How to Make a Time Series Plot in Google Sheets
Tracking your metrics over time is fundamental to understanding your business performance. A time series plot, or time series graph, is the perfect visual tool for this, turning rows of dated data into a clear story about trends, patterns, and outliers. This tutorial will walk you through exactly how to prepare your data, create a time series plot in Google Sheets, and customize it to uncover valuable insights.
What Exactly is a Time Series Plot?
A time series plot is a type of chart that displays data points in chronological order. Typically, it’s a line chart where the horizontal axis (the x-axis) represents time and the vertical axis (the y-axis) represents the value you are measuring. From website traffic and monthly sales to stock prices and daily temperatures, if your data has a timestamp, a time series plot can bring it to life.
Why is this so useful? Because viewing data chronologically helps you instantly spot:
Trends: Is your revenue steadily increasing, decreasing, or staying flat over the last year?
Seasonality: Do your sales always peak in December and dip in February? That’s seasonality.
Anomalies: Was there a sudden, unexpected spike in website users last Tuesday? A time series plot makes these outliers easy to see so you can investigate.
Patterns: You might notice a recurring cycle in your customer support tickets that corresponds with your product update schedule.
Instead of just looking at an abstract total like "we had 10,000 users this month," a time series plot shows you the narrative - how you got there day by day.
Step 1: Prepare Your Data for Plotting
The single most important step in creating an accurate time series plot is structuring your data correctly. If your data isn’t clean and properly formatted, Google Sheets will get confused and produce a chart that doesn’t make sense. Bad data in, bad graph out.
You need at least two columns:
Column A: The Time Component. This column should contain your dates, weeks, months, or even timestamps.
Column B: The Metric. This column should contain the numerical value you want to measure at each point in time.
Here’s an example of a simple, well-structured dataset for tracking daily website sessions:
Pro-Tip: Ensure Your Dates are Actually Dates
This is the most common pitfall. Sometimes, when you import or paste data, Google Sheets might see your dates as plain text ("Jan 1, 2024") instead of a proper date value. This messes up the chronological sorting on your chart's axis.
To fix this, highlight your entire date column, then go to the menu and select Format > Number > Date. This forces Google Sheets to recognize the values as dates, which is essential for a proper time series analysis.
Make sure your data is also:
Consistent: Use the same time interval throughout. If you're tracking daily data, make sure you have an entry for each day. If weekly, stick to a consistent weekly point (e.g., every Sunday).
Chronological: It helps to sort your data by date, ascending (oldest to newest), before you create the chart. Highlight your data and go to Data > Sort range.
Step 2: How to Create the Time Series Plot (Line Chart)
Once your data is prepped, creating the chart is surprisingly fast. Just follow these steps.
1. Select Your Data
Click and drag your mouse to highlight both columns, including the headers. In our example, you would select cells A1 through B32.
2. Insert the Chart
With your data selected, go to the menu at the top of the screen and click Insert > Chart. Google Sheets will automatically analyze your data and suggest a chart type. Because you have a column of dates and a column of numbers, it will almost always default to a line chart - which is exactly what we want for a time series plot.
3. Verify the Chart Type and Axes
When you insert a chart, the Chart Editor sidebar will appear on the right. Under the Setup tab:
Chart type: Confirm this is set to “Line chart.” If not, click the dropdown and select it. A "Smooth line chart" can also be visually appealing.
X-Axis: This should automatically be your date column (e.g., 'Date'). A critical setting here is the "Aggregate" checkbox. If your X-axis looks strange, with dates bunching up, ticking this box tells Google Sheets to treat your dates as a continuous scale, which is proper for a time series.
Series: This should be your metric column (e.g., 'Sessions'). This is the data that will be plotted as a line on the chart.
Step 3: Customize Your Plot for Maximum Clarity
A default chart is good, but a well-customized chart is great. A few small tweaks can make your time series plot much easier for you and your team to understand at a glance. In the Chart editor, switch from the Setup tab to the Customize tab.
Give Your Chart a Descriptive Title
Don’t stick with the generic "Sessions vs. Date." Be specific! Click on Chart & axis titles and change the Chart title to something like "Daily Website Sessions - January 2024." This gives immediate context to anyone looking at it.
Label Your Axes
While you're in the Chart & axis titles section, give your axes proper labels.
Vertical axis title: Change this to "Number of Sessions" or just "Sessions."
Horizontal axis title: You can often leave this blank if the dates are obvious, but adding "Date" can provide extra clarity.
Adjust the Style
Click on the Series dropdown within the Customize tab. Here you can tweak the appearance of your line.
Color: Change the line color to match your company's branding or to differentiate it from other series.
Line thickness: A slightly thicker line (e.g., 4px) can make the trend easier to see from a distance.
Point shape/size: You can add markers (like circles or squares) for each data point. This helps pinpoint the value for a specific day but can look cluttered if you have a lot of data. Use it judiciously.
Step 4: Advanced Time Series Plotting Techniques
Ready to go a step further? These slightly more advanced features can help you extract even more insight from your data.
Adding a Trendline
A trendline is a straight line that best represents the overall direction of your data. It smooths out the daily ups and downs to show you the bigger picture. Are you generally trending up or down?
In the Chart editor, go to Customize > Series scroll down and check the box for "Trendline." You can leave the type as "Linear" for a standard trend. This instantly shows if your daily sessions, despite some low days, are on an upward trajectory for the month.
Plotting Multiple Time Series
What if you want to compare your paid traffic sessions to your organic traffic sessions over time? That's easy. Just add another numeric column to your data. Your data should look like this:
Column A: Date
Column B: Organic Sessions
Column C: Paid Sessions
Now, when you select your data, just highlight all three columns (A, B, and C) before clicking Insert > Chart. Google Sheets is smart enough to detect the two separate metrics and will automatically plot them as two different colored lines on the same graph. You can then individually style each line in the Customize > Series section.
Dealing with Missing Data (Gaps)
What happens if your data tracking went down for a day and you have an empty cell? By default, Google Sheets will create a gap in your line chart.
If you'd rather have the line connect across the missing point, you can change this setting. Go to Customize > Chart style and find the dropdown for Plot null values. Here you can change how Google Sheets handles blanks.
Final Thoughts
Creating a time series plot in Google Sheets is a powerful, straightforward way to visualize your data's performance over time. By carefully preparing your data and using the chart customization options, you can move beyond simple summary numbers and start seeing the trends and patterns that drive your business forward.
As you get more comfortable, you'll find that the time-consuming part isn't making the chart - it's the manual process of exporting data from different sources like Google Analytics, Shopify, or Facebook Ads and pasting it into your sheet every week. We built Graphed to solve this exact problem. It connects directly to all your in-platform analytics tools, allowing you to create live, self-updating dashboards by simply describing what you want to see - no more CSVs or manual chart building required.