Helps with increasing date frequency in continuous X-axis mode

[Syndicate_Admin]

Hello everyone, I will appreciate your help with the following:

I have a graph of grouped columns and lines, where the X axis (date) is in "continuous" mode, this in order to visualize all the data of the spectrum. The problem is that I need as many dates as possible to be seen, as it only shows me 4-5 dates separated in a referential way. I attach images from my dashboard.

Thank you in advance for your support

[v-nmadadi-msft]

Hi @Syndicate_Admin,

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Thanks and regards

[v-nmadadi-msft]

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Thank you.

[v-nmadadi-msft]

Hi @Syndicate_Admin ,

May I ask if you have resolved this issue? If so, please mark the helpful reply and accept it as the solution. This will be helpful for other community members who have similar problems to solve it faster.

Thank you.

[DataNinja777]

Hi @Syndicate_Admin ,

While Power BI doesn’t directly control X-axis label frequency through DAX, there are a couple of DAX-based strategies you can use to help increase the number of visible date points on a continuous X-axis.

One common approach is to create a calculated column that truncates the datetime values to a specific grain like hourly or every 30 minutes. This gives more distinct values for plotting, making it more likely for Power BI to display them when axis density is increased.

Here’s an example where we round timestamps to the nearest hour:

RoundedTime = 
VAR dt = 'YourTable'[DateTime]
RETURN DATETIME(YEAR(dt), MONTH(dt), DAY(dt), HOUR(dt), 0, 0)

If your original data is too dense (e.g., every few seconds), Power BI will still struggle to render all of it. You can downsample it in DAX by filtering for every nth row or time window.

For example, if you want to keep just one record per hour:

IsHourlyPoint = 
VAR CurrentHour = HOUR('YourTable'[DateTime])
VAR CurrentMinute = MINUTE('YourTable'[DateTime])
RETURN IF(CurrentMinute = 0, 1, 0)

Then you can filter your visual with IsHourlyPoint = 1, reducing noise and increasing label clarity.

You can also use a formatted version of your date as the X-axis if you switch to categorical:

FormattedDateHour = FORMAT('YourTable'[DateTime], "dd-mmm hh:mm")

This allows you to preserve the granularity while forcing Power BI to treat it as text categories, showing more date labels—though the axis becomes non-continuous.

These DAX tricks won’t directly increase the label frequency in a continuous axis but can help structure your data in a way that makes Power BI more likely to show what you want, especially when paired with X-axis formatting options. Let me know your time granularity (e.g., minutes, hourly) and I can tailor the DAX more precisely.

Best regards,