You’ve undoubtedly seen many bar graphs in your lifetime. They’re common in magazines, newspapers, academic material, websites, and just about any other medium where someone wants to visualize meaning between two data sets. Incidentally, you probably understood what the graph’s data represented, which is what makes it such a useful visualization tool.

In this guide, we’ll take a deep dive into bar graphs, including all the various types and how they work. We’ll also cover some best practices for creating your own. But first, let’s start with a basic definition.

**What is a bar graph?**

Sometimes referred to as a bar chart or column chart, a bar graph is a visual tool used to compare frequencies, counts, totals, or data averages across different categories. The data in bar graphs can be anything from the number of students enrolled in a class to business earnings across quarters to yearly rainfall.

Put simply, bar graphs are graphical charts that compare discrete values between two categories of data.In most bar graphs, you list one data category along the left side of the graph, running from bottom to top, while you list the other category along the bottom, from left to right. You place each bar on one axis, corresponding to a specific data point, which stretches to correspond with the matching data point on the other axis. Bar graphs are extremely useful for understanding the differences between two data sets at a glance.

The two axes in bar graphs are referred to as the y-axis, where data points are plotted vertically, and the x-axis, where data is plotted horizontally. This is important to keep in mind, as the names of the different bar graphs can be a little confusing with respect to the axes. There’s often some confusion between bar graphs and histograms. While they look very similar, they’re actually quite different.

**The differences between a bar graph and a histogram**

A histogram is another visual chart that uses bars to represent information on two axes. One key difference is that a histogram is a statistical graph that displays continuous data and its frequencies. The other key difference is that histograms represent non-discrete data points. In short, the histogram data is non-discrete and visualizes the frequency of occurrences.

The easiest way to distinguish a bar graph from a histogram is to check whether you could move the bars around without changing the meaning of the data. If you can, you’re looking at a bar graph. With an understanding of the fundamentals of bar graphs, let’s look at the different types of bar graphs and what you use them for.

**The different types of bar graphs**

Basic bar graphs are straightforward. But there are a few different types to choose from, and some are better than others, depending on the type of data you’re visualizing.

**Vertical and horizontal bar graphs**

The most common bar graphs are called vertical bar graphs. They’re great for comparing data categories such as age groups or profits. On a vertical bar graph, each bar is placed on the x-axis corresponding to a parameter and grows upward to match the corresponding parameter on the y-axis. If you want to visualize data spread across a timeline, a vertical bar graph is one of the best ways to do so.

Where vertical bar graphs get troublesome is if you’re working with text-heavy data parameters. Positioning the bars along the x-axis doesn’t leave much room for labeling — this is where a horizontal bar graph comes in handy. Horizontal bar graphs are simply vertical bar graphs rotated to the right. By flipping the axes and having the bars grow from left to right, you leave more room for labels on the left side of the chart.

As we look at the other kinds of bar graphs, keep in mind that you can represent each one in a vertical or horizontal orientation. It really comes down to which one is more visually appealing and easier for the viewer to understand.

**Grouped bar graphs**

Bar graphs compare parameters from two data sets. But in some cases, you may want to add other parameters from one of those two data sets, which is where grouped bar graphs come in handy.

For example, if you have a vertical bar graph showing your company’s profits over the last four quarters, each bar would represent a single quarter matched to its value on the left. But if you wanted to visualize how two different products contribute to the overall profit, you could group two bars for each quarter to show how profits are doing across each quarter and for each product.

In theory, you can break data sets down into multiple categories and add several grouped bars, but doing so makes the graph harder to understand.

**Stacked bar graphs**

Following a similar formula, stacked bar graphs let you split a single column into multiple parameters. In a stacked bar graph, a single column is distinguished with different colors and corresponding labels to pull multiple parameters from a single data set. They’re good for big picture views of data since a large stacked bar chart can include quite a bit of information.

Following the previous example of quarterly profits by product, if the company in question has several products, a grouped bar graph would be the perfect tool to reach for to see how each product contributes overall. With a deep understanding of bar graphs, the next step is knowing when to use them.

**When should you use a bar graph?**

With the right tools and data, bar graphs are easy to create and powerful visualization tools to help you convey meaningful, measurable information, whether it’s to a teacher, a colleague, or a boss. If you want a powerful way to visualize the differences between a handful of parameters from two data sets, a bar graph is one of the best ways to do so.

Here are some opportunities where a bar graph would serve you well:

**Correlation:**If you want to visualize how two sets of seemingly disparate data correlate, you can check and present your findings with a bar graph.**Understanding large data sets:**If you’re working with a large amount of data in a tabular form, then visualizing the data can help clarify the bigger picture.**Sortable comparisons:**If you’re working with two sets of data where you need to rank parameters, the ability to rearrange and sort the columns and data points on bar graphs is visually powerful.

**Best practices for creating great bar graphs**

Creating bar graphs is straightforward, but to be sure, the idea is to communicate a complex idea in a way that’s simple to understand. Bar graphs should allow viewers to infer insights without too much mental overhead. These best practices will help get the job done:

**Column widths:**Make sure your columns are wider than the spacing between them.**Styling:**Use colors to make distinctions and reinforce the idea of the graph rather than for aesthetic purposes.**Keep bars simple:**Many tools let you add quirky design elements or images to your bar graph’s columns. It’s best to keep things simple to convey the overall message rather than distract from it.**Choose the right bar graph:**If you find that your information is crowded or hard to visualize, a different orientation or graph type is probably necessary.