How to Make a Time Series Plot in Tableau

Visualizing how your data changes over time is a cornerstone of effective analysis, helping you to spot trends, understand seasonal patterns, and make informed forecasts. This hands-on tutorial will guide you step-by-step through creating a powerful time series plot in Tableau, turning your raw date-based data into a clear and insightful visualization.

What is a Time Series Plot?

A time series plot, also known as a time series graph or a run chart, displays data points at successive, ordered points in time. The horizontal axis represents the time scale (days, months, years), and the vertical axis represents the metric you're measuring (sales, website traffic, user signups, etc.). Its primary purpose is to show how a variable changes over a specific period.

For any business, these plots are incredibly valuable for answering fundamental questions like:

Are our sales growing, declining, or staying flat over the last three years?
Do website sessions spike at a particular time of year, like during the holidays?
How did our ad spend last month correlate with the number of leads we generated?

By plotting your data over time, you can quickly move beyond static numbers and start to build a narrative around your performance, identifying patterns and outliers that a simple table would hide.

Preparing Your Data for Tableau

Before you build anything, a successful time series chart relies on well-structured data. The most important requirement is to have a dedicated column containing date or datetime information. Tableau is quite intelligent and usually recognizes date fields automatically, assigning them a small calendar icon in the Data pane.

However, you might run into a few common issues:

Dates stored as text: Sometimes, dates are imported as text strings (e.g., "January 2024" or "2024-01-15"). If you see "Abc" next to your date column instead of a calendar icon, Tableau considers it text. To fix this, right-click the field in the Data pane, go to Change Data Type, and select Date or Date & Time. If that doesn't work directly, use a calculation with the DATEPARSE function to tell Tableau how to read the string.
Discrete date parts: You might have separate columns for Year, Month, and Day. You can combine these in Tableau by creating a calculated field using the MAKEDATE function: MAKEDATE([Year], [Month], [Day]).
Data granularity: Think about the level of detail you need. Raw, daily transaction data gives you the most flexibility, as you can easily roll it up to weekly, monthly, or quarterly views in Tableau. If your data is pre-aggregated by month, you won't be able to drill down to see daily fluctuations.

Ensuring your time field is correctly formatted from the start will save you a lot of headaches later on.

Creating Your First Time Series Plot: A Step-by-Step Guide

Let's build a classic sales over time chart. For this example, we'll assume we're working with a simple e-commerce dataset containing an Order Date field and a Sales field.

Step 1: Connect to Your Data Source

Open Tableau and on the "Connect" pane, choose your data source (e.g., Microsoft Excel, Text File, or a server connection). Locate your file and open it. Tableau will display your data on the Data Source page. If everything looks correct, click on the "Sheet 1" tab at the bottom to go to the worksheet.

Step 2: Add Your Date Field to the Columns Shelf

In the Data pane on the left, find your date field (in our case, "Order Date"). Click and drag it onto the Columns shelf at the top of the worksheet. By default, Tableau will likely aggregate this to the highest level of detail, showing it as YEAR(Order Date). This little blue pill indicates that Tableau is treating the year as a discrete, categorical label.

Step 3: Add Your Measure Field to the Rows Shelf

Next, find the metric you want to measure (e.g., "Sales"). Click and drag it onto the Rows shelf. Tableau will now generate a visualization, probably a simple bar chart showing the sum of sales for each year in your dataset.

Step 4: Change the Mark Type to "Line"

To turn this into a time series plot, navigate to the Marks card (located in the middle-left of the worksheet). Click the dropdown menu that currently says "Automatic" and select Line. Your chart will instantly transform, connecting the points for each year with a line.

Step 5: Adjust the Date Granularity (Discrete vs. Continuous)

This is the most critical step for making your time series plot truly useful. Right now, our chart shows discrete years. What if we want to see a continuous flow of data over time, broken down by month? This is where understanding the difference between discrete (blue pills) and continuous (green pills) dates is crucial.

Discrete dates (blue): Treat date parts as separate categories. MONTH(Order Date) would show 12 points: January, February, etc., but it would aggregate all January sales across all years into one point.
Continuous dates (green): Treat dates as a continuous range on an axis. MONTH(Order Date) would show January 2022, February 2022, ... December 2023, etc., creating a proper timeline.

To change this, right-click the YEAR(Order Date) pill on the Columns shelf. In the bottom section of the context menu, you'll see options for continuous dates. Select the second "Month" option (the one below "More"). Your blue pill will turn green, and your chart will transform into a proper time series plot showing sales trending across an uninterrupted timeline of months.

You can now see the detailed fluctuations month by month and year by year, giving you a much richer view of sales performance.

Customizing and Enhancing Your Time Series Plot

A basic line chart is good, but Tableau offers powerful features to layer on more context and analytical depth.

Break Down by a Category

What if you want to see sales trends for different product categories? Simply drag the Category dimension from the Data pane and drop it onto the Color target on the Marks card. Tableau will automatically create a separate colored line for each category, allowing you to instantly compare their performance over time.

Add Markers to an Axis

For more granular charts (like daily data), the line can become hard to read. You can add markers for each data point by clicking on the Color target on the Marks card and under "Effects," selecting a marker style. This places a small circle or square on each day's data point.

Using a Dual Axis Chart

A dual-axis chart is perfect for comparing two different metrics over the same time period, like Sales and Profit, even if they have different scales.

Drag your second measure (e.g., Profit) onto the Rows shelf, creating a second line chart below your first one.
Right-click the new SUM(Profit) pill on the Rows shelf and select Dual Axis.
The two charts will be overlaid. You'll now have two separate Marks cards – one for each measure. You can change one of them to be a Bar chart while keeping the other a Line chart for a nice visual contrast.
Important: If the measures are conceptually linked (like sales and profit), right-click on the right-hand axis and select Synchronize Axis to ensure the scales match up correctly.

Adding Forecasts and Trend Lines

Tableau makes it incredibly easy to add analytical models to your view. Switch to the Analytics pane (next to the Data pane).

Forecast: Drag "Forecast" from the Analytics pane and drop it onto your chart. Tableau will project your data into the future based on historical patterns, complete with customizable confidence intervals.
Trend Line: Drag "Trend Line" onto the chart. This will draw a line of best fit through your data points, helping you to understand the overall direction (upward, downward, or flat) while ignoring short-term fluctuations. Hovering over the trend line gives you statistical information like the R-Squared and p-value.

Common Challenges and Solutions

Handling Gaps from Missing Dates

What happens if your store had no sales on a particular day? By default, Tableau might simply connect the dots between the day before and the day after, hiding the fact that there was a zero-sales day. To fix this, right-click your continuous (green) date pill on the Columns shelf and select Show Missing Values. Tableau will fill in the missing dates, causing the line to drop to zero and giving you a more accurate representation of your data.

Using Quick Table Calculations

Sometimes you don't just want to see the raw numbers, you want to see cumulative growth or period-over-period change. Table calculations do this without needing complex formulas.

Running Total: Right-click the SUM(Sales) pill on your Rows shelf, navigate to Quick Table Calculation, and select Running Total. Your line chart will now show cumulative sales, which is great for tracking progress toward a quarterly or annual goal.
Year Over Year Growth: You can quickly calculate percent difference from a prior period. Right-click your sales pill, choose Quick Table Calculation > Percent Difference. Then, right-click it again > Relative To > Previous Year. This lets you visualize YoY growth directly on the chart.

Final Thoughts

Creating a time series plot in Tableau is a fundamental skill that transforms raw data into a compelling narrative about performance over time. By moving your data from a spreadsheet into a dynamic visualization, you can quickly uncover trends, seasonality, and critical insights that drive better business decisions.

While mastering Tableau is an incredibly valuable skill, we know sometimes you just need answers without the manual setup. That's why we built Graphed to be your personal AI data analyst. You can skip the drag-and-drop process entirely and simply ask things like, "Show me monthly sales vs. ad spend for the last two years as a dual axis chart" and get an interactive, real-time dashboard in seconds. For day-to-day tracking and ad-hoc questions, get an answer instantly, turning hours of report-building into a simple conversation.