I have been struggling with the following calculation. I have tried a few previous, next and overs but I cant seem to get the syntax correct.
Basically i need to subtract demand from stock on hand, to get a new column. the the next row will use the newly created column as stock on hand and the subtract the demand for that row, then that result becomes the new stock on hand etc. i cant get it to loop. I have ranked the demand in order of date required per plant. AS the data set will have multiple Plants, SOH and demand.
The attached pic shows A020 only has one QTY short so that is straight forward, but for A030 opening SOH is 152, and the 1st date QTY short is 12, so i need 152-12 = 140. then the second date QTY which is ranked 2, needs to be 140 - 12 = 128, so then rank 3 uses 128 - 12 and so on. ie the SOH needs to dynamically update.
data set
It might not be natively possible in point-and-click Spotfire (happy to be corrected if this is incorrect).
You should consider writing a data function using R to do this groupby-loop operation.
Related
I'm new to Tableau. I am trying to make an inventory report which tells the user how much of certain product he/she should buy in advance.
Depending on the amount of days selected on the filter, the difference in days of the complete period should be calculated. For example: If the filtered dates are from 1/03/2021 to 09/03/2021, the result should be equal to 9. The formula I used is the following: date_difference = DATEDIFF("day",MIN(DATE([Fecha])), MAX(DATE([Fecha]))) + 1
The problem comes when I try to use the value given by such date filter. My next calculation should be:
calc = Quantity Inventory / (Units sold / date_difference). Both Quantity Inventory and Units sold are calculated fields in which I have no problem. However, instead of having a fixed value of 9, date_difference changes as shown in the image, giving me incorrect results for the desired calculation.
How can I make sure that the calculated field date_difference has the value of 9 on all rows?. Actually, if I add date_difference field by itself in a different Page it does show the proper value. The problem occurs when calculating calc and trying to add it to the table.
Note: Remember that the value of date_difference will change, depending on the range of time selected on the date filter
Thanks a lot in advance.
Step-1 Use this calculation for date_difference instead
DATEDIFF('day', {min(DATE([Fecha]))}, {max(DATE([Fecha]))}) +1
Step-2 Add Fecha filter to context, by right clicking it in filters shelf.
This will solve your problem. See the GIF
I have a table of challenge submissions (that records the time of submission of a challenge in a competition by different players, and whether the submission was correct or not) -
and another table that has the points associated with each challenge -
How do I plot a graph of running sum of points earned by the top 3 players in the competition over time (for last 24 hours only)? The catch here is that I only need to consider the first successful submission in case there are more than one successful submissions for a challenge in the competition (eg. Challenge #17 for Player A).
EDIT:
Dummy Data
Desired Output:
I am proposing a solution/answer assuming a few things-
Challenge acceptance time ends at 17:00 everyday
Different lines represent different challenges
Step-1 Create a CF to adjust date/time by calendar date - adjusted date as
DATEADD('hour', 7, [Date])
Note that I have added 7 hours to make the last calendar date/time for submission as 00 AM next day.
Step-2 Create another CF win_loss as
If [Success]='W' then 1 ELSE 0 end
step-3 create another CF game points as
[win_loss]*[Points (Points)]
Step-4 create another CF first win or loss as (don't worry about loss here)
{FIXED [Player], [Challenge], [success] : MIN([Date])} = [Date]
Step-5 create a set on 'players' field with TOP-3 with this formula (select top 3) by
sum(
IF [first win or loss]= TRUE
then [game points] END)
Step-6 build your view by dragging
set, MDY(adjusted date) & first win or loss on filters shelf/card
add mdy filter to context
[date] with exact date and discreet to columns
sum(game points) to rows
adding table calculation on measure - running total
right click sum(game points) click edit in shelf and replace the existing calculation by this one-
RUNNING_SUM(ZN(SUM([game points])))
(Note this will ensure your lines start at f(x)=0 always)
challenge on colors in marks card
sum(game points) to text in marks card.
Note- filters on (i) Set will ensure the top 3 players are in view only
(ii) adjusted date will ensure view for 24 hour challenge submission time
(iii) first win or loss will eliminate second and subsequent win(s) by same player for same challenge
I hope this will also make things clear to you.
You should get your desired view
OR change the date field to seconds to get a view like this
Context:
I have a data set for the weights of truck and trailer combinations coming into my site over the span of a few years. I have organized my data by seasons as I am trying to prove that the truck:trailers in winter are noticeably heavier due to ice, snow, and mud. The theory is, if the tare weight is higher in this season (the weight of the truck after it empties its load) than its Avg tare weight (which I need to calculate from the data) it can be deduced that the truck:trailer combinations are coming in with extra weight that we pay for in part as some snow/ice/mud falls off in the trailer emptying process.
What I've done so far:
I've defined a custom date range for my seasons
I've grouped Truck:Trailer by: count to get a duplicates column and, all rows to keep all my details
I've filtered out every combination I've seen less than 50 times, as i want good representation for each truck:trailer combo so that I can better emphasize repeated patterns
I've added an index column to better keep track of the individuals before expanding the details
What I need to do:
I only want to work with truck:trailer combinations which have weighed in for all four seasons at least once
I need to find the average tare weight of the truck:trailer combinations based over the extended range for both summer and autumn (the dry time of the year) while preserving the raw tare data for all seasons, as I need to eventually compare the winter tare values to this average.
example of my data
When I'm finished I'd like the data to look something like this
Pivot Chart
query data
For your first question (all seasons) you can add a column that holds the distinct count of the values in [Season] for each [Driver:Trailer]. Then filter your table on that column, keeping only the 4's. To achieve this, add the following m-code to your script in the Advanced Editor. Change the part after in to #"DistinctCount Season"
#"DistinctCount Season" = Table.Join(#"insert name previous step","Driver:Trailer",
Table.Group(#"insert name previous step", {"Driver:Trailer"},
{{"DistinctCountSeasons", each Table.RowCount(Table.Distinct(_,"Season")),
type number}}),"Driver:Trailer")
Insert the name of your previous step where indicated.
For second question:
You can use a matrix-visual for that in you report. First create a measure:
[AverageTare] = AVERAGE(table'[Tare])
Then put [Season] on Rows and the [AverageTare] on Values. You can create a group (right-click on [Season] in the FIELDS-pain) called [DrySeason], to combine the values for Spring and Summer.
If that doesn't work for you, explore the AVERAGEX function.
EDIT
In excel you can use a pivottable. Put [Season] on Rows and the [AverageTare] on Values. Right-click a value in the pivottable. Select Value Field Setting and choose Average. Then select the Seasons you want to group, right-click and select Group.
EDIT 2
To add a column in the Power Query Editor that holds the average [Tare] for the [Season] in each row, add the following steps to your script in the Avanced Editor:
#"GroupedSeasonAvg" = Table.Group(#"Insert name previous step", {"Season"}, {{"AVG", each List.Average([Tare]), type number}}),
#"JoinOnSeason" = Table.NestedJoin(#"Insert name previous step",{"Season"},GroupedSeasonAvg,{"Season"},"AVGGrouped"),
#"ExtractSeasonAVG" = Table.ExpandTableColumn(JoinOnSeason, "AVGGrouped", {"AVG"}, {"SeasonAVG"})
It works something like this:
"GroupedSeasonAvg" : Creates a table with the avereges for each [Season]
"JoinOnSeason": Creates a new column with tables joining the [Season] value for each row to [Season] in the grouped table.
#"ExtractSeasonAVG": Expand each table and keep only [AVG].
I know there must be a simple answer to this, but I can't find it.
I have added a couple of textboxes to a Matrix in a BIDS/SSRS report. I've given these textboxes values such as:
=Fields!WEEK1USAGE.Value
It works (after a fashion); when I run the report (either on the Preview tab, or on the Report Server site) I see the first corresponding data value on the report - but only one.
I would think that once a value has been assigned via expressions such as "=Fields!WEEK1USAGE.Value", each value would display (rows would automatically be added).
There must be some property on the Matrix or the textbox that specified this, but I can't see what it might be.
Here is how my report looks (very minimalistic, so far) in the Layout pane:
...and after running, on the Preview tab:
Obviously, I want the report to display as many rows as necessary, not just one. The textboxes do have a "RepeatWith" property, but there description doesn't sound interesting/useful/promising.
I don't see any property on the Matrix control that looks right, either.
I thought maybe the designer was only showing one row of values, and ran the report on the server, too, but there also it just shows the two values.
So what do I need to do to get all the data for a provided field?
Matrices are for display of grouped data and summary information, usually in a horizontally expanding pivot table type of format. Is a matrix really what you are after? Looking at your expression you have =Fields!Week1Usage.Value but in a matrix what I expect to see would be at least =Sum(Fields!Week1Usage.Value) or even better just =Sum(Fields!Usage.Value). Then you would have ProactDescription as your row group and the week as your column group and it would all just work out everything for you, grouping and summing by Proact vertically and expanding the weeks out horizontally.
What seems to be happening is that you have no grouping on rows or columns and no aggregation so it is falling back to the default display which is effectively the First function - it displays the first row of data and as far as the matrix is concerned it has done its job because there is no grouping.
Without knowing your problem or data, I'll make up a scenario that might be what you are doing and discuss how the matrix does the heavy lifting to solve that problem. Let's say you have usage data for multiple Proacts. Each time one is used you record the usage amount and the date and time it is used. It could be used multiple times per day but certainly multiple times in a week. So you might be able to get the times each Proact is used from a table like so:
SELECT ProactDescription, TimeUsed, Usage
FROM ProactUsage
ORDER BY ProactDescription, TimeUsed
In your report you want to show the total weekly usage for each Proact over multiple weeks. Something like this:
Proact Week1 Week2 Week3 ...
Description Usage Usage Usage ...
--------------------------------------------
Anise, Fennel 1 CT 20.00 22.50 16.35 ...
St John's Wort 15.20 33.90 28.25 ...
...
and so on. Using a dataset based on the SQL above we create a matrix and in the row group properties we group on =Fields!ProactDescription.Value and in the column group properties we group on a week expression like =DateDiff(DateInterval.Week, Fields!TimeUsed.Value, Today) and then in the intersection of the row and column we put =Sum(Fields!Usage.Value). To display the header of the column nicely put an expression like
="Week " & DateDiff(DateInterval.Week, Fields!TimeUsed.Value, Today)
The matrix automatically does all the summing by week and product and expands the weeks horizontally for as many as you are reporting. For bonus points you can also put totaling at the end of the columns and the rows to show the total use of that Proact for the period (row total) and total use of all Proacts in that week (column total).
I have a PowerPivot table for which I need to be able to determine how long an item was in an Error state. My data set looks something like this:
What I need to be able to do is to look at the values in the ID and State columns, and see if the value in the previous row is ERROR in the State column, and the same in the ID column. If it is, I then need to calculate the difference between the Changed Date values in those two rows.
So, for example, when I got to row 4, I would see that the value in the State column for Row 3, the previous row, is ERROR, and that the value in the ID column in the previous row is the same as the current row, so I would then calculate the difference between the Changed Date values in Row 3 and Row 4 (I don't care about the values in any of the other columns for this particular requirement).
Is there a way to do this in PowerPivot? I've done a fair amount of Internet searching, and it looks like if it can be done, it would use the EARLIER or EARLIEST DAX functions, but I can't find anything that tells me how, or even if, this can be done.
Thanks.
Chris,
I have had similar requirements many times and after a really long time of trial-and-error, I finally understood how EARLIER works. It can be very powerful, but also very slow so always check for the performance of your calculations.
To answer your question, you will need to create 4 calculated columns:
1) Item Rank - used for ranking the issues with same Item ID
=COUNTROWS(FILTER('ID', EARLIER([Item ID]) = [Item ID] && EARLIER([Date]) >= [Date]))
2) Follows Error - to easily find issue that follows EROR issue
=IF([State] = "EROR",[Item Rank]+1)
3) Time of Following Issue - simple lookup so that you can calculate the different
=IF([Follows Error]>0,
LOOKUPVALUE([Date], [User], [User], [Item Rank], [Follows Error]),
BLANK()
)
4) Time Diff - calculation of time different for the specific issue
=IF([State]="EROR",
DAY([Time of Following Issue])-DAY([Date]),
BLANK()
)
With those calculated columns, you can then easily create a powerpivot table, drag State and Item Id onto the ROWS pane and then simply add Time Diff to Values. You will get an overview of issues that contain string "EROR" issue and the time it took to resolve them.
This is what it looks like in PowerPivot window:
And the resulting Pivot table:
You can download my Excel file here (2013).
As I mentioned, be careful with the performance as the calculated columns with nested EARLIER and IF conditions might be a bit too performance-demanding. If there is a smarter way, I would be very happy to see it, but for now this works for me just fine.
Also, keep in mind that all calculated columns could be nested into 1, but I kept them separated to make it easier to understand the formulas.
Hope this helps :-)