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Anonymous
Not applicable

Qlik Sense - stacked bar chart - data model - dimensions - set analysis

Hi all,

I have a task I'm trying to solve. I've tested couple of ideas and I've got nothing but a partial solution (unsatisfactory).

Any help / pointing to a right direction much appreciated!

The goal:

One stacked bar graph displaying:

- one stacked bar: rolling forecasts (actuals, forecast values)

- second stacked bar: prior forecast (actuals, forecast values)

- stacked bar responding to filter pane (Date)

*note: to see how rolling and prior works in attached qvf use March-to-July as for other months there is no data available.

What I've done so far:

Cut original table to 3 tables (probably not the most optimal solution).

Created two stacked bar graphs instead of one.

Attachments:

Excel file with:

- Original data-set structure

- 3 sheets displaying 3 tables I've build (may not be the best way..)

- qvf with what I've got so far (two stacked bar graphs instead of one)


**I tend to omit the explanation on how the rolling and prior forecasts work (it is beyond the scope of this task - but if the explaining the logic is needed I can share the calculator with simple excel visualization).


Any questions let me know!

Thank you in advance!


Kind regards,

Chris.

4 Replies
sunny_talwar

In your attached qvf, I don't see anything in both your charts. You mentioned stacking charts when March to July is selected, but I don't see anything with or without selections. Have you attached the correct qvf file?

Anonymous
Not applicable
Author

Hi Sunny,

yes the attached is the correct qvf.

I'm using desktop for this exercise (Qlik Sense Desktop September 2017 - but the qvf itself was developed in 3.2 SR4).

Adding a screen showing the graphs when March is picked from the Date list.

Capture1.PNG

Chris.

Anonymous
Not applicable
Author

Adding the code for two bar graphs. Maybe this will help

marcingamza
Contributor
Contributor

Hi Chris,

You may use data island i the script to get a dimension on the chart, then you only need two measures to achieve the result.

See the attached files.

Hope it helps