Chord Diagram

Chord Diagram History

The history of chord diagrams centers around one individual: Martin Krzywinski, a genomics scientist from Canada.

To make it easier to compare relationships between genetic codes, Krzywinski developed Circos, a data visualization tool.

Circos debuted in 2004 and still exists today. It helps data users display information using the unique circular graphs layout. This layout forms the foundation of the chord diagram.

Essentially, Circos is a data visualization tool specifically built to create chord diagrams.

In 2007, New York Times ran an article, Close-Ups of the Genome, Species by Species by Species.” Within this article was a chord diagram created by Krzywinski. It’s the first time that chord diagrams hit the ‘mainstream.’

The introduction of the chord diagram collided with the trend of data visualization as an art form.

This movement, primarily kick-started by David McCandless’ 2010 TED Talk, created an interdisciplinary study between art and data science.

The chord diagram fits perfectly in this space because it is both aesthetic and informative. The colored connectors between each node create interesting, visual patterns that are pleasing to view.

As a result, many famous and even award-winning chord diagram data visualizations have appeared on the Internet and in major publications.

Today, chord diagrams are valuable tools that fit many purposes. You can map customer flow in a major department store, measure client sentiment in a hospital, measure relationships between seemingly-unconnected categories and more.

Every chord diagram is as eye-catching as it is an effective analysis tool.

Chord Diagram Definition

A chord chart is sometimes known as a radial network diagram. It is a pictorial representation of data highlighting relationships and flow between categories or other components.

Chord diagrams use a circular layout capable of including a high volume of information in a relatively compact visualization. This means there is not a vertical axis and horizontal axis, like in bar charts.

“Nodes” represent the various categories or items of your dataset. These nodes appear along the circumference of the circle. You can label nodes by name, color or other identifying means.

Connections between nodes (known as arcs) signify a flow or relationship between two (or more) items in your dataset. The thickness of the connection piece represents the magnitude of the relationship.

So, the thickest arcs are your most significant relationships in the data. Meanwhile, thinner links drawn between nodes represent a minor connection.

Non-ribbon chord diagrams are a common variation. It offers a simplified chart where only nodes and links appear. This allows you to focus solely on the connections within the data, instead of tertiary details.

Color is a valuable addition, no matter what type of chord chart data visualization you choose. Colors can separate nodes into their respective categories or bins, express different types of relationships (such as positive versus negative sentiments) and more.

It’s worth mentioning that chord diagram data visualizations are different from chord charts used in guitar music. The latter depicts the fretboard and where you need to place your fingers to play certain musical chords.

Chord Diagram Examples

Since chord diagrams are a favorite chart type among data visualization artists, there are many powerful examples of chord diagrams. These examples help clarify the different uses of chord visualization and how to effectively use these charts with your own data.

Let’s take a look at these chord chart examples.

Chord diagram example 1: Martin Krzywinski’s Close-Ups of the Genome, Species by Species by Species offers a great example of how to use a chord diagram.

The first chord diagram published shows the connections between the human genome and other entities in the animal kingdom, mainly chickens, mice, rhesus monkeys and chimps.

The purpose of the visual was to demonstrate the ways that the human genome contains similarities to other species. Krzywinski drew connections between the parts of the human genome found in these other animals.

Chord diagram example 2: Jen Lowe created an awarding-winning chord chart called “A Thousand Fibers Connect Us: Wikipedia’s Global Reach.

The objective of the visualization was to map how users across the world use and interact with content on Wikipedia. Specifically, it showed readership by language across different countries.

It also allowed viewers to compare Wikipedia usage in countries with low and high Internet access.

Chord diagram example 3: A large department store visualizes its customer reviews to improve the shopping experience.

They use a chord diagram to find common threads between subjects of complaint or praise and the specific departments responsible. For instance, if people commonly complain that the grocery department is unclean, you’ll see a defined link between these two nodes.

With this visualization, the store can quickly identify the strengths and weaknesses of each department, making it easy to create store-wide improvements.

What’s the Purpose of a Chord Chart?

Through the above chord diagram examples, you start to see some of the uses of chord diagrams.

To recap, chord diagrams express relationships between items in a dataset and the strength or magnitude of these connections compared to other links in the data.

The first “purpose” for the chord diagram was in Martin Krzywinski’s work in genomic studies. We highlighted this in the first example from the above section.

However, there are several situations where mapping interconnections in a dataset is valuable. You can see the flow of finances through different strategies or investments, measure the pathways of website visitors, and conduct a comparison analysis of various correlations and more.

Sentiment analysis of survey data is another common purpose of chord diagrams. This type of data is challenging to work with because responses may be text-based, which is unstructured.

You can use chord diagrams to look for common threads in responses. A more prominent link appears when survey participants frequently mention the same items together. You can investigate these connections to understand the aspects that audiences care most about or often mention together.

Essentially, the chord visualization is practical anytime drawing connections or visualizing flow in your data is valuable to your analysis goals.

Have a Goal for Your Chord Diagram Analysis

Whenever you create a chord diagram (or any chart for that matter), it’s crucial to have a goal or objective in mind.

This goal needs to answer a critical question: why are you creating this chart? What are you hoping to learn or discover from your chord diagram?

There are several reasons why setting this goal is vital.

First, it ensures that your charts provide tangible value to your team. The purpose behind your visualizations should support your primary business objectives. If the direction of your business is to increase clients, then your charts should explore relationships that deter or attract new customers.

The second reason to declare a goal for your chart is it ensures that you collect the correct data for your chart. You don’t want to visualize the wrong information or allow less-relevant data to distract from the primary objective of the graph.

When it’s time to actually analyze your chord chart, this objective will ensure that the analysis itself stays on task.

A chord diagram can reveal many interesting insights, but not all of these findings will be relevant to your goal.

To save time and energy, you should keep your chart’s goal in mind during the analysis process. It will ensure that you extract the proper insights leading to actions valuable to your team’s priorities.

Structure Your Data for Chord Diagram Visualization

After you set a goal for your chart, the next step is to collect and arrange your data.

The unique nature of the chord chart requires special care when arranging your dataset. There are a few header sections you should consider including in your chart.

Primary topic: Your primary topics are the nodes at the start of your links. For instance, if your chart showed the migration of people to the US, the primary topic would be data for each individual’s country of origin.

Again, most chord diagrams express the flow of data from one area to another. The primary topic is the initial starting point of that flow.

Subtopic: The subtopics are the endpoints of links. It’s where the flow of data travels to, instead of from.

That said, you may have multiple levels of subtopics, meaning links travel through more than two sets of nodes. In this case, you may need more than one level of subtopics.

Chord color: Colors are some of the best details to enhance your visual data storytelling. They are helpful in chord charts when trying to distinguish different nodes or types of links.

For example, if your chord diagram shows positive and negative sentiments, it’s smart to use green and red link colors to separate each one.

Primary topic value: This is where you begin entering numerical data. This category corresponds to the value or magnitude of your primary topics.

Subtopic value: Same as above but you’ll use the values that correspond to each subtopic item.

Here’s an example to show how this data might look in a table. In this sample, Ms. Apple’s 5th-grade class measured the height of each student at the beginning and end of the year.

The primary topic is the starting heights of individuals, while the subtopic is their end-of-year measurement. She may choose to use blue and pink link colors to distinguish boys from girls.

Since her start and end topics are themselves values, she doesn’t need to enter any more data. However, she may use the difference between the two measurements to determine the thickness of each link. This allows the class to identify significant growth spurts.

How to Create a Chord Diagram in Excel

Chord diagrams are not available as one of the standard Excel chart types. As a relatively new visualization type, it’s unlikely that the program will add it any time soon. Excel tends to be behind on new charts and has a limited selection available to users.

Thus, to make a chord diagram in Excel, you need an external tool, like ChartExpo. By using ChartExpo, you can quickly create beautiful chord diagrams in three easy steps.

Before getting started, you need to download the ChartExpo Excel add-in for data analysis. You can find it in the Microsoft App Source.

After downloading, you’ll have to restart Excel. The next time you open the program, the tool (and Excel chord diagrams) will be available.

The top-level menu of ChartExpo shows you the complete chart gallery. You can scroll through every Excel chart to find the chord diagram or filter the list by name using the search bar.

Once you select the chord chart, you have to input your data. You can simply click and drag to highlight the parts of your dataset you want to visualize. Otherwise, you can input the cell IDs and ranges manually.

With the chart type and data selected, all that’s left to do is to hit “Create Chart.” Your Excel chord diagram will appear next to your data.

You can save the Excel chord chart as an image or PDF file to use in emails, reports, presentations, etc. You may want to edit minor details of the chart as well, such as changing node colors or editing labels.

Create Chord Diagrams Online in Google Sheets

If you use Google Sheets instead of Excel, you’ll run into the same availability issues with chord diagrams. Google Sheets does not include this as one of the stock charting options.

Luckily, there is also a ChartExpo Google Sheets add-on. To download it, click on “Extensions” from the top toolbar in Google Sheets and hover over “Add-ons.” This shows a right dropdown menu with the option to “Get add-ons.”

Clicking this option will open the Google Workspace Marketplace. From there, you can search and download the ChartExpo Google Sheets add-on.

Once downloaded, this data visualization tool will appear under the “Add-ons” menu. Again, opening it will reveal the complete library of different chart types available with ChartExpo.

You can use the search bar to find the Google Sheets chord diagram quickly. However, you may want to scroll through the entire ChartExpo data visualization gallery to see the chart and graph types available.

In the future, you’ll want to make a chart in Google Sheets using another visualization aside from the chord diagram. So, it is a good idea to familiarize yourself with all of the options ChartExpo has to offer.

Past selecting your chart type, all that’s left is to grab your data by inputting which parts of your spreadsheet you want to use.

Click the “Create Chart” button and your new chord diagram appears instantly. Again, you can make minor edits and save the visualization as a chart image to export and use elsewhere.

Identifying the Parts of a Chord Diagram

In defining what is a chord diagram, we discussed several key terms, like nodes and links. Understanding what these pieces look like is vital to understanding your visualizations.

Nodes are the first thing to take note of. These are the items along the circumference of the circular diagram. They reflect your primary and subcategory topics.

If your chord chart shows links from one category to another, you want to arrange your nodes so each category is clearly distinguishable from the next. You should be able to easily separate each group and individual item from one another.

Think of the cord diagram layout as the face of the clock. You may have half your nodes at the bottom hemisphere (3 o’clock to 9 o’clock), with links to your subcategory at the top of the hemisphere (9 o’clock to 3).

If you have more than one subcategory, you’ll divide the clock face into even more parts. It’s also worth mentioning that groups of nodes will not always be equal. You may have 65% of the circular layout for one group and only 35% for the remaining nodes.

The origin and destination of links help express relationships between separate categories or topics.

Since some relationships are stronger than others, you need to evaluate the thickness of individual links. These thicker relationships are more substantial. We’ll focus more on this in the next section.

You’ll also want to pay attention to the labels for each node. This will help you identify what you’re actually looking at and which components correlate with one another.

Look for the Strongest Relationships and Chords

One of the first steps in analyzing a chord diagram is identifying the most prominent links in your data. Again, these are the most definite relationships, meaning either there is a strong correlation between the two nodes or a high magnitude of shared similarities.

In any visual analysis, you want to start with these significant parts because they often reflect the highest level of value. Thus, they are the most important parts.

For example, if you used a chord chart to measure common threads in survey data, your most significant links would demonstrate topics most often mentioned together.

By analyzing these strong connections in reviews, you discover several valuable insights:

• Audience interests and the topics cited most frequently together.
• The factors the audience likes most about your business (i.e., the things they talk about the most with positive sentiment).
• The factors the audiences liked least about your business (i.e., the areas that need immediate attention and improvement).

Thanks to the strong links in this chord diagram, you can capitalize on the strengths of your organization and repair the most problematic areas.

This doesn’t mean you should ignore the links that aren’t as prominent or defined. These may still represent crucial connections in your data.

Focusing on the most substantial relationships and chords in the diagram is about prioritizing the most important relationships.

If you’ve already investigated and analyzed these connections, you want to move to the remaining links.

Are there any Anomalies or Unexpected Results?

When charting your data with a chord diagram, there will be some connections that you’ve discovered in the past and are already known.

Alternatively, you may be performing the same analysis for a second time, meaning you already have an expectation of how your chart should look.

In these cases, pay attention to the parts of your chord diagram that you didn’t expect. Are there relationships that didn’t exist before or are new to your understanding?

Digging deeper into these connections will expand your knowledge of the data and produce a higher level of actionable intelligence. In other words, you want to investigate things you didn’t already know or expect.

Sometimes, these unexpected results appear as outliers or anomalies in the data. An anomaly occurs when data falls well outside the normal or expected range of results.

Let’s say you charted the payroll of every professional baseball team and their year-end record (wins vs losses). The expectation and proven correlation is teams with high payrolls win the most games.

If you notice a team has a very meager payroll but a very successful and competitive record, it’s an unexpected anomaly worth further investigation. This type of link will appear in your chord diagram because of how you arrange your nodes in a logical order.

How to Better Make Chord Diagrams

As easy as it is to use ChartExpo to make chord diagrams in just a couple of minutes, there are some mistakes you need to avoid.

The most significant issue occurs when your chord chart has too many links. It can become overwhelming to analyze because there are simply too many connections crisscrossing the center of the diagram.

If the readability of your chord diagram starts to become a problem, you may decide to remove weak or irrelevant connections from the visualization.

These links are likely too insignificant to matter and may distract from the most critical ones by contributing to the over-cluttering.

This is especially practical if you’re presenting the chord diagram to others. You want the audience to focus on the links that matter most.

Remember, chord diagrams are a less popular chart type. Even though they are effective tools for data analysis, many audiences may be unfamiliar with how to read and understand the information.

Removing excess nodes and links is a wise choice to help your audiences decipher the chart with greater ease. You can always present the information you omitted in future reports — just focus on what matters most for now.

Colors are another way to make chord charts easier to understand. You can use colors to separate different groups of nodes or types of links. In sentiment analysis, green and red links can easily distinguish positive and negative relationships.

If you utilize colors strategically, you can make your chord charts far more effective.

Analyze Sentiments and Intangible Relationships with Ease

Relationships are hard to manage, whether in life or in your data. These may be connections between data categories or sentiments and feelings shared by your target audience.

The problem is that feelings and connections are often intangible, meaning you can’t easily measure them with raw numbers.

Chord diagrams and other visualizations aim to quantify these intangibles using visual representations. The thickness of a link in a chord chart shows the magnitude of a relationship in a way that numbers can’t.

Relationships are particularly challenging to measure and understand when you have extremely large datasets. It’s hard to dig through the raw numbers and extract accurate correlations.

Again, chord diagrams come to the rescue. Visualizing these complex connections allows you to quickly and easily understand what’s going on in your data. It’s about seeing the bigger picture behind all the numbers and figures.

You can map every interconnection in your dataset using one chart, while also highlighting the most critical relationships — the ones that require the most attention.

Chord diagrams bring these critical connections straight to the surface, even when your dataset is massive or overly complex.

The accessibility of these insights through the lens of a chord chart allows you to respond faster to changes. This agility becomes a significant competitive advantage because you can react faster than the competition.

Visualize Flow and Relationships in Your Data

Aside from mapping out interconnections and relationships, chord diagrams are also useful in showing the flow of data through a high volume of nodes.

This approach to analysis is helpful in many applications. For instance, you can see how a finite resource (like money) flows through different categories, strategies, stages, etc.

This analysis allows you to detect and fix leaks and other issues in your flow. By repairing these problems, you streamline your data flow and achieve even greater results.

Flow is something that often changes constantly in data. If you aren’t carefully monitoring it, you may miss these damaging leaks or ignore potential opportunities to improve this stream.

Chord diagrams prevent you from missing these occurrences by providing a visualization you can routinely use and check the status and movement of your data.

Thanks to the agility of ChartExpo’s visualization tool, it’s fast and easy to update your chord diagrams with the latest figures.

Chord diagrams with ChartExpo enable you to proactively stay on top of your flow, fixing problems and seizing opportunities as they appear.

With other methods and chord diagram creators, it’s easy to find yourself struggling to keep up with the constant changes in your data.

This struggle creates a vicious cycle of playing “catch-up” with important changes to your data. You can only react to problems or opportunities that have already occurred.

What you want is the ability to anticipate these events and respond as or before they happen.

Measure Growth and Decline Simultaneously

Chord diagrams don’t discriminate between positive or negative insights. It shows connections in your data, whether good or bad.

Growth and decline are both inevitable. No matter how hard you work or strive to succeed, you’ll still face downturns at times.

Visualizing data with a chord chart shows both simultaneously, giving you complete visibility of the many ups and downs in your data.

This is a massive advantage. Tracking and monitoring your growth is vital. You need to know when progress is moving in the correct direction and at an acceptable rate.

While it feels good to pat yourself on the back at how quickly your organization is growing, you don’t want to ignore times when progress is in decline.

You can argue that it’s even more crucial to know when progress declines. Loss of performance or progress could be due to significant issues that require immediate attention. Ignoring these problems allows them to grow into more severe crises.

Ultimately, improvement to your results comes from two actions:

• Recognizing and acting on new opportunities that will directly influence performance to increase.
• Detecting and fixing problems that will create a loss of performance if left alone.

Chord diagrams enable you to discover insights relating to these types of actions. You’ll prevent losses in performance while also building growth through positive opportunities.

Understand What’s Working and What Isn’t

Part of actively tracking your progress is identifying the direct actions or factors responsible for these ups and downs.

Again, optimizing your results for success comes from capitalizing on emerging opportunities and stopping potential issues from hurting your results.

In today’s data-driven world, this success requires you to continuously recognize these risks and opportunities. You also need the agility to make immediate decisions based on the latest data.

Investigating links between nodes will help you discover tangible activities to respond to the intangible relationships and sentiments.

The more you explore your chord diagram visualizations, the more you’ll learn about what’s working and what isn’t across your many strategies and offerings.

You can quickly translate these insights into actions that directly improve performance.

If you pay attention to the most significant links in your data, you can prioritize your optimization efforts. This strategy ensures that you mitigate the issues with the greatest potential harm or capitalize on the opportunities with the highest possible value.

Thus, chord diagrams don’t just show you what needs attention. They also give you insight into the most effective order of acting on these items.

This solves one of the common questions that face decision-makers. “What do I do next?” Thanks to chord diagram insights, you always know what that next step is.

By always having that next step ready and waiting, you can continuously grow and improve without pause.

A 100% Code-free Chord Diagram Maker

The reason that we visualize data is to make it easier to understand. In this case, easier also means quicker.

Data moves very quickly and taking too long to analyze and understand it can become damaging. So, having an effective and efficient chart maker is critical to success with your data.

Sadly, many of the so-called best data visualization tools lack efficiency for one simple reason; they require coding.

This is because of how programs like Excel or Google Sheets work. These tools utilize JavaScript programming language to enable users to create charts and visualizations that don’t already exist in these applications.

Most data visualization software offers prewritten scripts that you can edit with your own data and settings. While using these chart template scripts isn’t that difficult, it takes time and some knowledge of coding.

If you don’t have this expertise, you may need to follow guides and tutorials to properly set your data into the right parts of the code.

These scripts are a necessity, but not for you. It is better to spend your time analyzing the charts, finding valuable insights and making data-driven decisions.

That’s why ChartExpo created a more automated system. You simply tell the tool what chart type you want to use and select your data.

Then, the ChartExpo graph maker automatically populates a JavaScript template. You never even have to see a piece of code because it all happens in the background.

Thanks to this automation, ChartExpo saves you ample time and eliminates potential headaches when dealing with these scripts by hand.

Create Professional Charts in 3 Easy Steps

ChartExpo’s efficiency doesn’t stop at removing the need for tedious coding (and troubleshooting those scripts when problems occur).

The team behind this chart creator designed it specifically to be as straightforward and simple as possible. Fixing a complex problem, like charting, with a simple approach, produces substantial rewards.

Not only do you make chord diagrams and other visualizations in less time, but you also remove the skill gap required by script-dependent tools.

This skill gap occurs because only a handful of people have the data or coding background to make charts using code-dependent tools.

It creates a traffic jam in your analysis where all visualization projects have to pass through these select people. Sometimes, it’s a single person responsible for coding all charts for a large team.

ChartExpo’s simple chart creator is accessible by all team members, regardless of their background in JavaScript or data science. This empowers your entire team to participate in the analysis process and interact with data.

To recap, the ChartExpo process is 3 easy steps:

• Choose your chart time from the expansive list of options.
• Select the data you want to chart from your table
• Click the “Create Chart” button to finalize your chart.

You can make charts in as few as 3 clicks with ChartExpo. It doesn’t get easier than that to make professional charts.

Plenty of Different Chart Types beyond Chord Diagrams

The chord diagram is a powerful and useful visualization option. However, it isn’t always the best chart type for your data. There are hundreds of other chart and graph types available.

Successful analysis relies a lot on your ability to align the data with the proper chart type. When you make the correct match, valuable insights become immediately apparent in your visualizations.

ChartExpo offers a massive chart gallery with all types of graphs and visualizations to choose from. With so many options, you’ll always have the perfect chart type for your data.

Plus, you can take the same data and visualize it using different chart types. If you aren’t sure what visualization to use, having lots of options is a very powerful advantage.

Often, there is not just one visualization that works for your data. There may be many. Looking at your data through the lens of different chart types reveals a broader spectrum of insights.

One chart may show you one part of the picture, but you need others to gain a complete view.

ChartExpo’s team routinely adds new visualizations to their offerings. As the needs of data users change, ChartExpo is always there to meet them.

You’d be hard-pressed to find data visualization software with more chart types than ChartExpo. The graph maker and analysis tool includes charts for financial data, digital marketing metrics, comparative analysis and so much more.

The only problem you’ll run into is identifying the different types of graphs and when to use them!

Build a Stronger Data Culture

Businesses across all industries and spaces are pushing to become data-driven. This means making decisions and developing strategies with the help of data.

Before the big data boom of the Digital Age, decision-makers relied primarily on gut feelings, past experiences and assumptions. Sometimes, these opinion-driven decisions pay off, but they often don’t.

Data-driven choices are far more accurate because there is no guesswork involved. If your data is from a trusted source and your analysis process doesn’t contain mistakes, you can trust data insights with an extremely high level of confidence.

This confidence transfers to the decisions you make. You don’t have to worry about whether each decision is the correct move or not because you have data evidence telling you it is the proper action to make.

So, becoming data-driven has its advantages, but the process of reaching this point isn’t always easy. ChartExpo helps by putting data and charts into the hands of more individuals.

It creates an environment where your entire organization is using data and charts. This includes collaborating on analysis projects, brainstorming how to act on insights and more.

Companies with a strong data culture consistently make correct decisions, thereby producing steady growth.

When issues arise, data-driven companies recognize the problem, find the cause and resolve it. ChartExpo helps teams build this culture and utilize data with a high level of effectiveness.