Hopefully the title makes some sense because I'm trying to wrap my head around the logic and I'm not quite sure how to phrase the question.I'll try to give a brief explanation of the end goal without over complicating it with unnecessary details.
I have a table of survey score averages for every month per person and a correlating table with the number of surveys each person received for each month. The logic is essentially multiple the score for each month by the number of surveys, combine them, divide by the total number of surveys within that time period to get their true average. Where things get a little complicated is that I have to include the ability to set a custom date range and return the value. So sometimes I might be looking at the average for Jan - Apr, other times I might just be looking at Feb-Mar etc.
I think sumproduct is going to get what I need done but I'm running into issues trying to write it out. I've written it several different ways and none of them worked so here's one that best conveys what I'm trying to do,
=SUMPRODUCT(--(F7:I7,L7:O7>=C2),--(F7:I7,L7:O7<=C3),--(E8:E12,K8:K12=B9),tbl_average[[Jan-20]:[Apr-20]],tbl_surveys[[Jan-20]:[Apr-20]])
I super appreciate any assistance I can get on this. I'm hoping the end result is not nearly as difficult as I'm making it out to be.
Some additional information:
I'm going to be using this same process to calculate multiple metrics across multiple worksheets.In the test example each of the tables will most likely be on different sheets. The dashboard with the calculated results will contain everyone's names and will be filtered and rearranged frequently, so I need to make sure we're always matching directly to their names and not just the relative rows. Basically, in my example I show that Agent 1 is always lined up on row 8 but that's not always going to be the case. Agent 1 could be in Row 8 on Sheet 1, Row 10 on Sheet 2, and Row 12 on Sheet 3 and I need all the correct values to multiply and sum against one another.
Related
I have a sheet which I point failures, it is divided by failures (rows) and days (columns), I point the quantity of failures by the type of failure that day. So I used the vlookup to show me the top 3 failures of each day, but there is a problem, when it has the same quantity of different failures, it shows the same failure, not the next one with the same quantity.
I've tried ways to correct this, but everything I found didn't work, because it has variable quantity depending the day, and what I found use the COUNTIF trick, I can't define a value, so it doesn't work.
can anyone help me please?
There's probably an easier way, but this formula should work:
=LET(day,Table1[Sunday],myarray,FILTER(CHOOSE({1,2},Table1[Failure],day),RANK.EQ(day,day)<=3),SORTBY(myarray,INDEX(myarray,,2),-1))
As you can see it returns an dynamic array containing the top 3 Failures in descending order, along with the number of failures.
This should account for any ties as you can see in my example. However, it is possible for the returned array to be more than 3 rows if there is a tie for third place. Not sure if that's desirable or not.
(I use the term "teams" generically here because the entirety of this question rests on ranking, and it seemed to be the most intuitive language to describe my problem.)
In a league of 30 teams, each day only 8 teams play. The results for those teams are ranked ordinally from 1 to 8 for the day. This continues "forever", so that additional results must be recorded every day.
Example after 4 days:
I want to calculate a single number to describe the relationship between two teams. For instance, given the example, the value (in a 2d table) that describes the relationship of Ace to Get is 1. Ace beat Get twice and Get beat Ace once (2-1).
I have been messing with Sumproduct, Match, and Index to get get values, which I could calculate using many extra tables, but I may need to add "teams" on the fly, and I do not know how large the pool of teams will become. Because of this, I was hoping to be able to use a single formula in the 2d relationship table. The results of that table, looking at just day 1 and day 2 given the previous example, are:
Is there a direct formula I can use to calculate the results to populate that table?
You can try following formula:
=IF($A11<>B$10;
SUMPRODUCT(
IF(MMULT(($B$1:$I$1)*($B$2:$I$3=$A11);ROW($1:$8)^0)
<MMULT(($B$1:$I$1)*($B$2:$I$3=B$10);ROW($1:$8)^0);
1;
-1)
*(((MMULT(--($B$2:$I$3<>$A11);ROW($1:$8)^0)=8)
+(MMULT(--($B$2:$I$3<>B$10);ROW($1:$8)^0)=8))
=0));
"")
Copy right and down.
So I'm trying to create an Excel sheet to split the values of 70 items into six groups.
For reference, this is to divide my grandma's estate evenly for her six children. I have approx. 70 items and their appraised values in an Excel sheet, but not sure the best way to go about this. I was hoping to use Solver, but haven't been able to figure it out.
Ideally I could make it so people could pick specific items that they want and run the Excel sheet again to re-balance all the values.
Thanks!
So set this up, based on a thrown together set of values.
Each sumproduct is held to be <= to the (total value / 6)-10. You may want to reduce this to 5 or 2 etc but the smaller you go the harder it is to solve due to the values of the items.
I have done this for 30 items, there is a limit to the number of variables in the Solver - if you hit that then you might consider pairing items, or manually setting some will help, see below.
You might want to add something for sentimental value - I will leave you to consider that.
As for manually setting some items then you can set those items to one, move them to the top or bottom and remove them from the Solver variable cells - that way they won't get changed, but they still need to be included for the value. If the values are similar then they can be taken out if the differences are ignored by the parties.
So, edited the model, see below. Note that 1 item is not allocated. This could be addressed by changing the constraint controlling cells J9:J38 but it comes down to the difficulty of finding an exact solution and that is also why the 10 can be adjusted...
I have an Index Match Match question that I have not been able to find the answer for in researching. Although the solution may actually might be different than an Index Match Match formula - I'm open to try something more efficient than my current workaround.
I have one worksheet with data from my company on it. We sell a Product (let's call it Coke Zero) and we track the weeks that we put a promotion on and how much profit we make by selling it to the retailer. For example a promotion for Coke Zero starts the first week of Jan and ends 3 weeks later and we make a gross profit of $100 each week the promotion runs. I then have an external database with sales data formatted on a weekly basis to tell me how many units of Coke Zero I sold in each week. My internal data has thousands of lines like this with dozens of products, however the promotions are consolidated on one single row regardless of if it runs for more than one week, making matching up to the external database difficult. I need to create a lookup for what our Gross Profit was for each week of the promotion.
I have attached an example image of the workbook + two data sheets of what I've tried to do, summarised below.
On the Internal Data Sheet I've created additional columns to the right with all of the weeks listed that the promotion is on for, and concatenated them with the Product Code to be able to match week by week to the data in the External data sheet. Then my lookup basically checks every column one after another until it finds one where the concatenate of Week_Product Code concatenate matches.
My current solution technically works but my final formula is really slow and cumbersome given the data can be anywhere from 10K-200K lines when looking at multiple retailers. I was hoping to find a more efficient formula to complete the lookup.
Current solution on the External Data Sheet Column E:
=IF(ISNUMBER(MATCH(D2,'Internal Data'!$E:$E,0)),INDEX('Internal Data'!$D:$D,MATCH(D2,'Internal Data'!$E:$E,0)),
IF(ISNUMBER(MATCH(D2,'Internal Data'!$F:$F,0)),INDEX('Internal Data'!$D:$D,MATCH(D2,'Internal Data'!$F:$F,0)),
IF(ISNUMBER(MATCH(D2,'Internal Data'!$G:$G,0)),INDEX('Internal Data'!$D:$D,MATCH(D2,'Internal Data'!$G:$G,0)),
"0")))
I got SUMPRODUCT to work using this formula in J2:
=SUMPRODUCT(--($B$2:$D$3=H2)*--($E$2:$E$3=I2)*$F$2:$F$3)
And, you don't need those concatenated lookup columns:
Well, that was fun.
According to a couple of web sites, SUMIFS and COUNTIFS are faster than SUMPRODUCT (for example: http://exceluser.com/blog/483/excels-sumifs-or-sumproduct-which-is-faster.html). I have a worksheet with an unknown number of rows (around 200 000) and I'm calculating performance reports with the numbers. I have over 6000 times almost identical SUMPRODUCT formulas with a couple of difference each times (only the conditions change).
Here is an example of what I got:
=IF(AFO4>0,
(SUMPRODUCT((Sheet1!$N:$N=$A4)
*(LEFT(Sheet1!$H:$H,2)="1A")
*(Sheet1!$M:$M<>"service catalog")
*(Sheet1!$J:$J="incident")
*(Sheet1!$I:$I<>"self-serve")
*(Sheet1!$AK:$AK=AFM$1)
*(Sheet1!$E:$E>=$E$1)
*(Sheet1!$E:$E<$E$2))
+SUMPRODUCT((Sheet1!$AJ:$AJ=$C4)
*(LEFT(Sheet1!$H:$H,2)="1A")
*(Sheet1!$M:$M<>"service catalog")
*(Sheet1!$J:$J="incident")
*(Sheet1!$I:$I="self-serve")
*(Sheet1!$AK:$AK=AFM$1)
*(Sheet1!$E:$E>=$E$1)
*(Sheet1!$E:$E<$E$2)))/AFO4,0)
Calculating that thing takes a little bit more than 1 second. Since I have more than 6000 of those formulas, it takes a little bit over an hour to calculate everything.
So, I'm now looking at how I could optimize that formula. Could I convert it to SUMIFS? Would it be faster? All I'm adding up here is 0s and 1s, I'm just counting the number of rows in my data source (Sheet1) where the set of conditions is met. Maybe COUNTIFS would work better?
I would appreciate any help to gain some execution time since we need to execute the formulas every month.
I can use VBA if that helps, but I always heard that Excel formulas were usually faster.
Instead of formulas, Why not use a PivotTable to crunch the numbers? You potentially face a longer one-time hit to load the data into the PivotCache, but after that, you should find a PivotTable recalculates much faster in response to filter changes than these computationally expensive formulas. Is there any reason you're not using one?
Here's some content from a book I'm writing, where I compare SUMPRODUCT, SUMIFS, DSUM, PivotTables, the Advanced Filter, and something called Range Slicing (which uses clever combinations of INDEX/MATCH on sorted data) to conditionally sum the records in a table that contains over 1 million sales records, based on choices you make from 10 different dropdowns:
Those dropdowns allow you to filter the database by a combination of the Store, Segment, Species, Gender, Payment, Cust. History, Order Status, Delivery Instructions, Membership Type, and Order Channel columns. So there’s some pretty mammoth filtering and aggregation going on in order to reduce those 1 million records down to just one sum. The file outlines six different ways to achieve this outcome, the first three of which are shown in the screenshot below:
As you’d expect, when all those dropdowns are set to the same settings, you get exactly the same answer out of all six approaches. But what you won’t expect is just how slow SUMPRODUCT is to calculate a new answer if you change one of those dropdowns, compared to the other approaches.
In fact, it turns out that the SUMIFS approach is 15 times faster than the SUMPRODUCT one at coming up with the answer on this mammoth dataset. But that’s nothing: The range slicing approach is 56 times faster!
The Range Slicing approach works by sorting your source data, and then using a series of clever formulas in helper columns to cleverly identifying exactly where any records of interest sit within that sorted data. This means that you can then directly sum just the few records that match rather than having to do a complex criteria match against hundreds of thousands of rows (or against a million rows, as in the example here).
Here’s how that looks in terms of my sample file. The number in the Rows helper column on the right-hand side shows that through some clever elimination, the SUM function at the bottom has to process only 18 rows of data (rows 292996 through 293014) rather than all 1 million rows. In other words, this is mighty efficient.
And here’s the second group of alternatives:
Yup, you can quite easily use a PivotTable here. And the PivotTable approach seems to be around 6 times faster than SUMPRODUCT—although you get a small amount of extra delay when calling up the filters, and the first time you perform a filter operation it takes quite a bit longer again, as Excel must load the PivotCache into memory. But let’s face it: Setting up the PivotTable in the first place is the easiest of any of these approaches, so it has my vote.
The DSUM approach is 12 times faster than SUMPRODUCT. That’s not as good as SUMIFS, but it’s still a significant improvement. The Advanced Filter approach is only 4 times faster than SUMPRODUCT—which isn’t really surprising because what it does is grab an extract of all records from the source data that match the criteria in that list, dump it into the spreadsheet, and then sum the result.
1st SUMPRODUCT could become
=COUNTIFS(Sheet1!$N:$N,$A4,Sheet1!$H:$H,"1A*",Sheet1!$M:$M,"<>service catalog",Sheet1!$J:$J,"incident",Sheet1!$I:$I,"<>self-serve",Sheet1!$AK:$AK,AFM$1,Sheet1!$E:$E,">="&$E$1,Sheet1!$E:$E,"<"&$E$2)
The LEFT part can be handled by a wildcard, as shown
change the second part along the same lines