What Is a Line Graph?

Written by Coursera Staff • Updated on

Learn more about line graphs as we explore what this powerful visual tool is and why professionals across various industries use it.

[Featured Image] A woman who is moving into a new home looks at a real estate line graph on a laptop.

Line graphs can be a powerful tool when representing how a specific variable changes over time. Professionals across industries use line graphs to show data trends, compare different variable behavior, and forecast future values. In this article, we will explore what line graphs are, the components of line graphs, how to make your own, and tips to enhance your graphs to represent your data accurately and clearly. 

What is a line graph?

Also sometimes called a line chart, line graphs are a type of graph that demonstrates how data points trend over a continuous interval. In a line graph, you plot data points on a set of axes and then draw a line to connect these points. The graph shows how the dependent variable changes with any deviations in the independent variable. 

You could use this type of graph if you want to show trends in your data, explore how your variables change over time, illustrate relationships between variables, or compare different relationships. Line graphs are commonly used to depict time-series data, making them valuable in many industries, including finance, science, and economics.

When are line graphs used?

You can use line graphs in many professions to represent how variables relate to one another and change over time. Some ways in which you might see line graphs used professionally include:

  • Visualizing market trends for investors

  • Company revenue forecasts

  • Tracking product prices or sales

  • Comparing the spending habits over time of different consumer groups

Components of a line graph

Understanding several essential components can help you correctly interpret the data visualization when analyzing a line graph. The main parts of the representation you will want to note include:

Graph title: 

The title can help you understand the content represented in the line graph. You will typically find the title at the top of the graph.


Line graphs have two axes:

  • X-axis: This horizontal axis represents the independent variable. In line graphs, this variable is often time. Labels and tick marks along the x-axis show the values of the interval.

  • Y-axis: This vertical axis represents the dependent variable, such as price. Labels and tick marks along the y-axis indicate the scale of the data.

Data points: 

Data points on your graph represent each measure. The point will correspond with a specific value of your independent and dependent variables, which you can then use to plot the point on the axes.

Connection lines: 

After you plot your points, you connect them with a line to better illustrate their overall trend. The line provides a visual representation of how changes in the independent variable change the dependent variable.


A legend represents the lines or data sets you plotted on the graph. It identifies each line by a label or color, making it easier for viewers to distinguish between different data series. You can typically find the legend within or near the graph, often in a corner.

Pros and cons of line graphs

Line graphs can effectively represent changes in variables over time. Because of their ease of use, many professionals use this type of visual across industries. If you think a line graph might be appropriate for your data types, understanding the advantages and disadvantages can help you feel confident in your choice while avoiding common pitfalls. Pros and cons to consider include: 


  • Easy trend visualizations: Using line graphs, you can easily see the data patterns over time and show how your variables change over time. 

  • Simplicity: Line graphs are generally easy to understand and interpret, which makes them an accessible way to represent data to a broad audience.

  • Comparison of trends: You can compare multiple data sets on the same graph with line graphs. Doing so helps you see how relationships are the same or different. 

  • Forecasting: By seeing how data has trended previously, you can predict future data trends. 


  • Only suitable for some data types: Line graphs are typically used with continuous data and are less appropriate for displaying discrete or non-continuous data.

  • Might misrepresent data: You can manipulate line graphs by changing the axes and scales. Because of this, the apparent trends may be over or underrepresented. 

  • Can lose clarity: If you include too many data points, graphs can become cluttered and hard to read. 

Types of line graphs

You can choose between several types of line graphs depending on your needs. A few typical line graph types include simple, multiple, and compound line graphs. 

Simple line graph:

You use a simple line graph to visualize the relationship between two variables. It typically shows how a single dependent variable changes in relation to an independent variable, with time being a common choice for the independent variable.

An example of a simple line graph would be plotting someone’s spending over a year, where spending (dollars) is on the y-axis and time is on the x-axis. An upward-sloping line indicates increased spending over the course of the year, and the slope represents the rate of spending growth.

Multiple line graph:

You use multiple line graphs to display two or more lines on the same graph, showing how numerous dependent variables change over the same period (usually time on the x-axis).

For example, you can compare the spending of different customers over the course of the year with multiple lines plotted on the graph, the same way you did for a single-line graph.

Compound line graph:

You use a compound line graph to categorize data into two or more subtypes, with each line representing a subtype’s contribution to the whole. The top line shows the total of all subtypes, and the gaps between lines illustrate the proportions of each part.

For example, you might want to track your overall spending for the year, but look at it divided into different areas of spending. You might plot your total spending over the year and then have lines representing spending on groceries, gas, house supplies, and leisure items. 

Additional tips to enhance your line graph

When you make your line graph, taking the time to improve clarity for the viewer and representing your data in an easily understood manner can help you stand out professionally. When elevating your line graph to the next level, consider these tips:

  • Spend time labeling your axes clearly. By making sure it is easy to tell what your graph represents and what the trends are showing you, you can ensure everything is clear when explaining your results to a general audience.

  • Explore different ways to connect your data points. Depending on your data types, interpolation or curved lines may be more appropriate. 

  • Keep it simple. Try to avoid overcrowding your graph and overloading your viewer with information.

  • Use different styles strategically. If you are showing more than one data set, using colors or markings strategically can help differentiate the patterns for viewers.

Learn more on Coursera

You can continue learning about graphing techniques with online courses offered on the Coursera learning platform. Classes like Algorithms on Graphs will introduce you to concepts in graph theory, data structures, and algorithms. 

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