I am trying to calculate number of customers which represent 80% of the profit so that I can use it in a calculated field which I can use in a reference line.
This is what I wrote
IIF(RUNNING_SUM([Profit])= (0.8*SUM([Profit])),
COUNTD([Customer Name]),0)
but it gives me error saying
"All fields must be constant or aggregate when using table calculation functions"
The logic is to "Count distinct number of customers which represent 80% of running total profits"
This is meant for a pareto chart, so the values are already sorted in descending order for it to work.
How do I create such calculated field which would give me number of top customers which will represent 80% of the profits?
Let me know if more clarifications are needed.
I think you are looking for a Pareto Chart. This might help:
http://www.theinformationlab.co.uk/2014/08/27/pareto-charts-tableau/
I would leverage the power of Table Calculations, where you can first do running total of profit and then simply calculate percentage of total.
Here is the link to step-by-step tutorial in Tableau10 for Pareto Analysis (80/20 rule):
https://www.tableau.com/learn/tutorials/on-demand/pareto-charts?signin=15df68b66e703787258911e79db040a7.
Hope this helps.
Related
I want to create a graph which shows the total capacity for each week relative to remaining availability across a series of specific dates. Just now when I attempt this in Power Bi it calculates this correctly for one of the values (remaining availability) but generates a value much higher than expected by manual calculation for the total capacity - instead showing the total for the entire column rather than for each specific date.
Why is Power Bi doing this and how can I solve it?
So far, I have tried generating the graph like this:
(https://i.stack.imgur.com/GV3vk.png)
and as you can see the capacity values are incredibly high they should be 25 days.
The total availability values are correct (ranging from 0 to 5.5 days).
When I create matrices to see the sum breakdown they are correct but it only appears to be that when combined together one of the values changes to the value for the whole column.
If anyone could help me with this issue that would be great! Thanks!
I am new to tableau and trying to show grand total for discrete columns however it shows blank. Is there a workaround. Can one total for discrete columns?
Here's the snapshot:
I tried to follow tableaus notes and removed the discrete columns and double clicked it , however it becomes continuos and tries to aggregate it. Is there a work around?
Please help
You can't grand total a discrete column. It either has to be continuous OR you create a WINDOW_SUM calculation to calculate the grand total, then put the total in the Title area instead of within the table.
An easy way is to move your discrete measure from the Rows shelf to the Text shelf and then make it continuous. If you have multiple measures, you can get a similar effect with the placeholder fields Measure Names and Measure Values
I'm fairly new to PowerBI, I want to calculate sum of averages as measure.
So average is perfectly fine but I couldn't manage to sum them.
average = AVERAGEX(SUMMARIZE(ProductionVolumeData,
ProductionVolumeData[ProductionOrderID],
MDCProductionVolumeData[MachineID],
"sum_volume",
SUM(ProductionVolumeData[Volume])),[sum_volume])
this formula calculates aggregates volume group by production order id and machine id and find mean.
I checked in table, it works for one ProductionOrderID but whenever I add another ProductionOrderID to table it also calculates average. What I want is to sum up averages.
How can I do that?
Thanks in advance
I'm facing an issue in QlikSense, trying to compute some statistical indicators (Percentiles, Quartiles, StdDev, Median etc.) on a dataset which is already grouped by the source.
I mean that my dataset is something similar to the following, in which I have for each combination of Week and Customer Age the total number of purchases:
I want to show the median of Customer Age, and due to the structure of the dataset I can't use fractile or median built-in functions, since they would come out with something different.
Let's suppose I want to calculate the median age of people for all the 3 weeks, so that I want to know what's the age of people who have done the 50% of my purchases.
To let you better understand the question, I show you the histogram:
In this case, the median I want to get is 24-26 years, since the 50% of the total population falls under that range.
I found a useful reference here, but I am having troubles in writing this formula in QlikSense
https://mba-lectures.com/statistics/descriptive-statistics/603/relationship-between-quartiles-decile...
Thanks a lot in advance.
[EDIT]: This is my Data Model View:
[EDIT 2]: Here is my qvf with a dataset more similar to the original one I'm using. As you can see, I can't get the correct result using your formula. In addition, I would like to use it in order to plot the trend of the median through weeks, but it doesn't seem to be possible (Even if I use the modified version of the formula I pointed out in the comments).
If you want to calculate median in such a scenario you need to weighted median and basically check which dimension value is in the middle:
Aggr(
If(
(Rangesum(
Above([# Purchases],0,RowNo())
)
/Sum(TOTAL [# Purchases]))>=0.5
and
(Rangesum(
Above([# Purchases],1,RowNo()-1))
/Sum(TOTAL [# Purchases]))<0.5
,[Customer Age])
,[Customer Age])
I have a problem with calculating CPC in Tableau.
I have the cost and the number of the click but Tableau is not calculating the right CPC. the formula I used : [Cost]/[Click]
I attached two tables in this request. first shows the table which I calculated all KPIs in Zeppelin. the second the calculation in Tableau.
The whole data set has many null and 0 values, but it is the same data set used in zeppelin.
May I ask for help,how to solve this issue?
The result of CPC is not correct in Tableau.
Helena,
the issue is that Tableau is using aggregate functions when you add measures, and in this case of CPC calculation, it's not correct.
Tableau is doing [cost]/[click] division (on row-level) and then simply averages all those numbers (you are basically calculating an average of an already average number).
What you are after is a bit different and you have to fix the math to make sure all costs are aggregated first and then divided by sum of all clicks, so:
SUM([cost]) / SUM([clicks])
This will give you the correct and mathematically sound numbers.
Hope this helps.
SUM([cost]) / SUM([clicks]) will resolve the issue