Handling fall time change in continuous Line Chart (also, how to format the X axis?)

[mjc123]

Hi all,

For context I'm using Microsoft Power BI Desktop v 2.151.1182.0 64-bit (February 2026).

Let's say I've got a SQL query that returns hourly data with the following fields: "Ept", "Utc", and "value". The first two are datetime2(0) fields, and the latter is just numerical. I've already created a measure for it which we'll also call "value" for the sake of it.

So I want to my "value" field on a line chart, ideally with "Ept" as the X-axis. When I drag "Ept" over into the "X-axis" field, it defaults to the full date heirarchy with Year, Quarter, Month and Day. I want to show the fully hourly data, so I right click on the field, and then select "Ept" rather than "Date Hierarchy". So far so good:

 => 

and that changes my chart from this:

to this:

Perfect - that's what I want.  But wait, what's that little blip to the left? Well, because November has two "01:00:00" hours, the value for those two hours is being duplicated:

How do I get it to display this properly without aggregating the hour? It seems MS BI does not make use of datetimeoffset data types, so when I return that format from my SQL query it just casts it as datetime, so I'm back in the same spot.  So next I tried charting with Utc instead:

Great - that works. That's what I want to see, but now the problem is that my x-axis is now shifted by 4 (or 5) hours, so now my first hour of data starts at 11/1/2025 04:00:00 instead of 00:00:00.

So my question is how can I show my chart in EPT without duplicating the duplicate hour? I can create a text column with the date/time showing the full "m/d/yyyy hh:mm:ss TZ" for example, and display it with the X-axis set to "Categorical" mode. works, but then it tries to label every single hour and adds a scroll bar, eg:

So that's not what I want either.

Ideally, I really want the UTC chart with the EPT labels.  Is that possible? Or at least possible to get something close?

---

Secondary question - far less important, but is there any way to change the default x-axis labels in a continous line chart?

it seems I can change the font details, color, units (not applicable for dates), decimal places, etc, but not change the format itself.  If I try changing the format of the underlying column itself, it only changes it in the tool tip:

[v-nmadadi-msft]

Hi @mjc123 

May I check if this issue has been resolved? If not, Please feel free to contact us if you have any further questions.

Thank you

[v-nmadadi-msft]

Hi @mjc123 

I wanted to check if you had the opportunity to share the requested information. Please feel free to contact us if you have any further questions.

Thank you.

[grazitti_sapna]

Hi @mjc123,

Your issue is caused by Daylight Saving Time (DST) where 01:00 AM occurs twice in Eastern Time (EDT → EST change).

What i can suggest is instead of using UTC in the x axis and showing EST in tooltips or labels.

Created a sample .pbix for you, hope this helps.

Also, while i select the X Axis type to continuous, I am just seening the time and not complete time Stamp.

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[mjc123]

Thanks for the response - unfortunately, other than adding "Utc" and "Ept" to the tooltips, what you sent is exactly what I already had.

Working off the example you provided, I want that same chart, but I want the X-Axis labels to start at 12:00 AM, not 4:00AM.   In other words, I basically want them to show what you added as "EPT Label", but in continuous mode so that not every single label is displayed

[grazitti_sapna]

Hi @mjc123,

Please see the attached file, is that what is required? As the data in this file is limited and utc date is starting from 4:00 a.m onwards so the x axis is startigng from 4 am, I've replaced X axis with ept and it's showing correct dates. also x axis is already continuous.

[v-nmadadi-msft]

Hi @mjc123 ,

Please provide sample data that covers your issue or question completely, in a usable format (not as a screenshot).

Do not include sensitive information. Do not include anything that is unrelated to the issue or question.

Please show the expected outcome based on the sample data you provided.

Regards

[mjc123]

Sorry - I was on vacation, just got back last night.

in terms of the most recent response from @grazitti_sapna, I'm seeing this:

The problem is that now it looks correct, but we're back to the issue of aggregating that Ept hour. As you can see from the data you generated yourself:

There is no row with a Value = 27.  Instead it's adding 12 + 15 for the two "1:00:00 AM" hours. 

To be clear, using your data there, I want to see this chart:

but with this x-axis labelled as some variation of: "12:00 AM, 01:00 AM, 01:00 AM, 02:00 AM, 03:00 AM, 04:00 AM, ..."
I say variation because we could even do something like this:
"12:00 AM ED, 01:00 AM ED, 01:00 AM ES, 02:00 AM ES, 03:00 AM ES, 04:00 AM ES, ..."

@v-nmadadi-msft, you asked for "sample data that covers your issue or question completely, in a usable format". You could honestly use the data @grazitti_sapna created, but here is a full month which is more applicable to what I'm doing:

let
    base64Str = "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",
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText(base64Str, BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Utc = _t, Ept = _t, Value = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Utc", type datetime}, {"Ept", type datetime}, {"Value", Int64.Type}})
in
    #"Changed Type"

If I drop that same code into @grazitti_sapna's example, I get this:

which would be fine, except for that blip on Nov 2nd:

You said, "Please show the expected outcome based on the sample data you provided.". It's hard to do that because if I knew how to do that I wouldn't be here. But I'll approximate it for you:

I achieved this simply by adding 30 minutes to the second 01:00 hour such that my raw data looked like this:

Maybe that's the solution. I'll have to adjust my SQL query to do that, but it's really a hack job and not "technically" correct. It boggles my mind that it never occurred to the devs that a user might want to chart a sub-daily timeseries chart with X-Axis labels in a timezone that includes a duplicate hour in the fall time change.  

[grazitti_sapna]

Hi @mjc123,

It's a bit clear about the requirement, I've altered the solution and created a .pbix.

Kindly see the attached

[mjc123]

Hi @grazitti_sapna, 

I'm not sure if your version of Power BI is working a little bit differently than mine, but the chart in your latest file looks very similar to what I had taken a screenshot of in my previous post. i.e:

It's the X-Axis labels that are the problem:

My ideal solution would be something like this (with or without the TZ indicator):

I realize I can do it by setting the axis to "Categorical", and that would work for small timescales like the above - but it breaks when trying to display, for example, an entire month (or more) of hourly data -- unless there's a setting somewhere to hide some of the category labels.

I can see you added an "EPT Display" column in your data, and I follow the math but for some reason it isn't evaluating properly for me:

It does work if I add a helper column... not sure why it isn't evaluating properly without it:

But either way, thsoe "EPT Display" values don't end up showing up in the X-Axis labels, only in the tooltips:

as noted previously, I can get exactly what I want by changing it to categorical:

but again, that's only good with a small data set. if I use the full month's data, I get this:

labels are correct, but now there's a scroll bar and that's not what I'm looking for.

I think that what I'm looking for simply isn't possible with the standard line chart visualization. I'll have to do a work-around like what I noted in my previous post, by adding 30 minutes to the duplicate hour or something like that.

[v-nmadadi-msft · Accepted solution]

Hi @mjc123   ,

There are potentially two workarounds in your scenario, You can address this by creating a new calculated column that explicitly handles the duplicate hour scenario instead of letting Power BI aggregate it implicitly. The idea is to build a column that detects when the same Ept timestamp appears more than once (like the repeated 01:00 AM during DST change) and slightly differentiates or tags those rows so they are treated as unique points on the axis. For example, you can use DAX to count occurrences of each timestamp and append a sequence or offset to the duplicate instances, which is potentially being used by you currently if I am not wrong. Another workaround is, you can handle this at the measure level by creating a DAX measure that intentionally ignores one of the duplicate timestamps so the visual doesn’t aggregate both values. The idea is to rank rows for each repeated Ept value (using a stable column like Utc), and then return the value only for the first occurrence while blanking out the rest. This way, the visual plots a single point for that hour without summing duplicates in Power BI.

I hope this information helps. Please do let us know if you have any further queries.
Thank you

[mjc123]

Hi @v-nmadadi-msft , thanks for that.  I think that's where my head ended up as well. Neither of the two options is ideal - but both will accomplish what I'm looking for at least in terms of the visual. For my calculations (in a matrix table) I need to include both hours, but at least for the visual nobody will notice a single hour missing.

I'll mark your post as the solution because I think it's the best we'll get without some fundamental changes to the way the visuals are handled; perhaps in some far flung update down the road 😄

[v-nmadadi-msft]

Hi @mjc123 ,

We really appreciate your efforts and for letting us know the update on the issue.

Please continue using fabric community forum for your further assistance.

Regards