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.
Related
Does anyone know if I can add two rows together so that I end up with just one row in Tableau (see screenshot)? So, if both rows are city Aachen and one row has a value for cost but not for purchasing power and the other row has a value for purchasing power but not cost, I would want just one row with both values. I am not interested in the columns "Table Name" and "Document Index(...". Thankful for any help!
Manipulating data like that in Tableau is usually no-go. Nevertheless, you can try Tableau prep and you should be able to do what you need here. Or maybe a different tool (even excel).
With that said, even though you have the info in two rows, the default approach for Tableau is always to aggregate data, so even if you have many rows with similar cases, once you take it to a viz using City (for example) as a dimension, this issue shouldn't really matter.
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 an issue that I have been trying to solve for the better part of a week now. I have a large database (in Google sheets) representing casestudies. I have some columns with multiple categories listed (in this example 'species', 'genera', and 'morphologies'), and I want to be able to tally how many times each category occurs in the data set.
I use Tableau to visalise the data, and the final output will be a large publc tableau. I know I can do a "find" based on the specific string, but I'd like the dataset to be dynamic and be able to handle new data being added without having to update calculated fields? Is there a way of finding uniqe terms (either from a single column of comma separated values, or from multiple columns), and tallying them?
Things I have tried so far:
1 - A pivot table in Tableau. Works well, but messes with all the other data, since it repeats lines.
2 - A pivot table on its own data source in Tableau. Also works well, and avoids the problem of messing with the other data. However, now each figure is disconnected from the others so I can't do a large dashboard where everything is filtered by each other (ie filtering species and genera by country at the same time).
3 - An SQL query() in google sheets, which finds all unique terms and queries them, which can then be plotted in Tableau. Also works well, but similar problem of the data being disconnected from all the other terms in the dataset.
Any ideas of a field calculation that will find, list and tally unique terms in a single comma separated column (or across multiple columns), without changing the data structure?
I have placed a sample data set here (google sheets), which is a smaller version of what I'm actually working on. In it I have marked comma separated columns in grey, and they're followed by a bunch of columns with the values split into columns. I only need to analyse either of those (ie either a calculation to separate comma separate values or from multiple columns).
I've also added a sample Tableau workbook here.
What is the best way to store metrics data used in displaying graphs?
Currently I have a table analytics(domain::text, interval_in_days::int, grouping::text, metric::text, type::text, labels[], data[], summary::json)
domain is the overall category of the metrics. Like what part of the application they're under. Could be sales or support etc.
the interval_in_days and grouping are 'view options' the end user can specify at the interface level to have a different view of the data points.
grouping can be date, day_of_week or time_of_day
interval_in_days can be 7, 30 or 90
labels is an array of the labels on the x-axis and data are the corresponding datapoints.
type is either data_series or summary. If data series, the row represent's the data used for drawing the graph, while a summary has the summary:json field populated with an object like {total_number_of_X: 132, median_X: 320.. etc}
metric is simply the metric the corresponding graph represents, so there's a separate graph for each value of metric
From this it follows that for each metric/graph I display, I have 9 (3 intervals * 3 groupings). For each domain I have a single row with type summary.
Every few hours I aggregate a lot of data across multiple tables into the analytics table. So I don't have to perform expensive queries adhoc.
I feel this is not the optimal approach, so I'm really interested in seeing how other people accomplishes the same task or any suggestions.
There is nothing wrong with storing 9 rows of raw data and later aggregating them to something more comfortable. It's a common approach and has performance benefits in some situations.
What I would really re-think in your design are the datatypes. From your description it seems you can transform all ::text fields into something like ::varchar(20). Then you can use STORAGE PLAIN on these columns and your table will become more efficient.
Also, consider adding foreign keys to describe what is stored in individual columns. For example, you stated grouping can be date, day_of_week or time_of_day, so you could have a groupings table that will list these options. But again, the foreign key would have to be covered by an index, so you may want to skip on that due to performance reasons.
I am attempting to join two datasets in to one tablix for a report. The second dataset requires a personID from the first dataset as its parameter.
If i preview this report only the first dataset is shown. but for my final result what i would like to happen is for each row of a student there is a rowgrouping (?) of that one students modules with their month to month attendance. Can this be done in report builder?
The best practice here is to do the join within one dataset (i.e. joining in SQL)
But in cases that you need data from two separate cubes(SSAS) the only way is the following:
Select the main dataset for the Tablix
Use the lookup function to lookup values from the second dataset like this:
=Lookup(Fields!ProductID.Value, Fields!ID.Value, Fields!Name.Value, "Product")
Note: The granularity of the second dataset must match the first one.
We had a similar issue and that can be resolved this way.
First of All, ensure the first data set's query and second data set's query are working fine by executing separately on the Database client tool such as Datastudio.
Build two data sets on SSRS tool with the respective queries and make sure both the data sets have same key column (personID).
On the SSRS report design, create a table from tool box and add the required columns from the first data set along with the matching key column(personID). Add a new column and use look up function to get the required column from the other data set against the same key column (personID).