Scatterplot trend line does not go through data

[dtan]

I am adding a trend line to a scatterplot. As you can see in the attached screen shot, the line does not go through the data. I cannot figure out what is going on here. In fact, two of my colleagues have looked at this and we're all stumped.

Things we've tried:

• Turning off all filters and slicers
• Filtering out blank values
• Filtering out values beyond the visible axes
• Turning off all axis limits (i.e., there is no data beyond the visible axes that could be pulling the line)

The line does respond to changes in filters: if we turn filters/slicers on and off, the line will shift, but it never actually goes through the displayed data.

Are there any other things that we should look at?

Edit/Update:

The y-axis is on a log scale. If I change the scale to linear, the line works properly. So, This appears to be a bug. When the y-axis is changed to log, the trend line continues to be on a linear scale. Is there any way to fix this?

Screen shot of y-axis on a linear scale (same data) added for comparison.

Log scale:

Linear scale:

[Anonymous]

Hi! I'm facing the exactly same issue here. Is there any workaround except creating a custom visual by myself?

[Anonymous]

Hi @dtan ,

Can you please share some sample data for test? It is hard to test without any sample data.

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Notice: please do mask on sensitive data before share

Regards,

Xiaoxin Sheng

[dtan]

Sure.  Here is a table of log-linear data that I created with python:

x	y
1	1000
2	784.76
3	615.8482
4	483.293
5	379.269
6	297.6351
7	233.5721
8	183.2981
9	143.845
10	112.8838
11	88.58668
12	69.51928
13	54.55595
14	42.81332
15	33.59818
16	26.36651
17	20.69138
18	16.23777
19	12.74275
20	10

When I plot this in PowerBI with y on a linear scale, the trend line is correct. When I plot with y on a log scale, the trend line no longer goes through the data.

Linear scale:

Log scale:

The data were created so that the relationship is perfectly log-linear, and the line should go exactly through the datapoints. Here is a plot I made with the data in python with the y data plotted as log10(y):

[Anonymous]

Hi @dtan ,

I can reproduce your scenario.
I build a table from your sample data and add a calculated column based y column, trend line works well as the result that your python code generated.

logY = LOG10([y])

Regards,

Xiaoxin Sheng

[dtan]

Thanks -- unfortunately with this fix (as in my Python demo) is that the y-axis is now in log-units. 

The ideal scenario we're trying for is to have the y-axis in their original units (e.g., 1, 10, 100), but with their spacing on a log scale, and the trend line reflecting the linearized relationship *after* the log transform.

I can't find a clear way to plot the log-transformed datapoints with the values on the y-axis in the original scale, but with the trend line showing the now linearized relationship in PowerBI.

In scripting-based plotting tools you can generally apply values to the y-axis for display purposes (e.g., have 1, 10, and 100, equispaced along the y-axis), while plotting the log-transformed data with the appropriate trendline. Is this possible in PowerBI? Is there a hacky workaround that can be done to display the y-axis in the original units, while plotting the log transformed data with trend line?

More generally, it seems less than ideal to have a trendline *not* go through data after the axis is changed to a log scale (independent of my particular problem -- this is a platform-level issue).