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mniepytalska_
Frequent Visitor

Limitations - the number of categories in the legend + the creation of a dot plot

Hey,
I have a question when creating a chart. I would like to “catch outlier observations”. Suppose I have a time interval, for example, from 02.04.2023-15.09.2024 I have data (for 500 ID, so 500 observations during defined time):

mniepytalska__0-1726503935122.png

I need to create a chart in Power BI, where let's give an example I created in Excel. On it, we can see that for one date (02.04.2023) there are two values (marked in a circle).

mniepytalska__1-1726504026724.png

I don't actually need to split the observations by ID, but I was looking to create a dot plot in Power BI where for one date I can display two values.
I figured out a line chart, but the limitation is up to 60 categories as you can see in the visualization below:

mniepytalska__2-1726504253138.png

Would it be possible to create a chart in Power BI where for many observations I can analyze outliers + I can add simple as in the chart, i.e. Median + Q1 + Q3?
Thank you very much in advance for your help 🙂

 

1 ACCEPTED SOLUTION
v-linyulu-msft
Community Support
Community Support

Hi,@mniepytalska_ 

Regarding the issue you raised, my solution is as follows:

1.Firstly, you need to create a calculated column as shown below to differentiate data with the same date:

Column = RANKX(FILTER('Table','Table'[date]=EARLIER('Table'[date])),'Table'[id],,ASC,Dense)

2.Secondly, adjust the settings of the visual object:

vlinyulumsft_0-1726556155061.png

3.Add reference lines to the visual object:

vlinyulumsft_1-1726556155062.png

4.Adjust the colours of both to be the same:

vlinyulumsft_2-1726556169229.png

vlinyulumsft_3-1726556169230.png

5.Here is the final result, which I hope meets your requirements:

vlinyulumsft_4-1726556183301.png

Please find the attached pbix relevant to the case.

 
Of course, if you have any new ideas, you are welcome to contact us.
 

Best Regards,

Leroy Lu

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

3 REPLIES 3
v-linyulu-msft
Community Support
Community Support

Hi,@mniepytalska_ 

Regarding the issue you raised, my solution is as follows:

1.Firstly, you need to create a calculated column as shown below to differentiate data with the same date:

Column = RANKX(FILTER('Table','Table'[date]=EARLIER('Table'[date])),'Table'[id],,ASC,Dense)

2.Secondly, adjust the settings of the visual object:

vlinyulumsft_0-1726556155061.png

3.Add reference lines to the visual object:

vlinyulumsft_1-1726556155062.png

4.Adjust the colours of both to be the same:

vlinyulumsft_2-1726556169229.png

vlinyulumsft_3-1726556169230.png

5.Here is the final result, which I hope meets your requirements:

vlinyulumsft_4-1726556183301.png

Please find the attached pbix relevant to the case.

 
Of course, if you have any new ideas, you are welcome to contact us.
 

Best Regards,

Leroy Lu

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Hi @v-linyulu-msft 
thank you very much for your answer and help - this is great! I am wondering about the usability in the future of this report, by a person who will only use the implemented reporting functionalities in Power BI. At the settings stage for 'Markers' I have to mark the color separately for each series, if a new 'category' appears it does not appear on the color I set for the previous ones. I do not have the option to set for all of them:

mniepytalska__0-1726646976001.png

 

Is there a solution to make sure that always the dots, no matter how many categories will appear on the same color?
Thank you in advance for your help 🙂

Hi @v-linyulu-msft 

To solve the problem, I used a line chart, where I have the option of setting the color for everyone:

mniepytalska__0-1726648061514.png

And in addition, I can have a trend line, which is impossible for a scatter graph. Thank you so much, this column saved my report and its functionality 🙂

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