How do you aggregate strings in Tableau? For example, at the detail level I have values of Yes and No but at the aggregated level I only want to show one of those values
For example, if the aggregation has a No in it then Show No otherwise show Yes.
i.e. if the level of detail contains a No then show no otherwise show Yes.
It would be a tad simpler if you used Boolean values instead of strings - also that would enforce that there were only two legal values. If your field, say it is called Completed, contained Boolean values (I.e. either TRUE or FALSE), then to show whether all records were completed, I.e. had the value TRUE in the Completed Column, you would simply use MIN([Completed]).
This works because Tableau treats True as greater than False, so MIN(condition) is true if and only if condition is True for every record - ignoring nulls. MAX(condition) is true if and only if there is at least one record with condition set to True. So for Booleans, you can read MIN() as “every” and MAX() as “any”.
The one wrinkle is if your boolean field allows null values. If so, you can decide between a few options. You can take the default behavior which is to silently ignore nulls as if they don’t exist, or you can wrap the field reference in a call to IFNULL() to supply a default value of your choice to replace the nulls. Really the same for any data type and aggregation function.
This technique is useful in several situations, including defining conditions for sets.
Finally, if your data set has to use strings such as “YES” and “NO” instead of booleans, you can convert to booleans easily by defining a new calculated field such as Completed as [Completed-Original] = “YES”
Related
I have some panel data in polars. The dataframe is sorted by its id column and then its date column (basically it's a bunch of time series concatenated together).
I've seen that polars has a .set_sorted method for working with expressions. I can of course set pl.col("id").set_sorted() but I want it to be aware that it's actually sorted in both id and date columns. In pandas I know the Index has an .is_monotonic_increasing property that is aware of whether all the columns of the Index are sorted but is there a way to do something similar with polars?
Have you tried
df.get_column('id').is_sorted()
and
df.get_column('date').is_sorted()
to see if they're each already known to be sorted?
For instance if I do:
df=pl.DataFrame({'a':[1,1,2,2], 'b':[1,2,3,4]})
df.get_column('a').is_sorted()
df.get_column('b').is_sorted()
Then I get 2 Trues even though I haven't ever told it that the columns are sorted.
In general, I don't think you want to be manually setting columns as sorted. Just sort them and it'll keep track of the fact that they're sorted.
If you do:
df=pl.DataFrame({'a':[1,2,1,2], 'b':[1,3,2,4]})
df.get_column('a').is_sorted()
df.get_column('b').is_sorted()
then you get False twice, as you'd hope. If you then do df=df.sort(['a','b']) and follow it up by checking the sortedness of a and b again then you see that it knows they're sorted
First of all, I have my array of columns parameter called $array_merge_keys
$array_merge_keys = ['Column1', 'Column2', 'NoColumnInSomeCases']
So then I am going to hash them, if the third NoColumnInSomeCases is not existed, I would like to treat it as null or some strings else there value.
But actually, when I use them with byNames(), it would return NULL because the last is not existed, even though first and second still have values. So I would expect byNames($array_merge_keys) always return value in order to hash them.
Since that problem cannot be solved, I am back to filter these only existed column
filter(columnNames('', true()), contains(['Column1', 'Column2', 'NoColumnInSomeCases'], #item_1 == #item)) => ['Column1', 'Column2']
But it comes to another problem that byNames() cannot compute on the fly, it said 'byNames' does not accept column or argument
array(byNames(filter(columnNames('', true()), contains(['Column1', 'Column2', 'NoColumnInSomeCases'], #item_1 == #item))))
Spark job failed: { "text/plain":
"{"runId":"649f28bf-35af-4472-a170-1b6ece50c551","sessionId":"a26089f4-b0f4-4d24-8b79-d2a91a9c52af","status":"Failed","payload":{"statusCode":400,"shortMessage":"DF-EXPR-030
at Derive 'CreateTypeFromFile'(Line 35/Col 36): Column name function
'byNames' does not accept column or argument
parameters","detailedMessage":"Failure 2022-04-13 05:26:31.317
failed DebugManager.processJob,
run=649f28bf-35af-4472-a170-1b6ece50c551, errorMessage=DF-EXPR-030 at
Derive 'CreateTypeFromFile'(Line 35/Col 36): Column name function
'byNames' does not accept column or argument parameters"}}\n" } -
RunId: 649f28bf-35af-4472-a170-1b6ece50c551
I have tried lots of ways, even created a new derived column (before that stream name) to store ['Column1', 'Column2']. But it said that column cannot be referenced within byNames() function
Do we have any elegant solution?
It is true that byName() cannot evaluate with late binding. You need to either use a Select transformation to set the columns in the stream you wish to hash first or send in the column names via a parameter. Since that is "early column binding", byName() will work.
You can use a get metadata activity in the pipeline to inspect which columns are present in your source before calling the data flow, allowing you to send a pipeline parameter with just those columns you wish to hash.
Alternatively, you can create a new branch, use a select matching rule, then hash the row based on those columns (see example below).
I am trying to create a visualisation where i can see where a product has passed 2 tests: test=overall and test=flash (these are part of the same column). then there is a column result which can be pass/fail. i want both of these tests to be pass and then i want to count the distinct products. I then want to include this figure in a dashboard that updates.
I think I want a LOD but not sure where to start. is this something i do in desktop or prepenter image description here
I am new to Tableau so LOD is something i am trying to get my head around
Use the below calculation,
if {fixed [Device]: min([Result])}='fail' then False else TRUE end
Pull this field to filter shelf and select TRUE to get only devices which pass both tests
You didn’t say how to treat devices that have both pass and fail entries for one of your tests. This expression tests whether a device has passed at least one overall test and at least one flash test. You could also use a version of this to define a set if you preferred
{ fixed [Device] : max([test] = “overall” and [Result] = “pass”) and
max([test] = “flash” and [Result] = “pass”) }
The key concept is that MIN() and MAX() operate on boolean arguments to return boolean values, treating True values and greater than False values. So MAX() tests whether the condition is ever satisfied; i.e. it returns true if the condition evaluates to true for at least one of the data records. Likewise, MIN() tests whether the condition is always satisfied; i.e. it returns true if the condition evaluates to true for every one of the data records.
If the condition ever evaluates to null, MIN() and MAX() ignore null values just like all other aggregation functions. So if that is an issue in your case, you can use IFNULL() around your expression to provide a default value.
First off this is my first attempt at a multi select. I've done a lot of searching but I can't find the answer that works for me.
I have a postgresql query which has bg.revision_key in (_revision_key) which holds the parameter. A side note, we've named all our parameters in the queries with the underscore and they all work, they are single select in SSRS.
In my SSRS report I have a parameter called Revision Key Segment which is the multi select parameter. I've ticked Allow multi value and in Available Values I have value field pointing to revision_key in the dataset.
In my dataset parameter options I have Parameter Value [#revision_key]
In my shared dataset I also have my parameter set to Allow multi value.
For some reason I can't seem to get the multi select to work so I must be missing something somewhere but I've ran out of ideas.
Unlike with SQL Server, when you connect to a database using an ODBC connection, the parameter support is different. You cannot use named parameters and instead have to use the ? syntax.
In order to accommodate multiple values you can concatenate them into a single string and use a like statement to search them. However, this is inefficient. Another approach is to use a function to split the values into an in-line table.
In PostgreSQL you can use an expression like this:
inner join (select CAST(regexp_split_to_table(?, ',') AS int) as filter) as my on my.filter = key_column
Then in the dataset properties, under the parameters tab, use an expression like this to concatenate the values:
=Join(Parameters!Keys.Value, ",")
In other words, the report is concatenating the values into a comma-separated list. The database is splitting them into a table of integers then inner joining on the values.
I store the following rows in my table ('DataScreen') under a JSONB column ('Results')
{"Id":11,"Product":"Google Chrome","Handle":3091,"Description":"Google Chrome"}
{"Id":111,"Product":"Microsoft Sql","Handle":3092,"Description":"Microsoft Sql"}
{"Id":22,"Product":"Microsoft OneNote","Handle":3093,"Description":"Microsoft OneNote"}
{"Id":222,"Product":"Microsoft OneDrive","Handle":3094,"Description":"Microsoft OneDrive"}
Here, In this JSON objects "Id" amd "Handle" are integer properties and other being string properties.
When I query my table like below
Select Results->>'Id' From DataScreen
order by Results->>'Id' ASC
I get the improper results because PostgreSql treats everything as a text column and hence does the ordering according to the text, and not as integer.
Hence it gives the result as
11,111,22,222
instead of
11,22,111,222.
I don't want to use explicit casting to retrieve like below
Select Results->>'Id' From DataScreen order by CAST(Results->>'Id' AS INT) ASC
because I will not be sure of the datatype of the column due to the fact that JSON structure will be dynamic and the keys and values may change next time. and Hence could happen the same with another JSON that has Integer and string keys.
I want something so that Integers in Json structure of JSONB column are treated as integers only and not as texts (string).
How do I write my query so that Id And Handle are retrieved as Integer Values and not as strings , without explicit casting?
I think your assumtions about the id field don't make sense. You said,
(a) Either id contains integers only or
(b) it contains strings and integers.
I'd say,
If (a) then numerical ordering is correct.
If (b) then lexical ordering is correct.
But if (a) for some time and then (b) then the correct order changes, too. And that doesn't make sense. Imagine:
For the current database you expect the order 11,22,111,222. Then you add a row
{"Id":"aa","Product":"Microsoft OneDrive","Handle":3095,"Description":"Microsoft OneDrive"}
and suddenly the correct order of the other rows changes to 11,111,22,222,aa. That sudden change is what bothers me.
So I would either expect a lexical ordering ab intio, or restrict my id field to integers and use explicit casting.
Every other option I can think of is just not practical. You could, for example, create a custom < and > implementation for your id field which results in 11,111,22,222,aa. ("Order all integers by numerical value and all strings by lexical order and put all integers before the strings").
But that is a lot of work (it involves a custom data type, a custom cast function and a custom operator function) and yields some counterintuitive results, e.g. 11,111,22,222,0a,1a,2a,aa (note the position of 0a and so on. They come after 222).
Hope, that helps ;)
If Id always integer you can cast it in select part and just use ORDER BY 1:
select (Results->>'Id')::int From DataScreen order by 1 ASC