Vertical or calculated datasets

Question: How do I create a code book from a vertical data set and what do I have to consider for DataLion?

Sometimes there is no raw data in a project, but values that have already been calculated, which are then listed one below the other in a column. An example could look like this:

Metric	Filter1	Filter2	Value
%	Full Sample	Total	45,4
%	Full Sample	Men	50,3
%	Full Sample	Women	43,9
n	Full Sample	Total	200
n	Full Sample	Men	120
n	Full Sample	Women	80

This means we have a column with the calculated values ("value") and then further columns with filters, metrics, target groups etc.

Here, a row does not correspond to a respondent or a case as in survey data, but to a combination of filters or metrics. So, there is often a single column with numbers, but behind these there are very different metrics (in the example percentage values and case numbers).

But evaluating such data sets is no problem with DataLion. A suitable code plan could look like this (snippet):

ID	Column	Value	Description	Short Decription	Type	Levels	…
1	Filter1			Sample	Frage	Filter
2	Filter1	Full Sample	Full Sample	Sample	Auspr	Filter
3	Filter1	Boost Sample	Boost Sample	Sample	Auspr	Filter
4	Filter2			Target group	Question	Filter
5	Filter2	Total	Total	Target group	Value	Filter
6	Filter2	Men	Men	Target group	Value	Filter
7	Filter2	Women	Women	Target group	Value	Filter
8	Metric			Metric	Question	Metrics
9	Metric	%	%	Metric	Value	Metrics
10	Metric	n	n	Metric	Value	Metrics
11	Value			Value	Question	Metrics
12	Value	<num>	Value	Value	Value	Metrics

The charts are then also easy to build, but you have to remember to choose the right metric. This can be done with counter variables, for example:

For example, if you want to compare men and women: click on the question 4 (target group). Then comes a (rather pointless) chart showing the number, i.e. 33% of the rows are total, 33% are men, 33% are women. But if you then set the filter to Metric = % and select "Value" as the calculation variable, then it makes sense.

Calculation variables can be activated in the backend as follows:

Then this option appears in the charts:

Alternatively, you could also select question 11 (Metrics -> Value) and then set the necessary filters as chart or global (Metric = % as chart filter and men vs. women as breaks in the chart).

Warning: With such data sets, it is important that all filters are always set so that you get a single value. If you don't set Filter2 here, for example, you would get either 139.6% (total) or 46.5% (mean value) as a percentage, both of which are wrong.