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Tableau | Data visualisation

Step Line Chart in Tableau: Tableau Quick Tip

A step line chart is one of the simplest ways to remove noise and let your audience see the trend without drowning in detail.

Tim Ngwena •31 January 2017 •1 min read •4 min watch •6.3K

Part ofTableau Charts

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A step line chart strips out daily noise so users can focus on the broader trend over time
Use a FIXED level of detail calculation combined with DATETRUNC to aggregate the data at a higher level than your visualisation displays
Typing DATETRUNC with 'week' returns the weekly total on every day in that week, which produces the stepped effect
You can change the aggregation level (week to month) just by editing the truncation string in the calculation
Be careful comparing two step charts side by side, as different aggregation levels change the axis scale and can mislead the user

0:00Hey, Tim here. And in this quick tip video,

0:04I'm going to show you how to create a step

0:06line chart. A step line chart is a really

0:08effective way of just removing the noise

0:11from

0:11the traditional line chart. It makes it

0:13very easy to see trends over a larger

0:15period of

0:16time without having to make the user sort

0:18of suffer by giving them more detail than

0:21is required. I use this chart to affect in

0:24my most recent makeover Monday where I was

0:26showing Donald Trump's tweets over several

0:28years, but I was trying to highlight the

0:31volume.

0:32To create this line chart, it's actually

0:34quite a simple thing. So I'm going to show

0:35you how

0:35to do that now. It works really well over

0:38sort of continuous data, continuous periods

0:41of time, but you can use this in any

0:43situation where you're trying to showcase

0:46volume. And

0:47in this particular example, I took the data

0:49down to a day level, okay? And I brought in

0:52the number of records. So I was basically

0:54seeing how much data is in each given day.

0:56And when you look at this fizz, you can

0:57start to see the noise that I'm talking

0:59about. It's

0:59really hard for me to focus on the general

1:01trend, which if you squint, you can just

1:03sort

1:04of see this general shape happening here.

1:07And I want to bring that out to the user,

1:09make it a little bit more clear. So I'm

1:12going to use the fixed level of detail

1:13calculation

1:14to highlight this trend a little bit more

1:16clearly. So I'm just going to right click

1:18number of records and I'm going to create a

1:20calculated field. I'm going to hold control

1:22and move my mouse wheel up. You can also

1:25hold control plus to do this. And I'm just

1:27going

1:27to type out my calculation. I typically

1:29type everything out and then I start

1:30filling in

1:31the blanks. So if I type in fixed, this is

1:33what I need. Hit enter. I need the date

1:36truncation

1:36function. Hit enter. I'm just going to

1:40close that off. I need to do a sum for my

1:42number

1:42of records. Go to the end. Close off that

1:46sum and then close off the fixed level of

1:49detail calculation. But I've still got an

1:51error here because my date truncation doesn

1:53't

1:53have anything in it. What I need to do is

1:55truncate the date and time. And the reason

1:58I'm doing this is because I actually want

2:00to tell Tableau to stop aggregating the

2:01data

2:02at a higher level than what my

2:04visualization is showing. In this

2:06particular case, a week.

2:08So I'm just going to go in here and type in

2:11week in between the speech marks, which is

2:14the notation for this function. And you'll

2:16see that my calculation becomes valid. So

2:18let me just describe this calculation one

2:20more time. I'm aggregating the number of

2:23records

2:24and I'm fixing it for the given week.

2:27Because I don't have a calculation which is

2:30truncating

2:31at the week level, I'm doing it in the

2:33calculation. So what this will do is it

2:35will return the

2:36total for the week on every given day in

2:38that week. And that's the effect that

2:40creates the

2:40step line chart. So I'm just going to hit

2:43OK. But before I do that, I'm going to name

2:45this example just so it's easy to find. I'm

2:48going to hit supply and it's here. I'm just

2:51going to bring that out, put it right next

2:53to my other number of records and you can

2:55start to see the effect happening. If I

2:57just make the size of the line a little bit

2:59smaller,

3:00you can see it's much easier to see the

3:02individual trends within the months because

3:05I'm aggregating

3:05at a much, much easier level to understand.

3:08And because this data set goes over

3:09multiple

3:10years, it makes more sense. Now if I wanted

3:13to, I could change this aggregation. So

3:15maybe

3:15a week isn't correct. Maybe I'd like to

3:18aggregate this down to the month. I can

3:20just type that

3:21in, hit apply and you can see it's starting

3:25to aggregate again at that level. Now you

3:28have to be careful because these two charts

3:30aren't the same. If you look at the axis,

3:33this is now in the thousands whereas this

3:34is still in the hundreds. So whilst the

3:36trend

3:37might be the same, you have to be careful

3:38about what you do when you put them next to

3:40each other. You don't want to confuse the

3:42user by showing two things that are

3:43actually

3:44vastly different. But you can keep custom

3:47izing this, keep playing around, but it's a

3:49very,

3:49very simple effect and if you add some

3:51flourishes and design touches to it, you

3:53can make it

3:54look nice and neat and simple and it's a

3:57very, very simple way of understanding a

4:00lot of

4:00information. I hope you've enjoyed this

4:02quick tip. Check out the next one next week

4:04and

4:04I'll see you soon.

Rollup

A step line chart removes the daily noise from a normal line chart so viewers can see the underlying trend over a long time period, and you can build one with a single fixed level of detail calculation.

The example uses daily data (a count of records per day) plotted as a line, which looks noisy and makes the overall trend hard to see. The goal is to smooth this into a cleaner stepped trend without losing the date-level granularity on the axis.

The Breakdown

Spot the noise in a daily line chart 0:41

Plotting a measure at day level over a long continuous time period often produces a jagged line where the general trend is hard to see, even if you squint. This is the problem a step line chart solves.
Create a FIXED LOD calculation 1:20

Right-click your measure and create a calculated field using {FIXED : SUM(...)}. This is the core building block — you need a fixed level of detail calculation to force aggregation at a coarser level than the visualisation's date grain.
Add DATETRUNC inside the FIXED clause 1:40

Inside the FIXED calculation, use DATETRUNC on your date field to tell Tableau to stop aggregating at the day level and instead aggregate at a higher level, such as 'week'. This must go inside the fixed clause for the step effect to work.
Understand why this creates the step effect 2:21

The calculation returns the total for the chosen period (e.g. the week) repeated on every day within that period, which is what produces the flat, stepped segments in the line.
Plot it and compare to the raw line 2:40

Add the new calculated field to the view alongside the original daily measure and reduce the line size; the stepped version makes the trend within each period far easier to read, especially over multi-year datasets.
Change the aggregation level anytime 3:00

As a quick tweak, you can edit the string inside DATETRUNC (e.g. 'week' to 'month') to re-aggregate at a different level — no need to rebuild the calculation from scratch.
Watch axis scale when comparing charts 3:21

Charts aggregated at different levels (week vs month) sit on different axis scales, so placing two step charts side by side can mislead viewers even if the underlying trend looks similar — check the axes before comparing.

Worth Knowing

Two step charts built at different aggregation levels (e.g. weekly vs monthly) will have different axis scales, so comparing them directly can visually mislead your audience even when the trend is genuinely similar.

Use It When

Reach for this when you're plotting volume or counts over a long continuous time span and the day-to-day fluctuation is drowning out the trend you actually want the audience to see.

How this Rollup was made provenance & method

A Rollup is drafted by AI from the video's transcript, then reviewed and edited by Tim. Everything used to produce this one is listed below — the model, the exact prompt, and the source video — so the process is transparent and reproducible.

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Prompt: The exact Rollup prompt (v2) — the full system prompt, unedited.
Source video: Watch on YouTube
Drafted: 5 July 2026 at 09:38
Reviewed & edited: 5 July 2026 at 09:41 · by Tim Ngwena

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