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])
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!
Data granularity is per customer, per invoice date, per product type.
Generally the idea is simple:
We have a moving average calculation of the volume per week. MA based on last 12 weeks (MA Volume):
window_sum(sum([Volume]),-11,0)/window_count(count([Volume]), -11,0)
We need to see the deviation of the current week vs the MA for that week (Vol DIFF):
SUM([Volume])-[MA Calc]
We need to sum up the deviations for a fixed period of time (Year/Month)
Basically this should show us whether on average, for a given period of time, we deviate positively or negatively vs the base.
enter image description here
Unfortunately I get errors like:
"Argument to SUM (an aggregate function) is already an aggregation, and cannot be further aggregated."
Or
"Level of detail expressions cannot contain table calculations or the ATTR function"
Any ideas how I can go around this one?
Managed to solve this one. Needed to add months to the view and then just WINDOW_SUM(Vol_DIFF).
Simple as that!
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.
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
It is a Tableau 8.3 Desktop Edition question.
I am trying to aggregate data using two different dimensions. So, I want to aggregate twice: first I want to sum over all the rows and then multiply the results in a cummulative manner (so I can build a graph). How do I do that? Ok, too vague, here follow some more details:
I have a set of historical data. The columns are the date, the rows are the categories.
Easy part: I would like to sum all the rows.
Hard part: Given this those summations I want to build a graph that for each date it shows the product of all the summations from the earlier date till this date.
In another words:
Take the sum of all rows, call it x_i, where i is the date.
For each date i find y_i such that y_i = x_0 * x_1 * ... * x_i (if there is missing data, consider it to be one)
Then show a line graph for the y values versus the date.
I have searched for a solution for this and tried to figure it out by myself, but failed.
Thank you very much for your time and help :)
You need n calculated fields (number of columns you have), and manually do the calculation you need:
y_i = sum(field0)*sum(field1)
Basically because you cannot iterate on columns. For tableau, each column represent a different dimension or measure. So it won't consider that there is a logic order among them, meaning, it won't assume that column A comes before column B. It will assume A and B are different things.
Tableau works better with tables organized as databases. So if you have year columns, you should reorganize your data, eliminate all those columns and create a single field called 'Date', which will identify the value of your measure for that date. Yes, you will have less columns but far more rows. But Tableau works better this way (for very good reasons).
Tableau 9.0 allows you to do that directly. I only watched a demo (it was launched yesterday), but I understand that now there is an option to selected those columns (in the Data Connection tab) and convert them to a database format.
With that done, you can use a PREVIOUS_VALUE function to help you. I'm not with Tableau right now. As soon as I get to it I'll update this with the final answer . Unless you take the lead and discover yourself before that ;)