Identifying Trends and Changes with Line Charts

A line chart visualizes data as a series of points connected by straight lines. It shows how values change over a continuous interval, most often time. Line charts are one of the most widely used data visualization tools because they are simple to build, easy to read, and ideal for highlighting upward or downward trends.

To build a line chart, you typically need two columns of data. The first column contains categories or time periods and is plotted on the x-axis. The second contains numeric values and is plotted on the y-axis. The charting tool connects each data point to create a continuous line. Multiple lines can be added to compare trends across products, teams, locations, or other dimensions.

Line charts are effective because they quickly show direction, rate of change, and patterns that support informed decision-making.

How a Line Chart Works

Line charts communicate changes clearly because they rely on a simple structure:

Data points

‍Each point represents a value at a specific time or interval.

Connected lines

‍Straight segments connect points in order, helping viewers see upward, downward, or flat trends.

X-axis (horizontal axis)

‍Shows time or another continuous variable such as days, months, years, or sequential stages.

Y-axis (vertical axis)

‍Shows the corresponding values such as revenue, temperature, website sessions, or units sold.

Multiple series

‍Adding more than one line helps compare related trends across the same timeline.

This structure makes it easy to identify patterns, spot anomalies, and understand long-term movement.

When to Use a Line Chart

Line charts work best when you want to show:

• How a value changes over time
• A trend that moves up or down
• Seasonality or recurring patterns
• Peaks, dips, and outliers
• The relationship between multiple series
• Progress toward a goal or threshold

Examples include questions like:

• Which quarter has the lowest revenue?
• When did a sudden spike in website traffic occur?
• How do monthly sales compare between products?
• Are customer satisfaction scores trending upward or downward?

Because line charts highlight change, they are especially useful in dashboards where teams monitor performance and take action quickly.

Types of Line Charts

Different types of line charts help tell different data stories.

Standard line chart

‍Shows a single trend over time.

Multi-series line chart

‍Compares several categories, products, or teams on the same timeline.

Symbol line chart

‍Uses circles or shapes on each point to highlight individual data values. Best for emphasizing precise points.

Step line chart

‍Connects values using steps rather than slopes. Useful when changes happen at specific intervals rather than continuously.

Curved or smoothed line chart

‍Uses smoothed curves to emphasize overall patterns rather than exact point-to-point changes.

Running total (cumulative) line chart

‍Shows how values accumulate over time.

Forecasting line

‍Extends the line into future time periods based on predictive models.

Selecting the right type helps focus attention on the message you want the viewer to understand.

Using a Line Chart to Visualize Trends

Line charts support decision-making across teams and industries. Common use cases include:

Department spending

‍Plot each department’s monthly spend to identify overspending or unusual spikes.

Stock or asset performance‍

Track the value of a stock, cryptocurrency, or asset over days, months, or years.

Revenue patterns

‍Compare historical revenue for multiple products to uncover growth trends and lagging areas.

Customer satisfaction‍

Visualize customer satisfaction scores to understand whether support initiatives are improving results.

Website performance

Monitor daily web traffic to identify drops, technical issues, or successful campaigns.

Combining Chart Types for a Cohesive Data Story

Line charts are clear and can provide direct insights into your data. However, there may not be enough information in a single line chart. Consider combining it with other chart types in a dashboard to tell a clearer picture of your data. 

For example, you can use a line chart to identify a spike in your sales across one quarter. Use an additional bar chart to visualize each product’s sales performance that quarter to see if one product drove the spike. Then add in a bubble chart to visualize customer demographics for that quarter to see what types of customers were buying your products. 

There are also many types of line charts that can help convey key points in your data in a different way. Consider what story you’d like to tell with your line chart, and then, make sure you’re using the right type of line chart for that story. Some other line chart types include: 

• Symbol lines. A symbol, typically a circle or donut shape, is used to mark each data point. Use it when you want to make individual data points more clear. It is most effective with grid lines included. 
• Step lines. Data points are connected by step lines rather than straight lines. Use it when you need to highlight irregularity in a specific data set. 
• Curved lines. Data points are connected with curved lines rather than straight ones. Use this chart type when the data points are less important than the trends and patterns in the line. 
• Running total lines. Each data point on the line shows the cumulative total of each data point preceding it. Use it when you want to show trend movement toward a larger whole. 
• Forecasting lines. Show how trends will continue into the future. Use it to predict how future decisions can impact trends.

Best Practices for Using a Line Chart

To make your line charts clear, accurate, and easy to interpret:

Include gridlines when helpful

‍Gridlines are optional, but they help readers interpret values when charts show multiple lines or dense data.

Use a meaningful starting value

‍Line charts often display changes rather than totals. You do not need to start at zero if it hides meaningful variation. Always label the axis clearly.

Limit the number of lines

‍Too many overlapping lines make the chart difficult to read. Aim for a maximum of five to seven lines. Use color and line style to differentiate series.

Use consistent intervals

‍Ensure the time intervals on the x-axis are evenly spaced. Irregular spacing can distort trends.

Label your axes

‍Clear axis labels prevent misinterpretation and make the chart more accessible.

Keep the chart simple

‍Remove unnecessary styling, colors, or 3D effects that distract from the data.

Common Line Chart Mistakes to Avoid

Avoiding these pitfalls improves clarity and accuracy:

• Using a categorical x-axis instead of a continuous one
• Plotting too many series in one chart
• Allowing inconsistent scales across the y-axis
• Failing to label axes or units
• Over-smoothing lines, which can distort the true data
• Using colors that are hard to distinguish