I've got a tablereport with on the rows product category and on the columns years. In the valuesection, I want to show the number of sales. This works fine. But now I also want to show the % of columntotal for the product categories.
I use dax:
Measure := count(factSales[salesnr])/calculate(count(factSales[salesnr]);all(factSales))
But this yields the percentage of grand total over all years. I want the percentage of columntotal for every seperate year.
The ALL(Table) function tells Power Pivot to ignore any filters applied over the whole table. Therefore, you're telling Power Pivot to count all the rows of the factsales table regarless of the Category or Year being filtered on the pivot table.
However, in your case, what you want is the sum for ALL the categories on each year. Since you want the sum of ALL the categories you must use `ALL(factsales[categories]). In this way, you're ignoring only the filters for the categories and not the filters for the years.
Based on the previous explanation the dax formula would be:
Measure :=
count(factSales[salesnr]) / calculate(count(factSales[salesnr]);all(factsales[categories]))
Related
I have a data frame that contains a column of total ads shown to a consumer, and also a binary column that shows whether they bought the product or not.
I want to calculate the conversion rate (# of People bought/# People in Group) after grouping the consumers based on the number of ads they have seen (e.g. Group 1: 0-9 ads, Group 2: 10-19 ads etc. all the way until say 300).
Is there a way to do this other than manually calculating by group (i.e doing 30 of the same calculation)? Perhaps with some sort of looping function?
I am trying to create a simple revenue per person calc that works with different filters within the data. I have it working for a single record, however, it breaks and aggregates incorrectly with multiple records.
The formula I have now is simply Sum([Revenue]) / Sum([Attendance]). This works when I only have a single event selected. However, as soon as I select multiple shows it aggregates and doesn't do the weighted avg.
I'm making some assumptions here, but hopefully this will help you out. I've created an .xlsx file with the following data:
Event Revenue Attendance
Event 1 63761 6685
Event 2 24065 3613
Event 3 69325 4635
Event 4 41996 5414
Inside Tableu I've created the calculated column for Rev Per Person.
Finally, in the Analysis dropdown I've enabled Show Column Grand Totals. This gives me the following:
Simple Fix
The problem is that all of the column totals are being calculated using the SUM aggregation. This is the desired behavior for Revenue and Attendance, but for Rev Per Person, you want to display the average.
In Analysis/ Totals / Total All Using you can configure the default aggregation. Here we don't want to set all of them though; but it's useful to know. Leave that where it is, and instead click on the Rev Per Person Grand Total value and change it from 'Automatic' to 'Average'.
Now you'll see a number much closer to the expected.
But it's not exactly what you expect. The average of all the Rev Per Person values gives us $9.73; but if you take the total Revenue / total Attendance you'd expect a value of $9.79.
Slight More Involved Fix
First - undo the simple fix. We'll keep all of the totals at 'Default'. Instead, we'll modify the Rev Per Person calculation.
IF Size() > 1 THEN
// Grand Total
SUM([Revenue]/[Attendance])
ELSE
// Regular View
SUM([Revenue])/SUM([Attendance])
END
Size() is being used to determine if the calculation is being done for an individual cell or not.
More information on Size() and similar functions can be found on Tableau's website here - https://onlinehelp.tableau.com/current/pro/desktop/en-us/functions_functions_tablecalculation.html
Now I see the expected value of $9.79.
I have a table visualisation in PowerBI that sums the top 10 products sold by sales quantity. I have a calculated column which shows the rate of sale, using other fields from the data source:
(quantity / # stores with product) / weeks on sale
The ROS calculates correctly, but it still sums and appears in the total row.. The number of stores and number of weeks are set to 'Don't Summarize', but they still add together and give some meaningless number in the total row. If i set ROS to 'Don't Summarize', to remove the total row, the summing of the rest of the table and therefore the filter I have on top N by quantity drops out.
It is very frustrating! Is there an option somewhere to simply not display total for a field?? I don't want to remove the total row completely as the other fields (e.g. Qty, Value, Margin) are useful to see a sum of.. It seems very strange that it is so difficult to do something so minor..
Additional info:
Qty is a SUM field.
Stores is not summarized and simply refers to the average number of stores that stock that product over the weeks of the trading season
Weeks is not summarized.
Weeks is not summarized and refers to the weeks that have passed in the trading season.
Example data:
Item.......Qty......Stores.....Weeks....ROS
Itm1........600........390.........2............0.77
Itm2........444........461.........2............0.48
Itm3........348........440.........2............0.40
Total.....1,392.....1,291*......6*...........1.65*
Fields marked with a * are those where the sum is a meaningless figure unrelated to the data. I do not actually need Stores and Weeks to show in the table, so the fact that they sum does not matter. However, ROS is essential, but the sum part is totally irrelevant and I do not want it to show. Any ideas? I am open to the idea of using R to overcome the lack of flexibility in the standard tables although my knowledge in this area is fairly limited.
I suspect you've made a common mistake - using a Calculated Column for ROS where you should've used a Measure.
If you rebuild that calculation as a Measure, then you can wrap the HASONEVALUE function around it, with the objective of showing a blank when there are multiple Item values in context (the Total row).
Roughly the Measure formula would be:
ROS = IF ( HASONEVALUE ( Mytable[Item] ) , << calculation >> , BLANK() )
I would also replace your use of / with the DIVIDE function, to avoid divide by zero errors.
You can remove individual totals for columns in tables and matrix objects in a round-about way by using field formatting.
Click the object, go to formatting, click the field formatting accordion, select the column or columns you want to affect from the drop-down list, set the font color to white, set 'apply to values' to off, and set 'apply to totals' to on.
A bit tedious if you have many columns, but you will have, in affect, whited-out the column totals.
Heads up, you might still have a problem with exporting data, though.
Cheers
Click on the table -> Fields -> expand the value field you don't want to include -> Select "Don't Summarize." This will exclude it from the "Total" row.
select do not summarise option for those metrics which you dont want total
Select the table you want to change
In the Visualizations pane:
Go to Format,
Find the Field Formatting option,
Choose the field you don't want to summarize.
Turn off 'apply to header',
Turn off 'apply to values',
Turn ON 'apply to total',
Change the font color to white.
I have a data set in BIRT Designer with two columns, one with day of week abbreviation names (Su, M, Tu, etc.) and the other with numerical representations of those days of the week starting at 0 and going to 6 (0, 1, 2, etc.). I want to determine what percentage of the total number of rows that each day of week represents. For example, if I have 100 total rows and 12 of those rows correspond to Su/0, 12% of the total rows are made up of Su.
I would like to perform this same calculation within BIRT and graph (bar graph) those percentages that each day consists of out of the total. I'm just learning how to use BIRT and assume that I need to do some scripting either when making my data set or when specifying the rows when making the chart. Any tips would be greatly appreciated.
Use computed columns.
Edit Data set > Computed Columns
The simplest way is to put one column that counts every row, for each day of the week. You can have a separate column that adds a count if the day of the week is a specific values
if (row["Day"] == "Su"){
1
}
I should add: that you can use a 'data' element in your table to compute the percentage. A 'Dynamic Text' item could also be used, but the data item gives you a binded value that you can make better use of later if needed.
Edit
To get a total row count, us a computed column I name mine 'All'
For the Expression use the value "1"
With some inspiration from James Jenkins I think I found my answer. It was pretty simple in the end, but all I needed to do was make a new computed column and instead of adding an expression, I simply set the Aggregation to "COUNT". That counts all of the rows in your table and puts that total on each row. That way you can use that total in any calculations that you may need to do. I have added a screenshot for clarity.
I'm in this situation.
I have a cube that has data aggregated by day.
This cube has a dimension with hierarchy (year-> month-> day).
in this hierarchy are visible every day for the last 4 months.
my problem is counting the days selected, because I need to do calculations based on the days observed (on a pivot).
example:
There are data for the day 11/11/2013 (amount orders), but in the hierarchy I select values from 10.11.2013 to 20.11.2013 ..
how do I calculate (amount orders) / 11?
11 is the number of days 10-20.
See my answer at MDX average fact items count by time dimension.
Having the day count as a measure in the cube would automatically apply all filters etc. without you having to take care of it.
You can use the Count() function to calculate the number of members in a set. Your set can consist of a range of dates if you use a colon between start and end date. Something like this:
Count({[Date].[Day].&[2013]&[11]&[10] : [Date].[Day].&[2013]&[11]&[20]})