My requirement is to get the second max date available in report and filter the data set on this.
I tried something like this:
datediff('day',dt,max(dt))=1
Referred to this link
any help?
You're going to need Tableau 9.0 for this. Basically because any calculation you do on Tableau depends on the level of detail you have on the worksheet (the dimensions you put in there). So datediff('day',dt,max(dt))=1 won't work. First because you're mixing aggregated fields (max(dt)) with non-aggreagated (dt). Second, because the aggregation depends on the dimensions in the workfield.
But Tableau 9.0 has a new awesome feature, called Level of Detail calculations. It allows you to perform calculations in the level of detail you choose, depending not on the dimensions on the sheet. It is also calculated BEFORE any calculation on the worksheet (just after context filters).
Now to the answer. First I'll figure out what is the max(dt). Let's call it max_dt
{ FIXED : MAX(dt) }
This will calculated the maximum of dt in all your database
Now to get the second max, you can go like this:
{ FIXED : MAX(IF dt != max_dt
THEN dt
END)
}
This will calculated the maximum of dt, ignoring those who are equal to max_dt (that is the true max(dt)). Therefore, the second max.
Take a look on those LOD calculations. They were just released, I'm having tons of fun with them right now
If the view has date dimension
The easy way to do this,is to create a calculated Last()=1
then filter off the records that evaluate to TRUE
Related
I am working in Tableau and trying to create a formula that will return me the value of each customer that walks into a store by dividing Net Sales / Traffic. When I try to combine the two separate formulas, it gives me the following error: Cannot mix aggregate and non-aggregate arguments with this function. The two functions I created that I'm trying to divide are:
SOT = (SUM([Sales Net])-SUM([Sales Gcard Net]))/SUM([Traffic Perday]) and SOT Goal
When I look at it in Tableau, it's stating that SOT is an aggregate function. How do I work around this to be able to get
SOT / SOT Goal
Aggregate variables are values that are calculated in the view, and depend on the level of aggregation in Tableau. e.g. sum(Sales) will show different values in Tableau if it’s next to a Region dimension, or if it’s next to a Category dimension.
In order to avoid the errors you can use many solutions. My favorite is indeed LOD expressions. In your view, though I do not have required sample data and therefore, I cannot try my hands on different possibilities here, I suggest that this should work-
SOT = ({SUM([Sales Net])}-{SUM([Sales Gcard Net])})/{SUM([Traffic Perday])}
Do remember that this solution will over-ride your filters and if you are using filters you have to add all those to Context.
EDIT
While trying different possibilities remember these things...
{SUM([Sales])} will sum the sales over entire data and {} i.e. curly braces wrapped around the sum function will cause to return the value as non-aggregate. In other words, this will work as LOD and if you'll add this field to view, the sum of entire sales will be shown against each row.
{FIXED [DIMENSION NAME] : sum([Sales])} will sum sales separately for each Dimension value. Fixed statement (LOD) again returns the value as non-aggregate value. if you'll add this field to view, the sum of entire sales for that dimension will be shown against each dimension.
i would like to calculate the average of values of each "main" column, as shown in the picture (named as bundling column). Each bundling(main) column has 1 to N "sub columns" (which are values for a certain datetime). The bundling itself is variable, it changes for different filters.
How can i reference to these sub columns to get the sum/count and average of these? I thought of using the "Window average" function but i don't have an idea how to define the start/end offset parameters. Not sure if window average is the correct option.
Thank you very much
A level of detail (LOD) calculation will allow you to control at what level the aggregation occurs.
{INCLUDE [Agg(Bundling)]: AVG([Agg(Error Select)]}
I am struggling with Custom Filter using Calculated Field.
Below is the screenshot of the same visualized chart.
What I am struggling is to create a filter where I can give a scale of Correlation, example - I want to show all the age groups and Ethnicity where the Correlation value is between 0.6 and 0.9
I am able to bring in one Measure Value and as you can see, the filter slider is there. But I need that filter to work on all the fields and not just one value. Like a Universal Slider for all the values.
Please help.
You cannot set one filter to be used on several measures. However what you can do is create two parameters and use them to filter each measure in relation.
create 2 parameters minCorrelation and maxCorrelation with values between 0 and 1 and stepsize of 0.1 (or whatever granularity you need)
open one of your filters and go to formula, use a custom formula like [0-17] > [minCorrelation] AND [0-17] < [maxCorrelation]
repeat that for every measure and the filter will adjust when you change the values for your parameters.
Simplified example: column of 'measure' data is binary 0's and 1's. The sum of the column (all the 1's summed) is 3948. The length of the column is 4567. 3948 is 86% of 4567. How do I create a bar chart showing this percentage. All I can get is a bar adding up to 100%.
I've tried absolutely everything in the percentage of dropdown, calculated fields, online tutorials, etc.
Two approaches:
Right click on your measure field on whichever shelf you placed it. Choose Quick Table Calc -> Percentage of Total. Experiment with different settings for "Compute Using" and read about addressing and partitioning of table calculations to learn how to specify percent of "what".
Or create a calculated field specific to your problem defined as below:
sum(int([my measure field] = 1)) / count(1)
Be sure to set the default number format for your calculated field to a percentage, by right clicking on it in the data pane (left margin) and revising the default properties
Note, the second calculation works because the INT() function converts True to 1 and False to 0, which is useful in several contexts.
You can go about this using the following method
Add 'measure' to Columns and make it a Discrete Dimension
Add SUM(Number of Records) to Rows. This should give you the bar chart you need.
This would help achieve what you are looking to do. For more customization and a better look for the graph you are looking to build in Tableau.
Add 'measure' to the colour legend and make it a Discrete Dimension.
Add SUM(Number of Records) as a Label and do a '% of Total' quick table calculation.
Is there a way to calculate the average across a table based on only the value in the first column (School Name) when the first column is a string value? The current values in School Average are not correct due to the additional column values (Grade and Teacher) needed prior to the measures.
This is an ideal use case for LOD calculations. An LOD calculation allows you to specify the dimensions for a calculation as part of the calculation definition -- instead of (solely) by the Tableau shelves and cards.
To start, you can define a calculated field called,say, School_Avg as
{ fixed [School Name] : avg([Grade]) }
Assuming you have a field called Grade.
There is much more to learn about LOD calculations. See the on line help to learn more.