TL;DR
- A line chart plots data points along an x-axis (time) and y-axis (value), connected by line segments to show trends at a glance.
- Use it to track change over time, spot spikes and dips, and compare multiple series: sales, stock prices, traffic, weather.
- Keep to 4 lines max, use equal time intervals, and pick your baseline carefully to avoid misleading readers.
- FusionCharts offers 7+ variants: multi-series, zoom & pan, scroll, multi-axis, spline, multi-series spline, step-line, each built for a different data challenge.
Line charts, including what many people search for as a “number line chart”, are one of the most fundamental tools in data visualization, and for good reason. Building one is simple: plot two variables, an x-axis (often time) and a y-axis (the value you’re measuring), then connect the points. This makes them ideal for tracking change and comparing multiple data sets side by side, which is why they show up everywhere, from sales dashboards to stock tickers to website analytics.
In this guide, we’ll cover what a line chart is, why it’s essential, where it falls short, how to pick the right variant for your data, and how to build one with FusionCharts.
Table of Contents
What Is a Line Chart?
A line chart represents data over a continuous time span, generally to show the trend of a measure (or variable) over time. Data values are plotted as points, then connected using line segments.
Using a line chart, you can trace the pattern of any dependent variable over time, such as share price, EPS (earnings per share) of a company, or weather recordings like temperature, precipitation, or humidity. They are also great for comparing how data changes across multiple groups over the same time period.
Explore more line chart examples in the FusionCharts gallery →
Why Do You Need a Line Chart?
Line charts earn their place in every analyst’s toolkit for three key reasons:
1. To See Changes in a Dependent Variable Over Time
Line charts are excellent for mapping continuous data sets over a period of time. Understanding change over time is relatively easy for the human mind to process. Business owners want to see profits increase over time, content publishers want to see traffic increase over time, and public bodies want to track tax, health, or infrastructure data over time. It gives you the best context for understanding what’s happening — and how to plan for the future.
UN Population Projection of the world until 2100. Source: Our World In Data
2. To Identify Trends and Spot Spikes and Dips
Line charts help you observe trends and identify key performance issues, good or bad. A line chart lets you pinpoint the exact moment something out of the ordinary happened, which helps you know exactly where to dig for answers.
A Simple Line chart from Google Trends shows the interest in Fidget Spinners in the United States from 2004 – 2018. It is easily evident that they were quite a fad in 2017
3. To Compare Patterns Across Multiple Segments
Multi-series line charts let you compare how different groups — however they’re segmented, whether by geography, internal teams, age groups, or financial quarters — are performing against each other. This helps you identify high-performing areas and isolate conditions that are dragging results down.
A multi-series line chart showing sales performance across different quarters, a visual example of the “hockey stick” pattern that results from quarterly sales commission cycles, as reps push to hit quota before each deadline
What are the Popular Business Uses of Line Charts?
Line charts aren’t just an analyst’s tool; they show up across nearly every business function. Here are some of the most popular business uses of line charts:
- Finance and investing: Tracking stock prices, portfolio value, or revenue and expenses across quarters.
- Sales and marketing: Visualizing lead generation, conversion rates, or campaign performance over a launch period.
- Web and product analytics: Monitoring daily active users, page views, or churn rate trends.
- Operations and supply chain: Plotting inventory levels, shipment volumes, or delivery times over time.
- Healthcare: Charting patient vitals, recovery timelines, or disease case counts are also a popular business use of line charts.
- Climate and environmental reporting: Visualizing temperature, rainfall, or emissions trends across years or decades.
Because a single line chart can flex across so many use cases, it’s often the first chart type teams reach for when a stakeholder asks, “how are we trending?”
What are the Limitations of Line Charts
1. They’re Bad at Representing Too Many Groups at Once
Plotting too many lines on a single chart makes it appear cluttered. Experts advise no more than four lines on a single chart; any more than that, and it becomes difficult to interpret. If you need to show more than four groups, consider grouping smaller ones into an “Others” category, or switch to a bar chart, which handles a larger number of groups more gracefully.
Line charts are not great at showing lots of groups. If you have a lot of groups, use a bar chart to compare them.
2. Irregular Class Intervals Can Give Inaccurate Insights
Data should always be plotted at equal intervals for the lines to accurately represent reality. When a line chart connects unequal or non-adjacent time intervals, it misrepresents the underlying information. Even when the interval is regular, using too many or too few classes can mask important patterns in the data.
You simply can’t compare equal intervals for some data points and then switch to a different interval and expect the result to be a meaningful trend line. If any decline occurred in a date range that wasn’t plotted, the resulting chart could mask it entirely, leading to inaccurate insights.
What are the Best Practices for Line Charts?
Follow these guidelines to keep your line charts clear, accurate, and easy to act on:
- Use lines only to connect adjacent values along an interval scale.
- Keep intervals equal in size to ensure accurate insights.
- When the focus is on a single line’s trend, call out the highest and lowest values to add helpful context.
- Choose a baseline that suits your data; a zero baseline doesn’t always represent change effectively.
- When comparing data sets, line charts are only useful if all axes follow the same scale.
- For smaller devices, use Sparklines; keep the data-to-ink ratio high by removing unnecessary elements like axis lines and titles.
- Ensure smooth interactivity: cross-lines with anchors and values, dimming other lines on hover, and responsive legend interactions all improve readability.
Learn more about configuring anchors and lines.
What are the Different Variants of Line Charts?
Line with Multiple Series
The multi-series line chart visualizes trends and relationships across multiple datasets. It consists of various data points connected using line segments, where each point represents a single value, helping you compare different groups on the same scale to see how each is performing relative to the others.
Example use cases:
- Comparing hourly temperatures across Boston, New York, Princeton, and Miami on a given day.
- Comparing closing stock prices of Apple, IBM, Microsoft, Amazon, and Facebook over a quarter.
- Comparing salesperson performance within an organization.
- Tracking a country’s import-export trend.
- Comparing metrics like retention rate or new sales across time zones or products.
Documentation: Live example
Line Chart with Zooming & Panning
The zoom line chart is a special type of multi-series line chart that allows analysis of thousands of data points at both macroscopic and microscopic levels. Zooming and panning make this kind of analysis efficient. It consists of multiple lines, where each line represents a category, and can easily plot thousands of data points, something that would produce indecipherable results on an ordinary line chart.
Example use cases:
- Large-scale reporting, like nationwide logistics performance across multiple quarters.
- Analyzing healthcare data for patients across geographies and conditions over decades.
- Tracking stock data across industries over the years.
- Monitoring daily web traffic on a website over six months.
- Tracking daily minimum and maximum temperatures for a location over five years.
Documentation: Zoom/Pan/Scroll features · Live example
Line Chart with Scrolling
A scroll line chart shows the magnitude of change over a period of time. Because of its scroll interactivity, it can render a large number of data points without overwhelming the canvas. Data values are plotted as points connected by line segments, with a horizontal scroll bar rendered at the bottom of the chart for navigation.
Example use cases:
- Plotting a large number of data points, like monthly sales across multiple years.
- Tracking the trend of a country’s military spending as a percent of GDP across the last century.
Documentation: Live example
Line Chart with Multiple Axes & Series
A multi-axis line chart is an interactive line chart that plots data using multiple axes, letting you plot data sets with different units and scale ranges. Data values are plotted as points connected by line segments, with multiple y-axes rendered along the left and right sides of the chart.
Where to use it:
- Comparing web visits and downloads across multiple sources.
- Comparing rainfall and temperature for a city.
- Comparing GDP and GDP growth percentage for a country over the last decade.
Documentation: Dual y-axis combination charts
Simple Spline Chart
A spline chart is a specialized form of the line chart used for plotting data that requires curve-fitting. Like a line chart, data values are plotted as points — but instead of straight line segments, this chart draws a fitted curve connecting them.
Where to use it:
- Rendering the impulse response of a system or the development lifecycle for a product.
- Comparing company revenue year over year for the last decade.
- Comparing electricity consumption across a city.
Documentation: Spline chart attributes
Spline Chart with Multiple Series
A multi-series spline chart is a specialized form of the multi-series line chart, also built for curve-fitted data, but across multiple categories at once. Like the multi-series line chart, data values are plotted as points; instead of straight segments, a fitted curve connects them.
Where to use it:
- Rendering the impulse response for multiple systems, or the development lifecycle for multiple products.
- Comparing company revenue across multiple decades.
- Comparing electricity consumption across various cities in a state.
Step-Line Chart
A step-line chart visualizes trends for events that aren’t continuous in nature. For a given data set, it lets you compare the magnitude and change in values at different points of the same series while also helping you discern intermittent patterns in the trend. Data values are plotted as points connected using vertical and horizontal lines, forming a step-like progression.
Where to use it:
- Showcasing a revenue-and-expense comparison for a company.
- Comparing renewable vs. non-renewable energy production.
- Tracking enrollments each year at an academic institute.
Documentation: Step line chart guide
How to Create a Line Chart with FusionCharts
Getting a line chart on the page with FusionCharts follows the same basic pattern across variants:
- Structure your data in JSON (or XML), with each data point mapped to a label and a value.
- Set the type attribute to the chart variant you need: line, msline (multi-series), zoomline, multiaxisline, spline, msspline, or stepline2d.
- Set the renderAt attribute to the container where the chart should render.
- Define width and height for the chart dimensions.
- Set dataFormat to match your data structure (JSON or XML).
- Customize cosmetics: anchors, colors, tooltips, and axis labels, using the relevant chart attributes reference.
For handling very large data sets (10,000+ points) without cluttering the canvas, FusionCharts also supports data-skipping controls like plotBinSize and labelBinSize, covered in the line, area, and column chart guide.
How to Choose Right Line Chart for Your Data
Choosing the right line chart is just as important as collecting accurate data. The right visualization makes trends easy to understand, while the wrong one can confuse your audience and lead to poor decisions. Here is a quick overview of how to choose right line chart for your data:
| If you need to | Use this variant |
| Track one metric over time | Simple line chart |
| Compare a handful of groups on the same scale | Multi-series line chart |
| Explore thousands of data points at both a macro and micro level | Zoom line chart |
| Fit a large data set into a compact dashboard space | Scroll line chart |
| Compare metrics with different units or scales | Multi-axis line chart |
| Show a smoothed trend instead of sharp angles | Spline chart |
| Show smoothed trends across multiple categories | Multi-series spline chart |
| Visualize non-continuous, event-based changes | Step-line chart |
Conclusion
Line charts remain one of the most versatile ways to make sense of change over time, but the “right” line chart depends entirely on your data’s shape, scale, and volume. Whether you’re tracking a single KPI or comparing thousands of data points across categories, FusionCharts’ line chart family has a variant built for the job.
Ready to see it in action?
Start your free FusionCharts trial and build your first interactive line chart in minutes, no credit card required.
