The Bar Line Chart

What is a Bar Line Chart?

A bar line chart (also known as a combination chart) is a data visualization tool that’s exactly what it sounds like – a combination of a bar chart and a line chart. A bar chart is best used to compare categorical data where the height represents a quantity of that category, and a line chart is best used to analyze continuous data, usually over a period of time. Combining the two, the bar line chart is useful for looking at a relationship between at least two variables that may have different scales of measurement.

Just like a bar chart and line chart, the structure of the bar line chart consists of a horizontal x-axis and a vertical y-axis, typically intersecting at the bottom of the y-axis and the left end of the x-axis. The slight difference is that bar line charts typically have a second vertical y-axis that connects with the right end of the x-axis, parallel to the first y-axis. This allows for the bars and lines to have different scales which is an important feature of this chart type.

When to Use a Bar Line Chart

With the possibility to have different measure scales, one on the left hand y-axis and one on the right hand y-axis, the bar line chart is ideal when you want to visualize variables that are normally hard to combine because of the significant difference in value ranges. It can also be useful when comparing variables of the same value range because the relationship between the variables is clear. Overall, use a bar line chart to validate the relationship between two or more variables that have different magnitudes and scales of measurement but are related in a meaningful way.

Let’s take a look at an example where the bar line chart is a great choice of visualization:

Chart made using Chartio

In this example, we’re interested in looking at a business’s customer payment trend over time. The bars of the chart represent the total amount paid by customers per month, and the line represents the total count, or number, of payments made. The x-axis represents the year 2018 by month, the left hand y-axis is the scale for the amount of payment, and the right hand y-axis is the scale for the count of payment.

From the bar line chart, it’s easy to see that both the business’s count and total amount of payments increased from January to August, but then dropped in September. Since the total amount of payments and the total count of payments follow the same trend, we can assume the two are related.  

When NOT to Use a Bar Line Chart

Determining when to use a bar line chart is usually simple, but there are some areas where a bar line chart is not the ideal visualization choice. First, the bar line chart only supports one dimension, and therefore cannot be used when you need to include two or more dimensions in the visualization.

Second, having a bar line chart with too many bars and lines can be overwhelming and likely make comparisons difficult. With an excessive number of bars, the x axis becomes overcrowded and the width of the bars decrease, making the line too compressed to gain information from. It’s hard to pinpoint exactly how many bars is too many, so use your best judgement. With an excessive number of lines, it can be difficult to tell the shape of each line and key points, especially if the lines overlap. If your chart is overcrowded, it would be useful to try a different chart type or make individual charts for each comparison.

Let’s take a look at an example where the bar line chart is NOT a great choice of visualization:

Chart made using Chartio

This example is very similar to the previous one– we’re still interested in looking at a business’s customer payment trend over time. This time, the bars of the chart represent the total amount paid by customers per day instead of month, and the line represents the total count, or number, of payments made. The x-axis represents the year 2018 by day from January to October, the left hand y-axis is the scale for the amount of payment, and the right hand y-axis is the scale for the count of payment.

So why is a bar line chart a poor choice of visualization for this data? Well, it’s obvious that the day-to-day payment trend is hard to detect due to the closeness and sporadic placement of data points across the x-axis; the chart is simply too overcrowded by the number of bars.

From this bar line chart, we can see the overall trend of the count of payments has increased from January to October, but it’s impossible to see the individual increases and decreases between each day and detect the important values in this chart. Because the line is so compressed and it’s hard to distinguish between the individual bars, it’s difficult to see if the two follow the same trend so we shouldn’t make assumptions about the relationship between the two variables.

Comparison of Comparison Chart Types

Simply put, the bar line chart is a data visualization that’s used to show comparisons between multiple values. Other types of visualizations that compare multiple values are the bar chart and the line chart. The table below gives the use case and pros and cons of the bar line, bar, and line charts:

Bar Line Chart

Bar Chart

Line Chart

Use

  • Visualize a data set with both a continuous and a categorical metric.
  • Visualize discontinuous (or discrete) data or to show the relationship between a part to a whole.
  • Visualize continuous data, often changes over time

Pros

  • Two axes allow for comparisons with different measurement scales
  • Clear comparison of different categories on a labeled scale
  • Ability to show individual data points and multiple datasets
  • Can easily show trends over time

Cons

  • Can be complex and complicate analysis
  • The order of the bars can impact interpretation
  • Can become cluttered easily
  • Data must have an order to make a structured line

References

About Bryn Burns

Hi! I'm Bryn Burns. I am a current senior at Virginia Tech pursuing degrees in Statistics and Mathematics. Data science and visualization are two things I'm very passionate about, as well as working with numbers and helping people learn. I'm thrilled to share my knowledge here at The Data School!