How to choose types of charts to display data effectively

By Indeed Editorial Team

Published 30 June 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

With the development of spreadsheet software, there has been an expansion in the different types of charts that people can use to help analyse data. As you continue in your future career, you might find that different charts have different uses. It's key to learn what types of charts are out there so you can best pick the one most suited to your needs. In this article, we provide simple steps to ensure that you can choose a chart quickly and effectively.

Related: A guide to the different types of charts and graphs

How to choose types of charts

Learning how to choose types of charts for your presentations is a key skill to learn. Doing so means that you can demonstrate your findings far more clearly. That's because data visualisation can materially improve a person's ability to understand raw data and draw conclusions from it. There are a number of different ways to decide which chart is right for you:

1. Identify what you're trying to highlight

Having collated your data, you may have a feel for what the overall data results tell you. Plus, when conducting your data collation, you likely had a hypothesis you wanted to prove using the data you achieved. It could have been that you were trying to emphasise a trend or show how something has changed over time. It could have been that you wanted to see if there was a link between two types of data. Whatever it is, remember to bear in mind your final end goal when trying to pick the right type of chart for you.

2. Know to whom you're showing your results

Know who that audience you're presenting your data to and what type of chart they may read better more easily. To do so, try to remember their level of knowledge when evaluating which chart to use. It could be that you're going to be showing these charts to highly intellectual scientists. If that's the case, they're going to be capable of reading a complex chart. If you're showing it to individuals who do not necessarily have an analytical mind, it may be better to use a more simplified graph.

Related: How to take your presentation skills to the next level

3. Consider how large your datasets are

The size of the dataset you use can often help determine which graph you pick. The larger the dataset, the more difficult it is to include every single data point on a chart. If you include every data point, the chart may become too busy and totally illegible as a result. Some charts, by their very nature, simplify the data by collecting all data points into one range and making them far more readable. Remember that charts are meant to present your findings clearly without making the reader work for the conclusion.

4. Identify what type of data you're working with

Data varies in type. Some types, like categories, for example, work better with charts like a bar chart. Other data can have a more continuous element so using line charts may be better. There may be many different charts, but there's usually only one or two types that can work for particular types of data. Again, remember that a resulting chart is meant to make your dataset easier to glean conclusions from. If the chart does not seem to make any sense, it may be that it does not work well with the data type you have.

5. Know how your variables change according to one another

Finally, datasets need at least two variables. It's important to consider how those elements relate or interact with one another. For example, take the common variable of time. You may want to show how one data variable changes due to time on a chart. Some charts can lend themselves better for displaying data in this way than others. If you identify the best chart possible for showing the relationship between your variables, you can help emphasise the point that you're trying to make.

Related: How to become a data scientist in 4 steps

Types of charts and their uses

Below are some of the most popular types of charts and their uses. The simplest ones to pull together are often the simplest to read for the end-user:

Bar chart

Bar charts are great when you have big sets of categorical data. They can be particularly useful if you want to show how those categories change over time. Another helpful element is that bar charts can easily show both positive and negative values which can be a key idea that not all charts are capable of displaying. You might limit the number of categories to keep bar charts as useful as possible. Too many and the average human mind can not take in all the information easily.

Pie chart

Pie charts are great for creating an impact quickly. That's because individuals usually understand the concept of a 'whole' easily. They're therefore perfect for use when you're trying to show proportions or percentages. They're most useful therefore when there are only a handful of categories that make up the dataset to 100. If there are too many categories, the sections can be too small to be meaningful. It's best to steer clear of pie charts, therefore, if you have a big dataset.

Line chart

Line charts are best used when you have continuous data. Time is the most obvious example of continuous data but that does not limit line charts to time value usage only. You can also use line charts to display different performance metrics and doing so can provide the reader with a quick way to compare data that would otherwise have been difficult to grasp. You can therefore easily use line charts when working with large and long datasets. It's best to label axes clearly which can help the reader derive conclusions more quickly.

Scatter graph

A scatter graph can be a complicated chart to use to show your results. But they do have their time and place. Within financial data or in scientific experiments, for example, data analysis using a scatter graph can help show the correlation between data or when common results take place. So, while results on their own are just one point on a graph, when taken as a whole with many other points, an individual can help strengthen their story through a scatter graph. Scatter graphs are most useful when the data points are not necessarily put in a particular order.

Area chart

Area charts are, in a way, a mix of a pie chart or bar chart with a line chart. They show how proportions can change over time or another continuous factor. They can be really helpful to readers who can quickly see how proportions vary so that they may start to think why - if the chart does not already tell them. These charts are therefore great to use with big data sets and can make complex data findings far easier to glean results from.

Combinations

Of course, many of these charts sadly may not suffice for some data sets. As a result, it can be better to try a combination of these charts to help illustrate a person's point better. Usually, it's best to limit the type of chart to just two. Any more and the chart area can be too cluttered for the reader to derive any material value from.

Tips for choosing types of chart

Sometimes, choosing a chart out of the many that are available is an overwhelming prospect. Use the tips below along with the suggested methods so that picking a graph or chart can become a lot easier:

  • Pie charts vs. bar charts: You might sometimes use bar charts and pie charts interchangeably. When you're unsure as to which to use and when, use a pie chart, particularly when you have five categories or less in your data.

  • Time value data: Time value data lends itself very well to line graphs. They're easy to read and users quickly glean relevant information from a line graph that explains time-based data sets.

  • Do not overcomplicate the page: it can be tempting when you have collated a large amount of data to use it all, but this can have negative implications for your work. Instead, simplifying it can make your final message far more powerful.

  • Remember the basics: One way that you can ensure your charts are legible is to make sure you include all the basics. As a result, label your axes, use scales and title your charts so the reader can make the most sense out of them immediately.

  • Area charts and bubble charts: Area charts and bubble charts are ideal for when you're comparing volumes within a dataset. Readers can more easily compare and derive information from the visual way of displaying volume data in this way.


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