIZE (
Data,
Data[Track],
Data[Date],
Data[Time],
"Total_km", DISTINCT ( Data[Kilometers Column] )
),
[Total_km]
)
Then, change [Revenue/Km] measure:
Revenue/Km = DIVIDE([Revenue], [Total Km])
Result:
The measure correctly calculates km on both subtotal and total levels.
The way it works:
First, we use SUMMARIZE to group records by trips (where trip is a unique combination of track, date and time). Then, we add a column to the summary that contains km for each trip. Finally, we use SUMX to iterate the summary record by record, and sum up trip distances.
The solution should work, although I would recommend to give more thoughts to the data model design. You need to build a better star schema, or DAX will continue to be challenging. For example, I'd consider adding something like "Trip Id" to each record - it will be much easier to iterate over such ids instead of grouping records all the time. Also, more descriptive names can help make DAX clean (names like km[km] look a bit strange :)
I'm trying to calculate the remaining balance of a home loan at any point in time for multiple home loans.
Its looks like it is not possible to find the home loan balance w/ out creating one of those long tables (example). Finding the future balance for multiple home loans would require setting up a table for ea. home (in this case, 25).
With a table, when you want to look at the balance after a certain amount of payments have been made for the home loan, you would just visually scan the table for that period...
But is there any single formula which shows the remaining loan balance by just changing the "time" variable? (# of years/mths in the future)...
An example of the information I'm trying to find is "what would be the remaining balance on a home loan with the following criteria after 10 years":
original loan amt: $100K
term: 30-yr
rate: 5%
mthly pmts: $536.82
pmts per yr: 12
I'd hate to have to create 25 different amortization schedules - a lot of copy-paste-dragging...
Thanks in advance!
You're looking for =FV(), or "future value).
The function needs 5 inputs, as follows:
=FV(rate, nper, pmt, pv, type)
Where:
rate = interest rate for the period of interest. In this case, you are making payments and compounding interest monthly, so your interest rate would be 0.05/12 = 0.00417
nper = the number of periods elapsed. This is your 'time' variable, in this case, number of months elapsed.
pmt = the payment in each period. in your case $536.82.
pv = the 'present value', in this case the principle of the loan at the start, or -100,000. Note that for a debt example, you can use a negative value here.
type = Whether payments are made at the beginning (1) or end (0) of the period.
In your example, to calculate the principle after 10 years, you could use:
=FV(0.05/12,10*12,536.82,-100000,0)
Which produces:
=81,342.32
For a loan this size, you would have $81,342.32 left to pay off after 10 years.
I don't like to post answer when there already exist a brilliant answer, but I want to give some views. Understanding why the formula works and why you should use FV as P.J correctly states!
They use PV in the example and you can always double-check Present Value (PV) vs Future Value (FV), why?
Because they are linked to each other.
FV is the compounded value of PV.
PV is the discounted value at interest rate of FV.
Which can be illustrated in this graph, source link:
In the example below, where I replicated the way the example calculate PV (Column E the example from excel-easy, Loan Amortization Schedule) and in Column F we use Excel's build in function PV. You want to know the other way... therefore FV Column J.
Since they are linked they need to give the same Cash Flows over time (bit more tricky if the period/interest rate is not constant over time)!!
And they indeed do:
Payment number is the number of periods you want to look at (10 year * 12 payments per year = 120, yellow cells).
PV function is composed by:
rate: discount rate per period
nper: total amount of periods left. (total periods - current period), (12*30-120)
pmt: the fixed amount paid every month
FV: is the value of the loan in the future at end after 360 periods (after 30 year * 12 payments per year). A future value of a loan at the end is always 0.
Type: when payments occur in the year, usually calculated at the end.
PV: 0.05/12, (12*30)-120, 536.82 ,0 , 0 = 81 342.06
=
FV: 0.05/12, 120, 536.82 , 100 000.00 , 0 = -81 342.06
Sorry for the ambiguous title, I have a query which is stumping me in Excel:
I have a range of temperature data, recordings from every minute of every day for 3 months.
I want to find out how many times the average temperature from 20:30-21:30 on each day is lower than the average temperature from 01:00-02:00 the following morning (about 5 hours difference).
If that is difficult to understand here is a "logic formula":
count(averageTemp(dateX(timeA-timeA+1))<(averageTemp(dateY(timeB-timeB+1)))
Here's a sample of the data as a screenshot:
Please help me out, this one has me scratching my head.
Enter this as an array formula (ctrl+shift+enter) and change "122401" to the last row number of your data range:
=SUM(IFERROR(--(AVERAGEIFS(C2:C122401,B2:B122401,"<="&TIMEVALUE("21:30"),B2:B122401,">="&TIMEVALUE("20:30"),A2:A122401,ROW(INDIRECT(A2&":"&A122401)))<AVERAGEIFS(C2:C122401,B2:B122401,"<="&TIMEVALUE("02:00"),B2:B122401,">="&TIMEVALUE("01:00"),A2:A122401,ROW(INDIRECT(A2+1&":"&A122401)))),0))
This assumes that the first set of temperatures from 01:00-02:00 does not have a matching set from 20:30-21:30.
I would input a flag in column D that takes value 1/0 whether the time is in the frame you are interested in.
So input in D2 = IF(OR(AND(B2<21:30,B2>20:30),AND(B2<01:00,B2>02:00))),1,0).
Then I would go in column C and check if in D I got 1, input a simple IF statement to check for the temperature.
Let me know if it works!
So I am working on a spreadsheet for a Butchery I manage and have run into a problem.
First off back story: We do $20 packs for certain bulk products that have a min/max weight range.
The Goal is to be able to put in this spreadsheet the desired minimum GP% and from that get a maximum weight based off that minimum profit margin.
For example a Beef Steak that Costs $17.50 p/kilo Would be minimum of 680g (at a GP% of 30.30%) and a maximum weight of 790g (at a GP% of 20.50%)
I have been 'googling' all day, and banging my head on my desk (as well as experimenting with different formula's) I am starting to think I may have to resort to programming a macro to perform this but I would prefer to be able to achieve in a formula on the cell that way I can copy-paste easily down the spreadsheet.
If anyone has a solution or can put me on the right track would be Awesome.
I think the formula you are looking for is :
your selling price (=20$) / your mark up on cost
where your mark up is :
your cost per kilo / (1- your margin)
So for 20% expected GP it gives :
= 20 / (17.5 / (1-0.2))
= 20 / 21.875
= 0.914... kilos
Balance is then :
Revenue = 20$
Cost = 0.914 * 17.5 = 16
Margin = 4
Margin % = 20
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