enter image description hereI ran into a problem with pipelinedb.
There is a NUMERIC type field in the Continuous Views I built, but the mrel table generated in pipelinedb is bytea. Why is this?
Have you met? There is a good solution. Thank you
Here is the photos：
This is the result of the two columns
This is the difference between the two columns
Materialization tables (<cv name>_mrel>) store all of the state necessary to incrementally update aggregate values. These are called "transition" values. For example, to incrementally update an average, both the item count and sum must be stored; storing the average itself is not sufficient.
Some of these transition values are encoded as bytea. There is then an "overlay" view on top of the materialization table that "finalizes" the transition value at read time to give you the up-to-date aggregate value.
Related
I am trying to filter a table visualization of all of my data by looking to see if a Study Number contains Activity A. If a Study Number contains Activity A then I want to filter for all rows containing those Study Numbers even if the Activity is not A. See mock data below. In my real data set I have ~55,000 rows.
I have created a calculated to return Study Numbers if Activity= A but I am not sure where to go from there. Thanks for any help.
If(UniqueConcatenate([Activity]) OVER ([Study Number])~="A","Y","N")
Will give you this resulting column that you can then filter on (or you can use the formula as a Data Limiting Expression:
I am creating an interactive 'calculator' using tableau. I have a series of dataframes that I have crossed with one another, such that the resulting dataframe is every possible combination between the tables, and every row is unique.
Each column is its own worksheet as a table. Each table in the dashboard is a pane. So, here we have a series of tables with selectable units of measurement, and the final pane on the dashboard should filter to the cell for its respective column, on the unique row of the dataset that the user has selected and 'filtered out'.
I'm having some issues getting this to work and not sure why.
The closest I can think to solving this would be 'Cascading Filters.' Here are a couple resources:
General Use
In dashboard action-filter form
The critical piece, however, is that the filters must be selected in a specific order - therefore making them 'cascading.' This may differ from your presumed concept of clicking/filtering in any order on the worksheets to then arrive to a final answer. I do think that this may be a limitation of Tableau - I don't think that a 'many to many' type of relationship can be set up within Action Filters.
I have a calculation and it outputs multiple values. Then I am creating a table on those values. For example, in below data my formula is
if data is 1 then calculation is `one`
if data is 2 then calculation is `two`
if data is 3 then calculation is `three`
as three doesn't really appear in the output, when I create a table, three is not displayed. Is there any way to display it?
I tried table layout >> show empty rows and columns and it didn't work
data calculation
1 one
2 two
Tableau discovers the possible values for a dimension field dynamically from the query results.
If ‘three’ does not appear in your data, then how do you expect Tableau to know to make a column header for that non existent, but potential, value? It can’t read your mind.
This situation does occur often though - perhaps you want row or column headers to remain stable, even when you change filters in a way that causes some to no longer appear in the query results.
There are a few ways you can force Tableau to pad ** or **complete a domain:
one solution is to pad your data to make sure each value for your dimension field appears in at least one data row.
You can often do this easily by using a union to append some extra rows to your original data. You can often add padding rows that don’t impact any results by leaving all your Measure columns null since nulls are ignored by aggregation functions
Another common solution that is a bit more effort is to make what is known as scaffolding data source that is not much more than a list of your dimension members. You can then use that data source as a primary data source with data blending, making your original data source secondary.
There are two situations where Tableau can detect the absence of data and leave space for it in the visualization automatically
for numeric types, you can create a bin field that will automatically pad for missing bins
similarly, date fields can show missing values because, like bins, Tableau can tell when a month doesn’t appear in the data and leave room for it in the view
I have Tableau report where I am showing data by category in columns.
The table shows all columns when there is no filter on data. But when filter is applied, some of the categories do not have data, so table shrinks, hiding columns without data
Is there a way to always show columns regardless of data or not in that column?
Please see screenshots below.
Go to Analysis >Table layout> Show columns with no data or
Analysis>Table layout>Show rows with no data
The next step depends on whether your "disappearing" fields are dimensions or measures.
If you want to force the display of members for specific dimensions, then one (kind of complex) solution is to use an advanced Tableau feature called data blending to force the existence of dimension members, even if there are no related measure values. The trick is to make a simple data source, say a text file, that lists the members of each dimension. Use that source as the primary data source, and make the original data source the secondary source.
Go to Analysis >Table layout> Show columns with no data or Analysis>Table layout>Show rows with no data
Also You can right click on header and select show missing values if you are using line chart.
Solution 1: (When you’re working with Dates or Numeric bins)
Right click on the numerical or Date column to extrapolate the missing values. As you notice in the lower part of the screenshot, this will not work on Categorical data !
Solution 2: Categorical Data
As indicated in the accepted answer, Analysis > Table Layout > Show Empty Rows will get you the same result for Categorical (Text) Data
Solution 3: Calculated Columns
If for some reason, none of the 2 above point & click solutions work, you can create calculated columns to calculate the measure for each of the Categories with the below formula and then line them up on the Columns to achieve the same result
Profit (Category 1)
IF MyColumn = "Category 1" THEN
Profit
ELSE
NULL
END
Profit (Category 2)
IF MyColumn = "Category 2" THEN
Profit
ELSE
NULL
END
Not the most convenient solution when you have hundreds of unique values in your column, but nevertheless a workaround !
I'm trying to annualise my data in tableau, but get an error in the Calculated Field.
"Cannot mix aggregate and non-aggregate arguments to function"
my formula is
sum(profit)/month(selected date) *12
How do I get an integer for the current month? That seems to be the problem, it tries to aggregate the month as well.
Thanks.
Short answer: wrap the call to month in a call to min() -- which works well if you have MONTH([selected date]) on the visualization as a dimension.
There are three types of calculated fields in Tableau:
row level calculations which act on a single data row. They can read from values of other fields in the same row and return a single value per row.
aggregate calculations which act on a partition or block of data rows. They can reference the result of aggregating the values for a field across the entire partition, using a an aggregate function like SUM() or MIN().
table calculations which act on an entire table of aggregated results.
You can't mix and match. Everything in a calculated field must be all at one level or another -- either all referenced fields must use aggregation functions (for aggregate calculated fields) or no referenced fields must use aggregation functions (for data row level calculated fields).
Hence the error message you saw.
Sometimes you know that all values for a field will be the same in a partition based on your visualization, so the aggregation function seems unnecessary. But Tableau still requires you to be explicit about how to turn a block of values into a single value, because the calculation must be defined even when the visualization is partitioned differently. In these cases, you can use min(), max(), avg(), or perhaps attr() because they all return the same value for a list of identical values.
The first two types are typically executed on the server (i.e. they are implemented by Tableau emitting SQL to send to the database server). Table calculations are executed by Tableau on the client site to post-process the results from the database server.
Table calcs are the most complicated type, but can be very useful. Explaining them is a post for another day.